Biology subjects

Banavar, G. S.

Publications and source records attributed to Banavar, G. S..

5 recordsLinked to original sources

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↗

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↗