Strategies for Metagenomic-Guided Whole-Community Proteomics of Complex Microbial Environments

Cantarel, Brandi L.; Erickson, Alison R.; VerBerkmoes, Nathan C.; Erickson, Brian K.; Carey, Patricia A.; Pan, Chongle; Shah, Manesh; Mongodin, Emmanuel F.; Jansson, Janet; Fraser, Claire M.; Hettich, Robert L.

doi:10.1371/journal.pone.0027173

Cited by 55 publications

(72 citation statements)

References 39 publications

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“…The 2D-DIGE strategy further solved the specific question of detecting differences between groups, a problem that faces even greater challenges in label-free shotgun metaproteomics. [26][27][28][29][30][31] A set of proteins from members of the Bacteroidetes phylum, largely Bacteroides species, were over-represented in CD microbiota. By contrast, under-represented proteins were mostly from Clostridiales (Firmicutes phylum), and more rarely from Prevotella and undefined Bacteroidales members.…”

Section: Discussionmentioning

confidence: 99%

Bacterial protein signals are associated with Crohn’s disease

Juste¹,

Kreil

Beauvallet³

et al. 2014

Gut

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ObjectiveNo Crohn’s disease (CD) molecular maker has advanced to clinical use, and independent lines of evidence support a central role of the gut microbial community in CD. Here we explore the feasibility of extracting bacterial protein signals relevant to CD, by interrogating myriads of intestinal bacterial proteomes from a small number of patients and healthy controls.DesignWe first developed and validated a workflow—including extraction of microbial communities, two-dimensional difference gel electrophoresis (2D-DIGE), and LC-MS/MS—to discover protein signals from CD-associated gut microbial communities. Then we used selected reaction monitoring (SRM) to confirm a set of candidates. In parallel, we used 16S rRNA gene sequencing for an integrated analysis of gut ecosystem structure and functions.ResultsOur 2D-DIGE-based discovery approach revealed an imbalance of intestinal bacterial functions in CD. Many proteins, largely derived from Bacteroides species, were over-represented, while under-represented proteins were mostly from Firmicutes and some Prevotella members. Most overabundant proteins could be confirmed using SRM. They correspond to functions allowing opportunistic pathogens to colonise the mucus layers, breach the host barriers and invade the mucosae, which could still be aggravated by decreased host-derived pancreatic zymogen granule membrane protein GP2 in CD patients. Moreover, although the abundance of most protein groups reflected that of related bacterial populations, we found a specific independent regulation of bacteria-derived cell envelope proteins.ConclusionsThis study provides the first evidence that quantifiable bacterial protein signals are associated with CD, which can have a profound impact on future molecular diagnosis.

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Section: Discussionmentioning

confidence: 99%

Bacterial protein signals are associated with Crohn’s disease

Juste¹,

Kreil

Beauvallet³

et al. 2014

Gut

View full text Add to dashboard Cite

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“…Protein profiles will be measured by two-dimensional nano liquid chromatography (2D-LC) and tandem mass spectrometry (MS/MS) (Cantarel et al, 2011; Presley et al, 2012), with proteins identified by searching custom databases consisting of the human genome, matched metagenomes from the same samples, and a defined set of reference genomes, including many that are in the HMP reference genome database. Based on preliminary results, it is anticipated that > 3,000 proteins will be identified per sample and that approximately half of the proteins will be human proteins based on a pretested method for preparation of the protein extracts.…”

Section: Ihmp Study: Characterizing the Gut Microbial Ecosystem For Dmentioning

confidence: 99%

The Integrative Human Microbiome Project: Dynamic Analysis of Microbiome-Host Omics Profiles during Periods of Human Health and Disease

2014

Cell Host & Microbe

441

218

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Much has been learned about the diversity and distribution of human-associated microbial communities, but we still know little about the biology of the microbiome, how it interacts with the host, and how the host responds to its resident microbiota. The Integrative Human Microbiome Project (iHMP, http://hmp2.org), the second phase of the NIH Human Microbiome Project, will study these interactions by analyzing microbiome and host activities in longitudinal studies of disease-specific cohorts and by creating integrated data sets of microbiome and host functional properties. These data sets will serve as experimental test beds to evaluate new models, methods, and analyses on the interactions of host and microbiome. Here we describe the three models of microbiome-associated human conditions, on the dynamics of preterm birth, inflammatory bowel disease, and type 2 diabetes, and their underlying hypotheses, as well as the multi-omic data types to be collected, integrated, and distributed through public repositories as a community resource.

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“…At first, Verberkmoes et al (2009b) published an analysis employing relative protein abundances (normalized spectral) for a comparison of two fecal samples and two distinct sequence databases. Cantarel et al (2011) used the same samples to test several computational strategies to improve protein identification. A new iterative workflow for protein identification leads to an increase of Clusters of Orthologous Groups (COG) categories (Rooijers et al, 2011).…”

Section: Label-free Approachesmentioning

confidence: 99%

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

et al. 2013

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The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ( 13 C, 15 N, 36 S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

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Strategies for Metagenomic-Guided Whole-Community Proteomics of Complex Microbial Environments

Cited by 55 publications

References 39 publications

Bacterial protein signals are associated with Crohn’s disease

Bacterial protein signals are associated with Crohn’s disease

The Integrative Human Microbiome Project: Dynamic Analysis of Microbiome-Host Omics Profiles during Periods of Human Health and Disease

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

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