Host‐derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin

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.

False‐negative detections from environmental DNA collected in the presence of large numbers of killer whales (Orcinus orca)

“…The need to consider potential contamination from sampling or laboratory sources is especially relevant when working with complex samples expected to contain low quantities of DNA. Trace human contamination of sequencing data that were found in 8 of the 9 samples is an inescapable issue in modern high-throughput sequencing facilities (see Hooper et al, 2019), as well as microbial contamination (Laurence, Hatzis, & Brash, 2014). Ultimately, both methods (qPCR and WGE) should have been susceptible to false-positives, as both approaches could conflate detections of DNA from closely related cetacean species and even more distantly related mammalian species such as humans, with detections of killer whale.…”

“…off Baja California sloughed skin independently of season and sea surface temperature; however, a tendency for a decrease in shed skin in cooler water was noted (Gendron & Mesnick, 2001). There is also evidence of water temperature influencing skin turnover rate in killer whales; for example, Antarctic killer whales make "skin maintenance migrations" of thousands of kilometers to warm waters to remove dead skin layers and associated diatom and microbial communities (Durban & Pitman, 2012;Hooper et al, 2019). While the sea surface temperature of the Northeast Atlantic waters sampled in this study are not as extreme as the frigid Antarctic waters, they may still be sufficiently cold to restrict blood flow to the outer skin layers, reducing turnover time and shedding rate, thus having an impact upon eDNA detection.…”

Spatial Structure of Marine Host-Associated Microbiomes: Effect of Taxonomy, Species Traits, and Study Design

“…The three studies of spatial structuring of marine mammal microbiomes (all examining the skin microbiome), all showed significant spatial structure (Bierlich et al, 2018;Grosser et al, 2019;Hooper et al, 2019).…”

A roadmap to mammalian oral microbiome evolution with dental calculus

“…Duplicate reads were removed with an in-house python script, which takes into account fragment length and sequence identity. The Illumina sequencing control phage PhiX was spiked into our sequencing runs and has previously been reported to have been erroneously integrated into many microbial genomes 23,67 . Reads were therefore mapped to PhiX (accession: GCA_000819615.1) with bwa mem v0.7.17 46,47 and the unmapped reads retained with SAMTools v1.9 68 and BEDTools v2.21.0 69 .…”

“…Collections in natural history museums provide the opportunity to study the effects of human-driven changes in animal populations over the last 200 years, including population declines and the introduction of pollutants like antibiotics [17][18][19][20] . Few studies to date have investigated microbiome changes in modern wild animal populations [21][22][23] , and historical populations remain virtually unexplored. Working with historical microbial DNA in any host species is challenging, and non-model host species pose additional difficulties.…”