Literature DB >> 23636904

Proteogenomics for environmental microbiology.

Jean Armengaud1, Erica Marie Hartmann, Céline Bland.   

Abstract

Proteogenomics sensu stricto refers to the use of proteomic data to refine the annotation of genomes from model organisms. Because of the limitations of automatic annotation pipelines, a relatively high number of errors occur during the structural annotation of genes coding for proteins. Whether putative orphan sequences or short genes encoding low-molecular-weight proteins really exist is still frequently a mystery. Whether start codons are well defined is also an open debate. These problems are exacerbated for genomes of microorganisms belonging to poorly documented genera, as related sequences are not always available for homology-guided annotation. The functional annotation of a significant proportion of genes is also another well-known issue when annotating environmental microorganisms. High-throughput shotgun proteomics has recently greatly evolved, allowing the exploration of the proteome from any microorganism at an unprecedented depth. The structural and functional annotation process may be usefully complemented with experimental data. Indeed, proteogenomic mapping has been successfully performed for a wide variety of organisms. Specific approaches devoted to systematically establishing the N-termini of a large set of proteins are being developed. N-terminomics is giving rise to datasets of experimentally proven translational start codons as well as validated peptide signals for secreted proteins. By extension, combining genomic and proteomic data is becoming routine in many research projects. The proteomic analysis of organisms with unfinished genome sequences, the so-called composite proteomics, and the search for microbial biomarkers by bottom-up and top-down combined approaches are some examples of proteogenomic-flavored studies. They illustrate the advent of a new era of environmental microbiology where proteomics and genomics are intimately integrated to answer key biological questions.
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Genome annotation; High-throughput proteomics; Microbiology; N-Terminomics; Proteogenomics; Translational start site

Mesh:

Year:  2013        PMID: 23636904     DOI: 10.1002/pmic.201200576

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  15 in total

1.  GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes.

Authors:  Jia Zhang; Ming-Kun Yang; Honghui Zeng; Feng Ge
Journal:  Mol Cell Proteomics       Date:  2016-09-14       Impact factor: 5.911

2.  Tissue-specific Proteogenomic Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline.

Authors:  Xun Zhu; Shangbo Xie; Jean Armengaud; Wen Xie; Zhaojiang Guo; Shi Kang; Qingjun Wu; Shaoli Wang; Jixing Xia; Rongjun He; Youjun Zhang
Journal:  Mol Cell Proteomics       Date:  2016-02-22       Impact factor: 5.911

3.  Proteogenomics: emergence and promise.

Authors:  Sam Faulkner; Matthew D Dun; Hubert Hondermarck
Journal:  Cell Mol Life Sci       Date:  2015-01-22       Impact factor: 9.261

4.  Proteogenomics of Gammarus fossarum to document the reproductive system of amphipods.

Authors:  Judith Trapp; Olivier Geffard; Gilles Imbert; Jean-Charles Gaillard; Anne-Hélène Davin; Arnaud Chaumot; Jean Armengaud
Journal:  Mol Cell Proteomics       Date:  2014-10-07       Impact factor: 5.911

Review 5.  Proteogenomics from a bioinformatics angle: A growing field.

Authors:  Gerben Menschaert; David Fenyö
Journal:  Mass Spectrom Rev       Date:  2015-12-15       Impact factor: 10.946

Review 6.  Systems-based approaches to unravel multi-species microbial community functioning.

Authors:  Florence Abram
Journal:  Comput Struct Biotechnol J       Date:  2014-12-03       Impact factor: 7.271

7.  Data for comparative proteomics of ovaries from five non-model, crustacean amphipods.

Authors:  Judith Trapp; Christine Almunia; Jean-Charles Gaillard; Olivier Pible; Arnaud Chaumot; Olivier Geffard; Jean Armengaud
Journal:  Data Brief       Date:  2015-08-12

8.  Assessing the exoproteome of marine bacteria, lesson from a RTX-toxin abundantly secreted by Phaeobacter strain DSM 17395.

Authors:  Emie Durighello; Joseph Alexander Christie-Oleza; Jean Armengaud
Journal:  PLoS One       Date:  2014-02-24       Impact factor: 3.240

9.  Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture.

Authors:  Alessandro Tanca; Antonio Palomba; Massimo Deligios; Tiziana Cubeddu; Cristina Fraumene; Grazia Biosa; Daniela Pagnozzi; Maria Filippa Addis; Sergio Uzzau
Journal:  PLoS One       Date:  2013-12-09       Impact factor: 3.240

10.  Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework.

Authors:  Pratik D Jagtap; James E Johnson; Getiria Onsongo; Fredrik W Sadler; Kevin Murray; Yuanbo Wang; Gloria M Shenykman; Sricharan Bandhakavi; Lloyd M Smith; Timothy J Griffin
Journal:  J Proteome Res       Date:  2014-10-23       Impact factor: 4.466

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