| Literature DB >> 30187987 |
Rebecca Hooper1, Jaelle C Brealey1, Tom van der Valk1, Antton Alberdi2, John W Durban3, Holly Fearnbach4, Kelly M Robertson3, Robin W Baird5, M Bradley Hanson6, Paul Wade7, M Thomas P Gilbert2,8, Phillip A Morin3, Jochen B W Wolf9,10, Andrew D Foote11, Katerina Guschanski1.
Abstract
Recent exploration into the interactions and relationship between hosts and their microbiota has revealed a connection between many aspects of the host's biology, health and associated micro-organisms. Whereas amplicon sequencing has traditionally been used to characterize the microbiome, the increasing number of published population genomics data sets offers an underexploited opportunity to study microbial profiles from the host shotgun sequencing data. Here, we use sequence data originally generated from killer whale Orcinus orca skin biopsies for population genomics, to characterize the skin microbiome and investigate how host social and geographical factors influence the microbial community composition. Having identified 845 microbial taxa from 2.4 million reads that did not map to the killer whale reference genome, we found that both ecotypic and geographical factors influence community composition of killer whale skin microbiomes. Furthermore, we uncovered key taxa that drive the microbiome community composition and showed that they are embedded in unique networks, one of which is tentatively linked to diatom presence and poor skin condition. Community composition differed between Antarctic killer whales with and without diatom coverage, suggesting that the previously reported episodic migrations of Antarctic killer whales to warmer waters associated with skin turnover may control the effects of potentially pathogenic bacteria such as Tenacibaculum dicentrarchi. Our work demonstrates the feasibility of microbiome studies from host shotgun sequencing data and highlights the importance of metagenomics in understanding the relationship between host and microbial ecology.Entities:
Keywords: zzm321990Orcinus orcazzm321990; Cetacea; contamination; metagenomics; microbiota
Mesh:
Year: 2018 PMID: 30187987 PMCID: PMC6487819 DOI: 10.1111/mec.14860
Source DB: PubMed Journal: Mol Ecol ISSN: 0962-1083 Impact factor: 6.185