​In a healthy state, microbiota (ensemble of microorganisms - bacteria, archaea, fungi, and viruses -and their collective genomes, termed microbiome), can mediate a variety of functions and biological processes in their hosts such as nutrition, energy metabolism, immune responses, or neurotransmission. Among the approaches available for studying microbiomes, metaproteomics, defined as the large-scale identification and quantification of proteins from microbial communities, is rapidly gaining traction as a method to directly observe the protein complement of organisms. Due to the paucity of molecular information for numerous animal species such as arthropods, microbial communities from these animals remain poorly characterized. Animal metaproteomics have focused on exploring the microbiomes from large animals such as mammals or birds and studies on small invertebrates are scarce. Metaproteomic data may be assigned using generalist databases encompassing all known genomes.

In the present study, researchers from SPI in Marcoule (Li2D) propose an iterative generalist database search strategy combining high-resolution mass spectrometry of proteins and RNA-seq of the host to characterize the microbiome of an organism not yet genome-sequenced. They propose to complement generalist databases with an RNA-seq-based protein database specific for the host, by using a previously RNA-seq data set acquired on Gammarus fossarum. The workflow was applied for the study of the microbiome of two tissues from the digestive tract of G. fossarum, a key species for aquatic systems with a body length of 2 to 15 mm, and an emergent model in environmental toxicology.

Gammarus fossarum © J.Armengaud/CEA

The pipeline proposed in this study allows discriminating host, residual food, and microbiome proteins, and identifies the main taxa and their functions at an unprecedented range, including archaea, bacteria, fungi, and parasites. These approaches pave the way for performing deep mechanistic studies in both host and host-associated microorganisms, and for fuller understanding of microbiome–host relationships.