Periodic Reporting for period 1 - Turbo-MPMI-Discovery (TurboID-charging discovery of plant pathogen virulence and host resistance mechanisms)
Reporting period: 2020-04-01 to 2022-05-31
Problem being addressed:
Pathogens inject effectors into host cells to manipulate host proteins for their invasion. Recognition of effectors by intracellular receptors activates plant immunity. Identifying effector-host interactor (host target and intracellular receptor) pairs remains challenging. A more sensitive and specific approach to define effector-host interactor pairs would greatly accelerate the understanding of plant-microbe interactions. Proximity labelling (PL) with biotin ("BioID") provides a novel method to detect proteins in the vicinity of a tagged protein. Taking advantage of the recently developed active ("TurboID") allele, this project aims at establishing a sensitive and specific method (TurboID based PL-MS) to identify effector-host interactor pairs and using it to identify host targets of protein and interacting effectors of host proteins during infection.
Why important for society:
The work supported by my MSCA project will break the bottleneck of defining effector-host interactor pairs and dramatically accelerate advances in the field of plant-microbe interactions.
Overall objectives:
Objective 1: Optimize conditions for TurboID-based IP in order to identify effector targets.
Objective 2: Isolate host targets of A. candida CCG effectors using TurboID-based PL-MS.
Objective 3: Identify effectors that bind host targets TCP14 or NLR-ID CHS3 during infection with TurboID-based PL-MS.
Pathogens inject effectors into host cells to manipulate host proteins for their invasion. Recognition of effectors by intracellular receptors activates plant immunity. Identifying effector-host interactor (host target and intracellular receptor) pairs remains challenging. A more sensitive and specific approach to define effector-host interactor pairs would greatly accelerate the understanding of plant-microbe interactions. Proximity labelling (PL) with biotin ("BioID") provides a novel method to detect proteins in the vicinity of a tagged protein. Taking advantage of the recently developed active ("TurboID") allele, this project aims at establishing a sensitive and specific method (TurboID based PL-MS) to identify effector-host interactor pairs and using it to identify host targets of protein and interacting effectors of host proteins during infection.
Why important for society:
The work supported by my MSCA project will break the bottleneck of defining effector-host interactor pairs and dramatically accelerate advances in the field of plant-microbe interactions.
Overall objectives:
Objective 1: Optimize conditions for TurboID-based IP in order to identify effector targets.
Objective 2: Isolate host targets of A. candida CCG effectors using TurboID-based PL-MS.
Objective 3: Identify effectors that bind host targets TCP14 or NLR-ID CHS3 during infection with TurboID-based PL-MS.
Objective 1: Optimize conditions for TurboID-based IP in order to identify effector targets.
Using plants co-expressing 35S::PopP2-TurboID-V5 and PAT2::RRS1-HA followed by biotin treatment at a gradient concentration (30-200 μM) for 1 h, biotinylation of RRS1 by PopP2-TurboID-V5 was saturated at 50 μM of biotin, which was selected as the optimal biotin concentration. During the optimization of the labelling duration, I noticed biotinylation efficiency is mainly determined by protein abundance rather than labelling time as biotinylation catalyzed by NLS-GFP-TurboID-V5 at high protein abundance for 30 min exceeded that caused by PopP2-TurboID-V5 at medium abundance for 8 h. Therefore, the labelling time for all my PL-MS was not set and decided based on bait protein abundance. 35S promoter was selected over estradiol-inducing promoter since PopP2 proteins were not detectable when the encoding gene was driven by the latter promoter.
Upon establishing the conditions, Arabidopsis plants overexpressing AvrRps4-FLAG-TurboID and PopP2-FLAG-TurboID were used for TurboID-based PL-MS. WRKY transcription factors, the known targets of AvrRps4 and PopP2, were identified in MS, which proves the feasibility of TurboID-based PL-MS for identifying effector targets. Novel potential interactors of AvrRps4 and PopP2, such as splicing factors and other types of transcription factors, were identified, and the genuineness of which is being tested.
Objective 2: Isolate host targets of A. candida CCG effectors using TurboID-based PL-MS.
To identify the host targets of the 6 A. candida CCG effectors, I generated Arabidopsis plants independently overexpressing the TurboID-V5 tagged CCG effectors. Unfortunately, the CCG effector proteins are below detection limit in all transgenic lines. As a result, the isolation of host targets of the CCG effectors was halted.
Objective 3: Identify pathogen effectors that interact with host targets TCP14 or NLR-ID CHS3 during an authentic in vivo interaction, using TurboID-based PL-MS.
To test whether the method is able to isolate host protein interacting-effectors during infection, Arabidopsis transgenic lines overexpressing TCP14-TurboID-V5 were infected with pathogens P. syringae and Hpa, then subjected for TurboID-based PL-MS. Known host interactors of TCP14 such as TCP8, TCP21 and TCP23 were identified, confirming the feasibility of TurboID-based PL-MS in isolating interactors of host proteins. Only one P. syringae effector, namely AvrE1, but no Hpa effectors were identified. AvrE1 is unlikely the genuine interacting effector of TCP14 as they localize in different subcellular compartments of plant cells. CHS3 carries an integrated Lim domain, which presumably bind the cognate effectors of CHS3. When transgenic lines overexpressing Lim domian-TurboID-V5 were infected with A. candica race Em2 and used for TurboID-based PL-MS to identify the cognate effectors of CHS3, no A. candica effectors were identified. BSL1 and NbVAMP72 of N. benthamiana are targeted by five and seven P. infestans effectors, respectively. When BSL1-TurboID-V5 and NbVAMP72-TurboID-V5 were transiently overexpressed in N. benthamiana followed by TurboID-based PL-MS, no P. infestans effectors were isolated. Collectively, it suggests TurboID-based PL-MS is unable to identify interacting effectors during effectors.
Using plants co-expressing 35S::PopP2-TurboID-V5 and PAT2::RRS1-HA followed by biotin treatment at a gradient concentration (30-200 μM) for 1 h, biotinylation of RRS1 by PopP2-TurboID-V5 was saturated at 50 μM of biotin, which was selected as the optimal biotin concentration. During the optimization of the labelling duration, I noticed biotinylation efficiency is mainly determined by protein abundance rather than labelling time as biotinylation catalyzed by NLS-GFP-TurboID-V5 at high protein abundance for 30 min exceeded that caused by PopP2-TurboID-V5 at medium abundance for 8 h. Therefore, the labelling time for all my PL-MS was not set and decided based on bait protein abundance. 35S promoter was selected over estradiol-inducing promoter since PopP2 proteins were not detectable when the encoding gene was driven by the latter promoter.
Upon establishing the conditions, Arabidopsis plants overexpressing AvrRps4-FLAG-TurboID and PopP2-FLAG-TurboID were used for TurboID-based PL-MS. WRKY transcription factors, the known targets of AvrRps4 and PopP2, were identified in MS, which proves the feasibility of TurboID-based PL-MS for identifying effector targets. Novel potential interactors of AvrRps4 and PopP2, such as splicing factors and other types of transcription factors, were identified, and the genuineness of which is being tested.
Objective 2: Isolate host targets of A. candida CCG effectors using TurboID-based PL-MS.
To identify the host targets of the 6 A. candida CCG effectors, I generated Arabidopsis plants independently overexpressing the TurboID-V5 tagged CCG effectors. Unfortunately, the CCG effector proteins are below detection limit in all transgenic lines. As a result, the isolation of host targets of the CCG effectors was halted.
Objective 3: Identify pathogen effectors that interact with host targets TCP14 or NLR-ID CHS3 during an authentic in vivo interaction, using TurboID-based PL-MS.
To test whether the method is able to isolate host protein interacting-effectors during infection, Arabidopsis transgenic lines overexpressing TCP14-TurboID-V5 were infected with pathogens P. syringae and Hpa, then subjected for TurboID-based PL-MS. Known host interactors of TCP14 such as TCP8, TCP21 and TCP23 were identified, confirming the feasibility of TurboID-based PL-MS in isolating interactors of host proteins. Only one P. syringae effector, namely AvrE1, but no Hpa effectors were identified. AvrE1 is unlikely the genuine interacting effector of TCP14 as they localize in different subcellular compartments of plant cells. CHS3 carries an integrated Lim domain, which presumably bind the cognate effectors of CHS3. When transgenic lines overexpressing Lim domian-TurboID-V5 were infected with A. candica race Em2 and used for TurboID-based PL-MS to identify the cognate effectors of CHS3, no A. candica effectors were identified. BSL1 and NbVAMP72 of N. benthamiana are targeted by five and seven P. infestans effectors, respectively. When BSL1-TurboID-V5 and NbVAMP72-TurboID-V5 were transiently overexpressed in N. benthamiana followed by TurboID-based PL-MS, no P. infestans effectors were isolated. Collectively, it suggests TurboID-based PL-MS is unable to identify interacting effectors during effectors.
I) Enhance my scientific competencies
My multidisciplinary project involved various state-of-the-art techniques, which improved my technical skills and competencies. I gained valuable expertise in proximity labelling during my project. TSL offers up-to-date training in proteomics and bioinformatics. Through analyzing the MS data from all objective 1 and 3, I obtained advanced training and experience in proteomics analysis and bioinformatics. Working with pathogens from three taxonomic kingdoms enabled me to acquire precious experience of working on new pathosystems (Arabidopsis-A. candida and Arabidopsis-G. orontii).
II) Establish scientific social network
My Fellowship research provided me an excellent opportunity to build collaborations with scientists worldwide, which boosted my collaborative potential as an independent scientist. Besides the collaborations described in the DoA, I also collaborated with Prof. Wangsheng Zhu and Prof. Hailong Guo at China Agricultural University and Prof. David Mackey at the Ohio State University. The collaborations will lead to at least 3 high-impact co-first author or co-correspondence author publications in one to two years.
My proposed approach using innovative sensitive methodologies is of general interest to scientists who investigate host-microbe interactions in plants and in animals. I have been making full use of networking opportunities to establish future collaborations when disseminating my results in seminars and conferences, at TSL, the NRP and beyond.
III) Improve professional and personal growth
My MSCA Fellowship allowed me to obtain complementary knowledge and skills underpinning a successful academic career. I worked closely with TSL’s Finance and Contracts Office to learn about the financial management and monitoring of my project. such experiences were invaluable in preparing me to run my own lab in the future. My career goal is to become a group leader and establish my own lab, the success of which relies on my technical and complementary skills, as well as communication capability. I took the unparalleled training opportunities offered by TSL to receive trainings covering these areas. Thus, my Fellowship equipped me for progressing as a professional and independent scientist.
My multidisciplinary project involved various state-of-the-art techniques, which improved my technical skills and competencies. I gained valuable expertise in proximity labelling during my project. TSL offers up-to-date training in proteomics and bioinformatics. Through analyzing the MS data from all objective 1 and 3, I obtained advanced training and experience in proteomics analysis and bioinformatics. Working with pathogens from three taxonomic kingdoms enabled me to acquire precious experience of working on new pathosystems (Arabidopsis-A. candida and Arabidopsis-G. orontii).
II) Establish scientific social network
My Fellowship research provided me an excellent opportunity to build collaborations with scientists worldwide, which boosted my collaborative potential as an independent scientist. Besides the collaborations described in the DoA, I also collaborated with Prof. Wangsheng Zhu and Prof. Hailong Guo at China Agricultural University and Prof. David Mackey at the Ohio State University. The collaborations will lead to at least 3 high-impact co-first author or co-correspondence author publications in one to two years.
My proposed approach using innovative sensitive methodologies is of general interest to scientists who investigate host-microbe interactions in plants and in animals. I have been making full use of networking opportunities to establish future collaborations when disseminating my results in seminars and conferences, at TSL, the NRP and beyond.
III) Improve professional and personal growth
My MSCA Fellowship allowed me to obtain complementary knowledge and skills underpinning a successful academic career. I worked closely with TSL’s Finance and Contracts Office to learn about the financial management and monitoring of my project. such experiences were invaluable in preparing me to run my own lab in the future. My career goal is to become a group leader and establish my own lab, the success of which relies on my technical and complementary skills, as well as communication capability. I took the unparalleled training opportunities offered by TSL to receive trainings covering these areas. Thus, my Fellowship equipped me for progressing as a professional and independent scientist.