Icenhour, C. R. | bioRxiv Science

bioRxiv2025

Unveiling the Human Nasopharyngeal Microbiome Compendium: Systematic Characterization of Community Architecture and Function Through a Comprehensive Meta-Analysis

The nasopharyngeal microbiome is critical for respiratory health, yet its compositional architecture remains largely uncharacterized, underlying conflicting reports of increased, decreased, or unchanged diversity during infection. Here, we demonstrate that these contradictions arise from a fundamentally overlooked factor: the nasopharynx is organized into six reproducible nasopharyngeal community state types (NPCSTs) that are associated with intrinsic diversity baselines independent of disease status. By uniformly reprocessing 7,790 16S rRNA gene sequencing samples from 28 studies, we show that NPCSTs explain 52% of community variance, four-fold more than study effects, and that disease-diversity associations are attenuated by over 92% after NPCST adjustment. To identify genuine disease markers, we applied NPCST-aware differential abundance testing to SARS-CoV-2 as a case study. Leave-one-study-out (LOSO) cross-validation across 10 cohorts confirmed 13 reproducible taxa with opposing shifts: obligate anaerobes typically studied in other body compartments were enriched, while resident hub genera were depleted with high directional consistency across LOSO iterations. Co-occurrence network analysis independently validated this pattern, identifying the depleted taxa as structural backbone hubs across all NPCSTs. To bridge microbiome ecology and clinical application, we developed the Nasopharyngeal Microbiome Health Index (NMHI), a continuous community-level wellness score achieving AUC of 0.90 and 0.92 in internal and external validations, respectively, with robust performance across all six NPCSTs (AUC: 0.848-0.953). An independent clinical cohort of 147 specimens confirmed that these NPCST and NMHI characteristics are reproducible. Unlike binary classifiers, NMHI quantifies nasopharyngeal health along a spectrum, establishing NPCST-aware analysis as a foundation for precision respiratory microbiome research.

bioinformatics↗

bioRxiv2024

Characterization of vaginal microbiomes in clinician-collected bacterial vaginosis diagnosed samples

Bacterial vaginosis (BV) is a type of vaginal inflammation caused by bacterial overgrowth, upsetting the healthy microbiome of the vagina. Existing clinical testing for BV is primarily based upon physical and microscopic examination of vaginal secretions, while more modern PCR-based clinical tests target panels of BV-associated microbes, such as the Labcorp NuSwab(R) test. Remnant clinician-collected NuSwab(R) vaginal swabs underwent DNA extraction and 16S V3-V4 rRNA gene sequencing to profile microbes in addition to those included in the Labcorp NuSwab(R) test. Community State Types (CSTs) were determined using the most abundant taxon detected in each sample. PCR results for NuSwab(R) panel microbial targets were compared against the corresponding microbiome profiles. Metabolic pathway abundances were characterized via metagenomic prediction from amplicon sequence variants (ASVs). Sequencing of 75 remnant vaginal swabs yielded 492 unique 16S V3-V4 ASVs, identifying 83 unique genera. NuSwab(R) assay microbe quantification was strongly concordant with quantification by sequencing (p << 0.01). Samples in CST-I (18 of 18, 100%), CST-II (3 of 3, 100%), CST-III (15 of 17, 88%), and CST-V (1 of 1, 100%) were largely categorized as BV-negative via the NuSwab(R) panel, while most CST-IV samples (28 of 36, 78%) were BV-positive or BV-indeterminate. BV-associated microbial and predicted metabolic signatures were shared across multiple CSTs. These findings show that 16S V3-V4 rRNA gene sequencing robustly reproduces PCR-based BV diagnostic testing results, accurately discriminates vaginal microbiome CSTs dominated by distinct Lactobacilli, and further elucidates BV-associated bacterial and metabolic signatures. ImportanceBacterial vaginosis (BV) poses a significant health burden for women during reproductive years and onward. Current BV diagnostics rely on either physical and microscopic evaluations by technicians or panels of select microbes. Here, we sequenced the microbiome profiles of samples previously diagnosed by the Labcorp NuSwab(R) test to better understand disruptions to the vaginal microbiome during BV. We show that microbial sequencing can reproduce targeted panel diagnostic results, while also broadly characterizing healthy and BV-associated microbial and metabolic biomarkers. This work highlights a robust, agnostic BV classification scheme with potential for future development of sequencing-based BV diagnostic tools.

microbiology↗