Emergent community architecture despite distinct diversity in the global whale shark (Rhincodon typus) epidermal microbiome

Abstract

Microbiomes confer beneficial physiological traits to their host, but microbial diversity is inherently variable, challenging the relationship between microbes and their contribution to host health. Here, we compare the diversity and architectural complexity of the epidermal microbiome from 74 individual whale sharks (Rhincodon typus) across five aggregations globally to determine if network properties may be more indicative of the microbiome-host relationship. On the premise that microbes are expected to exhibit biogeographic patterns globally and that distantly related microbial groups can perform similar functions, we hypothesized that microbiome co-occurrence patterns would occur independently of diversity trends and that keystone microbes would vary across locations. We found that whale shark aggregation was the most important factor in discriminating taxonomic diversity patterns. Further, microbiome network architecture was similar across all aggregations, with degree distributions matching Erdos–Renyi-type networks. The microbiome-derived networks, however, display modularity indicating a definitive microbiome structure on the epidermis of whale sharks. In addition, whale sharks hosted 35 high-quality metagenome assembled genomes (MAGs) of which 25 were present from all sample locations, termed the abundant ‘core’. Two main MAG groups formed, defined here as Ecogroup 1 and 2, based on the number of genes present in metabolic pathways, suggesting there are at least two important metabolic niches within the whale shark microbiome. Therefore, while variability in microbiome diversity is high, network structure and core taxa are inherent characteristics of the epidermal microbiome in whale sharks. We suggest the host-microbiome and microbe-microbe interactions that drive the self-assembly of the microbiome help support a functionally redundant abundant core and that network characteristics should be considered when linking microbiomes with host health.

Elasmobranchs Exhibit Species-Specific Epidermal Microbiomes Guided by Denticle Topography

“…An equally important contributor to the microbial compositions are the Sphingomonodacaea population which, belonging to the Alpha-proteobacteria clade, are key contributors to initial biofilm formation and are able utilize a wide array of organic compounds 45 . Together, these two major contributors dominate the microbiome of T. semifasciata , H. francisci , and C. ventriosum , and we theorize these phyla represent core contributors and regulators to the microbiome composition of elasmobranchs, being identified in multiple shark and ray species 5,8,15,19 .…”

“…The coupling of the eukaryotic host and its respective microbial communities ("microbiome") has been reclassified as a meta-organism, representing the mutualistic dependence between a multicellular organism and its respective microbial communities 1 . Factors such as host age 2 , life history 3 , diet 4,5 , environment 6,7 , and body site 8 contribute to the composition of microbial communities to varying extents, both internally (e.g., oral, gut, reproductive tracts, etc.) and externally (integumentary system, i.e.…”

“…The epidermal microbiome of different marine vertebrates such as teleost fish, cartilaginous fish (elasmobranchs), and marine mammals contains core microbial species that are conserved throughout their geographic regions and genetically distinction from the surrounding environment 4,12 . Whale sharks ( Rhincodon typus) from sub-tropical locations around the world share a core microbiome, including the genera Rheinheimera, Leeuwenhoekiella, Algoriphagus, Sphingoblium, Aeqorivita, and Flavobacterium 5 . Humpback whales ( Megaptera novaeangliae ) found across the northern Pacific, have a distinct set of microbial species including Psychrobacter , Tenacibaculum , uncultured Moraxellaceae , Flavobacterium , Flavobacteriaceae , and Gracilibacteri 13 .…”

Integration of metataxonomic datasets into microbial association networks highlights shared bacterial community dynamics in fermented vegetables

“…By integrating several public datasets together, we were able to characterize two successional shifts that were conserved among different fermentation ecosystems: the first from the initial microbial population of vegetables to Enterobacterales , and the second to an assemblage dominated by Lactobacillales . To test the significance of the core network we obtained, we used an approach based on comparison to a null model, which was similar to that developed by Röttjers et al [22], with a sampling of random graphs similar to Doane et al [32]. Indeed, the identification of core networks is a more challenging task than computation of the global intersection network [21].…”