UNDERSTANDING BENEFICIAL AND PATHOGENIC MICROORGANISMS AND THEIR INTERACTIONS WITH EACH OTHER AND HOSTS TO CONTROL PLANT DISEASES

This project is to create new, more effective, and more sustainable strategies to manage a plant-parasitic nematode (sugarbeet cyst nematode). The sugarbeet cyst nematode causes considerable economic damage, affecting sugar beets and a wide range of other important crop plants such as broccoli, Brussels sprouts, cabbage, canola, cauliflower, kale, mustard, spinach, Swiss chard, radish, rapini, and others. This nematode has been reported to be among the most damaging plant-parasitic nematodes in the world. Current methods to control this nematode are inadequate, and therefore new management strategies are needed. Our project will endeavor to create new management strategies by determining the relationships between a beneficial fungus and the sugarbeet cyst nematode, and then using that information to manage the nematode. If our project is successful, it has the potential to be extended to other nematodes that cause large amounts of crop damage, including the soybean cyst nematode.This project is also to create new, more effective, and more sustainable strategies to manage huanglongbing (HLB) disease of citrus. HLB is the most devastating citrus disease that affects all types of citrus. Current methods to control HLB are inadequate, and therefore new management strategies are needed. Our approach is to use a harmless virus to deliver antimicrobial molecules to the citrus phloem, which is a part of the plumbing in a plant, and also the habitat of the bacterium that is believed to cause HLB. We will create our antimicrobial molecules by linking a peptide that blocks an essential CLas enzyme and a peptide that enables penetration into the putative HLB pathogen. Essential enzymes are those that, when blocked, will kill the organism. We have identified the essential enzymes of the putative HLB pathogen by creating and analyzing metabolic models of the putative HLB pathogen. This project is also to create and utilize an in silico metabolic model of HLB. Such models are mathematical representations of functioning cells. We expect that this approach will provide researchers, engineers and agribusinesses with a powerful suite of tools and an unprecedented base of knowledge - which we expect will enable them to create (i) molecules that kill the putative HLB pathogen, (ii) citrus trees that are resistant to HLB, and (iii) early HLB detection methods.

1a. Determine the Interactions Among Crop Cultivars and the Indigenous Hyperparasite Dactylella oviparasitica Enabling Development of Sugarbeet Cyst Nematode Suppressive Soils1b. Developing Cropping Decision Models that Enable the Creation of Maintenance of Soils that Suppress the Sugarbeet Cyst NematodeThis objective is to develop predictive models of the population dynamics between D. oviparasitica and H. schachtii in relation to the types of sugar beet cultivars, soil and D. oviparasitica. This will be accomplished by performing a series of greenhouse experiments using sugar beet field soils from the Imperial Valley that contain various amounts of D. oviparasitica.The sugar beet cultivars are those commonly used by Imperial Valley (CA) growers. The comparison of soils that have been autoclaved and not is a standard method enabling the determination of biological suppressiveness; if there are microorganisms that reduce H. schachtii population densities in a soil, such reductions will be observed in the non-autoclave soils compared to the autoclaved soil, both of which will be subsequently infested with H. schachtii as described below. In addition, our experiments will only examine soils that contain H. schachtii population densities that are above the economic damage threshold of 2 eggs/gram of soil (1), because this is when an organism like D. oviparasitica will be needed. To accomplish this, we will both enumerate the number of nematodes in each field soil as described above in RT2 and add H. schachtii J2 juveniles as described below. We will also include one control soil, which will be our H. schachtii suppressive 9E field soil located at the Agricultural Operations on the UC Riverside campus (2).Probit regression analyses will be used to develop predictive models, which will be used to develop new and more effective cropping decision models for sugar beet growers.1c. Determine the Interactions Among Crop Cultivars and the Indigenous Hyperparasite Dactylella oviparasitica Enabling Development of Soils Suppressive Against Other Cyst Nematodes Including the Soybean Cyst Nematode1d. Developing Cropping Decision Models that Enable the Creation of Maintenance of Soils that Suppress the Other Cyst Nematodes Including the Soybean Cyst NematodeWe will perform studies similar to those described in Objective 1a/1b above to complete these objectives.2a. Create Peptides that Specifically Kill CLas with High Efficacy, and Test Them in Citrus by CTV Delivery and Engineered Plant DeliveryTo identify the anti-CLas peptides for this sub-objective, we will perform in silico docking experiments using homology models of essential CLas enzymes. Homology models are built using existing structure models of related homologous proteins. We will construct and use homology models because crystal structures of CLas enzymes are not currently available. An example of a homology model that we constructed is the CLas serine/tyrosine phosphatase (STP) structure, which was built using the Swissmodel workspace. Supporting this approach, we demonstrated that homology models can be very effectively used in studies endeavoring to identify inhibitory molecules, because we used this CLas STP model to design molecules (C1 and C2) that effectively reduced CLas populations (unpublished). Finally, an amino acid sequence analysis determined that 12 of the aforementioned 82 essential CLas enzymes have related homologous proteins with an existing structure, which will enable us to build homology structure models. One example essential CLas enzyme is acetyl-CoA carboxylase, and the homology model we built for it is shown to the right. Given these results, we will be able to create homology models for 12 essential CLas enzymes, which will provide us with plenty of targets to successfully complete this sub-objective.2b. Create and Utilize Metabolic Models of CLas, Citrus and ACP, and Their InteractionsKarsten Zengler's group will build high-quality metabolic models for the three organisms involved in HLB: CLas, ACP, and citrus. Some of this research has been completed, as Zengler created metabolic models for six CLas strains and Liberibacter crescens (BT-1) (manuscript in preparation). To create the other two models, Zengler's group will follow the established protocol for reconstructing quality metabolic models (3).Because metabolic models are mathematical representations functional cells, and their interactions, they can be used for a myriad of important purposes. For example, a prominent feature of these models is the ability to analyze and contextualize omics datasets - e.g. all of the RNA transcripts that are expressed when a pathogen invades a host. This contextualization allows this dataset to be greatly expanded from just a list of RNA transcripts to include all of the other cellular reactions and pathways that are turned on or off under the conditions when that sample was collected. Contextualization of omics datasets can also reveal the molecular basis of the interactions between different organisms and the associated environmental conditions. It also enables one to predict phenotypes a priori.2c. Identify Non-Pathogenic Microbes that Inhabit the Citrus Phloem, and Which Could be Used to Deliver Anti-CLas Agents to Manage HuanglongbingWe have used an optimized phloem collection method involving scraping bark peels. Illumina sequence analyses have been used to identify several non-pathogenic bacteria that inhabit the phloem. To validate these prior findings, the next steps will include performing microscopic experiments (FISH) and adding tagged bacteria to citrus and tracking their movement.3. Develop New Methods for Molecular Microbial Ecology and Their Associated Bioinformatic AnalysesWe currently are adding new functionalities to our PRISE2 algorithm for PCR primer and probe design.REFERENCES CITED1. Cooke DA, Thomason IJ, McKinney HE, Bendixen WE, Hagemann RW. 1979. Chemical Control of Heterodera schachtii on Sugarbeet in California. J Nematol 11:205-6.2. Westphal A, Becker JO. 1999. Biological Suppression and Natural Population Decline of Heterodera schachtii in a California Field. Phytopathology 89:434-40.3. Thiele I, Palsson BØ. 2010. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nature protocols 5:93.