NSF Arabidopsis 2010
Expression Profiling of Plant Disease Resistance Pathways Project
Xinnian Dong Lab   Frederick Ausubel Lab   Shauna Somerville Lab
IMDS Database
  User Name

Abstract, Phase 1 (completed)
Plants respond to pathogen attack through a variety of signaling pathways consisting of a large number of regulatory as well as effector genes. During the past several years, many defense-related genes have been identified through genetic analysis conducted in Arabidopsis thaliana. Importantly, Arabidopsis exhibits all of the major kinds of defense responses present in other plants. Although a relatively large number of Arabidopsis defense-related genes have been identified, progress in developing overall explanatory models of plant-pathogen interactions is currently limited by two major experimental roadblocks. First, most of the phenotypic tests that have been used to characterize pathogen-host interactions do not have sufficient discriminatory power to assign defense-related genes to specific signal response pathways. To circumvent this limitation, large-scale transcript profiling analyses will be carried out on appropriately selected Arabidopsis defense-related mutants, including double and triple mutants. Combining genetic epistasis analysis with genomic technologies should lead to the development of a much more detailed model of how the various defense-related genes function and interact in combating pathogen attack. The second factor limiting the understanding of the plant defense response is that it is simply not possible to analyze the overwhelming volume of current data using conventional methods. The large volume of microarray data that will be generated in the near future compounds this problem. Moreover, data from different laboratories are not directly comparable because standardized experimental conditions are not employed. To help mitigate the problems associated with the analysis of large data sets, a sophisticated web-accessible plant-microbe interaction database (PMIDB) will be created to provide a common repository and standardized format for experimental data. The specific aims of the project are to:

1) Use transcript-profiling analysis to identify Arabidopsis defense-related genes and construct a custom microarray (pathoarray) enriched for defense-related genes. These custom pathoarrays will be made available to the Arabidopsis community at a nominal cost with the expectation that the experimental results generated using these pathoarrays will be deposited in PMIDB.

2) Use the pathoarrays from Aim 1 and Arabidopsis defense-related mutants to define the expression signatures resulting from the activation of defense pathways.

3) Create a web-accessible plant-microbe interaction database (PMIDB). This database will be developed during the next four years and will contain standardized experimental procedures for analyzing host defense responses, a list of all the pathogenesis-related mutants and their phenotypes, a list of defense-related genes with links to various sequence databases, and expression profiles of different plant-pathogen interactions and different defense-related mutants.

This 2010 Project provides a unique opportunity for applying genomic approaches to genetic analysis of plant defense mechanisms. Understanding the mechanisms of plant defense is of interest not only to basic science but also to development of agriculture and protection of the environment.

Abstract, Phase 2 (completed)
This project will determine the function of transcription factors (TFs) in the Arabidopsis defense-response signaling network (see current candidate list). TFs are key switches that control plant defense responses against pathogens, and expression profiling using gene chip (microarray) is the most powerful genomics approach available for high through-put analysis of transcriptional events. In Aim 1, profiling will identify candidate TFs in understudied defense pathways, including those induced by the so-called "PAMP" molecules which are commonly associated with pathogens of plants as well as animals. In Aim 2, mutants in the candidate TF genes (see current list) will be identified to see whether disrupting the genes and their functions will affect any defense response. In Aim 3, the TFs identified in Aim 2 will be linked to GFP, a protein that glows under UV, to mark and sort cells expressing these TFs, and profiling will be conducted in these cells to identify genes whose expression patterns mirror those of the TFs (i.e., cohort transcriptomes). The important TFs will also be modified so their transport into the nucleus where they function can be controlled experimentally and their target genes will be identified. Collectively, these experiments will provide spatial, temporal, and hierarchical information on defense-related transcriptional events, which is currently lacking but needed to build a model of the transcriptional network of interacting defense pathways. All data obtained in this project will be deposited in IMDS (Integrated Microarray Database System) and made available to the public either at the time of publication or after a 6-month delay, whichever comes sooner."

Abstract, Phase 3

The intellectual merit of the proposed project
Combating infection is an essential part of adaptation to the environment (thematic area #2). The sessile nature of plants and the lack of a specialized immune system make it difficult to study plant immunity independently of other plant process. To fully understand how plants respond to pathogen challenge, a “systems biology” approach is most likely to uncover key regulatory networks underlying plant immunity and how they interface with global plant processes like growth and development. Arabidopsis is an ideal multicellular organism for systems study given the powerful genetic and genomic tools and resources developed with the support of NSF 2010 and Plant Genomes projects. Our group is in a unique position to carry out systems biology studies on plant immunity as the PIs have been at the frontier of using whole genome approaches in identifying essential components for all the major plant defense responses and in establishing a framework for placing these diverse components in an integrated network. However, there are still many parts missing in this network, including the identities of resistance output components and their regulators. This seriously impedes progress towards a comprehensive understanding plant immunity. Another major challenge is to understand the interconnections between different immune responses. For this, synergistic teamwork is critical for success. Our 2010 project aims to build not only a static network but also dynamic models of the plant immune system. The specific aims are:
Aim 1: Identification of the output components of plant disease resistance pathways
Aim 2: Identification of transcription factors for key transcriptomes in disease resistance pathways
Aim 3: Construction of the signaling network of plant immunity and modeling its dynamic regulation

This project is in its most productive phase as evidenced by recent major publications (and more in the pipeline). The group is now poised to use the power of systems biology approaches to decipher the complexities of plant immune response pathways.

Broader Impacts of the proposed research project
Losses due to pests and pathogens represent one of the major limitations to crop productivity worldwide. These include not only lost yield but also indirect losses of inputs, such as water, which are often limiting. The deployment of genetically engineered pathogen resistance has been hampered by the incomplete understanding of resistance mechanisms and how they interact with each other and with other physiological processes. The results of this project will expand the network of interactions among defense pathways to include those with auxin signaling and other plant hormones, and allow building of dynamic models of these interactions. With a systems level of understanding of how plants respond to pathogens, engineering resistant plants will be both more predictable and effective.


Last updated on 9/26/2016.
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