Performing Department
(N/A)
Non Technical Summary
Citrus greening, or Huanglongbing (HLB), is a devastating disease threatening the entire U.S. citrus industry. This research will mitigate citrus HLB losses by creating a portfolio of HLB resistance genes for transformation and gene editing approaches. Specific protein-protein interactions are a hallmark of compatible and incompatible host-pathogen outcomes. In a novel strategy that leverages high throughput data analysis and AI tools, citrus proteins that interact with Candidatus Liberibacter asiaticus (CLas) effectors in the phloem will be identified. Experimentally documented phloem-enriched citrus proteins that are upregulated during infection will be selected. Systematic analysis of CLas genomes will identify secreted hypothetical effector proteins conserved across these genomes. AlphaFold 3.0 will predict interaction of selected CLas effectors and citrus proteins. Potential gene targets with significant AlphaFold scores will be verified experimentally for strong interactions and for upregulation in infected citrus, as well as other characteristics. Potential gene targets will be ranked, and gene editing/transformation vectors will be constructed for up to 30 genes. A selection of citrus varieties and elite germplasm, chosen in consultation with growers, will be designated for transformation and gene editing. Transgenic/edited citrus lines will be propagated, and a subset of the plants will be transferred to field, while the remaining plants will be inoculated with CLas infected psyllids and evaluated for pathogen titer, symptomology, and expression of modified genes monthly, in greenhouse studies for up to two years. Research progress will be shared with the citrus industry and HLB scientists at meetings and through scientific and trade journals.?
Animal Health Component
35%
Research Effort Categories
Basic
50%
Applied
35%
Developmental
15%
Goals / Objectives
The major goalof this research is to mitigate citrus HLB financial losses by creating a portfolio of verified Huanglongbing (HLB) resistance genes, incorporate cognate genetic modifications into elite citrus germplasm, and contribute to our understanding of this host pathogen system to support consistent and sustained disease management.Objective 1. Build a data pipeline to identify hypothetical secreted CLas proteins and upregulated phloem enriched citrus proteins.We will systematically analyze CLas genomes to identify potential CLas effectors. Initially we will focus on novel proteins that have the following criteria: i.) for which functions are not known; ii.) which are conserved across CLas genomes; iii.) and which are secreted. We will use Pfam to exclude proteins with well-annotated domains of known function, focusing instead on those with Domains of Unknown Function (DUF) or proteins lacking any identifiable domain. Secondly, we will develop an annotated database of citrus transcripts and proteins that strongly and regularly respond to CLas infection. We will interrogate the efficiency of our data pipeline using verified transcriptional and proteomic data. Using high throughput data pipeline and in silico protein structure and interaction analysis it is now possible to screen all high potential citrus protein candidates with putative CLas effectors in a pair-wise fashion. However, it is strategic to first focus on citrus proteins that are documented to be enriched in the phloem, where the initial host-pathogen interactions assumedly occur.proteome from infected citrus [7]. This database will be the initial focus of initial in silico and laboratory-based analysis of interacting proteins (Figure 1). Other strategies to expand this citrus proteome database will be examined, such as identifying homologs of citrus proteins known to be phloem enriched in other plant species.Objective 2.Identify Clas and citrus proteins that are predicted to interact in the phloem and experimentally verify these interactions.In this objective we will take a novel approach to the discovery of CLas effectors and citrus protein targets, which have potentially for gene editing for the purpose of enhancing HLB resistance in citrus. Specifically, we will use AlphaFold3 to identify Clas and citrus proteins that reside in the phloem and strongly interact.Experimental validation of AlphaFold interaction scores will be conducted using several standard methods:Yeast two-hybrid (Y2H), co-immunoprecipitation (co-IP), andMBP/GST pull-down assay.Objective 3. Test potential resistance genes in citrus by creating transgenic citrus plants for analysis.Objective 4. Engage stakeholders to communicate research plans and results. Dissemination of research findings and collection ofgrower's feedback will be an essential part of this project. Given the long timeline required for thoroughly testing the effects of gene editing on growth and productivity and the potential for cultivar and environmental variability, it is critical that the most valuable cultivars and the best elite citrus germplasm is included in our genetic editing pipeline. Growers are the best source ofthis information, and we will actively solicit their input. Results from our work will be delivered to growers via educational talks, posterpresentations, and workshops at extension events in Florida, California, and Texas. We will present and discuss our results with growers in various grower's meetings including the Citrus Expo in Fort Myers, Florida, the Citrus Show in Fort Pierce, Florida, Growers Day at the Citrus Research and Education Center, University of Florida, University of California Riverside Citrus Day, Citrus Research Board Annual Citrus Conference, and other extension activities. Followingthe talks and poster presentation we will seek for growers and industry input via paper, mail, and electronic surveys. The information collected will be considered to adjust the research and extension activities. In addition, the findings will be disseminated via printed publications in trade journals, such as 'Citrus Industry' and 'Citrograph'.
Project Methods
-Bioinformatic analysis of citrus genomes and Liberibacter genomes to generate a list of possible pathgenic and resistance genes-Systematic analysis of citrus greening data and publications using large language models-Develop curated databases using big data tools-Create a data pipeline for selection of potential citrus disease resistance genes based on protein-protein interaction modles (Alpha Fold 3)- Confirm published experimental data on protein - protein interactions- Confirm published experimental data on upregulation of citrus genes during expression- Rank potential resistance genes and develop gene editing constructs- Test gene edited citrus plants for CLas reproduction and disease phenotypes-Present research progress and results at citrus meetings and in grower publications-Publish scientific findings in impactful journals, including data bases and methods developed in the project