IDENTIFICATION OF RICE GENES THAT STRUCTURE THE LEAF MICROBIAL COMMUNITY FOR ENHANCED DISEASE RESISTANCE

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: ACTIVE
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1032175
• Grant No.: 2024-67013-42479
• Cumulative Award Amt.: $849,999.00
• Proposal No.: 2023-10907
• Project Start Date: Jul 1, 2024
• Project End Date: Jun 30, 2027
• Grant Year: 2024
• Program Code: [A1402]- Agricultural Microbiomes in Plant Systems and Natural Resources

Recipient Organization
COLORADO STATE UNIVERSITY
(N/A)
FORT COLLINS,CO 80523

Performing Department
(N/A)

Non Technical Summary
Leaf microbiomes are affected by the plants they inhabit and the environment, and even small changes in the microbiome composition can impact plant fitness. However, little is known about how plants control their microbiome during disease or defense responses, or how the assembled microbiome influences plant health. This knowledge is paramount for promoting crop resilience in the face of increasing environmental stresses. Our long-term goal is to understand how the plant immune system regulates assembly of the leaf microbiome, and how that microbiome, in turn, modulates the host immune system to resist pathogens. In this proposal, we use the rice/bacterial blight (BB) system as a model to address how plants shape their microbiomes during biotic stresses. Our aims are to (1) identify rice genes that influence leaf microbiome assemblage during susceptible and resistant interactions; (2) validate the function of candidate genes orchestrating the assembly of the rice microbiome, and (3) identify plant and microbial markers for enhanced plant resistance. Overall, the proposed research will provide in-depth understanding of how plants undergoing biotic stresses guide leaf microbiome assembly and how the leaf microbiome can help plants defend themselves from disease stresses. Ultimately, our study will pave the way for improved rice breeding to ensure a healthy microbiome that will maximize rice yield and minimize losses due to diseases, ensuring food security for millions globally.

Animal Health Component

25%

Research Effort Categories

Basic

75%

Applied

25%

Developmental

0%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
212	1530	1060	100%

Knowledge Area
212 - Pathogens and Nematodes Affecting Plants;

Subject Of Investigation
1530 - Rice;

Field Of Science
1060 - Biology (whole systems);

Keywords

rice

defense response

disease resistance

genome-wide association studies

leaf microbiome

Goals / Objectives
Leaf microbiomes are affected by plant genotypes and the environment, and even small changes in the microbiome composition can impact plant fitness. However, little is known about if and how plants control their microbiome during disease or defense responses, or how the assembled microbiome influences plant health. This knowledge is paramount for promoting crop resilience in the face of increasing environmental stresses. Our long-term goal is to understand the role and mechanisms of the plant immune system in regulating assembly of the leaf microbiome, and how that assemblage, in turn, modulates the host immune system to resist pathogens. In this proposal, we use the rice/bacterial blight (BB) system as a model to address mechanisms by which plants can shape their microbiomes during biotic stresses. Our aims are to (1) identify rice genes that influence leaf microbiome assemblage during susceptible and resistant interactions using modified Transcriptome-wide association studies (TWAS) linked to microbiome analysis; (2) validate the function of candidate genes orchestrating the assembly of the rice microbiome through gene-editing studies, and (3) identify plant and microbial markers for enhanced plant resistance by integrating machine learning and genome-scale modeling. Overall, the proposed research will provide in-depth understanding of how plants undergoing biotic stresses guide leaf microbiome assembly and how the leaf microbiome can help plants defend themselves from disease stresses. Ultimately, our study will pave the way for improved rice breeding to ensure a healthy microbiome that will maximize rice yield and minimize losses due to diseases, ensuring food security for millions globally.Our long-term goal is to decipher the role and mechanisms of the plant immune system in regulating microbiota assembly processes and how the assembly of microbiota in turn modulates the host immune system to resist pathogens. To approach this goal, we will:Aim 1: Identify rice genes that influence leaf microbiome structure during susceptible and resistant interactions with the BB pathogen Xoo using modified Transcriptome-wide association studies (TWAS) linked to microbiome analysis (MWAS) and microbiome transcriptome-wide studies (mTWAS)].Aim 2: Validate the function of the candidate genes in orchestrating the assembly of the rice microbiome through rice genome-editing studies linked with disease/resistance phenotyping and microbiome analysis.Aim 3: Integrate machine learning and genome scale metabolic modeling to a) elucidate the mechanistic role of host mediated genetic control of phyllosphere microbiome in regulating pathogen establishment; and b) identify multi-omics host and microbiota biomarkers related to disease resistance.

Project Methods
Aim 1: Identify rice genes influencing leaf microbiome structure during susceptible and resistant interactions with the bacterial blight pathogenXoo.Transcriptome-wide association studies (TWAS) are a powerful approach to identify genes functioning in complex traits. Unlike traditional GWAS, which focuses on SNPS and their associations with traits, TWAS incorporates transcriptomic data to identify genes whose expression levels are associated with a specific phenotype, in our case, disease susceptibility/resistance and microbial community structure. In addition, TWAS is accommodating of small sample sizes and extreme phenotypes following the framework of Li et al. In this study, we will integrate gene expression data from rice AILs undergoing susceptibility or resistance with our existing GWAS results to identify candidate genes whose altered expression contributes to susceptibility or resistance. We will also identify microbial groups whose abundance is associated with susceptibility or resistance and determine the impact of identified candidate genes on abundance of those microbial groups.Aim 2: Validate the function of the candidate genes in orchestrating the assembly of the rice microbiome through rice genome-editing studies linked with disease/resistance phenotyping and microbiome analysis.We seek to understand the molecular mechanisms by which disease-resistance genes modulate the composition and diversity of the rice microbiome. Candidate genes identified from analysis of previous work and from the analyses in Aim 1 will be used to investigate their effect on the leaf microbial structure and disease resistance. First, we will utilize existing IR64 lines, both edited and unedited, in promoters of SWEET14 (not activated by PXO86 TALE AvrXa7 due to mutation in promoter = no disease) and SWEET11 and OsSWEET13 (susceptible due to activation of wild type SWEET14 promoter by PXO86 TALE AvrXa7 = disease) to analyze the impact of edited sugar transporters on the leaf microbiome under active resistant and disease interactions. By preventing expression of these sugar transporters, we will be able to discern how changes in sugar availability can affect the structure and diversity of the microbiome during resistant vs susceptible interactions and infected vs noninfected conditions.Second, we will use existing IR64 rice lines edited in the promoters of three DR genes (OsPAL4, OsGLP8-4, OsOXO4) (Table 2) that were confirmed to play a role in rice defense when activated by pathogen attack. In the DR-edited lines where DR gene activation by pathogen infection is absent and disease susceptibility increases, we will determine if changes in DR-gene regulated defenses and associated metabolites or structures affect the structure and diversity of the microbiome under infected vs noninfected conditions.Third, we will use CRISPR/Cas gene editing to knock out function of two candidate genes identified from the Roman-Reyna study,and evaluate the impact of the knock-outs on the rice microbiome and rice resistance to Xoo. The candidate genes Os02g019000 and Os04g235400 have tentatively been selected due to their colocalization with known disease and pest-resistance QTLs such as Xa2 (chr04[29644621-33083265]) for bacterial blight resistance, qSB-2 (chr02[23457248-30711734]) for sheath blight resistance and qGRH-2 chr02[23191143-31166188] for green rice leafhopper (GRH) resistance.Finally, we will knock out four candidate genes identified in Aim 1 using CRISPR/Cas gene editing, and evaluate the impacts on the rice leaf microbiome community and rice resistance to Xoo. The candidates will be selected based on the confidence of their prediction, and their putative functions. We will compare metagenome profiles between resistant and susceptible genotypes with and without infection, with the goal of understanding how disease-resistance genes may shape the microbiome's composition, particularly in response to the presence of disease-causing agents. This comparison will give us valuable insights into the role of predicted genes in microbiome assembly and help us uncover potential mechanisms of disease resistance.Aim 3: Integrate machine learning and genome scale metabolic modeling to a) elucidate the mechanistic role of host mediated genetic control of phyllosphere microbiome in regulating pathogen establishment; and b) identify multi-omics host and microbiota biomarkers related to disease resistance.Omics tools have revolutionized our ability to elucidate the functions of individual microbes in simple microbial communities.Yet, it remains challenging to predict microbial function under different environmental conditions and in response to interactions among different microbial taxa in more complex settings like those typical of agricultural ecosystems. Currently, we lack the knowledge, technologies, and computational and modeling approaches to predict how microbial interactions will affect community function. Here we will develop a predictive framework that can be used to provide tangible recommendations for exploiting the benefits that plant-associated microbiome provides to their hosts under stress conditions.

Progress 07/01/24 to 06/30/25

Outputs
Target Audience:Scientific colleagues through publications and discussions at meetings. Changes/Problems:As described above, we focused on Aim 2 this year, because of opportunities to move it forward more quickly (not because of problems). What opportunities for training and professional development has the project provided?At Colorado State University, this project currently has a Post Doctoral Fellow (Dr. Federico Martin, Research Associate II). Dr. Martin is trained as a molecular plant biologist, and in this project is adding microbiome science to his repertoire. In addition, he designed the guide RNAs for the ten rice defense response genes to be edited. One undergraduate student (Ellie Misra-Matson) is assisting Dr. Martin on aspects of this project, in particular, in screening rice mutants. Kristen Otto is a Research Associate working with Dr. Trivedi. She is performing the amplicon sequencing and will prepare samples for metagenome analysis. At IRRI, two Assistant Scientists, Israel Dave Ambita and Ian Paul Navea, are assisting Dr. Schepler-Luu. Israel performed the screen house studies involving the SWEET edited lines and near-isogenic lines, including the preparation of the DNA and RNA for transfer to CSU. Ian is performing the gene editing in rice. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?All amplicon sequencing and analysis for the SWEET edited and near-isogenic lines and metagenome analysis of a subset of the lines will be completed. In addition, we will complete the transcriptome analysisand begin developing a manuscript on this data. Newly edited lines will be advanced to the homozygous state for the edits and the edits confirmed. When ready, screen house experiments with these lines, with inoculation with Xoo, will be initiated.

Impacts
What was accomplished under these goals? Progress (October, 2024-April, 2025): In the first 6 months of the project, we prioritized Aim 2 for several reasons. First, seed for lines edited in different SWEET genes werereadily available, and provided the opportunity to assess how changes in sugar availability could affect the structure and diversity of the leaf microbiome under active resistant and disease interactions. Second, we were able to piggyback on another screenhouse experiment underway at IRRI that allowed us to evaluate the impacts of Xoo interactions with 5 additional BB R genes on the leaf microbiome; these R genes have different modes of action. Third, to ensure we could complete the assessment of edited candidate genes (beyond the SWEETs) within the timeframe of the proposal, we initiated the CRISPR/Cas gene editing of target genes in the first year. We established screenhouse (mimics field conditions) experiments of rice lines with promoter edits in OsSWEET13, 11 and 14. To allow evaluation of the impact of rice genetic background, we selected edits in three different rice varieties (IR64, Ciherang-sub1, and NSIC RC160). The lines were inoculated with X. oryzae pv. oryzae strains PXO339 or PXO86. Leaves were sampled at 8 days post inoculation (dpi) for amplicon sequencing (16s/ITS amplicon sequencing) and metagenome analysis (only a subset will be moved forward for metanalysis). In addition, leaves were sampled for RNA Seq analysis to determine impact on the rice leaf transcriptome. Leaf responses to the Xoo inoculations (lesion lengths) were assessed at 14 dpi. The edited lines showed the expected responses to pathogen inoculation, confirming the edits were intact and the Xoo strains were behaving appropriately. We have completed DNA extractions and RNA extractions are underway. Once sequencing is complete, we will progress to Aim 3. In a parallel screenhouse experiment, screenhouse experiments of near-isogenic rice lines with the R genes Xa4, xa5, Xa7, xa13, and Xa21 were inoculated with Xoo strain PXO86. Leaves were sampled at 8 dpi for amplicon sequencing and for RNA Seq analysis as above. Leaf responses to the Xoo inoculations (lesion lengths) were assessed at 14 dpi. The near-isogenic lines showed the expected responses to pathogen inoculation. We have completed DNA extractions and RNA extractions are underway. Once sequencing is complete, these will also progress to Aim 3. Editing of candidate genes identified in previous studies is being performed in rice cultivar IR64, for which a well-annotated genome is available. Historically, IR64 has been recalcitrant to editing, but recent improvements in transformation practices as well as editing technologies have overcome this problem. We used two editing strategies (Dual pegRNA and Dual sgRNA) to generate knock-out edits in two target genes, a catalase isozyme A (OsCatA), a malate synthase (OsMS). Plants with these edits are being regenerated now. Given the high level of success in editing in IR64, we have proceeded to target ten additional genes to generate knock-out versions, that include: five members of phenylalanine ammonia lyase (PAL) gene family, two members of the Germin-like protein (GLP) gene family, and three members of the WRKY transcription factor gene family. Guide RNAs for all these genes have been generated and the development of the vectors is in progress. Transformation of rice plants will take place in the coming months. In addition, we are pursuing an alternative editing approach to generating gene knock-out lines. IR64 (an indica variety) contains an allele of an oxalate-oxidase (OsOXO4) gene that shows lower transcriptional activity during immune responses against multiple rice pathogens compared to the allele found in japonica rice varieties. The lower transcriptional activity is due to polymorphisms in the proximal promoter area of the OsOXO4 gene that affect specific cis-regulatory elements (CRE). We have taken a prime editing approach to create insert of short indel containing multiple CREs into the OsOXO4 gene promoter to mimic the japonica allele. The vector is currently being assembled and the transformation of IR64 plants will take place in the coming months at the same time as the above-mentioned constructs.

Publications

• Type: Peer Reviewed Journal Articles Status: Published Year Published: 2025 Citation: Delgado-Baquerizo M, Singh BK, Liu YR, S�ez-Sandino T, Coleine C, Mu�oz-Rojas M, Bastida F, Trivedi P. Integrating ecological and evolutionary frameworks for SynCom success. New Phytol. 2025 Apr 3. doi: 10.1111/nph.70112. Epub ahead of print. PMID: 40177999.