Transkingdom network analysis provides insight into host-microbiome interactions in Atlantic salmon

Area of Science:

• Aquatic biology
• Microbiome research
• Computational biology

Background:

• Atlantic salmon gut is a dynamic system for host-microbiota interaction studies.
• Limited understanding of these interactions and computational tools for omics data integration exists.

Purpose of the Study:

• To develop and apply a computational pipeline for integrative analysis of host and microbial omics data.
• To investigate host-microbiota interactions in Atlantic salmon during environmental transitions.

Main Methods:

• Developed a pipeline integrating host RNAseq and microbial 16S rRNA amplicon sequencing data.
• Utilized weighted correlation network analysis for network inference and module detection.
• Employed module profile comparisons to identify host-microbiota interactions.

Main Results:

• Identified significant correlations between host gene expression modules and microbial community modules.
• Observed extensive gut epithelial transcriptome reprogramming and microbiota composition changes during fresh-/salt-water transition.
• Found evidence of host-microbiota interactions linked to feed composition, growth, and sex.

Conclusions:

• The developed pipeline effectively integrates multi-omics data to reveal host-microbiota interactions.
• Atlantic salmon gut exhibits significant transcriptional and microbial adaptations to environmental changes and diet.
• The findings highlight the complex interplay between host, microbiota, environment, and diet in salmon.