title: Insights into resistome and stress responses genes in Bubalus bubalis rumen through metagenomic analysis.
abstract: Buffalo rumen microbiota experience variety of diets and represents a huge reservoir of mobilome, resistome and stress responses. However, knowledge of metagenomic responses to such conditions is still rudimentary. We analyzed the metagenomes of buffalo rumen in the liquid and solid phase of the rumen biomaterial from river buffalo adapted to varying proportion of concentrate to green or dry roughages, using high-throughput sequencing to know the occurrence of antibiotics resistance genes, genetic exchange between bacterial population and environmental reservoirs. A total of 3914.94 MB data were generated from all three treatments group. The data were analysed with Metagenome rapid annotation system tools. At phyla level, Bacteroidetes were dominant in all the treatments followed by Firmicutes. Genes coding for functional responses to stress (oxidative stress and heat shock proteins) and resistome genes (resistance to antibiotics and toxic compounds, phages, transposable elements and pathogenicity islands) were prevalent in similar proportion in liquid and solid fraction of rumen metagenomes. The fluoroquinolone resistance, MDR efflux pumps and Methicillin resistance genes were broadly distributed across 11, 9, and 14 bacterial classes, respectively. Bacteria responsible for phages replication and prophages and phage packaging and rlt-like streptococcal phage genes were mostly assigned to phyla Bacteroides, Firmicutes and proteaobacteria. Also, more reads matching the sigma B genes were identified in the buffalo rumen. This study underscores the presence of diverse mechanisms of adaptation to different diet, antibiotics and other stresses in buffalo rumen, reflecting the proportional representation of major bacterial groups.
authors.affiliation: Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry (CVSAH), Anand Agricultural University (AAU), Anand, 388 001, Gujarat, India.
authors.forename: Bhaskar
authors.initials: B
authors.lastname: Reddy
authors.forename: Krishna M
authors.initials: KM
authors.lastname: Singh
authors.forename: Amrutlal K
authors.initials: AK
authors.lastname: Patel
authors.forename: Ancy
authors.initials: A
authors.lastname: Antony
authors.forename: Harshad J
authors.initials: HJ
authors.lastname: Panchasara
authors.forename: Chaitanya G
authors.initials: CG
authors.lastname: Joshi
mesh_terms: D000818:Animals; D000890:Anti-Infective Agents / Q000494:pharmacology; D044822:Biodiversity; D002020:Buffaloes; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D004352:Drug Resistance, Microbial; D054892:Metagenome; D056186:Metagenomics / Q000379:methods; D008826:Microbial Sensitivity Tests; D064307:Microbiota / Q000187:drug effects / Q000235:genetics; D010802:Phylogeny; D012417:Rumen / Q000382:microbiology*; D013312:Stress, Physiological
chemical_list: D000890:Anti-Infective Agents