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Speaker at  and Expo on Applied Microbiology 2023 - Deep Chanda
National Institute of Technology, India
Title : In search of obesity-linked signature gut microbial features and species contributors of reproducible pathway shifts

Abstract:

Since 1975, the prevalence of obesity, now recognized as a serious global health problem, has almost tripled. Numerous other factors, such as demography (Ogden et al., 2014), appetite regulation (Spiegelman and Flier, 2001), lifestyle (Hankinson et al., 2010; Hu et al., 2003), hormone signaling (Spiegelman and Flier, 2001), and others play a significant role in the aetiology of obesity along with genetics (Locke et al., 2015) and epigenetics. Independent research has recently linked the gut microbiome to obesity as well. The majority of cohorts-specific 16s rRNA gene sequence-based studies differ in their reporting of alteration in community structure like change in diversity, Firmicutes/Bacteroidetes ratio as well as in differentially abundant genus. Although there has been effort to pool such cohort-based studies to find underlying reproducible patterns, they failed to deliver beyond species- and function (gene and pathway)- level information associated with obese host-gut microbiome interactions. On the other hand, whole genome sequence (WGS) based pooled studies are absent that can provide generalized understanding of obesity-associated alterations in species and function level of obese gut microbiome.

To address these issues, we have curated approximately 2000 metagenomic samples from different geographical locations (China, Denmark, Great Britain, Ireland, Israel, Japan, Kazakhstan, Sweden) processed, statistically analyzed, and validated with independent machine learning experiments. We performed taxonomic and functional profiling of the metagenomic samples and applied univariate statistical analyses on each dataset to check dataset-specific alterations. The signature microbial features were then identified by random-effect meta-analyses and independently verified through machine learning analyses. Moreover, we integrated taxonomic and functional features through the gene copy number information of each species to pinpoint species drivers for the altered signature gut microbial pathways linked to obesity. The reproducibility of the drivers across the datasets were also assessed.

We could establish a panel of obesity-linked reproducible species and functional pathways from our pooled statistical analyses which were validated with random forest-based machine learning experiment. Some of the signature species are established probiotics while some has been reported to have beneficial roles against metabolic syndrome by producing short chain fatty acids (SCFAs) and increasing gut barrier integrity. We inferred that obesity-related dysbiosis is caused by a reduction of total microbial diversity leading to altered functional patterns. Additionally, we also pointed out the main drivers of the functional diversity seen in lean people which may be treated as targets for future therapeutic intervention.

Audience Take Away:

  • Reproducible community structure alterations in obese gut microbiome.
  • Signature taxonomic and functional signals linked to obese and lean gut microbiome.
  • Systematic integration of gut microbial taxonomic and function levels to pinpoint drivers of the obesity-linked functional shifts for targeting possible therapeutic interventions.

Biography:

Deep Chanda studied Zoology in Visva-Bharati and graduated with an MSc in 2015. Thereafter he awarded Junior Research Fellowship (JRF) from Council of Scientific and Industrial Research (CSIR) in 2018 and joined the “Laboratory of Cellular Differentiation & Metabolic Disorder” as a PhD scholar under the supervision of Dr. Debojyoti De at Department of Biotechnology, National Institute of Technology Durgapur. Currently he is a Senior Research Fellow at the same laboratory. His area of interest is obese host-gut microbiome interaction

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