Metaproteomics

A special issue of Proteomes (ISSN 2227-7382).

Deadline for manuscript submissions: closed (31 October 2018) | Viewed by 37742

Special Issue Editors


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Guest Editor
Institute of Animal Science, Universität Hohenheim, 70599 Stuttgart, Germany
Interests: microbiome–animal interaction; gut microbiome
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Guest Editor
Research Group Bioinformatics (MF 1), Robert Koch Institute, 13353 Berlin, Germany

Special Issue Information

Dear Colleagues,

In recent years, advances in mass spectrometry instrumentation and bioinformatics are supporting microbial ecologists to gain deeper insights into microbial community functions and interaction with their environment. Together with the increasing amount of genomic information, a better understanding of the microbial processes is now possible. The proper identification of microbial peptides and proteins is one of the main challenges in metaproteomics. In addition, several other challenges have to be considered starting with a representative sampling and extraction method, appropriate proteomics workflow, quantification of proteins and data analyses. Thus, scientists are still facing several bottlenecks using metaproteomics which indicate the need for a very dynamic development of the methodology. We are interested in receiving original studies using metaproteomics in combination with other Omics tools to discover microbial communities associated with environmental samples, humans or animals. In addition, methodological studies improving the metaproteomics workflow are of interest.

We look forward to receiving your manuscripts in which metaproteomics is used as the key methodology.

Sincerely,

Prof. Dr. Jana Seifert
Dr. Thilo Muth
Guest Editor

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Keywords

  • Metaproteomics
  • Microbial functions
  • Microbial ecology
  • Bioinformatics
  • Combination of Omics

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Published Papers (6 papers)

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Editorial

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3 pages, 141 KiB  
Editorial
Editorial for Special Issue: Metaproteomics
by Jana Seifert and Thilo Muth
Proteomes 2019, 7(1), 9; https://doi.org/10.3390/proteomes7010009 - 5 Mar 2019
Cited by 2 | Viewed by 3652
Abstract
As the proteome-level counterpart of metagenomics, metaproteomics extends conventional single-organism proteomics and allows researchers to characterize the entire protein complement of complex microbiomes on a large scale [...] Full article
(This article belongs to the Special Issue Metaproteomics)

Research

Jump to: Editorial

15 pages, 2515 KiB  
Article
Analysis of the Bacterial and Host Proteins along and across the Porcine Gastrointestinal Tract
by Johanna Tröscher-Mußotter, Bruno Tilocca, Volker Stefanski and Jana Seifert
Proteomes 2019, 7(1), 4; https://doi.org/10.3390/proteomes7010004 - 10 Jan 2019
Cited by 28 | Viewed by 4571
Abstract
Pigs are among the most important farm animals worldwide and research to optimize their feed efficiency and improve their welfare is still in progress. The porcine intestinal microbiome is so far mainly known from sequencing-based studies. Digesta and mucosa samples from five different [...] Read more.
Pigs are among the most important farm animals worldwide and research to optimize their feed efficiency and improve their welfare is still in progress. The porcine intestinal microbiome is so far mainly known from sequencing-based studies. Digesta and mucosa samples from five different porcine gastrointestinal tract sections were analyzed by metaproteomics to obtain a deeper insight into the functions of bacterial groups with concomitant analyses of host proteins. Firmicutes (Prevotellaceae) dominated mucosa and digesta samples, followed by Bacteroidetes. Actinobacteria and Proteobacteria were much higher in abundance in mucosa compared to digesta samples. Functional profiling reveals the presence of core functions shared between digesta and mucosa samples. Protein abundances of energy production and conversion were higher in mucosa samples, whereas in digesta samples more proteins were involved in lipid transport and metabolism; short-chain fatty acids production were detected. Differences were also highlighted between sections, with the small intestine appearing more involved in carbohydrate transport and metabolism than the large intestine. Thus, this study produced the first functional analyses of the porcine GIT biology, discussing the findings in relation to expected bacterial and host functions. Full article
(This article belongs to the Special Issue Metaproteomics)
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19 pages, 4993 KiB  
Article
Challenges in Clinical Metaproteomics Highlighted by the Analysis of Acute Leukemia Patients with Gut Colonization by Multidrug-Resistant Enterobacteriaceae
by Julia Rechenberger, Patroklos Samaras, Anna Jarzab, Juergen Behr, Martin Frejno, Ana Djukovic, Jaime Sanz, Eva M. González-Barberá, Miguel Salavert, Jose Luis López-Hontangas, Karina B. Xavier, Laurent Debrauwer, Jean-Marc Rolain, Miguel Sanz, Marc Garcia-Garcera, Mathias Wilhelm, Carles Ubeda and Bernhard Kuster
Proteomes 2019, 7(1), 2; https://doi.org/10.3390/proteomes7010002 - 8 Jan 2019
Cited by 44 | Viewed by 7000
Abstract
The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we [...] Read more.
The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we will discuss in this study, there are still major challenges notably in data analysis that need to be overcome. Here, we analyzed 212 fecal samples from 56 hospitalized acute leukemia patients with multidrug-resistant Enterobactericeae (MRE) gut colonization using metagenomics and metaproteomics. This is one of the largest clinical metaproteomic studies to date, and the first metaproteomic study addressing the gut microbiome in MRE colonized acute leukemia patients. Based on this substantial data set, we discuss major current limitations in clinical metaproteomic data analysis to provide guidance to researchers in the field. Notably, the results show that public metagenome databases are incomplete and that sample-specific metagenomes improve results. Furthermore, biological variation is tremendous which challenges clinical study designs and argues that longitudinal measurements of individual patients are a valuable future addition to the analysis of patient cohorts. Full article
(This article belongs to the Special Issue Metaproteomics)
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15 pages, 3769 KiB  
Article
Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework
by Clemens Blank, Caleb Easterly, Bjoern Gruening, James Johnson, Carolin A. Kolmeder, Praveen Kumar, Damon May, Subina Mehta, Bart Mesuere, Zachary Brown, Joshua E. Elias, W. Judson Hervey, Thomas McGowan, Thilo Muth, Brook L. Nunn, Joel Rudney, Alessandro Tanca, Timothy J. Griffin and Pratik D. Jagtap
Proteomes 2018, 6(1), 7; https://doi.org/10.3390/proteomes6010007 - 31 Jan 2018
Cited by 35 | Viewed by 8519
Abstract
The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. [...] Read more.
The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics “Contribution Fest“ undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software. Full article
(This article belongs to the Special Issue Metaproteomics)
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Article
MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data
by Michael Riffle, Damon H. May, Emma Timmins-Schiffman, Molly P. Mikan, Daniel Jaschob, William Stafford Noble and Brook L. Nunn
Proteomes 2018, 6(1), 2; https://doi.org/10.3390/proteomes6010002 - 27 Dec 2017
Cited by 44 | Viewed by 8174
Abstract
Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to [...] Read more.
Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed “MetaGOmics”) that automates the quantitative functional (using Gene Ontology) and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis—including comparing the functional makeup between samples. MetaGOmics is freely available at https://www.yeastrc.org/metagomics/. Full article
(This article belongs to the Special Issue Metaproteomics)
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8700 KiB  
Article
Multi-Omic Biogeography of the Gastrointestinal Microbiota of a Pre-Weaned Lamb
by Antonio Palomba, Alessandro Tanca, Cristina Fraumene, Marcello Abbondio, Francesco Fancello, Alberto Stanislao Atzori and Sergio Uzzau
Proteomes 2017, 5(4), 36; https://doi.org/10.3390/proteomes5040036 - 18 Dec 2017
Cited by 13 | Viewed by 4827
Abstract
The digestive functions of the pre-weaned lamb gastrointestinal tracts (GITs) have been the subject of much research in recent years, but the microbial and host functions underlying these complex processes remain largely unknown. Here, we undertook a proof-of-principle metaproteogenomic investigation on luminal and [...] Read more.
The digestive functions of the pre-weaned lamb gastrointestinal tracts (GITs) have been the subject of much research in recent years, but the microbial and host functions underlying these complex processes remain largely unknown. Here, we undertook a proof-of-principle metaproteogenomic investigation on luminal and mucosal samples collected from 10 GITs of a 30-day-old pre-weaned lamb. We demonstrate that the analysis of the diverse ecological niches along the GITs can reveal microbiota composition and metabolic functions, although low amounts of microbial proteins could be identified in the small intestinal and mucosal samples. Our data suggest that a 30-day lamb has already developed mature microbial functions in the forestomachs, while the effect of the milky diet appears to be more evident in the remaining GITs. We also report the distribution and the relative abundance of the host functions, active at the GIT level, with a special focus on those involved in digestive processes. In conclusion, this pilot study supports the suitability of a metaproteogenomic approach to the characterization of microbial and host functions of the lamb GITs, opening the way to further studies aimed at investigating the impact of early dietary interventions on the GIT microbiota of small ruminants. Full article
(This article belongs to the Special Issue Metaproteomics)
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