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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain <it>Sphingomonas paucimobilis </it>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.</p> <p>Conclusions</p> <p>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.</p

A comparison of algorithms for a complete backtranslation of oligopeptides

International audienceIn the context of new metabolic pathways discovery, a full backtranslation of oligopeptides can be a promising approach. When studying complex environments where the composing microorganisms are unknown it is also preferable to have all the complete nucleic sequences corresponding to an enzyme of interest. In this paper, we revisit the existing bioinformatics applications, which bring partial reverse translation solutions, and we compare two algorithms based on oligopeptide degeneracy able to efficiently compute a complete backtranslation of oligopeptides. Such algorithms are precious for the discovery of new organisms and we show their performances on simulated and real biological data sets