Biology subjects

Banavar, G.

Publications and source records attributed to Banavar, G..

5 recordsLinked to original sources

bioRxiv2026

The human gut microbiome activity is resilient and stable for up to six months: a large stool metatranscriptomic study

The human microbiome influences health and disease through diverse biochemical and functional outputs (e.g. enzymes, structural proteins, metabolites, and other cellular components) that affect nearly every aspect of human physiology. Metatranscriptomics (MT), an unbiased RNA sequencing approach, is a high-throughput and high-content method that quantifies both gut microbial taxonomy and active biochemical functions. Because microbial community composition and gene expression are dynamic, understanding temporal variation in the gut metatranscriptome across multiple time scales is essential. Here, we report the temporal dynamics of gut microbiome species and functions using a large cohort (n=6,157) with a clinically validated stool MT test. We quantified microbiome stability from hours to years and assessed taxonomic and functional resilience to major luminal perturbations, such as colonoscopy bowel preparation. Longitudinal analyses of samples collected within the same day, and across days, weeks, months, and years, revealed consistently high stability in both composition and gene expression within a single day and, importantly, across an approximate six-month period. Among individuals reporting stable diets and no antibiotic exposure, taxonomic and functional profiles remained stable for up to three years. Following colonoscopy preparation, our preliminary study of the microbiome demonstrated strong resilience, returning to its pre-procedure state within one week. Overall, these findings demonstrate that the gut microbiome is generally stable over a six-month time frame, with longer-term changes occurring gradually. These findings support the robustness of stool-based MT profiling for species-level and pathway-resolved functional analysis in longitudinal research and health applications.

microbiology↗

bioRxiv2024

Sub-optimal activity of gut microbiome functional pathways increases the odds of Irritable Bowel Syndrome in a large adult human population

Functional gastrointestinal disorders present diagnostic and therapeutic challenges, and there is a strong need for molecular markers that enable early health insights and intervention. Herein, we present an approach to assess the gut microbiome with stool-based gut metatranscriptome data from a large adult human population (n = 80,570), using irritable bowel syndrome as an example that features both an abnormal gut microbiome and a spectrum of distinct conditions. We develop a suite of eight gut microbial functional pathway scores, each of which represents the activity of a set of interacting microbial functional features (based on KEGG orthology) relevant to known gut biochemical activities. We use a normative approach within a subpopulation (n = 9,350) to define "Good" and "Not Optimal" activities for these transcriptome-based gut pathway scores. We hypothesize that Not Optimal scores are associated with irritable bowel syndrome (IBS) and its subtypes (i.e., IBS-Constipation, IBS-Diarrhea, IBS-Mixed Type). We show that Not Optimal functional pathway scores are associated with higher odds of IBS or its subtypes within an independent cohort (n = 71,220) using both the Rome IV Diagnostic Questionnaire as well as self-reported phenotypes. Rather than waiting to diagnose IBS after symptoms appear, these functional pathway scores can help to provide early health insights into molecular pathways that may contribute to IBS. These molecular endpoints could also assist with measuring the efficacy of practical interventions, developing related algorithms, providing personalized nutritional recommendations, diagnostic support, and treatments for gastrointestinal disorders like IBS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/580548v4_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@d84aaeorg.highwire.dtl.DTLVardef@f2276org.highwire.dtl.DTLVardef@19fab7aorg.highwire.dtl.DTLVardef@1b2f738_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Microbial functional pathways based on metatranscriptomic profiling enable effective saliva-based health assessments for precision wellness

It is increasingly recognized that an important step towards improving overall health is to accurately measure biomarkers of health from the molecular activities prevalent in the oral cavity. We present a general methodology for computationally quantifying the activity of microbial functional pathways using metatranscriptomic data. We describe their implementation as a collection of eight oral pathway scores using a large salivary sample dataset (n=9,350), and we evaluate score associations with oropharyngeal disease phenotypes within an unseen independent cohort (n=14,129). As clinical validation, we show that the relevant oral pathway scores are significantly worse in individuals with periodontal disease, acid reflux, and nicotine addiction, compared with controls. Given these associations, we make the case to use these oral pathway scores to provide molecular health insights from simple, non-invasive saliva samples, and as molecular endpoints for actionable interventions to address the associated conditions. HighlightsO_LIMicrobial functional pathways in the oral cavity are quantified as eight oral scores C_LIO_LIScores are significantly worse for individuals with oropharyngeal disease phenotypes C_LIO_LIThis methodology may be generalized to other pathways and other sample types C_LIO_LIThese scores provide longitudinal health insights in a precision wellness application C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/565122v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@12fb7bdorg.highwire.dtl.DTLVardef@1c7dbf3org.highwire.dtl.DTLVardef@39700forg.highwire.dtl.DTLVardef@ebf63c_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2021

A clinically validated human saliva metatranscriptomic test for global systems biology studies

We report here the development of a high throughput, automated, inexpensive, and clinically validated saliva metatranscriptome test that requires less than 100 microliters of saliva. The RNA in the samples is preserved at the time of collection. Samples can then be stored and transported at ambient temperatures for up to 28 days without significantly affecting the test results. Another important feature of the sample preservative is that it inactivates all classes of pathogens, enabling safe transportation globally. Given the unique set of convenience, low cost, safety, and technical performance, this saliva metatranscriptomic test can be integrated into longitudinal, global scale, systems biology studies that will lead to an accelerated development of precision medicine diagnostic and therapeutic tools. Method SummaryThis report describes an important improvement to saliva transcriptome analysis. While current methods are complicated and expensive, the method reported here includes at-home sample collection, global shipping at ambient temperatures and pathogen inactivation at the point of collection; it uses fully automated, clinically validated and licensed laboratory and bioinformatic analyses.

microbiology↗

bioRxiv2021

Evidence-based precision nutrition improves clinical outcomes by analyzing human and microbial molecular data with artificial intelligence

Many studies have shown that foods and nutritional ingredients play an important role in healthy human homeostasis, either directly or via the microbiome. We have developed an objective, integrated, and automated approach to personalized food and supplement recommendations that is powered by artificial intelligence and individualized molecular data from the gut microbiome, the human host, and their interactions. The process starts with a clinically validated transcriptomic analysis of a persons stool (and some cases also blood) sample, from which the following molecular data are computed using clinically validated bioinformatics: 1. Quantitative strain-level taxonomic classification of all microorganisms, 2. Gene expression level for microbial genes, 3. Gene expression level for all human genes. These molecular data are converted into personalized nutritional recommendations (foods and supplements) using algorithms derived from clinical research studies and domain knowledge. We describe an application of our precision nutrition technology platform to human populations with irritable bowel syndrome (IBS), depression, anxiety, and type 2 diabetes (T2D). In these pilot interventional studies, our precision nutrition program achieved significant improvements in clinical outcomes of IBS (39% for severe IBS), depression (31% for severe depression), anxiety (31% for severe anxiety), and the risk score for T2D (>30% reduction relative to the control arm). These data support the integration of data-driven precision nutrition into the standard of care.

systems biology↗