Biology subjects

Qu, E. B.

Publications and source records attributed to Qu, E. B..

6 recordsLinked to original sources

bioRxiv2025

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission events, and identifying antimicrobial resistance mutations. While many tools have been developed to identify single nucleotide variants (SNVs) from whole-genome sequencing, they often suffer from high false positive rates due to the complexity of bacterial genomes and the need for different filtering cutoffs across sample types and sequencing depths. As datasets increase in size, the manual filtering required for high accuracy presents a significant obstacle. Here, we present AccuSNV, a novel deep learning-based tool for high-precision and automated bacterial SNV calling. Unlike traditional methods that process one sample at a time, AccuSNV leverages a convolutional neural network (CNN) that integrates alignment information across multiple samples, enhancing precision through learned across-sample patterns. We evaluated AccuSNV against seven popular SNV calling tools using simulated data from six bacterial species with varied sequencing depths, numbers of isolates, mutations, and divergence levels. To further validate its real-world utility, we tested AccuSNV on multiple curated bacterial datasets containing reported SNVs. In both simulated and real-world scenarios, AccuSNV consistently achieved the best performance. Moreover, AccuSNV provides comprehensive user-friendly downstream analysis modules and outputs, including mutation annotation information, phylogenetic inference, dN/dS calculations, and optional manual filtering. Together with the automated deep learning-based calling, these features make AccuSNV broadly accessible to users with different levels of computational expertise.

bioinformatics↗

bioRxiv2025

Phage-mediated lysis does not determine Cutibacterium acnes colonization on human skin

Despite Cutibacterium acnes being the most abundant and prevalent bacteria on human skin, only a single type of phage has been identified that infects this host. Here, we leverage this one-to-one system to systematically characterize how the phage-bacteria arms race shapes C. acnes evolution and community composition on individual people. Our analysis reveals a surprising lack of phage-mediated selection despite global prevalence of C. acnes phages. Analysis of anti-phage defense systems across 3,205 bacterial genomes revealed a limited, phylogenetically restricted defense repertoire under weak selective pressure to diversify or be maintained. Functional assays did not reveal alternative phage resistance mechanisms or fitness costs associated with defense gene carriage that could explain this limited immune arsenal. This lack of pressure to maintain phage resistance could not be explained by lack of phage colonization, as examination of 471 global human facial skin metagenomes demonstrated that even in samples with high virus-to-microbe ratio, phage-sensitive clades dominate on-person populations. Together, these findings indicate that phage pressure, while present, does not play a critical role in determining strain fitness and success within C. acnes populations on human skin. We propose that this observed weak phage-mediated selective pressure can be explained by the anatomy of skin: C. acnes growth is thought to occur at the bottom of pores, where exposure to phage may be limited by physical barriers. Together, this portrait of a static arms race provides a strong contrast with other microbial species in different ecosystems and expands understanding of phage-bacteria interactions in the human microbiome.

genomics↗

bioRxiv2025

Microbiome diversity of low biomass skin sites is captured by metagenomics but not 16S amplicon sequencing

Established workflows for microbiome analysis work well for high microbial biomass samples, like stool, but often fail to accurately define microbial communities when applied to low microbial biomass samples. Here, we systemically compare microbiome analysis methods --16S rRNA sequencing, shallow metagenomics, and qPCR PMP panels--as well as extraction methods across skin swab samples and mock community dilutions. While extraction method minimally impacted results, with no significant signal for method-specific contamination or bias, we observed critical differences in inferred composition across analysis methods for low biomass samples. Metagenomic sequencing and qPCR revealed concordant, diverse microbial communities on low biomass leg skin samples, whereas 16S amplicon sequencing exhibited extreme bias toward the most abundant taxon. Both qPCR and metagenomics showed that female genital tract bacteria dominated the leg skin microbiome in about half of female subjects. Metagenomics also enabled sub-species analysis, which demonstrated that individuals have consistent within-species diversity across high-biomass forehead and low-biomass leg skin sites. This work illustrates that shallow metagenomics provides the necessary sensitivity and taxonomic resolution to characterize species and strain-level diversity in extremely low biomass samples, opening possibilities for microbiome discovery in previously unexplored niches. ImportanceDespite the importance of the skin microbiome in health and disease, there have been far fewer studies characterizing the microbiome of skin compared to that of the gut. In part, this is because microbiome methods were initially developed for bacteria-rich samples like stool and these methods perform poorly on bacteria-poor samples like skin swabs. The perceived difficulty of getting reliable data from such low biomass sites has limited the scope and types of analyses performed. Here we demonstrate that shotgun, whole-genome, metagenomic sequencing recovers the full input from even very dilute control community samples, and reveals a highly diverse population even on very low biomass skin sites. We describe a streamlined sample processing and analysis pipeline which can be applied broadly to characterize low biomass microbiome samples and reveal new host-microbiome interactions.

microbiology↗

bioRxiv2025

Intraspecies associations from strain-rich metagenome samples

Genetically distinct strains of a species can vary widely in phenotype, reducing the utility of species-resolved microbiome measurements for detecting associations with health or disease. While metagenomics theoretically provides information on all strains in a sample, current strain-resolved analysis methods face a tradeoff: de novo genotyping approaches can detect novel strains but struggle when applied to strain-rich or low-coverage samples, while reference database methods work robustly across sample types but are insensitive to novel diversity. We present PHLAME, a method that bridges this divide by combining the advantages of reference-based approaches with novelty awareness. PHLAME explicitly defines clades at multiple phylogenetic levels and introduces a probabilistic, mutation-based, framework to accurately quantify novelty from the nearest reference. By applying PHLAME to publicly available human skin and vaginal metagenomes, we uncover previously undetected clade associations with coexisting species, geography, and host age. The ability to characterize intraspecies associations and dynamics in previously inaccessible environments will propel new mechanistic insights from accumulating metagenomic data.

microbiology↗

bioRxiv2023

Widespread B-vitamin auxotrophy in marine particle-associated bacteria

Microbial community assembly is governed by trophic interactions that mediate the transfer of carbon sources and biomass building blocks between species. However, central metabolism corresponds to only a small fraction of the biosynthetic potential of microbes: metabolites such as antimicrobial compounds, signaling molecules, and co-factors are underexplored forces shaping microbial communities. Here, we focus on B vitamin exchange in coastal marine bacterial communities that degrade particulate organic matter and find that natural seawater communities are vitamin limited. While almost a third of bacterial isolates from these communities are B vitamin auxotrophs, the pioneering degraders that first arrive on particles are vitamin producers that likely support auxotrophs through cross-feeding. However, combining experiments and a resource-explicit model, we show that auxotroph growth is often not restored by coculture with vitamin producers, but rather requires lysis and subsequent vitamin recycling. Our results highlight the importance of vitamin auxotrophies and lysis-mediated cross-feeding as important factors controlling microbial community assembly and succession on marine particles.

microbiology↗

bioRxiv2019

Trophic Selective Pressures Organize the Composition of Endolithic Microbial Communities from Global Deserts

Studies of microbial biogeography are often convoluted by extremely high diversity and differences in microenvironmental factors such as pH and nutrient availability. Desert endolithic (inside rock) communities are exceptionally simple ecosystems that can serve as a tractable model for investigating long-range biogeographic effects on microbial communities. We conducted a comprehensive survey of endolithic sandstones using high-throughput marker gene sequencing to characterize global patterns of diversity in endolithic microbial communities. We also tested a range of abiotic variables in order to investigate the factors that drive community assembly at various trophic levels. Macroclimate was found to be the primary driver of endolithic community composition, with the most striking difference witnessed between hot and polar deserts. This difference was largely attributable to the specialization of prokaryotic and eukaryotic primary producers to different climate conditions. On a regional scale, microclimate and properties of the rock substrate were found to influence community assembly, although to a lesser degree than global hot versus polar conditions. We found new evidence that the factors driving endolithic community assembly differ between trophic levels. While phototrophic taxa were rigorously selected for among different sites, heterotrophic taxa were more cosmopolitan, suggesting that stochasticity plays a larger role in heterotroph assembly. This study is the first to uncover the global drivers of desert endolithic diversity using high-throughput sequencing. We demonstrate that phototrophs and heterotrophs in the endolithic community assemble under different stochastic and deterministic influences, emphasizing the need for studies of microorganisms in context of their functional niche in the community.

microbiology↗