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LAB-Secretome: a genome-scale comparative analysis of the predicted extracellular and surface-associated proteins of Lactic Acid Bacteria

Miaomiao Zhou13*, Daniel Theunissen23, Michiel Wels123 and Roland J Siezen123

Author affiliations

1 Centre for Molecular and Biomolecular Informatics, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, The Netherlands

2 TI Food and Nutrition, Wageningen, The Netherlands

3 NIZO food research, Ede, The Netherlands

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Citation and License

BMC Genomics 2010, 11:651  doi:10.1186/1471-2164-11-651

Published: 23 November 2010



In Lactic Acid Bacteria (LAB), the extracellular and surface-associated proteins can be involved in processes such as cell wall metabolism, degradation and uptake of nutrients, communication and binding to substrates or hosts. A genome-scale comparative study of these proteins (secretomes) can provide vast information towards the understanding of the molecular evolution, diversity, function and adaptation of LAB to their specific environmental niches.


We have performed an extensive prediction and comparison of the secretomes from 26 sequenced LAB genomes. A new approach to detect homolog clusters of secretome proteins (LaCOGs) was designed by integrating protein subcellular location prediction and homology clustering methods. The initial clusters were further adjusted semi-manually based on multiple sequence alignments, domain compositions, pseudogene analysis and biological function of the proteins. Ubiquitous protein families were identified, as well as species-specific, strain-specific, and niche-specific LaCOGs. Comparative analysis of protein subfamilies has shown that the distribution and functional specificity of LaCOGs could be used to explain many niche-specific phenotypes.

A comprehensive and user-friendly database LAB-Secretome was constructed to store, visualize and update the extracellular proteins and LaCOGs webcite. This database will be updated regularly when new bacterial genomes become available.


The LAB-Secretome database could be used to understand the evolution and adaptation of lactic acid bacteria to their environmental niches, to improve protein functional annotation and to serve as basis for targeted experimental studies.