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Deep metaproteomic analysis of human salivary supernatant.

ABSTRACT: The human salivary proteome is extremely complex, including proteins from salivary glands, serum, and oral microbes. Much has been learned about the host component, but little is known about the microbial component. Here we report a metaproteomic analysis of salivary supernatant pooled from six healthy subjects. For deep interrogation of the salivary proteome, we combined protein dynamic range compression (DRC), multidimensional peptide fractionation, and high-mass accuracy MS/MS with a novel two-step peptide identification method using a database of human proteins plus those translated from oral microbe genomes. Peptides were identified from 124 microbial species as well as uncultured phylotypes such as TM7. Streptococcus, Rothia, Actinomyces, Prevotella, Neisseria, Veilonella, Lactobacillus, Selenomonas, Pseudomonas, Staphylococcus, and Campylobacter were abundant among the 65 genera from 12 phyla represented. Taxonomic diversity in our study was broadly consistent with metagenomic studies of saliva. Proteins mapped to 20 KEGG pathways, with carbohydrate metabolism, amino acid metabolism, energy metabolism, translation, membrane transport, and signal transduction most represented. The communities sampled appear to be actively engaged in glycolysis and protein synthesis. This first deep metaproteomic catalog from human salivary supernatant provides a baseline for future studies of shifts in microbial diversity and protein activities potentially associated with oral disease.

SUBMITTER: Jagtap P

PROVIDER: S-EPMC3517020 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Deep metaproteomic analysis of human salivary supernatant.

Jagtap Pratik P McGowan Thomas T Bandhakavi Sricharan S Tu Zheng Jin ZJ Seymour Sean S Griffin Timothy J TJ Rudney Joel D JD

Proteomics 20120401 7

The human salivary proteome is extremely complex, including proteins from salivary glands, serum, and oral microbes. Much has been learned about the host component, but little is known about the microbial component. Here we report a metaproteomic analysis of salivary supernatant pooled from six healthy subjects. For deep interrogation of the salivary proteome, we combined protein dynamic range compression (DRC), multidimensional peptide fractionation, and high-mass accuracy MS/MS with a novel tw ...[more]

PMID: 22522805

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Project description:BACKGROUNDResearch involving microbial ecosystems has drawn increasing attention in recent years. Studying microbe-microbe, host-microbe, and environment-microbe interactions are essential for the understanding of microbial ecosystems. Currently, metaproteomics provide qualitative and quantitative information of proteins, providing insights into the functional changes of microbial communities. However, computational analysis of large-scale data generated in metaproteomic studies remains a challenge. Conventional proteomic software have difficulties dealing with the extreme complexity and species diversity present in microbiome samples leading to lower rates of peptide and protein identification. To address this issue, we previously developed the MetaPro-IQ approach for highly efficient microbial protein/peptide identification and quantification.RESULTHere, we developed an integrated software platform, named MetaLab, providing a complete and automated, user-friendly pipeline for fast microbial protein identification, quantification, as well as taxonomic profiling, directly from mass spectrometry raw data. Spectral clustering adopted in the pre-processing step dramatically improved the speed of peptide identification from database searches. Quantitative information of identified peptides was used for estimating the relative abundance of taxa at all phylogenetic ranks. Taxonomy result files exported by MetaLab are fully compatible with widely used metagenomics tools. Herein, the potential of MetaLab is evaluated by reanalyzing a metaproteomic dataset from mouse gut microbiome samples.CONCLUSIONMetaLab is a fully automatic software platform enabling an integrated data-processing pipeline for metaproteomics. The function of sample-specific database generation can be very advantageous for searching peptides against huge protein databases. It provides a seamless connection between peptide determination and taxonomic profiling; therefore, the peptide abundance is readily used for measuring the microbial variations. MetaLab is designed as a versatile, efficient, and easy-to-use tool which can greatly simplify the procedure of metaproteomic data analysis for researchers in microbiome studies.

Project description:BackgroundThe consecutive monoculture for most of medicinal plants, such as Rehmannia glutinosa, results in a significant reduction in the yield and quality. There is an urgent need to study for the sustainable development of Chinese herbaceous medicine.Methodology/principal findingsComparative metaproteomics of rhizosphere soil was developed and used to analyze the underlying mechanism of the consecutive monoculture problems of R. glutinosa. The 2D-gel patterns of protein spots for the soil samples showed a strong matrix dependency. Among the spots, 103 spots with high resolution and repeatability were randomly selected and successfully identified by MALDI TOF-TOF MS for a rhizosphere soil metaproteomic profile analysis. These proteins originating from plants and microorganisms play important roles in nutrient cycles and energy flow in rhizospheric soil ecosystem. They function in protein, nucleotide and secondary metabolisms, signal transduction and resistance. Comparative metaproteomics analysis revealed 33 differentially expressed protein spots in rhizosphere soil in response to increasing years of monoculture. Among them, plant proteins related to carbon and nitrogen metabolism and stress response, were mostly up-regulated except a down-regulated protein (glutathione S-transferase) involving detoxification. The phenylalanine ammonia-lyase was believed to participate in the phenylpropanoid metabolism as shown with a considerable increase in total phenolic acid content with increasing years of monoculture. Microbial proteins related to protein metabolism and cell wall biosynthesis, were up-regulated except a down-regulated protein (geranylgeranyl pyrophosphate synthase) functioning in diterpenoid synthesis. The results suggest that the consecutive monoculture of R. glutinosa changes the soil microbial ecology due to the exudates accumulation, as a result, the nutrient cycles are affected, leading to the retardation of plant growth and development.Conclusions/significanceOur results demonstrated the interactions among plant, soil and microflora in the proteomic level are crucial for the productivity and quality of R. glutinosa in consecutive monoculture system.

Project description:The use of metaproteomics for studying the human gut microbiota can shed light on the taxonomic profile and the functional role of the microbial community. Nevertheless, methods for extracting proteins from stool samples continue to evolve, in the pursuit of optimal protocols for moistening and dispersing the stool sample and for disrupting microbial cells, which are two critical steps for ensuring good protein recovery. Here, we evaluated different stool sample processing (SSP) and microbial cell disruption methods (CDMs). The combination of a longer disintegration period of the stool sample in a tube rotator with sonication increased the overall number of identified peptides and proteins. Proteobacteria, Bacteroidetes, Planctomycetes, and Euryarchaeota identification was favored by mechanical cell disruption with glass beads. In contrast, the relative abundance of Firmicutes, Actinobacteria, and Fusobacteria was improved when sonication was performed before bead beating. Tenericutes and Apicomplexa identification was enhanced by moistening the stool samples during processing and by disrupting cells with medium-sized glass beads combined with or without sonication. Human protein identifications were affected by sonication. To test the reproducibility of these gut metaproteomic analyses, we examined samples from six healthy individuals using a protocol that had shown a good taxonomic diversity and identification of proteins from Proteobacteria and humans. We also detected proteins involved in microbial functions relevant to the host and related mostly to specific taxa, such as B12 biosynthesis and short chain fatty acid (SCFA) production carried out mainly by members in the Prevotella genus and the Firmicutes phylum, respectively. The taxonomic and functional profiles obtained with the different protocols described in this work provides the researcher with valuable information when choosing the most adequate protocol for the study of certain pathologies under suspicion of being related to a specific taxon from the gut microbiota.

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Deep metaproteomic analysis of human salivary supernatant.

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Deep metaproteomic analysis of human salivary supernatant.

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