Biology subjects

Vuyisich, M.

Publications and source records attributed to Vuyisich, M..

10 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↗

bioRxiv2023

A novel method for sampling subgingival microbiome - a comparative metatranscriptomic study

The subgingival microbiome has been implicated in several oral and systemic diseases, such as periodontitis, arthritis, and Alzheimers disease. However, subgingival sampling is challenging and cannot be readily performed outside of primary care facilities. In order to support global, diverse, direct-to-participant clinical research studies, we developed a novel method of sampling the subgingival microbiome by rotationally swabbing the supragingival area, which we named subgingival-P (for proxy) samples. To validate this method, we sampled and metatranscriptomically analyzed subgingival and subgingival-P samples of three different teeth in 20 individuals. The subgingival-P samples were comparable to the subgingival samples in the relative abundances of microorganisms and microbial gene expression levels. Our data demonstrate that the novel method of collecting and analyzing the subgingival-P samples can act as a proxy for the subgingiva, paving the way for large and diverse studies investigating the role of the subgingival microbiome in health and disease.

microbiology↗

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↗

bioRxiv2020

An accurate aging clock developed from the largest dataset of microbial and human gene expression reveals molecular mechanisms of aging

Accurate measurement of the biological markers of the aging process could provide an "aging clock" measuring predicted longevity and allow for the quantification of the effects of specific lifestyle choices on healthy aging. Using modern machine learning techniques, we demonstrate that chronological age can be predicted accurately from (a) the expression level of human genes in capillary blood, and (b) the expression level of microbial genes in stool samples. The latter uses the largest existing metatranscriptomic dataset, stool samples from 90,303 individuals, and is the highest-performing gut microbiome-based aging model reported to date. Our analysis suggests associations between biological age and lifestyle/health factors, e.g., people on a paleo diet or with IBS tend to be biologically older, and people on a vegetarian diet tend to be biologically younger. We delineate the key pathways of systems-level biological decline based on the age-specific features of our model; targeting these mechanisms can aid in development of new anti-aging therapeutic strategies.

systems biology↗

bioRxiv2020

A clinically validated human capillary blood transcriptome test for global systems biology studies

Chronic diseases are the leading cause of morbidity and mortality globally. Yet, the majority of them have unknown etiologies, and genetic contribution is weak. In addition, many of the chronic diseases go through the cycles of relapse and remission, during which the genomic DNA does not change. This strongly suggests that human gene expression is the main driver of chronic disease onset and relapses. To identify the etiology of chronic diseases and develop more effective preventative measures, a comprehensive gene expression analysis of the human body is needed. Blood tissue is easy to access and contains a large number of expressed genes involved in many fundamental aspects of our physiology. We report here the development of a whole blood transcriptome clinical test that is high throughput, automated, inexpensive, and clinically validated. The test requires only 50 microliters of blood from a finger prick, enabling access by diverse populations that have been traditionally under-represented in clinical research. The transcripts in the samples are preserved at the time of collection and can be stored and/or transported at ambient temperatures for up to 28 days. The sample preservative protects integrity, while also inactivating all pathogens (bacteria, fungi, and viruses), enabling safe transportation globally. Given its unique set of usability features and clinical performance, this test should be integrated into longitudinal, population-scale, systems biology studies.

systems biology↗

bioRxiv2019

A robust metatranscriptomic technology for population-scale studies of diet, gut microbiome, and human health

A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiomes functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intra-sample variability, rapid changes, and RNA degradation. Here, we describe a robust and automated stool metatranscriptomic method, called Viomega, which was specifically developed for population-scale studies. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. We applied this method to 10,000 human stool samples, and performed several small-scale studies to demonstrate sample stability and consistency. In summary, Viomega is an inexpensive, high throughput, automated, and accurate sample-to-result stool metatranscriptomic technology platform for large-scale studies and a wide range of applications.

systems biology↗

bioRxiv2019

Gut microbiome activity contributes to individual variation in glycemic response in adults

Limiting post-meal glycemic response is an important factor in reducing the risk of chronic metabolic diseases, and contributes to significant health benefits in people with elevated levels of blood sugar. In this study, we collected gut microbiome activity (i.e., metatranscriptomic) data and measured the glycemic responses of 550 adults who consumed more than 30,000 meals from omnivore or vegetarian/gluten-free diets. We demonstrate that gut microbiome activity makes a statistically significant contribution to individual variation in glycemic response, in addition to anthropometric factors and the nutritional composition of foods. We describe predictive models (multilevel mixed-effects regression and gradient boosting machine) of variation in glycemic response among individuals ingesting the same foods. We introduce functional features aggregated from microbial activity data as candidates for association with mechanisms of glycemic control. In summary, we demonstrate for the first time that metatranscriptomic activity of the gut microbiome is correlated with glycemic response among adults.

systems biology↗