PT  - JOURNAL ARTICLE
AU  - Nicolas Nalpas
AU  - Lesley Hoyles
AU  - Viktoria Anselm
AU  - Tariq Ganief
AU  - Laura Martinez-Gili
AU  - Cristina Grau
AU  - Irina Droste-Borel
AU  - Laetitia Davidovic
AU  - Xavier Altafaj
AU  - Marc-Emmanuel Dumas
AU  - Boris Macek
TI  - An Integrated Workflow for Enhanced Taxonomic and Functional Coverage of the Mouse Faecal Metaproteome
AID  - 10.1101/2020.11.17.386938
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.11.17.386938
4099  - http://biorxiv.org/content/early/2020/11/17/2020.11.17.386938.short
4100  - http://biorxiv.org/content/early/2020/11/17/2020.11.17.386938.full
AB  - The intestinal microbiota plays a key role in shaping host homeostasis by regulating metabolism, immune responses and behaviour. 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 faecal samples is challenging due to the physical structure of the sample, presence of contaminating host proteins and coexistence of hundreds of species. Furthermore, there is a lack of consensus regarding preparation of faecal samples, as well as downstream bioinformatic analyses following metaproteomic data acquisition. Here we assess sample preparation and data analysis strategies applied to mouse faeces in a typical LC-MS/MS metaproteomic experiment. We show that low speed centrifugation (LSC) of faecal samples leads to high protein identification rates and a balanced taxonomic representation. During database search, protein sequence databases derived from matched mouse faecal metagenomes provided up to four times more MS/MS identifications compared to other database construction strategies, while a two-step database search strategy led to accumulation of false positive protein identifications. Comparison of matching metaproteome and metagenome data revealed a positive correlation between protein and gene abundances, as well as significant overlap and correlation in taxonomic representation. 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.Competing Interest StatementThe authors have declared no competing interest.