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Science project, catalase and hydrogen peroxide experiment.

How do living cells interact with the environment around them? All living things possess catalysts , or substances within them that speed up chemical reactions and processes. Enzymes are molecules that enable the chemical reactions that occur in all living things on earth. In this catalase and hydrogen peroxide experiment, we will discover how enzymes act as catalysts by causing chemical reactions to occur more quickly within living things. Using a potato and hydrogen peroxide, we can observe how enzymes like catalase work to perform decomposition , or the breaking down, of other substances. Catalase works to speed up the decomposition of hydrogen peroxide into oxygen and water. We will also test how this process is affected by changes in the temperature of the potato. Is the process faster or slower when compared to the control experiment conducted at room temperature?

What happens when a potato is combined with hydrogen peroxide?

• Hydrogen peroxide
• Small glass beaker or cup
• Divide the potato into three roughly equal sections.
• Keep one section raw and at room temperature.
• Place another section in the freezer for at least 30 minutes.
• Boil the last section for at least 5 minutes.
• Chop and mash a small sample (about a tablespoon) of the room temperature potato and place into beaker or cup.
• Pour enough hydrogen peroxide into the cup so that potato is submerged and observe.
• Repeat steps 5 & 6 with the boiled and frozen potato sections.

Observations & Results

Watch each of the potato/hydrogen peroxide mixtures and record what happens. The bubbling reaction you see is the metabolic process of decomposition , described earlier. This reaction is caused by catalase, an enzyme within the potato. You are observing catalase breaking hydrogen peroxide into oxygen and water. Which potato sample decomposed the most hydrogen peroxide? Which one reacted the least?

You should have noticed that the boiled potato produced little to no bubbles. This is because the heat degraded the catalase enzyme, making it incapable of processing the hydrogen peroxide. The frozen potato should have produced fewer bubbles than the room temperature sample because the cold temperature slowed the catalase enzyme’s ability to decompose the hydrogen peroxide. The room temperature potato produced the most bubbles because catalase works best at a room temperature.

Conclusions

Catalase acts as the catalyzing enzyme in the decomposition of hydrogen peroxide. Nearly all living things possess catalase, including us! This enzyme, like many others, aids in the decomposition of one substance into another. Catalase decomposes, or breaks down, hydrogen peroxide into water and oxygen.

Want to take a closer look? Go further in this experiment by looking at a very small sample of potato combined with hydrogen peroxide under a microscope!

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Investigating an enzyme-controlled reaction: catalase and hydrogen peroxide concentration, class practical or demonstration.

Hydrogen peroxide ( H 2 O 2 ) is a by-product of respiration and is made in all living cells. Hydrogen peroxide is harmful and must be removed as soon as it is produced in the cell. Cells make the enzyme catalase to remove hydrogen peroxide.

This investigation looks at the rate of oxygen production by the catalase in pureed potato as the concentration of hydrogen peroxide varies. The oxygen produced in 30 seconds is collected over water. Then the rate of reaction is calculated.

Lesson organisation

You could run this investigation as a demonstration at two different concentrations, or with groups of students each working with a different concentration of hydrogen peroxide. Individual students may then have time to gather repeat data. Groups of three could work to collect results for 5 different concentrations and rotate the roles of apparatus manipulator, result reader and scribe. Collating and comparing class results allows students to look for anomalous and inconsistent data.

Apparatus and Chemicals

For each group of students:.

Pneumatic trough/ plastic bowl/ access to suitable sink of water

Conical flask, 100 cm 3 , 2

Syringe (2 cm 3 ) to fit the second hole of the rubber bung, 1

Measuring cylinder, 100 cm 3 , 1

Measuring cylinder, 50 cm 3 , 1

Clamp stand, boss and clamp, 2

Stopclock/ stopwatch

For the class – set up by technician/ teacher:

Hydrogen peroxide, range of concentrations, 10 vol, 15 vol, 20 vol, 25 vol, and 30 vol, 2 cm 3 per group of each concentration ( Note 1 )

Pureed potato, fresh, in beaker with syringe to measure at least 20 cm 3 , 20 cm 3 per group per concentration of peroxide investigated ( Note 2 )

Rubber bung, 2-holed, to fit 100 cm 3 conical flasks – delivery tube in one hole (connected to 50 cm rubber tubing)

Health & Safety and Technical notes

Wear eye protection and cover clothing when handling hydrogen peroxide. Wash splashes of pureed potato or peroxide off the skin immediately. Be aware of pressure building up if reaction vessels become blocked. Take care inserting the bung in the conical flask – it needs to be a tight fit, so push and twist the bung in with care.

Read our standard health & safety guidance

1 Hydrogen peroxide: (See CLEAPSS Hazcard) Solutions less than 18 vol are LOW HAZARD. Solutions at concentrations of 18-28 vol are IRRITANT. Take care when removing the cap of the reagent bottle, as gas pressure may have built up inside. Dilute immediately before use and put in a clean brown bottle, because dilution also dilutes the decomposition inhibitor. Keep in brown bottles because hydrogen peroxide degrades faster in the light. Discard all unused solution. Do not return solution to stock bottles, because contaminants may cause decomposition and the stock bottle may explode after a time.

2 Pureed potato may irritate some people’s skin. Make fresh for each lesson, because catalase activity reduces noticeably over 2/3 hours. You might need to add water to make it less viscous and easier to use. Discs of potato react too slowly.

3 If the bubbles from the rubber tubing are too big, insert a glass pipette or glass tubing into the end of the rubber tube.

SAFETY: Wear eye protection and protect clothing from hydrogen peroxide. Rinse splashes of peroxide and pureed potato off the skin as quickly as possible.

Preparation

a Make just enough diluted hydrogen peroxide just before the lesson. Set out in brown bottles ( Note 1 ).

b Make pureed potato fresh for each lesson ( Note 2 ).

c Make up 2-holed bungs as described in apparatus list and in diagram.

Investigation

d Use the large syringe to measure 20 cm 3 pureed potato into the conical flask.

e Put the bung securely in the flask – twist and push carefully.

f Half-fill the trough, bowl or sink with water.

g Fill the 50 cm 3 measuring cylinder with water. Invert it over the trough of water, with the open end under the surface of the water in the bowl, and with the end of the rubber tubing in the measuring cylinder. Clamp in place.

h Measure 2 cm 3 of hydrogen peroxide into the 2 cm 3 syringe. Put the syringe in place in the bung of the flask, but do not push the plunger straight away.

i Check the rubber tube is safely in the measuring cylinder. Push the plunger on the syringe and immediately start the stopclock.

j After 30 seconds, note the volume of oxygen in the measuring cylinder in a suitable table of results. ( Note 3 .)

k Empty and rinse the conical flask. Measure another 20 cm 3 pureed potato into it. Reassemble the apparatus, refill the measuring cylinder, and repeat from g to j with another concentration of hydrogen peroxide. Use a 100 cm 3 measuring cylinder for concentrations of hydrogen peroxide over 20 vol.

l Calculate the rate of oxygen production in cm 3 /s.

m Plot a graph of rate of oxygen production against concentration of hydrogen peroxide.

Teaching notes

Note the units for measuring the concentration of hydrogen peroxide – these are not SI units. 10 vol hydrogen peroxide will produce 10 cm 3 of oxygen from every cm 3 that decomposes.( Note 1 .)

In this procedure, 2 cm 3 of 10 vol hydrogen peroxide will release 20 cm 3 of oxygen if the reaction goes to completion. 2 cm 3 of liquid are added to the flask each time. So if the apparatus is free of leaks, 22 cm 3 of water should be displaced in the measuring cylinder with 10 vol hydrogen peroxide. Oxygen is soluble in water, but dissolves only slowly in water at normal room temperatures.

Use this information as a check on the practical set-up. Values below 22 cm 3 show that oxygen has escaped, or the hydrogen peroxide has not fully reacted, or the hydrogen peroxide concentration is not as expected. Ask students to explain how values over 22 cm 3 could happen.

An error of ± 0.05 cm 3 in measuring out 30 vol hydrogen peroxide could make an error of ± 1.5 cm 3 in oxygen production.

Liver also contains catalase, but handling offal is more controversial with students and introduces a greater hygiene risk. Also, the reaction is so vigorous that bubbles of mixture can carry pieces of liver into the delivery tube.

If collecting the gas over water is complicated, and you have access to a 100 cm 3 gas syringe, you could collect the gas in that instead. Be sure to clamp the gas syringe securely but carefully.

The reaction is exothermic. Students may notice the heat if they put their hands on the conical flask. How will this affect the results?

Health and safety checked, September 2008

http://www.saps.org.uk/secondary/teaching-resources/293-student-sheet-24-microscale-investigations-with-catalase Microscale investigations with catalase – which has been transcribed onto this site at Investigating catalase activity in different plant tissues.

(Website accessed October 2011)

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Testing for catalase enzymes

In association with Nuffield Foundation

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Try this class experiment to detect the presence of enzymes as they catalyse the decomposition of hydrogen peroxide

Enzymes are biological catalysts which increase the speed of a chemical reaction. They are large protein molecules and are very specific to certain reactions. Hydrogen peroxide decomposes slowly in light to produce oxygen and water. The enzyme catalase can speed up (catalyse) this reaction.

In this practical, students investigate the presence of enzymes in liver, potato and celery by detecting the oxygen gas produced when hydrogen peroxide decomposes. The experiment should take no more than 20–30 minutes.

• Eye protection
• Conical flasks, 100 cm 3 , x3
• Measuring cylinder, 25 cm 3
• Bunsen burner
• Wooden splint
• A bucket or bin for disposal of waste materials
• Hydrogen peroxide solution, ‘5 volume’

Health, safety and technical notes

• Read our standard health and safety guidance.
• Wear eye protection throughout. Students must be instructed NOT to taste or eat any of the foods used in the experiment.
• Hydrogen peroxide solution, H 2 O 2 (aq) – see CLEAPSS Hazcard HC050  and CLEAPSS Recipe Book RB045. Hydrogen peroxide solution of ‘5 volume’ concentration is low hazard, but it will probably need to be prepared by dilution of a more concentrated solution which may be hazardous.
• Only small samples of liver, potato and celery are required. These should be prepared for the lesson ready to be used by students. A disposal bin or bucket for used samples should be provided to avoid these being put down the sink.
• Measure 25 cm 3  of hydrogen peroxide solution into each of three conical flasks.
• At the same time, add a small piece of liver to the first flask, a small piece of potato to the second flask, and a small piece of celery to the third flask.
• Hold a glowing splint in the neck of each flask.
• Note the time taken before each glowing splint is relit by the evolved oxygen.
• Dispose of all mixtures into the bucket or bin provided.

Teaching notes

Some vegetarian students may wish to opt out of handling liver samples, and this should be respected.

Before or after the experiment, the term enzyme will need to be introduced. The term may have been met previously in biological topics, but the notion that they act as catalysts and increase the rate of reactions may be new. Similarly their nature as large protein molecules whose catalytic activity can be very specific to certain chemical reactions may be unfamiliar. The name catalase for the enzyme present in all these foodstuffs can be introduced.

To show the similarity between enzymes and chemical catalysts, the teacher may wish to demonstrate (or ask the class to perform as part of the class experiment) the catalytic decomposition of hydrogen peroxide solution by manganese(IV) oxide (HARMFUL – see CLEAPSS Hazcard HC060).

If students have not performed the glowing splint test for oxygen for some time, they may need reminding of how to do so by a quick demonstration by the teacher.

More resources

Add context and inspire your learners with our short career videos showing how chemistry is making a difference .

Additional information

This is a resource from the  Practical Chemistry project , developed by the Nuffield Foundation and the Royal Society of Chemistry.

Practical Chemistry activities accompany  Practical Physics  and  Practical Biology .

© Nuffield Foundation and the Royal Society of Chemistry

• 11-14 years
• 14-16 years
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Specification

• Enzymes act as catalysts in biological systems.
• Factors which affect the rates of chemical reactions include: the concentrations of reactants in solution, the pressure of reacting gases, the surface area of solid reactants, the temperature and the presence of catalysts.
• Describe the characteristics of catalysts and their effect on rates of reaction.
• Recall that enzymes act as catalysts in biological systems.
• 7.6 Describe a catalyst as a substance that speeds up the rate of a reaction without altering the products of the reaction, being itself unchanged chemically and in mass at the end of the reaction
• 7.8 Recall that enzymes are biological catalysts and that enzymes are used in the production of alcoholic drinks
• C6.2.4 describe the characteristics of catalysts and their effect on rates of reaction
• C6.2.5 identify catalysts in reactions
• C6.2.14 describe the use of enzymes as catalysts in biological systems and some industrial processes
• C5.2f describe the characteristics of catalysts and their effect on rates of reaction
• C5.2i recall that enzymes act as catalysts in biological systems
• C6.2.13 describe the use of enzymes as catalysts in biological systems and some industrial processes
• C5.1f describe the characteristics of catalysts and their effect on rates of reaction
• C5.1i recall that enzymes act as catalysts in biological systems
• B2.24 The action of a catalyst, in terms of providing an alternative pathway with a lower activation energy.
• 2.3.5 demonstrate knowledge and understanding that a catalyst is a substance which increases the rate of a reaction without being used up and recall that transition metals and their compounds are often used as catalysts;
• 7. Investigate the effect of a number of variables on the rate of chemical reactions including the production of common gases and biochemical reactions.

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Catalase Enzyme Lab

A common enzyme lab for students to measure the impact of temperature and pH on the efficiency of catalase. Catalase is an enzyme is found in almost all living organisms that breaks down hydrogen peroxide (H 2 O 2 ) into oxygen and water. Many teachers use raw chicken liver or potato as the source of the catalase. I’ve done both and frankly potato is less stinky and is easier to clean up after. Here is the gist of the lab:

• Students will need: potato puree, tweezers, a beaker full of hydrogen peroxide, and a stopwatch.
• Peel a raw potato and cut it into pieces. Place the potato in the blender and add a small amount of water. Puree until smooth. (One large potato should be enough for 1 class period).
• Note: The potato will turn brown relatively quickly as it comes in contact with the air. Don’t worry! This does not impact the results of the experiment.
• Collect the paper discs out of your hole puncher (or hit up the copy center at your school).
• Using tweezers, have students dip a paper disc in the potato puree. Place the paper in the bottom of the beaker of peroxide and start the stopwatch. As the catalase on the paper disc breaks peroxide into oxygen and water, the disc will float. Have students time how long it takes for the paper to rise.
• pH: To show students the impact of pH on enzyme efficiency, have them add a few drops of an acid and a base to the potato purees on a spot plate. Vinegar and bleach are great options. Repeat the experiment and have students determine at which pH catalase works best.
• Option 1: Change the temperature of the peroxide. Place a beaker of peroxide in an ice bath, and another in a warm water bath. This option tends to yield the best results.
• Option 2: Change the temperature of the potato puree. This can be done easily by putting some of the puree in the fridge and some in the microwave (or boil it at home ahead of time). This does not always give the best results because the cold potato can warm up pretty quickly, but still works if you don’t have water baths available.

• Have students do multiple trials (at least 3) and take the average. Sometimes they get weird data, so this helps with accuracy.
• If you are testing multiple variables, have students get fresh peroxide before starting the new variable. For example, have students collect all the temperature data, get fresh peroxide, and then collect pH data.
• If the paper disc takes more than 1 minute to rise, tell students that the enzyme is denatured and they can stop timing and move on to the next trial.
• When I first started doing this lab I used petri dishes for all the potato purees and it was a lot of clean up. I recently switched to chemistry spot plates (pictured above) and it made clean up so much easier!

If you have any additional questions, leave me a comment! ​Rock on,

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Monday, March 5, 2012

Easy enzyme experiment: potato catalase.

67 comments:

Thank you so much, helped a lot in Biology

Glad to have helped!

Catalase is an enzyme that catalyzes the transformation of hydrogen peroxide into water and oxygen. This enzyme functions as a natural antioxidant protecting the cell against oxidative damage. This enzyme finds applications in Research and Clinical Chemistry. It also finds diverse industrial applications in textiles, waste treatment, cosmetics and as a disinfectant agent. catalase

How much potato? How much peroxide? Into what size testube? I would like to run this for a class so Im trying to get all materials together. Also, can I simple grate the potatos ahead of time?

Begin with about 40 grams of peeled potato and blend it in about 100ml of water and ice. Mix this well and add 1 ml to a test tube. Test tubes of 10 to 15ml work well. Add several drops of H2O2 to the potato blend in the bottom of the test tube. Exact amounts do not matter, as long as they are relatively close. Yes, you can mash or blend potatoes ahead of time. Blending works best. I really don't know why I used the word "mash" in this post. Hope this helps. -Matt

Oh-ya, be sure to test this ahead of time and adjust volumes as necessary. The experiment works differently with different potatoes. Error on the side of more potatoes. More potato means more foam.

Thanks. I did a test run this morning with straight potato peelings.Slower reaction but good enough. Started with the liquids first and the dropped in the peels, followed by swirling of the tt to get them to the bottom.My peroxide might be a little dated but 3% and ten minures later the tots were being lifted out of the tubes!

Great! Thanks for letting me know. I never have tried it that way but it sounds extremely easy. I'll have to try your method sometime.

Hi, I have recently done an AS level catalase experiment. We cut out thin discs of potato and put them into a 10cm^3 solution of hydrogen peroxide then measured how long it takes for them to rise to the top. Our independent variable was different concentrations of hydrogen peroxide. Our results showed that as the concentration of H2O2 increased, the rate of reaction increased. I was wondering if you could explain the theory of this. Thanks!

The more substrate(H2O2) for the enzyme to react with the faster the reaction will take place. Higher concentration of H2O2 means there is more substrate for catalase to react with.

Hello, what was your research questionf for it if I may know?¿

If you were to plan an experiment to determine the effect of substrate concentration on enzyme activity. What would you write as the method?

Simply vary the concentration of H2O2, which is the substrate. With store bought H2O2, vary the concentration by adding 100% of the H2O2 to potato extract, 75% H2O2, 50%, 25% and 0%, all to different tubes. Create these various H2O2 concentrations by mixing the H2O2 with water.

Which are the dependent, independent and controlled variables?

Dependent is always going to be bubbles produced when H2O2 is added. The independent variable depends on what type of experiment you are running, it could be H202 concentration, amount of potato, temperature, or pH. Control variables also depend on what type of experiment you are running.

what are the conclusion and discussion?

That entirely depends on how you carry out your experiment.

How much time is needed for this process to occur ?

The reaction happens instantly and only takes a few seconds.

LIFE SAVER!!! had to write a stupid report and didnt have any idea where to begin!

Hi Matt I'm just wondering are there any other conditions we can test on catalase. I mean instead of testing the usual temperature, pH and substrate concentration, are there other conditions that can be manipulated to produce an effect result?

Another condition you can modify is buffer concentration. This can be done simply by modifying NaCl concentration the substrate or enzyme is in.

Yo Matt help mout here why does the bubbles from the oxygen produce remain constant and decrease

Not sure what you mean exactly, but bubbles decrease as the substrate of H2O2 decreases.

hey, I am needing the measurements of your foam in this experiment of a class assignment, I need to compare to a similar experiment I would be very grateful if you could give me your results. cheers

What difference would you expect to see in the experiment using varying temperatures ?

This helped me quite a lot for a Biochemistry that I have to do for school. However, the information on altering the PH levels is rather limited. Would it be possible for you to recommend some online sight where I could find more information on this? Please and thank you in advance :)

hi sir/ma'am, do you mind writing down the materials needed for this experiment and how much is needed for the experiment for it to work effectively as i may be using this experiment for year 12 assessment and i want to make sure it works efficiently. thankyou soo much!

Hello, I am wondering if when adding the baking soda I also have to add some type of liquid to get a reaction. I already know that I'm going to add peroxide to one experiment but for the second one I would like to use baking soda. Let me know, thanks :)

Hi, can I ask something.. Is the rate of enzymatic reaction always directly dependent on the enzymatic concentration? Thank you so much :D

Yes it is, although can also be directly dependent on the temperature of the enzyme and the pH level :)

The results are not able to be measured are they? I need results involving numbers but I really liked the experiment. Is there any way I could do it?

Did you have any sources of error?

hey can you tell me some things that i can put in my discussion?

What are the manipulated results?

Hello! I just want to thank you for uploading this, im supposed to do the lab tomorrow however my teacher refused to help me in any sort of way so thank so much! :D

You know PHEOC? What's the 'Problem' for this lab?

please really want to know the enzymes reaction on prepared potato

why blend the potato? is potato not uniform throughout?

What happens if you add Meat or Something else

This was quite informative :-)

Ayanna, Mickeisha thought that this was not as informative

what are the variables in this experiment

ur stupid I hate school

nu u stupyd

What happens if the oxygen is present? Does it effervesce?

Other than a higher temperature what else will increase the reaction rate?

Why do we cut the potatoes

Why must we cut the potato's

The best results come from fresher potatoes! I cut potato in class as students are ready for the potato.

Will putting, for example: an ammonia solution to lower the pH not affect the reaction of hydrogen peroxide and catalase? And does it matter whether the acidic or basic solution is put in before or after adding the hydrogen peroxide?

what are some experimental sources of error which can occur

thank you so much. however i would like to inquire what happens when three test tubes are set up each containing about three slices of a raw potato and in the first test tube distilled water is added, to the second hydrogen peroxide is added and to the third boiled water is added. what is observed in each test tube and explain each observation. thank you.

Catalase, So how many catalase are there in 1 potato?

Hi Dear, i Like Your Blog Very Much..I see Daily Your Blog ,is A Very Useful For me. Other than tuition, science practical SmartLab also provide full scale Science Lab / Practical lessons for students taking their GCE ’O’ / ‘A’ Level exam Visit Now - http://www.smartlab.com.sg/Tuition/

If I process potatoes in a Green Star twin gear juice extractor, low 110 rpm with minuscule heat generation, where is the catalase found, in the potato juice, in the potato juice starch fallout, or in the potato pulp? Which kind potatoes have the greatest amount of catalase?

We just did a lab on enzyme catalase, and found out that the reaction rate for the cold liver /peroxide has faster reaction compared to the warm liver /peroxide,how is that possible?

Hi! If we ran this experiment, how would we be able to measure the amount of oxygen produced by the reaction the combination of potatoes and hydrogen peroxide produce?

Author doing a great huge job, thx very interesting experiments, if somebody what to get more information about enzyme you can find it here

what experiment should I do to test the effect of a change in substrate concentration on the activity of the enzyme, using potatoes?

Found you via Pinterest. This has become a weekly meal in our house. thanks for the recipe.

What evidence do you have that the enzyme is not changed in the reactions and can be used more than once

Gracias 🙏🏿 a student from starehe girls helped

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High School

Molecular biology.

The structure and function of enzymes is a central theme in cellular and molecular biology. In this laboratory exercise, a crude cell extract is prepared from potatoes.

Activity of the enzyme, catalase [which catalyzes the reaction 2H 2 O 2 (l) → 2H 2 O(l) + O 2 (g)], is then studied using a simple assay for O 2 . To conduct the assay, a filter is soaked in crude potato extract, then transferred to the bottom of a beaker containing hydrogen peroxide. Catalase causes O 2 to collect in the filter, which in turn causes the filter to rise. Students are able to explore the effect of enzyme and/or substrate concentration and pH on the amount of product formed by measuring the time taken for each filter to collect enough oxygen to rise. Students average their results, calculate the inverse of the “time to rise,” and pool the data in order to plot the characteristic curve showing the dependence of enzyme activity on substrate and enzyme concentration.

Catalase Teacher Edition (CIBT)

Catalase Student Edition (CIBT)

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Table 1. Solution concentrations, volumes and observations for Experiment 1: Observing the enzyme reaction.

*The chemical reaction was observed with the introduction of catechol to the potato extract (tube 2).

Table 2. Solution concentrations, volumes and observations for Experiment 2: The effect of substrate concentration on enzyme activity.

*The reaction time for tube 1 was the fastest due to the high substrate concentration and lower dH 2 0 concentration.

Table 3. Solution concentrations, volumes and observations for Experiment 3: The effect of enzyme concentration on enzyme activity.

*Lower Dh20 and higher potato extract concentrations allowed for a faster reaction time

for tube 1.

Table 4. Solution concentrations, Buffer pH, volumes, and observations for Experiment 4: The effect of pH on enzyme activity.

*The reaction rate increased as the pH increased, with a pH of 6 being the best buffer for catechol oxidase activity. Increasing the pH past 6 showed a decrease in the reaction rate.

Table 5. Solution concentrations, temperatures, volumes and observations for Experiment 5: The effect of temperature on enzyme activity.

*The fastest reaction rate was observed at 37°C. The colder the temperature (0°C – 15°C), the slower the reaction rate. Enzyme denaturation was observed at 100°C.

Table 6. Solution concentrations, volumes and observations for Experiment 6: Inhibitor Effects – Inhibiting the Action of Catechol Oxidase

*The fastest, and most pronounced reaction was observed in tube 1 (the solution without phenylthiourea)

Enzyme Lab Discussion

For the first experiment, Observing the Enzyme Reaction, it was hypothesized that the enzyme reaction would only occur in the second test tube due to the fact that it was the only tube to contain both the enzyme and substrate. As expected, the solution in tube 2 was the only solution to show the characteristic yellow-brown pigment of benzoquinone production, which was caused by the potato extract converting its catechol into the new product.

In experiment 2, The Effect of Substrate Concentration on Enzyme activity, the hypothesis was that the tube with the higher substrate concentration would show a faster and more pronounced chemical reaction than the tube with less catechol.

The hypothesis was supported by the fact that the higher catechol concentration in tube 1 allowed for a similar result to tube 2 from experiment 1, the only difference being that the extra 5mL of dH 2 0 diluted some of the yellowish-brown color observed in the first reaction.

While there was a chemical reaction observed in tube 2 (experiment 2), it was much slower (with a translucent peach pigment) due to lower a catechol concentration and a higher dH 2 0 concentration. The higher the concentration of catechol, the more benzoquinone that can be produced.

It was hypothesized in experiment 3, The Effect of Enzyme Concentration on Enzyme Activity, that the higher the concentration of enzyme in the solution, the faster and more pronounced the chemical reaction would be.

This hypothesis was able to be accepted based on the rate at which the tube with the higher potato extract concentration reacted. Tube 1 had 400μL more potato extract and 400μL less dH 2 0 than tube 2. Because enzymes are biological catalysts that speed up chemical reaction time, the solution in tube 1 quickly changed from a bluish-green pigment, to the yellowish-brown color associated with benzoquinone.

The lower concentration of potato extract and a higher concentration of dH20 in tube 2 showed no change in color, other than the cloudiness of the potato extract itself.

In experiment 4, The Effect of pH on Enzyme Activity, the initial hypothesis was that the lower the pH level of the buffer added to the solution, the quicker the reaction rate would be. This hypothesis was not supported by the data observed because higher acidity levels actually slowed the production of benzoquinone – which was the opposite of what was predicted.

The solution with a pH buffer of 4 remained cloudy white, while the solution with a 6 pH buffer turned yellowish-brown. As the pH increased, the benzoquinone production rate increased. While lower pH buffers proved to be too acidic, more neutral buffers allowed for the best environment for catechol oxidase activity.

Buffer pH levels higher than 6 showed a slower and less pronounced chemical reaction as well – illustrating the enzyme reaction’s need for neutrality.

The hypothesis for experiment 5, The Effect on Temperature on Enzyme Activity, was that extremely low temperature would slow the rate of benzoquinone production, while extremely high temperatures would cause the enzymes to denature. This hypothesis was supported by the rate at which the solutions at 0°C – 15°C slowly reacted, and the rate at which the solution at 37°C quickly produced benzoquinone.

After five minutes at each solution’s designated temperature, the colder solutions barely started to change color, while the warmer temperatures quickly reacted – so much so that at 100°C, the enzymes denatured and the solution began to pale in pigment. Colder temperatures slowed the movement of molecules in the solutions, while warmer temperatures (not including 100°C) allowed for a better environment for catechol oxidase activity.

For experiment 6, Inhibitor Effects – Inhibiting the Action of Catechol Oxidase, it was hypothesized that the addition of phenylthiourea (PTU) would keep the enzyme reaction from occurring. The hypothesis was able to be accepted due to the fact that the tubes which contained the PTU showed very little change in pigment.

Tube 1 served as the control, which showed the production of benzoquinone (yellowish-brown color) and allowed for comparison between the three solutions. Considering PTU is a non-competitive inhibitor, tubes 2 and 3 contained solutions that prevented the enzyme from catalyzing the reaction, regardless of whether or not the substrate was bound to the active site.

The only real issue with any of the 6 experiments was the unsupported hypothesis for the Effect of pH on the Enzyme Activity experiment. I must have tied the preservative nature of benzoquinone with how acidic lemon juice keeps apples from turning brown, so I assumed a low pH would increase the reaction rate. In reality, acidity slows the reaction rate – which is why the apples don’t change color.

In conclusion, these experiments have shown that benzoquinone production can only occur with the presence of both an enzyme and substrate. Factors such as substrate and enzyme concentration, pH, temperature, and the presence of noncompetitive inhibitors can affect enzyme reaction. High substrate concentration will allow for greater benzoquinone production, while high enzyme concentration will speed up the reaction rate – and vise versa.

In order for enzyme reaction to rapidly occur, it must be done in an environment where the pH is as close to neutral as possible, with the reaction rate slowing in both highly acidic or basic solutions. The same goes for temperature – extremely high or extremely cold temperatures can decrease enzyme reaction rates, or cause the enzymes to denature altogether.

The introduction of a noncompetitive inhibitor (such as phenylthiourea) allows it to bind to the allosteric site on the enzyme, which keeps the reaction from occurring (regardless of the enzyme or substrate concentration).

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Laboratory Manual For SCI103 Biology I at Roxbury Community College

Enzymes are macromolecular biological catalysts. The molecules upon which enzymes may act are called substrates and the enzyme converts the substrates into different molecules known as products. Almost all metabolic processes in the cell need enzyme catalysis in order to occur at rates fast enough to sustain life. Metabolic pathways depend upon enzymes to catalyze individual steps. Enzymes are known to catalyze more than 5,000 biochemical reaction types. Most enzymes are proteins, although a few are catalytic RNA molecules. The latter are called ribozymes. Enzymes’ specificity comes from their unique three-dimensional structures.

Like all catalysts, enzymes increase the reaction rate by lowering its activation energy. Some enzymes can make their conversion of substrate to product occur many millions of times faster. An extreme example is orotidine 5’-phosphate decarboxylase, which allows a reaction that would otherwise take millions of years to occur in milliseconds. Chemically, enzymes are like any catalyst and are not consumed in chemical reactions, nor do they alter the equilibrium of a reaction. Enzymes differ from most other catalysts by being much more specific. Enzyme activity can be affected by other molecules: inhibitors are molecules that decrease enzyme activity, and activators are molecules that increase activity. Many therapeutic drugs and poisons are enzyme inhibitors. An enzyme’s activity decreases markedly outside its optimal temperature and pH.

Some enzymes are used commercially, for example, in the synthesis of antibiotics. Some household products use enzymes to speed up chemical reactions: enzymes in biological washing powders break down protein, starch or fat stains on clothes, and enzymes in meat tenderizer break down proteins into smaller molecules, making the meat easier to chew.

In this laboratory, we will study the effect of temperature, concentration and pH and on the activity of the enzyme catalase. Catalase speeds up the following reaction:

2 H 2 O 2 -> 2 H 2 O + O 2

Hydrogen peroxide is toxic. Cells therefore use catalase to protect themselves. In these experiments, we will use catalase enzyme from potato.

The first experiment will establish that our catalase works (positive control) and that our reagents are not contaminated (negative control).

Hydrogen peroxide will not spontaneously degrade at room temperature in the absence of enzyme. When catalase is added to hydrogen peroxide, the reaction will take place and the oxygen produced will lead to the formation of bubbles in the solution. The height of the bubbles above the solution will be our measure of enzyme activity (Figure 8.2 ).

8.1 Positive and negative controls (Experiment 1)

8.1.1 experimental procedures.

• Obtain and label three 15 ml conical plastic reaction tubes.
• Add 1 ml of potato juice (catalase) to tube 1 (use a plastic transfer pipette).
• Add 4 ml of hydrogen peroxide to tube 1. Swirl well to mix and wait at least 20 seconds for bubbling to develop.
• Use a ruler (Figure 8.1 ) and measure the height of the bubble column above the liquid (in millimeters; use the centimeter scale of the ruler) and record the result in Table 8.1 .
• Add 1 ml of water.
• Add 4 ml of hydrogen peroxide. Swirl well to mix and wait at least 20 seconds.
• Measure the height of the bubble column (in millimeters) and record the result in Table 8.1 .
• Add 1 ml of potato juice (catalase).
• Add 4 ml of sucrose solution. Swirl well to mix; wait 20 seconds.
• Measure the height of the bubble column and record the result in Table 8.1 .

Figure 8.1: A ruler with metric (cm) and imperial (inch) scales.

Figure 8.2: Results from experiment 1. Compare with your results!

8.2 Effect of temperature on enzyme activity (Experiment 2)

8.2.1 experimental procedures.

Before you begin with the actual experiment, write down in your own words the hypothesis for this experiment:

• Obtain and label three tubes.
• Add 1 ml of potato juice (catalase) to each tube.
• Place tube 1 in the refrigerator, tube 2 in a 37 °C (Celsius) heat block, and tube 3 in a 97 °C heat block for 15 minutes.
• Remove the tubes with the potato juice (catalase) from the refrigerator and heat blocks and immediately add 4 ml hydrogen peroxide to each tube.
• Swirl well to mix and wait 20 seconds.
• Measure the height of the bubble column (in millimeters) in each tube and record your observations in Table 8.2 .

Do the data support or contradict your hypothesis?

Figure 8.3: Results from experiment 2. Compare with your results!

8.3 Effect of concentration on enzyme activity (Experiment 3)

8.3.1 experimental procedures.

• Measure the height of the bubble column (in millimeters) and record your observations in Table 8.3 .
• Add 3 ml of potato juice (catalase).

Figure 8.4: Results from experiment 3. Compare with your results!

8.4 Effect of pH on enzyme activity (Experiment 4)

8.4.1 experimental procedures.

• Obtain 6 tubes and label each tube with a number from 1 to 6.
• Place the tubes from left (tube #1) to right (tube #6) in the first row of a test tube rack.
• Add to 1 ml of potato juice (catalase) to each tube.
• Add 2 ml of water to tube 1.
• Add 2 ml of pH buffer 3 to tube 2.
• Add 2 ml of pH buffer 5 to tube 3.
• Add 2 ml of pH buffer 7 to tube 4.
• Add 2 ml of pH buffer 9 to tube 5.
• Add 2 ml of pH buffer 12 to tube 6.
• Add 4 ml of hydrogen peroxide to each of the six tubes.
• Swirl each tube well to mix and wait at least 20 seconds.
• Measure the height of the bubble column (in millimeters) in each tube and record your observations in Table 8.4 .

Figure 8.5: Results from experiment 4. Compare with your results!

Figure 8.6: Catalase activity is dependent on pH. The data shown in this figure were obtained by three groups of students during a previous laboratory session. The triangles represent the data from the experimental results shown in Figure 8.5 .

8.5 Cleaning up

• Empty the contents of the plastic tubes into the labeled waste container (brown bottle) in the chemical fume hood.
• Discard the empty tubes and other waste in the regular waste basket.
• Rinse the glass rod and glassware with water and detergent.
• Return the glass ware to the trays on your bench where you originally found them.

8.6 Review Questions

• What is a catalyst?
• What are enzymes?
• What is the name of the enzyme that we studied in this laboratrory session?
• What is an enzyme substrate?
• What is the substrate of the enzyme that we used in this laborator seesion?
• What are the products of the reaction that was catalized by the enzyme that we studied in this laboratory seesion?
• What is the active site of an enzyme?
• What is the purpose of the negative and positive controls?
• State the hypothesis that was tested in experiment 2?
• State the hypothesis that was tested in experiment 3?
• State the hypothesis that was tested in experiment 4?
• The enzyme from potato appeared to work better at 4 °C than at 37 °C. Would you expect the same if we had used the equivalent human enzyme? Justify your answer.
• Why did heating the enzyme at high temperature (> 65 °C) result in loss of activity?

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Manipulating Enzymes: Potato Catalase

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The experiment was performed to precipitate casein from milk and albumin from egg white by denaturation using heat and reducing agents, to detect the presence of proteins and amino acids in the test samples by qualitative color reactions, and to determine the enzyme activity of catalase in raw and cooked tissue samples, and the enzyme activity of bromelain in meat tenderizer and pineapple juice. Casein and Albumin precipitated in the entire test (Table S1) except for the ethanol. This may be due to dependence in temperature. Casein, L-tyrosine, and L-tryptophan gave positive results for Xanthoproteic test with the formation of yellow solution due to nitration of the activated aromatic rings. Albumin and casein gave positive results for Biuret test with the formation of violet colored solution due to the reaction between peptide bonds and copper ions. Albumin, casein and tyrosine gave positive results for Millon's test indicated by the formation of a brick-red precipitate or solution due to the reaction between the nitrated product and mercury ion. The presence of ions disrupts also the 3D structure of a protein. Albumin and cysteine gave positive results for sulfur test indicated by the precipitation of gray lead(II) sulfide in the solution. The darker the shade of the color reactions, the higher the concentration of the protein or the amino acid in the sample. The enzymatic activity of catalase in living tissues (or in raw samples) is higher than the ones in cooked living tissues (or non-living). Enzyme activity can be slowed down at a lower temperature or they can exhibit no activity at all at high temperature because they were already denatured. Concentration is also factor wherein low concentrations of the enzyme in a compound may slow down its catalytic activity. .

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Dean, A-BIO 113 Enzyme Lab Report

08. Investigation into the effect of enzyme or substrate concentration on enzyme activity

• 00:24  Why do you have to grind the potato cells?
• 00:54  How would cell debris on the disc affect the rise time?
• 01:00 What gas is given off by this reaction?
• 01:03  How does this gas affect the density of the paper disc?
• 01:03  What effect does this density change have on the disc rise time?
• 01:05 How can you use this method to investigate the effect of enzyme concentration (mass of potato used) or substrate (H 2 O 2 ) concentration on enzyme activity?

freshly cut potato cylinders

pestle and mortar

specimen tubes / test tubes

stock solution of hydrogen peroxide

filter paper discs

deionised water

paper towel

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• Open access
• Published: 18 June 2024

Enhanced stress resilience in potato by deletion of Parakletos

• Muhammad Awais Zahid   ORCID: orcid.org/0000-0001-7065-5369 1 ,
• Nam Phuong Kieu 1 ,
• Frida Meijer Carlsen   ORCID: orcid.org/0000-0002-9608-0556 2 ,
• Marit Lenman 1 ,
• Naga Charan Konakalla   ORCID: orcid.org/0000-0003-3981-3044 1 ,
• Huanjie Yang 1 ,
• Sunmoon Jyakhwa 1 ,
• Jozef Mravec 2   nAff3 ,
• Ramesh Vetukuri 1   nAff4 ,
• Bent Larsen Petersen   ORCID: orcid.org/0000-0002-2004-9077 2 ,
• Svante Resjö 1 &
• Erik Andreasson   ORCID: orcid.org/0000-0003-0666-7204 1  

Nature Communications volume  15 , Article number:  5224 ( 2024 ) Cite this article

736 Accesses

Metrics details

• Agricultural genetics
• Molecular engineering in plants

Continued climate change impose multiple stressors on crops, including pathogens, salt, and drought, severely impacting agricultural productivity. Innovative solutions are necessary to develop resilient crops. Here, using quantitative potato proteomics, we identify Parakletos, a thylakoid protein that contributes to disease susceptibility. We show that knockout or silencing of Parakletos enhances resistance to oomycete, fungi, bacteria, salt, and drought, whereas its overexpression reduces resistance. In response to biotic stimuli, Parakletos -overexpressing plants exhibit reduced amplitude of reactive oxygen species and Ca 2+ signalling, and silencing Parakletos does the opposite. Parakletos homologues have been identified in all major crops. Consecutive years of field trials demonstrate that Parakletos deletion enhances resistance to Phytophthora infestans and increases yield. These findings demark a susceptibility gene, which can be exploited to enhance crop resilience towards abiotic and biotic stresses in a low-input agriculture.

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Introduction.

As a result of climate change, crops are likely to increasingly encounter biotic and abiotic stresses that negatively impact plant growth and yield that results in losses of billions of dollars 1 . To develop climate-change-resilient crops, it is important to understand plant responses to stress and identify factors that can provide tolerance to both biotic and abiotic stresses 2 .

Plants have evolved sophisticated mechanisms to adapt to environmental changes 3 . These include complex signal transduction pathways involving reactive oxygen species (ROS), calcium (Ca 2+ ), and hormonal signalling, mediated by a network of receptors and other regulatory proteins 4 . A critical aspect of the plant immune response is pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI), which relies on the perception of PAMPs via pattern-recognition receptors (PRRs) 5 . For example, Arabidopsis recognises flg22 (a 22-amino-acid epitope of bacterial flagellin) by PRR FLS2, which encodes a leucine-rich repeat receptor kinase (LRR-RK) 6 . This recognition activates parallel signalling pathways involving secondary messengers, such as ROS and Ca 2+ , which trigger transcriptional changes 7 .

Perception of biotic stimuli leads to biphasic ROS accumulation in two oxidative bursts. The first rapid ROS burst occurs within a few minutes after stress detection and is mainly generated by plasma-membrane-bound NADPH respiratory burst oxidase homologs (RBOHs) 8 . The second ROS burst, mainly contributed by the chloroplasts, is initiated within hours of stress perception 9 , 10 . Ca 2+ bursts help to propagate intracellular signals and are essential for PAMP-induced ROS production 7 , 11 . Chloroplast-mediated signalling pathways play key roles in generating ROS and Ca 2+ bursts; biosynthesis of phytohormones, such as salicylic acid (SA); and retrograde signaling 9 , 11 . The thylakoid-membrane-associated calcium-sensing receptor (CAS) plays a crucial role in these processes, including PTI-induced transcriptional induction, SA biosynthesis, and both bacterial as well as fungal resistance 12 , 13 , 14 . For example, pathogen effectors can modulate CAS activity in chloroplasts to suppress plant immune responses 15 . CAS also plays an important role in plant responses to abiotic stimuli 14 . Expression of  rice CAS increases drought stress and preventing drought-induced reduction of photosynthetic efficiency in Arabidopsis  16 .

It is becoming evident that immune signalling and abiotic stress responses overlap 17 , 18 . There is a need to elucidate the factors controlling biotic and abiotic stress signalling in plants and to identify factors that may confer broad-spectrum resistance to develop sustainable control strategies for agriculture. One such strategy, whose practical implementation in agriculture has been aided by advances in CRISPR technology 19 , involves disrupting the expression of susceptibility (S) genes, i.e., plant genes that facilitate pathogen infection 20 .

Here, to assist in the improvement of crop resilience, we examine the immune response of the agriculturally important crop potato by performing quantitative proteomic analysis. We identify a protein (dubbed Parakletos, an ancient Greek word meaning helper, which is chosen because the protein itself has no obvious functional domains), and demonstrate its importance in plant stress responses. Its overexpression in Nicotiana benthamiana reduces the intensity of flg22-induced ROS bursts and Ca 2+ bursts, whereas its silencing has the opposite effect, inducing over-expression of several defence-related genes after stress. Moreover, parakletos -knockout (KO) potato lines and parakletos -silenced N. benthamiana plants show increased resistance to several pathogens and improved tolerance to salt and drought stresses. Overall, our results indicate that Parakletos is a negative regulator of plant stress responses. In addition, Parakletos homologs are identified in all main crop plants, including wheat, rice and maize, suggesting that knocking it out could be a valuable tool for developing more resistant crops.

Changes in abundance of potato proteins

In order to find breeding targets towards stress mitigation, we analysed changes in protein abundance in potato leaves in response to treatment with disarmed Agrobacterium tumefacien s (as compared to a control treatment with infiltration medium only), using a precursor intensity-based proteomics analysis (Supplementary Fig.  1a ). After subcellular fractionation to reduce RuBisCo content, we identified and quantified 2178 proteins. Of these, 114 proteins increased significantly ( p  < 0.05) in abundance, and 51 decreased in abundance (Supplementary Data  1 ). Table  1 shows the 10 proteins exhibiting the highest changes in abundance. The proteins that increased in abundance included a plastocyanin and photosystem II reaction center protein L (PSII-L), and proteins decreased in abundance included MAPKs, histone H2B, and a hexose transporter.

Functional test of candidate proteins identifies Parakletos

To assess the functional significance of the above findings, we analysed our dataset to identify potential immune response proteins. Five candidates were selected based on the criteria that each exhibited pronounced changes in abundance following treatment with disarmed A. tumefaciens and small gene family size. Homologs of the candidates in N. benthamiana were then identified. To assess their importance in plant immunity, the candidates were either transiently expressed or silenced in N. benthamiana plants that were subsequently infected with Phytophthora infestans (Table  2 ). Of the candidates selected for functional validation was a small protein M1CUF4, which was named as Parakletos. Overexpression of Parakletos increased P. infestans infection severity in terms of lesion diameter, sporangia counts, and increased P. infestans biomass, while its silencing showed the reversed phenotype (Fig.  1a, b and Supplementary Fig.  1b–d ). Parakletos showed no significant homology to any known domains or proteins, and has no functional data described in any system. However, localisation prediction algorithms 21 suggested that Parakletos contains both a chloroplast transfer peptide and a thylakoid luminal transfer peptide (Fig.  1c ). To confirm the predicted subcellular localisation of Parakletos, we constructed a Parakletos C-terminal fusion with mCherry and transiently expressed it in N. benthamiana . As expected, immunoblotting after thylakoid-fractionation indicating localisation in the thylakoid (Fig.  1d ) and confocal imaging showed that Parakletos was only localised in chloroplasts (Fig.  1e ). Furthermore, confocal microscopy and immunoblotting experiments indicated a rapid and transient reduction in Parakletos protein levels following flg22 treatment in N. benthamiana and potato (Fig.  1e, f and Supplementary Fig.  1e, f ). A decline in Parakletos protein was also observed post P. infestans inoculation, followed by an increase (Supplementary Fig.  1g ). Additionally, by immunoblotting, an elevation in Parakletos protein levels was detected 18 hours after Agrobacterium infiltration (Supplementary Fig.  1h ), corroborating the proteomic data. The three mass spectrometry peptides of Parakletos from the proteomics data and the conservation of the mature protein in the four potato alleles and N. benthamiana in Parakletos are shown in Fig.  1c . An alignment of sequences homologous to Parakletos indicates that all major crop plants examined contain this gene (Fig.  1g and Supplementary Fig.  1i ).

a Phytophthora infestans infection assay on Nicotiana benthamiana leaves infiltrated with disarmed Agrobacterium carrying Parakletos overexpression ( Parakletos -OE) vector or empty vector (EV). b N. benthamiana leaves post-silencing using virus-induced gene silencing (VIGS) with TRV2: GFP or TRV2: Parakletos constructs. Exact p -values determined by two-tailed Student’s t -test in a, b compared to control plants; box plots shown ( n  = 24, n=biological replicates). The centerline in box plots indicate medians, the + sign indicates the mean, the box borders delimit the lower and upper quartiles, and the whiskers show the highest and lowest data points. c , Sequence of Parakletos protein, including all four Désirée alleles, aligned with N. benthamiana homolog. d Immunoblot analysis showing localisation of Parakletos-mCherry fusion protein. e Confocal microscopy images of Parakletos-mCherry in N. benthamiana leaves at 0, 20, and 120 minutes post-treatment with flg22 (1 μM). f Immunoblot analysis of total protein (Parakletos-mCherry) in N. benthamiana , with and without flg22 treatment (1 μM at 0 h, 20 min, and 120 min). g Phylogenetic tree of putative plant Parakletos proteins, constructed using MEGA 11 software based on full-length sequences. All experiments were replicated thrice with similar results. Source data are provided as a Source Data file.

Parakletos negatively regulates ROS, calcium bursts and defence-related gene transcription

The silencing of Parakletos and the transient decline in Parakletos protein abundance following flg22 and P. infestans treatment triggered us to test whether the temporary suppression of Parakletos may coincide with the accumulation of secondary messengers in the signalling pathway. To investigate this phenomenon, we monitored changes in the concentrations of two primary secondary messengers, ROS and Ca 2+ , in N. benthamiana plants where Parakletos was either overexpressed or silenced, following flg22 treatment. Parakletos overexpression significantly weakened the amplitude of the first flg22-induced ROS burst (Fig.  2a ), while its silencing enhanced it (Fig.  2b ). Flg22 induction and ROS assays showed that expression of Parakletos -mCherry resulted in weaker ROS bursts than in control (mCherry-Empty vector [EV]) plants, confirming that the fusion protein was active (Supplementary Fig.  2a ). A second ROS burst initiated after about 120 minutes, was also stronger in Parakletos -silenced plants than in controls (Fig.  2c ). Moreover, expression of the RBOHB gene, which encodes a ROS-generating enzyme, increased in TRV2: Parakletos plants (Fig.  2d ). Similarly, the flg22-induced Ca 2+ bursts were less intense in Parakletos -overexpressing plants and more intense in Parakletos -silenced plants (Fig.  2e , f). These findings suggest that Parakletos is a suppressor of immunity-related ROS and Ca 2+ signalling.

a, b ROS production in response to flg22 (1 μM) in Nicotiana benthamiana plants transiently expressing Parakletos, or in silenced plants, measured as total relative light units (RLU). c Elevated second ROS peak in response to 0.1 µM flg22 in Parakletos -silenced plants. d Expression of NbRBOHB (normalized to EF-1α) in Parakletos -silenced plants after infiltration (12 hpi) with flg22 (1 µM) relative to controls. e, f Aequorin (AEQ) was transiently expressed along with Parakletos for over-expression studies or transiently expressed alone in 3-4 week-old silenced plants to monitor cytosolic Ca 2+ bursts in response to flg22 (1 μM). g–i Relative expression levels of ( g ) ICS1 (12hpi), ( h ) PR1 (12 hpi) and ( i ) PTI5 (45 minutes post infiltration) (normalized to EF-1α) were measured in N. benthamiana leaves in which Parakletos was transiently expressed or silenced, with or without flg22 treatment. j , Tetraallelic detection of mutations sizes in CRISPR/Cas9 generated parakletos -KO (knock-out) potato lines (L19, L24, and L32). k , ROS production during the response to flg22 (8 μM) in parakletos -KO potato plants and Désirée-WT (background control). l parakletos -KO potato plants and Désirée-WT were subjected to nitroblue tetrazolium (NBT) staining 2 days post-infection with Phytophthora infestans . m – o Effects of dual Parakletos and CAS silencing in N. benthamiana . m , ROS levels determined in 3–4-week-old silenced plants induced with 1 μM flg22. n , Cytosolic Ca 2+ bursts in response to flg22 (1 μM). o , Lesion diameter (mm) in the Phytophthora infestans infection assays. Data were analyzed by two-tailed Student’s t -tests ( a – i, k,l ) or one-way ANOVA followed by Tukey’s test ( m-o ). Exact p ( a - i, k,j ) or adjusted p ( m-o ) values were shown in figures. Box plots display individual data points for a – i, k – o ( a – c, e, f , n  = 12; d, g – I, n  =  4; k , n  = 8; l , n  = 24; m , n  = 12; n , n  = 8; o , n  = 12, n =biological replicates). The centerline in box plots indicate medians, the + sign indicates the mean, the box borders delimit the lower and upper quartiles, and the whiskers show the highest and lowest data points. All experiments were conducted at least two to three times with similar results. Source data are provided as a Source Data file.

Since responses to P. infestans and flg22 treatment were linked to Parakletos, ROS production, and Ca 2+ levels, we examined changes in the expression of defence-related genes, including isochorismate synthase 1 ( ICS1 ), which is involved in SA biosynthesis 22 , and pathogenesis-related gene 1 ( PR1 ), a common marker for the SA signalling pathway 23 . Treatment with flg22 increased ICS1 and PR1 expression in TRV2: Parakletos plants but had no significant effect on their expression in plants overexpressing Parakletos (Fig.  2g,h ). Silencing or over-expressing Parakletos did not influence ICS1 or PR1 expression without flg22 (Fig.  2g, h ). Additionally, transcript levels of PTI5 , a marker for PAMP-induced responses, increased following flg22 treatment in TRV2: Parakletos plants relative to controls (Fig.  2i ). These results show that flg22 treatment triggered over-induction of several defence-related genes in TRV2: Parakletos plants, which is consistent with their reduced P. infestans infection severity and enhanced ROS and Ca 2+ bursts.

After observing the significant effects of Parakletos manipulation in N. benthamiana i.e. its role in enhancing pathogen resistance and its involvement in stress signalling, we moved back to potato. We aimed to further investigate its role in crop plants and to explore the potential for field trials. To achieve this, we generated parakletos knockout (KO) lines in potato using CRISPR/Cas9 technology. We confirmed full tetra-allelic knockout of parakletos in these lines by Sanger sequencing analyses (Fig.  2j and Supplementary Fig.  3 ). These KO lines exhibited enhanced ROS bursts like those seen in parakletos -silenced N. benthamiana plants (Fig.  2k and Supplementary Fig.  2b ), and NBT staining experiments revealed that their superoxide (O 2 •− , a major ROS) levels increased only after P. infestans inoculation (Fig.  2l and Supplementary Fig.  2c ). Moreover, microscopic examination of sections from NBT-stained leaves showed increased staining in the chloroplasts of Parakletos -KO lines, indicative of elevated chloroplastic ROS (cROS) (Supplementary Fig.  2d ). Furthermore, overexpression of Parakletos-mCherry in potato resulted in less ROS (Supplementary Fig.  2e ). These data indicate that the function of Parakletos is conserved between N. benthamiana and Potato.

We next tested the hypothesis that Parakletos acts in the same pathway as CAS, a thylakoid master regulator of plant immune responses, by silencing their expression individually and jointly (Supplementary Fig.  2f ). The resulting plants were then subjected to ROS and Ca 2+ assays following flg22 exposure and P. infestans infection (Fig.  2m–o ). In accordance with previous described results (Fig.  2b, c ), Parakletos silencing enhanced the flg22-induced first and second ROS bursts. Interestingly, in plants in which both Parakletos and CAS were silenced, the ROS bursts were not significantly stronger than those in TRV2: GFP control or TRV2: CAS plants (Fig.  2m ) but were clearly weaker than in plants in which only Parakletos was silenced. Similar results were found for Ca 2+ assay (Fig.  2n ). Also, P. infestans infection severity was reduced in TRV2: Parakletos plants compared with TRV2: GFP controls, and infection severity in TRV2: Parakletos/CAS and TRV2: CAS plants did not differ significantly from controls (Fig.  2o ). Co-immunoprecipitation experiments showed that Parakletos interacts with CAS, but not with the negative control CPK16 G2A , a mutant which localizes in chloroplasts 12 (Supplementary Fig.  2g ). These findings suggest that Parakletos and CAS are in the same protein complex.

Absence of Parakletos enhances broad-spectrum disease resistance and increases salt and drought stress tolerance

As Parakletos caused changes in conserved stress signalling pathways via ROS and Ca 2+ , we further investigated the effects of various stress conditions on parakletos -KO potato mutants. These mutants were less severely infected by both P. infestans (hemibiotroph) and Alternaria solani (necrotroph) than WT controls (Fig.  3a, b ). We also performed disease assays using the bacterial pathogens Dickeya dantatii (necrotroph) and Pseudomonas syringae pv. tomato DC3000 HopQ1 (hemibiotroph) in Parakletos -silenced N. benthamiana plants. Again, the degree of infection in Parakletos -silenced plants was lower than in controls (Fig.  3c, d ). Finally, salt and drought stress experiments showed that parakletos -KO potato mutants are more tolerant to these stress conditions than controls (Fig.  3e, f and Supplementary Fig.  4a–c ). We also detected no significant differences between parakletos mutants and Désirée-WT controls in terms of plant height, biomass, or other visible traits (Supplementary Fig.  4d ). These results clearly show that Parakletos loss of function increases plant resilience to both biotic and abiotic stress without affecting plant growth under controlled conditions.

a– d , Disease symptoms and infection assays with ( a ) the oomycete pathogen Phytophthora infestans , (b) the fungus Alternaria solani on Parakletos-KO potato plants, and ( c, d ) the bacterial pathogens Dickeya dadantii and Pseudomonas syringae dHopQ in Nicotiana benthamiana parakletos-silenced plants. e , Effect of salt stress (60 mM NaCl) on parakletos -KO plants. f Effect of drought stress (20% PEG) on parakletos -KO plants. Individual data points are plotted as box plots in a– c ( n  = 24), d ( n  = 4), e ( n  = 20) and f ( n  = 12), n =biological replicates. The centerline in box plots indicate medians, the + sign indicates the mean, the box borders delimit the lower and upper quartiles, and the whiskers show the highest and lowest data points. Exact p -values were determined using two-tailed Student’s t -tests on treated plants compared with control plants. Experiments were repeated at least three times with similar results. Source data are provided as a Source Data file.

CRISPR/Cas9 deletion of Parakletos enhances late-blight resistance and yield in the field

Potato late blight, caused by P. infestans , is a major disease that can severely reduce potato yield, and requires intense fungicide treatment to eradicate it. Therefore, after testing Parakletos mutants under controlled conditions, we assessed their growth and resistance to P. infestans in open GM-classified field trials (with no fences) conducted in southern Sweden (Fig.  4a ). Parakletos mutant lines (designated parakletos- 19 and −24) and Désirée-WT controls were cultivated in a random block design with four replicates. We found that the severity of late blight in Parakletos mutant lines was significantly lower than those of the Désirée-WT controls, as indicated by the area under the disease progress curve (AUDPC) (Fig.  4b, c ). In both years of testing, the KO lines showed at least 20% increases in yield compared with Désirée-WT (Fig.  4c ) in plots without fungicide treatments against P. infestans . Furthermore, we observed no significant differences in growth parameters or visible traits between Parakletos mutant lines and Désirée-WT controls, or in other parameters such as quantum yield of PSII (φPSII) and stomatal conductance (mmol m −2 s −1 ) (Fig.  4d and Supplementary Fig.  4e–g ). In parallel trials at the same location, but with standard efficient fungicide treatments (no visible diseases), no significant yield differences were detected between Désirée-WT and the KO lines (Fig.  4e ). These findings indicate that knocking out Parakletos increases resistance to P. infestans resulting in yield increase with no apparent effect on growth and that Parakletos can be a tool for future sustainable agriculture.

a Photograph of potato plants in the field trial at Borgeby, Sweden. b , Representative image of plants naturally infected with Phytophthora infestans in the field. c Untreated plot for late blight, disease incidence based on area under the disease progress curve (AUDPC) for parakletos -KO lines (L19 and L24) compared with Désirée background control for year 2021 and year 2022 and in lower panel tuber yield in tonnes per hectare (ton ha −1 ) in 2021 and 2022. d Physiological parameters of indicated lines in untreated plot for the year 2022: quantum yield of PSII (φPSII) and Stomatal conductance (mmol m −2 s −1 ). e For fungicide-treated plots, tuber yield in tonnes per hectare (ton ha −1 ) obtained at in 2021, 2022, and 2023. Individual data points are plotted as box plots in c – e , with ( c ) year 2021 (Désirée =3, L19 = 4, L24 = 4), year 2022 ( n  = 4), ( d ) n  = 20, and ( e ) year 2021 n  = 2, year 2022 n  = 4, year 2023 n  = 4. The centerline in box plots indicate medians, the + sign indicates the mean, the box borders delimit the lower and upper quartiles, and the whiskers show the highest and lowest data points. Data were analysed by two-tailed Student’s t -test compared with respective control plants, exact p- values were shown in figures. Source data are provided as a Source Data file.

A quantitative proteomic analysis of proteins from potato leaves identified over 100 proteins with abundances that were significantly affected by challenge with disarmed A. tumefaciens (Supplementary Data  1 ), indicating their potential involvement in general plant immune and stress responses. Many of the differentially regulated proteins in our proteomics dataset are related to photosynthesis, which is consistent with the idea that chloroplasts play important roles in coordinating biotic and abiotic stress responses 24 . In addition to photosynthesis, chloroplasts contribute to plant stress resilience by synthesizing hormones, such as SA, and harbouring secondary signalling messengers, including ROS and Ca 2+ 25 .

Screening of candidate proteins in our proteomics dataset revealed a thylakoid protein that we named Parakletos. We showed that Parakletos is a negative regulator of resistance to diverse pathogens, including P. infestans (Figs.  1 a, b and 4a–d ). Over-expressing Parakletos in N. benthamiana increased the severity of infection, while silencing it enhanced resistance; these traits were associated with changes in the amplitude of ROS and Ca 2+ bursts (Fig.  2a–f ). ROS production has been linked to resistance to multiple pathogens, and perception of plant pathogens triggers biphasic ROS bursts 8 . Parakletos silencing enhances the first flg22-induced ROS burst and increases resistance to P. infestans infection. Recently, the gene MKK1 has been shown to negatively regulate PTI by suppressing flg22-induced ROS bursts, thus promoting P. infestans infection 26 . Parakletos silencing also increased the transcription of several defence-related genes after flg22 treatment. One such gene, RBOHB , was more strongly expressed in Parakletos -silenced plants than in controls (Fig.  2d ), suggesting a mechanism by which Parakletos could affect plasma-membrane-related ROS production. However, elevated RBOHB transcript levels are unlikely to affect flg22-induced ROS bursts directly because transcript regulation occurs on a longer timescale than ROS bursts. Besides affecting flg22-induced ROS bursts associated to the plasma membrane, Parakletos -KO plants also exhibited increased cROS following P. infestans inoculation (Supplementary Fig.  2d ). The chloroplast is a main site of ROS production in plant cells and plays an important role in redox homeostasis and retrograde signaling 27 . We also found that expression of the SA-biosynthesis-related gene ICS1 , and the SA signalling pathway marker gene PR1 , is increased in Parakletos -silenced plants (Fig.  2g, h ). This is consistent with previous reports that SA levels are related to broad-spectrum disease resistance 28 , as well as potato resistance to necrotrophic pathogens such as A. solani and Dickeya solani 29 , 30 . Flg22 treatment also increased the expression of a PTI marker gene PTI5 in Parakletos -silenced plants (Fig.  2i ). PTI5 participates in regulation of ROS- and SA-regulated gene expression 31 . Furthermore, elevated SA levels promote ROS accumulation in accordance with our detection of elevated levels of transcripts of both ROS- and SA-related genes in Parakletos -silenced plants following biotic stress 32 , 33 .

The effects of Parakletos silencing on Ca 2+ , ROS, and P. infestans resistance in N. benthamiana were reversed if CAS was also silenced (Fig.  2m–o ). Additionally, we present an indication that CAS and Parakletos may function together within a complex (Supplementary Fig  2g ). Therefore an attractive hypothesis is that Parakletos inhibits CAS function during biotic and abiotic stress, and that the transient reduction in Parakletos levels we observed relieves this repression.

We show that CRISPR/Cas9-mediated KO of parakletos in potato or silencing of Parakletos in N. benthamiana provides broad-spectrum resistance to P. infestans , A. solani, D. dantanii , and P. syringae and enhances plant tolerance towards salt and drought stress under controlled conditions (Fig.  3 ). This is consistent with the effects of other genes that affect the ROS, Ca 2+ , and SA pathways 28 , 34 . However, mitigation of salt and drought stress has not to our knowledge been directly shown with other S genes. Deleting parakletos did not cause a significant growth penalty, and no changes in expression of defence genes were detected in unchallenged plants; thus, we hypothesized that Parakletos only functions under stress conditions, making it a good candidate for use in agricultural contexts. This might make Parakletos a more attractive susceptibility gene than for example DMR6 , which exhibits increased defence gene expression in unchallenged KO plants 28 . Two years of field trials showed that CRISPR/Cas9-mediated parakletos -KO potato plants were significantly more resistant to late-blight disease than controls, increased yield by at least 20 %, and exhibited no detectable growth defects (Fig.  4 and Supplementary Fig.  4e–g ). We emphasize that while parakletos deletion could contribute to late blight protection, it should be considered part of a broader integrated pest management strategy, rather than a standalone solution. This approach not only can extend the effectiveness of existing resistance genes but also provides a valuable defense against other stresses where options for fungicides or resistant genes are limited, including abiotic stress conditions.

A speculation could be that in nature, with a higher degree of competition than in agricultural settings, Parakletos is important in fine-tuning stress responses and thereby reducing the cost of resistance. In contrast, in an agricultural setting, with generally more light and nutrients for each plant, increased transient defence activation could be beneficial, for example, by the mutation of the negative regulator Parakletos. This is in line with the removal of deleterious mutations, which is an important factor in plant domestication 35 . To determine the full agricultural value of Parakletos , field trials should be repeated in several potato genotypes and locations. Also, CRISPR KO experiments targeting Parakletos homologs should be conducted in other crops (Fig.  1g ).

In conclusion, our crop-to-model-to-crop study based on proteomics data identified a defence repressor protein named Parakletos. Parakletos may be classified as a susceptibility gene whose silencing or KO confers broad-spectrum resistance to multiple pathogens and enhances salt and drought stress tolerance without affecting plant growth. Moreover, knocking out this gene using CRISPR/Cas9 conferred resistance to P. infestans in field-grown plants and increased the yield at least 20%. These results illustrate the potential of crop proteomic analysis of general plant immunity in the search for factors that can increase stress resilience and provide valuable tools for low-input agriculture.

Plant material and growth conditions

Nicotiana benthamiana and Solanum tuberosum Désirée plants were cultivated at 20 °C with 14/10 hour light/dark cycles in a controlled environment chamber. The light intensity was kept at 160 μmol m −2 s −1 , and humidity at 65%. Plantlets of N. benthamiana were transplanted into separate pots two weeks after germination and grown for 3-4 weeks. Potato plantlets were transplanted into separate pots and grown for 3-5 weeks.

Plasmid constructs and Parakletos gene sequencing

For over-expression studies candidate genes were amplified by PCR using primers with GATEWAY-compatible attB1 and attB2 tails and recombined, using BP clonase, into pDONR_201 (Life Technologies). Sequenced and selected pENTRY-clones were recombined with the destination vector pK2GW7.0, for gene expression driven by the 35 S CaMV promoter, using LR clonase (Life Technologies). For virus-induced gene silencing (VIGS) studies, the SGN VIGS Tool ( https://vigs.solgenomics.net/ ) was used to select the best target region of each gene. An approximately 300 bp long region of each gene was amplified with PCR using primers containing BsaI overhangs and cloned into Tobacco Rattle Virus (TRV) RNA2 vector pJK037 using BsaI (New England Biolabs) and T7 DNA ligase (New England Biolabs). Constructs for localisation studies were assembled using Gibson Assembly® Cloning Kit (New England BioLabs® Inc). The entry vector pk2GW7.0, and mCherry from pSAT4A-mcherry-N1 ( https://abrc.osu.edu/stocks/number/CD3-1081 ) were amplified by PCR with overhangs compatible for Gibson Assembly®. Potato lines overexpressing parakletos-mCherry or mCherry (EV, ctr) were created with Agrobacterium-mediated transformation 36 . The coding sequence of the potato Parakletos gene was analyzed for possible CRISPR targets and their numbers of off-targets using CRISPOR , and targets with the lowest numbers of potential off-targets were selected. The gRNA spacers were assembled into the Csy4 multi-gRNA vector pDIRECT_22C, using protocol 3A 37 to form the plasmid pDIRECT_22C_StParakletos. Potato parakletos -KO mutant lines were created and verified following the protocol of Kieu et al. 38 . Genomic DNA was prepared from WT and CRISPR-Cas9 mutants and used as a template in PCR using Phusion and two different Parakletos-primer combinations (Supplementary Table  1 ). Products were run on agarose gels. The PCR products were gel extracted and cloned into the pJET system (ThermoFisher). All selected plasmids were Sanger-sequenced (Eurofins).

Protein fractionation and proteomic analysis

Potato plants were infiltrated with either A. tumefaciens or infiltration medium only (control) as described in 39 , 40 . The plants were sampled for protein extraction at 18 hpi (hours post infiltration). Eight biological replicates originating from two independent experiments were processed. Each sample consisted of two stabs from two potato leaflets at 18 hpi, corresponding to 100 mg fresh weight. Each sample was cooled on ice and put in a 1.5 mL Eppendorf tube with sea sand then processed with a Subcellular Protein Fractionation Kit for Tissues (ThermoFisher Scientific; Waltham, MA, USA, Cat. No. 87790) with minor modifications 39 , 40 . Briefly, proteins were consecutively extracted using ice-cold buffers and the final supernatants frozen at –80 °C until further use. The samples were homogenized in buffer 1, passed through a tissue and centrifuged at 500 g for 5 min at 4 °C. The pellet was washed once in buffer 1 and centrifuged. The pellet was re-suspended in buffer 2, vortex-mixed and incubated at 4 °C for 10 min with gentle mixing. After centrifugation at 3000 g for 5 min, the pellet was washed once with buffer 2. Buffer 3 was added to the resulting pellet, and the mixture was vortex-mixed and incubated for 30 min at 4 °C with gentle mixing. After incubation, the sample was centrifuged at 5000 g for 5 min at 4 °C, and the supernatant cleared by re-centrifugation at 16,000 g for 10 min at 4 °C.

Tryptic digestion and mass spectrometry

Proteins were separated on a 14% SDS-PAGE gel. The whole lane was removed and washed, and the proteins were digested using trypsin (Promega Trypsin Gold, Madison, WI, USA). The digests were desalted with C18-based spin columns (The Nest Group, Inc., Southborough, MA, USA) 41 . Samples were analyzed using a Q Exactive mass spectrometer interfaced with an Easy-nLC liquid chromatography system (both supplied by Thermo Fisher Scientific, Waltham, MA, USA). Peptides were analysed using NanoViper Pepmap pre-column (100 μm x 2 cm, particle size 5 μm, Thermo Fischer Scientific) and an in-house packed analytical column (75 μm x 30 cm, particle size 3 μm, Reprosil-Pur C18, Dr. Maisch) using a linear gradient from 7% to 35% B over 75 min followed by an increase to 100% B for 5 min, and 100% B for 10 min at a flow of 300 nL/min. Solvent A was 0.2% formic acid in water and solvent B was 80% acetonitrile, 0.2% formic acid. Precursor ion mass spectra were acquired at 70 K resolution and MS/MS analysis was performed in a data-dependent mode of the 10 most intense precursor ions at 35 K resolution and normalized collision energy setting of 27. Charge states 2 to 6 were selected for fragmentation and dynamic exclusion was set to 30 s.

Peptide data analysis

Raw MS data were converted to Mascot generic file (mgf) format with ProteoWizard, as reported in Resjö et al. 39 . A S. tuberosum protein database from UniProt ( www.uniprot.org ), downloaded on 17 January 2017 and concatenated with a decoy database of equal size (random protein sequences with conserved protein length and amino acid distribution: 106,210 target and decoy protein entries in total) was generated using a modified version of the decoy.pl script from MatrixScience ( http://www.matrixscience.com/help/decoy_help.html ). This database was searched using the mgf files with Mascot version 2.3.01 in the Proteios software environment ( https://proteios.org ). Search tolerances were 7 ppm for precursors and 0.5 Da for MS/MS fragments. One missed cleavage was allowed and carbamidomethylation of cysteine residues was used as a fixed modification and oxidation of methionines as a variable modification. The q -values were calculated using the target-decoy method and the search results were filtered with a threshold peptide-spectrum match q -value of 0.01 to obtain a false discovery rate of 1% in the filtered list. Quantitative peptide analysis, was performed as reported earlier 40 . Normalized peptide data for 24946 identified peptide features was imported into InfernoRDN ( https://omics.pnl.gov/software/InfernoRDN ) and protein intensities were generated using the RRollup procedure. This resulted in quantitative data for 2178 proteins, which was then used in the further analysis. Differential expression was statistically analyzed using Limma 42 , and all p -values were adjusted for multiple comparisons using the Benjamini-Hochberg procedure to calculate the corresponding q -values 43 . A q -value < 0.01 was required for a statistically significant differential expression.

Agrobacterium-mediated transient expression and gene silencing in Nicotiana benthamiana

Transient expression was performedas reported earlier with minor modifications 44 . Briefly, Agrobacterium tumefaciens strain GV2260 harboring binary vector for Parakletos expression or empty vector was grown in LB medium supplemented with antibiotics at 28 °C overnight. Bacteria were pelleted by centrifugation and re-suspended in an infiltration buffer (10 mM MES, 10 mM MgCl 2 , and 150 μM acetosyringone) to an OD600 of 0.1-0.2 and incubated at room temperature in the dark for 2 hours. Four to five weeks old N. benthamiana leaves were infiltrated using a 1 mL needless syringe. VIGS was performed in N. benthamiana , as outlined in reference 45 . Agrobacterium tumefaciens strain GV2260 with binary TRV2: Parakletos or TRV2: GFP plasmid was mixed in infiltration buffer in a 1:1 ratio with bacteria carrying binary plasmid TRV1 at a final OD600 of 0.5. Two weeks old N. benthamiana plants were infiltrated and grown for another 3 weeks in a controlled growth chamber.

Pathogen infection assays

Phytophthora infestans strain 88069 was grown on rye agar media plates and used for infection studies with N. benthamiana and S. tuberosum . Sporangia were collected after 12-14 days and their density was adjusted to 40000 per mL for infecting VIGS-treated N. benthamiana leaves, 25000 per mL for potato leaves and 60000 per mL for leaves subjected to Agrobacterium -mediated transient expression. Portions (10 µL) of sporangia suspension were placed on agro-infiltrated or VIGS-treated N. benthamiana leaves, and 25 µL on potato leaves. The infected plants were then maintained in a clear box with water to maintain 90-100% relative humidity. Infection severity was recorded 4–7 dpi by measurement of lesion diameter 46 . P. infestans biomass was quantified using a CFX96TM Realtime PCR system (Bio-Rad) 47 . Sporangia on 7-day-old leaves, of VIGS- and Agrobacterium -mediated over-expressing plants, were released by vortex-mixing the leaves in 5 mL water and then counted (sporangia/mL) using a haemocytometer. Pseudomonas syringae pv. tomato DC3000 HopQ1 infection assay was performed as reported in Üstün et al 48 ., bacteria was grown at 28 °C in King’s B medium with rifampicin. Bacterial suspensions with an OD600 of 0.0001 were syringe-infiltrated into fully expanded leaves. The resulting bacterial colonies were counted after plate incubation for 1–2 days at 28 °C. Dickeya dadantii infection assay was performed as described in Kieu et al 49 ., and results were recorded by measuring the size of lesions on each leaf at 5dpi. Infection assay for Alternaria solani strain 112 was conducted with results recorded by measuring the size of lesions at 5 dpi 24 .

Subcellular fractionation

Cell fractionation of N. benthamiana leaves, subjected to Agrobacterium -mediated transient expression of Parakletos-mCherry, was performed under very dim light or in darkness at 4 o C 50 , with some modifications. Fresh leaves were ground in 2 mL icecold grinding buffer (50 mM Hepes/KOH (pH 7.5), 330 mM sorbitol, 2 mM EDTA, 1 mM MgCl 2 , 5 mM ascorbate, 0.05% BSA, 10 mM sodium fluoride, 1 mM PMSF and 50 μM NaOV4), filtered through a prewetted 40μm filter and centrifuged at 2400 g for 4 minutes. The pellet was resuspended in 1 mL shock buffer (50 mM Hepes/KOH (pH 7.5), 5 mM sorbitol, 5 mM MgCl 2 , 10 mM sodium fluoride, 1 mM PMSF and 50 μM NaOV4) and centrifuged at 7500 g for 4 min. The supernatant was re-centrifuged for 10 min at maximum speed and samples saved as “stroma fraction”, while the thylakoid pellet was resuspended in 200 μL storage buffer (50 mM Hepes/KOH (pH 7.5), 100 mM sorbitol, 10 mM MgCl 2 , 10 mM sodium fluoride, 1 mM PMSF and 50 μM NaOV4) and 30 μL samples were saved as “thylakoid fraction”. Samples were run on 12% SDS gels and analyzed by western blot using an antibody against mCherry (see Immunoblotting).

ROS measurements

ROS burst were detected in N. benthamiana and S. tuberosum leaf discs (0.125 cm 2 ). Leaf discs were taken from leaves that had been pre-infiltrated (at 24 hpi) or from VIGS/KO plants. To minimize damage, leaf disks were cleaned with water and incubated overnight in wells of 96-well plates containing 200 µL water in the dark. The water was then replaced with 200 µL of solution containing luminol (17 mg/mL) and horseradish peroxidase (10 mg/mL) in sterile water, together with 1 μM synthetic flg22 peptide (QRLSTGSRINSAKDDAAGLQIA). The generation of reactive oxygen species (ROS) was monitored by recording light emitted through the oxidation of luminal in the following 60-240 minutes using a GloMax® Navigator Microplate Luminometer. ROS bursts were defined as amounts of light released during this period, expressed in relative light units (RLU). Nitro blue tetrazolium (NBT) staining was carried out on potato leaves inoculated with or without P. infestans . Leaf dish samples (Φ 12 mm) collected 48 hpi were submerged into 0.2% NBT solution for 30 min and then replaced with 96% ethanol. Heat treatment (90 0 C) was applied to remove chlorophyll pigment rapidly. Pictures were taken and quantified with ImageJ.

Calcium burst measurements

Calcium burst was detected in N. benthamiana leaf discs 12 . For over-expression studies, N. benthamiana plants were transiently co-expressed with aequorin (AEQ) and the construct of interest. Plants used in the VIGS study were transiently expressed only with AEQ. Leaf discs (0.125 cm 2 ) were taken and washed with water and incubated overnight in wells of 96-well plates containing 100 µL of 5 mM coelenterazine (Sigma) in the dark. The leaf discs were treated with a 1 mM flg22 and transient increase in calcium was recorded. Aequorin luminescence was measured with GloMax® Navigator Microplate Luminometer. Ca 2+ bursts were defined as amounts of light released during this period, expressed in relative light units (RLU).

Salt and drought stress

Stem cuttings from potato wild-type (WT) parakletos mutants (L19, 24, 72) were rooted on full strength MS-agar media for 7 days at 20 °C, and then transferred to hydroponics solution (4.3 g basal Murashige & Skoog salt (Duchefa biochemie) in 5 liter, pH 5.8 ± 0.2) with or without supplemented NaCl (60 mM) for salt stress. Likewise, for the drought stress experiment the 7-day rooted plantlets were equilibrated in the hydroponic solution before drought stress treatment in 20% PEG solution (polyethylene glycol 6000, Sigma). After 2 days, the PEG solution were removed, plant roots were washed 4 times with water and plants were keep in hydroponics solution for recovery. The plants were monitored daily to observe stress-induced changes. The fresh weight of WT and mutant plants was measured after 7 days recovery.

Quantitative PCR

Total RNA was extracted from fresh leaf tissues using a Qiagen RNeasy mini kit (Qiagen, Hilden, Germany) following the manufacturer’s recommendations. Nanodrop spectrophotometry was used to quantify RNA. A SuperScript III cDNA Synthesis Kit was used to synthesize cDNA (Thermofisher). The Platinum SYBR Green qPCR SuperMix kit (Thermofisher) was used to conduct qPCR on four biological and three technical replicates. The delta-delta Ct method was used to evaluate all qPCR data using CFX manager, with expression levels normalized to that of the housekeeping gene EF1. The primers to quantify the mRNA from NbEF1, NbICS1, NbPR1, NbrbohB, NbPTI5 and NbCAS are previously published 12 , 51 , rest of the primer details are available in primers list (Supplementary Table  1 ).

Confocal imaging: Agrobacterium GV2260 harboring relevant constructs were grown to a concentration of 0.8 OD600 and infiltrated in leaves (abaxial side) of 4-5 weeks old plants using a blunt 1 mL syringe. Three days post-infiltration, 0.5*0.5 cm leaf slices were cut, mounted in water and immediately examined using a Leica SP5 II confocal microscope equipped with a UV diode (405 nm), argon (488 nm) laser, HeNe (543 nm) laser and an N PLAN 50.0×0.75 BD or HCX PL APO lambda blue 20.0×0.70 IMM UV objective. The discs were sequentially scanned with the following settings, laser intensity 50% and: autofluorescence, 405 nm/emission 430–472 nm; GFP, excitation 488 nm/emission 503–542 nm; mCherry, excitation 543 nm/emission 568–633 nm. All scans were performed at room temperature (20–23 °C). The signals were compared to those from empty vector-infiltrated leaves. The pictures were processed with LAS X (Leica Microsystems) software to generate overlays and enhance contrast/brightness. For flagellin induction 1-3 mL of 1 mM flg22 was infiltrated in the infiltrated areas of the tobacco leaves according to the time schedule. All pictures were treated identically.

Light microscopy: Leaf discs stained with NBT were examined using an inverted bright-field microscope. Images were captured at 400x magnification using a ZEISS Axiocam 503 microscope camera. The stained chloroplasts were analyzed using FIJI Image J software 52 , where stained chloroplasts were selected and quantified by area from the captured images.

Immunoblotting

Leaf material from transiently expressed constructs in N. benthamiana was completely grinded on dry ice using a mortar and pestle. Protein were extracted using cold (PEB) buffer (100 mM Tris, pH 6.8, 10%, glycerol, 0.5%, SDS, 0.1%, Triton X-100, 5 mM EDTA, 10 mM DTT, 5 μL protease inhibitor cocktail (cOmplete™, Sigma)). Samples were centrifuged 10 min at 10.000 rpm and the supernatants kept on ice. Samples were heated to 100 °C for 5 min in Laemmli Sample Buffer (BIO-RAD). Membranes (0.2 µm Nitrocellulose membrane (BIO-RAD)) were in 5% skim milk solution, and the primary antibody (BIO-RAD AHP2326, Polyclonal IgG Goat anti mCherry or Invitrogen- A-11120 GFP Monoclonal Antibody) was used in an overnight incubation 4°C. After washing the secondary antibody, polyclonal rabbit anti-goat immunoglobulins/HRP (DAKO) was added and incubated 1 h under gentle shaking at RT. The membrane was washed three times and developed using SuperSignal® West Dura Extended Duration Substrate (Thermofisher) and visualised on a Universal Hood III (BIO-RAD) apparatus and analysed with the BIO-RAD Image Lab 5.2.1 software.

Co-immunoprecipitation in N. benthamiana

Co‐immunoprecipitation assay was performed as previously reported 53 , 54 with modifications. Briefly, three leaves of 5-week-old N. benthamiana plants were syring-infiltrated with Agrobacterium tumefaciens strain GV3101 expressing CPK16-GFP/CAS-GFP and mCherry/Parakletos-mCherry. Two days later, leaves were cut and ground in liquid nitrogen and homogenized in extraction buffer (50 mM Tris pH 7.5, 150 mM NaCl, 2.5 mM EDTA, 10% glycerol, 1% TritonX-100, 5 mM dithiothreitol, 1% plant protease inhibitor (Sigma, catalogue no. P9599)) (v/v). Proteins were solubilized at 4 °C with gentle agitation for 30 min before filtering through miracloth. The filtrate was centrifuged at 15,000  g for 20 min at 4 °C. An input sample was taken. For immunoprecipitation, 50 μL of GFP-Trap agarose beads (50% slurry, ChromoTek) were added and the mixture was incubated with gentle agitation for 4 h at 4 °C. Beads were harvested by centrifugation at 1,500  g for 2 min and washed three times in extraction buffer. Fifty microlitres of 4× elution buffer (NuPage) were added and incubated at 90 °C for 10 min. The samples were then spun at 13,000  g for 5 min before loading and running on SDS–PAGE and western blot detection with GFP antibody and mCherry antibody (see Immunoblotting).

Phylogenetic analysis of plant Parakletos proteins

Protein sequences were identified by BLASTP using the NCBI (2022/10/30) and Uniprot (2022_11) databases. MEGA 11 was used for the alignment of full-length sequences using MUSCLE 55 . The evolutionary history was inferred by using the Maximum Likelihood method and JTT matrix-based model. The robustness of different nodes was assessed by bootstrap analysis using 1000 replicates.

Field trials

Field trials of genetically modified potato plants were conducted at an established field station in Borgeby, southern Sweden, located at 55°45'12.6“N 13°03'10.7“E. Permission for these trials was granted by the Swedish Board of Agriculture (Dnr 4.6.18-01726/2020). Utilizing a randomized block design, the trials consisted of four replicates, with each replicate comprising a row of ten plants. We carried out fungicide treated and untreated trials in parallel. The trials followed the procedures outlined in reference 56 . Throughout the trials, there was adherence to the ‘Environmental Code’ (1998:808), the Swedish Board of Agriculture’s Code of Regulations (SJVFS 2003:5), and the Regulation 2002:1086 regarding the deliberate release of GMOs into the environment.

Late blight disease incidence based on area under the disease progress curve (AUDPC) was calculated 57 from disease scoring from mid-June until 19 th of august for year 2021 and from mid-June until 8 th of august for year 2022. Both trails were sprayed against aphids with Fibro (paraffin oil) once per week, and once with the insecticide Teppiki. The fungicide-treated trial were treated with recommended doses of Revus (three times), followed by Ranman Top (two times), Infinito (two-four times) and Ranman Top (two times). All treatments were according to the manufacturer’s recommendations. Fungicide treatment continued until the week before haulm killing. The data for fungicide treated plots in 2021, we regarded as difficult to conclude; thus, we repeated the fungicide-treated field trial in 2023. Stomatal conductance (gsw, mol m −2 s −1 ) and photosynthesis measurements, including the quantum yield of PSII (ΦPSII), were collected using the Licor (LI-600) instrument, which was used for field trials in 2022 and 2023. For the field trials in 2021, maximum quantum efficiency (Fv/Fm) was recorded with the FluorPen FP 100. Default program settings were used to estimate the stomatal conductance and photosynthesis measurements.

Statistical analysis and data representation

All statistical analyses were performed by one-way ANOVA with the Minitab 18.1 software ( https://www.minitab.com ) or by two-sided Student’s t- test (unequal variance) with Office Excel software. Box plots were plotted using BoxPlotR 58 . Details about the statistical approaches used can be found in the figure legends. Each experiment was repeated at least three times and data were represented as the mean ± SD or SE, as indicated; “n” represents number of samples. The centerline in a box plot indicates the median, + sign specifies mean value, the box borders delimit the lower and upper quartiles, and the whiskers show the highest and lowest data points. Adobe Illustrator 2022 software was utilized for figure presentation.

Reporting summary

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

Data availability

The MS proteomics data have been deposited at the ProteomeXchange Consortium via PRIDE partner repository with the dataset identifier PXD038421 . All data supporting the findings of this work are available in the paper, Supplementary Information files, and repository platform.  Source data are provided with this paper.

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Acknowledgements

We thank Jiorgos Kourelis for providing PJK037 gateway-compatible plasmid for virus-induced gene silencing. We thank Laura Medina and Eleanor Gilroy for providing CAS-GFP and TRV2:GFP, respectively. We also thank Daniel Hofius and Alan Collmer for generously providing Pseudomonas syringae pv tomato DC3000. We thank Dr. Fredrik Levander from the Department of Immunotechnology, Lund University and the Proteomics Core Facility at Sahlgrenska Academy for performing the peptide data analyses. This work was funded by following: Novo Nordisk Foundation NNF19OC0057208 (to E.A); Formas-The Swedish Research Council for sustainable development 2019-00512 and 2020-01211 (to EA and ML); Stiftelsen Lantbruksforskning R-19-25-282 (to EA); Carl Trygger Foundation CTS19:14 (to EA); The Nilsson-Ehle Endowments 40927 and 43352 from the Royal Physiographic Society of Lund (to M.A.Z.) and DFF/Independent Research Fund Denmark 1032-00399B (to BLP).

Open access funding provided by Swedish University of Agricultural Sciences.

Author information

Jozef Mravec

Present address: Institute of Plant Genetics and Biotechnology, Plant Science and Biodiversity Center,-Slovak Academy of Sciences, Akademická 2, 950 07, Nitra, Slovakia

Ramesh Vetukuri

Present address: Department of Plant Breeding, Swedish University of Agricultural Sciences, 234 22, Lomma, Sweden

Authors and Affiliations

Department of Plant Protection Biology, Swedish University of Agricultural Sciences, 234 22, Lomma, Sweden

Muhammad Awais Zahid, Nam Phuong Kieu, Marit Lenman, Naga Charan Konakalla, Huanjie Yang, Sunmoon Jyakhwa, Ramesh Vetukuri, Svante Resjö & Erik Andreasson

Department of Plant and Environmental Sciences, University of Copenhagen, Frederiksberg C, Denmark

Frida Meijer Carlsen, Jozef Mravec & Bent Larsen Petersen

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Contributions

M.A.Z., M.L., N.P.K., S.R., and E.A. jointly conceptualized the study, with M.A.Z. taking the lead. The experiments were carried out by M.A.Z., N.P.K., F.M.C., M.L., N.C.K., H.Y., S.J., J.M., R.V., B.L.P., S.R., and E.A. Data visualization and statistical analysis were performed by M.A.Z. and S.R. The manuscript was written by M.A.Z. with input from all authors and corrected by E.A. All authors read and approved the final manuscript.

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Correspondence to Erik Andreasson .

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Competing interests.

M.A.Z., N.P.K., M.L., N.C.K., R.V., S.R., and E.A. are inventors on the patent application “Method of providing broad-spectrum resistance to plants, and plants thus obtained” (WO2022177484A1), where reduction of Parakletos expression is used for making plants more resistant. The other authors declare no competing interests.

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Zahid, M.A., Kieu, N.P., Carlsen, F.M. et al. Enhanced stress resilience in potato by deletion of Parakletos . Nat Commun 15 , 5224 (2024). https://doi.org/10.1038/s41467-024-49584-4

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June 25, 2024

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Farmland weeds can help combat pests

by University of Bonn

Leaving some weeds between crops can help to combat pests on agricultural land, according to a new study carried out by the University of Bonn. This step has particularly positive effects in combination with other measures: the cultivation of different types of crops and planting strips of wildflowers. The results have now been published in the Journal of Pest Science .

Intercropping, i.e. planting different types of crops on the same field has a number of benefits: The crops have different requirements and the crops face less competition than when grown in monocultures. This means that they make better use of the water and nutrients and deliver a better yield overall. Some types of crops—such as beans—are also able to fix nitrogen from the air, thereby delivering this nutrient as a natural fertilizer. The other crop also benefits as a result.

"Intercropping also makes it difficult for weeds to grow," says Prof. Thomas Döring from the Institute of Crop Science and Resource Conservation (INRES) at the University of Bonn. "The crops are also much less infested with pests. Insects usually specialize on one type of plant and they thus find fewer of the right type of plants with intercropping."

While these benefits have been proven many times, Döring and his colleague Dr. Séverin Hatt have now investigated whether these benefits can be improved even further in combination with other measures.

Strips of wildflowers attract aphid predators

The researchers cultivated two different crop mixes—beans and wheat and poppy and barley—in a field experiment lasting two years. In addition, they planted strips of wildflowers along the edges of the fields. "These strips attract beneficial insects that feed on pests," explains Döring, who is also a member of the PhenoRob Cluster of Excellence and the transdisciplinary research area "Sustainable Futures." "These insects include hoverflies and ladybirds, whose larvae are very effective predators of aphids."

In fact, the researchers found that aphid colonization of the mixed crops fell significantly next to the wildflower strips. They also discovered another effect: Mixing beans and wheat or poppy and barley naturally suppressed the growth of weeds without actually eradicating them completely. If the farmer took no additional measures, wild plants would continue to randomly grow across the field.

Residual weeds make it easier for beneficial insects to spread

"We have now been able to demonstrate that these residual weeds make it easier for beneficial insects to spread deeper into the field," says Döring. "And they did not reduce the yield in the process. In contrast, the study showed that they even helped to control pests."

The results were collected from fields that were cultivated under organic farming conditions. The extent to which these findings can be transferred to conventional farming still needs to be investigated.

However, the researchers are already able to issue a clear recommendation for organic farming based on their findings: Farmers should plant wildflower strips, use a greater mix of seeds and consider tolerating some residual weeds. This combination of measures will help them keep pests under control and at the same time maintain weeds at an acceptable level.

Provided by University of Bonn

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