Biology subjects

Vinatzer, B. A.

Publications and source records attributed to Vinatzer, B. A..

6 recordsLinked to original sources

bioRxiv2026

Whole genome similarity provides a rapid, robust framework for classification of fungal taxa from the genus rank to intraspecies variants

Rapid and accurate microbial identification is critical for interpreting biological data in basic research and when making applied decisions on how to effectively treat patients and control human, animal, and plant diseases. Advancements in high-throughput sequencing have the potential to expedite fungal species identification and thus fungal biological research; however, analyses of ever-increasing numbers of genomes also present computational challenges. In this work, we evaluated how whole-genome similarity can serve as the basis for accurate classification and identification across the Kingdom Fungi and the Phylum Oomycota. Results from the computationally efficient k-mer-based tool sourmash are compared with those from more computationally demanding BLAST-based similarity method ANIb, as well as with conventional phylogenomic approaches, including maximum-likelihood concatenated ortholog trees and SNP-based methods. We observed that sourmash delivers orders-of-magnitude gains in speed and memory efficiency while maintaining strong concordance with phylogenomic methods. We found that a k-mer size of 21 is robust for genus and species determination, and that larger k-mers are well-suited for identification below the species rank. These results demonstrate that k-mer-based whole-genome similarity provides a scalable framework for fungal classification, enabling rapid analysis, lowering computational and bioinformatic barriers, and supporting the development of efficient identification pipelines.

bioinformatics↗

bioRxiv2025

An interactive dashboard for global reports of the Ralstonia solanacearum species complex

The Ralstonia solanacearum species complex (RSSC) is a globally distributed group of gram-negative, soil-borne bacteria that cause wilt diseases on a broad range of hosts. Due to these pathogens impact on economically important plant species, there is a need for consolidated and visualized information on RSSC pathogen isolation data. We developed an interactive dashboard designed to allow users to explore and analyze the genetic diversity of the RSSC. The dashboard visualizes data in the form of maps, charts, and tables with a variety of user-interactive filters for taxonomic, geographic, and host of isolation specifications. This Ralstonia Wilt Dashboard will aid in communicating knowledge to researchers, regulatory scientists, and other stakeholders to improve disease control and regulation. This report highlights the deployment of the Ralstonia Wilt Dashboard and provides four case studies that address focused scientific questions (https://ralstoniadashboard.shinyapps.io/RalstoniaWiltDashboard/).

microbiology↗

bioRxiv2023

Genetic and functional diversity help explain pathogenic, weakly pathogenic, and commensal lifestyles in the genus Xanthomonas

The genus Xanthomonas has been primarily studied for pathogenic interactions with plants. However, besides host and tissue specific pathogenic strains, this genus also comprises nonpathogenic strains isolated from a broad range of hosts, sometimes in association with pathogenic strains, and other environments, including rainwater. Based on their incapacity or limited capacity to cause symptoms on the host of isolation, nonpathogenic xanthomonads can be further characterized as commensal and weakly pathogenic. This study aimed to understand the diversity and evolution of nonpathogenic xanthomonads compared to their pathogenic counterparts based on their co-occurrence and phylogenetic relationship and to identify genomic traits that form the basis of a life-history framework that groups xanthomonads by ecological strategies. We sequenced genomes of 83 strains spanning the genus phylogeny and identified eight novel species, indicating unexplored diversity. While some nonpathogenic species have experienced a recent loss of a type III secretion system, specifically, the hrp2 cluster, we observed an apparent lack of association of the hrp2 cluster with lifestyles of diverse species. We gathered evidence for gene flow among co-occurring pathogenic and nonpathogenic strains, suggesting the potential of nonpathogenic strains to act as a reservoir of adaptive traits for pathogenic strains and vice versa. We further identified traits enriched in nonpathogens that suggest a strategy of stress tolerance, rather than avoidance, during their association with a broad range of host plants.

ecology↗

bioRxiv2021

Experimental evidence pointing to rain as a reservoir of tomato phyllosphere microbiota

Plant microbiota play essential roles in plant health and crop productivity. Comparisons of community composition have suggested seeds, soil, and the atmosphere as reservoirs of phyllosphere microbiota. After finding that leaves of tomato (Solanum lycopersicum) plants exposed to rain carried a higher microbial population size than leaves of tomato plants not exposed to rain, we experimentally tested the hypothesis that rain is a so far neglected reservoir of phyllosphere microbiota. Rain microbiota were thus compared with phyllosphere microbiota of tomato plants either treated with concentrated rain microbiota, filter-sterilized rain, or sterile water. Based on 16S rRNA amplicon sequencing, one-hundred and four operational taxonomic units (OTUs) significantly increased in relative abundance after inoculation with concentrated rain microbiota but no OTU significantly increased after treatment with either sterile water or filter-sterilized rain. Some of the genera to which these 104 OTUs belonged were also found at higher relative abundance on tomatoes exposed to rain outdoors than on tomatoes grown protected from rain in a commercial greenhouse. Taken together, these results point to precipitation as a reservoir of phyllosphere microbiota and show the potential of controlled experiments to investigate the role of different reservoirs in the assembly of phyllosphere microbiota.

microbiology↗

bioRxiv2019

Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences

Routine strain-level identification of plant pathogens directly from symptomatic tissue could significantly improve plant disease control and prevention. Here we tested the Oxford Nanopore Technologies (ONT) MinION sequencer for metagenomic sequencing of tomato plants either artificially inoculated with a known strain of the bacterial speck pathogen Pseudomonas syringae pv. tomato (Pto), or collected in the field and showing bacterial spot symptoms caused by either one of four Xanthomonas species. After species-level identification using ONTs WIMP software and the third party tools Sourmash and MetaMaps, we used Sourmash and MetaMaps with a custom database of representative genomes of bacterial tomato pathogens to attempt strain-level identification. In parallel, each metagenome was assembled and the longest contigs were used as query with the genome-based microbial identification Web service LINbase. Both the read-based and assembly-based approaches correctly identified Pto strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of Xanthomonas perforans group 2. This result was confirmed by whole genome sequencing of colonies isolated from one of the samples. Although in our case, metagenome-based pathogen identification at the strain-level was achieved, caution still needs to be exerted when interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.

microbiology↗

bioRxiv2019

LINbase: A Web service for genome-based identification of microbes as members of crowdsourced taxa

The development of next generation and third generation DNA sequencing technologies in combination with new efficient algorithms allows scientists to economically, quickly, and precisely identify microbes at all taxonomic levels and even attribute pathogen isolates to specific disease outbreaks. However, current taxonomic practice has not kept up with the sequencing revolution and continues to rely on cumbersome journal publications to describe new species. Here we introduce a Web service that allows any user to genomically circumscribe any monophyletic group of bacteria as a taxon and associate with each taxon a name and short description. Any other user can immediately identify their unknown microbe as a member of any of these crowdsourced taxa using gene or genome sequences. The Web service is called LINbase. It leverages the previously described concept of Life Identification Numbers (LINs), which are codes assigned to individual organisms based on genome similarity. Most genomes currently in LINbase were imported from GenBank, but users have the option to upload their own genome sequences as well. Importantly, LINbase allows users to share the precise identity of their sequenced genomes without sharing the actual genome sequences, making not yet published or private genome sequences discoverable by the scientific community stimulating collaboration between academia and industry. LINbase is available at http://www.LINbase.org.

bioinformatics↗