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Bayesian Decomposition Analysis of Bacterial Phylogenomic Profiles

  • Original Research Article
  • Published:
American Journal of Pharmacogenomics

Abstract

Background

The past two decades have seen the appearance of new infectious diseases and the reemergence of old diseases previously thought to be under control. At the same time, the effectiveness of the existing antibacterials is rapidly decreasing due to the spread of multidrug-resistant pathogens.

Aim

The aim of this study was to the identify candidate molecular targets (e.g. enzymes) within essential metabolic pathways specific to a significant subset of bacterial pathogens as the first step in the rational design of new antibacterial drugs.

Methods

We constructed a dataset of phylogenomic profiles (vectors that encode the similarity, measured by BLAST scores, of a gene across many species) for a series of 31 pathogenic bacteria of interest with 1073 genes taken from the reference organisms Escherichia coli and Mycobacterium tuberculosis. We applied Bayesian Decomposition, a matrix decomposition algorithm, to identify functional metabolic units comprising overlapping sets of genes in this dataset.

Results

Although no information on phylogeny was provided to the system, Bayesian Decomposition retrieved the known bacteria phylogenic relationships on the basis of the proteins necessary for survival. In addition, a set of genes required by all bacteria was identified, as well as components and enzymes specific to subsets of bacteria.

Conclusion

The use of phylogenomic profiles and Bayesian Decomposition provide important insights for the design of new antibacterial therapeutics.

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Notes

  1. 1Supplementary material can be found at http://bioinformatics.fccc.edu/suppl/phylo|URL}.

  2. BC stands for BioCyc and is used for ontology identification.

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Acknowledgements

We wish to thank the National Institutes of Health, National Cancer Institute (for grant CCCG CA06927 to Dr R. Young), the Pennsylvania Department of Health (grant to Dr Ochs), the Pew Foundation for support.

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Authors and Affiliations

  1. Division of Population Science, Bioinformatics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA

    Ghislain Bidaut &  Michael F. Ochs

  2. Structural and Genomic Information Laboratory, (CNRS UPR2589), Marseille, France

    Ghislain Bidaut, Karsten Suhre & Jean-Michel Claverie

  3. School of Medicine, University of Mediterranee, Marseille, France

    Jean-Michel Claverie

Authors
  1. Ghislain Bidaut
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  2. Karsten Suhre
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  3. Jean-Michel Claverie
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  4. Michael F. Ochs
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Corresponding author

Correspondence to Michael F. Ochs.

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Bidaut, G., Suhre, K., Claverie, JM. et al. Bayesian Decomposition Analysis of Bacterial Phylogenomic Profiles. Am J Pharmacogenomics 5, 63–70 (2005). https://doi.org/10.2165/00129785-200505010-00006

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  • DOI: https://doi.org/10.2165/00129785-200505010-00006

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