Biology subjects

Roman-reyna, V.

Publications and source records attributed to Roman-reyna, V..

5 recordsLinked to original sources

bioRxiv2026

Metagenomics for bacterial spot pathogen and virulence factor tracking for Ohio fresh market tomato and pepper production

Bacterial spot is a consistent threat to global tomato and pepper productions; however, Ohios fresh market production currently lacks the updated surveillance data necessary to provide accurate management solutions. While traditional diagnostics focus on identification of a single causal agent, shotgun metagenomic sequencing (MGS) offers a comprehensive view of the infection court. An assignment-first MGS workflow was developed and validated in this study, utilizing Kraken2 databases to extract Xanthomonas species associated with bacterial spot and to characterize the microbial communities of bacterial spot in Ohio production systems. Through in silico spiking experiments, thresholds were established for bacterial spot identification. Species and pathovar identification via average nucleotide identity (ANI) remained accurate at abundance as low as 0.1%. A minimum of 2% Xanthomonas reads were required for high genome completeness (BUSCO >90%) and 3% for reliable type III secretion system (T3SS) effector profiling. Analysis of 63 samples from fresh-market production fields identified Xanthomonas hortorum pv. gardneri, Xanthomonas euvesicatoria pv. euvesicatoria, and Xanthomonas arboricola residing in symptomatic samples, alongside other taxa including Pseudomonas and Stenotrophomonas. Phylogenetic comparisons of metagenome-assembled genomes (MAGs) were comparable to whole genome sequences (WGS) from the same samples, supporting the reliability of culture-independent diagnostics. These results provide a robust framework for utilizing metagenomics as a diagnostic tool, expanding our knowledge of bacterial spot population structure in Ohio, and uncovering the bacterial communities associated with bacterial spot.

genomics↗

bioRxiv2026

Ecogenomic Diversity of Clavibacter nebraskensis in North America

Gosss wilt and leaf blight of maize is caused by Clavibacter nebraskensis and has reemerged as an important disease in North America. Despite its epidemiological relevance, this species remains poorly characterized in terms of population structure, functional diversity, and ecological differentiation, particularly among strains reported from Mexico. In this study, long-read whole-genome sequencing and phenotypic assays were used to characterize genomic diversity, virulence, and fitness-associated traits in C. nebraskensis. We generated 24 long-read genomes, including 20 contemporary Mexican isolates and four historical United States strains collected between 1969 and 1996, and compared them with publicly available genomes from North America and South Africa. Phylogenomic analyses confirmed that all strains cluster within the C. nebraskensis clade, and gene accumulation curves supported a closed pangenome with accessory gene variation linked to geographic origin and isolation period. Functional assays showed strain-level variation in virulence, enzymatic activity, bacteriocin antagonism, polysaccharide production, biofilm formation, and pigmentation. Cellulolytic activity was associated with disease severity, whereas pigment-related traits were linked to thiamine metabolism. Overall, these results indicate that C. nebraskensis comprises ecologically heterogeneous populations, structured around alternative survival and competition strategies. Integrating genome-wide comparisons with functional characterization of fitness-related traits provides a framework for understanding the biological factors underlying Gosss wilt. dynamics

microbiology↗

bioRxiv2023

Live tracking of a plant pathogen outbreak reveals rapid and successive, multidecade episome reduction

Quickly understanding the genomic changes that lead to pathogen emergence is necessary to launch mitigation efforts and reduce harm. Often the evolutionary events that result in an epidemic typically remain elusive long after an outbreak, which is particularly true for plant pathogens. To rapidly define the consequential evolutionary events result in pathogen emergence, we tracked in real-time a 2022 bacterial plant disease outbreak in US geranium (Pelargonium x hortorum) caused by Xhp2022, a novel lineage of Xanthomonas hortorum. Genomes from 31 Xhp2022 isolates from seven states showed limited chromosomal variation, and all contained a single plasmid (p93). Time tree and SNP whole genome analysis estimated that Xhp2022 emerged in the early 2020s. Phylogenomic analysis determined that p93 resulted from cointegration of three plasmids (p31, p45, and p66) present in a 2012 outbreak. p31, p45 and p66 were individually found in varying abundance across X. hortorum isolates from historical outbreaks dating to 1974 suggesting these plasmids were maintained in the broader metapopulation. p93 specifically arose from two co-integration events from homologous and Tn3 and XerC-mediated site-specific recombination. Although p93 suffered a 49kb nucleotide reduction, it maintained critical fitness gene functions encoding, for example, metal resistance and virulence factors, which were likely selected by the ornamental production system. Overall we demonstrate how rapid sequencing of current and historical isolates track the evolutionary history of an emerging, ongoing threat. We show a recent, tractable event of genome reduction for niche adaptation typically observed over millenia in obligate and fastidious pathogens. SignificanceGenome-resolved epidemiology is rapidly changing how we track pathogens in real-time to support stakeholders and health. This research highlights how we responded to a current disease outbreak of geranium. Our work revealed that a new group of the bacterial plant pathogen Xanthomonas horotrum emerged in 2022 as a result of a recent genome reduction. We determined that three distinct plasmids were present in the broader X. hortorum metapopulation since 1974. In 2012, the three plasmids were altogether present in individual isolates; then in 2022, all three plasmids co-integrated while maintaining critical fitness genes but losing extraneous genomic material. This parallels genome efficiency and reduction that we see across millenia or even millions of years with obligate parasites with increased niche-specificity.

microbiology↗

bioRxiv2021

Metagenomic sequencing for rapid identification of Xylella fastidiosa from leaf samples

Xylella fastidiosa (Xf) is a globally distributed plant pathogenic bacterium. The primary control strategy for Xf diseases is eradicating infected plants; therefore, timely and accurate detection is necessary to prevent crop losses and further pathogen dispersal. Conventional Xf diagnostics primarily relies on quantitative PCR (qPCR) assays. However, these methods do not consider new or emerging variants due to pathogen genetic recombination and sensitivity limitations. We developed and tested a metagenomics pipeline using in-house short-read sequencing as a complementary approach for affordable, fast, and highly accurate Xf detection. We used metagenomics to identify Xf to strain level in single and mixed infected plant samples at concentrations as low as one picogram of bacterial DNA per gram of tissue. We also tested naturally infected samples from various plant species originating from Europe and the United States. We identified Xf subspecies in samples previously considered inconclusive with real-time PCR (Cq > 35). Overall, we showed the versatility of the pipeline by using different plant hosts and DNA extraction methods. Our pipeline provides taxonomic and functional information for Xf diagnostics without extensive knowledge of the disease. We hope this pipeline can be used for early detection of Xf and incorporated as a tool to inform disease management strategies. IMPORTANCEXylella fastidiosa (Xf) destructive outbreaks in Europe highlight this pathogens capacity to expand its host range and geographical distribution. The current disease diagnostic approaches are limited by a multiple-step process, biases to known sequences, and detection limits. We developed a low-cost, user-friendly metagenomic sequencing tool for Xf detection. In less than three days, we were able to identify Xf subspecies and strains in field-collected samples. Overall, our pipeline is a diagnostics tool that could be easily extended to other plant-pathogen interactions and implemented for emerging plant threat surveillance.

microbiology↗

bioRxiv2019

The rice leaf microbiome has a conserved community structure controlled by complex host-microbe interactions

Understanding the factors that influence the outcome of crop interactions with microbes is key to managing crop diseases and improving yield. While the composition, structure and functional profile of crop microbial communities are shaped by complex interactions between the host, microbes and the environment, the relative contribution of each of these factors is mostly unknown. Here, we profiled the community composition of bacteria across leaves of 3,024 rice (Oryza sativa) accessions from field trials in China and the Philippines using metagenomics. Despite significant differences in diversity between environments, the structure and metabolic profiles of the microbiome appear to be conserved, suggesting that microbiomes converge onto core functions. Furthermore, co-occurrence analysis identified microbial hubs that regulate the network structure of the microbiome. We identified rice genomic regions controlling the abundance of these hubs, enriched for processes involved in stress responses and carbohydrate metabolism. We functionally validated the importance of these processes, finding that abundance of hub taxa was different in rice mutants with altered cellulose and salicylate accumulation, two major metabolites at the host-microbe interactions interface. By identifying key host genomic regions, host traits and hub microbes that govern microbiome composition, our study opens the door to designing future cropping systems.

microbiology↗