The Unipept metaproteomics analysis pipeline

Mesuere, Bart; Debyser, Griet; Aerts, Maarten; Devreese, Bart; Vandamme, Peter; Dawyndt, Peter

doi:10.1002/pmic.201400361

Cited by 116 publications

(108 citation statements)

References 13 publications

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“…These 15 strains had 40–86% peptidome similarity to one another based on tryptic peptidome analysis (Unipept) (Supplemental Data Figure 2). Pairwise similarities were computed as a fraction of the size of the intersection over the size of the union of both peptidomes (15). Peptidome similarities between a representative strain D (ST231) isolate and representative members of strain A (ST281), strain B (ST348), or strain C (ST353) were about 60%.…”

Section: Resultsmentioning

confidence: 99%

A Novel Peptidomic Approach to Strain Typing of Clinical Acinetobacter baumannii Isolates Using Mass Spectrometry

et al. 2016

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Background Acinetobacter baumannii is a common nosocomial pathogen and strain-typing methods play important roles in hospital outbreak investigations and epidemiologic surveillance. We describe a method for identifying strain-specific peptide markers based on LC-MS/MS profiling of digested peptides. This method classified a test set of A. baumannii isolates collected from a hospital outbreak with discriminatory performance exceeding that of MALDI-TOF-MS. Methods Following the construction of a species “pan-peptidome” by in silico translation and digestion of whole genome sequences, a hypothetical set of genome-specific peptides for an isolate was constructed from the disjoint set of the pan-peptidome and the isolate’s calculated peptidome. The genome-specific peptidome guided selection of highly expressed genome-specific peptides from LC-MS/MS experimental profiles as potential peptide markers. The species specificity of each experimentally identified genome-specific peptide was confirmed through a Unipept lowest common ancestor analysis. Results Fifteen A. baumannii isolates were analyzed to derive a set of genome- and species-specific peptides that could be used as peptide markers. Identified peptides were cross-checked with protein BLAST against a set of 22 A. baumannii whole genome sequences. A subset of these peptide markers was confirmed to be present in the actual peptide profiles generated by multiple reaction monitoring and targeted LC-MS/MS. The experimentally identified peptides separated these isolates into six strains that agreed with multilocus sequence typing analysis performed on the same isolates. Conclusions This approach may be generalizable to other bacterial species, and the peptides may be useful for rapid MS strain tracking of isolates with broad application to infectious disease diagnosis.

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Section: Resultsmentioning

confidence: 99%

A Novel Peptidomic Approach to Strain Typing of Clinical Acinetobacter baumannii Isolates Using Mass Spectrometry

et al. 2016

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“…Only peptides with a false discovery rate (FDR) < 1% estimated by Percolator 50 and only rank 1 peptides were accepted as identified. Unipept v3.2 51 was applied to assign proteins to their phylogenetic origin. GhostKoala 52 and KEGG classifier were used for functional annotation.…”

Section: Methodsmentioning

confidence: 99%

Land use driven change in soil pH affects microbial carbon cycling processes

et al. 2018

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Soil microorganisms act as gatekeepers for soil–atmosphere carbon exchange by balancing the accumulation and release of soil organic matter. However, poor understanding of the mechanisms responsible hinders the development of effective land management strategies to enhance soil carbon storage. Here we empirically test the link between microbial ecophysiological traits and topsoil carbon content across geographically distributed soils and land use contrasts. We discovered distinct pH controls on microbial mechanisms of carbon accumulation. Land use intensification in low-pH soils that increased the pH above a threshold (~6.2) leads to carbon loss through increased decomposition, following alleviation of acid retardation of microbial growth. However, loss of carbon with intensification in near-neutral pH soils was linked to decreased microbial biomass and reduced growth efficiency that was, in turn, related to trade-offs with stress alleviation and resource acquisition. Thus, less-intensive management practices in near-neutral pH soils have more potential for carbon storage through increased microbial growth efficiency, whereas in acidic soils, microbial growth is a bigger constraint on decomposition rates.

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“…Moreover, peptides from sequences which could not be annotated by MEGAN were iteratively subjected to LCA taxonomic classification using the ‘Metaproteome analysis’ module of the Unipept web application (Mesuere et al, 2015). …”

Section: Methodsmentioning

confidence: 99%

Metaproteogenomics Reveals Taxonomic and Functional Changes between Cecal and Fecal Microbiota in Mouse

et al. 2017

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Previous studies on mouse models report that cecal and fecal microbial communities may differ in the taxonomic structure, but little is known about their respective functional activities. Here, we employed a metaproteogenomic approach, including 16S rRNA gene sequencing, shotgun metagenomics and shotgun metaproteomics, to analyze the microbiota of paired mouse cecal contents (CCs) and feces, with the aim of identifying changes in taxon-specific functions. As a result, Gram-positive anaerobes were observed as considerably higher in CCs, while several key enzymes, involved in oxalate degradation, glutamate/glutamine metabolism, and redox homeostasis, and most actively expressed by Bacteroidetes, were clearly more represented in feces. On the whole, taxon and function abundance appeared to vary consistently with environmental changes expected to occur throughout the transit from the cecum to outside the intestine, especially when considering metaproteomic data. The results of this study indicate that functional and metabolic differences exist between CC and stool samples, paving the way to further metaproteogenomic investigations aimed at elucidating the functional dynamics of the intestinal microbiota.

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The Unipept metaproteomics analysis pipeline

Cited by 116 publications

References 13 publications

A Novel Peptidomic Approach to Strain Typing of Clinical Acinetobacter baumannii Isolates Using Mass Spectrometry

A Novel Peptidomic Approach to Strain Typing of Clinical Acinetobacter baumannii Isolates Using Mass Spectrometry

Land use driven change in soil pH affects microbial carbon cycling processes

Metaproteogenomics Reveals Taxonomic and Functional Changes between Cecal and Fecal Microbiota in Mouse

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