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Fumiaki Katagiri



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Ph.D., Rockefeller University, 1991 
M.S., Kyoto University, Japan, 1986 
B.S., Kyoto University, Japan, 1984 

Research Statement

Plant Immune Signaling Network

A major type of plant immunity against pathogen is inducible immunity: immune responses are turned on upon recognition of pathogen attack. The immune signaling network mediating signal transduction for inducible immunity needs to be highly resilient because pathogens that can evolve much faster than plants interfere with components of the network. Essentially, resilience of the plant immune signaling network hides the underlying mechanisms from pathogen evolution. At the same time, since immune responses are expensive, unnecessary immune responses cost plant fitness. Since the reliability of pathogen attack signals varies, outputs of the immune signaling network need to be tunable through selection according to the reliability of pathogen attack signals. A main focus of our research is to understand how the network properties, such as resilience and tunability, emerge from the structure and the dynamics of the plant immune signaling network.

In a resilient network, a deficiency in part of the network does not strongly affect the network function because some other parts of the network compensate the deficiency. Thus, a conventional genetic approach of comparing a single gene mutant phenotype to the wild-type phenotype does not provide much information about the mechanism. We developed an approach called network reconstitution to overcome this problem: first, multiple genes, each of which is important for different parts of the network (different subnetworks), are simultaneously mutated to almost completely break the network function; second, the subnetworks are restored to the broken network, one by one or in combinations, to learn the function of each subnetwork and interactions between subnetworks. Thus, the network reconstitution approach enables mechanistic understanding of a resilient network. 

We have been using the model plant Arabidopsis thaliana to apply the network reconstitution approach to the immune signaling network. We have been collecting high-dimensional data, such as mRNA profiles by RNA-seq, from a set of plants with comprehensive reconstituted versions of the network, through the time course after treatment with various immune elicitors. In collaboration with Chad Myers’ group (UMN, Dept of Computer Science and Engineering), we are currently applying differential equation-based models to these data to discover the quantitative rules of mechanistic interactions among the subnetworks during the dynamic process of response to the immune elicitors. Once we learn most of such rules, we will be able to simulate the network dynamics in silico to investigate emergence of the network properties in detail. 

We are working on extension of this modeling approach to spatially heterogeneous cases. In plants, cells that directly recognize pathogens and cells surrounding these cells respond differently (spatial heterogeneity). In collaboration with Shigeyuki Betsuyaku’s group (University of Tsukuba, Japan), we are developing a technology to generate spatial genetic heterogeneity in a laser-guided manner: e.g., only cells that were previously illuminated with a laser have a specific receptor gene functional. We are planning to use this technology to collect spatially heterogeneous data to support a differential equation model approach that allows spatial heterogeneity. 

The source of complex network behaviors is convergence of multiple signals at some network components. We are biologically studying such signal converging points at the molecular level. For example, we have experimentally discovered a subnetwork in which a signal for one mode of immunity inhibits that for another mode of immunity. This discovery appears to represent a mechanism to limit unnecessary immune responses. 

We are also interested in how such a resilient network evolved during evolution of land plants. We do not know how but generally know when. Lycophytes or land plants lower than lycophytes, such as mosses, lack many important network component genes. Such genes start to appear in ferns and gymnosperms. All angiosperms, including basal angiosperms, have almost complete sets of them. Thus, evolution of the immune signaling network we see in Arabidopsis started in a common ancestor of ferns and higher plants and has largely completed in the most recent common ancestor of all angiosperms. Note that this does not mean that lower land plants lack immunity or that they do not have any immune signaling subnetworks common to angiosperms. This means that how the components are put together as a network is very different between lower land plants and angiosperms. 

Having similar sets of network components does not guarantee that the immune signaling networks of angiosperms work in a similar manner. In collaboration with Jane Glazebrook’s group (UMN, Dept of Plant and Microbial Biology), we are investigating whether we can detect differences in subnetwork interactions among Arabidopsis, tomato, and rice, by applying the network reconstitution approach to these species. The CRISPR/Cas9 technology has made the network reconstitution approach practical in plant species other than Arabidopsis as well. 

Having undergraduate researchers involved is another focus of ours. Every semester 10+ undergraduate students had been working together as a team to map Arabidopsis immunity genes using a quantitative genetics approach. Due to the renovation of the lab space, the program is interrupted in fall, 2018. We are planning to resume the program with a new project in spring, 2019. 

Selected publications 

  1. Tsuda, K., Sato, M., Stoddard, T., Glazebrook, J., and Katagiri, F. (2009) “Network properties of robust immunity in plants” PLoS Genet 5(12), e1000772. 
  2. Sato, M., Tsuda, K., Wang, L., Coller, J., Watanabe, Y., Glazebrook, J., and Katagiri, F. (2010) “Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling” PLoS Pathog 6(7), e1001011.
  3. Qi, Y., Tsuda, K., Glazebrook, J., and Katagiri, F. (2011) “Physical association of pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) immune receptors in Arabidopsis” Mol Plant Pathol 12, 702-708.
  4. Qi, Y., Tsuda, K., Nguyen, L. V., Wang, X., Lin, J., Murphy, A. S., Glazebrook, J., Thordal-Christensen, H., and Katagiri, F. (2011) “Physical association of Arabidopsis hypersensitive induced reaction proteins (HIRs) with the immune receptor RPS2” J Biol Chem 286, 31297-21307.
  5. Igarashi, D., Tsuda, K., and Katagiri, F. (2012) “The Peptide Growth Factor, Phytosulfokine, Attenuates Pattern-Triggered Immunity” Plant J. 71, 194-204.
  6. Igarashi, D., Tsuda, K., and Katagiri, F. (2013) “Pattern-triggered immunity suppresses programmed cell death triggered by fumonisin B1.” PLoS ONE 8, e60769.
  7. Tsuda, K., Mine, A., Bethke, G., Igarashi, D., Botanga, C. J., Tsuda, Y., Glazebrook, J., Sato, M., and Katagiri, F. (2013) “Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis.” PLoS Genet 9, e1004015.
  8. Kim, Y., Tsuda, K., Igarashi, D., Hillmer, R. A., Sakakibara, H., Myers, C. L, and Katagiri, F. (2014) “Signaling mechanisms underlying the robustness and tunability of the plant immune network” Cell Host Microbe 15, 84-94.
  9. Katagiri, F., Canelon-Suarez, D., Griffin, K., Petersen, J., Meyer, R. K., Siegle, M., and Mase, K. (2015) “Design and Construction of an Inexpensive Homemade Plant Growth Chamber” PLOS ONE 10, e0126826.
  10. Hillmer, R. A., Tsuda, K., Rallapalli, G., Asai, S., Truman, W., Papke, M. D., Sakakibara, H., Jones, J. D. G., Myers, C. L., and Katagiri, F. (2017) “The Highly Buffered Arabidopsis Immune Signaling Network Conceals the Functions of its Components” PLOS Genet 13, e1006639.
  11. Hatsugai, N., Igarashi, D., Mase, K., Lu, Y., Tsuda, Y., Chakravarthy, S., Wei, H.-L., Foley, J. W., Collmer, A., Glazebrook, J., and Katagiri, F. (2017) “A plant effector-triggered immunity signaling sector is inhibited by pattern-triggered immunity” EMBO J 36, 2758-2769.
  12. Lu, Y., Truman, W., Liu, X., Bethke, G., Zhou, M., Myers, C. L., Katagiri, F., and Glazebrook, J. “Different modes of negative regulation of plant immunity by calmodulin related genes” Plant Physiol 176, 3046-3061.
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