MetaPro-IQ: a universal metaproteomic approach to studying human and mouse gut microbiota

Abstract

BackgroundThe gut microbiota has been shown to be closely associated with human health and disease. While next-generation sequencing can be readily used to profile the microbiota taxonomy and metabolic potential, metaproteomics is better suited for deciphering microbial biological activities. However, the application of gut metaproteomics has largely been limited due to the low efficiency of protein identification. Thus, a high-performance and easy-to-implement gut metaproteomic approach is required.ResultsIn this study, we developed a high-performance and universal workflow for gut metaproteome identification and quantification (named MetaPro-IQ) by using the close-to-complete human or mouse gut microbial gene catalog as database and an iterative database search strategy. An average of 38 and 33 % of the acquired tandem mass spectrometry (MS) spectra was confidently identified for the studied mouse stool and human mucosal-luminal interface samples, respectively. In total, we accurately quantified 30,749 protein groups for the mouse metaproteome and 19,011 protein groups for the human metaproteome. Moreover, the MetaPro-IQ approach enabled comparable identifications with the matched metagenome database search strategy that is widely used but needs prior metagenomic sequencing. The response of gut microbiota to high-fat diet in mice was then assessed, which showed distinct metaproteome patterns for high-fat-fed mice and identified 849 proteins as significant responders to high-fat feeding in comparison to low-fat feeding.ConclusionsWe present MetaPro-IQ, a metaproteomic approach for highly efficient intestinal microbial protein identification and quantification, which functions as a universal workflow for metaproteomic studies, and will thus facilitate the application of metaproteomics for better understanding the functions of gut microbiota in health and disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-016-0176-z) contains supplementary material, which is available to authorized users.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease

“…Recent proteomics-based advances have attempted to address the issue of the microbiome complexity by improving methods in sample preparation 16,17 database search strategies and algorithms, 18,19 and implementation of proteogenomics. 20,21 Despite these extensive improvements to metaproteomics, the sensitivity of LC-MS/MS instrumentation constrains data collection to a small percentage of the most abundant peptides in a proteomic sample.…”

An in vitro model maintaining taxon-specific functional activities of the gut microbiome

“…Elucidating the microbiome's functions requires a comprehensive quantification of the transcripts, proteins and/or metabolites produced by the microbial community. Here we used a metaproteomic approach we recently developed 38 to simultaneously characterize the microbiome's taxonomic biomass contributions and its functional activity while developing and validating a high-throughput in vitro model for the Maintenance of gut microbiome Profiles (MiPro).…”

“…To assess the stability of functional activities, the identified proteins were annotated with clusters of orthologous group (COG) categories and the abundance of each COG category was calculated by summing the LFQ intensities of all the proteins belonging to the same COG category 38 . Principal component analysis (PCA) was used to assess the relatedness of the samples based on the functional makeup of the metaproteomes.…”

“…Protein extraction, trypsin digestion, and desalting steps were carried out as previously described 38 , with a minor modification of the cell washing step. Briefly, for general analysis, the samples were washed two times with PBS at 14,000 × g, 4°C for 20 min.…”

Activity-Based Protein Profiling—Enabling Multimodal Functional Studies of Microbial Communities

“…Several approaches to address this problem have been developed over the past few years (ComPIL, MetaLab, etc.) (Chatterjee et al 2016; Zhang et al 2016; Cheng et al 2017). Such tools will likely play a key role in successfully drawing conclusions out of massive proteomics datasets.…”