Lineage-specific microbial protein prediction enables large-scale exploration of protein ecology within the human gut

Nature Communications, vol. 16, pp. 3204

Abstract

Microbes use a range of genetic codes and gene structures, yet these are often ignored during metagenomic analysis. This causes spurious protein predictions, preventing functional assignment which limits our understanding of ecosystems. To resolve this, we developed a lineage-specific gene prediction approach that uses the correct genetic code based on the taxonomic assignment of genetic fragments, removes incomplete protein predictions, and optimises prediction of small proteins. Applied to 9634 metagenomes and 3594 genomes from the human gut, this approach increased the landscape of captured expressed microbial proteins by 78.9%, including previously hidden functional groups. Optimised small protein prediction captured 3,772,658 small protein clusters, which form an improved microbial protein catalogue of the human gut (MiProGut). To enable the ecological study of a protein's prevalence and association with host parameters, we developed InvestiGUT, a tool which integrates both the protein sequences and sample metadata. Accurate prediction of proteins is critical to providing a functional understanding of microbiomes, enhancing our ability to study interactions between microbes and hosts.

Authors 4

1. Matthias A. Schmitz Aachen Functional Microbiome Research Group

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Functional Microbiome Research Group, RWTH University Hospital, Aachen, Germany

2. Nicholas J Dimonaco

   Queen's University Belfast · Aberystwyth University

   Affiliation as printed

   Department of Computer Science, Aberystwyth University, Aberystwyth, UK

   Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, UK

3. Thomas Clavel Aachen Functional Microbiome Research Group

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Functional Microbiome Research Group, RWTH University Hospital, Aachen, Germany

4. Thomas C. A. Hitch corresponding Aachen Functional Microbiome Research Group

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Functional Microbiome Research Group, RWTH University Hospital, Aachen, Germany. thitch@ukaachen.de