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Open Access Research article

Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

Sébastien Terrat123, Eric Peyretaillade12, Olivier Gonçalves12, Eric Dugat-Bony23, Fabrice Gravelat23, Anne Moné23, Corinne Biderre-Petit23, Delphine Boucher12, Julien Troquet4 and Pierre Peyret12*

Author Affiliations

1 Clermont Université, Université d'Auvergne, Laboratoire: Microorganismes Génome et Environnement, BP 10448, F-63000 CLERMONT-FERRAND, France

2 CNRS, UMR 6023, Laboratoire: Microorganismes Génome et Environnement, F-63173 AUBIERE, France

3 Clermont Université, Université Blaise Pascal, Laboratoire: Microorganismes Génome et Environnement, BP 10448, F-63000 CLERMONT-FERRAND, France

4 Biobasic Environnement, Biopôle Clermont-Limagne, 63360 Saint-Beauzire, France

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BMC Bioinformatics 2010, 11:478  doi:10.1186/1471-2105-11-478

Published: 23 September 2010

Abstract

Background

Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes.

Results

First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality) can be used to study a complex environment efficiently.

Conclusions

We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments, and it may also be used to study any group of genes. The Metabolic Design software is freely available from the authors and can be downloaded and modified under general public license.