An integrated workflow for enhanced taxonomic and functional coverage of the mouse fecal metaproteome. (1st January 2021)

• Record Type: Journal Article
• Authors: Nalpas, Nicolas; Hoyles, Lesley; Anselm, Viktoria; Ganief, Tariq; Martinez-Gili, Laura; Grau, Cristina; Droste-Borel, Irina; Davidovic, Laetitia; Altafaj, Xavier; Dumas, Marc-Emmanuel; Macek, Boris
• Is Part Of: Gut microbes. Volume 13:Isuse 1(2021)
• Publication Date: 2021-01-01
• Subjects: Metaproteomics -- microbiome -- Mus musculus -- mass spectrometry -- proteogenomics; Gastrointestinal system -- Microbiology -- Periodicals; Microbiology -- Periodicals; Intestine, Small -- Periodicals; 616.3
• DOI: 10.1080/19490976.2021.1994836
• Languages: English
• ISSNs: 1949-0984

Abstract

ABSTRACT: Intestinal microbiota plays a key role in shaping host homeostasis by regulating metabolism, immune responses and behavior. Its dysregulation has been associated with metabolic, immune and neuropsychiatric disorders and is accompanied by changes in bacterial metabolic regulation. Although proteomics is well suited for analysis of individual microbes, metaproteomics of fecal samples is challenging due to the physical structure of the sample, presence of contaminating host proteins and coexistence of hundreds of taxa. Furthermore, there is a lack of consensus regarding preparation of fecal samples, as well as downstream bioinformatic analyses following metaproteomics data acquisition. Here we assess sample preparation and data analysis strategies applied to mouse feces in a typical mass spectrometry-based metaproteomic experiment. We show that subtle changes in sample preparation protocols may influence interpretation of biological findings. Two-step database search strategies led to significant underestimation of false positive protein identifications. Unipept software provided the highest sensitivity and specificity in taxonomic annotation of the identified peptides of unknown origin. Comparison of matching metaproteome and metagenome data revealed a positive correlation between protein and gene abundances. Notably, nearly all functional categories of detected protein groups were differentially abundant in the metaproteome compared to what would be expected from the metagenome, highlighting the need to perform metaproteomics when studying complex microbiome samples.