presentation of antigen phagocytosis

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Home > Books > Phagocytosis - Main Key of Immune System

Macrophages: Phagocytosis, Antigen Presentation, and Activation of Immunity

Submitted: 02 March 2023 Reviewed: 09 March 2023 Published: 26 March 2023

DOI: 10.5772/intechopen.110832

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Macrophages are phagocytes and one of the white blood cells discovered by Ilya I. Mechnikov in 1892. They engulf and digest foreign substances like pathogens and conduct antigen presentation, mature from haematopoietic stem cells in bone marrow, moving into blood vessels and become monocytes, and differentiate into macrophages in the tissue. Macrophages have intracellular granules called lysosome accumulating digestive enzymes. Their life span is several months and proliferates by cell division. There are three roles: First one is phagocytosis. Macrophages incorporate pathogens and work in natural immunity. In inflammation, macrophages aggregate after neutrophils recruitment and engulf pathogens into cellular phagosomes, fused with lysosomes and degrade. Second role is antigen presentation. Macrophages present fragment of digested foreign substances on cell surface MHC class II molecules and release cytokines. Dendritic cells and B cells are also APCs expressing MHC class II. CD4+ T cells recognize antigens presented on macrophages by using TCR. Only well-matched helper T cells via MHC class II-TCR interaction are activated. The third is activation of immunity. Cytokines produced by T cells activate macrophages and differentiate them into inflammatory M1 and wound-healing M2 macrophages.

• macrophages
• phagocytosis
• antigen presentation
• activation of immunity
• tissue regeneration

Author Information

Kazuki santa *.

• Tokyo College of Biotechnology, Tokyo, Japan

*Address all correspondence to: [email protected]

1. Introduction

1.1 development of macrophages.

Macrophages are originated from variety of cells. In the early development, it depends on the tissues; however, macrophages are derived from yolk sac and replaced by the macrophages derived from liver and bone marrow [ 1 ]. Tissue resident macrophages are divided into two types, macrophages derived from circulating monocytes and having other origins including yolk sac, embryonic liver, and embryo near dorsal aorta-derived macrophages. In the adulthood, they are independently kept from their original monocytes. Tissue-specific macrophages differentiate from circulating monocytes by the ability of migration at the time of inflammation. Dendritic cells differentiate from monocytes as well as macrophages. Macrophages have variety of morphologies and phenotypes because they distribute in many organs and tissues. Instead of neutrophils that live only few days, the life span of the macrophages is several months. The diameter of the human macrophage is about 21 μm.

1.2 Differentiation and subtypes

Macrophages differentiate from premature M0 to M1 or M2 phenotypes depending on various factors from the signal transduction molecules, growth factors, transcription factors, and epigenetic or post-transduction changes to cytokines, cell adherence molecules, and metabolites [ 2 ]. Furthermore, macrophages change their activation state in response to microbes and microbial products like LPS. Recently, it is said that the classifications of macrophages are not easy because of the plasticity of the macrophages.

M1 macrophages are the so-called classically activated macrophages, pro-inflammatory macrophages, and killer macrophages. M1 macrophages produce high levels of IL-12 after the stimulation of LPS and IFN-γ. The feature of M1 macrophages is possessing specific pathways which converts arginine into “killer molecules” nitric oxide. M1 macrophage is the phenotype observed in early inflammation phase activated by IFN-γ, TNF, and damage-associated molecular patterns (DAMPS). They show high antigen presenting ability, producing high amounts of NO and reactive oxygen spices (ROS), showing increased expression of IL-12 and IL-23, and decreased IL-10 expression. In addition, M1 macrophages express high levels of MHC class II molecules, CD68, CD80, and Th1 cell-inducing chemokine CXCL9 and CXCL12 [ 3 ].

M2 macrophages are called alternatively activated macrophages and wound healing macrophages divided into M2a, M2b, M2c, and M2d phenotypes. They are a typical phenotype of tissue-resident macrophages and participate in constructive process including wound healing and tissue repair. These macrophages are stimulated by several factors including parasitic and fungal infection, immune complexes, apoptotic cells, macrophage colony stimulation factors (M-CSF), IL-13, TGF-β, and Th2 cytokine IL-4, and cytokines produced by Th2 cells like IL-25 and IL-33. Signal transduction pathways including STAT6, IRF4, PPARδ, and PPARδ are required for the differentiation of M2 macrophages. Generally, M2 macrophages produce low IL-1, IL-6, and TNF-α, whereas producing low IL-12. A typical feature of M2 macrophages is converting arginine to ornithine “repair molecules.” Ornithine is important for wound healing and required for vascular and endothelial regeneration. M2 macrophages are also important for clearance of pathogens, anti-inflammation, metabolism, wound healing, tissue regeneration, immune regulation, and progression of tumours. On the other hand, M2 macrophages induce tissue fibrosis in the lung and liver, and progressively stimulate tumour growth as tumour-related macrophages. M2 phenotypes are characterised by the expression of CD206, CD163, FIZZ1, and Ym1/2. There are four types of M2 macrophages a, b, c, and d. These are different by their cell surface markers, secreting cytokines, and biological function. However, the common feature of these M2 macrophages is the production of IL-10 [ 4 ].

M2a macrophages are activated by IL-4 or IL-13. IL-4 induces the expression of the mannose receptor (CD206). Upregulation of IL-10, TGF-β, CCL17, CCL18, and CCL22 induces cell proliferation, cell repair, and endocytosis of M2a macrophages.

Immune complex, toll-like receptor (TLR) and their ligands, and IL-1β activate M2b macrophages. When activated, these subtypes of macrophages produce both proinflammatory and anti-inflammatory cytokines TNF-α, IL-1β, IL-6, and IL-10. M2b macrophages work on immune response and regulation of inflammation. High IL-10-producing and low IL-12-producing M2b macrophages are the so-called regulatory macrophages (Mreg). Mregs are recently focused on their ability to induce regulatory T cells (Treg) [ 5 ].

M2c macrophages are activated by glucocorticoid, IL-10, TGF-β, and inactivated macrophages. The feature of M2c macrophages is high expression of anti-inflammatory IL-10, TGF-β, CCL16, CCL18, and tyrosine-protein kinase MER (MerTK), which enhance phagocytosis activity.

TLR antagonist, IL-6, and adenosine activate M2d macrophages. Adenosine induces the expression of IL-10 and vascular endothelial growth factor (VEGF) and enhances angiogenesis and tumour progression.

M2 macrophages are important for the stability of blood vessels because they produce VEGF-A and TFG-β. In acute lesion, macrophages change their phenotype from M1 to M2; however, these changes will be lost in chronic lesion. This dysregulation results in insufficient M2 macrophages and induces the deficiency of growth factor. The lack of growth factors and anti-inflammatory cytokines from M2 macrophages and excess production of proinflammatory cytokines from M1 macrophage prevent sufficient repair of wound healing. Normally, depletion of neutrophils by apoptosis after eating debris and pathogens induces the switch of macrophages from M1 to M2, but inflammation is unnecessary at that time. Then, M1 macrophages cannot eat apoptosis-inducing neutrophils, and this phenomenon increases the numbers of macrophages and inflammation because of the dysregulation [ 6 ].

2. Classification of macrophages by the tissue

2.1 adipose tissue macrophages: adipose tissue.

Macrophages exist in body fat and increase in case of obesity.

2.2 Monocytes: bone marrow, blood

The largest white blood cells in the blood. They develop into macrophages and dendritic cells.

2.3 Kupffer cells: liver

Kupffer cells exist in the liver and also known as stellate macrophages. Kupffer cells were named after Karl Wilhelm von Kupffer. They work as the first defence against gut bacteria and endotoxin in the liver.

2.4 Alveolar macrophages: pulmonary alveoli

Macrophages exist in alveoli and bronchus. Alveolar macrophages have high activity to get rid of dusts and microbes in the lung.

2.5 Microglia: central nerve system

A family of glial cells with different origin from other family of cells. Most of glial cells developed from ectoderm; however, alveolar macrophages are developed from mesoderm and haematopoietic stem cells. Microglia have phagocytic activity in the nerve and participate in the repair of neural tissue after the tissue damage.

2.6 Hofbauer cells: placenta

Eosinophilic histocytes found in the placenta, often seen in early pregnancy, named after J. Isfred Isidore Hofbauer. Hofbauer cells are considered as a type of macrophage.

2.7 Intraglomerular mesangial cells: kidney

Intraglomerular mesangial cells exist in basement membrane surrounded by glomerular capillaries. They are considered as a type of fibroblast.

2.8 Osteoclasts: bone

Osteoclasts are the specialist of absorbing or destroying bone in the process of bone regeneration. They are usually polygonal giant cells with 5–20 nuclei, but sometimes mononuclear osteoclast can be found. Bone marrow-derived monocyte progenitors differentiate into osteoclasts. The marker of osteoclasts is tartrate-resistant acid phosphatase. On the other hand, the marker of osteoblast is alkaline phosphatase.

2.9 Langerhans cells: skin

Langerhans cells are named after Paul Langerhans. Usually, they are regarded as dendritic cells other than macrophages.

2.10 Epithelioid cells: granulomas

Activated macrophages similar to epithelial cells. They have a thin eosinophilic cytoplasm with small granules and nucleus less dense than lymphocytes. They are found in granulomatous inflammation and participate in arthritis.

2.11 Red pulp macrophages (sinusoidal lining cells): red pulp in spleen

Macrophages found in red pulp in spleen are necessary for the blood homeostasis by depleting damaged or aged red blood cells with the phagocytosis.

2.12 Intestinal macrophages: intestine

Macrophages specifically evolved in intestinal environment. Intestinal macrophages do not induce inflammation to coexist with intestinal microbiome. They do not excrete proinflammatory cytokines such as IL-1, IL-6, and TNF-α. TGF-β produced by surrounding environment changes these macrophages from proinflammatory phenotype to non-inflammatory phenotype. Intestinal macrophages conduct phagocytosis, but they do not produce cytokines after phagocytosis nor express receptors for LPS, IgA, and IgG.

2.13 Others

Sinus histiocytes: lymph nodes

Tissue macrophages leading to giant cells: connective tissue

Peritoneal macrophages: peritoneal cavity

LysoMac: Peyer’s patch

3. Function of macrophages

3.1 phagocytosis.

Macrophages are one of the three professional phagocytes with other phagocytes including granulocytes (eosinophils, neutrophils, and basophils) and dendritic cells (DC). Phagocytosis is the process that microorganisms entering the host and recognised by phagocytes and incorporated and destroyed. This process starts after the interaction with pathogen-specific receptors (usually pathogen-specific sugar or lipid structures) on phagocytes and the surface molecular on pathogens. Typical phagocyte receptors are dectin-1 and mannose receptor (CD206), and both are the family of members of c-type lectin. Dectin-1 expressed on macrophages and neutrophils connects with glucose polymers on the cell walls of fungus. On the other hand, CD206 expressed on macrophages and DCs connects with variety of ligands on fungus, bacteria, and virus. Generally, macrophages exist in all of tissues and monitor potential pathogens with amoebic motility. Most of macrophages are strategically placed where microbes invade or debris accumulate [ 7 ].

After starting interaction with pathogens, phagocytic plasma membrane in macrophages engulfs pathogens into phagosomes, large membrane-enclosed endocytic vesicles (endosomes). Phagosomes enclose pathogens, merged with lysosomes containing antimicrobial peptides and enzymes, and form phagolysosomes. Toxic peroxides like superoxide radicals in phagolysosomes kill and digest pathogens after acidification and enzymic processes. Macrophages ultimately digest over 100 bacteria through digestive compounds in their lifetime. However, some bacteria have resistant properties to these digestive methods. Mycobacterium tuberculosis survives within the macrophages through inhibiting the fusion to phagosomes. To reproduce themselves, Salmonella enterica serovar Typhi induces phagocytosis to incorporate into macrophages, inhibits lysosomal digestion, and triggers apoptosis of macrophages. Furthermore, leishmaniasis causes Leishmania parasitises in macrophages.

3.2 Activation of natural immunity

Macrophages participate in natural immunity by engulfing and digesting pathogens. They protect hosts from the infections and damages through phagocytosis [ 8 ]. Macrophages are the first defence against pathogens working with neutrophils and are specific phagocytes with long life. After the invasion of pathogens, neutrophils are firstly recruited to the site of infection, die after phagocytosis of pathogens, and generate neutrophil traps (NETs). Then, macrophages are recruited and digest NETs after approximately 48 hours later. Recruited macrophages digest pathogens and dead cells through phagocytosis. Finally, they initiate immune responses through releasing factors like TNF-α to recruit other immune cells such as lymphocytes.

3.3 Adaptive immunity and antigen presentation

Macrophages are the most important antigen-presenting cells (APC) as well as dendritic cells (DC), which have important roles in the initiation of immune responses. Furthermore, they produce strong modification factors and chemical substances, such as enzymes, complement proteins, and IL-1. At the same time, macrophages activate to seek microorganisms and tumour cells through their lymphokine receptors.

Antigen-digested macrophages present pathogen antigens to helper T cells, most of which are protein molecules expressed on the surface of pathogens. Antigen presentation is conducted by MHC class II molecules (MHCII) on the surface of macrophages presenting antigens incorporated. Antibody production attaching to the pathogenic antigens starts from plasma B cells after the antigen presentation by APCs and making macrophages easy to adhere to cell membrane of pathogens the so-called opsonisation.

In lymph nodes, antigen presentation via macrophages through MHCII stimulates Th1 cells to start proliferation. B cells recognise same unprocessed antigen by the cell surface antibodies and then incorporate and process them through endocytosis. MHCII molecules on the surface of B cells present processed antigens. T cells that recognise antigen-MHCII complex with co-stimulatory factor CD40-CD40L help B cells to produce antibodies. Then, macrophages incorporate opsonised pathogens by antibodies and eliminate them from the body. However, regarding phagocytosis, recently dendritic cells are more focused than macrophages.

Macrophages provide another defence pathway against fungus and parasites. After the recognition of specific antigen on the cell surface, activated T cells differentiate into effector cells and produce lymphokines. Produced lymphokines stimulate macrophages to more offensive form.

4. Role of macrophages in tissue regeneration and homeostasis

4.1 wound healing.

Macrophages have significant roles in wound healing. By 2 days after the injury, they replace neutrophils and become the dominant cells in the place where injured. Monocytes are attracted to the wound site by the growth factors released from platelets and other cells and then enter the site from bloodstream through the blood vessel wall. The number of monocytes in the injured sites peaks at 1.5 days. At the site of injury, monocytes mature into macrophages. In addition, spleen contains half the numbers of macrophages as a spare, and they are sent to the wound sites when injured [ 9 ].

The main role of macrophages is conducting phagocytosis to the microbes and injured tissues. In addition, protease released from macrophages induces tissue necrosis. After 3 to 4 days of injury, macrophages secrete variety of factors including cytokines, which proliferate and attract cells involved in wound healing. Under the stimulation of low oxygen environment, macrophages induce and generate accelerating factors of angiogenesis. These factors stimulate cells to promote the growth of epithelial cells, create granulation tissues, and form new extracellular matrix. Then, macrophages direct the next stage of wound healing via the secretion of these factors.

4.2 Muscle regeneration

There are two waves in muscle regeneration by macrophages. The first wave is the increased population of phagocytes after the damage of muscular fibre with development of rhabdomyolysis and muscle membrane inflammation by the use of muscle. This population peaks after 24 hours of recruitment to the muscle damage and rapidly decreases after 48 hours. The second wave is non-phagocytic macrophages distributes near the close region of regenerative fibres. These cells peak at 2 to 4 days, and the numbers of the cells remain increased for few days whilst muscle tissue is reconstituted. The first groups of cells do not have any benefits for muscle repair, but second croups are beneficial. They release soluble factors related to the muscle growth, differentiation, repair, and regeneration [ 10 ].

4.3 Foot regeneration

In salamanders, macrophages participate in not only consume debris but also a typical regeneration of limbs. Depletion of macrophages in salamanders resulted in the failure of limb regeneration [ 11 ].

4.4 Macrophages related with the maintenance of homeostasis

All of tissues have residential macrophages interacting with stromal and functional tissue. These macrophages are unmovable, protecting tissues from inflammatory injuries and provide essential factors to support tissue physiological functions [ 12 ].

4.5 Maintenance of pigments

Melanophages, a tissue-resident macrophages, absorb pigments from organ specific or exogenous out-cellular environment. In contrast to melanocytes, melanophages only accumulate melanin incorporated from lysosome-like phagosomes. This phenomenon occurs by which melanophages conduct phagocytosis of tissues from dead skin macrophages. This occurs because melanophages conduct phagocytosis of tissue from dead skin macrophages.

4.6 Nerve-associated macrophages

Nerve-associated macrophages are macrophages related to neurone. They have elongated morphology and stretch up to 200 μm.

5. Macrophages in disorders

5.1 pathogen hosting macrophages.

Generally, macrophages destroy pathogens by phagocytosis. However, some pathogens live in macrophages by interrupting this phagocytosis processes. This phenomenon hides pathogens from immune system and provides them environment to reproduce themselves. Tuberculosis-inducing mycobacterium and Leishmania species are well known [ 13 ].

5.2 Heart diseases and cardiovascular diseases

Macrophages are main cause in the onset of progressive plaque lesions in atherosclerosis. Residential M2 macrophages incorporate oxidised LDL in the cells and become form cells which clogging blood vessels. In addition, both M1 and M2 macrophages participate in the progression of atherosclerosis. M1 macrophages enhance atherosclerosis through inflammation induction. M2 macrophages eliminate cholesterol, but incorporated oxidised cholesterol induces apoptotic form cells from macrophages [ 14 ].

On the other hand, macrophages are recruited to the place where tissue regeneration is required after acute myocardial infraction, removing apoptotic cells and debris.

5.3 Tissue fibrosis

M2 macrophages induce tissue fibrosis by the production of TGF-β in the damaged lung and liver.

Macrophages participate in HIV infection. In addition to CD4+ T cells, macrophages become the storage of reproductive virus. Gp120 protein on HIV couples with chemokine receptor CCR5 to invade into cells.

Some macrophage subtypes participate in the progression of cancer. Cancer-related macrophages participate in tumour cell growth and invasion, progression of angiogenesis, and suppression of anti-tumour immune cells.

5.6 Obesity

Proinflammatory macrophages in fat tissues participate in obesity-related complications such as insulin resistance and type-2 diabetes.

5.7 Inflammatory bowel disease (IBD)

Macrophages participate in inflammatory bowel diseases (IBD) including Crohn’s disease (CD) and ulcerative colitis (UC). In healthy intestine, macrophages suppress the inflammation; however, in the patients with IBD, the numbers and diversity of macrophages change and cause adverse effects on the onset of disorders.

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Phagocytosis: A Fundamental Process in Immunity

Carlos rosales.

1 Departamento de Inmunología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Mexico

Eileen Uribe-Querol

2 División de Estudios de Posgrado e Investigación, Facultad de Odontología, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Mexico

One hundred years have passed since the death of Élie Metchnikoff (1845–1916). He was the first to observe the uptake of particles by cells and realized the importance of this process for the host response to injury and infection. He also was a strong advocate of the role of phagocytosis in cellular immunity, and with this he gave us the basis for our modern understanding of inflammation and the innate and acquired immune responses. Phagocytosis is an elegant but complex process for the ingestion and elimination of pathogens, but it is also important for the elimination of apoptotic cells and hence fundamental for tissue homeostasis. Phagocytosis can be divided into four main steps: (i) recognition of the target particle, (ii) signaling to activate the internalization machinery, (iii) phagosome formation, and (iv) phagolysosome maturation. In recent years, the use of new tools of molecular biology and microscopy has provided new insights into the cellular mechanisms of phagocytosis. In this review, we present a general view of our current knowledge on phagocytosis. We emphasize novel molecular findings, particularly on phagosome formation and maturation, and discuss aspects that remain incompletely understood.

1. Introduction

Élie Metchnikoff (1845–1916) made his original observations in the 1880s while studying invertebrate marine organisms. He found special cells attacking small thorns placed into starfish larvae. Based on these findings, he later moved into immunology and championed the concept of cellular immunity. For his contributions he was awarded the Nobel Prize in 1908 [ 1 ]. He shared the prize with Paul Ehrlich, a supporter of humoral immunity. Together they provided the bases for modern immunology.

Phagocytosis is an important process for nutrition in unicellular organisms, while in multicellular organisms it is found in specialized cells called phagocytes. Phagocytosis consists in recognition and ingestion of particles larger than 0.5  μ m into a plasma membrane derived vesicle, known as phagosome. Phagocytes can ingest microbial pathogens, but importantly also apoptotic cells. In this way, they contribute to the clearance of billions of cells that are turned over every day. Thus phagocytosis becomes essential not only for microbial elimination, but also for tissue homeostasis. Professional phagocytes [ 2 ] include monocytes, macrophages, neutrophils, dendritic cells, osteoclasts, and eosinophils. These cells are in charge of eliminating microorganisms and of presenting them to cells of the adaptive immune system. In addition, fibroblasts, epithelial cells, and endothelial cells can also perform phagocytosis. These nonprofessional phagocytes cannot ingest microorganisms but are important in eliminating apoptotic bodies [ 3 , 4 ].

Phagocytes must recognize a large number of different particles that could potentially be ingested, including all sorts of pathogens and also apoptotic cells. This recognition is achieved thanks to a variety of discrete receptors that distinguish the particle as a target and then initiate a signaling cascade that promotes phagocytosis. Receptors on the plasma membrane of phagocytes can be divided into nonopsonic or opsonic receptors. Nonopsonic receptors can recognize directly molecular groups on the surface of the phagocytic targets. Among these receptors there are lectin-like recognition molecules, such as CD169 and CD33; also related C-type lectins, such as Dectin-2, Mincle, or DNGR-1; scavenger receptors [ 5 ]; and Dectin-1, which is a receptor for fungal beta-glucan [ 6 ]. Other receptors, such as SR-A or CD36, can recognize both apoptotic and microbial polyanionic ligands, but their signaling capacity is not well described [ 5 ]. Interestingly, toll-like receptors (TLRs) [ 7 ] are detectors for foreign particles, but they do not function as phagocytic receptors. However, TLRs often collaborate with other nonopsonic receptors to stimulate ingestion [ 8 ].

Opsonic receptors recognize host-derived opsonins that bind to foreign particles and target them for ingestion. Opsonins include antibodies, complement, fibronectin, mannose-binding lectin, and milk fat globulin (lactadherin) [ 3 ]. The best characterized and maybe most important opsonic phagocytic receptors are the Fc receptors (FcR) and the complement receptors (CR). FcRs bind to the constant (Fc portion) of immunoglobulin (Ig) G [ 9 , 10 ] or IgA antibodies [ 11 ]. Complement receptors, such as CR3, bind to iC3b deposited on the particle after complement activation [ 12 ].

After recognition of the target particle, phagocytic receptors initiate signaling cascades that remodel lipids in the cell membrane and regulate the actin cytoskeleton in order to extend the cell membrane around the particle [ 13 ]. During this part of the process, phagocytic receptors also engage in a sequential order and cooperate to complete the formation of the phagosome [ 14 ].

Once the particle is internalized inside the early phagosome, this vacuole can fuse with vesicles coming from the endoplasmic reticulum and the Golgi complex to form an intermediary phagosome [ 15 – 21 ]. The contribution of the endoplasmic reticulum to phagosome formation and maturation is not completely understood, particularly in relation to cross-presentation of antigens. This is the process by which MHC class I (MHC-I) molecules can also present peptides from extracellular proteins. MHC-I molecules are delivered to the phagosome, where they are loaded with peptide and then recycled back to the plasma membrane. At present, it is not possible to convincingly describe a trafficking pathway for MHC-I molecules leading to cross-presentation. While classic (endogenous) MHC-I loading is basically restricted to the secretory pathway, cross-presentation involves interaction between this pathway and the phagocytic pathway [ 22 ]. A complete discussion of cross-presentation is beyond the scope of the present review. The reader is directed to recent excellent reviews on this topic [ 23 , 24 ]. Similarly, the contribution of the Golgi complex to phagosome formation is a matter of debate. Despite the fact that a role for the Golgi complex during phagocytosis by macrophages has been ruled out consensually by several groups [ 25 – 27 ], it is important to notice that these reports are mainly focused on Fc γ receptor-mediated phagocytosis. In contrast, it was recently reported that recruitment of Golgi-derived secretory vesicles during phagosome formation was important for uptake of most particles, except IgG-opsonized ones [ 20 ]. The formation of an intermediary phagosome is dynamic process involving fusion of endocytic vesicles and fission of secretory vesicles, resulting in remodeling of the membrane and progressive acidification of the phagosome [ 28 ]. Later this intermediary phagosome turns into a microbicidal vacuole, the phagolysosome, by fusing with lysosomes and changing its membrane and interior characteristics through a process named phagolysosome maturation [ 28 ].

2. Particle Recognition

The first step in phagocytosis is the detection of the particle by phagocytes. This, as mentioned before, is accomplished by specialized receptors on the cell membrane. Foreign particles, such as microbial pathogens, can be recognized directly by receptors that bind molecules not found in higher organisms, or indirectly through opsonins. Several receptor types are found on a single phagocyte and they cooperate for recognition and ingestion of the particle. Some receptors can bind to pathogen-associated molecular patterns (PAMPs) but not necessarily initiate phagocytosis. TLRs and some G-protein coupled receptors prepare (prime) the cell for phagocytosis by inducing inside-out activation of phagocytic integrins.

2.1. Receptors for Foreign Particles

2.1.1. pattern-recognition receptors.

Some receptors that directly bind PAMPs and seem to be phagocytic receptors include Dectin-1, mannose receptors, CD14, and scavenger receptor A (SR-A) ( Table 1 ). Dectin-1 binds to polysaccharides of some yeast cells [ 29 ]. Mannose receptors bind mannan [ 30 ]. CD14 binds to lipopolysaccharide-binding protein [ 31 ]. SR-A can detect lipopolysaccharide (LPS) on some gram-negative bacteria [ 32 ] and on Neisseria meningitidis [ 33 ]. Among these receptors, Dectin-1 has been clearly shown to be sufficient for activating phagocytosis. When it is expressed on heterologous cells that normally cannot perform phagocytosis, it gives the cells phagocytic capabilities [ 29 , 34 ]. However, for other PAMP receptors the phagocytic potential is still a matter of debate. It may be that they induce phagocytosis indirectly by tethering the particle to the phagocyte surface, or by priming the phagocyte [ 35 ] to ingest the particle via other receptors.

Human phagocytic receptors and their ligands.

∗ TIM, T cell immunoglobulin mucin; BAI-1, brain-specific angiogenesis inhibitor 1; MFG, milk fat globule.

2.1.2. Opsonic Receptors

Foreign particles can also be recognized by phagocytes through soluble molecules that will bind to the particles, tagging them for ingestion. Once on the surface of the target particle, these molecules, called opsonins, are in turn recognized by specific receptors on the membrane of phagocytes. In this manner, opsonins function as a bridge between the phagocyte and the particle to be ingested. Antibody (IgG) molecules and complement components are important opsonins that induce efficient phagocytosis, and their receptors have been studied extensively ( Table 1 ). Fc γ receptors (Fc γ R) are a family of glycoproteins expressed on the membrane of leukocytes, capable of binding the Fc portion of IgG molecules [ 10 , 36 ]. These receptors can bind to the various IgG subclasses with different affinities [ 9 ] and when crosslinked by multivalent antigen-antibody complexes can induce phagocytosis and other cellular responses [ 9 ]. Complement receptors (CRs) recognize components of the complement cascade, deposited on the surface of phagocytic targets [ 37 ]. There are now three recognized gene superfamilies of complement receptors: (i) the short consensus repeat (SCR) modules that code for CR1 and CR2, (ii) the β 2 integrin family members CR3 and CR4, and (iii) the immunoglobulin Ig-superfamily member CRIg [ 12 ]. Complement receptors, such as the integrin α M β 2 (also known as CD11b/CD18, CR3, or Mac-1), bind the complement component iC3b deposited on pathogens to promote phagocytosis [ 38 , 39 ].

2.2. Receptors for Apoptotic Cells

In addition to foreign pathogens, in a normal organism there are millions of cells that die by apoptosis every day. These apoptotic bodies are constantly cleared by phagocytosis. Recognition of apoptotic bodies involves several signals. First, cells in apoptosis release molecules that normally do not exist outside cells. Some of these molecules include ATP, lysophosphatidylcholine, and sphingosine 1-phosphate. These soluble molecules function as chemoattractants for phagocytes. Also, apoptotic cells are displayed on their surface molecules, such as phosphatidylserine (PS) not normally present on a healthy cell [ 54 ]. These surface molecules function as an “eat me” signal [ 55 ] for phagocytes. Some receptors such as TIM-1, TIM-4 [ 48 ], stabilin-2 [ 49 ], and BAI-1 (brain-specific angiogenesis inhibitor 1) directly recognize PS [ 50 ]. Other receptors, for example, MFG-E8 (lactadherin), can connect PS to α V β 3 integrins [ 51 ]. Apoptotic cells can also be recognized by scavenger receptors A (SR-A), MARCO, and CD36 [ 56 ]. CD36 bind modified lipids, including oxidized PS [ 53 ]. Many normal cells can also express some amounts of PS on their membranes. However, PS increases as much as 300-fold in apoptotic cells, creating a threshold that prevents phagocytosis of normal cells. There are some cells, for example, activated B and T cells, that may present large amounts of PS on their membrane. To prevent phagocytosis, these cells express molecules that deliver a “do not eat me” signal [ 4 ]. CD31 is one such molecule. It prevents phagocytosis by promoting cell detachment after homotypic (self)-binding [ 57 ]. Also, CD47 is another molecule that blocks phagocytosis of cells expressing it on their surface. CD47 binds to the receptor SIRP α (signal regulatory protein α ), on the membrane of phagocytes, and delivers an inhibitory signal for actin assembly [ 58 ]. Another level of complexity is the fact that multiple receptors bind apoptotic cells directly or indirectly and professional phagocytes coexpress many of these receptors. Thus, there are still many unidentified mechanisms for phagocytosis via apoptotic receptors. Because, it is now recognized that clearance of apoptotic cells is fundamental for tissue homeostasis [ 59 ], future research will bring us great surprises in this area.

2.3. Receptor Cooperation

For an efficient recognition of the target particle, multiple receptors on the phagocyte must engage multiple ligands on the particle. This interaction depends on the relative affinity of the molecules involved and also on their density on the surface of both the leukocyte and the particle. In addition, the relative mobility of the receptors on the membrane of the phagocyte affects the avidity of the interaction [ 60 ]. Because phagocytic receptors get activated when they aggregate in the plane of the membrane, only receptors capable of fast lateral diffusion are more likely to form multimers and get activated than immobile receptors (see section on phagosome formation). Aggregation (also called crosslinking) of the receptors is additionally promoted by the active nature of phagocytes, which constantly form membranous projections to probe their environments [ 61 , 62 ]. Thus, particle recognition by receptor binding and activation are very active processes.

Another aspect of receptor cooperation is observed when integrin receptors, such as the CR3, increase their affinity for their ligand only after the phagocyte gets extra stimuli through TLRs [ 63 ], Fc receptors [ 64 ], or CD44 [ 65 ]. These receptors initiate intracellular signaling that activates the small GTPase Rap1 [ 66 ], which in turn provokes conformational changes in the integrin, leading to its increased affinity. This process is called inside-out signaling because the signal that activates the integrin comes from inside the cell. During the phagocytic process integrins get activated to promote efficient receptor binding all around the target particle (see later).

3. Particle Internalization

When a particle interacts with phagocyte receptors, a series of signaling events are triggered to activate phagocytosis. Important changes in membrane remodeling and the actin cytoskeleton take place leading to the formation of pseudopods that cover the particle. At the point of contact, a depression of the membrane (the phagocytic cup) is formed. Then, the membrane surrounds the target particle and within few minutes it closes at the distal end, leaving a new phagosome. The signaling cascades are known in great detail for the Fc receptors and the complement receptors, since these are the best-studied phagocytic receptors [ 38 , 67 , 68 ]. Signaling for other phagocytic receptors is just beginning to be explored. Great interest exists in this area and research will certainly be fruitful in the near future.

3.1. Fc γ Receptor Signaling

Fc γ receptors get activated in the plane of the phagocyte membrane when they aggregate after binding to their IgG ligands that cover the particle to be ingested. In humans there are several types of activating Fc γ Rs that are coexpressed by professional phagocytes along with the only inhibitory Fc γ RIIb. The clustering of activating Fc γ Rs results in the phosphorylation of immunoreceptor tyrosine-based activation (ITAM) motifs present within the cytoplasmic domain of the receptor (as is the case with Fc γ RIIa and Fc γ RIIc), or in an associated FcR common γ -chain (as with Fc γ RI and Fc γ RIIIa) [ 9 , 10 , 69 ]. ITAM phosphorylation is carried out by Src-family kinases (Lyn, Lck, and Hck specifically), creating a docking site for the SH2 domains of the tyrosine kinase Syk, which can itself phosphorylate neighboring ITAM tyrosines [ 38 , 70 ]. The mechanism by which receptor aggregation induces phosphorylation of the ITAM tyrosines remains elusive. Aggregation may induce accumulation of the Fc γ Rs in cholesterol-enriched lipid rafts, where Src-family kinases are concentrated. This model is supported by the fact that Fc γ RIIa becomes associated with detergent-resistant membranes (DRMs) upon activation by aggregation [ 71 , 72 ] and that depletion of cholesterol with methyl- β -cyclodextrin inhibits Fc γ RII phosphorylation in response to aggregation [ 71 ]. Association of Fc γ RIIa with DRMs depends on its palmitoylation on a cysteine residue [ 73 ]. Despite these reports, the model of lipid rafts presents some limitations that need to be considered. For example, not all Fc γ receptors are palmitoylated (like Fc γ RIIa is); thus other receptors may not associate with lipid rafts or they would do by another mechanism. Interestingly, a transmembrane mutant form of Fc γ RIIa that failed to associate with lipid rafts was still able to trigger phagocytosis [ 73 ]. Also, the use of methyl- β -cyclodextrin to eliminate cholesterol from the cell membrane may be a very harsh treatment and the functional condition of the cell afterwards is not clear. Moreover, lipid rafts disruption by cholesterol depletion did not inhibit phagocytosis in macrophages [ 74 ]. In addition, there is still a debate whether DRMs really reflect the segregation of lipids in membranes or are artificially induced by the detergents used in their preparation. Thus, the model of lipid rafts needs to be considered with caution [ 75 ].

As mentioned above, different phagocytes express more than one activating Fc γ R, and at the same time they also express the inhibitory Fc γ RIIb. The coexpression of both activating and inhibitory Fc γ R results in simultaneous triggering of activating and inhibitory signaling pathways [ 10 ]. Thus, a particular phagocyte will initiate phagocytosis when the sum of activating and inhibiting signals reaches a threshold of activation that is determined by the relative expression of both types of Fc γ R [ 76 ]. The importance of the inhibitory Fc γ RIIb in regulating many IgG-mediated responses in different leukocytes was made evident in Fc γ RIIb-deficient mice, which showed enhanced activity of many IgG-mediated cell responses including phagocytosis [ 77 ]. Another molecule that negatively regulates phagocytosis of macrophages is CD47 via SIRP α [ 78 , 79 ]. Ligation of CD47 leads to phosphorylation of the immunoreceptor tyrosine-based inhibition (ITIM) motif in the cytoplasmic tail of SIRP α , which in turn recruits the phosphatase SHP-1 [ 58 ]. By super-resolution microscopy, it has become evident that many receptors are found in clusters at the plasma membrane on a nanometer scale [ 80 ]. In the case of resting macrophages, it was recently found that nanoclusters of Fc γ RI are constitutively associated with nanoclusters of SIRP α . Upon Fc receptor activation, Src-family kinase signaling leads to segregation of Fc γ RI and SIRP α nanoclusters [ 81 ], and co-ligation of SIRP α with CD47 prevented nanocluster segregation. Thus, when the balance of signals favors activation, Fc γ RI nanoclusters are separated from the inhibitory signal [ 81 ].

After Fc γ R phosphorylation, Syk binds to the ITAM motifs and gets also activated. Syk has also been shown to be required for phagocytosis [ 38 , 70 ] and it is responsible for activation of several additional signaling proteins that get recruited to the Fc γ R signaling complex ( Figure 1 ). The transmembrane protein LAT (linker for activation of T cells) is phosphorylated by Syk. Phosphorylation of LAT induces docking of additional adaptors: Grb2 binds to LAT, and in turn it recruits Gab2 (Grb2-associated binder 2). Gab2 is also phosphorylated by Syk. Other proteins are then also recruited to the complex. Among them is phospholipase C (PLC) γ 1, which produces inositoltrisphosphate (IP 3 ) and diacylglycerol (DAG). These second messengers cause calcium release and activation of protein kinase C (PKC), respectively. PKC leads to activation of extracellular signal-regulated kinases (ERK and p38) [ 82 ]. The guanine nucleotide exchange factor (GEF) Vav activates GTPases of the Rho and Rac family, which are involved in regulation of the actin nucleation complex Arp2/3, which induces the actin polymerization that drives pseudopod extension. Other enzymes such as phosphatidylinositol 3-kinase (PI 3-K) activate the GTPase Rac and nuclear factors like NF- κ B ( Figure 1 ).

Fcγ receptor signal transduction . Fc γ RIIa crosslinking by immunoglobulin (IgG) bound to a particle induces activation of Src family kinases (SFK), which phosphorylate tyrosine residues in the ITAMs (red box) of the cytoplasmic tail of the receptor. Then, Syk associates with phosphorylated ITAMs and leads to phosphorylation and activation of a signaling complex formed by the scaffold protein LAT (linker for activation of T cells) interacting with various proteins. Some of these proteins are phospholipase C gamma (PLC γ ), which produces inositoltrisphosphate (IP 3 ) and diacylglycerol (DAG). These second messengers cause calcium release and activation of protein kinase C (PKC), respectively. PKC leads to activation of extracellular signal-regulated kinases (ERK and p38). The guanine nucleotide exchange factor Vav activates the GTPase Rac, which is involved in regulation of the actin nucleation complex Arp2/3, via the nucleation-promoting factor Scar/WAVE. Rac is also involved in activation of transcription factors such as NF- κ B and JNK. The enzyme phosphatidylinositol 3-kinase (PI3K), which is recruited and activated by Syk, generates the lipid phosphatidylinositol-3,4,5-trisphosphate (PIP 3 ) at the phagocytic cup. This lipid also regulates Rac activation and contractile proteins such as myosin. Another GTPase, Cdc42, is also activated during Fc γ R signaling by an unknown mechanism and induces actin polymerization by activating the nucleation-promoting factor WASp (Wiskott-Aldrich Syndrome protein). P represents a phosphate group. ER, endoplasmic reticulum.

3.1.1. Lipid Signals

Signaling events regulating phagosome formation have also been examined by fluorescence imaging techniques. Detection of lipids and several activating proteins has shown that different molecules associate and dissociate from phagosomes in an orderly fashion ( Figure 2 ). Phosphatidylinositol-4,5-bisphosphate [PI(4,5)P 2 ] is present in large amounts in the inner leaflet of the plasma membrane of resting phagocytes. During phagocytosis, the concentration of PI(4,5)P 2 increases in the pseudopods that form the phagocytic cup but then decreases abruptly [ 83 ]. The drastic disappearance of PI(4,5)P 2 following its modest initial accumulation is essential to allow particle internalization, probably by facilitating actin disassembly [ 84 ]. Several pathways contribute to the disappearance of PI(4,5)P 2 . PLC γ is phosphorylated and recruited to the phagocytic cup in a Syk-dependent manner, probably by interaction with LAT [ 83 , 85 ]. PLC γ activity is critical because its inhibition prevents DAG production and blocks phagocytosis [ 83 ]. In addition, DAG leads to activation of PKC ε , which enhances phagocytosis [ 86 ]. PI(4,5)P 2 is also consumed when it becomes phosphorylated by PI-3K, producing PI(3,4,5)P 3 at the phagocytic cup [ 87 ]. PI-3K is recruited and activated by Syk [ 88 ], or by adaptor proteins such as Gab2 [ 89 ] ( Figure 1 ). These dramatic changes in membrane lipid composition during Fc γ receptor-mediated phagocytosis demonstrate that distinct molecules are activated and recruited in a carefully orchestrated manner to induce phagosome formation.

Signaling molecules concentrated in different parts of the membrane during phagocytosis . A phagocyte cell membrane around an IgG-opsonized particle is shown at different stages of phagosome formation. After initial recognition, membrane protrusions form a phagocytic cup (a), then pseudopods extend around the particle (b), and membrane fusion events at the distal end close the new vacuole (c), which is finally separated as an intracellular phagosome (d). Fluorescent protein chimeras were used to locate (colored lines) the signaling molecules PI(4,5)P2, DAG, PKC, PI(3,4,5)P3, PI(3)P, active (GTP-bound) Cdc42, Rac1, Rac2, and actin.

3.1.2. Small GTPases

Small GTPases of the Rho family are important regulators of the actin cytoskeleton. These enzymes function as molecular switches alternating between an active (GTP-bound) state and an inactive (GDP-bound) state [ 90 ]. For activation, they need to release GDP and replace it with GTP. This action is catalyzed by guanine nucleotide exchange factors (GEFs). Later, GTP is hydrolyzed to GDP returning the GTPase to its inactive state. This last step is enhanced through interactions with GTPase-activating proteins (GAPs). The GTPases Rac and Cdc42 are activated and recruited to the forming phagosome during Fc γ receptor-mediated phagocytosis ( Figure 1 ) [ 91 ]. Cdc42 is activated early in phagocytosis mostly at the rims of the phagocytic cup [ 92 ] ( Figure 2 ). Rac1 is activated throughout the entire nascent phagosome, whereas Rac2 is activated later, mostly at the base of the phagocytic cup [ 92 ] ( Figure 2 ). Cdc42 and Rac participate in regulating the localized formation of actin fibers, necessary for pseudopod extension, by activating the nucleation-promoting factors WASp (Wiskott-Aldrich Syndrome protein) and Scar/WAVE, respectively [ 93 ] ( Figure 1 ). WASp and Scar, in turn, activate the Arp2/3 complex for actin polymerization [ 94 ] ( Figure 1 ).

3.2. Complement Receptor Signaling

The integrin CR3 is the best-studied phagocytic complement receptor. For a long time, it has been recognized that engagement of CR3 on macrophages triggers a distinct form of phagocytosis, characterized by “sinking” of the particle into the cell without forming the characteristic pseudopods of Fc γ R phagocytosis [ 95 ]. However, this idea has been questioned by recent microscopy observations that showed membrane protrusions encircling the targets during CR3-mediated phagocytosis [ 62 , 96 ]. Still, it is thought that integrin CR3 signaling for phagocytosis is very different from Fc γ R signaling. Early reports demonstrated that phagocytosis of complement- opsonized zymosan and of complement-opsonized erythrocytes was unaffected by tyrosine kinase inhibitors [ 97 ]. This ruled out the participation of tyrosine kinases in this type of phagocytosis. In addition, macrophages from Syk −/− mice showed normal levels of CR-mediated phagocytosis [ 98 ]. However, β 2 integrin stimulation by adhesive ligands, or by artificial integrin cross-linking with antibodies induced various cellular responses in a Src and/or Syk kinase-dependent manner [ 99 ]. More recently, it was shown that Syk is phosphorylated during CR3-mediated phagocytosis and its inhibition prevents particle ingestion [ 100 ]. Also, Syk can be indirectly activated by integrins via the ITAM-bearing FcR γ chain and/or DAP12 [ 101 ]. The reason Syk −/− macrophages are capable of CR-mediated phagocytosis while the other experimental systems clearly implicate Syk in integrin signaling remains a mystery. It might be possible that genetically deficient cells have upregulated other molecules, for example, Zap70, that allow the bypass of Syk during CR-mediated phagocytosis.

Other differences between Fc γ R- and CR-mediated phagocytosis seem to be the cytoskeleton requirements for particle internalization. The actin cytoskeleton is required for Fc γ R-mediated phagocytosis, whereas the actin and microtubule cytoskeletons are required for CR-mediated phagocytosis [ 97 , 102 ]. Moreover, in complement phagocytosis F-actin accumulation and particle ingestion depend on RhoA, but not on Rac or Cdc42 [ 103 , 104 ], and binding of iC3b-opsonized erythrocytes increased levels of Rho-GTP but not of Rac-GTP [ 105 ]. However, ingestion of iC3b-opsonized erythrocytes is reduced in cells where Rac1 and Rac2 were deleted [ 106 ]. Together these findings challenge the classical model that CR3-mediated phagocytosis depends only on RhoA [ 106 ].

Rho, in turn, leads to actin polymerization via two mechanisms ( Figure 3 ). First, Rho can activate Rho kinase, which phosphorylates and activates myosin II [ 107 ]. Inhibition of Rho kinase activity also prevents accumulation of Arp2/3 and actin assembly at the phagocytic cup [ 107 ]. Second, Rho can induce accumulation of mDia1 (mammalian diaphanous-related formin 1) and polymerized actin in the phagocytic cup. Interfering with mDia activity inhibits CR3-mediated phagocytosis while having no effect on Fc γ R-mediated phagocytosis [ 108 ]. Also, mDia1 binds directly to the microtubule-associated protein CLIP-170 and induces its accumulation at the phagocytic cup [ 109 ]. This pathway also provides a link to the microtubule cytoskeleton required for CR-mediated phagocytosis [ 97 , 102 ]. Thus, microtubules and actin seem to function cooperatively in CR-mediated phagocytosis ( Figure 3 ).

Complement receptor signaling in phagocytosis . The complement receptor 3 (CR3 integrin) binds the complement fragment iC3b and initiates a signaling cascade that activates Rho, either independently of tyrosine kinases (in macrophages) or via Syk, which is recruited through an ITAM-bearing molecule (such as DAP12 or the Fc receptor γ chain). Syk may also activate the GEF Vav to further activate Rho. Rho, in turn, leads to actin polymerization via two mechanisms. Rho can activate Rho kinase (ROCK), which phosphorylates and activates myosin II, inducing accumulation of Arp2/3 and actin assembly at the phagocytic cup. Rho can also induce accumulation of mDia1 (mammalian diaphanous-related formin 1), which promotes actin polymerization. In addition, mDia1 binds directly to the microtubule-associated protein CLIP-170 providing a link to the microtubule cytoskeleton. P represents a phosphate group. ITAM, immunoreceptor tyrosine-based activation motif.

The signaling pathway for Rho activation is not clearly defined. Two regions in the cytosolic domain of the β 2 subunit of the integrin receptor are important for Rho activation during phagocytosis [ 105 ], but it is not clear how the integrin connects to a Rho GEF for activation. In addition, Vav (a Rho/Rac GEF) originally reported to participate in Fc γ R-mediated phagocytosis, but not in CR-mediated phagocytosis [ 110 ], can also activate Rho [ 106 ]. Since, Rho participates in Arp2/3 activation and actin polymerization by CR3 [ 104 ] and Vav is a substrate for Syk [ 111 ], it is possible that a connection exists for Rho activation via Syk and Vav [ 3 ] ( Figure 3 ).

4. Phagosome Formation

As indicated before, phagocytosis commences by interaction of phagocytic receptors with ligands on the surface of target particles. Then, receptors must aggregate to initiate signaling pathways that regulate the actin cytoskeleton, so that the phagocyte can produce membrane protrusions for involving the particle. Finally, the particle is enclosed in a new vesicle that pinches out from the plasma membrane.

4.1. Initial Interactions

The initial interactions of phagocytic receptors with the particle are not easy, since receptor ligands do not usually cover the particle uniformly and receptors are not freely accessible on the cell membrane. In fact, most phagocytic receptors are short molecules that extend only around 5 nm from the surface of the cell ( Figure 4(a) ) and are found among many much longer, usually rigid, transmembrane glycoproteins present throughout the membrane. These glycoproteins form a thick layer, known as glycocalyx, covering the cell membrane, that can effectively conceal short receptors [ 112 ]. Mucins, high molecular weight, heavily glycosylated proteins, CD44 and hyaluronan, and transmembrane phosphatases such as CD45 and CD148 are components of the glycocalyx that can reduce ligand access to receptors on the phagocyte membrane ( Figure 4(a) ). In addition, the lateral diffusion of receptors on the cell membrane can be effectively reduced by glycocalyx components that are tethered to cytoskeletal structures. These glycoproteins effectively act as the “pickets” of a cytoskeletal “fence” [ 13 , 14 ] that impedes free diffusion of other membrane molecules. This is the case for phagocytic receptors, which move only in discrete areas on the cell membrane among these immobile picket fences ( Figure 4(b) ).

Cooperation among phagocytic receptors . (a) Most phagocytic receptors, such as receptors for antibody (Fc γ RIIa) and receptors for complement (Integrin CR3) are small molecules that extend only few nanometers from the plasma membrane. In contrast, transmembrane glycoproteins, such as phosphatases CD45 (CD45RO and CD45RA isoforms), are much longer and usually rigid molecules. (b) In the resting state, receptors cannot diffuse freely throughout the membrane. Their movement is restricted by fences of transmembrane glycoprotein “pickets” attached to an actin mesh. (c) Fc γ R aggregation triggers an inside-out signal that activates integrins. Fc γ R-induced activation of phospholipase C (PLC) produces diacylglycerol (DAG) that leads to activation of CalDAG (a Rap GEF), which in turn activates Rap. Activated Rap (Rap GTP) is responsible for integrin activation by disrupting interactions between integrin subunits and promoting binding to talin, vinculin, and the actin cytoskeleton.

Phagocytes improve interactions of receptors with possible targets by (i) creating active membrane protrusions that allow the cell to explore larger areas, increasing the chances for receptors to engage their ligands [ 61 , 113 ], and by (ii) selectively removing some of these larger glycoproteins allowing the receptors to diffuse more freely on the membrane [ 114 ]. The phosphatase CD45 can extend more than 40 nm from the cell membrane [ 115 ], and it is a real steric obstacle for phagocytic receptors. Removing these large molecules could greatly improve receptor binding. Indeed, removal of CD45 was first observed during Dectin-1-mediated phagocytosis in a structure that was called “phagocytic synapse” [ 116 ], for its similarity to the T lymphocyte immune synapse [ 117 ]. When T cell receptor (TCR) molecules on the T lymphocyte interact with MHC/peptide molecules on an antigen-presenting cell, a central cluster of engaged TCR is formed. The TCRs are surrounded by a ring of integrin LFA-1 (lymphocyte-function-associated antigen-1) molecules, and CD45 is excluded from the central area. TCR interactions span around 15 nm, while integrin interactions span around 30–40 nm between the two cells. Thus removal of the larger molecules helps an efficient TCR interaction. A similar situation for Fc γ R-mediated phagocytosis has also been elegantly described recently by Sergio Grinstein's group [ 114 ].

Besides its steric interference, there is another reason for removing CD45 from Fc γ Rs. The tyrosine phosphatase CD45 must be taken away from sites of Fc γ R engagement to allow full activation of Src tyrosine kinases, which phosphorylate ITAM sequences needed for activation of phagocytosis signaling [ 115 ]. First, CD45 must be allowed to diffuse more on the membrane. The lateral diffusion of CD45 is restricted by interactions between its cytoplasmic domain with ankyrin and spectrin molecules that connect to the actin cytoskeleton [ 118 ]. These interactions can be reduced by signals that alter the cytoskeleton and prime the cell for phagocytosis. TLR ligands, for example, LPS and bacterial DNA, can reduce the restricted diffusion of immunoreceptors [ 119 ]. Second, the more motile CD45 molecules need to be kept away from the engaged phagocytic receptor. This is achieved by the creation of a diffusion barrier made of activated integrins [ 114 ]. Fc γ Rs (and also G-protein coupled receptors or TLR) deliver signals for inside-out activation of integrins. Inactive integrins exist in a bent conformation that does not bind ligands. The signal from Fc γ R can produce DAG and Ca 2+ , which together activate CalDAG-GEF1 (a GEF for Rap). The small GTPase Rap in its GTP form is then able to recruit RIAM and talin to the cytoplasmic tail of the β subunit of integrins [ 120 ] ( Figure 4(c) ). This triggers the unfolding of the integrin into a high affinity “active” state. Kindlin-3 is another molecule that also binds to the β subunit of integrins causing their activation [ 121 , 122 ]. The extended active integrin can then bind to many different ligands on the target particle [ 123 ]. Thus, integrins participate in Fc γ R-mediated phagocytosis by promoting adhesion to the opsonized particle [ 124 ]. In addition, the integrin molecules that get engaged by ligands get also tethered to the actin cytoskeleton and, with this, they form a diffusional barrier for CD45 molecules. The extended integrin bound to the target particle effectively pushes out the larger glycocalyx components, such as CD45 ( Figure 5 ). As more integrin molecules get engaged they function as a progressive wave migrating ahead of the engaged Fc γ Rs, allowing new receptors to aggregate in microclusters [ 14 ] ( Figure 5 ).

Initial engagement of phagocytic receptors . Aggregation Fc γ RIIa by an IgG opsonized particle initiates signaling. Receptor ITAMs (red rectangles) are phosphorylated by Src-family kinases (SFK) and recruit Syk. This leads to inside-out signaling for integrin (CR3) activation via the GTPase Rap. Activated integrin binds to adaptor molecules such as talin, vinculin, and kindlin-3 and connect to the actin cytoskeleton. Activated integrins also bind to the particle (via multiple possible ligands [ 113 ]) and form a diffusion barrier that excludes larger molecules, such as the transmembrane phosphatase CD45. This allows other Fc receptors to be engaged and increase the signaling for phagocytosis.

4.2. Actin Remodeling in Membrane Protrusions

After a target particle is detected, the phagocytic process requires remodeling of the actin cytoskeleton to promote changes of the plasma membrane. The process is very complex and we have only a partial understanding of it. However, several important steps directed by actin remodeling, to form the pseudopodia that will cover the particle, can be identified. First, the membrane-associated cortical cytoskeleton, of the resting phagocyte, needs to be disrupted. Second, nucleation of actin filaments takes place in order to initiate F-actin polymerization and extension of pseudopodia. Third, actin gets depolymerized from the base of the phagocytic cup and the phagosome is closed at the distal end [ 13 ]. These steps of the precise temporal and spatial activation and inactivation of multiple proteins that govern F-actin dynamics are described next and presented in Figure 6 .

Cytoskeleton changes during phagocytosis . (a) Phagocytes explore their surroundings for phagocytic targets by projecting membrane ruffles, filopodia, and podosomes. These membranes contain mostly linear actin fibers. (b) Upon recognition of a target particle, the actin cytoskeleton is disrupted at the phagocytic cup by the action of coronins (F-actin debranching proteins) and cofilin and gelsolin (F-actin-severing proteins). (c) As more phagocytic receptors get engaged around the particle, the cell extends pseudopodia, which contain new branched actin fibers. Actin nucleation and F-actin polymerization are mediated by the Arp2/3 protein complex, which can be stimulated by the GTPases Rac and Cdc42, via the nucleation-promoting factor Scar/WAVE. (d) At the last step, depolymerization of actin filaments from the base of the nascent phagosome may facilitate curving of the membrane around the particle and provide room for fusion of internal vesicles, a source of endomembranes. Actin depolymerization is controlled by phosphatidylinositol 3-kinase (PI3K), through its product phosphatidylinositol (3,4,5)-trisphosphate (PIP 3 ), which may recruit Rho GAPs that inactivate the GTPases Rac and Cdc42, thus reducing Arp2/3 activity. PIP 3 also recruits myosins, which provide contractile activity that facilitates phagosome closure. At the same time, phospholipase C (PLC) cleaves phosphatidylinositol (4,5)-bisphosphate (PIP 2 ) to generate diacylglycerol (DAG) and inositol-trisphosphate (IP 3 ). The reduction of PIP 2 will liberate cofilin and increase F-actin severing activity.

A resting phagocyte presents a membrane-associated cortical cytoskeleton that provides cell shape. Upon activation, this cytoskeleton is disrupted by the action of coronins (F-actin debranching proteins) [ 125 ] and cofilin [ 126 ] and gelsolin [ 127 ] (F-actin-severing proteins). Coronin 1 rapidly accumulates at the nascent phagosome during both Fc γ R- and CR-mediated phagocytosis [ 125 ], and, in macrophages, it can interact with F-actin and inhibit the Arp2/3 complex [ 125 ]. Coronin 1 debranches F-actin leaving linear fibers that can be severed by cofilin and gelsolin ( Figure 6 , step (b)). Their activity is controlled by modulating their association with filaments, or by sequestering them away from filaments by binding to phosphoinositides, such as PI(4,5)P 2 [ 127 , 128 ]. In addition, the vesicular OCRL phosphatase activity to hydrolyze PI(4,5) P 2 seems to contribute to the step of actin depolymerization [ 129 ]. The role for these enzymes in phagocytosis is much more complex than just described, and future research is needed in this area [ 13 ]. This initial disruption of the cytoskeleton has two consequences: it provides G-actin monomers for incorporation into new filaments and increases the mobility of nonligated receptors on the membrane (see previous section). The second step is the nucleation of actin filaments to initiate F-actin polymerization and extension of pseudopodia ( Figure 6 , step (c)). This is achieved mainly by the action of the Arp2/3 protein complex, which can be stimulated by different pathways. In fact, as indicated above the signaling pathways triggered by the best-studied phagocytic receptors, namely, Fc γ Rs and CRs, are very different (see Figures ​ Figures1 1 and ​ and3). 3 ). For Fc γ R-mediated phagocytosis, Arp2/3 is recruited to the nascent phagocytic cup, where its actin-nucleating activity is stimulated by WASp and N-WASp [ 130 , 131 ], which in turn are activated by Cdc42-GTP and PI(4,5)P 2 [ 132 ]. In the case of CR-mediated phagocytosis, actin polymerization is associated with RhoA [ 133 ]. This GTPase recruits and stimulates mDia formins [ 108 ], which in turn also activate the Arp2/3 complex ( Figure 3 ). However, other GTPases, such as Rap, seem to play a role in CR-mediated phagocytosis, independently of RhoA [ 134 ]. Rap-GTP also activates profilin, which is essential for actin polymerization via formins [ 135 ]. Rap can also activate the GTPase Rac [ 106 ]. But as discussed earlier, the role of Rac in complement-mediated phagocytosis remains a subject of debate.

4.3. Phagosome Sealing

The last step in phagosome formation is characterized by elimination of F-actin from the base of the phagocytic cup, just before the membrane protrusions fuse at the other end to seal the nascent phagosome ( Figure 6 , panel (d)). Depolymerization of actin filaments from the phagocytic cup may also facilitate curving of the membrane around the particle and provide room for fusion of internal vesicles, a source of endomembranes [ 129 ]. The mechanism for actin removal from the forming phagosome has been poorly defined, and much more research is needed in this topic. The mechanism for removing F-actin must include the termination of actin polymerization and the detachment and depolymerization of existing filaments. Both steps seem to be controlled by phosphoinositides, in particular PI(3,4,5)P 3 , the product of PI-3K. Inhibition of this enzyme prevents depolymerization of actin at the base of the phagocytic cup and arrests extension of pseudopods [ 136 ]. PI(3,4,5)P 3 can activate Rho-family GAPs, which will induce deactivation of the GTPases stimulated during phagocytosis [ 137 , 138 ]. Supporting this idea is the fact that PI-3K inhibition causes accumulation of activated Cdc42 and Rac at the phagocytic cup [ 92 , 137 ]. However, because inhibition of PI-3K blocks phagocytosis even when GTPases are constitutively activated [ 137 ], this enzyme must control other molecules important for phagocytosis. One such molecule is PI(4,5)P 2 , which decreases by the action of PI-3K, but also by the action of PLC γ . Since PI(4,5)P 2 sequesters cofilin and gelsolin and it is required for WASp activation, its reduction will increase F-actin severing (by liberation of cofilin and gelsolin) and reduce actin polymerization (by inhibition of WASp) [ 13 ]. Other molecules regulated by PI(3,4,5)P 3 are myosins. Myosins exert contractile activity that functions as a purse string to facilitate phagosome closure [ 139 – 142 ] ( Figure 6 , step (d)).

Recently, the process of phagosome formation and closure has been revisited thanks to live microscopy with the technique of total internal reflection fluorescent microscopy (TIRFM) [ 143 ]. In this way, an important role for dynamin-2 in phagosome formation was revealed. Dynamin-2, which mediates the scission of endocytic vesicles, was recruited along with actin during phagosome formation, and depolymerization of actin led to impaired dynamin-2 recruitment or activity. Also, dynamin-2 accumulated at the site of phagosome closure [ 144 ]. Thus, it seems there is a cross-talk between actin and dynamin for phagosome formation and closure before dynamin functions for scission [ 144 ].

5. Phagolysosome Maturation

The phagosome changes its membrane composition and its contents, to turn into a phagolysosome, a vesicle that can destroy the particle ingested. This transformation is known as phagosome maturation ( Figure 7 ) and consists of successive fusion and fission interactions between the new phagosome and early endosomes, late endosomes, and finally lysosomes. At the end, the mature phagosome, also called phagolysosome, has a different membrane composition, which allows it to contain a very acidic and degradative environment [ 145 , 146 ].

Phagosome maturation . (A) The nascent phagosome gets transformed into a microbicidal vacuole, the phagolysosome, by sequential interactions with vesicles from the endocytic pathway. Four stages of maturation have been described: early (a), intermediate (b), late (c), and phagolysosome (d). In this process, the phagosome becomes increasingly acidic by the action of a proton-pumping V-ATPase and gets various degradative enzymes. The composition of the membrane also changes to include molecules that control membrane fusion, such as the GTPases Rab. See text for details. EEA1, early endosome antigen 1; ESCRT, endosomal-sorting complex required for transport; HOPS, homotypic protein sorting; ILV, intraluminal vesicle; LAMP, lysosomal-associated membrane protein; NADPH, nicotinamide adenine dinucleotide phosphate oxidase; RILP, Rab-interacting lysosomal protein; vPS34, vacuolar protein-sorting 34.

5.1. Early Phagosome

The new phagosome rapidly gets the properties of early endosomes, by fusing with sorting and recycling endosomes [ 28 ]. Its interior becomes a little acidic (pH 6.1–6.5) but it is not very destructive. Membrane fusion events between the phagosome and early endosomes are regulated by the small GTPase Rab5 [ 147 , 148 ]. This membrane GTPase is required for the transition from an early to a late phagosome. Rab5 functions through the recruitment of EEA1 (early endosome antigen 1), which promotes fusion of the new phagosome with early endosomes [ 149 ]. Rab5 also recruits class III PI-3K human vacuolar protein-sorting 34 (hvPS34), which, in turn, generates phosphatidylinositol 3-phosphate [PI(3)P] [ 150 ]. This lipid then helps fix EEA1 to the cytosolic face of the phagosome and promotes recruitment of other proteins involved in phagosome maturation, including Rab7, a marker of late endosomes [ 151 , 152 ]. EEA1 functions as a bridge that tethers early endosomes to incoming endocytic vesicles [ 153 ] and binds to syntaxin 13, a SNARE (soluble NSF-attachment protein receptor) protein required for membrane fusion [ 154 ]. Despite fusion with multiple early endosomes, the new phagosome does not seem to change size. This is due to the retrieval of vesicles to endosomes and the trans-Golgi network. Acidification of the phagosome lumen results from the gradual accumulation of active V-ATPases on the phagosome membrane. This V-ATPase is a multimeric protein complex that translocates protons (H + ) into the lumen of the phagosome using cytosolic ATP as an energy source [ 155 , 156 ] ( Figure 7 ). In order to keep an electrical balance across the phagosome membrane, negative anions (mainly Cl − ) also move inside, while cations (such as K + and Na + ) move outside [ 157 , 158 ].

5.2. Intermediate Phagosome

As maturation proceeds, Rab5 is lost, and Rab7 appears on the membrane. The vpsC-homotypic protein-sorting (HOPS) complex mediates the transition from Rab5 to Rab7 endosomes [ 152 ] and may function in a similar fashion in phagosome maturation. Rab7 mediates the fusion of the phagosome with late endosomes [ 159 ]. At the same time, intraluminal vesicles are now formed. They contain membrane-associated molecules that are intended for degradation. These vesicles seem to arise from inwards budding and pinching of the limiting membrane of the phagosome [ 145 ]. The membrane proteins marked for degradation are ubiquitinated and associate with the endosomal-sorting complex required for transport (ESCRT) [ 160 ]. This complex forms a circular array that directs the vesicles into the lumen of the phagosome [ 161 ] ( Figure 7 ).

5.3. Late Phagosome

Once the intermediate phagosome eliminates the proteins that will be recycled or degraded, it continues maturation to a late phagosome. Rab7 accumulates and becomes a marker for this stage. Rab7 recruits new proteins to the membrane. One such protein is Rab-interacting lysosomal protein (RILP), which binds to the dynein-dynactin complex [ 162 , 163 ] and brings the phagosome in contact with microtubules. This mediates the centripetal movement of late phagosomes and lysosomes [ 162 , 163 ] that brings the organelles in close contact so that SNARE proteins, such as VAMP (vesicle-associated membrane protein) 7 and VAMP8 can complete membrane fusion [ 164 , 165 ]. At this stage, the lumen gets more acidic (pH 5.5–6.0), thanks to more V-ATPase molecules on the membrane [ 155 ] ( Figure 7 ). In addition, lysosomal-associated membrane proteins (LAMPs) and luminal proteases (cathepsins and hydrolases) are incorporated from fusion with late endosomes or from the Golgi complex [ 145 , 146 ].

5.4. Phagolysosome

The last stage in the maturation process involves fusion of late phagosomes with lysosomes, to become phagolysosomes. Phagolysosomes are the ultimate microbicidal organelle [ 28 ]. Phagolysosomes count with many sophisticated mechanisms directed to eliminate and degrade microorganisms. They are highly acidic (pH as low as 4.5) thanks to the large number of V-ATPase molecules on their membrane [ 156 ]. Phagolysosomes are also characterized by a PI(3)P-enriched internal membrane [ 166 , 167 ] and by the lack of mannose-6-phosphate receptors [ 168 ]. They also contain a number of hydrolytic enzymes, including various cathepsins, proteases, lysozymes, and lipases [ 155 ]. Other microbicidal components of the phagosome are scavenger molecules, such as lactoferrin that sequesters the iron required by some bacteria [ 169 ] and the NADPH oxidase that generates superoxide (O 2 − ) [ 170 ] ( Figure 7 ). Superoxide can dismutate to H 2 O 2 , which can in turn react with O 2 − to generate more-complex reactive oxygen species (ROS), such as hydroxyl radicals and singlet oxygen [ 171 ]. In addition, H 2 O 2 can be combined with Cl − ions into hypochlorous acid by the enzyme myeloperoxidase [ 172 ].

6. Conclusion

Phagocytosis is an elegant and very complex process for the ingestion and elimination of pathogens and apoptotic cells. It is performed by a series of cells we call professional phagocytes. They are monocytes, macrophages, neutrophils, dendritic cells, osteoclasts, and eosinophils. It is evident that phagocytosis is fundamental for tissue homeostasis, controlling important aspects of inflammation and the immune response. Clearly, the many cell types that can perform phagocytosis and the overwhelming number of different phagocytic targets require more than one mechanism to complete this cellular function. We have presented the main four steps of phagocytosis to provide a general view of the whole process. Still, we have to keep in mind that this description corresponds primarily to opsonic receptors. We have very little knowledge of the signaling pathways other phagocytic receptors activate. Similarly, the process of phagosome maturation has gained much information from studies on vesicular traffic. Yet, important gaps remain in every step. Also, how the final phagolysosome completes its antimicrobial or degradative functions is not completely clear. But, the fact that several microbial pathogens have developed special ways for interfering with phagolysosome function gives us another opportunity to learn from them novel aspects on phagocytosis. In addition, the resolution of the phagolysosome, after the infection or the inflammation processes have terminated, is an area that has brought very little attention. What are the molecular details and functional implications of ingesting different particles? How the various phagocytic receptors on the same phagocyte cooperate? And how the various phagocytes participate in tissue homeostasis? These are important questions that future research in this exciting area will have to address. An improved understanding of phagocytosis is essential for the clear implications it has for antigen presentation and autoimmune disease.

Acknowledgments

The authors thank Lilian Araceli González Hernández for preparing the list of references. Research in the authors' laboratory was supported by Consejo Nacional de Ciencia y Tecnología, Mexico (Grant 254434 to Carlos Rosales), and by Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México, Mexico (Grant PAPIIT IA202013-2 to Eileen Uribe-Querol).

Conflicts of Interest

The authors declare that they do not have any conflicts of interest in the subject discussed in this review.

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Antigen Processing and Presentation

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Original Author(s): Antonia Round Last updated: 17th July 2023 Revisions: 9

• 1 Antigen Presentation
• 2.1 MHC Class I Molecules
• 2.2 MCH Class II Molecules
• 3.1 T Cell Receptors
• 3.2 Co-Receptors
• 4 Clinical Relevance – Autoimmune disease

T cells can only recognise antigens when they are displayed on cell surfaces. This is carried out by  Antigen-presenting cells (APCs) , the most important of which are dendritic cells, B cells, and macrophages. APCs can digest proteins they encounter and display peptide fragments from them on their surfaces for other immune cells to recognise.

This process of antigen presentation allows T cells to “see” what proteins are present in the body and to form an adaptive immune response against them. In this article, we shall discuss antigen processing, presentation, and recognition by T cells.

Antigen Presentation

Antigens are delivered to the surface of APCs by Major Histocompatibility Complex (MHC) molecules. Different MHC molecules can bind different peptides. The MHC is highly polygenic and polymorphic which equips us to recognise a vast array of different antigens we might encounter. There are different classes of MHC, which have different functions:

• MHC class I  molecules are found on all nucleated cells (not just professional APCs) and typically present intracellular antigens such as viruses.
• MHC class II molecules are only found on APCs and typically present extracellular antigens such as bacteria.

This is logical because should a virus be inside a cell of any type, the immune system needs to be able to respond to it. This also explains why pathogens inside human red blood cells (which are non-nucleated) can be difficult for the immune system to find, such as in malaria.

Whilst this is the general rule, in cross-presentation extracellular antigens can be presented by MHC class I, and in autophagy intracellular antigens can be presented by MHC class II.

Antigen Processing

Before an antigen can be presented, it must first be processed . Processing transforms proteins into antigenic peptides.

MHC Class I Molecules

Intracellular peptides for MHC class I presentation are made by proteases and the proteasome in the cytosol, then transported into the endoplasmic reticulum via TAP (Transporter associated with Antigen Processing) to be further processed.

They are then assembled together with MHC I molecules and travel to the cell surface ready for presentation.

Fig 1 – Diagram demonstrating the production of peptides for MHC class I presentation

MCH Class II Molecules

The route of processing for exogenous antigens for MHC class II presentation begins with endocytosis of the antigen. Once inside the cell, they are encased within endosomes that acidify and activate proteases, to degrade the antigen.

MHC class II molecules are transported into endocytic vesicles where they bind peptide antigen and then travel to the cell surface.

Fig 2 – Diagram showing processing of antigens for MHC Class II presentation by a dendritic cell

The antigen presented on MHCs is recognised by T cells using a T cell receptor (TCR) . These are  antigen-specific .

T Cell Receptors

Each T cell has thousands of TCRs , each with a unique specificity that collectively allows our immune system to recognise a wide array of antigens.

This diversity in TCRs is achieved through a process called V(D)J recombination during development in the thymus. TCR chains have a variable region where gene segments are randomly rearranged, using the proteins RAG1 and RAG2 to initiate cleavage and non-homologous end joining to rejoin the chains.

The diversity of the TCRs can be further increased by inserting or deleting nucleotides at the junctions of gene segments; together forming the potential to create up to 10 15 unique TCRs.

TCRs are specific not only for a particular antigen but also for a specific MHC molecule. T cells will only recognise an antigen if a specific antigen with a specific MHC molecule is present: this phenomenon is called  MHC restriction .

Co-Receptors

As well as the TCR, another T cell molecule is required for antigen recognition and is known as a co-receptor. These are either a CD4 or CD8 molecule:

• CD4 is present on T helper cells and only binds to antigen-MHC II complexes.
• CD8 is present on cytotoxic T cells and only binds to antigen-MHC I complexes.

This, therefore, leads to very different effects. Antigens presented with MHC II will activate T helper cells and antigens presented with MHC I activate cytotoxic T cells. Cytotoxic T cells will kill the cells that they recognise, whereas T helper cells have a broader range of effects on the presenting cell such as activation to produce antibodies (in the case of B cells) or activation of macrophages to kill their intracellular pathogens.

Clinical Relevance – Autoimmune disease

It is important to note that APCs may deliver foreign antigens or self-antigens. In the case of autoimmune diseases, self-antigens are presented to T cells, which then initiates an immune response against our own tissues.

For example, in Graves’ disease , TSHR (thyroid stimulating hormone receptor) acts as a self-antigen and is presented to T cells. This then activates B cells to produce autoantibodies against TSHRs in the thyroid. This results in the activation of TSHRs leading to hyperthyroidism and a possible goitre.

[start-clinical]

Clinical Relevance - Autoimmune disease

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Macrophages: Phagocytosis, Antigen Presentation, and Activation of Immunity

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Module 20: The Immune System

Antigen-presenting cells, learning outcomes.

• Describe the structure and function of antigen-presenting cells

Unlike NK cells of the innate immune system, B cells (B lymphocytes) are a type of white blood cell that gives rise to antibodies, whereas T cells (T lymphocytes) are a type of white blood cell that plays an important role in the immune response. T cells are a key component in the cell-mediated response—the specific immune response that utilizes T cells to neutralize cells that have been infected with viruses and certain bacteria. There are three types of T cells: cytotoxic, helper, and suppressor T cells. Cytotoxic T cells destroy virus-infected cells in the cell-mediated immune response, and helper T cells play a part in activating both the antibody and the cell-mediated immune responses. Suppressor T cells deactivate T cells and B cells when needed, and thus prevent the immune response from becoming too intense.

An antigen is a foreign or “non-self” macromolecule that reacts with cells of the immune system. Not all antigens will provoke a response. For instance, individuals produce innumerable “self” antigens and are constantly exposed to harmless foreign antigens, such as food proteins, pollen, or dust components. The suppression of immune responses to harmless macromolecules is highly regulated and typically prevents processes that could be damaging to the host, known as tolerance.

The innate immune system contains cells that detect potentially harmful antigens, and then inform the adaptive immune response about the presence of these antigens. An antigen-presenting cell (APC) is an immune cell that detects, engulfs, and informs the adaptive immune response about an infection. When a pathogen is detected, these APCs will phagocytose the pathogen and digest it to form many different fragments of the antigen. Antigen fragments will then be transported to the surface of the APC, where they will serve as an indicator to other immune cells. Dendritic cells are immune cells that process antigen material; they are present in the skin (Langerhans cells) and the lining of the nose, lungs, stomach, and intestines. Sometimes a dendritic cell presents on the surface of other cells to induce an immune response, thus functioning as an antigen-presenting cell. Macrophages also function as APCs. Before activation and differentiation, B cells can also function as APCs.

After phagocytosis by APCs, the phagocytic vesicle fuses with an intracellular lysosome forming phagolysosome. Within the phagolysosome, the components are broken down into fragments; the fragments are then loaded onto MHC class I or MHC class II molecules and are transported to the cell surface for antigen presentation, as illustrated in Figure 1. Note that T lymphocytes cannot properly respond to the antigen unless it is processed and embedded in an MHC II molecule. APCs express MHC on their surfaces, and when combined with a foreign antigen, these complexes signal a “non-self” invader. Once the fragment of antigen is embedded in the MHC II molecule, the immune cell can respond. Helper T- cells are one of the main lymphocytes that respond to antigen-presenting cells. Recall that all other nucleated cells of the body expressed MHC I molecules, which signal “healthy” or “normal.”

Figure 1. An APC, such as a macrophage, engulfs and digests a foreign bacterium. An antigen from the bacterium is presented on the cell surface in conjunction with an MHC II molecule Lymphocytes of the adaptive immune response interact with antigen-embedded MHC II molecules to mature into functional immune cells.

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• Open access
• Published: 13 August 2024

Galectin-3 induces pathogenic immunosuppressive macrophages through interaction with TREM2 in lung cancer

• Qiaohua Wang 1 , 2   na1 ,
• Yongjian Wu 1 , 3 , 4   na1 ,
• Guanmin Jiang 2 &
• Xi Huang 1 , 3 , 4  

Journal of Experimental & Clinical Cancer Research volume  43 , Article number:  224 ( 2024 ) Cite this article

Metrics details

High infiltration of tumor-associated macrophages (TAMs) is associated with tumor promotion and immunosuppression. The triggering receptor expressed on myeloid cells 2 (TREM2) is emerged as a key immunosuppressive regulator for TAMs, however, how TREM2-expressing TAMs are recruited and what ligands TREM2 interacts with to mediate immunosuppression is unknown.

Flow cytometry and single-cell RNA sequencing were used to analyze TREM2 expression. Mechanistically, mass spectrometry and immunoprecipitation were employed to identify proteins binding to TREM2. Phagocytosis and co-culture experiments were used to explore the in vitro functions of galectin3-TREM2 pair. Establishment of TREM2 f/f -Lyz2-cre mice to validate the role of TREM2 signaling pathway in lung carcinogenesis. GB1107 were further supplemented to validate the therapeutic effect of Galectin3 based on TREM2 signaling regulation.

This study identified that abundant TREM2 + macrophages were recruited at the intra-tumor site through the CCL2-CCR2 chemotactic axis. Galectin-3 impaired TREM2-mediated phagocytosis and promoted the conversion of TREM2 + macrophages to immunosuppressive TAMs with attenuated antigen presentation and co-stimulatory functions both in vitro both in vivo, and galectin-3 is a potential ligand for TREM2. Genetic and pharmacological blockade of TREM2 and galectin-3 significantly inhibited lung cancer progression in subcutaneous and orthotopic cancer models by remodeling the tumor immune microenvironment.

Our findings revealed a previously unknown association between galectin-3 and TREM2 in TAMs of lung cancer, and suggested simultaneous inhibition of galectin3 and TREM2 as potent therapeutic approach for lung cancer therapy.

Graphical Abstract

The immune system is crucial for preventing tumorigenesis; however, tumor cells often induce an immunosuppressive tumor microenvironment (TME) that actively suppresses immune responses to evade immune surveillance [ 1 ]. For instance, cancer cells directly suppress T-cell responses by binding to adaptive immune checkpoints such as programmed death 1 (PD-1) [ 2 ] and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) [ 3 ]. Immune checkpoint blockade (ICB) therapy has demonstrated efficiency in various cancers, including non-small cell lung cancer (NSCLC) [ 4 ], metastatic melanoma [ 5 ] and renal cancer [ 6 ]. However, owing to limitations such as the lack of tumor neoantigens [ 7 ], inability to reverse T cell exhaustion [ 8 ], and intratumoral presence of immunosuppressive immune cells, such as tumor-associated macrophages (TAMs) [ 9 ], only a small proportion of individuals respond to treatment. TAMs represent a significant innate immune cell population within the TME, accounting for approximately half of the local hematopoietic cells, with heterogeneity raging from anti- to pro-tumoral activity and differentiable plasticity [ 10 ]. The recruitment of TAMs from circulating monocytes/macrophages to the TME is primarily mediated by chemokines like CCL2, CCL5, and CXCL12 [ 11 ].

TAMs suppress the function of CD8 + tumor-infiltrating lymphocytes (TILs) and exert immunosuppressive effects by secreting interleukin-10 (IL-10) [ 12 ]. Clinically, increased intra-tumoral TAMs are associated with unfavorable outcomes across multiple solid tumor indications [ 13 ], indicating their significance as central mediators of immunosuppression in the TME. However, therapies that target TAMs reduction elicit poor anti-tumor responses. Therefore, novel strategies are required to precisely target TAMs and improve the efficacy and safety of TAMs-targeting therapies. The differentiation of TAMs to M2-like TAMs through complex cytokine connection inhibiting T-cell function and leading to tumor progression [ 14 ]. Current strategies against TAMs involve inhibiting their recruitment and differentiation, as well as re-educating TAMs to adopt an M1-like phenotype through activation or inhibition of checkpoint receptors. Among these, enhanced TAM-mediated phagocytosis plays a crucial role in tumor control by enhancing innate anti-tumor immunity and cross-activating T cell-mediated adaptive immune responses [ 15 ]. Therefore, identifying and targeting novel prophagocytic receptors will hold promise for advancing cancer immunotherapies against TAMs. We focused on a novel myeloid cell-expressed immunomodulator with prophagocytic activity, the triggering receptor expressed on myeloid cells 2 (TREM2). TREM2 is a transmembrane receptor belonging to the immunoglobulin superfamily, and has been recently identified in various tumors. TREM2 regulates phagocytosis, inflammation, metabolism, and cell survival by binding to the adaptor protein DNAX activation protein 12 (DAP12) [ 16 ]. The TREM2 receptor interacts with a variety of ligands, primarily anionic molecules, including bacterial products, DNA, and lipoproteins [ 17 ]. In addition, galectin-3 is identified as a potential endogenous ligand of TREM2 in Alzheimer’s disease (AD) [ 18 ]. Galectin-3 is a multifunctional protein of the beta-galactosidase-binding protein family [ 19 ]. Galectin-3 can promote macrophage differentiation to an M2-like phenotype and inhibit CD8 + T cell-mediated anti-tumor effects [ 20 ]. However, the phagocytic effects of TREM2 on tumor cells and the ligands that bind to TREM2 to exert specific phagocytic functions remain unclear.

TREM2 in TAMs fosters an immunosuppressive TME in different cancers [ 21 ]. Specifically, TREM2 in TAMs promotes tumor progression in colorectal carcinoma [ 22 ], ovarian carcinoma [ 23 ] and hepatocellular carcinoma (HCC) following transarterial chemoembolisation (TACE) [ 24 ] by remodeling the landscape of tumor-infiltrating myeloid cells and weakening the anti-tumor ability of CD8 + T cells. Additionally, TREM2 expression in cancer cells directly facilitates their survival, as observed in esophageal adenocarcinoma [ 25 ]. However, in gliomas, TREM2 inhibits tumor progression by enhancing the phagocytosis of tumor cells [ 26 ] and promoting MHC-II-related CD4 + T cell responses [ 27 ]. In summary, based on the different expression profiles and physiological functions of TREM2 and the heterogeneity of different cancer types, TREM2 exerts contrasting effects on tumor progression. In lung cancer, TREM2 + DCs exhibit immunosuppressive tumor-promoting properties [ 28 ], and TREM2 + mononuclear macrophages inhibit the accumulation and cytolytic activity of NK cells [ 29 ]. However, the upstream regulators of TREM2 in TAMs during the immune response to lung cancer need to be further elucidated.

Our findings indicated that abundant TREM2 + TAMs were recruited into the intratumor site through the CCL2-CCR2 chemotactic axis. In vitro, galectin-3 impairs TREM2-mediated phagocytosis and promotes the conversion of TREM2 + macrophages to pro-tumoral M2-like TAMs. Furthermore, liquid chromatography-mass spectrometry identified that soluble galectin-3 secreted by tumor cells was a potential ligand for TREM2. The galectin-3-TREM2 receptor signaling is responsible for TAMs infiltration and immunosuppressive. In vivo, combination therapy with TREM2 knockout and the galectin-3 inhibitor GB1107 substantially inhibited lung cancer progression. In summary, our results elucidated the galectin-3 is a potential ligand for TREM2 in TAMs. Notably, galectin-3-TREM2 may serve as a key immune checkpoint for tumor immune escape, providing a theoretical basis for providing potent targets against TAMs.

Materials and methods

Ethics statement and clinical samples.

Between August 2019 to December 2020, 123 lung cancer patients (lung cancer group) from the outpatient department of the Fifth Affiliated Hospital of Sun Yat-sen University (Zhuhai, China) were included in this study. Inclusion and exclusion criteria: The clinical diagnosis of lung cancer in all included patients was based on chest imaging followed by tissue biopsy according to the Clinical Diagnosis and Treatment Guidelines for Lung Cancer of the Chinese Society of Oncology (2018 edition). Those with tissue biopsy results of non-malignant tumors were excluded. In addition, 64 healthy volunteers without clinical diseases were recruited from the Health Management Examination Centre of the Fifth Affiliated Hospital of Sun Yat-sen University. The research was approved by the Medical Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University (approval number: L233-1), and informed consent was obtained from all participants. Supplementary Table 1 provides comprehensive details regarding the clinical characteristics of these individuals.

SPF-grade C57BL/6 wild-type (WT) mice (The Jackson Laboratory, RRID: IMSR_JAX: 000664) were procured from the Guangdong Provincial Laboratory Animal Centre. TREM2 KO mice (The Jackson Laboratory, RRID: IMSR_JAX: 027918), TREM2 f/f mice (mice carrying the loxP-flanked alleles of the TREM2 exon) (Nanjing GemPharmatech, RRID: N/A), Lyz2-cre mice (mice expressing Cre recombinase under the control of the Lyz2 promoter) (The Jackson Laboratory, RRID: IMSR_JAX: 032291), DAP12 KO mice (Nanjing GemPharmatech, RRID: N/A) and CD45.1 mice (The Jackson Laboratory, RRID: IMSR_JAX: 002014) were procured from GemPharmatech (Nanjing, China). All the mice were bred at the Laboratory Animal Centre of the Fifth Affiliated Hospital of Sun Yat-sen University. To generate myeloid-specific knockout mice for the TREM2 allele, breeding involved crossing TREM2 f/f mice with Lyz2-cre mice to achieve the lyz2-specific deletion of TREM2 ( TREM2 f/f -Lyz2-cre) mice. Mice were backcrossed to a C57BL/6 background for more than six generations. Genomic DNA extracted from tail biopsies was used for genotyping all mice via polymerase chain reaction (PCR). Male mice ranging from 6 to 8 weeks were employed for the experiments, with all animal procedures receiving approval from the Animal Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University (approval number: 00174). The tumor-bearing mice were assigned to each treatment group with 6–10 replications in randomization.

Cells and transfection

The human lung cancer cell line A549 (ATCC, RRID: CVCL_4V07) and H292 (ATCC, RRID: CVCL_0455), mouse fibroblast cell line L929 (ATCC, RRID: CVCL_AR58), mouse lung adenocarcinoma cell line LLC (ATCC, RRID: CVCL_4358), mouse mononuclear macrophage leukemia cell line RAW264.7 (ATCC, RRID: CVCL_C6 × 3), and human embryonic kidney epithelial cell line 293T (ATCC, RRID: CVCL_0063) were procured from ATCC. These cell lines were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Gibco, Grand Island, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS) (Hyclone, Logan, USA), 100 U/mL penicillin, and 100 µg/mL streptomycin sulfate (pen-strep) (Invitrogen, California, USA) at 37 °C in a humidified atmosphere containing 5% CO2. Cell line authenticity was verified by STR analysis. LLC-luc-mCherry cells (luciferase-carrying LLC cells) were established in our laboratory with lenti-virus and cultured in DMEM. Plasmids and siRNAs were transfected into 293T cells and LLC using Lipofectamine 2000 (Invitrogen, California, USA), followed by cell harvesting 36 h after transfection. Mouse bone marrow derived macrophages (BMDMs) were generated following protocols. Briefly, after rinsing with phosphate-buffered saline (PBS), the femur and tibia were cultured in cell culture dishes supplemented with 30% (v/v) L929 conditioned medium (CM) as a source of colony-stimulating factor 1 (CSF-1). Replace the medium on day 4, and cells were used for phagocytosis assay on day 7. Mouse peritoneal macrophages were obtained as following protocols. Briefly, flushing the peritoneum with 5 mL of cold PBS for three times to isolate the peritoneal macrophages. The peritoneal macrophages will attach to the petri dishes. After 4 h, the non-macrophage cells were removed by washing with warm PBS for three times. Afterward, the adherent macrophages were cultured in complete RPMI 1640 supplemented with 30% (v/v) L929 CM. Replace the medium on day 4, and cells were used for phagocytosis assay on day 7. Peripheral blood mononuclear cells (PBMCs) were isolated using density gradient centrifugation with Ficol-Biocoll solution (MD Pacific, Tianjin, China). The PBMCs were seeded into cell culture dishes with serum-free RPMI 1640 medium and then incubated at 37 °C for 2 h. After gentle washing, the adherent cells, mainly representing monocytes, were cultured in RPMI 1640 medium supplemented with 10% human serum (Gimini, Beijing, China). Replace the medium on day 4, and cells were used for phagocytosis assay on day 7.

In vitro phagocytosis assay

In a 24-well cell culture plate, 1 × 10 5 macrophages were seeded overnight. The macrophages were then treated with the CM of tumor cells for 24 h, followed by incubation in a serum-free medium for 2 h. Subsequently, the target cells underwent washing and were labelled with 5 µM of carboxyfluorescein succinimidyl ester (CFSE) (CST, Boston, USA) or 2 µM of pHrodo iFL Green STP (Thermo Fisher Scientific, Waltham, Massachusetts, USA), and then 2 × 10 5 CFSE-labelled target cells were introduced into the plate. After incubation at 37 °C for 2 h, the macrophages underwent extensive washing and were observed under an inverted microscope (OLYMPUS IX71, Tokyo, Japan). The phagocytic efficiency was determined by evaluating the number of macrophages that contained CFSE + target cells per 100 macrophages. In the flow cytometry-mediated phagocytosis experiments, at the end of the phagocytic phase, all cells in the wells were collected and washed, and stained with anti-mouse F4/80 (BioLegend Cat# 123,116, RRID: AB_893481) or anti-human CD68 (BioLegend Cat# 333,810, RRID: AB_2275735) antibodies at 4 °C for 30 min, and then analyzed by flow cytometry (Attune NxT, Thermo Fisher Scientific, Waltham, USA). After gating the F4/80 + or CD68 + macrophages, the phagocytic efficiency was evaluated by measuring the percentage of F4/80 + or CD68 + cells that contained CFSE-derived green fluorescence in FlowJo (BD Biosciences, RRID: SCR_008520).

Adoptive monocyte transfer assay

Adoptive monocyte transfer assay was performed as previously described [ 30 ]. Briefly, bone marrow from WT or TREM2 f/f -Lyz2-cre mice was harvested, and monocytes were purified using Sony Flow cytometer (Sony, Tokyo, Japan). A total of 2 × 10 6 monocytes were intravenously injected into the tail vein of CD45.1 recipient mice. After 24 h, a subcutaneous tumor transplantation assay was performed as previously described.

Orthotopic lung tumor implantation assay

WT or TREM2 f/f -Lyz2-cre mice aged 6–8 weeks were anesthetized with 2% isoflurane (RWD, Shenzhen, China). A total of 30 µL of PBS or matrigel (Corning, New York, USA) containing 1 × 10 6 luciferase-carrying LLC (LLC-luc) cells was injected into the left lung parenchyma from 1 cm above the lower rib line. The incisions were sealed using absorbable sutures. During and after the surgery, the mice were kept on a heating pad until they regained consciousness from anesthesia. On day 19, the mice were euthanized, and the lungs were collected for tumor counting and HE staining. In the survival studies ( n  = 10), each mouse was injected with 5 × 10 6 LLC-luc cells in the lung to obtain the desired survival time.

Co-immunoprecipitations (CO-IP) and immunoblots

For exogenous CO-IP, 293T cells were transfected with HA/Flag tagged plasmids, and the cell lysate was incubated with anti-HA agarose beads or anti-Flag M2 affinity beads overnight at 4 ℃. For endogenous CO-IP, tumor-infiltrating macrophages were lysed and incubated with anti-TREM2 (Cell Signaling Technology Cat# 91,068, RRID: AB_2721119) and protein A/G plus-agarose (Merck Millipore, Massachusetts, USA) overnight at 4 ℃. Immunoblots were performed as following protocols. Briefly, cell lysate was lysed in RIPA lysis (Ding guo, Guangzhou, China) for 30 min at 4 ℃, subsequently, it was centrifuged and boiled after the addition of loading buffer. After running and transferring the protein to PVDF membrane (Roche, Basel, Switzerland), the membrane underwent sequential incubation with primary and secondary antibodies, and then the PVDF membrane was observed using with LAS500 ultrasensitive chemiluminescence imager (ImageQuant, RRID: SCR_014246). The grey value of the protein band was analyzed using the ImageJ gel image analyses software, and the relative grey value was normalized to the grey value of β-actin. Image J (Fiji, RRID: SCR_002285) was used to analyze the grey value of each protein band, and the grey value of β-actin was used as a standard value.

Real-time fluorescence quantitative PCR (RT-qPCR)

After extracting total RNA using TRIZOL (Invitrogen, CA, USA), 1 µg of total RNA was reversely transcribed into cDNA. Then the mixture of cDNA, specific primers listed in Supplementary Tables 2 , and SYBR green (Applied Biosystems, CA, USA) were amplified using the CFX96 fluorescence quantitative PCR instrument (Bio Rad, CA, USA). β-actin was used to normalize the relative gene expression, and the ΔΔCt method was used to calculate the fold change in mRNA expression.

Liquid chromatography-mass spectrometry

Following the surgical procedure, human lung cancer tissues were finely minced using razor blades on ice. The harvested cells were lysed using RIPA lysis buffer and subjected to immunoprecipitation with either anti-TREM2 antibody (Cell Signaling Technology Cat# 91,068, RRID: AB_2721119) or control IgG along with protein A/G agarose beads (Merck Millipore, Massachusetts, USA) overnight at 4 °C. The unbound proteins were washed away, and the agarose beads bound to the antibodies and the corresponding proteins were collected for analyses. Then the liquid chromatography–mass spectrometry was performed on an Orbitrap Fusion Lumos (ThermoFisher Scientific, Waltham, USA).

Flow cytometry analyses involved the following antibodies: PE-anti-human/mouse TREM2 (R&D Systems Cat# FAB17291P, RRID: AB_884528) was from R&D Systems (Minnesota, USA). PE-anti-human/mouse Galectin-3 (BioLegend Cat# 125,405, RRID: AB_2136764), FITC-anti-mouse CD45.2 (BioLegend Cat# 109,806, RRID: AB_313443), FITC-anti-mouse CD11b (BioLegend Cat# 101,206; RRID: AB_312788), APC-anti-mouse F4/80 (BioLegend Cat# 123,116, RRID: AB_893481), PerCP-Cy5.5-anti-mouse CD3 (BioLegend Cat# 100,218, RRID: AB_1595492), APC/Cyanine7-anti-human CD45 (BioLegend Cat# 982,310, RRID: AB_2715773), APC anti-human CD68 (BioLegend Cat# 333,810, RRID: AB_2275735), PE-anti-mouse CD45.1 (BioLegend Cat# 110,707, RRID: AB_313496), APC/Cyanine7-anti-human/mouse Ly6G/Ly6C (Gr1) (BioLegend Cat# 108,423, RRID: AB_2137486), PE-anti-mouse Granzyme B (BioLegend Cat# 372,208, RRID: AB_2687032), APC/Cyanine7-anti-mouse CD8 (BioLegend Cat# 128,011, RRID: AB_1659242), PerCP-Cy5.5-anti mouse-Ly6C (BioLegend Cat# 109,806, RRID: AB_313443), FITC-anti-human CD4 (BioLegend Cat# 317,408, RRID: AB_571951), PerCP-Cy5.5-anti-mouse NK1.1 (BioLegend Cat# 108,728, RRID: AB_2132705), FITC-anti-mouse CD3 (BioLegend Cat# 100,204, RRID: AB_312661), PE/Cyanine7-anti-mouse CD206 (MMR) (BioLegend Cat# 141,720, RRID: AB_2562248), PE-anti-Nos2 (iNOS) (BioLegend Cat# 696,805, RRID: AB_2876745), APC-anti-mouse H-2K b (MHC I) (BioLegend Cat# 116,518, RRID: AB_10564404), PE-anti-mouse I-A/I-E (MHC II) (BioLegend Cat# 107,607, RRID: AB_313322), PE-anti-mouse CD86 (BioLegend Cat# 159,204, RRID: AB_2832568), APC-anti-mouse CD80 (BioLegend Cat# 104,714, RRID: AB_313135), and APC-anti-mouse CCR2 (BioLegend Cat# 150,627, RRID: AB_2810414), APC-anti-mouse Perforin (BioLegend Cat# 154,303, RRID: AB_2721462), FITC-anti-mouse CD4 (BioLegend Cat# 100,510, RRID: AB_312713), FITC-anti-human CD3 (BioLegend Cat# 300,406, RRID: AB_314060) were obtained from Biolegend (California, USA). Fixable Viability Dye eFluor™ 506 (Thermo Fisher Scientific Cat# 65-0866-14) was from Thermo Fisher Scientific (Waltham, USA).

Immunoprecipitations , immunoblots and Immunofluorescence involved the following antibodies: Anti-Flag-tag (DYKDDDK) (Cell Signaling Technology Cat# 14,793, RRID: AB_2572291), anti-Myc-tag (Cell Signaling Technology Cat# 2276 S, RRID: AB_331783), anti-HA-tag (Cell Signaling Technology Cat# 3724 S, RRID: AB_1549585), anti-Syk (Cell Signaling Technology Cat# 2712, RRID: AB_2197223), anti-Src (Cell Signaling Technology Cat# 2109, RRID: AB_2106059), anti-β-actin (Sigma-Aldrich Cat# A5316, RRID: AB_476743), anti-Galectin-3 (R and D Systems Cat# MAB1197, RRID: AB_2136769), anti-Phospho-Syk (Tyr525/526) (Cell Signaling Technology Cat# 2710, RRID: AB_2197222), anti-Phospho-Src (Tyr419) (Affinity Biosciences Cat# AF3162, RRID: AB_2834597), Anti-TREM2 (D8I4C) (Cell Signaling Technology Cat# 91,068, RRID: AB_2721119), Anti-TREM2 (R&D Systems Cat# AF1828, RRID: AB_2208689), and Anti-CD68 (EPR20545) (Abcam Cat# ab213363, RRID: AB_2801637).

Agonists and inhibitors

Tyrosine kinase inhibitor (Genistein) (absin, Shanghai, China), Syk inhibitor (R406) (Selleck Chemicals, Houston, USA), Src inhibitor (PP2) (Solarbio, Beijing, China), TREM2 Fc (R&D Systems, Minnesota, USA), GB1107 (Selective Galectin-3 inhibitor) (TargetMol, Boston, Massachusetts), Recombinant mouse Galectin-3 protein (rm Galectin-3) (R&D Systems, Minnesota, USA).

Human GAL3 (Galectin3) ELISA Kit was from Elabscience (Wuhan, China). Mouse CCL2/MCP1 ELISA Kit was from MEIMIAN (Jiangsu, China). Mouse Granzyme B ELISA Kit and Mouse Perforin ELISA kit were from Abcam (Cambridge, England).

CM collection

When the LLC, A549 or L929 cells reached approximately 50% confluence, the medium was changed to fresh complete medium. Two days later, the CM was centrifuged at 4 °C for 5 min, 10 min, and 20 min at 500 g, 2000 g, and 2000 g, respectively. The medium was then stored at -80 ℃.

Immunofluorescence (IF) and immunohistochemistry (IHC)

293T cells overexpressing TREM2-HA and Galectin-3-Flag were washed and fixed with 4% paraformaldehyde (BBI Life Sciences, Shanghai, China), then permeabilized and blocked with 3% Triton X-100- and 5% BSA-containing PBS for 1 h. Following overnight incubation with anti-HA (Cell Signaling Technology Cat# 3724 S, RRID: AB_1549585) and anti-Flag (Cell Signaling Technology Cat# 14,793, RRID: AB_2572291) primary antibodies, the cells were subsequently stained with Alexa Fluor 488-conjugated goat anti-mouse IgG (Invitrogen Cat# A-11,059, RRID: AB_2534106) and Alexa Fluor 594-conjugated goat anti-rabbit IgG (Abcam Cat# ab150080, RRID: AB_2650602) for 1 h. In the case of paraffin sections, anti-CD68 (EPR20545) (Abcam Cat# ab213363, RRID: AB_2801637) and anti-TREM2 (R&D Systems Cat# AF1828, RRID: AB_2208689) antibodies were applied. Following this, cell nuclei were counterstained with DAPI (Invitrogen, California, USA) for 5 min and observed using an LSM 780 laser-scanning confocal microscope (Carl Zeiss, Oberkochen, Germany). For immunohistochemistry experiments , after secondary antibodies incubation, the solution containing streptomyces complex antitoxin peroxidase was applied and followed by an 1 h-incubation at room temperature. Finally, the DAB staining (Boster, Wuhan, China) was performed, and visualized using the inverted fluorescence microscope. For actin polarization experiments , 2 × 10 5 RAW264.7 cells were seeded in the confocal dishes. The next day, cells were stimulated with LLC CM along with GB1107 (5 µM) for 24 h. After mixing macrophages and CFSE-labelled LLC at a ratio of 1:2 and following an incubation at 37 °C for 30 min, the cells then underwent fixation, washing, permeabilization, and blocking, similar to 293T cells as detailed above. Subsequently, an incubation with anti-β-actin antibody (AC-74) (Sigma-Aldrich Cat# A5316, RRID: AB_476743) was performed overnight at 4 °C, followed by an incubation with Alexa Fluor 488-conjugated goat anti-mouse IgG (Invitrogen Cat# A-11,059, RRID: AB_2534106) for 1 h. Then the cells were observed using an LSM 780 laser-scanning confocal microscope.

Hematoxylin-eosin (H&E) staining

Following euthanasia of the mice, the lungs were harvested and fixed overnight in 4% paraformaldehyde. Subsequently, the lungs were embedded in paraffin and sliced into 5 μm sections. H&E staining (Biosharp, Beijing, China) was conducted, and the samples were analyzed using an optical microscope (Olympus FV1000, Tokyo, Japan).

Intraperitoneal tumor clearance assay

WT or TREM2 f/f -Lyz2-cre mice received an intraperitoneal injection of 200 µL of LLC CM for 2 days, and then the mice were intraperitoneally injected with 5 × 10 6 CFSE-labelled LLC in 100 µL of PBS. After 24 h, the cells presented in the peritoneal cavity were harvested with 2% FBS-containing PBS, and the remaining CFSE + target cells were quantified using flow cytometry.

Subcutaneous tumor transplantation assay

WT, TREM2 f/f -Lyz2-cre, or DAP12 KO mice were subcutaneously injected with approximately 1 × 10 6 LLC into the right flank. The tumor volume was measured on alternate days using a caliper and calculated using the following formula: (length × width 2 )/2. Starting on day 5, the galectin-3 inhibitor, GB1107, was administered orally at a dose of 10 mg/kg daily as previously described [ 20 ]. The experiment was concluded before the tumors reached the allowable size limit of 1.5 cm in diameter. Following the termination of the experiment, the tumors were dissected, weighed, sectioned into small slices, filtered over a 40-µm filter, and washed with PBS. The tumor-infiltrating immune cells were then stained with relevant antibodies and detected using flow cytometry. Additionally, the tumor grinding supernatant was analyzed by ELISA.

Whole-body bioluminescence imaging

As previously described [ 31 ], the D-luciferin potassium salt (Abmole, shanghai, China) was reconstituted in PBS and intraperitoneally injected to tumor-bearing mice at a dosage of 150 mg/kg. After being anesthetized with 2% isoflurane, the mice underwent imaging with the Caliper IVIS Lumina III system (Perkin Elmer, Waltham, Massachusetts, USA) 15 min following the injection of D-luciferin potassium salt. The Region of Interest (ROI) was specified as a circle with a radius of 2 cm covering the lung area. Total flux (photos/s) and average radiance (p/s/cm 2 /sr) within the ROI were measured using the Caliper Life Sciences Living Image software.

Solid-phase binding assay

The experimental procedures of solid-binding assay were previously described [ 32 ]. Following overnight coating of the 96-well plate with TREM2-Fc or control IgG (2 µg/mL) (R&D Systems, Minneapolis, USA) in PBS overnight at 4 °C, the plate was washed and subsequently blocked with 3% BSA in PBS for at 37 °C 1 h. Next, the recombinant human galectin-3 protein (R&D Systems, Minneapolis, USA) was diluted and added to the plate at indicated concentrations in PBS containing 0.5% BSA, followed by an incubation at 37 °C for 1 h. Subsequently, the binding of galectin-3 protein was detected using biotinylated anti-galectin-3 antibody (Elabscience, Cat# E-AB-22,006) at 37 °C for 1 h. Then the plate underwent washing and subsequent incubation with avidin–horseradish peroxidase (Elabscience, Wuhan, China) at 37 °C for 30 min. Following another round of washing, the plate was exposed to the TMB substrate solution (Elabscience, Wuhan, China), and the absorbance was measured at 450 nm.

Statistical analyses

GraphPad Prism (San Diego, RRID: SCR_002798) was used for the statistical analyses, with data presented as mean ± SD. P  values were calculated using a two-tailed Student’s t-test and one-way or two-way analyses of variance (ANOVA), for calculating the comparison of one group and more than one group, respectively. For survival analyses, P  values were calculated using the log-rank (Mantel–Cox) test. A P  < 0.05 was considered statistically significant.

TREM2 + macrophages are increased and recruited in the intratumor site of lung cancer via the CCL2-CCR2 axis

TREM2 is identified as a key player in the regulation of tumor-associated myeloid cells [ 21 ], however, its specific role and immune regulatory mechanisms in lung cancer remains unclear. To evaluate the expression profile of TREM2 in lung cancer, we initially analyzed peripheral blood mononuclear cells (PBMCs) of 35 lung cancer patients and 30 healthy volunteers. Consistent with previous results, TREM2 expression was higher in monocytes of lung cancer [ 28 ] (Fig.  1 A and Supplementary Fig.  1A ). Further analyses between the TNM stage of lung cancer and TREM2 expression indicated increased TREM2 expression in the monocytes of patients with both early and advanced lung cancer. Moreover, there was a higher expression of TREM2 observed in patients with advanced lung cancer compared to those with early-stage disease (Fig.  1 B and Supplementary Fig.  1B ). In the TME of lung cancer, immunohistochemical staining revealed elevated expression of TREM2 in intratumor tissues, resembling tumor-infiltrating macrophages (Fig.  1 C). The correlation analyses between TREM2 and TILs in lung cancer performed using the TIMER 2.0 website (cistrome.org) [ 33 ], showed that TREM2 expression exhibited a strong correlation with mononuclear macrophages (Supplementary Fig.  1C ). Moreover, the immunofluorescence results showed a clear and abundant population of cells co-expressing CD68 and TREM2 in human lung cancer than that in healthy lung (Fig.  1 D). Similarly, in mouse lung cancer models, TREM2 expression was upregulated in both lung-infiltrating macrophages and splenic monocytes in tumor-bearing mice, which is consistent with observations in humans (Supplementary Fig.  1D ).

TREM2 +  macrophages are increased and recruited in the intratumor site of lung cancer via the CCL2-CCR2 axis. ( A ) Proportion of TREM2 expression in PBMCs from lung cancer patients ( n  = 35) and healthy donors ( n  = 30) were analyzed by flow cytometry. ( B ) Proportion of TREM2 expression in CD14 + monocytes from healthy donors ( n  = 64) and lung cancer patients ( n  = 123) with different TNM stages was analyzed by flow cytometry. ( C ) Immunohistochemical staining of TREM2 in adjacent normal lung and intratumor lung tissues ( n  = 5). Scale bars, 20 μm. ( D ) Immunofluorescence staining of TREM2 + TAM in adjacent normal lung and intratumor lung tissues ( n  = 5) by DAPI counterstaining. Scale bars, 20 μm. ( E ) Correlation analyses between TREM2 expression abundance and various monocyte chemokines of lung cancer in the TCGA database. ( F ) Main monocyte chemokine levels in lung cancer and the adjacent normal lung were determined by RT-qPCR. ( G ) Monocyte chemokine CCL2 levels in lung cancer and the adjacent normal lung were determined by ELISA. ( H-I ) CCR2 expression in peripheral blood monocytes ( H ) and tumor infiltrating macrophages ( I ) of lung cancer-bearing mice were determined by flow cytometry. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001. ns, no significance

TAMs are usually dependent on chemokines such as CCL2, CCL5 and CXCL12 for recruitment from peripheral monocytes/macrophages into the TME at the primary tumor site [ 11 ]. To investigate the relationship between TREM2 + macrophages and circulating monocytes, we analyzed the correlation between TREM2 and major monocyte chemokines through the TIMER2.0 website (cistrome.org) [ 33 ]. We found that TREM2 was strongly associated with CCL2, CCL3, CCL13, and CCL17 in lung cancer (Fig.  1 E). RT-qPCR analyses of CCL2, CCL3, CCL13, and CCL17 revealed that the transcription level of CCL2 in lung cancer was notably elevated compared to that in healthy lung (Fig.  1 F). Moreover, the protein level of CCL2 was elevated in lung cancer (Fig.  1 G). In the TME, monocytes/macrophages often express CCR2 and bind to CCL2 to form a chemotactic axis for recruitment as TAMs [ 34 ]. Our examination of CCR2 expression in monocytes/macrophages indicated a reduction in TREM2 knockout monocytes/macrophages (Fig.  1 H and I). Collectively, these findings confirmed that the CCL2-CCR2 chemotactic axis may contribute to the increase in TREM2 + macrophages in lung cancer.

Tumor educated TREM2 + macrophages have impaired phagocytosis activity and acquire an M2-like phenotype

For an exploration of the up-regulated TREM2 in macrophages, we analyzed the single cell RNA sequencing data of human lung adenocarcinoma [ 35 ], and identified TREM2-positive macrophages (TREM2 + M) and TREM2-negative macrophages (TREM2 − M) (Supplementary Fig.  2A-C ). Furthermore, GO-BP analyses revealed that signaling pathways associated with phagocytosis, antigen presentation and activation of T cells, which are closely related to phagocytosis [ 36 ], were enriched in TREM2 + macrophages (Supplementary Fig.  2D ), suggesting that the upregulation of TREM2 in mononuclear macrophages may be associated with altered phagocytosis.

To further explore whether TREM2 affects macrophage-mediated phagocytosis, bone marrow-derived macrophages from WT mice (WT BMDMs) and TREM2 f/f -Lyz2-Cre mice (TREM2 KO BMDMs) were isolated and cultured for phagocytosis experiments (Fig.  2 A). Immunofluorescence images showed that the macrophages were able to phagocytose LLC (Fig.  2 B), and phagocytosis rate of TREM2 KO BMDMs was attenuated (Fig.  2 C). In addition, to investigate phagocytosis in tumors, BMDMs were stimulated with 50% tumor cell-conditioned medium derived from LLC (LLC CM) in vitro. Surprisingly, LLC CM significantly reduced the phagocytic activity of WT BMDMs similar to that of TREM2 KO BMDMs (Fig.  2 C), indicating that the tumor cell-CM may have transformed the phenotype of the macrophages, resulting in a reduction in macrophage function, including phagocytosis. Similarly, a phagocytosis assay between mouse peritoneal macrophages or human monocyte-derived macrophages and tumor cells showed that TREM2 deficiency/blockade or tumor cell-CM treatment reduced the phagocytosis rate (Fig.  2 D and E). Furthermore, the results of in vivo intraperitoneal tumor cell clearance assay showed that TREM2 f/f -Lyz2-Cre mice exhibited reduced ability to clear tumor cells (Fig.  2 F). The pHrodo IFL green STP ester, a novel pH-responsive fluorescent dye for phagocytosis, was employed to validate the impact of TREM2 deficiency or LLC CM on the phagocytic activity of macrophages (Fig.  2 G and H). Immunosuppressive M2-like macrophages have reduced phagocytic capacity [ 37 ]. Therefore, tumor cell-CM may down-regulate phagocytic function by converting macrophages into an M2-like phenotype. The LLC CM-stimulated BMDMs were analyzed for macrophage differentiation-related genes and TREM2 deficiency notably decreased M2-like phenotypic markers ( CD206 and Arg1 ) expression (Fig.  2 J), and critically increased M1-like phenotypic markers ( Nos2 and TNFα ) expression (Fig.  2 K) in LLC CM-treated macrophages. In addition, LLC CM increased transcription level of Ccr2 , which was inhibited by TREM2 deficiency (Fig.  2 I). These results suggested that tumor cell-CM impairs macrophage-mediated phagocytosis and converts macrophages to an M2-like phenotype which depends on TREM2.

Tumor-educated TREM2 +  macrophage has impaired phagocytosis activity and acquires an M2-like phenotype. ( A ) Flowchart of phagocytosis experiment. ( B ) Demonstration of phagocytic morphology of macrophages on tumor cells. Macrophages, red; tumor cell, green. Scale bars, 5 μm. ( C ) Phagocytosis (red arrows) of tumor cells (green) by LLC CM-pretreated WT or TREM2 KO BMDMs with fluorescence microscopy. Scale bars, 50 μm. ( D ) Phagocytosis assay between WT or TREM2 KO peritoneal macrophages which were pretreated with LLC CM for 24 h and LLC were detected by flow cytometry. ( E ) Phagocytosis assay between A549 CM-pretreated human macrophages which were then blocked with rhTREM2 Fc (1 µg/mL) and LLC was detected by flow cytometry. ( F ) Intraperitoneal tumor cell clearance experiments between LLC CM-pretreated WT or TREM2 KO mice and LLC. ( G ) Flow chart of phagocytosis assay using pHrodo green dye. ( H ) Phagocytosis (red arrows) of pHrodo green labelled LLC (green) by LLC CM-pretreated WT or TREM2 KO BMDMs with fluorescence microscopy. Scale bars, 50 μm. ( I-K ) After 24 h of LLC CM treatment, the transcription levels of Ccr2 ( I ), M2-like macrophage markers ( CD206 , Arg1 ) ( J ) and M1-like macrophage markers ( Nos2 , TNFα ) ( K ) in WT or TREM2 KO BMDMs were detected by RT-qPCR. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001. ns, no significance

Tumor derived galectin-3 is a ligand for TREM2

To elucidate how tumor cell-CM modulates TREM2-mediated phagocytosis and phenotypic transformation of macrophages, immunoprecipitation and mass spectrometry analyses were performed (Fig.  3 A). Liquid chromatography-mass spectrometry identified 154 proteins that were more than 2-fold enriched in the anti-TREM2 group, and 7 of the 154 proteins were secreted proteins (Fig.  3 B and Supplementary Table 3 ). Among these secreted proteins, galectin-3 exhibits high expression levels in non-small cell lung cancer (NSCLC), and galectin-3 deficiency or pharmacological blockade significantly inhibits lung cancer progression [ 20 ]. In addition, galectin-3 serves as an intrinsic ligand for TREM2 in AD-associated microglia [ 18 ]. Immunohistochemical analyses demonstrated a high expression of galectin-3 in lung cancer (Fig.  3 C). ELISA results demonstrated a significant increase in the protein level of galectin-3 in lung cancer compared to normal lung (Fig.  3 D), indicating that galectin-3 may have a crucial regulatory function in the progression of lung cancer. To investigate the relationship between TREM2 and galectin-3, co-immunoprecipitation (CO-IP) experiments were performed. The exogenous CO-IP results showed that both human- and mouse-derived TREM2 and galectin-3 could bind to each other (Fig.  3 E and Supplementary Fig.  3A-C ). The interaction between TREM2 and galectin-3 was also confirmed in F4/80 + macrophages from patients with lung cancer using endogenous CO-IP experiments (Fig.  3 F). Moreover, immunofluorescence experiments showed obvious co-localization of TREM2 and galectin-3 in 293T cells (Fig.  3 G). To further explore the specific binding domains of TREM2 and galectin-3, exogenous CO-IP experiments were performed, which demonstrated that TREM2 full-length, TREM2-Ig (immunoglobulin-like) domain alone, and TREM2-lacking either the transmembrane (∆TM) or the cytoplasmic (∆Cyto) domain could all interact with galectin-3; however, this binding disappeared in the absence of the Ig domain (∆Ig) (Fig.  3 H and I). In addition, galectin-3 lacking either the N-terminal (∆NLD) or tandem repeat sequence (∆Repeats) domain could interact with TREM2; however, this binding disappeared in the absence of carbohydrate recognition domain (∆CRD) (Fig.  3 J), indicating that Galectin-3 combined with TREM2 via its carbohydrate recognition domain (CRD). To validate the interaction between galectin-3 and TREM2, a solid-phase binding assay was conducted, which demonstrated a concentration-dependent binding of galectin-3 to TREM2-Fc (Fig.  3 K). These findings suggest that galectin-3 is a ligand for TREM2 by interacting with the galectin-3-CRD and TREM2-Ig domains.

Tumor derived galectin-3 is a ligand for TREM2. ( A ) Illustration of human lung cancer tissue protein precipitated by anti-TREM2 or IgG antibody ( n  = 3), and peptides enriched in each complex were identified by mass spectrometry. ( B ) Venn diagram and tables showing secreted proteins concentrated in the TREM2 enriched complex. ( C ) Immunohistochemical staining of galectin-3 in adjacent normal lung and intratumor areas of lung tissues ( n  = 5). Scale bars, 20 μm. ( D ) Galactin-3 levels in lung cancer or normal lung lavage were determined by ELISA. ( E ) 293T cells were transfected with pcDNA3.1-vector/pcDNA3.1-hTREM2-HA/pcDNA3.1-hGalectin-3-Flag plasmids as indicated. Anti-HA antibody was employed for exogenous CO-IP experiments. ( F ) F4/80 + macrophages were sorted from human lung cancer tissue. Anti-TREM2 antibody was employed for endogenous CO-IP experiment. ( G ) 293T cells were transfected with pcDNA3.1-TREM2-HA and pcDNA3.1-Galectin-3-Flag plasmids. The co-localization between TREM2 and Galectin-3 was examined using confocal microscopy. Scale bars, 5 μm. ( H ) 293T cells were transfected with pcDNA3.1-TREM2-HA/pcDNA3.1-TREM2-ΔIg-HA/pcDNA3.1-TREM2-ΔTm-HA/pcDNA3.1-TREM2-ΔCyto-HA/pcDNA3.1-Galectin-3-Flag/pcDNA3.1-vector plasmids as indicated. Anti-Flag antibody was employed for exogenous CO-IP experiments. ( I ) 293T cells were transfected with pcDNA3.1-vector/pcDNA3.1-TREM2-Ig-HA/pcDNA3.1-TREM2- HA/pcDNA3.1-Galectin-3-Flag plasmids as shown. Anti-Flag antibody was employed for exogenous CO-IP experiments. ( J ) 293T cells were transfected with pcDNA3.1-vector/pcDNA3.1-TREM2-HA/pcDNA3.1-Galectin-3-ΔNH2-Flag/pcDNA3.1-Galectin-3-ΔCRD-Flag/pcDNA3.1-Galectin-3- ΔRepeats-Flag plasmids as indicated. Anti-HA antibody was employed for exogenous CO-IP experiments. ( K ) Galectin-3 protein bound to TREM2 in the plate was determined using anti-Galectin-3 antibody. Data represent mean ± SD from three experiments. **, P  < 0.01; ***, P  < 0.001

Galectin-3 inhibits the TREM2/DAP12 receptor complex to suppress the Src-Syk signaling pathway and alter macrophages to an M2-like phenotype

TREM2 signaling in myeloid cells is mainly dependent on the adaptor DAP12, which mediates intracellular signaling via the protein tyrosine kinase Syk [ 38 ]. Although the role of the TREM2-DAP12 receptor complex in lung cancer progression is unknown, our findings elucidated that TREM2 or DAP12 deficiency inhibited lung cancer progression in vivo (Supplementary Fig.  4A and 4B ), suggesting that TREM2 affects lung cancer progression through the adaptor molecule, DAP12. Moreover, the relationship between galectin-3 and the TREM2-DAP12 signaling remains unclear. Exogenous CO-IP experiments confirmed the TREM2-DAP12 interaction (Fig.  4 A); however, there was no interaction between galectin-3 and DAP12 (Fig.  4 B). Subsequently, CO-IP experiments among TREM2-HA, galectin3-Flag, and DAP12-Myc were performed. The results revealed the detectability of any two proteins in precipitates enriched with anti-HA, anti-Flag, or anti-Myc antibodies (Fig.  4 C and E), indicating that these three proteins can bind to form a complex that regulates downstream signaling pathways. TREM2 promotes phagocytosis in bacteria and apoptotic neurons through the DAP12-Src-Syk signaling pathway [ 38 ]. However, whether macrophages phagocytose tumor cells through the DAP12-Src-Syk signaling pathway is unknown. By examining the phosphorylation levels of Src and Syk in the galectin-3 inhibitor GB1107, or LPS (as a positive control) [ 39 ] treated-BMDMs which were pre-stimulated with LLC CM, we found that GB1107 activated the phosphorylation levels of Src and Syk over time in WT BMDMs (Fig.  4 F and G). However, the activation of p-Src and p-Syk phosphorylation by GB1107 was significantly reduced in TREM2 KO BMDMs (Fig.  4 H and I). Moreover, treatment with recombinant mouse galectin-3 protein (rm galectin-3) reduced the activation levels of p-Src and p-Syk phosphorylation in WT BMDMs, whereas no significant effect was observed in TREM2 KO BMDMs (Fig.  4 J and K), suggesting that galectin-3 inhibited the Src-Syk signaling pathway downstream of TREM2.

Galectin-3 inhibits TREM2/DAP12 receptor complex to suppress Src/Syk signaling pathway and altered macrophage to an M2-like phenotype. (A , B ) 293T cells were transfected with plasmids as shown, and anti-HA ( B ) or anti-Flag ( B ) antibodies were employed for exogenous CO-IP experiments. ( C-E ) 293T cells were transfected with plasmids as shown and anti-HA ( C ), anti-Flag ( D ), or anti-Myc ( E ) antibodies were employed for exogenous CO-IP experiments, respectively. (F , G ) After 24 h of LLC CM treatment with the addition of GB1107 (5 µM), and 2 h of stimulation with LPS (1 ng/mL), the phosphorylation levels of Src and Syk in indicated time point were analyzed by western blot ( F ). The gray values of p-Syk and p-Src protein bands were analyzed by Image J software, and the relative gray values were standardized to the gray values of Syk and Src ( G ). (H , I ) After 24 h of LLC CM treatment with the addition of GB1107 (5 µM), and 2 h of stimulation with LPS (1 ng/mL), the phosphorylation levels of Src and Syk in WT or TREM2 KO BMDMs were analyzed by western blot ( H ). The gray values of p-Syk and p-Src protein bands were analyzed by Image J image analyses software, and the relative gray values were standardized to the gray values of Syk and Src ( I ). (J , K ) After 24 h of LLC CM treatment with the addition of rm galectin-3 (200 ng/ml), and 2 h of stimulation with LPS (1 ng/mL), the phosphorylation levels of Src and Syk in WT or TREM2 KO BMDMs were analyzed by western blot ( J ). The gray values of p-Syk and p-Src protein bands were analyzed by Image J image analyses software, and the relative gray values were standardized to the gray values of Syk and Src ( K ). ( L ) Phagocytosis assay between WT or TREM2 KO BMDMs which were pretreated with LLC CM supplemented with GB1107 (5 µM) for 24 h and LLC were detected by flow cytometry. ( M ) Following a 24 h-treatment with LLC CM supplemented with GB1107 (5 µM), the F-actin polarization of RAW264.7 cells blocked with anti-TREM2 antibody was observed by confocal microscopy. Scale bars, 5 μm. Quantitative statistics of F-actin polarization were analyzed by Image J image analyses software. ( N-P ) After 24 h of LLC CM which was supplemented with GB1107 (5 µM) treatment, the transcription levels of Ccr2 ( N ), M2-like macrophage markers ( CD206 , Arg1 ) ( O ) and M1-like macrophage markers ( Nos2 , TNFα ) ( P ) in WT or TREM2 KO BMDMs were detected by RT-qPCR assay. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001. ns, no significance

Galectin-3 promotes tumor growth by inhibiting phagocytosis, macrophage re-polarization and T-cell immune responses [ 40 ]. However, whether galectin-3 affects TREM2-mediated phagocytosis and macrophage repolarization remains unclear. The findings from the phagocytosis assay indicated that the galectin-3 inhibitor GB1107 enhanced the phagocytosis of LLC CM-stimulated WT BMDMs, but had no significant effect on TREM2 KO BMDMs (Fig.  4 L). Phagocytosis by macrophages ultimately leads to alterations in cytoskeletal proteins, known as actin polarization [ 41 ]. Further actin polarization experiments showed that GB1107 induced significant actin polarization in RAW264.7 cells, but blockade of TREM2 markedly attenuated actin polarization (Fig.  4 M), suggesting that galectin-3 inhibition promotes TREM2-mediated actin polarization. Moreover, GB1107 treatment or TREM2 deficiency significantly inhibited the expression of Ccr2 (Fig.  4 N) and M2-like phenotypic markers ( CD206 and Arg1 ) (Fig.  4 O), but markedly promoted M1-like phenotypic markers (Nos2 and TNFα ) expression (Fig.  4 P) in both LLC CM-stimulated WT and TREM2 KO BMDMs. These results indicate that galectin-3 in tumor cell-CM inhibits TREM2-mediated phagocytosis and could synergizes with TREM2 to polarize macrophages to an M2-like phenotype.

TREM2 promotes lung cancer progression via increasing M2-like macrophages and suppressing T/NK cell-mediated anti-tumor immune responses in vivo

To explore the regulatory function of TREM2 on mononuclear macrophages in tumor progression, we established a monocyte co-injection model in CD45.1 mice [ 30 ] (Fig.  5 A). The proportion of tumor-infiltrating CD45.2 + macrophages was notably increased in the group injected with WT monocytes compared to the group injected with TREM2 KO monocytes (Fig.  5 B), suggesting that TREM2 promotes the recruitment of circulating monocytes to the TME. In addition, TREM2 KO monocyte-injected mice had smaller tumor volumes and weights and slower tumor growth than those of WT monocyte-injected mice (Fig.  5 C and E), suggesting that TREM2 loss-of-function myeloid cells inhibit lung cancer progression. In addition, tumor-infiltrating immune cells analyzed by flow cytometry indicated that the proportion of M2-like macrophages was reduced in mice receiving TREM2 KO monocytes (Fig.  5 F), whereas the proportions of CD8 + T and NK cells were elevated (Fig.  6 A). Furthermore, TREM2 induced the M2-like TAMs in vivo by increasing the expression of CD206 (Fig.  5 G), while decreasing the expression of Nos2 (Fig.  5 H). Moreover, TREM2 inhibited macrophage-expressed antigen-presenting molecules MHC-I/II (Fig.  5 K and L) and the coactivators CD80/CD86 (Fig.  5 I and J), suggesting that TREM2 also affects T cell-mediated anti-tumor immune response. Therefore, we then analyzed the function of tumor-infiltrating T cells and found that TREM2 inhibited T cell-mediated secretion of anti-tumor molecules, including granzyme B and perforin (Fig.  6 C and D). Moreover, TREM2 inhibited NK cell-mediated secretion of anti-tumor molecules, including granzyme B and perforin (Fig.  6 E and F), which was consistent with the previous findings that TREM2 + mononuclear macrophages suppressed NK cell accumulation and cytolytic activity in lung cancer [ 29 ]. Similarly, ELISA results showed consistently increased granzyme B and perforin in the tumor-grinding fluid of mice injected with TREM2 KO monocytes (Fig.  6 B), indicating that TREM2 promotes tumor growth in vivo by increasing the number of M2-TAMs and inhibiting the anti-tumor function of CD8 + T and NK cells.

TREM2 promotes lung cancer progression and promotes M2-like immunosuppressive macrophage infiltration in the TME. ( A ) Diagram illustrating the establishment of a subcutaneous lung cancer model in CD45.1 mice injected with CD45.2 WT or TREM2 KO monocytes ( n  = 5). ( B ) Representative flow plots and quantification of CD45.2 + macrophages in tumor-infiltrating macrophages. ( C ) Tumor size of each group. ( D ) tumor weight of each group. ( E ) Tumor growth rate of each group. ( F ) Proportion of tumor-infiltrating macrophages was detected by flow cytometry. ( G-L ) Representative flow plots and quantification of CD206 ( G ), Nos2 ( H ), CD80 ( I ), CD86 ( J ), MHC I ( K ), and MHC II ( L ) in tumor-infiltrating macrophages of each group. The data represent the mean fluorescence intensity (MFI) of the specified molecule. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001. ns, no significance

TREM2 impaired the infiltration and functionality of anti-tumor CD8 +  T and NK cells in vivo. ( A ) In the adoptive monocyte transfer model, the proportion of anti-tumor CD8 + T and NK cells was detected by flow cytometry. ( B ) The concentrations of perforin and granzyme B in the tumor tissue grinding supernatant were detected by ELISA. ( C-D ) Representative flow plots and quantification of granzyme B ( C ) and perforin ( D ) producing CD8 + T cells in the TME. ( E-F ) Representative flow plots and quantification of granzyme B ( E ) and perforin ( F ) producing NK cells in the TME. Data represent mean ± SD from three experiments. **, P  < 0.01; ***, P  < 0.001. ns, no significance

Combination therapy with TREM2 knockout and the galectin-3 inhibitor GB1107 significantly inhibits lung cancer progression

To further explore whether galactin-3-TREM2 interaction affects the progression of lung cancer, we established a subcutaneous transplantation tumor model of lung cancer in WT and TREM2 f/f -Lyz2-Cre mice and administered GB1107 treatment daily (Fig.  7 A). The results showed that TREM2 f/f -Lyz2-Cre mice exhibited reduced tumor volumes and weights, slower tumor growth, and the combination therapy with the galectin-3 inhibitor GB1107 significantly decreased the tumor burden (Fig.  7 B and D). To further explore the effect of the galectin3-TREM2 interaction on lung cancer progression under physiological conditions, we constructed an orthotopic lung cancer model using luciferase-carrying LLC cells (LLC-luc) (Fig.  7 E). The results demonstrated that TREM2 deficiency inhibited lung tumor formation and progression, which were further inhibited by GB1107 treatment (Fig.  7 F and G). Furthermore, dynamic observations using IVIS fluorescence imaging showed that TREM2 deficiency inhibited lung tumor growth, which was markedly suppressed by GB1107 treatment (Fig.  7 H). Moreover, survival analyses revealed that TREM2 deficiency prolonged the survival time of tumor-bearing mice, and combination treatment with GB1107 considerably improved their lifespan (Fig.  7 I). These results indicated that TREM2 deficiency inhibits lung cancer progression, which can be further inhibited by galectin-3 inhibition.

Combination therapy of the galectin-3 inhibitor GB1107 and TREM2 deficiency significantly inhibit lung cancer progression and reduced the immunosuppressive M2-like TAMs infiltration. ( A ) Schematic representation of an immunocompetent subcutaneous lung cancer model using the murine lung cancer cell line LLC ( n  = 5). Mice were orally administered GB1107 (10 mg/kg) daily beginning on day 5 until the mice were sacrificed on day 19. ( B ) Tumor size of each group. ( C ) Tumor weight of each group. ( D ) Tumor growth rate of each group. ( E ) Schematic illustration of an immunocompetent orthotopic lung cancer model using LLC-luc ( n  = 3). Mice were orally administered GB1107 (10 mg/kg) daily beginning on day 5 until the mice were sacrificed on day 19. ( F ) Representative images of tumorigenesis in each group. ( G ) Representative HE staining of lung tissues from each group and statistical analyses of tumor nodules. ( H ) In vivo IVIS images of orthotopic lung cancer in each group at corresponding time points and results of quantitative fluorescence analyses. ( I ) Survival rate of orthotopic lung cancer in each group ( n  = 8). ( J ) In the orthotopic lung cancer model, the percentage of tumor-infiltrating macrophages was analyzed using flow cytometry. ( K-L ) Representative flow plots ( K ) and quantification ( L ) of CD206, Nos2, CD80, CD86, MHC I and MHC II in tumor-infiltrated macrophages in each group. The data is displayed as MFI. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001

Flow cytometric analyses of tumor-infiltrating immune cells showed that the proportion of macrophages was decreased in TREM2 f/f -Lyz2-Cre mice; however, the percentages of CD8 + T and NK cells were increased compared to those in WT mice, and were further decreased or increased in combination with GB1107 treatment, respectively (Figs.  7 J and 8 A). In addition, dual inhibition of TREM2 and galectin3 significantly increased the M2-like TAMs in vivo by promoting CD206 expression while inhibiting Nos2 expression (Fig.  7 K and L). Furthermore, the dual blockade of TREM2 and galectin3 notably increased the expression of the coactivators CD80/86 (Fig.  7 K and L) and antigen-presenting molecules MHC I/II (Fig.  7 K and L) on TAMs. Moreover, tumor-infiltrating CD8 + T cells and NK cells in TREM2-deficient mice were more capable of secreting perforin and granzyme B, and GB1107 treatment further enhanced it (Fig.  8 B and E). Similarly, ELISA results showed increased granzyme B and perforin in the tumor-grinding fluid of TREM2-deficient mice, which were further enhanced by GB1107 treatment (Fig.  8 F). Collectively, these results suggest that dual blockade of galectin3 and TREM2 inhibit lung tumor growth in vivo by decreasing immunosuppressive macrophages and facilitating the anti-tumor function of CD8 + T and NK cells.

Combination of the Galectin-3 inhibitor and TREM2 deficiency enhanced the infiltration and functionality of anti-tumor CD8 +  T and NK cells. ( A ) In the orthotopic lung cancer models, the percentage of anti-tumor CD8 + T and NK cells were analyzed using flow cytometry. ( B-C ) Representative flow plots and quantification of granzyme B ( B ) and perforin ( C ) producing CD8 + T cells in TME. ( D-E ) Representative flow plots and quantification of granzyme B ( D ) and perforin ( E ) producing NK cells in TME. ( F ) The concentrations of perforin and granzyme B in the tumor tissue grinding supernatant were detected by ELISA. ( G ) A propose model to illustrate the mechanism of galetin3-TREM2 axis in promoting lung cancer progression. Data represent mean ± SD from three experiments. *, P  < 0.05; **, P  < 0.01; ***, P  < 0.001

High infiltration of TAMs is a characteristic feature of the TME, not only in lung cancer but also in other cancers [ 42 ]. Peripheral circulating monocytes are usually recruited to the TME through various chemokine networks, such as CCL2, CCL7, and CCL13 [ 11 ]. Patrolling monocytes can be protective in the early stages of cancer. However, when bone marrow-derived monocytes gradually become the predominant subtype of TAMs, they often lead to the progression of primary and metastatic tumors [ 11 ]. Hendrikx T et al. found that bone marrow-derived monocytes recruited during steatohepatitis acquired high TREM2 expression in the circulation [ 43 ], suggesting that TREM2 may affect the circulating monocytes recruitment to the disease focus. In addition, increased TREM2 expression in TAMs promotes tumor progression in colorectal cancer [ 44 ], ovarian cancer [ 23 ], and TACE [ 24 ]. Our findings revealed a high TREM2 expression in lung cancer macrophages, and abundant TREM2 + macrophages are enriched in the intratumor site in the presence of the CCL2-CCR2 chemotactic axis. Importantly, TREM2 deficiency inhibits lung cancer progression in vivo by reducing the population of M2-like TAMs and enhancing both the quantity and functionality of CD8 + T and NK cells. As far as we know, this study represents the first investigation to document that TREM2 affects TAMs infiltration by regulating the chemotactic axis, paving the way for new therapeutic avenues to inhibit cancer development.

TAMs are highly plastic and heterogeneous cell populations in the TME that make up to 50% of certain solid tumors [ 45 ]. The significance of TAMs in tumor immunity has garnered notable interest in recent years. TAMs acquire a polarized M2-like phenotype, which involves in subverting adaptive immunity and promoting tumor growth and progression. However, TAMs can mediate anti-tumor effects (M1-like phenotype) through immunosurveillance, including phagocytosis and innate immune sensing. Current TAMs-targeting therapies include (1) alteration of the constitution of TAMs, (2) immunosuppressive TAMs blockade, (3) reprogramming of M2-TAMs, and (4) novel targets, such as TREM2, Siglec-15, and MARCO [ 46 ]. Among them, notable advancements have been made in reprogramming pro-tumor M2-like TAMs, which have impaired phagocytic activity, into anti-tumor M1-like TAMs with robust phagocytic activity [ 47 ]. As a surface receptor, TREM2 plays a significant part in macrophage-mediated tumor immune responses, including phenotypic switching and phagocytosis [ 48 ]. TREM2 promotes phagocytosis of a series of damaged substances in the organism and foreign objects in a non-specific manner [ 16 ]. In addition, the absence of TREM2 hampers the capacity of myeloid cells within glioma to engulf tumor cells [ 27 ]. Our findings revealed that TREM2 promotes macrophage-mediated phagocytosis of tumor cells but is inhibited upon treatment with LLC CM. Furthermore, LLC CM management promotes the conversion of TREM2 + macrophages to a tumor-promoting M2-like phenotype, suggesting that special molecules in tumor cell-derived CM could regulate the physiological function of TREM2, such as impairing TREM2-mediated phagocytosis.

TREM2 exerts multiple functions by binding to a range of ligands, primarily anionic molecules, including bacterial products, lipids (APOE, and CLU/APOJ), and anionic molecules [ 49 ], but the identification of highly specific TREM2 ligands is largely unknown. Krasemann S et al. reported that the TREM2-APOE pathway serves as the primary regulator of phenotypic alterations in microglia during neurodegenerative diseases, making it a potential target for reinstating microglial homeostasis [ 49 ]. Moreover, the co-localization of TREM2 and galectin-3 has been identified in AD-associated microglia [ 18 ], suggesting that galectin-3 may be a potential endogenous TREM2 ligand which requires further validation. The results of liquid chromatography-mass spectrometry revealed that soluble galectin3 is a potential ligand of TREM2 in TAMs. Exogenous/endogenous CO-IP experiments and immunofluorescence experiments demonstrated the interaction and co-localization of TREM2 and galectin-3. A solid phase binding assay further confirmed their direct binding. TREM2 consists of a short extracellular structural domain, a transmembrane helix, and a short cytoplasmic tail that lacks signal transduction or transportation motifs [ 16 ]. Galectin-3 consists of a short NH2-terminal structural domain, a repetitive collagen alpha-like sequence, and a single CRD consisting of 140 amino acids. Furthermore, CO-IP results demonstrated that the TREM2-galectin-3 interaction was dependent on the TREM2-Ig and galectin-3-CRD domains. These data elucidate that galectin-3 is a ligand for TREM2 in TAMs.

Galectin-3 is a multifunctional protein of the beta-galactosidase-binding protein family [ 19 ]. Galectin-3 plays crucial roles in cancer, including promotion of tumor cell survival, angiogenesis, tumor transformation, tumor progression and metastasis [ 50 ]. The unique structure of galectin-3 allows it to interact with an excess of ligands, such as laminin and fibronectin in a carbohydrate-dependent or independent manner [ 51 ]. Galectin-3 has a high expression level in NSCLC patients [ 52 ]. Galectin-3 can promote macrophage differentiation to an M2-like phenotype and inhibit CD8 + T cell-mediated anti-tumor effects; therefore, galectin-3 deficiency or pharmacological blockade can significantly inhibit lung cancer progression [ 20 ]. Similarly, we found that galectin-3 expression was notably elevated in both the TME of lung adenocarcinoma patients and in the supernatant of LLC. Functionally, the galectin-3 inhibitor GB1107 alleviated the inhibitory effect of tumor cell-CM on TREM2-mediated phagocytosis. Moreover, the galectin-3 inhibitor GB1107 reversed the LLC CM-induced and TREM2-dependent M2-like macrophages transformation, suggesting that the galectin-3-TREM2 interaction may affect the downstream signaling pathway of TREM2, thereby affecting the function and phenotype of macrophages.

TREM2 signal transduction in macrophages primarily depends on the cytoplasmic adapter protein DAP12. DAP12 mediates the functions of TREM2, such as phagocytosis, by recruiting and phosphorylating downstream Src and Syk tyrosine kinases [ 16 ]. Herein, we found that TREM2-mediated phagocytosis of tumor cells was dependent on the DAP12-Src-Syk signaling pathway, which was inhibited by galectin-3 in LLC CM. Therefore, the galectin-3-TREM2 interaction inhibits the phosphorylation of Src and Syk downstream of TREM2 signaling and is involved in suppressing phagocytosis and promoting the M2-like phenotype switching of macrophages. The exact downstream signaling pathways and mechanisms by which TREM2 downstream molecules Src and Syk induce macrophage phenotypic transformation and phagocytosis remain unclear. Notably, combination therapy with TREM2 knockout and the galectin-3 inhibitor GB1107 substantially inhibited lung cancer progression in vivo by decreasing tumor-infiltrating M2-like macrophages and increasing antitumor CD8 + T and NK cells. Moreover, combination therapy upregulates antigen-presenting factors, such as MHC I/II and the coactivators CD80/86 in macrophages, promoting adaptive anti-tumor immune responses.

In summary, our findings elucidate that elevated TREM2 expression is correlated with increased infiltration of immunosuppressive M2-like TAMs and suppression of intratumoral CD8 + T and NK cell responses in lung cancer. TREM2 + TAMs are recruited to the intratumor area through the CCL2-CCR2 chemotactic axis from peripheral TREM2 + monocytes. Tumor-educated TREM2 + macrophages are converted into M2-like TAMs by interacting with the novel ligand galectin-3 enriched in the TME. Notably, TREM2 knockout combined with the galectin-3 inhibitor GB1107 substantially inhibited the immunosuppressive effect of M2-TAMs and enhanced T/NK cell-mediated anti-tumor effects, improving the efficacy of lung cancer therapy (Fig.  8 G). Overall, we provide molecular and cellular insights into the manipulation of tumor progression by TREM2 + TAMs and propose a valuable approach for remodeling the anti-tumor TME, emphasizing that TREM2 blockade in combination with galectin-3 inhibitors may present a practical strategy for the clinical management of lung cancer or other cancer types.

Data availability

Data confirming the results of this study are presented in the manuscript and are available from the corresponding author upon reasonable request. The single-cell RNA sequencing data included in this study were obtained from the Gene Expression Omnibus (GEO) (NIH, RRID: SCR_005012) database of the National Centre for Biotechnology Information (NCBI), with the accession number GSE123904. Source data are provided with this paper.

Abbreviations

Tumor-associated macrophages

Triggering receptor expressed on myeloid cells 2

Tumor microenvironment

Non-small cell lung cancer

DNAX activation protein 12

Conditioned medium

Gene Expression Omnibus

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Acknowledgements

We acknowledge all members of the laboratories of Prof. Guanmin Jiang and Prof. Xi Huang for the scientific discussions. We acknowledge all the patients that participated in the study protocols. We also thank all the members of the animal core facility for technical assistance. Illustrations were created with BioRender.com.

This work was supported by grants from the National Natural Science Foundation of China (82072062, 82072365, 82270016, 82272388), Natural Science Foundation of Guangdong Province (2023A1515030065, 2024A1515012898), the open research funds from the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital (202301-102).

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Qiaohua Wang and Yongjian Wu contributed equally to this work.

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Center for Infection and Immunity, Guangdong Provincial Engineering Research Center of Molecular Imaging, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China

Qiaohua Wang, Yongjian Wu & Xi Huang

Department of Clinical Laboratory, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China

Qiaohua Wang & Guanmin Jiang

Guangdong-Hong Kong-Macao University Joint Laboratory of Interventional Medicine, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China

Yongjian Wu & Xi Huang

Zhuhai Engineering Research Center of Infection and Immunity, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China

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Contributions

Q.W. and Y.W. performed the experiments; Q.W., Y.W., G.J. and X.H. designed the experiments; Q.W. and Y.W. were involved in methodology design; Q.W. and Y.W. analyzed the data; Q.W., Y.W., G.J. and X.H. reviewed and revised the draft. All authors read the final version of the manuscript and approved the final manuscript.

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Correspondence to Guanmin Jiang or Xi Huang .

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Wang, Q., Wu, Y., Jiang, G. et al. Galectin-3 induces pathogenic immunosuppressive macrophages through interaction with TREM2 in lung cancer. J Exp Clin Cancer Res 43 , 224 (2024). https://doi.org/10.1186/s13046-024-03124-6

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Age-dependent changes in phagocytic activity: in vivo response of mouse pulmonary antigen presenting cells to direct lung delivery of charged PEGDA nanoparticles

• Emma R. Sudduth   ORCID: orcid.org/0000-0002-8141-6416 1 ,
• Aida López Ruiz   ORCID: orcid.org/0000-0003-1936-611X 1 ,
• Michael Trautmann-Rodriguez   ORCID: orcid.org/0000-0002-2965-3537 1 &
• Catherine A. Fromen   ORCID: orcid.org/0000-0002-7528-0997 1  

Journal of Nanobiotechnology volume  22 , Article number:  476 ( 2024 ) Cite this article

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Current needle-based vaccination for respiratory viruses is ineffective at producing sufficient, long-lasting local immunity in the elderly. Direct pulmonary delivery to the resident local pulmonary immune cells can create long-term mucosal responses. However, criteria for drug vehicle design rules that can overcome age-specific changes in immune cell functions have yet to be established.

Here, in vivo charge-based nanoparticle (NP) uptake was compared in mice of two age groups (2- and 16-months) within the four notable pulmonary antigen presenting cell (APC) populations: alveolar macrophages (AM), interstitial macrophages (IM), CD103 + dendritic cells (DCs), and CD11b + DCs. Both macrophage populations exhibited preferential uptake of anionic nanoparticles but showed inverse rates of phagocytosis between the AM and IM populations across age. DC populations demonstrated preferential uptake of cationic nanoparticles, which remarkably did not significantly change in the aged group. Further characterization of cell phenotypes post-NP internalization demonstrated unique surface marker expression and activation levels for each APC population, showcasing heightened DC inflammatory response to NP delivery in the aged group.

The age of mice demonstrated significant preferences in the charge-based NP uptake in APCs that differed greatly between macrophages and DCs. Carefully balance of the targeting and activation of specific types of pulmonary APCs will be critical to produce efficient, age-based vaccines for the growing elderly population.

Graphical Abstract

The elderly population is extremely susceptible to severe respiratory infection related to altered immune cell phenotypes in the aged lung [ 1 , 2 ]. Over time, older individuals demonstrate a reduction in cell-based and other clearance mechanisms in the pulmonary microenvironment, leading to compounding effects influencing immune system regulation [ 2 , 3 ]. This dysfunction in immune homeostasis leads to a chronic low-grade pro-inflammatory microenvironment in the lung that remains untreated by current therapeutic approaches and unaddressed by existing vaccine platforms [ 2 , 3 , 4 ]. It is well established that the altered immune microenvironment in elderly patients leads to reduced immunity and vaccine responses [ 5 , 6 , 7 ], as well as decreased therapeutic interactions with immune cells as a result of age [ 8 , 9 , 10 ]. Pulmonary delivery may prevail in inducing more effective prophylactics for the elderly, as this route of administration offers a direct approach to target local immune cells in the lung and overcomes challenges of systemic administration that often fails to promote strong cellular or humoral pulmonary responses [ 8 , 9 , 10 ]. Indeed, the inherent machinery and function of local pulmonary immune cells to sample inhaled debris make them a ripe target for nano-based designs to activate widespread mucosal immunity [ 11 , 12 , 13 , 14 ]. However, inhaled delivery has yet to establish age-specific formulations that can address changes in immune function occuring over time [ 11 , 15 , 16 ]. Thus, there is clear motivation to study novel delivery platforms specifically within aged populations to better activate long-term respiratory immunity, which can be accomplished via precise targeting of pulmonary innate immune cells.

Throughout all stages of life, antigen-presenting cells (APCs), a specific class of innate immune cells, act as the first line of active defense against pathogens to clear harmful bodies within the lung [ 17 , 18 , 19 ]. These cells are critical for monitoring and maintenance of the lung microenvironment but can additionally activate T and B cell-based immunity, both locally and through drainage into local lymph nodes [ 19 , 20 , 21 , 22 ]. There exist four primary pulmonary APC types: alveolar macrophages (AMs), interstitial macrophages (IMs), and two types of conventional dendritic cells (cDCs), CD103 + and CD11b + DCs [ 17 , 23 , 24 ]. AMs represent the most abundant and widely studied APC in the lung that are uniquely located above the endothelial layer at the air-liquid interface and whose main role is to engulf inhaled debris [ 9 , 19 , 20 ]. IMs are a relatively newly characterized cell type that are less abundant than AMs and located within the interstitium of the lung [ 20 , 23 , 25 ]. Their role is less well-understood but are believed to act as a secondary clearing cell type after AMs and as potential stimulators of local pulmonary T cells [ 20 , 23 ]. The cDCs are similarly diverse in their roles; CD103 + DCs function as the main migratory APC, whereas CD11b + DCs are critical for regulation of local T cell phenotypical expression in the lung [ 24 , 26 ]. Hence, all four of these cell types are critical players in the immune defense system against major pathogenic infection in the lung, granting them massive unrealized potential as vaccine and drug targets [ 11 , 27 , 28 ].

Growing appreciation for the effect of age on the immune system has begun to elucidate the impaired functions adopted by these cell types with increasing age [ 3 , 8 , 9 ]. In the case of lung APCs, there have been a handful of studies that have characterized changes to relative population abundance and an overall decreased uptake of foreign entities in the lung in aged subjects, largely focusing on changes with AMs [ 3 , 29 ]. Previous work has established that the late stages of aged lungs (murine as well as human) exhibit signs of “inflammaging” (chronic low-grade inflammation associated with age) and “immunosenescence” (altered, less efficient immune response) that contributes to a reduction in APCs’ ability to appropriately target and respond to inhaled pathogenic material [ 2 , 3 ]. Furthermore, traditional cellular senescence, a state in which cells no longer proliferate and demonstrate increased endosomal activity, can occur in all cell types, further reducing clearance capacity in the lung [ 30 , 31 ]. Aging is correlated to increasing rates of improper phagocytosis and subsequent immune activation by these cell types over time [ 2 , 3 , 4 , 32 ]. It is believed that the accumulation of unengulfed debris and dysfunctional cell types within the lung microenvironment inhibits the ability of these APCs to identify and properly respond to pathogenic viruses [ 8 , 9 , 10 ]. Particulate-based vaccines capable of targeting pulmonary APCs throughout varied aged environments could offer significant opportunities to overcome these impairments and restore pulmonary health, building on decades of advancements in nanotechnology that can now enable directed immune responses in APCs for prophylactic and therapeutic applications [ 33 , 34 , 35 ].

Already, there have been a variety of studies of particulate carriers for pulmonary immune studies, which have been recently reviewed [ 11 ]. Importantly, relative size and surface charge of particulates are the major factors that influence their ability to deposit in various lung regions, cross mucosal barriers, and interact with immune cells [ 11 , 36 ]. However, nanoscale interactions between particles and pulmonary immune cells are still poorly understood and are often times conflicting. For example, inhaled NPs greater than 200 nm are preferentially internalized by AMs and demonstrate reduced mucus penetration capabilities, and yet 200 nm NPs conjugated to antigens have demonstrated greater antibody generation than smaller 30 nm NPs [ 11 , 37 ]. Moreover, anionic NPs demonstrate greater mucus penetration than positive NPs, and yet AMs preferentially uptake these formulations, while preferential uptake of cationic NPs has been documented in cDCs [ 11 , 38 ]. Additionally, NP shape and moduli also influence cellular interactions and aerodynamic properties; geometries with higher shape factor have decreased aerodynamic diameters which are capable of deep lung penetration [ 11 , 39 ]. Even further, material choice and surface properties, such as PEGylation, are intricately involved with not only pulmonary mucosal clearance, but also innate immune responses in the lung [ 11 , 40 ]. Despite the growing body of work evaluating these design parameters in the lung, most studies have been performed in young murine models, and thus, no systematic approach has been applied to understand the specific changes to APC uptake of NPs in the aged microenvironment. Thus, additional studies are needed to better understand the changing APC immune profile within the lung throughout the aging process to formulate age-specific NP design rules.

To establish NP physiochemical design rules that increase targeting to pulmonary APC subtypes across age, we sought to compare the uptake of poly(ethylene glycol) diacrylate (PEGDA) NPs in varied murine lung APC populations between young and aged mice. We began by characterizing the changes in APC phenotype between young (2-months) and aged (16-months) mice to establish differences in the functionality of these cells and characterize any impairment imparted by age [ 10 , 41 ]. Then, PEGDA hydrogel NPs of two distinct and opposing charges were synthesized and delivered via orotracheal instillation to both aged groups to quantify aged-based differences in NP phagocytosis as it relates to surface charge. Our results demonstrate that cell counts, NP uptake, and activation profiles of the four APC populations are uniquely affected by age, setting important precedence for the design of future inhalable therapeutics that seek to treat elderly patients.

For all biological studies, dilutions and formulations were performed with sterile 1X PBS (Phosphate Buffered Saline; Fisher Scientific). All other reagents were used as provided by the manufacturer and stored following manufacturer’s instructions. Reagents were obtained from Fisher Scientific unless otherwise noted within subsections below.

Nanoparticle synthesis

A pre-polymer solution to form 50 wt% solid PEGDA-based hydrogel NPs was composed of 88.8 wt% PEGDA (Sigma Aldrich), 10 wt% charge-establishing co-monomer, 1 wt% diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO; Sigma Aldrich), and 0.2 wt% Cy5 Maleimide (Fluoroprobes) in deionized water. 2-aminoethyl methacrylate hydrochloride (AEM, Sigma Aldrich) and 2-carboxyethyl acrylate (CEA, Sigma Aldrich) were used as the cationic ((+)NP) and anionic ((-)NP) functional co-monomers, respectively, to synthesize charged hydrogel NPs. The reverse emulsion photopolymerization technique to synthesize PEGDA hydrogel NPs has been described previously [ 42 , 43 , 44 ]. Briefly, polar, pre-polymer solution and non-polar, Silicone Oil AP1000 (Sigma Aldrich) were homogenized at roughly 1 mL total volume using a high-speed, benchtop vortex by placing the tube at an angle and applying pressure continuously along the tube to mix the non-polar and polar solutions. This was followed by tip sonication for 30 s at 30% amplification. Polymerization via UV irradiation was performed using APM LED UV Cube ( \(\:\lambda\:\:\) = 365 nm, distance from light source = ~ 28 cm, intensity = ~ 5–10 mW/cm 2 ) for ~ 30 s. Hexanes (Sigma Aldrich) were added to the polymerized mix to wash the silicone oil from the suspension. Particles were then washed twice in ethanol by centrifugation at 13,200 rpm for 10 min and stored in ethanol till use.

Thermogravimetric analysis (TGA)

Thermogravimetric Analysis (TGA) using TGA 550 (TA instruments) was used to determine bulk stock concentration of NP solutions. A known volume of NP stock solution in ethanol was aliquoted onto a hanging pan and, once loaded into the furnace, the temperature was increased to 90 °C followed by a 10 min isothermal incubation. Final weight measurements from at least two technical replicates were averaged and then divided by the known volume to ascertain the mass concentration.

Dynamic light scattering (DLS)

Dynamic Light Scattering (DLS) was performed using a Malvern Zetasizer Nano S Instrument (Malvern Instruments). Hydrodynamic diameter (D h ), polydispersity index (PDI), and zeta potential were measured at room temperature from 0.1 mg/ml solutions of NPs in either water or ethanol. Previously, it was determined that the (+) NPs yielded more disperse NPs suspensions when in ethanol, while (-)NPs were more disperse when in water [ 45 ]; DLS measurements were thus obtained in different solvents according to this preference, with sizing confirmed using cryo-SEM. Measurements were averaged from at least two independent replicates.

Animal studies

All studies involving animals were performed in accordance with National Institutes of Health (NIH) guidelines for the care and use of laboratory animals and approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Delaware. Female C57BL/6 (Jackson Laboratories) of two age groups (2-months and 16-months) were housed in a pathogen-free facility at the University of Delaware and given unrestricted access to chow and water. Mice were dosed via orotracheal instillation following a standard procedure by suspension via their incisors and gently grabbing and moving the tongue aside to block the esophagus, allowing direct delivery to the trachea and minimal dosage to the gastrointestinal tract (Supplemental Figure S1 A) [ 38 , 46 ]. Dosages of 100 µg of NPs were administered in sterile 50 µL 1X PBS under anesthesia with isoflurane. All studies including APC uptake, histology, and inflammatory surface marker analysis had an end point of 24 or 72 h. Terminal bronchoalveolar lavage fluid (BALF) was obtained via cannulation of the trachea restrained by a suture tie (Supplemental Figure S1 B). Here, 1 mL of sterile 1X PBS was dispensed into the lungs then was withdrawn and stored for cellular imaging.

APC phenotype and uptake analysis

After BALF collection, the whole lungs from NP-treated and untreated samples were removed. These were physically minced and digested in 1.5 mL of 5 mg/ml Collagenase IV (Gibco) for up to 2 h with an additional 500 µL of Collagenase IV added and pipette mixed after 30 min until a single cell suspension was achieved. The suspension was then filtered through a 70 μm cell strainer and resuspended in 1 mL RBC lysis buffer (Fisher Scientific). Samples were vigorously pipetted for 30–45 s, centrifuged at 500 rpm for 5 min, and then washed twice in 200 µL 1X PBS. Primary antibody staining was applied to the samples beginning with a Zombie Stain (Biolegend) diluted in 1X PBS for 15 min at room temperature followed by a single wash in 1X PBS and an additional wash in FACS buffer (2% Fetal Bovine Serum in 1X PBS; Fisher Scientific). Prior to further antibody staining, whole lung digests were split in half, one half to assess APC populations and the other to assess APC inflammatory response. Depending on the staining group, a combined antibody cocktail solution (refer to Supplemental Table S1 ) diluted in FACS buffer was applied for 30 min on ice followed by a single wash in FACS buffer and an additional wash in 1X PBS. Samples were fixed for 15 min in 100 µL of 4% PFA buffer (paraformaldehyde in 1X PBS; Fisher Scientific), washed a single time in 1X PBS followed by an additional wash in FACS. Samples were resuspended in 200 µL of FACS buffer and then run with appropriate fluorophore channels (refer to Supplemental Table S1 ) continuously on the Novocyte Flow Cytometer (Agilent Technologies). In between stains and washes, samples were centrifuged for 5 min at 500 rpm. Cell vs. debris gate was determined by gating samples with high forward-scatter area (FSC-A) and side-scatter area (SSC-A). Singlets were isolated as having a 1:1 ratio of SSC-A and side-scatter height (SSC-H), as this has previously been used as a rough correlation for the spherical, cellular relationship between granularity and diameter [ 43 , 44 , 45 ]. CD45 + cells were then isolated from a histogram plot. Macrophages were identified as MerTK + / CD64 + , with further gating identifying AMs as MHC II − / SiglecF + and IMs as MHC II + / SiglecF − . DCs were identified from a secondary MerTK − / CD64 − gate and selected by high expression of MHC II + and CD11c + . The two subtypes were then separated as CD103 + DCs or CD11b + DCs. NP uptake was determined as %NP + based on the percentage of events greater in fluorescence intensity than 1% of the untreated population on the NP + channel, as well as through median fluorescence intensity (MFI) of NP + cells on the same channel. An additional inflammatory panel was identified with the same initial steps isolating cells, singlets, and CD45 + cells. Then AMs were isolated as CD11c + / SiglecF + , while a broad cDC class was identified as CD11c + / SiglecF − / MHCII + . These cells were also stained with CD80 and CD86 for surface marker comparison. Cellular counts, MFI on cellular marker channels, and relative gating schematics were used for comparison between groups.

Post-euthanasia, representative whole lung samples were filled gravitationally with a mixture of 50:50 PBS: OCT (Optical Cutting Temperature, Fisher Scientific) solution via suspension of the mouse by its incisors and administering solution through a cannula in the trachea. After inflating and securing via a suture tie, the whole chest cavity was carefully removed, placed into a block, and then covered with OCT. The block was placed in an ethanol: ice mixture to rapidly freeze the sample and then was stored at − 80 °C. Tissue sections were achieved at 7 and 10 μm using the Avantik QS12 Cryostat (Avantik) and stored at − 80 °C till staining. Immunohistochemistry was performed using the Sakura Tissue-Tek Genie ® Advanced Staining System (Sakura Finetek USA) for CD45 stain. H&E (Hematoxylin & Eosin) staining was performed using Leica Autostainer XL (Leica Biosystems). For immunofluorescence histology, samples were fixed for 10 min in cold acetone followed by two washes in PBS. To prevent nonspecific binding, a FACS buffer was applied for 30 min. Following, primary anti-Hamster CD11c (Invitrogen) was applied to sections at 10 µg/ml and left overnight in a humidified chamber at 4 °C. Afterwards, slides were washed twice in FACS buffer and then stained with Goat anti-Hamster IgG (H + L) FITC (Invitrogen) at 1:100 dilution for 1 h at room temperature. After additional two washes in FACS buffer, DAPI (4′,6-diamidino-2-phenylindole; Fisher Scientific) was applied for 30 min. Following a final wash in FACS buffer, Pro-Long Diamond Antifade (Fisher Scientific) was applied before applying a cover slip. Images were acquired using the Biotek Cytation 5 Cell Imaging Multimode Reader (Agilent Biotek).

BALF cellular uptake imaging

Following collection, BALF was centrifuged at 500 rpm for 5 min and then supernatant was removed and saved for other analysis. The pellet was resuspended in 500 µL RBC lysis buffer and vigorously pipetted for 30–45 s. After a 1X PBS wash, the pellet was resuspended in 200 µL of FACS buffer and plated onto a glass-bottom 96 well plate. Cells were allowed to settle to the bottom of the plate via incubation for 2 h and then the plate was spun down for 5 min at 500 rpm. The samples were washed once in PBS and then fixed in 200 µL of 4% PFA buffer for 15 min. Following a final wash in PBS, cells were resuspended in 200 µL of FACS buffer and stored at 4 °C until staining. Cells were stained with DAPI for 30 min and Fluorescent Dye 488-I Phalloidin (Fisher Scientific) for 5 min with a wash of 200 µL of 1X PBS in-between and after each stain. Cells were resuspended in 200 µL of FACS buffer and then imaged using Biotek Cytation 5 Cell Imaging Multimode Reader (Agilent Biotek).

Statistical analysis

GraphPad prism 9 (GraphPad Software Inc.) was used to generate all quantitative figures and perform all statistical analyses. Numerical data is represented as mean ± standard deviation (SD) unless reported otherwise in figure captions. Appropriate post hoc statistical tests were reported in figure captions. Results shown other than histology are representative of at least two independent experiments, with particle or biological replicates reported in figure captions.

Comparison of immunophenotype between 2- and 16-month murine models

We first sought to characterize the basal APC phenotype within the 2- and 16-month C57BL/6 mice. We established a flow-cytometry gating scheme of single-cell whole lung digests to identify AMs, IMs, CD103 + DCs, and CD11b + DCs in the two age groups (Fig.  1 A, staining information Supplemental Table S1 ) [ 25 ]. After gating for cells, followed by singlets, and then the live cell population, the samples were further isolated for myeloid origin through CD45 + expression (Fig.  1 B). Following this, macrophages could be isolated by high CD64 and MerTK expression, which were then further categorized as AM or IM using SiglecF and CD11b expression. DCs were isolated from their low CD64 and MerTK but high MHCII and CD11c expression. These were then categorized as CD103 + or CD11b + . However, when applying the same gating scheme to the aged model (16-months), there appeared to be considerable shifts in the markers used for identification of cell types. Macrophages exhibited higher MerTK expression overall and a drastic increase in CD11b expression for the AM population (Fig.  1 D). While the DC gate showed similar expression of MHC II and CD11c compared to the young group, the ungated portion of the sample showed an increase in MHC II overall, somewhat hindering the analogous gating scheme for DCs from the young mice (Fig.  1 D). Furthermore, the aged model showed a noticeable decrease in CD103 + DC events, and the introduction of a new cell type that was neither CD103 + or CD11b + , labeled as DC3 (Fig.  1 D). This DC3 group showed noticeably low expression of CD11b, CD45, and MHC II in comparison to the other DC types (Supplemental Figure S2 ) but was a unique and separate population from either of the other DC types, as shown through back gating strategies (Supplemental Figure S2 ). Previous literature has not explored shifts in lung DC populations in aging studies, but as these cell populations in this age group specifically have rarely before been studied, it is not surprising that unique phenotypes may be discovered.

Advanced age demonstrates shift in APC population phenotype. Whole murine lung samples were digested into a single cell suspension for multicolor flow cytometry analysis of four pulmonary antigen presenting cells (APCs) of interest (alveolar macrophages (macs.; AMs), interstitial macrophages (IMs), CD103 + dendritic cell (DCs), and CD11b + DCs across two ages (2- and 16-months). ( A ) Study overview schematic including cells and age models of interest. ( B ) Primary gating for cells, singlets, live cells, and CD45 + cells. C - D .) Representative flow gating scheme for 2-months ( C ) and 16-months ( D )

Population phenotype expression comparison between the two ages showed similar trends in relative expression for the 8 markers selected (CD45, MerTK, CD64, CD11c, SiglecF, CD103, CD11b, and MHC II; refer to Supplemental Figure S3 ). However, apparent shifts in expression of certain markers were noticeable between the two groups. Thus, relative fold change for each marker of the untreated 16-month group was compared to untreated young mice to characterize changes in phenotype of the four APCs (Fig.  2 A). Here, the most significant change observed for all cell types was an increase in CD11b expression, with a nearly 10-fold increase for AMs and 6-fold increase for CD103 + DCs (Fig.  2 A). AMs also demonstrated a significant increase in MHC II expression compared to other cell types (Fig.  2 A). These results for AMs are in line with other previously reported analysis of aged lung models, but as of yet had not been quantified in a pre-senescent, 16-month aged model [ 47 ]. Another interesting result was a substantial increase in CD11c expression for the IMs (Fig.  2 A). This cell type does not typically present CD11c; however, other studies have found greater presence of CD11c + macrophages in inflamed microenvironments and it is known that this marker is inherently involved in phagocytosis [ 48 , 49 , 50 ]. Further quantitative analysis from untreated data showed a slight yet nonsignificant increase in CD45 + cell counts but an overall significant increase in CD45 expression in the 16-month age group (Fig.  2 B). Representative frozen lung histology further confirmed that CD45 expression increased at the tissue-level using a primary CD45 IHC stain (refer to Supplemental Figure S4 A-D).

16-month lung presents unique cellular immunophenotype. Cellular comparison was performed of the murine lung for two age groups of mice (2- and 16-months). ( A ) Fold change in surface marker MFI of 16-month isolated cell types compared to average expression of the 2-month group. Boxes with Xs indicate markers that were not expressed in those cell types. ( B ) Multicolor flow cytometry analysis of overall CD45 + cell counts and CD45 median fluorescence intensity (MFI). C-F.) Flow cytometry isolated individual cell counts for alveolar macrophages (AM; C ), interstitial macrophages (IM; D ), CD103 + dendritic cells (DCs; E ), and CD11b + DCs ( F ) in the two ages. Displayed numerical results represents mean ± SD ( n  = 5) from untreated group results. Indicated significance is calculated via unpaired Student’s t-tests [ p  < 0.05 (*), 0.01 (**), 0.001 (***), < 0.001 (****)]

Moreover, cell counts for the four APC cells of interest all demonstrated changes with age ( Fig.  2 C-F). Here, the 16-month age demonstrated noticeable yet nonsignificant decrease in AM cell counts accompanied with a complementary significant increase in IM cell counts (Fig.  2 C and D). This phenomenon has been observed previously in literature and is believed to be the result of a turnover of guard from AM-dominated clearance in young individuals to a more CD11b + cell type dominated lung population over time in aged lungs [ 51 , 52 ]. Interestingly, the DC cells also showed a similar trend, in which there was a reduction in CD103 + DCs events, previously seen in Fig.  1 D, accompanied by an increase in CD11b + DC count, which has yet to be reported in literature (Fig.  2 E and F). Additional representative H&E staining of frozen lung tissue demonstrated no significant influx of inflammatory bodies in the 16-month sample compared to the 2-month mice (refer to Supplemental Figures S4 E-F).

Altered in vivo nanoparticle uptake by aged APCs in the lung

In order to quantify the change in NP uptake of these unique age groups, an inert PEGDA hydrogel NP was synthesized using a reverse emulsion photopolymerization technique. This particle chemistry has widely been used in literature, as the monomeric components are readily modifiable for tunability of design (Fig.  3 A) [ 38 , 42 , 44 , 45 , 53 ]. Additionally, similar PEGDA NPs synthesized with the same cationic and anionic monomeric components in single-dose, short term studies have shown non-inflammatory responses in the lung, making them ideal vehicles for pulmonary phagocytic studies of APCs without induction of a pro-inflammatory effect [ 38 , 53 ]. Here, different NPs charge was evaluated to determine preferential uptake between the aforementioned APCs of interest reported in young and old mice. Two formulations of PEGDA NPs were synthesized with opposing surface charges by inclusion of two charged functional monomers (Fig.  3 A). The cationic charged functional monomer contained an amine-presenting functional group, which will be referred to as (+)NP and shown in bright pink data figures for the remainder of this article (Fig.  3 B). The anionic monomer contained a carboxylic acid-presenting group, referred to as (-)NP and shown as bright purple data figures from hereon (Fig.  3 B). The NPs synthesized here displayed high uniformity in hydrodynamic size (D h ), polydispersity index (PDI), and zeta potential (Fig.  3 C). Both formulations achieved NPs around 200–300 nm in D h and an absolute zeta potential around 25 mV (Fig.  3 C). Here, it was desired to achieve zeta potentials greater than 20 mV to ensure distinctions in NP charge and sufficient electrostatic interactions between NPs to minimize aggregation over time. While there is roughly 100 nm difference in D h of the two formulations, the (-)NP had a larger PDI pointing to some degree of polydispersity to ensure a reasonable overlap in particle sizes, such that both formulations should be expected to be internalized via phagocytosis. Cryo-scattering electron microscopy images of hydrogel NPs also demonstrated high sphericity of the particles (refer to Supplemental Figure S5 ). All further studies delivered these PEGDA NPs directly to murine lungs via orotracheal instillation, a pulmonary delivery technique that has shown restricted lung localization [ 38 ], and after a specified amount of time, the BALF and whole lung were successfully acquired for analysis (Fig.  3 D). We chose to compare NP uptake to an untreated group in both ages rather than a PBS-only, placebo group since previous studies using PBS-only groups have not demonstrated elevated inflammatory signals or soluble factors and thus the untreated group serves as a useful reference for NP distribution [ 43 , 44 , 54 , 55 ].

PEGDA Nanoparticle Formulation and Dosing Timeline. Poly(ethylene-glycol) diacrylate (PEGDA) hydrogel nanoparticles (NPs) at 50 wt% solid were synthesized using a reverse emulsion photopolymerization technique for uptake studies. ( A ) Composition of PEGDA pre-particle composition (left) and specific co-monomer chemical structures (right) of PEGDA NPs. ( B ) Surface presentation of synthesized NPs (pink = (+) NP, purple = (-) NP) ( C ) Dynamic light scattering data for NPs. Results represent mean ± SD, n  = 2 independent batch replicates. D h = hydrodynamic size, PDI = polydispersity index ( D ) Timeline of dosage experiments with NPs leading to collection of bronchoalveolar lavage fluid (BALF), serum, and whole lung tissue for analysis

A preliminary study delivering PEGDA NPs of both charges via orotracheal instillation to 2-month-old murine lungs was used to assess short-term NP uptake after 24 h via %NP + (refer to Supplemental Figures S6 and S7 ). While there was significant uptake of both formulations by the macrophage populations, there was minimal uptake (less than 10%) by DC populations (refer to Supplemental Figure S6 ). Thus, the remainder of the studies performed used an incubation period of 72 h to allow for appropriate cellular uptake by all populations and to match previously reported literature (Fig.  3 C) [ 38 , 54 ]. From digested lung samples that were treated with either formulation, NP uptake was quantified using %NP + (Fig.  4 A, D, G and J) as well as median fluorescence intensity (MFI), an average fluorescence value used to roughly determine the quantity of NPs phagocytosed by NP + cells (Fig.  4 B, E, H and K). Additionally, a final parameter of total fluorescence that combined these two previously mentioned through multiplication was further used to average NP uptake across these four cells of interest (Fig.  4 C, F and I, & 4 L).

Nanoparticle uptake shifts with charge, age, and type of cell. Two ages of mice (2- and 16- months) were dosed via orotracheal instillation with 100 µg of positive [(+)NP] or negative [(-)NP] PEGDA NPs. After 72 h, flow cytometry determined NP uptake in four APCs in the lung including alveolar macrophages (AMs, A - C ), interstitial macrophages (IMs, D - F ), CD103 + dendritic cells (DCs, G - I ), and CD11b + DCs ( J - L ). Parameters shown include percent of cell population with NP uptake (%NP; A , D , G , J ), median fluorescence intensity of the NP channel (MFI; B , E , H , K ), and the total fluorescence (%NP*MFI; C , F , I , L ). Data represents mean ± SD ( n  = 5). Indicated significance is calculated via two-way ANOVA [Tukey Test, p  < 0.05 (*), 0.01 (**), 0.001 (***), < 0.001 (****)]

Of note, AMs showed a significantly higher proportion of NP + cells compared to any other group regardless of age or surface charge (Fig.  4 A). This is consistent with known studies of AMs, which have shown that these AMs are the dominating phagocytic cell in the lung [ 20 ]. In the 2-month group, the AM population showed nearly 80% uptake after 72 h with no preference to either formulation based on NP + cells (Fig.  4 A). However, the aged group showed significant reduction NP uptake, with a reduction between the (-)NP uptake and (+)NP in comparison to their respective young group controls (Fig.  4 A). Interestingly, all young groups other than AMs showed a preference for (+)NP uptake, with IMs, CD103 + DCs, CD11b + DCs all exhibiting roughly 20% uptake after 72 h of (+)NPs (Fig.  4 D, G and J). Other than the CD11b + DC group, the interstitial populations also demonstrated a significant decrease in (+)NP uptake in the aged group but no change in the (-)NP uptake (Fig.  4 D, G and J).

While the %NP + uptake exhibited only minor changes across age, more noticeable results emerged for NP + MFI of the four APCs of interest. AMs of both age groups showed high preferential uptake for (-)NPs; however, the aged AM group demonstrated a highly significant ( p  < 0.001) decrease in uptake of (-)NPs ( Fig.  4 B ) . For the (+)NP, AMs showed no change in uptake across age (Fig.  4 B). Additionally, while the IM population showed minimal uptake of NPs in the young population compared to the AMs, there was a dramatic increase ( p  < 0.01) in the quantity of (-)NP uptake in NP + cells in the aged population (Fig.  4 E). There was noticeably greater variability within the IM population in terms of (-)NP uptake; this may speak to how undefined and nonlinear the aging process can be between subjects. However, these results are in line with the theory that the IM population may take on a more phagocytic role in the lung with the declining function of the AM population in aged individuals [ 20 , 23 ]. Furthermore, the combination %NP + *MFI for the AM and IM populations supports notion that anionic drug formulations have greater uptake by macrophages in the mucosa (Fig.  4 C and F).

In comparison to the dramatic change in uptake of NPs by macrophages, the DC populations overall showed minimal uptake of NPs with overall MFIs roughly 100 times less than that of the AM population (Fig.  4 H and K). While both DC types appeared to have a slight trend toward (+)NP preference in %NP + , there was significantly higher quantity of (-)NP uptake in the young population of CD103 + DCs (Fig.  4 H). Interestingly, there appeared to be an increase in NP uptake for all formulations and DC types in the aged group, with CD103 + DCs increasing in (+)NP uptake and CD11b + DCs having a drastic increase ( p  < 0.01) in both NP formulations (Fig.  4 H and K). Thus, in combination with the %NP + data, both DC populations showed no consistent change in NP uptake with age, while only the CD11b + DC group exhibited preferential (+)NP uptake in both ages (Fig.  4 I and L). Additionally, the other DC population isolated, DC3, was analyzed for NP uptake, which showed very similar results to the CD11b + DC population (refer to Supplemental Figure S8 ). Surprisingly, the DC3 subset showed increased percentage of NP uptake but reduced MFI for NP + cells compared to other DC types (refer to Supplemental Figure S8 A-C).

In addition to whole lung flow cytometry results, cells were isolated from bronchoalveolar lavage fluid (BALF) to further visualize changes in NP uptake across age. Thus, cells from BALF were appropriately plated and treated to visualize nuclei (DAPI; blue), actin (Phalloidin; grey), and NPs (pink); Fig.  5 ). Here, (+)NPs show similar consistent uptake across cells that is similar for both age groups (Fig.  5 A and C). In comparison, uptake of (-)NPs in the 2-month group was noticeably higher than the 16-month group (Fig.  5 B and D). Additionally, representative images in conjuncture with further supplemental images showed consistent trends within a variety of cells (refer to Supplemental Figure S9 ). Since BALF has been shown to primarily consist of AMs (> 90%), these results are consistent with flow cytometry results from Fig.  4 [ 56 ].

Aged phagocytotic cells in BALF show reduced NP uptake. After 72 h orotracheal instillation of positive (+) or negative (-) PEGDA NPs, cells isolated from BALF from 2- and 16-month mice. Representative stained images to identify nuclei (DAPI; blue), actin (Phalloidin; grey), and NP uptake (pink) were taken for 2-month (+)NP ( A ), 2-month (-)NP ( B ), 16-month (+)NP ( C ), and 16-month (-)NP ( D ). Images were taken using Biotek Cytation 5 Multimode Imager in which exposure was modified to visualize NPs in various samples. 2-month (-) NP samples ( B ) were at least 2x shorter in integration time than all other conditions. Scale bar represents 50 μm

Further fluorescence histology of frozen lung tissue from representative mice dosed with NPs for 72 h were obtained to ensure trends of cells other than AMs were consistent with flow results. Tissue was treated and imaged to visualize nuclei (DAPI; blue), CD11c (primary anti-hamster CD11c; green), and NPs (pink) Fig.  6 ). CD11c was used for DC and and to a lesser extent AM isolation. Arrows on individual images point to Cy5-NPs, where white indicates CD11c + NP + cells, while pink demonstrates NP + locations without CD11c + cell present. As expected, for both age groups, only the (+)NP formulation showed NPs that were not overlapping with CD11c + cells (Fig.  6 A, E, C and G). Since (+)NPs demonstrated much fewer AM-specific uptake and all the interstitial cell types exhibited reduced number of NP + cells in comparison to AMs, this suggests a higher chance of “non-associated” NPs in the tissue, which have not undergone localization specifically with AMs or DCs. In comparison, the (-)NP formulation showed higher consistency in uptake of CD11c + cell across both ages with higher prevalence in the 2-month group (Fig.  6 B, F, D and H). Unlike the BALF images however, there was no consistent pattern in the number of NPs that had been phagocytosed between age groups (Fig.  6 A and H). This is again consistent with the fact that DCs uptake NPs in low quantities and thus fluorescence imaging may not capture precise changes in this regard. These representative images were consistent with additional supplementary files (refer to Supplemental Figure S10 ). Thus, these results are also in line with flow cytometry results from Fig.  4 .

Immunofluorescence histology highlights CD11c + cellular uptake of NPs. Frozen whole lung murine tissue was sectioned at 10 μm thickness after 72 h dosage of either positive (+; A , C , E , G ) or negative (-; B , D , F , H ) nanoparticles (NPs; pink) via orotracheal instillation. The tissue was stained with primary anti-hamster CD11c, secondary IgG Alexa Fluor 488 (green), and DAPI (nuclei; blue). Representative images ( n  = 1) represent 2-month specimens (A, B, E, F) and 16-month specimens ( C , D , G , H ). White arrows indicate overlap between CD11c + , NP + cells, while pink arrows represent non-overlapping “non-localized” NPs. Images acquired using Biotek Cytation 5 Multimode Imager and exposure was modified for viewing of nanoparticles and CD11c stains in each image. Top and bottom row scale bars represent 100 μm and 25 μm, respectively

Nanoparticle-mediated phenotype of aged APCs in the lung

Once NP uptake was ascertained, the phenotype of the NP + cells was analyzed to determine if the particular advanced age group used here showed signs of increased inflammatory potential. H&E analysis from previous data of 2-month age group dosed with similar PEGDA charged NPs had not shown significant upregulation of inflammatory response [ 38 ]. However, it was particularly interesting to ascertain if the contrary would be noted in the 16-month group. Representative H&E images showed no change in inflammatory expression for either formulation for the aged group, signaling that no major event of inflammation occurred due to NP delivery (refer to Supplemental Figure S11 ). Further analysis of the 8 markers used for identification of the 4 APC cell types showed an increase in CD11b expression for all cells and NP formulations in the aged group after NP uptake, as determined via fold change comparison to MFI of young group for various surface markers (refer to Supplemental Figure S12 ). Interestingly, AMs from the 16-month group showed only a decrease in CD11c expression after NP uptake while all other cell types showed much greater variation in phenotype following NP uptake (refer to Supplemental Figure S12 ). Of note, all interstitial cell types showed an increase in MerTK expression and both DC types showed an increase in CD11c following NP uptake compared to the age-matched UT average expression (refer to Supplemental Figure S12 ).

In addition to the full flow cytometry panel used to isolate the 4 APCs of interest in the lung, a simpler panel that used the same initial gating scheme (cells, singlets, live cells, CD45 + ) isolated AMs (CD11c + , SiglecF + ) and broadly DCs (CD11c + , SiglecF − , MHC + ) (Fig.  7 A). This allowed for additional comparison of pro-inflammatory surface markers CD80 and CD86 as well as MHC II after NP uptake. MHC II, a marker of “self” to immune cells that is critical for antigen presentation to T cells, may become activated after NP uptake and maturation of the cell [ 21 , 43 , 54 ]. The untreated specimens presented different CD80, CD86, and MHC II expression between age groups (refer to Supplemental Figure S13 ). Results from Fig.  7 represent age-appropriate fold change data from NP + cells of each type allowing for comparison of the increase in inflammatory expression after NP uptake. From this, it was shown that all inflammatory markers for the 16-month AMs showed significantly increased expression compared to the 2-month population for both the cationic and anionic NP formulations (Fig.  7 B and D). Additionally, the (+)NP dosed population also exhibited increased MHC II expression in comparison to the (-)NP in the 16-month group AM population (Fig.  7 D). Thus, the higher expression of MHC II for (+)NP formulation here is in line with the decreasing rate of (-)NP uptake in the aged AM population.

Nanoparticle uptake in aged cells changes activation profile. A .) Multicolor flow cytometry results from partial lung tissue digests after 72-hr pulmonary delivery of PEGDA NPs. Alveolar macrophages (AMs; CD45 + , CD11c + , SiglecF + ) and dendritic cells (DCs; CD45 + , CD11c + , MHCII high ) were isolated from partial lung digest. AMs ( B - D ) and DCs ( E - G ) expression of CD80 ( B , E ), CD86 ( C , F ), and MHCII ( D , G ) were compared across NP treatments using fold change from age-appropriate UT. Data represents mean ± SD ( n  = 5). Indicated significance is calculated via two-way ANOVA [Tukey Test, p  < 0.05 (*), 0.01 (**), 0.001 (***), < 0.001 (****)]

Similarly, to the AM population, the DCs also showed an increase in CD80 and CD86 expression after NP uptake for each formulation in the aged group (Fig.  7 E and F). Of note, in comparison to the AMs, the DCs showed much higher relative fold changes for CD80 and CD86 expression for the age population (Fig.  7 E and F). Additionally, both age groups of (+)NP + samples showed a significant increase in CD86 expression in comparison to the (-)NP + population (Fig.  7 F). This trend was upheld for the 2-month population for MHCII expression, in which (+)NP formulations were significantly higher than (-)NP expression; however, this trend was not found in the 16-month population (Fig.  7 G). However, the increased inflammatory state in the age model may show a trend towards over inflammatory responses by these cell types; thus proper balancing of safe activation of immunity will be necessary for therapeutics designed for the aged.

In this study, we characterized the composition of four pulmonary APC subtypes in mice 2- and 16-months of age and documented changes to their association of NPs of different surface charges, with the goal to develop elderly-specific design rules for pulmonary NP vaccines. We report distinct population changes within the APCs present within the lung in each age group, which have interesting relationships with subsequent NP association that can be extrapolated for better vaccine design. Taken together, these findings illuminate a complex interplay between APC abundance, phagocytic capacity, and NP internalization that is highly dependent on the aged microenvironment and are important to the future of commercial pulmonary vaccine delivery.

Our choice to evaluate 16-month-old mice as our “aged” group roughly corresponds to the age of a ~ 60-year-old human and represents a pre-senescent, yet aged group. This age group in mice has never previously before been characterized for changes in pulmonary APC phenotype; thus, an important goal of our study was to compare the functionality of these cells to those of the young group [ 10 , 41 ]. Studying pulmonary immune responses to NPs within aged, yet pre-senescent models is critical to learn how clearance mechanisms are altered and thus could be targeted before the onset of significant senescence. In characterizing the APC dynamics, we observe that a 16-month murine model exhibited clear signs of altered APC function in the lung while not demonstrating definitive signs of “inflammaging”. Comparison of phenotypical markers of aging, namely higher expression of CD45, CD11b, and CD11c, agrees with current literature of these APCs in older murine models [ 2 , 3 , 47 ]. Moreover, the enhanced inflammatory reaction toward NP uptake by AMs and DCs as shown through CD80 and CD86 expression highlights the gradual chronic inflammatory environment that is induced in aged individuals, with onsets well before the classical global senescent definition. However, classical inflammation and senescent hallmarks, such as increase in inflammatory bodies, were not observed within the lung tissue [ 2 , 47 ]. We believe this duality in response can be explained by the fact that, while the mice used here are significantly more aged than the majority of studies on pulmonary immune responses, they are still younger than the senescent benchmark age of 18 months [ 10 , 30 ]. While senescence certainly alters response and has been linked to the natural degression of aged microenvironment, it is not the first significant change to initiate negative impacts on cellular responses in later stages of life. Thus, a broader, kinetic understanding of natural aging-induced characteristics must be determined to understand the onset of immune impairment and its relationship with vaccine failure in elderly individuals.

In this work, we also elucidated key NP interactions with aged APCs that could be used for elderly-specific pulmonary vaccine designs. Our PEG-based NPs serve as non-inflammatory materials that allow studies of APC tracking within the lung after pulmonary delivery, [ 53 ] with important reference data of this chemistry established in the literature for pulmonary APCs in young mice [ 38 , 54 ]. The NPs of ~ 300 nm enabled rapid phagocytosis by all pulmonary APCs cell types; [ 33 , 34 ] moreover, the high degree of tunability with this platform makes it a valuable tool to probe age-specific effects [ 11 ]. Positive and negative charges on the PEGDA platform were induced via the addition of one of two charge-contributing co-monomers in the pre-polymer monomeric mixture and importantly, neither formulation yielded a global acute inflammatory response in the airway. Notably, variation of the co-monomer led to a nearly 100 nm difference in hydrodynamic diameter between the two groups under the same synthesis conditions. However, both NP types were greater than 200 nm; accordingly, we expect that neither NP formulation would enhance mucus penetration [ 57 ], which would have increased their access to the interstitial APCs, and both formulations would be readily internalized by APCs via phagocytosis [ 58 ]. However, we do acknowledge that this difference in NP size may have played an additional role in cellular NP uptake or contributed to the variability seen in our results.

Using these NPs, we confirm that AMs demonstrate decreased NP internalization with age, pointing to reduced phagocytic capacity even in this timepoint in the aging process. Interestingly, complimentary increases in the IM population suggest that this cell type can serve as a secondary reservoir of cells capable of phagocytotic function after such reductions in the long-lived AM functionality due to age. Indeed, the aged IMs showed greater phagocytic capacity especially for negatively charged NPs, supporting the role of this cell type, and pointing to a possible alternative APC target for future vaccines for the elderly population. While the mechanism behind this shifted uptake profile remains unknown, changes to the phagocytic capacity of these cells as well as the altered lung microenvironment with age likely contributes. Recent work on the role that (apo)lipoprotein and scavenging receptors have on macrophages responses to PEG NPs and inflammatory diseases may provide necessary answers to the changes observed here [ 59 , 60 ].

The complimentary shift observed in the DC population numbers also has important ramifications for their use as vaccine targets. Importantly, the increase in CD11b + DC populations could signal an increase in monocyte-derived infiltrates, which occur naturally in aging but are less effective at antigen presentation and migration than CD103 + DCs [ 3 , 24 ]. Additionally, the discovery of a third CD11c + / MHC II + DC type, DC3, was completely unexpected for this study, as no other reports have determined another major class of cDC in the murine lung. However, the majority of current knowledge on aged DCs has been determined using circulating DCs from the blood of aged human subjects and not from lung sources [ 7 , 61 , 62 ]. Moreover, these studies have shown conflicting results on if DC population numbers shift in aged individuals and point to a continued need to advance tissue-specific knowledge of DC behavior and cell populations in aged subjects [ 7 , 61 , 62 ]. The changes we observed in aged DC population dynamics, even in this pre-senescent stage, may explain impairments in antigen presentation that are typically observed in aged subjects and lead to heightened infection and poor response to traditional vaccine treatments.

However, the increased NP + MFI trend by DCs in the aged lung alludes to pulmonary delivery as being a promising alternative route of administration of vaccines for the elderly specifically. Moreover, the knowledge that cationic NPs maintained their preferential uptake in the CD11b + DC type may be helpful in developing vaccines for maturation and even restimulation of local T cells within the lung to fight off reoccurring infections, which are common in the elderly population. The discovery that the DCs, even more so than macrophages, showed a propensity toward over-inflammatory expression after inert NP uptake may serve as a cautionary warning for the use of inflammatory material in elderly-specific vaccines. Hence, while healthy inflammation is necessary to rally other immune cells to the site of infection or disease, there is a delicate balance that must be maintained to stimulate appropriate and transient inflammatory conditions that can boost vaccine-like effects [ 63 , 64 , 65 ]. As such, in the chronically inflamed and immunosenescent case of elderly lungs, this balance may be even more difficult, yet critical to ascertain in order to develop prophylactic vaccines that no longer require multiple boosters but rather are specifically designed for expected changes to this microenvironment. Protein- and genetic-level alterations to aged macrophages and DCs in the lung are poorly understood as of now but may explain the differences observed here in APC functionality as it relates to the NP uptake and future vaccine platform designs.

To date, few studies have been performed on aged models due to the high cost of acquiring and maintaining them in healthy condition. Additionally, while chemicals that can induce senescence in certain cell types have been discovered, there is no comprehensive aged in vitro pulmonary model to use for rapid, high throughput testing of immunotherapies for aged macrophages and DCs. Increased access to aged models and development of complex aged in vitro set ups would be extremely useful for studying specific immunoengineering vaccine platform strategies for the elderly population [ 66 ]. While insights of age-related decline in adaptive immune function is increasingly understood [ 2 ], studies of APC functionality in age are critical in understanding changes to innate immune function in elderly lungs [ 67 , 68 ]. Our current set of results provides an important outlook to the changes of pulmonary APC phagocytic capacity with advancing age. However, this study is a mere snapshot of an aging, pre-senescent APC response, limited by the selection of a single time point for cargo uptake, a finite number of surface marker utilization, and the comparison of only two distinct age groups in female mice. The work here also does not include any studies of antigen-presentation capacity or migration by these APC types, which is an essential piece of knowledge to understand stimulation of local and distal adaptive immune cells for systemic immunity, especially in response to vaccination. It is pertinent that further studies are performed across a greater variety of age groups, immune cells, and delivery cargos to understand short- and long-term implications of APC immune cell involvement across changes to lifespan that build from this work to fully realize pulmonary vaccines that can better interface with the elderly immune microenvironment of the lung.

Current vaccine treatment strategies for the elderly have mostly been nonspecific, focusing on high payload delivery and increased frequency to overcome impairments in delivery [ 7 , 69 , 70 ]. Alternatively, potent, targeted inhalable platforms may increase efficacy alongside patient compliance and comfort, as they can be delivered without the use of needles and through handheld devices [ 11 ]. Building from the changes observed here in the phagocytic capacity of pulmonary APCs with age and their preference for distinct NP formulation parameters will assist in developing localized vaccines and therapeutics that can promote successful long-term immunity in the aged population. Thus, as the advancing age of our society continuously grows, developing effective vaccines that are tailored to the aged phenotype is critical to ascertain for future generations.

Data availability

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Antigen-presenting cell

Poly(ethylene)-glycol

Alveolar macrophage

Dendritic cell

Interstitial macrophage

Interleukin

Tumor Necrosis Factor

Nanoparticle

Phosphate buffered saline

Ultraviolet

2’-aminoethyl methacrylate

Carboxyethyl acrylate

Thermogravimetric assay

Dynamic light scattering

Hydrodynamic diameter

Polydispersity index

National Institute of Health

Institutional Animal Care and Use Committee

Bronchoalveolar lavage fluid

Red blood cells

Flow cytometry buffer

Paraformaldehyde

Median fluorescence intensity

Optical cutting temperature

Standard deviation

Hematoxylin & eosin

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Acknowledgements

The authors acknowledge Debbie Powel at the Bioimaging Center (University of Delaware) for acquiring cryo-SEM images and Charles Riley (University of Delaware) for his assistance with histology studies. They also acknowledge Adhya Anilkumar (University of Delaware) for assistance in flow cytometry experiments.

Research reported in this work was supported by the National Institutes of Health—National Institute of General Medical Sciences under Award Numbers R35GM142866. ES was additionally funded by NIGMS Award Number T32-GM133395. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Microscopy and histology were supported by grants from the NIH-NIGMS (P20 GM103446) and (P20 GM139760).

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ES and CF conceptualized the study. ES, ALR, and MTR performed the experimental investigations and curated the data. ES was responsible for methodology, validation, and data visualization. ES, ALR, and CF wrote the original draft. ES and CF reviewed and edited the final manuscript. CF was responsible for project administration, funding acquisition, and supervision.

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Sudduth, E.R., López Ruiz, A., Trautmann-Rodriguez, M. et al. Age-dependent changes in phagocytic activity: in vivo response of mouse pulmonary antigen presenting cells to direct lung delivery of charged PEGDA nanoparticles. J Nanobiotechnol 22 , 476 (2024). https://doi.org/10.1186/s12951-024-02743-7

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Age-dependent changes in phagocytic activity: in vivo response of mouse pulmonary antigen presenting cells to direct lung delivery of charged PEGDA nanoparticles

Affiliations.

• 1 Chemical and Biomolecular Engineering Department, University of Delaware, 150 Academy St, Newark, DE, 19716, USA.
• 2 Chemical and Biomolecular Engineering Department, University of Delaware, 150 Academy St, Newark, DE, 19716, USA. [email protected].
• PMID: 39135064
• PMCID: PMC11318229
• DOI: 10.1186/s12951-024-02743-7

Background: Current needle-based vaccination for respiratory viruses is ineffective at producing sufficient, long-lasting local immunity in the elderly. Direct pulmonary delivery to the resident local pulmonary immune cells can create long-term mucosal responses. However, criteria for drug vehicle design rules that can overcome age-specific changes in immune cell functions have yet to be established.

Results: Here, in vivo charge-based nanoparticle (NP) uptake was compared in mice of two age groups (2- and 16-months) within the four notable pulmonary antigen presenting cell (APC) populations: alveolar macrophages (AM), interstitial macrophages (IM), CD103 + dendritic cells (DCs), and CD11b + DCs. Both macrophage populations exhibited preferential uptake of anionic nanoparticles but showed inverse rates of phagocytosis between the AM and IM populations across age. DC populations demonstrated preferential uptake of cationic nanoparticles, which remarkably did not significantly change in the aged group. Further characterization of cell phenotypes post-NP internalization demonstrated unique surface marker expression and activation levels for each APC population, showcasing heightened DC inflammatory response to NP delivery in the aged group.

Conclusion: The age of mice demonstrated significant preferences in the charge-based NP uptake in APCs that differed greatly between macrophages and DCs. Carefully balance of the targeting and activation of specific types of pulmonary APCs will be critical to produce efficient, age-based vaccines for the growing elderly population.

Keywords: Aging; Antigen presenting cells; Nanoparticles; Phagocytosis; Pulmonary delivery; Pulmonary immunity.

© 2024. The Author(s).

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Conflict of interest statement

The authors declare no competing interests.

Advanced age demonstrates shift in…

Advanced age demonstrates shift in APC population phenotype. Whole murine lung samples were…

16-month lung presents unique cellular…

16-month lung presents unique cellular immunophenotype. Cellular comparison was performed of the murine…

PEGDA Nanoparticle Formulation and Dosing…

PEGDA Nanoparticle Formulation and Dosing Timeline. Poly(ethylene-glycol) diacrylate (PEGDA) hydrogel nanoparticles (NPs) at…

Nanoparticle uptake shifts with charge,…

Nanoparticle uptake shifts with charge, age, and type of cell. Two ages of…

Aged phagocytotic cells in BALF…

Aged phagocytotic cells in BALF show reduced NP uptake. After 72 h orotracheal…

Immunofluorescence histology highlights CD11c +…

Immunofluorescence histology highlights CD11c + cellular uptake of NPs. Frozen whole lung murine…

Nanoparticle uptake in aged cells…

Nanoparticle uptake in aged cells changes activation profile. A .) Multicolor flow cytometry…

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• Published: 14 August 2024

Recognition and control of neutrophil extracellular trap formation by MICL

• Mariano Malamud 1 ,
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• Cecilia Rodrigues 1 ,
• Petruta L. Morvay 1 , 2 ,
• Pierre Redelinghuys 2 ,
• Tina Bedekovic 1 ,
• Maria J. G. Fernandes 9 ,
• Ruqayyah Almizraq   ORCID: orcid.org/0000-0001-8494-6538 10 ,
• Donald R. Branch 10 ,
• Borko Amulic 8 ,
• Jamie Harvey 1 ,
• Diane Stewart 2 ,
• Raif Yuecel 11 ,
• Delyth M. Reid 2 ,
• Alex McConnachie   ORCID: orcid.org/0000-0002-7262-7000 3 ,
• Matthew C. Pickering   ORCID: orcid.org/0000-0002-1153-0192 12 ,
• Marina Botto   ORCID: orcid.org/0000-0002-1458-3791 12 ,
• Iliyan D. Iliev   ORCID: orcid.org/0000-0003-0884-9749 5 , 6 ,
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• Gordon D. Brown   ORCID: orcid.org/0000-0002-0287-5383 1 , 2  

Nature ( 2024 ) Cite this article

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• Cell biology
• Infectious diseases
• Rheumatic diseases

Regulation of neutrophil activation is critical for disease control. Neutrophil extracellular traps (NETs), which are web-like structures composed of DNA and neutrophil-derived proteins, are formed following pro-inflammatory signals; however, if this process is uncontrolled, NETs contribute to disease pathogenesis, exacerbating inflammation and host tissue damage 1 , 2 . Here we show that myeloid inhibitory C-type lectin-like (MICL), an inhibitory C-type lectin receptor, directly recognizes DNA in NETs; this interaction is vital to regulate neutrophil activation. Loss or inhibition of MICL functionality leads to uncontrolled NET formation through the ROS–PAD4 pathway and the development of an auto-inflammatory feedback loop. We show that in the context of rheumatoid arthritis, such dysregulation leads to exacerbated pathology in both mouse models and in human patients, where autoantibodies to MICL inhibit key functions of this receptor. Of note, we also detect similarly inhibitory anti-MICL autoantibodies in patients with other diseases linked to aberrant NET formation, including lupus and severe COVID-19. By contrast, dysregulation of NET release is protective during systemic infection with the fungal pathogen Aspergillus fumigatus . Together, we show that the recognition of NETs by MICL represents a fundamental autoregulatory pathway that controls neutrophil activity and NET formation.

The immune system needs to balance immune responses to be able to control infectious challenge but at the same time avoid excessive inflammation that could generate host tissue damage 3 , 4 . Neutrophils, the most abundant immune cell type in circulation, contribute to the first line of defence against a large number of pathogens and are critical in this fine balance as their antimicrobial responses must be tightly regulated to maintain homeostasis 5 , 6 . Neutrophils are activated based on pro-inflammatory signals that trigger various effector functions depending on their surface receptor composition and intracellular protein content 7 , 8 . For instance, neutrophils can respond to microorganisms via phagocytosis, generation of reactive oxygen species (ROS), and degranulation or the release of NETs 2 . NETs are defined as extracellular structures composed of DNA and cytosolic, granular and nuclear proteins assembled on a scaffold of decondensed chromatin 1 . NETs contain, neutralize and kill microorganisms including fungi, bacteria and parasites, but they can also be released in response to other stimuli, including crystals and immune complexes 9 , 10 , 11 . Of note, neutrophils and, in particular, NETs that are released following cell activation are associated with autoimmune pathogenesis, such as in rheumatoid arthritis or systemic lupus erythematosus (SLE) 12 , 13 . Moreover, NETs have been linked to the development of autoantibodies that are also associated with progression and severity of autoimmune diseases 6 , 7 . In inflammatory diseases, such as COVID-19 infection, neutrophils can acquire a persistent inflammatory signature that leads to increased NET release, which is associated with disease severity 14 , 15 , 16 .

NETs function as immune stimulants, acting as damage-associated molecular patterns that induce local inflammation and tissue damage 7 . NETs contain various molecules recognized by immune cell receptors. For example, following internalization of NETs by macrophages and dendritic cells, the cytosolic sensor cyclic GMP–AMP synthase (cGAS) recognizes the DNA backbone of NETs 17 . In addition, the cell-surface receptor TLR9 also recognizes NET–DNA in a process that is facilitated via two NET proteins: LL-37, which potentiates a type I IFN induction, and HMGB1, which acts through the receptor for advanced glycation products (RAGE) 18 , 19 , 20 , 21 , 22 . Recently, it has been shown that TLR4 recognizes and is activated by NET-associated histones, whereas histone containing chromatin DNA regulates TLR4 recruitment to endosomes 23 . However, the mechanisms that regulate cellular responses to NETs are still incompletely understood 23 .

Loss or mutation of inhibitory receptors are often associated with unchecked inflammation and destructive autoimmunity 24 . Recent work from our group has indicated that MICL (also known as CLEC12A) is one such receptor, which can regulate the pathogenesis of rheumatoid arthritis 25 . In contrast to wild-type (WT) mice, we showed that MICL-deficient animals ( Micl −/− ) undergoing collagen antibody-induced arthritis (CAIA) presented with exacerbated joint inflammation that did not resolve 25 . Through investigating the underlying mechanism, we discovered that MICL functions as an essential pattern recognition receptor (PRR) for NETs on neutrophils. Recognition of NETs by MICL inhibits neutrophil activation and further NET formation, regulating a positive-feedback cycle that, on the one hand, protects from excessive inflammation during multiple autoimmune diseases, but on the other hand, increases susceptibility to invasive infections.

MICL regulates neutrophil responses

Micl − /− mice exhibit enhanced and non-resolving joint inflammation compared with WT mice during CAIA 25 (Extended Data Fig. 1a ). To understand the underlying mechanism, we first determined the cell type (or types) responsible for this phenotype by analysing the cellular infiltrate in the hind paws of arthritic mice by flow cytometry. Day 7 was selected for analysis, representing the peak clinical score in WT mice undergoing CAIA (Extended Data Fig. 1a ). We found a significant increase in neutrophils (defined as CD45 + Ly6G + CD11b + cells) in the joints of Micl −/ − animals, whereas other myeloid populations were unaffected (Fig. 1a,b and Extended Data Fig. 1b ). Analyses of an earlier time point (day 5) showed that neutrophil numbers were higher in the joints of MICL-deficient mice even during early stages of inflammation, when there was no apparent clinical difference between the two groups of mice, again without affecting other myeloid populations (Extended Data Fig. 1c ). Of note, MICL deficiency also exacerbated joint inflammation in another effector phase model of rheumatoid arthritis: the K/BxN serum transfer model 26 (Extended Data Fig. 2a ). As in CAIA, Micl −/− mice in the K/BxN serum transfer model presented higher numbers of neutrophils than WT mice (Extended Data Fig. 2b ). There were no alterations in the frequency of cellular populations in the bone marrow or blood of naive Micl −/− mice (Extended Data Fig. 2c,d ).

a , tSNE plots of CD45 + myeloid populations in the inflamed ankle joint during CAIA displayed as CD11b + cells (grey), neutrophils (blue), Ly6C high cells (green), Ly6C low cells (orange) and remaining antigen-presenting cells (APCs; pale violet). b , Myeloid cell populations (defined as shown in the gating strategy in Extended Data Fig. 1b ) in the inflamed ankle joint during CAIA at day 7 are represented as a percentage of total live cells (pooled data from two independent experiments with four mice per group per experiment). WT versus Micl −/− neutrophils P  < 0.0001. c , Schematic representation of the anti-Ly6G-mediated neutrophil depletion strategy in the CAIA model. D0, day 0; LPS, lipopolysaccharide. d , Quantification of neutrophils (CD45 + CD11b + F4/80 − SSC high ) in the peripheral blood at day 9 by flow cytometry ( n  = 1 experiment with 3 mice per group). Isotype versus anti-Ly6G WT P  = 0.0035 and Micl −/− P  = 0.0021. e , Severity scoring of WT and knockout ( Micl −/− ) mice treated with isotype or anti-Ly6G antibodies (Abs), as indicated ( n  = 1 experiment with 5 mice per group). f , Schematic representation of neutrophil adoptive transfer during CAIA in WT mice. KO, knockout. g , CAIA severity scoring in WT mice that received adoptively transferred WT or knockout neutrophils, as indicated (pooled data from two independent experiments with five mice per group per experiment). Day 8 WT versus Micl −/− P  = 0.0013. h , Representative Safranin O-stained sections of the tarsal joints of WT mice that received adoptively transferred WT or knockout neutrophils, as indicated at day 8 (left). Synovial inflammation (black asterisks) is indicated. Scale bars, 500 µm. The histological arthritis severity score is also shown (right; nine mice per group). WT versus Micl −/− P  = 0.0281. Data are represented as mean ± s.d. ( b , d , e , g , h ). Statistical significance was determined by two-way analysis of variance (ANOVA) with Bonferroni’s multiple comparisons test ( b , d , e , g ). Data were analysed using an unpaired two-tailed Student’s t -test ( h ). * P  < 0.05, ** P  < 0.01 and **** P  < 0.0001. Schematics in panels c , f were created using BioRender ( https://biorender.com ).

Source Data

We next analysed the expression of key neutrophil adhesion and activation molecules (CD18, CD11b and CD62L) and chemotactic receptors (CXCR2 (ref. 27 ), CCR1 and C5aR 28 , 29 ) by flow cytometry. Neutrophils in the joints of Micl −/− mice under CAIA exhibited increased expression of CD18 and CD11b, and decreased expression of the lymphoid organ homing receptor CD62L, compared with WT animals, indicative of a heightened state of activation (Extended Data Fig. 2e ). This activated phenotype was only observed in cells isolated from the joints and not on neutrophils concomitantly isolated from the peripheral blood of mice undergoing CAIA (Extended Data Fig. 2e ). Analysis of receptors controlling neutrophil migration revealed increased expression of C5aR and the chemokine receptor CXCR2 on neutrophils isolated from the joints of Micl −/− mice, compared with WT animals, although the increase of the former was not statistically significant (Extended Data Fig. 2f ). By contrast, expression levels of CXCR2 and C5aR were comparable between neutrophils isolated from the peripheral blood of WT and Micl −/− mice (Extended Data Fig. 2f ). The expression of CCR1 on neutrophils was unaffected by MICL deficiency (Extended Data Fig. 2f ). MICL-deficient animals in the K/BxN serum transfer model of arthritis showed similar changes in neutrophil activation (Extended Data Fig. 2g ). There were no differences in the expression of key adhesion and activation molecules and chemotactic receptors in the bone marrow or blood neutrophils of naive animals (Extended Data Fig. 2h,j ). Together, these data demonstrate that MICL deficiency is characterized by an increased number and an enhanced activation of neutrophils in the joints of mice during CAIA and in the K/BxN serum transfer model of arthritis.

Neutrophils contribute significantly to the pathology of CAIA 30 . To investigate whether these cells were solely responsible for the exacerbated disease in Micl −/− mice, we successfully depleted circulating neutrophils via anti-Ly6G administration following the onset of CAIA (Fig. 1c,d and Extended Data Fig. 3a ). Of note, clinical disease was significantly reduced following neutrophil depletion, and to an equivalent level, in both WT and Micl −/− mice (Fig. 2e ). A similar reduction in disease severity occurred in both groups of mice following neutrophil depletion using the less-specific marker GR-1 (Extended Data Fig. 3b–e ). These data show that the elevated pathology in the Micl −/− mice undergoing CAIA was stemming from the neutrophil compartment.

a , ROS generation by MSU, PMA, zymosan or A. fumigatus hyphae-stimulated bone marrow neutrophils, depicted as relative light units (RLU), over time. Data are a representative example of n  = 4 independent experiments and mean ± s.d. performed in triplicate. Area under curve was analysed using unpaired two-tailed Student’s  t -test. WT versus Micl −/− MSU P  < 0.0001, A. fumigatus P  = 0.0056 and not significant (NS). b , Sytox green fluorescent images of MSU-induced NETs and NET formation percentage by thioglycollate-elicited neutrophils (3 fields of view per condition) 4 h post-stimulation with PMA or MSU, or medium alone (–). Data are represented as mean ± s.d. ( n  = 3 independent experiments performed in triplicate). Scale bars, 500 µm. Statistical significance was determined by two-way ANOVA with Bonferroni’s multiple comparisons test. WT versus Micl −/− MSU P  = 0.0304. c , Representative confocal immunofluorescence microscopy of NETs in CAIA WT and Micl −/− day 11 synovial sections (as per Extended Data Fig. 1a ; n  = 1 experiment with 3 mice per group). GR-1 (purple), DAPI (blue), citrullinated histone 3 (cit-H3; yellow) and DNA/H1 (green) are shown. NETs are defined as GR-1 + cit-H3 + DNA/H1 + -stained cells. Scale bars, 100 µm. d , Schematic of the PAD4 inhibitor CAIA treatment regime. e , f , Image stream quantification of NET-positive cells ( e ) and neutrophils isolated from arthritic ankle joints ( f ) at day 11 during PAD4 inhibitor (BB-CL-amidine) treatment. Pooled data are from 2 independent experiments with n  = 7 biologically independent mice per group, represented as mean ± s.d. Statistical significance was determined using two-way ANOVA with Tukey’s multiple comparisons test. WT versus Micl −/− P  = 0.0063 and Micl −/− versus Micl −/−  + PAD4 inhibitor P  = 0.0295 ( e ). g , Severity scoring of WT and Micl −/− mice during CAIA treated with vehicle or the PAD4 inhibitor (GSK484). The black arrow indicates the start of treatment. Data shown are a representative example of n  = 2 experiments with 4 mice per group, represented as mean ± s.d. Statistical significance was determined by two-way ANOVA with Tukey’s multiple comparisons test. Days 8–10 Micl −/− versus Micl −/−  + GSK484 P  < 0.0001. * P  < 0.05, ** P  < 0.01 and **** P  < 0.0001. The diagram in panel d was created using BioRender ( https://biorender.com ).

We then investigated whether the aberrant neutrophil response in the Micl −/− mice resulted from a cell-intrinsic or cell-extrinsic defect. For this, we isolated neutrophils from the bone marrow of naive WT or Micl −/− mice (Extended Data Fig. 3f ) and performed a single adoptive transfer of these cells into arthritic WT mice at day 7 post-induction of CAIA (Fig. 1f ). We detected transferred cells in the joints even 48 h post-transfer (Extended Data Fig. 3g ). Although transfer of WT neutrophils did not significantly alter disease severity (Fig. 1g,h ), transfer of MICL-deficient neutrophils into WT mice induced a significant increase in joint inflammation, determined by both clinical score and histological changes (Fig. 1g,h ). Together, these data reveal that aberrant neutrophil function underlies the pathology of Micl −/− mice during CAIA.

MICL controls NET formation

We then determined how loss of MICL was affecting neutrophil function. A previous report has suggested that MICL negatively regulates the respiratory burst in neutrophils in response to specific ligands, such as uric acid crystals (monosodium urate (MSU)) 31 . Indeed, we recapitulated this observation and showed that Micl −/− neutrophils induced a significantly elevated ROS in response to MSU, but not to phorbol-12-myristate-13-acetate (PMA) or zymosan, a potent inducer of ROS and a ligand for a related C-type lectin (Dectin-1) 32 , respectively (Fig. 2a ). Micl −/− neutrophils also produced higher levels of ROS in response to A. fumigatus hyphae, which are also known to induce ROS 33 (Fig. 2a ). As ROS production is involved in induction of NETs 34 , we examined this programmed cell death response and found that neutrophils from Micl −/− mice exhibited significantly increased NET formation in vitro following MSU stimulation (Fig. 2b and Extended Data Fig. 4,b ). NET formation was unaltered following PMA stimulation (Fig. 2b and Extended Data Fig. 4a ). The ability of diphenyleneiodonium chloride (DPI) to inhibit NET formation in cells from MICL-deficient animals revealed the dependence of this response on NADPH oxidase (Extended Data Fig. 4c ). MICL transduces intracellular inhibitory signals through SHP1/2 (refs. 35 , 36 ); we found that inhibition of SHP1/2 increased NET formation in WT neutrophils, but not in MICL-deficient neutrophils, indicating that inhibitory signalling from MICL was required to regulate this response (Extended Data Fig. 4d ). Of note, we detected increased NET formation (defined as GR-1 + cit-H3 + DNA/H1 + -stained cells) in the joints of Micl −/− mice undergoing CAIA at day 11 by immunofluorescence (Fig. 2c and quantification in Extended Data Fig. 4e ) and by imaging flow cytometry (Fig. 2e and Extended Data Fig. 4f ).

In addition to ROS, the formation of NETs can require histone citrullination through protein arginine deaminase 4 (PAD4) 37 . Using two different PAD4 inhibitors, BB-CL-amidine 38 and GSK484 (ref. 39 ), complete inhibition of NET formation in vitro was shown (Extended Data Fig. 5a ). In vivo (Fig. 2d ), imaging flow cytometry revealed that treatment with these inhibitors led to a significant reduction in the number of NETs detectable in the joints of Micl −/− but not WT mice during CAIA (Fig. 2e ). There was no effect of the inhibitor on the number of neutrophils recruited into the joints of these mice (Fig. 2f ). Treatment of Micl −/− mice with both PAD4 inhibitors reduced the severity of the disease back to WT levels (Fig. 2g and Extended Data Fig. 5b ). There was no significant effect of the inhibitors on disease development in WT mice (Fig. 2g and Extended Data Fig. 5b ), as expected 40 . Specific PAD4 inhibition also reduced disease severity in MICL-deficient mice during the K/BxN serum transfer model of arthritis (Extended Data Fig. 5c ). Administration of DNase I to degrade NETs in vivo ameliorated the enhanced clinical severity in the Micl −/− mice undergoing CAIA, but had no effect on disease severity in WT mice (Extended Data Fig. 5d ). Thus, these data show that aberrant regulation of NET formation underlies the pathology of MICL-deficient mice during models of arthritis.

Anti-MICL antibodies link to NET diseases

We had previously shown that administration of antibodies targeting MICL was able to exacerbate CAIA in WT mice, recapitulating the phenotype of MICL-deficient animals 25 . Here we found that treatment of WT neutrophils with anti-MICL antibodies resulted in elevated ROS production in response to MSU, but not zymosan, suggesting that these antibodies were blocking receptor functionality (Extended Data Fig. 6a ). To gain more insight into the effect of anti-MICL antibodies on neutrophil activation, we administered anti-MICL monoclonal antibodies to WT mice during CAIA in the presence of NET inhibitors. As previously observed, administration of anti-MICL antibodies exacerbated CAIA pathology in WT mice (Extended Data Fig. 6b ). Administration of a PAD4 inhibitor completely reduced disease symptoms to the levels seen in the isotype control-treated mice (Extended Data Fig. 6b ), revealing that aberrant NET formation was underlying the effect of the anti-MICL antibodies on disease pathology.

To further substantiate the receptor-blocking effect of anti-MICL antibodies, we tested them using an alternative model: collagen-induced arthritis (CIA). This is an important T cell-dependent model of arthritis that recapitulates both the pathophysiology and the histological presentation of human disease, although C57BL/6 mice, the same background on which our knockout model was based, are resistant to this model of disease 41 . However, the ability of anti-MICL antibodies to alter MICL function enabled us to explore the role of this receptor during CIA induced in DBA/1 mice. As before, administration of anti-MICL antibodies to DBA/1 mice exacerbated CIA disease and increased the number of neutrophils in the joints (Extended Data Fig. 6c ). These results confirm that antibodies to MICL interfere with key functions of this receptor and its ability to regulate neutrophil activation, exacerbating arthritic inflammation in different mouse models.

As we previously detected the presence of anti-MICL antibodies in a small cohort of patients with rheumatoid arthritis 25 , we explored whether these antibodies could affect neutrophil activation. Here we found that anti-human MICL antibodies were able to enhance the respiratory burst and NET formation in human neutrophils in vitro in response to MSU, but not to PMA (Fig. 3a,b ). Moreover, serum samples from patients with rheumatoid arthritis were able to increase ROS production in human neutrophils following stimulation with MSU (Fig. 3c and Extended Data Fig. 6d ); this effect directly correlated with the anti-MICL serum titres, demonstrating that patient anti-MICL antibodies interfere with MICL function.

a , ROS generation by MSU or PMA of human neutrophils (hPMNs) in the presence or absence of anti-MICL antibodies (anti-hMICL), depicted as RLU over time. Anti-hMICL versus isotype MSU P  = 0.0084. b , Fluorescence of NET-bound Sytox green of MSU or PMA-induced NETs in hPMNS in the presence or absence of anti-hMICL. MSU anti-hMICL versus isotype P  = 0.0043. RFU, relative fluorescence units. c , ROS generation by MSU of hPMNs in the presence of serum from patients with rheumatoid arthritis (RA) and healthy controls (HC). HC1 versus RA38 P  < 0.0001, HC1 versus RA40 P  < 0.0001, HC2 versus RA38 P  < 0.0001 and HC2 versus RA40 P  < 0.0001. d , Level of anti-MICL autoantibodies detected in serum samples from patients with rheumatoid arthritis ( n  = 199) and healthy controls ( n  = 132). Abs 450 , absorbance at 450 nm. e , Correlation of MICL autoantibody titres with rheumatoid factor levels in SERA cohort serum from patients with rheumatoid arthritis. f , Correlation of MICL autoantibody titres with CCP levels in SERA cohort serum from patients with rheumatoid arthritis. g , Level of anti-MICL autoantibodies detected in serum from patients with SLE ( n  = 40) and healthy controls ( n  = 25). h , Level of anti-MICL autoantibodies detected in serum from patients with mild/moderate (mCOVID-19; n  = 25) and severe (sCOVID-19; n  = 67) COVID-19 and healthy controls ( n  = 36). sCOVID-19 versus mCOVID-19 P  = 0.0472 and sCOVID-19 versus healthy controls P  = 0.0284. i , ROS generation and area under curve (AUC) of hPMNs stimulated with MSU in the presence of serum from patients with SLE pre-incubated with Fc–hMICL. Data are a representative example of n  = 3 ( a , b ) or n  = 2 ( c , i ) independent experiments, and mean ± s.d. performed in triplicate. The AUC was analysed by one-way ANOVA with Tukey’s multiple comparisons test. Box plots extend from the 25th to 75th percentile, including the median, and whiskers extend from the minimum to maximum value ( d , g , h ). Data were analysed by unpaired two-tailed Student’s t -test ( d , g ), a Spearman correlation and two-sided t -test ( e , f ), or using one-way ANOVA with Kruskal–Wallis multiple comparisons test ( h ). * P  < 0.05, ** P  < 0.01, *** P  < 0.001 and **** P  < 0.0001.

To determine whether anti-MICL antibodies were influencing clinical severity, we further analysed the prevalence of these antibodies in patients with rheumatoid arthritis, using an ELISA-based assay 25 . For this, we interrogated 200 serum samples from patients, along with matched controls, obtained from the Scottish Early Rheumatoid Arthritis (SERA) cohort 42 . We found that the majority of patients with rheumatoid arthritis presented with significantly elevated titres of anti-MICL autoantibodies (Fig. 3d ). High levels of autoantibodies were also detected in some healthy controls without rheumatoid arthritis. Although we did not find an association between the level of anti-MICL autoantibodies and DAS28 or Sharp erosion scores (data not shown), after correcting for age and sex, we detected an association between the level of anti-MICL antibodies and the level of rheumatoid factor, an autoantibody targeting the Fc region of IgG antibodies, which is used to diagnose, classify and predict development of rheumatoid arthritis 43 , 44 (Fig. 3e ). We also found a significant correlation between the level of anti-MICL autoantibodies and the level of anti-cyclic citrullinated peptide (CCP) antibodies in patients with rheumatoid arthritis (Fig. 3f ), indicative of a direct link of serum anti-MICL antibodies with NETosis and disease severity 45 , 46 . Together, these results show that autoantibodies targeting MICL interfere with the function of this receptor and correlate with severity of rheumatoid arthritis in patients.

We next determined whether anti-MICL autoantibodies were associated with any other NET-linked inflammatory diseases. Of note, we found high titres of anti-MICL antibodies in patients with SLE (Fig. 3g ) and severe COVID-19 (Fig. 3h ), both of which are inflammatory disorders where disease severity has been linked to NETosis 15 , 47 . Moreover, as we found in rheumatoid arthritis, serum samples containing anti-MICL antibodies from patients with SLE or severe COVID-19 were able to modulate neutrophil function, as demonstrated by increased ROS production following MSU stimulation (Extended Data Fig. 6e,f ). We demonstrated the specificity of this response through the addition of a soluble chimeric protein containing the C-type lectin-like domain (CTLD) of human MICL, which abrogated the serum effect on the neutrophil response (Fig. 3i and Extended Data Fig. 6g ). A related control CTLD had no effect on these responses (Extended Data Fig. 6g ). Thus, autoantibodies that modulate MICL-mediated neutrophil functions are present in patients with a wide variety of NET-related pathologies.

MICL is a PRR for NETs

Given that NETs can activate pro-inflammatory functions of naive neutrophils 48 , we wondered whether antibody-mediated interference or loss of MICL function was affecting neutrophil responses to NETs themselves. We observed that following exposure to preformed NETs, MICL-deficient neutrophils induced significantly increased levels of ROS and higher formation of NETs compared with the response of WT neutrophils (Fig. 4a,b and Extended Data Fig. 7a,b ). ROS production in MICL-deficient cells was unaltered when neutrophils were stimulated with NETs treated with polymyxin B (Extended Data Fig. 7c ). Following stimulation of cells from both groups of mice with preformed NETs, the ability of both ROS (DPI) and NET (PAD4) inhibitors to prevent NET formation shows that this process is dependent on NADPH and PAD4 activity (Extended Data Fig. 7d ). To show that human MICL was functioning similarly, we generated MICL-knockout human neutrophils derived from CD34 + haematopoietic progenitors 49 (Extended Data Fig. 7e ) and found increased ROS production in response to preformed NETs compared with control cells (Extended Data Fig. 7f ). Of note, we also demonstrated that normal neutrophils isolated from healthy human controls had significantly elevated ROS responses to human NETs in the presence of anti-human MICL antibodies (Fig. 4c ).

a , ROS generation by bone marrow neutrophils stimulated with preformed NETs, depicted as RLU over time. Data are a representative example of n  = 4 independent experiments, depicted as mean ± s.d. performed in triplicate. mNET, preformed mouse NETs. b , Immunofluorescence staining for MPO (yellow), cit-H3 (magenta) and DNA (DAPI; grey) of neutrophils stimulated with preformed NETs. Scale bars, 200 µm. Quantification is in Extended Data Fig. 7b . c , ROS generation by human neutrophils stimulated with preformed NETs in the presence or absence of antibodies targeting MICL. Data are a representative example of n  = 2 independent experiments, depicted as mean ± s.d. performed in duplicate. hPMNs versus anti-hMICL P  = 0.0011 and anti-hMICL versus isotype P  = 0.0016. d , Fc–MICL recognition of untreated NETs (NETs), proteinase K-treated (+prot K) or DNase-treated (+DNase I) NETs by ELISA. e , MICL-expressing BWZ reporter cell recognition of untreated NETs, proteinase K-treated or DNase-treated NETs. OD, optical density. Pooled data from two independent experiments, depicted as mean ± s.d. performed in triplicate ( d , e ). f , Neutrophil infiltration (CD45 + CD11b + Ly6G + cells) 4 h after preformed NETs or LPS injection in the peritoneum of WT and Micl −/− mice. Pooled data are from two independent experiments ( n  = 9 mice per group), depicted as mean ± s.d. NETs WT versus Micl −/− P  = 0.0384. * P  < 0.05, ** P   < 0.01 and **** P  < 0.0001.

To determine whether MICL was functioning as a PRR for NETs themselves, we examined the ability of a soluble chimeric protein consisting of the CTLD of mouse MICL fused to the Fc region of human IgG1 (Fc–mMICL) to directly recognize NETs. Using this Fc–protein and a structurally related control protein, we showed that MICL binds directly to NETs using an ELISA-based assay (Fig. 4d ). Moreover, recognition of NETs by MICL could also be demonstrated in a cellular context using MICL-expressing reporter cells 50 (Fig. 4e ). MICL recognition of NETs was blocked in the presence of antibodies targeting MICL (Extended Data Fig. 7g ), showing that antibodies to MICL block the ability of the receptor to recognize its ligand. To determine which component of NETs is required to interact with this receptor, we treated NETs with DNase I or proteinase K, and found that treatment with DNase abolished the ability of MICL to recognize NETs (Fig. 4d,e ). Furthermore, MICL-deficient neutrophils stimulated with DNase-treated NETs induced significantly lower levels of ROS (Extended Data Fig. 7h ). Consistent with these observations, MICL was able to recognize genomic DNA, and this interaction could be blocked in the presence of anti-MICL antibodies (Extended Data Fig. 7i ).

To show a direct role for MICL in response to NETs in vivo, we injected preformed NETs into the peritoneum of Micl −/− and WT mice. Neutrophil recruitment was significantly higher in Micl −/− mice treated with NETs, but similar to WT in mice administered with LPS (Fig. 4f ), revealing a specific negative regulatory function of MICL following recognition of NETs. Moreover, there was a trend to higher levels of cell-free DNA measurements following NET administration in MICL-deficient mice (Extended Data Fig. 7j ). Collectively, our data show that MICL functions as a PRR for NETs, regulating activation and NET formation in both mouse and human neutrophils.

MICL regulates fungal-induced NETs

To validate our hypothesis that NET sensing by MICL functions as a universal regulator of neutrophil activation and NET formation, we examined neutrophil responses elicited by A. fumigatus . NET formation is critical in the immune response to A. fumigatus , restraining fungal growth and preventing tissue dissemination 51 , 52 . We demonstrated that NETs are released in response to A. fumigatus hyphae 53 , 54 (Fig. 5a ), and both MICL-deficient neutrophils and human neutrophils treated with anti-MICL antibodies induce higher levels of NET formation in vitro in response to this pathogen (Fig. 5a and Extended Data Fig. 8a ). Of note, MICL-deficient mice were significantly more protected than WT mice following intravenous infection with A. fumigatus conidia (Fig. 5b ). This increased susceptibility of WT mice was associated with increased fungal burdens in the brains of these animals at day 2 post-infection (Fig. 5c and Extended Data Fig. 8b ). Analysis of inflammatory responses showed that serum levels of IL-6 and brain levels of G-CSF were significantly higher in infected WT than in MICL-deficient mice (Fig. 5d,e ), showing that MICL functions to restrain systemic inflammation during invasive aspergillosis. Furthermore, we confirmed that the increased survival of MICL-deficient mice was associated with higher NET formation, as the treatment of these animals with a PAD4 inhibitor (GSK484), but not with the vehicle, increased the susceptibility of the knockout mice to A. fumigatus infection to levels similar to those observed in WT mice (Fig. 5f and vehicle control shown in Extended Data Fig. 8c ). Moreover, administration of the inhibitor increased fungal burdens in the brains of MICL-deficient mice (Fig. 5g ). There was no effect of the NET inhibitor or vehicle control on disease development and fungal burdens in WT mice 53 (Fig. 5g and Extended Data Fig. 8c ). Thus, dysregulation of NET formation in MICL-deficient mice results in increased resistance to a systemic fungal infection.

a , Fluorescence of A. fumigatus hyphae-induced NETs bound to Sytox green in bone marrow-isolated neutrophils from WT and MICL-deficient mice or human neutrophils in the presence of antibodies to MICL. The fluorescence background signal from the unstimulated controls was subtracted from values. Data are a representative example of n  = 3 independent experiments, depicted as mean ± s.d. performed in triplicate. The AUC was analysed using an unpaired two-tailed Student’s t -test. WT versus Micl −/− P  = 0.0272 and anti-hMICL versus isotype P  = 0.0032. b , Survival of mice following intravenous infection with 10 6 A. fumigatus conidia ( n  = 15 mice per group). Pooled data are from two independent experiments, analysed by log-rank test; P  = 0.0005. c – e , Brain fungal burdens ( c ), and serum ( d ) and brain ( e ) cytokine levels of mice 2 days after intravenous infection with 10 6 A. fumigatus conidia. Values are mean ± s.e.m. of pooled data from two independent experiments. n  = 12 ( c ) or n  = 8 ( d , e ) biologically independent mice, analysed using an unpaired two-tailed Student’s t -test. IL-6 WT versus Micl −/− P  = 0.0185 ( d ) and G-CSF WT versus Micl −/− P  = 0.0492 ( e ). CFU, colony-forming unit. f , Survival of mice following intravenous infection with 10 6 A. fumigatus conidia and treated with GSK484 (PAD4 inhibitor). Pooled data are from two independent experiments; n  = 14 biologically independent mice, analysed by log-rank test. g , Brain fungal burdens of mice 2 days after intravenous infection with 10 6 A. fumigatus conidia treated with GSK484 (PAD4 inhibitor) or vehicle control. Values are mean ± s.e.m. of 1 experiment with n  = 6 biologically independent mice, analysed by one-way ANOVA with Tukey’s multiple comparisons test. WT vehicle versus Micl −/− vehicle P  = 0.0378, WT + GSK4848 versus Micl −/− vehicle P  = 0.0356 and Micl −/− vehicle versus Micl −/−  + GSK484 P  = 0.0242. * P  < 0.05, ** P  < 0.01, *** P  < 0.001 and **** P  < 0.0001.

The integration of signalling between diverse receptors helps to refine and modulate immune responses 55 . Inhibitory receptors regulate immune cell activation, avoiding excessive inflammation and host tissue damage. Our data revealed that MICL, an inhibitory C-type lectin receptor, is vital for the regulation of key neutrophil functions. We discovered that MICL is a PRR for NETs, and that this interaction is essential for controlling key neutrophil responses, including the respiratory burst and further induction of NETs themselves. This regulation is critical for limiting NET-mediated inflammatory conditions, such as in arthritis, SLE or severe COVID-19 infections, in which MICL prevents the formation of a positive-feedback loop that leads to uncontrolled inflammation (Extended Data Fig. 9 ). By contrast, this regulation of NET formation supresses robust control of invasive infections, promoting disease susceptibility.

In the context of arthritis, we showed that loss of MICL functionality increases NET formation and neutrophil activation by NETs, triggering an inflammatory chain reaction that leads to increased joint inflammation in three mouse models of arthritis. We also found that anti-MICL antibodies block the receptor function, and that the presence of these antibodies influences the severity of disease in mouse models and in patients with rheumatoid arthritis. In fact, we demonstrated that serum samples from patients with rheumatoid arthritis possessing anti-MICL autoantibodies, and antibodies to mouse or human MICL, are able to recapitulate MICL-deficient neutrophils, in terms of dysregulation of ROS production and NET release. NETs are released locally in the inflamed joints of patients with rheumatoid arthritis, and the citrullinated neo-epitopes generated during this process promote the formation of anti-CCP antibody that contribute to the perpetuation of the disease 6 , 56 . Of note, we found that the level of autoantibodies to MICL correlate with the level of anti-CCP antibodies in patients, indicating a direct link between MICL function and NET formation in patients with rheumatoid arthritis. Moreover, we showed that autoantibodies capable of blocking MICL function are also present in other autoinflammatory conditions, including SLE and severe COVID-19, in which NETs are linked to disease pathology 15 , 47 . Thus, MICL represents a universal novel autoregulatory pathway that prevents aberrant neutrophil activation and subsequent tissue damage in autoimmunity.

Neutrophils also have a crucial role in protection against fungal pathogens, such as A. fumigatus 57 . Protective neutrophil responses to A. fumigatus hyphae involve ROS production and NET formation 51 , 52 , 54 . Although PAD4 is required for NET formation in response to A. fumigatus , previous studies using Pad4 -knockout mice have suggested no role for this enzyme during infection 53 . Indeed, we found that PAD4 inhibition does not affect disease severity in WT mice. Here we discovered that the PAD4 pathway is stringently regulated by MICL, but that mice lacking this receptor use this pathway to restrict fungal infection through increased NET formation. Pharmacological inhibition of NET formation using a PAD4 inhibitor blocked this pathway in MICL-deficient mice, reverting their susceptibility to infection back to WT levels. Our data show that similar MICL-mediated control of the PAD4 pathway also occurs during autoimmune disease. Indeed, the PAD4 pathway has previously been shown not to be required for effector phase responses during arthritis 58 , as we found in our WT mice (Fig. 2g and Extended Data Fig. 5b ). Of note, our data show that in the absence of MICL (or inhibition of receptor function by anti-MICL antibodies), the PAD4 pathway becomes activated during autoimmune disease, leading to dysregulated NET formation and aberrant inflammation.

In conclusion, we defined a key mechanism by which MICL regulates neutrophil activation and NET formation. MICL directly recognizes NETs, inducing intracellular signalling that dampens neutrophil responses and preventing the formation of a positive-feedback loop leading to further NET formation. In patients with rheumatoid arthritis, SLE and severe COVID-19, this feedback loop becomes dysregulated by autoantibodies to MICL, leading to a worsened disease outcome. It is likely that autoantibodies to MICL are also associated with the severity of other NET-mediated autoimmune disorders, such as anti-neutrophil cytoplasmic antibody-associated vasculitis. Given that we also observed elevated levels of anti-MICL antibodies in a proportion of healthy individuals, future work should explore the possibility that the presence of such autoantibodies are associated with, or predispose towards, the development of autoimmune disease. Our data also reveal that NET sensing by MICL can have different clinical outcomes depending on the context. In this sense, our results suggest therapeutic targeting of MICL with antibodies to increase ROS and NET formation, contributing to fungal clearance, could be used to treat disseminated forms of invasive infection. Conversely, blocking of the antibody–receptor interaction could be of therapeutic benefit for NET-mediated inflammatory disease. In summary, our observations revealed a novel and fundamental function of inhibitory pathways underlying infectious and non-infectious disease pathogenesis.

Micl −/− and C57BL/6J mice were bred and maintained under specific pathogen-free (SPF) conditions at the University of Aberdeen, University of Exeter and Charles River Laboratories. Mice were housed in separate groups with bedding exchanges between cages every 2 days for 1 week before commencement of experiments, and maintained on a 12 h–12 h dark–light cycle (07:00–19:00) at 20–24 °C and relative humidity of 55 ± 15%. Mouse experiments were performed by random assignation of age-matched (6–8 weeks old) and sex-matched mice in experimental or control groups at the beginning of each experiment; females were co-housed and experiments were not blinded. All experiments conformed to the ethical review committee of the University of Aberdeen, University of Exeter and the UK Home Office regulations (project license numbers: P79B6F297 and P6A6F95B5).

Male mice received intraperitoneal (i.p.) injections of 2 mg of ArthritoMab monoclonal antibody cocktail (MD Bioproducts) on day 0, followed by 50 μg of lipopolysaccharide (LPS) i.p. (MD Biosciences) on day 3. Joint inflammation was scored visually using a scale of 0 (no visible signs of redness or swelling) to 4 (extensive swelling with signs of deformity). To achieve neutrophil depletion during CAIA, 500 μg of rat anti-mouse Ly6G (clone 1A8, Bio-X-Cell) or isotype control (rat anti-mouse IgG2a; Bio-X-Cell) was administered i.p. to mice every 48 h from day 5 onwards. Alternatively, 50 μg of rat anti-mouse GR-1 (clone RB6-8C5) or isotype control (rat anti-mouse IgG2b) was administered i.p. every 48 h from day 5 onwards. Mice were culled on day 5, 7, 10, 11 or 13, as indicated in the text. For adoptive transfer experiments, bone marrow neutrophils were isolated as detailed below and stained with cell proliferation dye eFluor 670 (eBioscience). Labelled cells (5 × 10 6 ) were transferred intravenously (i.v.) to WT mice on day 7 following induction of CAIA. Mice were culled on day 9. To investigate the role of NET formation, mice undergoing CAIA were injected i.p. with 2 mg kg −1 daily of BB-CL-amidine (Cayman Chemical), 4 mg kg −1 daily of GSK484 (Cambridge Biosciences), 75 U per animal of DNase I (Merck) or vehicle (5% DMSO in 10% cyclodextran for BB-Cl-amidine or ethanol 99.9% diluted 1:50 in 0.9% NaCl for GSK484) from day 7 to day 10. Mice were culled on day 11.

K/BxN serum transfer model of arthritis

Male mice were administered i.p. with 100 μl of serum from transgenic K/BxN mice 26 . The development of clinical symptoms were monitored daily and mice were culled on day 10. Joint inflammation was scored visually using a scale of 0 (no visible signs of redness or swelling) to 4 (extensive swelling with signs of deformity). To investigate the role of NET formation, mice were injected i.p. with 4 mg kg −1 daily of GSK484 or vehicle (ethanol 99.9% diluted 1:50 in 0.9 % NaCl) from day 7 to day 10. Mice were culled on day 11.

Male DBA/1 mice were purchased from Inotiv and maintained at the University of Exeter. Mice were treated subcutaneously with 100 μl of Immunization Grade Chick Type II Collagen (Chondrex; 200 µg per mouse) in Complete Freund’s Adjuvant (Sigma-Aldrich) at day 0 and with 100 μl of Immunization Grade Chick Type II Collagen (200 µg per mouse) in Incomplete Freund’s Adjuvant (Sigma-Aldrich) at day 14, followed by an i.p. injection of 50 µg of LPS at day 26. Of anti-MICL antibodies, 0.7 mg of isotype control antibodies or PBS were administered i.p. every 48 h from day 17 to day 33. Mice were culled at day 35. In our animal facility, naive DBA/1 animals did not develop any spontaneous form of arthritis by 13 weeks of age (the latest timepoint in our experiments).

For histology, paws were fixed in 4% paraformaldehyde (PFA) overnight at 4 °C and decalcified in 10% EDTA for 3–4 weeks. Decalcified paws were embedded in optimal cutting temperature (OCT) and cryosectioned or embedded in paraffin wax and sectioned before staining with haematoxylin and eosin, or Safranin O, haematoxylin and fast green. Scoring of histological sections was performed blinded using an arthritis severity score as previously described 18 .

Immunofluorescence staining protocol

Frozen tissue sections were thawed for 30 min at room temperature and washed with PBS before permeabilization with 0.25% Triton X-100 or 0.5% saponin in PBS for 10 min. After permeabilization, sections were washed with PBS again and blocked with 3% BSA at room temperature for 30 min. Tissue sections were stained with primary antibodies (anti-cit-H3 (Abcam), anti-DNA/H1 (Merck) and anti-GR-1 (produced in-house 59 )) diluted in blocking buffer (3% BSA in PBS) for 1 h 30 min in a humidified chamber, after which they were washed with PBS-Tween-20 (0.05%) and stained with secondary antibodies for 1 h at room temperature in the dark. Sections were washed as before and counterstained with 1 μg ml −1 DAPI and mounted in Vectashield antifade mounting medium for fluorescence (Vectorlabs). Coverslips were sealed with nail polish and slides were stored in the dark at 4 °C until imaging. Fluorescence was visualised using the Zeiss confocal LSM700 microscope and Zen Black software (Zeiss). The quantification of positive area (area + %) for each channel was conducted using Fiji software. Image preprocessing included utilizing the built-in ‘Moments’ algorithm for thresholding each channel.

Neutrophil isolation

Bone marrow neutrophils were isolated using Histopaque (Merck) by a density gradient centrifugation method or using the EasySep Mouse Neutrophil Enrichment Kit (StemCell Technologies) according to the manufacturer’s guidelines. Flow cytometry analysis confirmed an approximately 90% pure neutrophil population (the remaining population consisting primarily of monocytes). To isolate thioglycollate-elicited neutrophils, mice were injected i.p. with 1 ml of 3% thioglycollate broth. After 4 h, mice were culled and neutrophils were harvested by peritoneal lavage with PBS 5 mM EDTA.

Human neutrophils from the blood of healthy donors were purified using a Ficoll-Paque density centrifugation method 60 or using the EasySep direct human neutrophil isolation kit (StemCell Technologies) as per the manufacturer’s instructions. Samples were obtained from consenting healthy donors with the approval of the Faculty of Health and Life Sciences ethics review board, University of Exeter (eCLESBio000371) and the College of Life Sciences and Medicine ethics review board, University of Aberdeen (CERB number 1243).

CD34 + cell isolation and CRISPR-mediated knockout

Peripheral blood mononuclear cells (PBMCs) were isolated from apheresis blood waste (NHSBT) with ethical approval from NHS Research Ethics Committee (REC 18/EE/0265) by density centrifugation using Histopaque-1077 (Sigma-Aldrich) according to the manufacturer’s instructions. After washing, cells were resuspended in red cell lysis buffer (55 mM NH 4 Cl, 0.137 mM EDTA and 1 mM KHCO 3 , pH 7.5) and incubated on ice for 10 min. Next, to enrich haematopoietic stem cells, CD34 + cells were isolated from PMBCs using a human CD34 Microbead Kit (Miltenyi Biotec) according to the manufacturer’s protocol. Isolated cells were cultured in Iscove’s modified Dulbecco’s medium (IMDM) supplemented with 10% (v/v) FBS and 1% (v/v) penicillin–streptomycin at 37 °C in 5% CO 2 . Cytokines were added at the indicated concentrations and days of culture: stem cell factor (SCF; 50 ng ml −1 ; day 0–5 of culture), Flt-3 ligand (50 ng ml −1 ; day 0–5 of culture), interleukin-3 (IL-3; 10 ng ml −1 ; day 0–5 of culture), granulocyte–macrophage colony-stimulating factor (GM-CSF; 10 ng ml −1 ; day 3–7 of culture) and granulocyte colony-stimulating factor (G-CSF; 10 ng m −1 ; day 7–14 of culture). All functional assays were completed between day 17 and day 18 of culture 49 .

CRISPR-mediated knockout was completed using the AmaxaTM 4D-Nucleofector (Lonza) using a P3 Primary Cell 4D-NucleofectorTM X Kit S (Lonza) and TrueCut Cas9 Protein v2 (Invitrogen) according to the manufacturers’ instructions. In brief, day 3 cultured neutrophils were resuspended in the mixture of P3 Primary Cell Solution and supplement 1 containing 50 pmol Cas9 and 125 pmol of guide RNA (62.5 pmol of two guides with the same gene target). Cells were transferred into nucleocuvette strip and electroporated using the EO-100 program. After electroporation cells were transferred into six-well plates containing StemSpan medium (StemCell Technologies) supplemented with FBS and penicillin–streptomycin and containing SCF, Flt-3 and IL-3. From day 5 onwards, cells were cultured as outlined above in IMDM. All functional assays were completed between day 17 and day 18 of culture. Guide RNAs were designed using Knockout Guide Design (Synthego). The following single guide RNAs were used (Synthego, modified single guide RNA with EZ scaffold): CLEC12A + 9979452: UGAAUAUCUCCAACAAGAUC and CLEC12A-9979406: GUUGUAGAGAAAUAUUUCUC; negative control scrambled #1: GCACUACCAGAGCUAACUCA and negative control scrambled #2: GUACGUCGGUAUAACUCCUC. Cells were stained with anti-CD66-PE/Dazzle (clone G10F5; diluted 1:50), anti-CD15-AF700 (clone Hi98; diluted 1:50), anti-CD16-APC (clone 3G8; diluted 1:50) and anti-hMICL or isotype control antibodies at 10 µg ml −1 to confirm loss of MICL expression.

Bone marrow neutrophils and human neutrophils were isolated as described above and resuspended in OptiMEM (Thermo Fisher Scientific) supplemented with 5% FCS. Cells (5 × 10 5 ) were added to each well of a white 96-well flat-bottomed plate and stimulated in triplicate with 200 μg ml −1 MSU crystals (Invivogen), 25 μg ml −1 Zymosan (Molecular Probes), 100 nM PMA (Sigma), isolated NETs (100 μg ml −1 based on NET–DNA concentration) or A. fumigatus hyphae (1 × 10 4 conidia per well incubated for 12 h at 37 °C) in the presence of 100 μM luminol (Sigma). Chemiluminescence was measured every 3 min for 2 h in a FLUOStar Optima microplate reader (BMG Labtech) or a Spark Cyto (Tecan) at 37 °C with 5 % CO 2 .

Bone marrow and thioglycollate-elicited neutrophils were isolated as described above. Cells were resuspended in RPMI (without phenol red; Thermo Fisher Scientific) supplemented with 2% DNase −/− mouse serum and seeded in an eight-well iBidi μ-slide (iBidi). Cells were stimulated with 100 μg ml −1 of MSU crystals (Invivogen), 100 nM PMA (Sigma), isolated NETs (100 μg ml −1 based on NET–DNA concentration) or A. fumigatus hyphae and incubated at 37 °C with 5% CO 2 for 4 h. In some experiments, as indicated in the text, DPI (10 μM; Sigma) or NSC-87877 (5 μM; Cayman Chemical) were included in the assays. Extracellular DNA was visualized with 5 μM Sytox Green (Invitrogen). In experiments without fixation, cells were previously stained with Draq5 (Thermo Fisher Scientific) and cell-impermeable Sytox Green, and images were acquired on an inverted Zeiss AxioObserver Z1 using a PlanApo ×20/0.75 NA dry lens (Carl Zeiss) and a Hamamatsu Fusion sCMOS camera with an attached incubation chamber (PeCon GmbH) at 37 °C. Fluorescent images were analysed in Image J, and NETs defined as Sytox Green-positive cells showing extrusions were counted.

NET (%) = (total Sytox Green-positive cells extruding NETs/total cells counted) × 100

For kinetic curves of NET formation, neutrophils were seeded in a 96-well black plate with a transparent bottom and the cells were left to adhere for 30 min in a cell culture incubator. Cells were stimulated with the defined reagents and 5 μM Sytox Green. Fluorescence signal (504-nm excitation and 523-nm emission) was measured every 10 min for 7 h in a Spark Cyto (Tecan) at 37 °C with 5% CO 2 .

NETs were isolated as previously described 61 . In brief, bone marrow-isolated or purified human neutrophils were plated in a six-well plate at a density of 1 × 10 6 cells per well in RPMI without phenol red. Following stimulation with 100 nM PMA for 4 h at 37 °C, the culture medium was removed and NETs were partially digested by application of a restriction enzyme mix combining the enzymes BseRI, PacI, NdeI and AfIII (New England Biolabs) at a concentration of 5 U ml −1 in NEB buffer for 1 h at 37 °C. Supernatants were collected and centrifuged at 300 g for 10 min at 4 °C. NET supernatants were transferred to a fresh tube and stored at −80 °C until used. When indicated, NETs were treated with DNase I (Thermo Fisher Scientific) or proteinase K (Roche) for 1 h at 37 °C.

Recognition of isolated NETs by MICL was assessed by ELISA. A 96-well plate (Nunc Maxisorp) was coated with NETs diluted in PBS overnight at 4 °C. Wells were washed and blocked with blocking buffer (5% BSA) at room temperature. Fc–mMICL or Fc–mCLEC12B at 1 μg ml −1 in blocking buffer was added and incubated for 2 h at room temperature. Bound Fc-fusion proteins were detected with horseradish peroxidase-conjugated goat anti-human IgG (Jackson Immunoresearch) diluted 1:10,000 for 1 h. TMB substrate was added, and absorbance was measured using a plate reader (Tecan). Purification of Fc–MICL and Fc–mCLEC12B, from transduced HEK293T cells (originally purchased from the American Type Culture Collection (ATCC), but not tested for Mycoplasma contamination for the experiments detailed in this paper), was performed as previously described 32 .

To analyse the recognition of isolated NETs by MICL using a MICL-expressing cell line, a 96-well plate was coated with NETs diluted in PBS overnight at 4 °C. Wells were washed, and BWZ.36 NFAT-LacZ cells (provided by W. Yokoyama; not tested for Mycoplasma contamination for the experiments detailed in this paper) expressing the CD3ζ chain fused to the transmembrane and carbohydrate recognition domain (CRD) of mMICL or mCLEC12B were added (2 × 10 5 cells per well) for 18 h at 37 °C. After stimulation, cells were centrifuged at 800 g for 2 min and washed two times with PBS. Of CPRG substrate buffer, 100 µl was added per well. The reaction was stopped 4 h later with the addition of 50 µl of glycine-EDTA buffer, and the absorbance was measured using a plate reader 62 (Tecan). Antibody crosslinking with the appropriate receptor antibody was used to confirm the functionality of the chimeric receptor constructs.

To analyse neutrophil infiltration by isolated NETs, 6–8-week-old Micl −/− and C57BL/6J mice were injected i.p. with 300 μg NETs or 50 μg LPS. Four hours later, mice were euthanized, and their peritoneal cells were counted and analysed by flow cytometry. Cell-free DNA was evaluated using the Quant-iT PicoGreen dsDNA Assay (Invitrogen) following the manufacturer’s instructions.

Immunofluorescent staining of in vitro samples

Neutrophils (5 × 10 4 ) were plated in an eight-well iBidi μ-slide (iBidi) 1 h before stimulation with isolated NETs, PMA or MSU. Four hours after stimulation, cells were fixed for 20 min at 37 °C with 2% PFA and permeabilized with 0.5% Triton X-100 in PBS. Samples were blocked with 3% (v/v) normal goat serum, 1% (w/v) BSA in PBS and incubated with anti-cit-H3 (Abcam) and anti-myeloperoxidase (R&D) antibodies. The secondary antibodies donkey anti-rabbit Cy5 and rabbit anti-goat Alexa Fluor 488 were used. Finally, the samples were stained with DAPI.

Fluorescence quantification was conducted by segmenting the DAPI channel using QuPath software (version 0.4.3) with the Cellpose extension ( https://github.com/BIOP/qupath-extension-cellpose ). Before segmentation, preprocessing of the DAPI channel was carried out using Fiji software to mitigate background noise, involving background subtraction and enhanced contrast built-in functions.

Preprocessing of the GFP and Texas Red channels involved a background subtraction of the mean grey value and two times the standard deviation of an empty region (background noise). The quantification of each channel was conducted using the measurement function of Fiji software, utilizing the mask generated by Qupath.

Flow cytometry and monoclonal antibodies

Cells were isolated from the hind paw ankle joint of arthritic mice using the protocol previously described 20 . Peripheral blood was collected by cardiac puncture or tail nicking in the presence of EDTA and red blood cell lysis performed using PharmLyse (BD Biosciences). Single-cell suspensions were stained with fixable viability dye eFluor 780 (eBioscience) and further stained with conjugated antibodies for same-day acquisition or fixed in 2% PFA. Conjugated antibodies used in these experiments included: anti-CD45-FITC (clone 102), anti-CD45-PerCP-cyanine5.5 (clone 102), anti-CD11b-BUV395 (clone M1/70), anti-CD11b-PE-Cy7 (clone M1/70), anti-GR-1-APC (clone RB6-8C5), anti-MHC-II-FITC (clone 2G9), anti-MHC-II-BUV496 (clone 2G9), anti-C5aR-BV510 (clone 20/70), anti-Ly6G-BV421 (clone 1A8), anti-Ly6G-Spark Blue 550 (clone 1A8), anti-Ly6G-APC (clone 1A8), anti-CD62L-BV510 (clone MEL-14), anti-CD18-BV650 (clone C71/16), anti-CD18-APC (H155-78), anti-F4/80-AF700 (clone BM8), anti-F4/80-PE-Cy7 (clone BM8), anti-Ly6C-PE-Cy7 (clone HK1.4), anti-Ly6C-Brilliant Violet 570 (clone HK1.4), anti-CCR1-PE (clone 643854), anti-CXCR2-APC (clone SA045E1), anti-CD11c-BV711 (clone HL3), anti-B220-BV605 (clone RA3-6B2) and anti-CD3-Alexa Fluor 647 (clone 17A2). All were purchased commercially from eBioscience, R&D systems or BioLegend and used diluted 1:600. Anti-mCLEC12A-biotinylated 21 , anti-hCLEC12A 63 and isotype control AFRC MAC 49 (ECACC 85060404; isotype for anti-MICL) were generated in-house and used at 10 μg ml −1 . Anti-mCLEC12A-biotinylated 21 and anti-hCLEC12A 63 antibodies were validated using mouse and human CLEC12A-transduced NIH3T3 fibroblast (originally purchased from the ATCC; not tested for Mycoplasma contamination for the experiments detailed in this paper). Cells were acquired using a BD LSR II Fortessa flow cytometer (BD Biosciences), BD LSRFortessa X-20 flow cytometer (BD Biosciences) or Cytek Aurora Spectral cytometer (Cytek). See Extended Data Fig. 1b for the cellular gating strategy. Data were collected using BD FACSDiva v8.0.3 (BD Biosciences) or SpectroFlo software v3.2.1 (Cytek) and analysed using FlowJo v10 software (BD Biosciences).

Imaging flow cytometry

Single cells isolated from the arthritic joint, as detailed above, were fixed in 1% PFA for 30 min at 37 °C. Cells were washed with PBS 2 mM EDTA for 5 min at 500 g and stained with conjugated antibodies (detailed above), anti-DNA/histone 1 (Merck Millipore; 1.4 μg ml −1 ) and anti-cit-H3 (Abcam; diluted 1:300) for 1 h at room temperature. The secondary antibodies goat anti-rabbit APC (Molecular probes) and goat anti-mouse AF488 (Invitrogen) at 1 μg ml −1 were added for 1 h at 4 °C. Cells were washed and resuspended in 50 μl of PBS 2 mM EDTA before acquisition using the Amnis ImageStreamX MKII (Luminex) INSPIRE acquisition software. Files were analysed using IDEAS software v6.2 (Luminex).

Single cells were selected by plotting the area feature of brightfield channel 1 (BF1) versus the aspect ratio parameter of the same brightfield channel, which is the ratio of minor axis to the major axis of the applied mask, and describes the shape of the mask applied to the cells (Extended Data Fig. 7f ). Focused cells were then selected by plotting the ‘Gradient RMS’ feature of BF1 against the BF1 contrast parameter. Cells with high-gradient and high-contrast value were more in focus and chosen for further analysis. All focused cells were used in the analysis for the presence of the cellular fluorescence parameters. Fluorescence parameters were measured in channel 2 (DNA/histone H1-AF488), channel 11 (cit-H3-APC) and channel 7 (Ly6G-BV421) with magnification set to ×40.

Serum collection from patients with rheumatoid arthritis

Serum samples from patients with rheumatoid arthritis were obtained from the SERA cohort 42 (Extended Data Table 1 ). Sera from healthy controls were obtained by collection of whole blood in a BD vacutainer serum collection tube (BD Biosciences). The blood was allowed to clot for 15–30 min at room temperature, after which the tubes were centrifuged at 2,000 g for 10 min in a 4 °C. Sera were removed, aliquoted and stored at −80 °C. Serum samples were obtained from consenting healthy donors with the approval of the College of Life Sciences and Medicine ethics review board, University of Aberdeen (CERB number 1243).

Serum collection from patients with COVID-19

Blood from 121 patients diagnosed with SARS-CoV-2 infection at Weill-Cornell Medicine between March and July 2020. Research on patients with COVID-19 was reviewed and approved by the Institutional Review Board of Weill-Cornell Medicine (New York Presbyterian and Lower Manhattan hospitals; #IRB 20-03021645 and #IRB 20-03021671). Informed consents were obtained from all enrolled patients and health-care workers by trained staff, and records were maintained in our research database for the duration of the study. All patients were classified as mild/moderate ( n  = 25) and severe ( n  = 66) disease according to oxygen requirements with mild/moderate disease defined as SARS-CoV-2 infection and less than 6 l of non-invasive supplementary oxygen to maintain SpO2 > 92%, and severe disease was defined as SARS-CoV-2 infection requiring hospitalization and received 6 l or more supplementary oxygen or mechanical ventilation. For controls, we used blood samples from 36 SARS-CoV-2-negative individuals collected by the JRI IBD Live Cell Bank Consortium at Weill-Cornell Medicine. Heparinized plasma and serum samples were aliquoted, heat-inactivated at 56 °C for 1 h and then stored at −80 °C.

Serum collection from patients with SLE

All patients with SLE in the study met the revised American College of Rheumatology criteria 64 and the SLICC criteria 65 . Some patients had a history of biopsy-proven nephritis according to the International Society of Nephrology/Renal Pathology Society classification. Healthy female volunteers (with no family history of autoimmune disease) served as age-matched and ethnicity-matched controls. All patients provided informed consent, and samples used in this research project were obtained from the Imperial College Healthcare Tissue Bank (ICHTB). The ICHTB is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Imperial College Healthcare NHS Trust and Imperial College London. The ICHTB is approved by Wales REC3 to release human material for research (22/WA/0214), and the samples for this project (ref: R13010a) were issued from sub-collection reference number IMM_MB_13_001.

ELISAs from human patients

Sera from patients with rheumatoid arthritis, COVID-19 and SLE and healthy controls were screened for the presence of MICL autoantibodies using a modified ELISA method 25 . In brief, Nunc Maxisorp 96-well plates were coated with equivalent amounts of the Fc-fusion proteins Fc–hMICL and Fc–mCLEC12B diluted in PBS overnight at 4 °C. Plates were blocked with 10% BSA and 10% HI goat serum (Merck) in PBS for 1 h. Sera from patients with rheumatoid arthritis, COVID-19 and SLE and healthy control were diluted to a 1:256 dilution in PBS and added to the pre-blocked plate and incubated for 2 h. Bound autoantibodies were detected with horseradish peroxidase-conjugated goat anti-human F(ab′)2 fragment (Jackson Immunoresearch) diluted 1:50,000 in PBS for 1 h. TMB substrate was added, and absorbance was measured at 450 nm in a plate reader (Tecan).

A. fumigatus systemic infection model

Micl −/− and C57BL/6J female mice were injected intravenously with 10 6 A. fumigatus ATCC 13073 conidia, as previously described 66 . Mice were culled when they lost 20% body weight or had become moribund. To investigate the role of NET formation, mice were injected i.p. with 4 mg kg −1 daily of GSK484 (Cambridge Biosciences) from day 1 to day 5. Organs were homogenized in PBS and used for the determination of fungal burdens and levels of inflammatory cytokines. Fungal burdens were determined by serial dilution onto potato dextrose agar plates and normalized to organ weights. Cytokines were measured by ELISA (BD Biosciences), as described by the manufacturer, and normalized to protein concentration.

Statistical analysis

Data are represented as mean ± s.d., unless otherwise indicated. All statistical analyses were performed using GraphPad Prism (v9, GraphPad Software) and depicted in the respective figure legends. For all experiments with two groups, two-tailed unpaired Student’s t -tests (equal variances) or two-tailed Mann–Whitney tests were used. One-way or two-way ANOVA (with equal variances) with correction for multiple comparisons was performed for experiments with more than two groups. All P  < 0.05 were considered statistically significant.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All data necessary for the conclusions of this study are provided with the paper. Additional data on patients with rheumatoid arthritis are available on request from the SERA and approval by the SERA Access Committee 42 .  Source data are provided with this paper.

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Acknowledgements

We thank the staff of the animal facilities at the University of Aberdeen and the University of Exeter for support and care for animals; C. Paterson from the University of Glasgow for assistance in establishing a Material Transfer Agreement; C. Parkin and D. Thompson for support with microscopy; and M. Stacey for valuable input. We acknowledge funding from the Wellcome Trust (102705 and 097377), Versus Arthritis (21164, 20775 and 21156), the US National Institutes of Health (R01DK121977 and R01AI163007), Versus Arthritis Centre of Excellence, Medical Research Council (MR/L020211/1) and the MRC Centre for Medical Mycology (MR/N006364/1). SLE tissue samples were provided by the Imperial College Healthcare Tissue Bank funded by the National Institute for Health Research (NIHR), Biomedical Research Centre based at the Imperial College Healthcare NHS Trust and Imperial College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

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Contributions

G.D.B., J.A.W., M.M. and L.W. conceived and designed the study and guided the interpretation of the results. M.M. and L.W. performed the majority of the experiments and data analysis. F.C., A.J.R., I.M.D., A.P.-B., F.S., R.S., E.A.S., C.R., P.L.M., P.R., D.S., R.Y. and D.M.R. assisted with experiments. P.Z. performed CRISPR-mediated knockout of haematopoietic stem cells. F.P. and T.B. performed microscopy experiments and analysis. J.H. provided support with animal experiments. A.McIntosh, A.McConnachie, T.K., I.D.I., I.B.M., M.B. and M.C.P. provided the human patient data and analysis. C.D.B., M.J.G.F. and B.A. provided critical conceptual input and reagents. R.A. and D.R.B. provided reagents. M.M. and G.D.B. wrote the manuscript. All of the authors provided comments on and approved the final version of the manuscript.

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Extended data figures and tables

Extended data fig. 1 micl regulates inflammation during arthritis..

a , Schematic of the CAIA model and severity scoring shown as mean ± SEM (pooled data from three independent experiments, n = 16 biologically independent mice) assessed over time. Statistical significance was determined by two-way ANOVA with Bonferroni’s multiple comparisons test. Schematic in panel a was created using BioRender ( https://biorender.com ). b , Flow cytometry gating strategy used for characterisation of the ankle joint cellular infiltrate. Cells isolated from the inflamed joint were first gated to identify single viable cells using a fixable viability dye. CD11b + populations were further gated into subsets namely; neutrophils (Ly6G + CD11b + ) and Ly6C high cells (Ly6C high F4/80 + CD11b + ) or Ly6C low cells (Ly6C low F4/80 + CD11b + ). Antigen presenting cells (APCs) were gated as MHC II + CD11b + . c , Neutrophils and Ly6C high (defined as shown in the gating strategy in Extended Data Fig. 1b ) in the ankle joint during CAIA at day 5 are represented as a percentage of total live cells (n = 1 experiment with 6 mice/group). Statistical significance determined by two-way ANOVA with Bonferroni’s multiple comparisons test. WT, wild-type mice; * p  < 0.05.

Extended Data Fig. 2 MICL is required for controling neutrophil responses during arthritis.

a , Schematic of K/BxN serum transfer model and severity scoring shown as mean ± SD analysed over time. b , Total live cell populations (defined by gating strategy in Extended Data Fig. 1b ) isolated from inflamed joints on day 10, mean ± SD. Neutrophils WT vs MICL −/− p  = 0.0086. a , b , Data is a representative example of three independent experiments, with 4 mice/group/experiment, and analysed using two-way ANOVA with Bonferroni’s multiple comparisons test. Schematic in panel a was created using BioRender ( https://biorender.com ). c , d , tSNE plots of CD45 + myeloid populations displayed as neutrophils (blue), Ly6C high cells (green), Ly6C low cells (orange), antigen presenting cells (APCs) (pale violet), and all other subpopulation (grey) in the bone marrow ( c ), and blood ( d ) of naïve mice. Data is a representative example of three independent experiments, with 4 mice/group/experiment, represented as mean ± SD. e , f , Fold change in mean fluorescent intensity (MFI), relative to wild-type mice of ( e ) neutrophil activation markers (CD11b, CD18, CD62L) and ( f ) chemokine receptors (CXCR2, CCR1, C5aR), isolated concomitantly from joints or blood of arthritic mice during CAIA on day 7 (pooled data from two independent, n = 10 biologically independent mice). g , Fold change in mean fluorescence intensity (MFI) on neutrophils, relative to wild-type mice of CD11b, CD18, CD62L and CCR1, isolated from the joints of arthritic mice on day 10. Data is a representative example of n = 3 independent experiments with 4 mice/group/experiment, shown as mean ± SD and analysed using two-way ANOVA with Bonferroni’s multiple comparisons test. h , j , Fold change in mean fluorescent intensity (MFI) relative to wild-type mice of neutrophil activation markers (CD11b, CD18, CD62L) and chemokine receptors (CXCR2, CCR1), isolated concomitantly from bone marrow ( h ) and blood ( j ) of naïve mice (representative example of n = 2 experiments with 5 mice/group/experiment). WT, wild-type mice; KO, MICL −/− mice; * p  < 0.05; ns, not significant.

Extended Data Fig. 3 Neutrophil depletion reduces inflammation in WT and MICL −/− mice during arthritis.

a , Flow cytometry gating strategy used to confirm αLy6G antibody-mediated neutrophil depletion in CAIA model at day 9. Neutrophils were identified as CD45 + CD11b + SSC high cells. b , Schematic representation of the αGR-1-mediated neutrophil depletion strategy in the CAIA model. Schematic in panel b was created using BioRender ( https://biorender.com ). c , Flow cytometry contour plot-illustrating depletion of peripheral blood neutrophils 48 h post-injection with αGR-1. d , Severity scoring of WT and KO mice treated with isotype or αGR-1 antibodies, as indicated (pooled data from two independent experiments, n = 12 biologically independent mice). Data is represented as mean ± SEM. e , Quantification of neutrophils (CD45 + CD11b + SSC hi ) and monocytes (CD45 + CD11b + F4/80 + ) in the peripheral blood on day 11. n  = 4 (neutrophils) or n  = 3 (monocytes) biologically independent mice represented as mean ± SD. f , Contour plot showing purity of neutrophils after bone marrow isolation. g , Pseudo-colour plot illustrating endogenous and cell-tracker labelled, adoptively transferred CD45 + CD11b + Ly6G + neutrophils in the joint at day 9 (48 h post-transfer).WT, wild-type mice; KO, MICL −/− mice; Ab, αGR-1 or isotype; ns, not significant; *, p  < 0.05.

Extended Data Fig. 4 MICL regulates NET formation.

a , Fluorescence of NET-bound Sytox green of MSU or PMA-induced NETs in thioglycollate-elicited neutrophils analysed using a SPARK CYTO reader (Tecan) every 10 min for up to 7 h. Data is a representative example of n = 3 independent experiments, mean ± SD performed in triplicate. b , Representative Sytox green fluorescent (cyan), Draq5 (magenta), and bright field (grey) images of MSU-induced NETs in bone marrow neutrophils isolated from WT and MICL-deficient animals. Cells were stained unfixed. Quantification (as percentage of Sytox green positive cells extruding NETs) shown as mean ± SD, n = 1 experiment performed in triplicate. Statistical significance determined by Student’s t-test. c , Representative Sytox green fluorescent and bright field images of MSU-induced NETs in thioglycollate-elicited neutrophils isolated from MICL-deficient animals with and without DPI pre-treatment. Scale bar = 100 µm. Quantification (mean ± SD) shown right (n = 2 experiments performed in triplicate). Statistical significance determined by Student’s t-test. d , Fluorescence of NET-bound Sytox of MSU-induced NETs in thioglycollate-elicited neutrophils with and without NSC87877 treatment analysed 4 h after stimulation. Pooled data from two independent experiments performed in duplicate represented as mean ± SD. e , Representative confocal immunofluorescence microscopy images of NETs in CAIA WT and MICL −/− synovial sections on day 11 (as per schedule in Extended Data Fig. 1a ). GR-1 (purple), DAPI (blue), Cit-H3 (yellow), and DNA/H1 (green) and quantification of cit-H3/GR-1 area (n = 1 experiment with 3 mice/group). NETs are defined as GR-1+Cit-H3 + DNA/H1+ stained cells. Scale bar = 100 µm. Statistical significance determined by Student’s t-test. f , Representative imaging flow cytometry examples of NET positive (+) and NET negative (−) neutrophils isolated from the ankle joints of mice at day 11 during CAIA. BF, Brightfield; DNA/H1 (green); Ly6G (purple); Cit-H3 (red). *, p  < 0.05.

Extended Data Fig. 5 Neutrophil NET formation drives arthritis disease severity in MICL −/− mice.

a , Representative Sytox green fluorescent and bright field images of MSU-induced NETs in thioglycollate-elicited neutrophils in the presence of 100 μM BB-Cl-amidine or 10 μM GSK484. Scale bar = 200 µm. b , Schematic representation of BB-Cl-amidine treatment regime during CAIA and severity scoring of WT and KO mice during CAIA treated with vehicle or PAD4 inhibitor. Black arrow indicates start of the treatment. Data are represented as mean ± SEM (pooled data from two independent experiments with 5 mice/group/experiment). c , Schematic representation of GSK484 treatment regime during K/BxN serum transfer model and severity scoring of WT and KO mice during K/BxN serum transfer model treated with vehicle or GSK484. Black arrow indicates start of the treatment. Data is a representative example of n = 2 independent experiments, mean ± SD, 5 mice/group/experiment. d , Schematic representation of DNaseI treatment regime and severity scoring of WT and KO mice during CAIA (n = 1 experiment with 6 mice/group). Black arrow indicates start of the treatment. b , c , d , Statistical significance was determined by two-way ANOVA with Tukey’s post hoc test. WT, wild-type mice; KO, MICL −/− mice; ns, not significant; *, p < 0.05. Schematics in panels b – d were created using BioRender ( https://biorender.com ).

Extended Data Fig. 6 Anti-MICL antibodies exacerbate autoinflammatory diseases.

a , ROS generation by MSU (left) or zymosan (right) of neutrophils derived from WT animals in the presence/absence of antibodies targeting MICL (αMICL) depicted as relative light units (RLU) over time. Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. b , Schematic and severity scoring of the GSK484 treatment regime during CAIA in the presence of anti-MICL or isotype control monoclonal antibodies. Severity scoring is shown as mean ± SD, n = 1 experiment with 3 mice/group. c , Schematic, severity scoring and cell recruitment in the inflamed joints at day 35 during CIA model. Severity scoring is shown as mean ± SD, n = 1 experiment with 6 mice/group, myeloid cell populations are represented as a percentage of total live cells. Statistical significance determined by two-way ANOVA with Tukey’s post hoc test. Schematics in panels b , c were created using BioRender ( https://biorender.com ). d , Level of anti-MICL autoantibodies in serum from healthy controls (HC) and RA patients used to stimulate human neutrophils in Fig. 3c . e , ROS generation by MSU of human neutrophils in the presence of serum from SLE patients and healthy controls (HC). Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. f , ROS generation by MSU of human neutrophils in the presence of pooled serum from sCOVID-19 patients and healthy controls (HC). Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. g , ROS generation and area under curve (AUC) of human neutrophils stimulated with MSU in the presence of pooled serum from sCOVID-19 patients pre-incubated with Fc-hMICL or Fc-control. Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. WT, wild-type mice; KO, MICL −/− mice; ns, not significant; *, p < 0.05.

Extended Data Fig. 7 MICL recognizes NETs.

a , NET-bound Sytox green fluorescence of bone marrow-isolated neutrophils stimulated with preformed murine NETs (mNETs). Data is a representative example of n = 3 independent experiments, mean ± SD performed in triplicate. b , Mean fluorescence intensity (MFI) of cit-H3 and MPO (mean ± SD, 3 fields of view per condition) during NET formation in WT or MICL-deficient mNETs-stimulated neutrophils. Statistical significance determined by Student’s t-test. c , ROS production of MICL-deficient neutrophils mNETs-stimulated with or without polyxymin B. Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. d , NET formation and quantification of area under curve (AUC, right) of WT or MICL-deficient mNETs-stimulated neutrophils with GSK484 or DPI. Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. e , Fold change in MFI of MICL expression on cultured neutrophils (CD66b + CD15 + ), relative to human neutrophils treated with negative control scrambled guide RNA. f , ROS production by preformed NETs of human MICL-knockout cultured neutrophils (hKO) or human WT derived from CD34 + haematopoietic progenitors. Data is a representative example of n = 2 independent experiments, mean ± SD performed in triplicate. g , Fc-MICL NET recognition by ELISA in the presence/absence of anti-MICL antibodies. Pooled data represented as mean ± SD of n = 2 independent experiments performed in triplicate. Statistical significance determined by One-way ANOVA and Bonferroni multiple comparison test. h , ROS production of MICL-deficient neutrophils stimulated with untreated NETs, Proteinase K-treated NETs or DNaseI-treated NETs. Data is a representative example of n = 3 independent experiments, mean ± SD performed in triplicate. i , Fc-MICL genomic DNA recognition by ELISA in the presence/absence of anti-MICL antibodies. Pooled data represented as mean ± SD of n = 2 independent experiments performed in triplicate. Statistical significance determined by One-way ANOVA and Bonferroni multiple comparison test. j , Cell free DNA concentration 4 h after NETs or LPS intraperioteneal injection in WT and MICL-deficient animals (n = 1 experiment with 6 animals/group). *, p < 0.05.

Extended Data Fig. 8 MICL regulates NET formation during fungal infection.

a , Representative Sytox green fluorescent (DNA, green) and calcofluor white (blue) images of A. fumigatus -induced NETs in bone marrow neutrophils isolated from WT or MICL-deficient animals and quantification as percentage of neutrophils under NETosis (3 fields of view per condition) at 4 h post-stimulation. Statistical significance determined by student’s t-test. b , Tissue fungal burdens of mice two days after intravenous (i.v) infection with 10 6 A. fumigatus conidia (values shown are mean± SEM of pooled data from two independent experiments, n  = 14 biologically independent mice). c , Survival of mice following i.v infection with 10 6 A. fumigatus conidia and treated with vehicle control (n = 1 experiment with 6 mice/group) analysed by log-rank test. p  = 0.0195. CFU, colony-forming unit. *, p < 0.05.

Extended Data Fig. 9 Proposal model for MICL in NETs recognition.

MICL directly recognizes NETs and this interaction regulates neutrophil activation. In the absence of MICL or in the presence of antibodies targeting this receptor, this interaction fails to occur, generating a positive feedback loop of neutrophil activation that on the one hand increases the severity of autoimmunity, but on the other, increases the ability to resist invasive infections. Diagram was created using BioRender ( https://biorender.com ).

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Malamud, M., Whitehead, L., McIntosh, A. et al. Recognition and control of neutrophil extracellular trap formation by MICL. Nature (2024). https://doi.org/10.1038/s41586-024-07820-3

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DOI : https://doi.org/10.1038/s41586-024-07820-3

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