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Protein Homology Network Families Reveal Step-Wise Diversification of Type III and Type IV Secretion Systems

Overview of attention for article published in PLoS Computational Biology, December 2006
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Title
Protein Homology Network Families Reveal Step-Wise Diversification of Type III and Type IV Secretion Systems
Published in
PLoS Computational Biology, December 2006
DOI 10.1371/journal.pcbi.0020173
Pubmed ID
Authors

Duccio Medini, Antonello Covacci, Claudio Donati

Abstract

From the analysis of 251 prokaryotic genomes stored in public databases, the 761,260 deduced proteins were used to reconstruct a complete set of bacterial proteic families. Using the new Overlap algorithm, we have partitioned the Protein Homology Network (PHN), where the proteins are the nodes and the links represent homology relationships. The algorithm identifies the densely connected regions of the PHN that define the families of homologous proteins, here called PHN-Families, recognizing the phylogenetic relationships embedded in the network. By direct comparison with a manually curated dataset, we assessed that this classification algorithm generates data of quality similar to a human expert. Then, we explored the network to identify families involved in the assembly of Type III and Type IV secretion systems (T3SS and T4SS). We noticed that, beside a core of conserved functions (eight proteins for T3SS, seven for T4SS), a variable set of accessory components is always present (one to nine for T3SS, one to five for T4SS). Each member of the core corresponds to a single PHN-Family, while accessory proteins are distributed among different pure families. The PHN-Family classification suggests that T3SS and T4SS have been assembled through a step-wise, discontinuous process, by complementing the conserved core with subgroups of nonconserved proteins. Such genetic modules, independently recruited and probably tuned on specific effectors, contribute to the functional specialization of these organelles to different microenvironments.

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Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Portugal 1 2%
Italy 1 2%
Australia 1 2%
Sweden 1 2%
Luxembourg 1 2%
Unknown 53 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 35%
Student > Ph. D. Student 13 22%
Professor > Associate Professor 5 8%
Professor 4 7%
Student > Postgraduate 4 7%
Other 9 15%
Unknown 4 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 52%
Biochemistry, Genetics and Molecular Biology 8 13%
Computer Science 7 12%
Environmental Science 2 3%
Engineering 2 3%
Other 5 8%
Unknown 5 8%