bioRxiv Science⌕ Search

Biology subjects

Tighe, S.

Publications and source records attributed to Tighe, S..

4 recordsLinked to original sources

Differential efficiency of sampling devices in the measurement of microbial diversity of Yellowstone National Park hot springs

Metagenomic characterization of low-biomass Yellowstone National Park (YNP) hot spring waters remains challenging because microbial recovery is influenced by filtration methodology, sample preservation, DNA extraction, and sequencing strategy. We characterized thermophilic microbial communities in alkaline YNP hot spring waters (62-90.5{degrees}C) using three high-temperature-compatible filtration systems (Sterivex, Supor, and polycarbonate membranes), automated onsite DNA extraction ({micro}Titan), and shotgun metagenomic sequencing with Illumina short-read and Oxford Nanopore Technologies (ONT) long-read platforms. Across all filtration systems and sequencing workflows, microbial communities were consistently dominated by Bacteria ([~]90% of reads), whereas Archaea represented <10% of recovered sequences. Dominant microbial populations were reproducibly recovered across all approaches; however, recovery of lower-abundance taxa varied among methods. This variability was most evident in polycarbonate-filtered samples, which exhibited greater replicate-to-replicate variation and less consistent detection of microbial species. Thermocrinis ruber and related Aquificae-associated thermophiles dominated the hottest waters (78.5-90.5{degrees}C), whereas warmer effluent-channel waters (63.5-66.5{degrees}C) contained T. ruber together with photosynthetic taxa, including Synechococcus spp. and Candidatus Thermochlorobacter aerophilum. Archaeal communities were primarily represented by Pyrobaculum- and Thermoproteus-related taxa. Non-metric multidimensional scaling analyses indicated that overall community structure was largely unaffected by filtration or sequencing methodology, whereas alpha-diversity metrics showed that filter selection influenced richness and diversity estimates. These findings identify field-deployable workflows for metagenomic characterization of low-biomass thermophilic aquatic systems and demonstrate the importance of integrating filtration and sequencing strategies for studying extremophile microbiomes under remote sampling conditions. IMPORTANCEAccurate characterization of low-biomass geothermal water microbiomes remains challenging because microbial recovery is strongly influenced by sample handling, filtration efficiency, DNA extraction chemistry, and sequencing methodology. This study demonstrated that Yellowstone National Park alkaline hot spring water microbiomes were consistently dominated by Bacteria (>90% of recovered reads), whereas Archaea represented <10% of community abundance across all filtration systems. Although dominant microbial populations were reproducibly recovered, filtration-device selection influenced the recovery of microbial diversity and low-abundance taxa. By integrating field-deployable onsite DNA extraction with ONT shotgun metagenomic sequencing, this work evaluates practical workflows for studying thermophilic planktonic microbial communities under remote field conditions. These findings are relevant, not only to geothermal microbiology, but also to low-biomass environments in medical, pharmaceutical, and aerospace industries, where rapid onsite processing and contamination-aware workflows are essential for preserving authentic microbial signatures in extreme environments.

ecology↗

Genomic and morphologic characterization of a planktonic Thiovulum (Campylobacterota) dominating the surface waters of the sulfidic Movile Cave, Romania

Life in Movile Cave (Romania) relies entirely on carbon fixation by bacteria. The microbial community in the surface water of Movile Caves hypoxic air bells is dominated by large spherical-ovoid bacteria we identified as Thiovulum sp. (Campylobacterota). These form a separate phylogenetic cluster within the Thiovulaceae, consisting mostly of freshwater cave bacteria. We compared the closed genome of this Thiovulum to that of the marine strain Thiovulum ES, and to a genome we assembled from public data from the sulfidic Frasassi caves. The Movile and Frasassi Thiovulum were very similar, differing greatly from the marine strain. Based on their genomes, cave Thiovulum can switch between aerobic and anaerobic sulfide oxidation using O2 and NO3- as electron acceptors, respectively. NO3-, is likely reduced to NH3 via dissimilatory nitrate reduction to ammonia using periplasmic nitrate reductase (Nap) and hydroxylamine oxidoreductase. Thus, Thiovulum, is likely important to both S and N cycles in sulfidic subterranean aquatic ecosystems. Additionally, we suggest that the short peritrichous flagella-like structures typical of Thiovulum are type IV pili, for which genes were found in all Thiovulum genomes. These pili may play a role in veil formation, connecting adjacent cells and the exceptionally fast swimming of these bacteria.

microbiology↗

RT-qPCR DETECTION OF SARS-CoV-2 RNA FROM PATIENT NASOPHARYNGEAL SWAB USING QIAGEN RNEASY KITS OR DIRECTLY VIA OMISSION OF AN RNA EXTRACTION STEP

The ongoing COVID-19 pandemic has caused an unprecedented need for rapid diagnostic testing. The Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) recommend a standard assay that includes an RNA extraction step from a nasopharyngeal (NP) swab followed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to detect the purified SARS-CoV-2 RNA. The current global shortage of RNA extraction kits has caused a severe bottleneck to COVID-19 testing. We hypothesized that SARS-CoV-2 RNA could be detected from NP samples via a direct RT-qPCR assay that omits the RNA extraction step altogether, and tested this hypothesis on a series of blinded clinical samples. The direct RT-qPCR approach correctly identified 92% of NP samples (n = 155) demonstrated to be positive for SARS-CoV-2 RNA by traditional clinical diagnostic RT-qPCR that included an RNA extraction. Thus, direct RT-qPCR could be a front-line approach to identify the substantial majority of COVID-19 patients, reserving a repeat test with RNA extraction for those individuals with high suspicion of infection but an initial negative result. This strategy would drastically ease supply chokepoints of COVID-19 testing and should be applicable throughout the world.

microbiology↗

Comprehensive Benchmarking and Ensemble Approaches for Metagenomic Classifiers

BackgroundOne of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest (n=35) to date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of eleven metagenomics classifiers. We also assess the effects of filtering and combining tools to reduce the number of false positives.\n\nResultsTools were characterized on the basis of their ability to (1) identify taxa at the genus, species, and strain levels, (2) quantify relative abundance measures of taxa, and (3) classify individual reads to the species level. Strikingly, the number of species identified by the eleven tools can differ by over three orders of magnitude on the same datasets. However, various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Indeed, leveraging tools with different heuristics is beneficial for improved precision. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species and where customized tools may be required.\n\nConclusionsThe results of this study provide positive controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision and recall. We show that proper experimental design and analysis parameters, including depth of sequencing, choice of classifier or classifiers, database size, and filtering, can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

genomics↗