Template:NYMU-2015project-wetlab

Experiment

Prevention

Concept

After P. infestans penetrates the cell wall of potato, it will exploit the potato and in turn infect potatoes nearby within 3 days. Since it will infect other potatoes in such a short time that there is no effective biological method to react against it and inhibit the development of the disease, we decide to prevent the disease at the very beginning by rendering the potatoes the ability to prevent the invasion of P. infestans.

Under certain conditions, the zoospores of P. infestans will attach to the surface of potato leaves, penetrate the cell wall with high turgor pressure and some enzymes, and secrete effector proteins, such as Avr3, into potato cells. The binding of the effector protein to the transmembrane receptor PI3P is essential and helps mediate the translocation of the effector protein into the potato cell. It suppresses plant resistance-gene-based immunity; thus, P. infestans enter potato cells without any resistance.

To stop the effector protein from entering potato cell, we found through literature research that reduction in translocated effector is a promising way to decrease the virulence of pathogens and improve disease resistance in potatoes. In previous research, FYVE protein domain from Hrs or EEA1 can also bind to PI3P receptor strongly in animal cells. We then decided to construct a FYVE protein domain with high affinity to PI3P that can compete with the effector protein to inhibit the entry of P. infestans.

Oomycete and potato cell
Effector protein bonding with PI3P and entering
Dimeric FYVE preventing effector from bonding with PI3P

FYVE protein domain

Dimeric FYVE protein

The FYVE protein domain is a well-conserved PI3P-binding domain in various organisms with only 78 amino acids, originally existing in EEA1 and Hrs proteins of human and mouse, respectively, but also in many other proteins. However, according to literature research, EEA1 and Hrs protein are too large and may take a long time for the plant to degrade, so we extracted only the FYVE domain from Hrs protein, whose ability of binding to PI3P was better than others. Yet the monomeric FYVE is relatively unstable in the cytoplasm, so we constructed a dimeric FYVE to improve the stability.

Experimental Design

We chose dimeric FYVE as our competitive inhibitor against the Avr3 secreted by P. infestans. We first conducted modeling simulation, and the dissociation constant of monomeric FYVE was far higher than the RXLR of Avr3 and was quite unstable. After we connected two FYVE domain with a linker protein, enhancing the affinity and stability of the substrate, the dissociation constant was lowered from 250 to 3.8.

The Construction of dimeric FYVE

To construct the dimeric FYVE, we designed primers containing enzyme cutting sites "EcoRI, XbaI, SpeI, PstI" and coding sequence of the linker protein to extract monomeric FYVE domain from the Mus musculus embryonic cDNA. We then used restriction enzyme cloning method to insert the dimeric FYVE into pSB1C3.

Circuit construction

pSAT6-EYFP-N1 is a vector which can express foreign genes in plant cells through transfection. So we designed a set of primers to extract monomeric and dimeric FYVE from pSB1C3 and transfer it into the vector for transfection. The circuit is displayed on the below, containing viral constitutive promoters CaMV35S followed by the coding sequence of dimeric FYVE. The coding sequence of the enhanced yellow fluorescence protein follows that of the dimeric FYVE as a reporter gene to indicate whether the dimeric FYVE works well in the plant.

Dimeric FYVE circuit

Transfection of plasmid DNA into plant cells

To check whether dimeric FYVE works well in plant, we inserted dimeric FYVE into vector PSAT6–EYFP-N1 and transfect the recombinant plasmid DNA into tobacco protoplasts, BY-2. BY-2 cells and potato cells share many common biological features as tobacco (Nicotiana tabacum) and potato (Solanum tuberosum) that both belong to the Solanaceae family. If the dimeric FYVE works well in BY-2 cell, we will see yellow fluorescence on the endosome of the cell.



After transfecting the dimeric FYVE into BY-2 cells, we check whether the survival of the cell is influenced or not. Propidium iodide (or PI) is an intercalating agent and a fluorescent molecule used to stain cells and is the most commonly used dye to quantitatively assess DNA content. We stained the constructed BY-2 cell with PI for observation under the confocal microscope. The plant cell will become red if it is dead; on the other hand, if the dimeric FYVE did not influence the survival of the plant when binding to PI3P, the cell will emits yellow fluorescence.



Second, we fused the cell with Wortmannin, a PI3K inhibitor restraining the synthesis of PI3P. If the binding between dimeric FYVE and PI3P is effective, inhibiting the production of PI3P will lead to the redistribution of dimeric FYVE into cytoplasm. To check if the dimeric FYVE actually binds to PI3P, we compared the engineered BY-2 cells containing dimeric FYVE and one that did not, with only the experiment group treated with Wortmannin. The one treated with Wortmannin shows a dispersion of yellow fluorescence, and the other emitting concentrated light around the PI3P receptor. With this experiment, we can confirm that dimeric FYVE not only expresses in the engineered BY-2 protoplast but also binds to the PI3P receptor as expected.

Promoter choice

Though the depletion of PI3P may be an effective way to prevent P. infestans from invading the potato, the constitutive expression of FYVE protein domain may cause certain physiological effects to the potato since PI3P is an important receptor for membrane trafficking to plants. Therefore, the timing of the expression of FYVE is the key to successful implementation of this strategy.



We chose promoter Gst1 as it will be activated in the potato cell within 24 hours of the infection of P. infestans and the production of it will be down-regulated after infection. Furthermore, promoter Gst1 will be mildly activated when the plant is wounded; namely, when the plant is most vulnerable to late blight.

Results

  1. Monomeric and dimeric FYVE gel images (plate)
  2. We first extracted the FYVE domain from the Mus musculus embryonic cDNA and put it in the PSB1C3 vector. The gel image(A) which displayed the correct band size, 523base pairs, indicated the successful cloning. Secondly, we used restriction enzyme cloning to put the second FYVE domain to build the dimeric FYVE. The gel image(B) showing the band of 745bp indicated the construction of dimeric FYVE was successful. We designed a set of primers with new cutting sites, XhoI and HindIII , to extract the dimeric FYVE from PSB1C3 and transferred it into another vector, PSAT6-EYFP-N1. The gel image(C) with the band size of 474bp indicated that the result was successful.

  3. Dimeric FYVE binding test
  4. The preparation of protoplast was conducted in the transgenic plant core lab of Academia Sinica. The picture on the right indicates the By-2 cells processed with the digestion of enzymes Cellulase Onozuka RS and Macerozyme R-10. The result of preparing protoplasts was successful.

    We were ready to add enzyme solution into By-2 cells.
    After adding the enzyme solution, we removed the liquid into a plastic petri dish. And kept on horizontal shaker at 30 rpm in darkness at room temperature.
    The By-2 cells were processed by enzyme solution and became protoplasts.This step was to centrifuge the solution.

    After the PEG transfection steps, we then incubated the cells in darkness at 26℃for 16 hours. The pictures below are the protoplasts expressing fluorescence. It indicated the successful transfection of plasmid DNA into By-2 cells.

    In the competitive inhibitor binding test, we first compared BY-2 cells containing only an empty pSAT6 vector expressing only EYFP with the experiment group containing the dimeric FYVE fused with EYFP. The picture (a) showed that the cell without dimeric FYVE had dispersion of fluorescence in the whole cell, but the picture (b) with dimeric FYVE showed the concentrated light around the endosomes containing PI3P receptors. Secondly, we fused 1 ul Wortmannin, an inhibitor of the synthesis of PI3P, with 100ul protoplasts. The one treated with Wortmannin obviously showed the dispersion of fluorescence(pic). We took a series of photos every 5 minutes after treating the protoplasts with the inhibitor. With the comparison between these photos, we strongly suggest that dimeric FYVE not only expresses within the engineered BY-2 protoplasts but also binds to the PI3P receptor.

    Detection

    Introduction

    One major problem in controlling potato late blight is that there is no simple and convenient way to detect the disease. If we want to make sure that our potato has not been infected by P. infestans , we have to examine the potato in the laboratory for approximately a week. We want our detection system to be simple and convenient, and can instantly report the infection to the user. So the solution we reached is to design a soil based microbial fuel cell (SMFC) that can detect salicylic acid, a chemical that is produced when potato is injured or infected. With this device, we can know whether the potato is infected immediately at home.



    We choose to utilize the mtr (metal reduction) pathway of Shewanella oneidensis MR-1. Shewanella oneidensis MR-1 is a gram negative bacteria that is widely used for constructing microbial fuel cells because how it produce electricity is well characterized. The mtr pathway contains 4 proteins: CymA, mtrA, mtrB, mtrC. CymA is a transmembrane protein that can transport electrons out of the cell membrane, and can then activate proteins mtrA, B, and C consecutively. From literature research, mtrB gene plays a pivotal role in stabilizing other component in this pathway. Therefore, in our project we utilize mtrB to create our biosensor by detecting changes in electric signals.

    Experimental Design

    To create this long term biosensor, we first knock out the endogenous mtrB gene in Shewanella oneidensis MR-1. By reintroducing mtrB gene under the control of sensor (nahR), we can control the bacteria to generate electricity when it detects salicylic acid.



    We managed to design our sensor system using mtrB. However, the mere expression of mtrB is not enough. As electric signals in the soil can also be detected by the soil-based microbial fuel cell we created and can constitutively produce electric currents. This electric signal caused by soil itself somehow come as a background noise. When the electric signals emitted by the plant is not intense enough or when the number of bacteria in the soil drops, users may easily confuse it with the signals produced by the soil and make wrong judgments on pathogen control. Thus, we incorporate the oscillator into our circuit design. Even when the currents are not strong enough, users can still easily tell the difference between the electric signals emitted by the soil and those by the infected plant by recognizing the oscillating pattern of the latter.

    Main circuit

    As the circuit showed below, we first tested the oscillator and sensor with GFP as reporter. Then we replaced GFP with MtrB to test the expression of MtrB will also oscillate.

    Results

    Cure

    Concept

    Our goal is to kill P. infestans without harming the potatoes and environment. Fungicides used to kill P. infestans nowadays contain lots of heavy metals, such as Cu2+ that will do harm to both the plant and environment. At first we try to use some antimicrobial peptides; however they will not only kill P. infestans but also do harm to potatoes as well. Therefore, we try to look for the naturally acquired defensin that can weaken or even kill P. infestans from other plants. Although there are other chemicals that might be effective in inhibiting the growth of P. infestans, such as 2, 6-dichlorobenzonitrile (2,6-DCB), but some of these may also do harm to bacteria itself. Based on the reasons above, we finally choose Lm-def, a defensin isolated from maca (Lepidium meyenii) that can effectively weaken and inhibit the growth of P. infestans.

    Experimental Design

    Circuit construction

    The pET expression system originally features a C-terminal 6x His tag. In our circuit design, we use different sets of primers to test on which terminus His-tag is added will optimize the expression of defensing and also to facilitate protein purification. In order to mass produce defensin, we choose T7 promoter, which allows leaky expression of the His-tagged protein, and transform the entire plasmid into E.coli BL21 (DE3), whose expression of large amounts of proteins of interest can be induced under the regulation of the native lac operon.

    His-tagged protein purification and functional test

    We incubate liquid culture of the selected colonies at 37 degrees Celsius overnight before we lyse it with liquid homogenization using a continuous high pressure cell disrupter. Afterwards, the raw lysate is incubated to run affinity chromatography so as to cleave the polyhistidine tag from the recombinant protein. Then we wash it with phosphate buffer. For purity assessment, we run SDS-PAGE. Lastly, we conduct Bradford’s protein assay for concentration measurement.

    Antimicrobial activity test

    Next, to test the activity of defensin against P. infestans in vitro, we incubate in advance the oomycete acquired from Taiwan Agricultural Research Institute on rye agar plates at 18 degrees Celsius for ten days to acquire sporangia and hyphal pieces. Dilution broth solution is then prepared by boiling fresh pea seeds for 20 minutes in distilled water and autoclaved for sterilization. We harvest P. infestans in sterile water; later, we use hemocytometer to count the number of sporangia and dilute it to 250 sporangia per 100 microliter with the dilution broth solution. We take the 100 lambda spore suspension and add to it 50 lambda of recombinant protein and 50mM Tris-HCl buffer in a 96 well microtiter plate. The mixture will then be incubated in darkness at 18 degrees Celsius for an entire day. Spore germination and hyphal growth will be monitored several times at certain points during incubation under light microscope and will be measured with a plate reader at 595 nm 24 hours after inoculation.

    Results

    (1) Defensin final gel image
    (2) Protein purification gel image (SDS PAGE)
    (3) Functional test of submitted parts
    (4) Antimicrobial activity test resultmorphology change and growth monitoring
    (5) Growth rate assay of E. coli BL21 (DE3)

    Functional Prototype

    Our defense systen contains three different: prevention, detection, and cure. So how do we connect this three part together to form an impeccable defense system? First, we plant the genetically modified potato in the farm to prevent the disease from infecting the whole farm in a short period of time. Secondly, we implement the soil based microbial fuel cell that can detect and report whether the potato is infected or not immediately, in case that the potato can’t fend of the disease. When the SMFC detects the disease, it will send an electric signal that can trigger the spraying system. The spraying system will then spray the environmentally friendly defensin that we produced automatically. Man power is not required in the whole process except planting the potatoes.



    Also, the defense system will also connect to a phone app that we created, so that we can know whether the potatoes are healthy or not. The defense system is localized, socialized, and mobilized.

    Modeling

    Overview

    FYVE inhibition

    This model was designed to investigate the competitive binding between FYVE protein domain and PI3P. Before we construct the circuit with FYVE, we have to determine whether the affinity between FYVE and PI3P is strong enough to compete with Avr3 effector protein secreted by P. infestans . We characterize this agonist-antagonist competition model by Gaddum-Schild equation. This model consists of two parts: monomeric FYVE and dimeric FYVE. According to paper research, monomeric FYVE is not so stable but the affinity of both monomeric and dimeric FYVE is quite high. The model is used to determine how much FYVE protein domain we should link with a linker so that the affinity of FYVE will be high enough to compete with Avr3.

    Result

    Conclusion

    As we can see in the models dimeric FYVE is not only more stable but also have higher affinity to compete with avr3, the effector protein secreted by P. infestans . To create FYVE protein domain with higher affinity, we can link as much FYVE domain artificially as we want. However, it takes a lot of time to add a linker protein between FYVE and connect two FYVE together. Moreover, the longer the FYVE is, the longer it takes for the palnt to degrade the protein we created, which might have a negative impact to the potato. By constructing this model, we can find out the simplest way to create a competitive inhibitor and save the time for trial and error.

    Parameters

    Kd monomeric FYVE Dissociation constant of monomeric FYVE 420 nM Structural Basis for Endosomal Targeting by FYVE Domains
    Kd dimeric FYVE Dissociation constant of dimeric FYVE 38 nM Phosphatidylinositol 3-Phosphate Induces the Membrane Penetration of the FYVE Domains of Vps27p and Hrs
    Kd Avr3 Dissociation constant of Avr3 210 nM External Lipid PI3P Mediates Entry of Eukaryotic Pathogen Effectors into Plant and Animal Host Cells

    Reference:

    1. Structural Basis for Endosomal Targeting by FYVE Domains
    2. Phosphatidylinositol 3-Phosphate Induces the Membrane Penetration of the FYVE Domains of Vps27p and Hrs
    3. External Lipid PI3P Mediates Entry of Eukaryotic Pathogen Effectors into Plant and Animal Host Cells

    Oscillation

    We construct a Lux/Aiia quorum-sensing oscillator so that S. oneidensis-MR1 will generate oscillating current which can help farmers tell if the potatoes are infected. We build two models to characterize the outcome of the genetic oscillator. The first model is used to predict whether the genetic oscillator will work. Since it is possible that some of the engineered S. oneidensis we inoculated on anode won’t survive, the second model is used to predict whether the gene expression will oscillate when there are only a few bacteria left on the anode.

    Population simulation with delay differential equation

    Since our circuit design is based on the circuit published by Danino et al.[1] our first model is a slight modification of the equation from the supplementary information. This model consists of four delay differential equation. We added one more delay differential equation to this model to simulate the expression of MtrB gene.

    Parameters

    Description Parameter Value
    CA Synthesis constant of Aiia 1
    CI Synthesis constant of LuxI 4
    CmtrB Synthesis constant of MtrB 1(assume)
    δ Hill function constant 10-3
    α Hill function constant 2500
    k1 Hill function constant 0.1
    τ Time delay of the production of LuxR::AHL 10
    k Kinetic constant of AHL synthesis 1
    b Synthesis rate of AHL 0.06
    γA Enzymatic degradation rate of Aiia 15
    γI Enzymatic degradation rate of LuxI 24
    γH Enzymatic degradation rate of AHL 0.01
    γmtrB Enzymatic degradation rate of MtrB 0.007(assume,[3])
    D AHL membrane diffusion 2.5
    f 0.3
    g Kinetics constant of AHL degradation 0.01
    d0 Maxium cell density 0.88

    Conclusion

    As you can see in the graph, the production of Aiia and LuxI will oscillate as the time goes by. However, the production of MtrB will build up instead of oscillating. This is because MtrB is too stable and it is not totally degraded before the next period of oscillation. Thus, it is necessary to be targeted for proteolysis by adding a degradation tag in MtrB coding sequence.

    Single cell simulation with ODE

    If we inoculate the engineered S. oneidensis MR-1 into the anode of our SMFC, chances are that some of the bacteria will not survive in soil. Thus, it is necessary to simulate if the oscillator will work with only a single bacteria or a small population of bacteria.

    With a small amount of bacteria, there will not have a significant time delay, and that’s why we chose a set of ODE to simulate the genetic oscillator.

    Conclusion

    As we can see in this model, even if there is only a small amount of bacteria left on the anode, the oscillator can still work. However, the current output will be much lesser than that of a large population of bacteria.

    Parameters

    Descriptions Parameter Units Value
    Basal production rate LuxI AiiA a0LI a0A μM/min μM/min 7.79x10-6 6.18x10-6
    Active production rate LuxI AiiA mtrB kpLI kpLA kpmtrB μM μM μM 0.9 0.84 0.33(assume[4])
    Cell reaction rate AHL production rate LuxR AHL association rate LuxR AHL dissociation rate AHL::Aiia catalytic rate AHL conc. adjustsment for environment AHL membrane diffusion constant kp2 kr1+ kr1− kcataA ηenv ηcell 1/min μM/min 1/min 1/min 1/min 1/min 16 5.99x10-5 6x10-6 7x103 3x10-5 3
    Michaelis-Menten constants LuxR::AHL complex Aiia complex KmLA KmaA μM μM 1.00x10-2 1.4977x103
    Degradation related parameters LuxR::AHL complex AHL τLA τAA˜ 1/min 1/min 2.40x10-2 2.76x10-3
    Enzymatic degradation Inverse of KMclx Vmax × ET OT / KMclx for LuxI Vmax × ET OT / KMclx for Aiia f δ1 δ2 δ3 1/μM 1/μM.min 1/μM.min 1/μM.min 4.12x10-2 7.16x10-1 2.50x10-2 0.99x10-2 (assume[4])

    Reference

    1. Danino. T, Mondragon-Palomino, O, Tsimring, L. & Hasty, J. “A synchronized quorum of genetic clocks.” Nature 463, 326-330 (2010).
    2. Petros Mina, Mario di Bernardo, Nigel J. Savery, Krasimira Tsaneva-Atanasova. “Modelling emergence of oscillations in communicating bacteria: a structured approach from one to many cells.” Published 7 November 2012
    3. Danino. T, Mondragon-Palomino, O, Tsimring, L. & Hasty, J. “A synchronized quorum of genetic clocks.” Nature 463, 326-330 (2010).

    Epidemic

    P. infestans is an oligate parasite, which means it can’t complete its life cycle without exploiting potato. However, if a potato is infected by P. infestans, the disease will spread through the potato farm within 20 days.

    In this model, we try to show the difference between planting the potato we engineered and planting potato that is susceptible or moderately resistant to potato late blight. Traditionally, SEIR model will be the perfect model to characterize epidemiology. However, we made some changes to the assumption of the traditional SEIR model so that the model can reflect the reality of potato late blight epidemiology much better.

    Epidemology Symbol Meaning
    Suspected The potato that is slightly or moderately resistant to P. infestans
    Exposed Potatoes that are infected by a low amount of P. infestans , but they are still curable andwill not spread the disaese
    Infected Potatoes that are infected by a large amount of P. infestans . Potatoes infected will spread the disease and jeopardize the whole potato farm
    Immunized Potatoes that has been transformed by us and is resistant against P. infestans

    According to our assumptions, we developed a set of ordinary differential equations that can characterize the epidemic of potato late blight.

    Parameters

    SEIR MODEL(COEFFICIENTS) γ transmission rate(1/days) 0.25
    α Promoter activation rate(1/days) 1.0
    ε Latent rate(1/days) 0.2 British Columbia Ministry of Agriculture[3]
    μ Infection rate(1/days) 0.2
    k Rate of resistance to late blight 0.75 External Lipid PI3P Mediates Entry of Eukaryotic Pathogen Effectors into Plant and Animal Host Cells[2]
    beta Daeth rate of normal potato(1/days) 1/365
    SEIR MODEL(VARIABLE) S The amount of all potatoes X(1)
    E The amount of suspected individual X(2) Global analysis of an SEIR model with varying population size and vaccination
    I The amount of infected individual X(3) [1]
    R The amount of potato that survive X(4)
    V The amount of potato being immunized X(5)

    Result

    As we can see from the model,with our genetically modified potatoes can prevent 80% of the potatoes from being infected, while only 20% of the moderately resistant potatoes can survive during the epidemic of potato late blight. Also as we can see in the graphs above, the survival rate do fit our sassumption the the potatoes under the destruction of late blight only end in two consequences----death(once the potatoes exposed to small amount of P. infestans are seriously infected ) or survive (once the “exposed potato” truned into “immunized potato”). This graphs not only show that our potatoes might be effective in fighting potato late blight in the real world but also show that potato late blight is a disease that needs to be take care of seriously and a impeccible system is necessary to fight against the disease.

    Conclusion

    As we can see from the model,with our genetically modified potatoes can prevent 80% of the potatoes from being infected, while only 20% of the moderately resistant potatoes can survive during the epidemic of potato late blight. Also as we can see in the graphs above, the survival rate do fit our sassumption the the potatoes under the destruction of late blight only end in two consequences----death(once the potatoes exposed to small amount of P. infestans are seriously infected ) or survive (once the “exposed potato” truned into “immunized potato”). This graphs not only show that our potatoes might be effective in fighting potato late blight in the real world but also show that potato late blight is a disease that needs to be take care of seriously and a impeccible system is necessary to fight against the disease.

    Reference

    1. Chengjun Suna, Ying-Hen Hsiehc. “Global analysis of an SEIR model with varying population size and vaccination” doi:10.1016/j.apm.2009.12.005
    2. Kale SD1, Gu B, Capelluto DG, Dou D, Feldman E, Rumore A, Arredondo FD, Hanlon R, Fudal I, Rouxel T, Lawrence CB, Shan W, Tyler BM. “External Lipid PI3P Mediates Entry of Eukaryotic Pathogen Effector into Plant and Animal Host Cells” Cell. 2010 Sep 17;142(6):981-3.
    3. British Columbia Ministry of Agriculture