Catabolic Machinery of the Human Gut Microbes Bestow Resilience Against Vanillin Antimicrobial Nature

Abstract

Vanillin is a phenolic food additive commonly used for flavor, antimicrobial, and antioxidant properties. Though it is one of the widely used food additives, strategies of the human gut microbes to evade its antimicrobial activity await extensive elucidation. The current study explores the human gut microbiome with a multi-omics approach to elucidate its composition and metabolic machinery to counter vanillin bioactivity. A combination of SSU rRNA gene diversity, metagenomic RNA features diversity, phylogenetic affiliation of metagenome encoded proteins, uniformly (R = 0.99) indicates the abundance of Bacteroidetes followed by Firmicutes and Proteobacteria. Manual curation of metagenomic dataset identified gene clusters specific for the vanillin metabolism (ligV, ligK, and vanK) and intermediary metabolic pathways (pca and cat operon). Metagenomic dataset comparison identified the omnipresence of vanillin catabolic features across diverse populations. The metabolomic analysis brings forth the functionality of the vanillin catabolic pathway through the Protocatechuate branch of the beta-ketoadipate pathway. These results highlight the human gut microbial features and metabolic bioprocess involved in vanillin catabolism to overcome its antimicrobial activity. The current study advances our understanding of the human gut microbiome adaption toward changing dietary habits.

Culture-Independent Exploration of the Hypersaline Ecosystem Indicates the Environment-Specific Microbiome Evolution

“…The 5.39% of total protein features were also found associated with stress resistance, virulence, and genetic transformations (Supplementary Table 5). The percentage of protein features for stress resistance, virulence, and genetic transformation in the current metagenomic dataset was higher as compared to other ecosystems (Yadav et al, 2020). A higher percentage of these protein features might be extending physiological flexibility to the salt lake microbes to thrive in the hypersaline environment.…”

“…The sequence dataset (Supplementary Table 1) was uploaded into the Metagenome Rapid Annotation using Subsystem Technology (MG-RAST) server 4.0.3 1 (Meyer et al, 2008) for quality filtering (reads with Phred score > 15 were trimmed for removing adapter contamination and screened to remove host genomic DNA sequences) (Yadav et al, 2020). The quality-filtered sequences were also used to perform the genome assembly using MEGAHIT assembler (Li et al, 2015) (Supplementary Method 2).…”

“…Predicted protein features were clustered (90% identity) and processed for their similarity using BLAT algorithm against the M5NR protein database, RefSeq database, and Subsystems database (e-value < 10 −5 , minimum identity >60%). Taxonomic and functional affiliation of protein features was predicated with their feature abundance profile, data source abundance profile, and lowest common ancestor (LCA) abundance profile (Yadav et al, 2020).…”

“…Both negative and positive modes of electrospray ionization (ESI) were used to capture the metabolic profile. LC-MS spectra were analyzed with an XCMS server (Yadav et al, 2020).…”

“…Exploration of the salt lake microbiome will enrich the understanding of microbiome functioning in nutrient-deprived extreme conditions (Naghoni et al, 2017). Metagenomics and metabolomics are the pioneer culture-independent tools to explore the untapped microbial world to unveil microbiome genetic composition and functional metabolic pathways (Ahmed et al, 2018;Yadav et al, 2020Yadav et al, , 2021. Metagenomic exploration of the freshwater, alkaline, and saline water ecosystem has identified unique inhabitants and their unique genetic machinery (Poli et al, 2017).…”