21 research outputs found

    Finding undetected protein associations in cell signaling by belief propagation

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    External information propagates in the cell mainly through signaling cascades and transcriptional activation, allowing it to react to a wide spectrum of environmental changes. High throughput experiments identify numerous molecular components of such cascades that may, however, interact through unknown partners. Some of them may be detected using data coming from the integration of a protein-protein interaction network and mRNA expression profiles. This inference problem can be mapped onto the problem of finding appropriate optimal connected subgraphs of a network defined by these datasets. The optimization procedure turns out to be computationally intractable in general. Here we present a new distributed algorithm for this task, inspired from statistical physics, and apply this scheme to alpha factor and drug perturbations data in yeast. We identify the role of the COS8 protein, a member of a gene family of previously unknown function, and validate the results by genetic experiments. The algorithm we present is specially suited for very large datasets, can run in parallel, and can be adapted to other problems in systems biology. On renowned benchmarks it outperforms other algorithms in the field.Comment: 6 pages, 3 figures, 1 table, Supporting Informatio

    Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA – a Bayesian approach

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    <p>Abstract</p> <p>Background</p> <p>Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge.</p> <p>Results</p> <p>A computing tool (ArrayLeaRNA) has been developed for gene expression analysis. It implements a Bayesian approach which is based on the Gumbel distribution and uses printed genomic DNA control features for normalization and for estimation of the parameters of the Bayesian model and prior knowledge from predicted operon structure. The method is compared with two other approaches: the classical LOWESS normalization followed by a two fold cut-off criterion and the OpWise method (Price, et al. 2006. BMC Bioinformatics. 7, 19), a published Bayesian approach also using predicted operon structure. The three methods were compared on experimental datasets with prior knowledge of gene expression. With ArrayLeaRNA, data normalization is carried out according to the genomic features which reflect the results of equally transcribed genes; also the statistical significance of the difference in expression is based on the variability of the equally transcribed genes. The operon information helps the classification of genes with low confidence measurements.</p> <p>ArrayLeaRNA is implemented in Visual Basic and freely available as an Excel add-in at <url>http://www.ifr.ac.uk/safety/ArrayLeaRNA/</url></p> <p>Conclusion</p> <p>We have introduced a novel Bayesian model and demonstrated that it is a robust method for analysing microarray expression profiles. ArrayLeaRNA showed a considerable improvement in data normalization, in the estimation of the experimental variability intrinsic to each hybridization and in the establishment of a clear boundary between non-changing and differentially expressed genes. The method is applicable to data derived from hybridizations of labelled cDNA samples as well as from hybridizations of labelled cDNA with genomic DNA and can be used for the analysis of datasets where differentially regulated genes predominate.</p

    Role of the Single-Stranded DNA–Binding Protein SsbB in Pneumococcal Transformation: Maintenance of a Reservoir for Genetic Plasticity

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    Bacteria encode a single-stranded DNA (ssDNA) binding protein (SSB) crucial for genome maintenance. In Bacillus subtilis and Streptococcus pneumoniae, an alternative SSB, SsbB, is expressed uniquely during competence for genetic transformation, but its precise role has been disappointingly obscure. Here, we report our investigations involving comparison of a null mutant (ssbB−) and a C-ter truncation (ssbBΔ7) of SsbB of S. pneumoniae, the latter constructed because SSBs' acidic tail has emerged as a key site for interactions with partner proteins. We provide evidence that SsbB directly protects internalized ssDNA. We show that SsbB is highly abundant, potentially allowing the binding of ∌1.15 Mb ssDNA (half a genome equivalent); that it participates in the processing of ssDNA into recombinants; and that, at high DNA concentration, it is of crucial importance for chromosomal transformation whilst antagonizing plasmid transformation. While the latter observation explains a long-standing observation that plasmid transformation is very inefficient in S. pneumoniae (compared to chromosomal transformation), the former supports our previous suggestion that SsbB creates a reservoir of ssDNA, allowing successive recombination cycles. SsbBΔ7 fulfils the reservoir function, suggesting that SsbB C-ter is not necessary for processing protein(s) to access stored ssDNA. We propose that the evolutionary raison d'ĂȘtre of SsbB and its abundance is maintenance of this reservoir, which contributes to the genetic plasticity of S. pneumoniae by increasing the likelihood of multiple transformation events in the same cell

    Silicon-based microcantilevers for multiple biological sample deposition

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    International audienceArrays of silicon-based microcantilevers with passivated aluminum electrodes properly designed have been used to generate microarrays by depositing microspots of biological samples using a direct contact deposition technique. Using this approach, with a single loading, arrays of more than a hundred spots, from the femtoliter to the picoliter range, containing fluorescent-labelled oligonucleotides (15 mers) and proteins were directly patterned on a glass slide. The aim here was to check whether our system could be used for depositing various biological samples with the same cantilevers without the need to replace them for each sample. The strategy was to adapt the conventional cleaning and drying procedures used with a commercial DNA or protein microspotter. All the results presented demonstrate that our system perfectly matches the need for generating high-density DNA and protein chips in terms of size, density and the capacity of depositing different samples without cross-contamination
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