BackgroundThe massive characterization of host-associated and environmental microbial communities has represented a real breakthrough in the life sciences in the last years. In this context, metaproteomics specifically enables the transition from assessing the genomic potential to actually measuring the functional expression of a microbiome. However, significant research efforts are still required to develop analysis pipelines optimized for metaproteome characterization.ResultsThis work presents an efficient analytical pipeline for shotgun metaproteomic analysis, combining bead-beating/freeze-thawing for protein extraction, filter-aided sample preparation for cleanup and digestion, and single-run liquid chromatography-tandem mass spectrometry for peptide separation and identification. The overall procedure is more time-effective and less labor-intensive when compared to state-of-the-art metaproteomic techniques. The pipeline was first evaluated using mock microbial mixtures containing different types of bacteria and yeasts, enabling the identification of up to over 15,000 non-redundant peptide sequences per run with a linear dynamic range from 104 to 108 colony-forming units. The pipeline was then applied to the mouse fecal metaproteome, leading to the overall identification of over 13,000 non-redundant microbial peptides with a false discovery rate of <1%, belonging to over 600 different microbial species and 250 functionally relevant protein families. An extensive mapping of the main microbial metabolic pathways actively functioning in the gut microbiome was also achieved.ConclusionsThe analytical pipeline presented here may be successfully used for the in-depth and time-effective characterization of complex microbial communities, such as the gut microbiome, and represents a useful tool for the microbiome research community.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-014-0049-2) contains supplementary material, which is available to authorized users.

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Milk fat globules (MFGs) are vesicles released in milk as fat droplets surrounded by the endoplasmic reticulum and apical cell membranes. During formation and apocrine secretion by lactocytes, various amounts of cytoplasmic crescents remain trapped within the released vesicle, making MFGs a natural sampling mechanism of the lactating cell contents. With the aim of investigating the events occurring in the mammary epithelium during bacterial infection, the MFG proteome was characterized by two-dimensional difference gel electrophoresis (2-D DIGE), SDS-PAGE followed by shotgun liquid chromatography-tandem mass spectrometry (GeLC-MS/MS), label-free quantification by the normalized spectral abundance factor (NSAF) approach, Western blotting, and pathway analysis, using sheep naturally infected by Mycoplasma agalactiae. A number of protein classes were found to increase in MFGs upon infection, including proteins involved in inflammation and host defense, cortical cytoskeleton proteins, heat shock proteins, and proteins related to oxidative stress. Conversely, a strikingly lower abundance was observed for proteins devoted to MFG metabolism and secretion. To our knowledge, this is the first report describing proteomic changes occurring in MFGs during sheep infectious mastitis. The results presented here offer new insights into the in vivo response of mammary epithelial cells to bacterial infection and open the way to the discovery of protein biomarkers for monitoring clinical and subclinical mastitis.

To date, most metaproteomic studies of the gut microbiota employ stool sample pretreatment methods to enrich for microbial components. However, a specific investigation aimed at assessing if, how, and to what extent this may impact on the final taxonomic and functional results is still lacking. Here, stool replicates were either pretreated by differential centrifugation (DC) or not centrifuged. Protein extracts were then processed by filter-aided sample preparation, single-run LC, and high-resolution MS, and the metaproteomic data were compared by spectral counting. DC led to a higher number of identifications, a significantly richer microbial diversity, as well as to reduced information on the nonmicrobial components (host and food) when compared to not centrifuged. Nevertheless, dramatic differences in the relative abundance of several gut microbial taxa were also observed, including a significant change in the Firmicutes/Bacteroidetes ratio. Furthermore, some important microbial functional categories, including cell surface enzymes, membrane-associated proteins, extracellular proteins, and flagella, were significantly reduced after DC. In conclusion, this work underlines that a critical evaluation is needed when selecting the appropriate stool sample processing protocol in the context of a metaproteomic study, depending on the specific target to which the research is aimed. All MS data have been deposited in the ProteomeXchange with identifier PXD001573 (http://proteomecentral.proteomexchange.org/dataset/PXD001573).

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