Oligotyping reveals community level habitat selection within the genus Vibrio
Schmidt, Victor T.
Zettler, Erik R.
Mincer, Tracy J.
Murphy, Leslie G.
Amaral-Zettler, Linda A.
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KeywordOligotyping; Vibrio ecology; Host-microbe interactions; Illumina sequencing; 16S rRNA analysis; Plastisphere; Aquaculture pathogens; Meta-analysis
The genus Vibrio is a metabolically diverse group of facultative anaerobic bacteria, common in aquatic environments and marine hosts. The genus contains several species of importance to human health and aquaculture, including the causative agents of human cholera and fish vibriosis. Vibrios display a wide variety of known life histories, from opportunistic pathogens to long-standing symbionts with individual host species. Studying Vibrio ecology has been challenging as individual species often display a wide range of habitat preferences, and groups of vibrios can act as socially cohesive groups. Although strong associations with salinity, temperature and other environmental variables have been established, the degree of habitat or host specificity at both the individual and community levels is unknown. Here we use oligotyping analyses in combination with a large collection of existing Vibrio 16S ribosomal RNA (rRNA) gene sequence data to reveal patterns of Vibrio ecology across a wide range of environmental, host, and abiotic substrate associated habitats. Our data show that individual taxa often display a wide range of habitat preferences yet tend to be highly abundant in either substrate-associated or free-living environments. Our analyses show that Vibrio communities share considerable overlap between two distinct hosts (i.e., sponge and fish), yet are distinct from the abiotic plastic substrates. Lastly, evidence for habitat specificity at the community level exists in some habitats, despite considerable stochasticity in others. In addition to providing insights into Vibrio ecology across a broad range of habitats, our study shows the utility of oligotyping as a facile, high-throughput and unbiased method for large-scale analyses of publically available sequence data repositories and suggests its wide application could greatly extend the range of possibilities to explore microbial ecology.
© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Microbiology 5 (2014): 563, doi:10.3389/fmicb.2014.00563.
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