Abstract
BackgroundThe Atlantic salmon gut constitutes an intriguing system for studying host-microbiota interactions due to the dramatic environmental change salmon experiences during its life cycle. Yet, little is known about the role of interactions in this system and there is a general deficit in computational methods for integrative analysis of omics data from host-microbiota systems. MethodsWe developed a pipeline to integrate host RNAseq data and microbial 16S rRNA amplicon sequencing data using weighted correlation network analysis. Networks are first inferred from each dataset separately, followed by module detections and finally robust identification of interactions via comparisons of representative module profiles. Through the use of module profiles, this network-based dimensionality reduction approach provides a holistic view into the discovery of potential host-microbiota symbionts. ResultsWe analyzed host gene expression from the gut epithelial tissue and microbial abundances from the salmon gut in a long-term feeding trial spanning the fresh-/salt-water transition and including two feeds resembling the fatty acid compositions available in salt- and fresh-water environments, respectively. We identified several host modules with significant correlations to both microbiota modules and variables such as feed, growth and sex. Although the strongest associations largely coincided with the fresh-/salt-water transition, there was a second layer of correlations associating smaller host modules to both variables and microbiota modules. Hence, we identify extensive reprogramming of the gut epithelial transcriptome and large scale coordinated changes in gut microbiota composition associated with water type as well as evidence of host-microbiota interactions linked to feed.
Highlights
Plants and animals are hosts to a myriad of bacteria, archaea, fungi, protozoa and viruses that make these multicellular organisms their home
To gain insight into host-microbiota interactions in the Atlantic salmon (Salmo salar) gut, we performed an integrative analysis of RNA-seq data from the gut epithelial tissue [15] and 16S rRNA amplicon sequencing data from the gut content [20,35] collected from a long-term feeding trial (Supplementary Fig. 1)
We developed a computational pipeline for integrating host and microbiota omics datasets based on weighted network analysis (Supplemental Fig. 2)
Summary
Plants and animals are hosts to a myriad of bacteria, archaea, fungi, protozoa and viruses that make these multicellular organisms their home. The migration from fresh- to salt-water would kill most fish species, and requires the salmon to undergo substantial changes in the regulation of body chemistry to successfully adapt (smoltification). This transition represents a barrier to the gut microbiota, which in addition has to adapt to the differences in food between rivers and the ocean.
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