The investigating functional molecular pathways of an organism are at the basis of the understanding of complex microbial ecosystems. In the case of unicellular organisms, the description of protein pathways provides information on the functionality of a microbial consortium. We recently developed a semi-automated pipeline for the analysis of metaproteomics data to depict the newborn mouse gut phylotypes.1 Here we present a refined bioinformatics tool to extend the analysis to a more interesting description of the metabolic functions correlated with the characterized microbial taxa, using a typical PDO Italian cheese as model. Metaproteomics raw data are analyzed to obtain a representation of the bacterial population at different taxonomic levels on the bases of the taxon-specificity of a tryptic peptide list, comparing it with that coming from the already available metaproteomics and metagenomics applications such as Megan2. As a further development we managed for the automated association of taxa to metabolic pathways (KEGG database) and of proteins to groups of cluster orthologs (COG). We optimized parameters to have the maximum number of protein and minimum FDR, and then developed a series of python scripts to integrate and improve, the output of available application, and manipulate raw data. This investigation aims at providing a functional insight in metagenomic analysis, and at offer a direct evaluation of protein functional pathways which are actually controlling the consortia homeostasis.

Bioinformatics pipeline for metaproteomics data analysis : investigation on microbial populations and their respective functional role in cheese / A. Cavola, A. Soggiu, A. Urbani, S. Levi Mortera, C. Piras, P. Roncada - In: 9th Annual Congress ItPA : Next Generation Proteomics / [a cura di] Italian Proteomics Association. - Milano : EdiSES, 2014 Jun. - ISBN 9788879598231. - pp. 143-143 (( Intervento presentato al 9. convegno ItPA Annual Congress : Next generation Proteomics tenutosi a Napoli nel 2014.

Bioinformatics pipeline for metaproteomics data analysis : investigation on microbial populations and their respective functional role in cheese

A. Soggiu;C. Piras;P. Roncada
2014-06

Abstract

The investigating functional molecular pathways of an organism are at the basis of the understanding of complex microbial ecosystems. In the case of unicellular organisms, the description of protein pathways provides information on the functionality of a microbial consortium. We recently developed a semi-automated pipeline for the analysis of metaproteomics data to depict the newborn mouse gut phylotypes.1 Here we present a refined bioinformatics tool to extend the analysis to a more interesting description of the metabolic functions correlated with the characterized microbial taxa, using a typical PDO Italian cheese as model. Metaproteomics raw data are analyzed to obtain a representation of the bacterial population at different taxonomic levels on the bases of the taxon-specificity of a tryptic peptide list, comparing it with that coming from the already available metaproteomics and metagenomics applications such as Megan2. As a further development we managed for the automated association of taxa to metabolic pathways (KEGG database) and of proteins to groups of cluster orthologs (COG). We optimized parameters to have the maximum number of protein and minimum FDR, and then developed a series of python scripts to integrate and improve, the output of available application, and manipulate raw data. This investigation aims at providing a functional insight in metagenomic analysis, and at offer a direct evaluation of protein functional pathways which are actually controlling the consortia homeostasis.
metaproteomics ; microbiology ; cheese
Settore VET/05 - Malattie Infettive degli Animali Domestici
Settore MED/07 - Microbiologia e Microbiologia Clinica
Settore BIO/10 - Biochimica
Italian Proteomics Association
http://www.itpa.it/Attivita/2014/IX-ItPA-Congress-2014
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/236986
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