Laurent Tichit

A Comprehensive Analysis of Gene Expression Changes Provoked by Bacterial and Fungal Infection in C. elegans

While Caenorhabditis elegans specifically responds to infection by the up-regulation of certain genes, distinct pathogens trigger the expression of a common set of genes. We applied new methods to conduct a comprehensive and comparative study of the transcriptional response of C. elegans to bacterial and fungal infection. Using tiling arrays and/or RNA-sequencing, we have characterized the genome-wide transcriptional changes that underlie the hosts response to infection by three bacterial (Serratia marcescens, Enterococcus faecalis and otorhabdus luminescens) and two fungal pathogens (Drechmeria coniospora and Harposporium sp.). We developed a flexible tool, the WormBase Converter (available at http://wormbasemanager.sourceforge.net/), to allow cross-study comparisons. The new data sets provided more extensive lists of differentially regulated genes than previous studies. Annotation analysis confirmed that genes commonly up-regulated by bacterial infections are related to stress responses. We found substantial overlaps between the genes regulated upon intestinal infection by the bacterial pathogens and Harposporium, and between those regulated by Harposporium and D. coniospora, which infects the epidermis. Among the fungus-regulated genes, there was a significant bias towards genes that are evolving rapidly and potentially encode small proteins. The results obtained using new methods reveal that the response to infection in C. elegans is determined by the nature of the pathogen, the site of infection and the physiological imbalance provoked by infection. They form the basis for future functional dissection of innate immune signaling. Finally, we also propose alternative methods to identify differentially regulated genes that take into account the greater variability in lowly expressed genes.

Clust&See: A Cytoscape plugin for the identification, visualization and manipulation of network clusters ,

BACKGROUND AND SCOPE Large networks, such as protein interaction networks, are extremely difficult to analyze as a whole. We developed Clust&See, a Cytoscape plugin dedicated to the identification, visualization and analysis of clusters extracted from such networks. IMPLEMENTATION AND PERFORMANCE Clust&See provides the ability to apply three different, recently developed graph clustering algorithms to networks and to visualize: (i) the obtained partition as a quotient graph in which nodes correspond to clusters and (ii) the obtained clusters as their corresponding subnetworks. Importantly, tools for investigating the relationships between clusters and vertices as well as their organization within the whole graph are supplied.

A quantitative genome-wide RNAi screen in C. elegans for antifungal innate immunity genes

BackgroundCaenorhabditis elegans has emerged over the last decade as a useful model for the study of innate immunity. Its infection with the pathogenic fungus Drechmeria coniospora leads to the rapid up-regulation in the epidermis of genes encoding antimicrobial peptides. The molecular basis of antimicrobial peptide gene regulation has been previously characterized through forward genetic screens. Reverse genetics, based on RNAi, provide a complementary approach to dissect the worm’s immune defenses.ResultsWe report here the full results of a quantitative whole-genome RNAi screen in C. elegans for genes involved in regulating antimicrobial peptide gene expression. The results will be a valuable resource for those contemplating similar RNAi-based screens and also reveal the limitations of such an approach. We present several strategies, including a comprehensive class clustering method, to overcome these limitations and which allowed us to characterize the different steps of the interaction between C. elegans and the fungus D. coniospora, leading to a complete description of the MAPK pathway central to innate immunity in C. elegans. The results further revealed a cross-tissue signaling, triggered by mitochondrial dysfunction in the intestine, that suppresses antimicrobial peptide gene expression in the nematode epidermis.ConclusionsOverall, our results provide an unprecedented system’s level insight into the regulation of C. elegans innate immunity. They represent a significant contribution to our understanding of host defenses and will lead to a better comprehension of the function and evolution of animal innate immunity.

Clone mapper: an online suite of tools for RNAi experiments in Caenorhabditis elegans.

RNA interference (RNAi), mediated by the introduction of a specific double-stranded RNA, is a powerful method to investigate gene function. It is widely used in the Caenorhabditis elegans research community. An expanding number of laboratories conduct genome-wide RNAi screens, using standard libraries of bacterial clones each designed to produce a specific double-stranded RNA. Proper interpretation of results from RNAi experiments requires a series of analytical steps, from the verification of the identity of bacterial clones, to the identification of the clones’ potential targets. Despite the popularity of the technique, no user-friendly set of tools allowing these steps to be carried out accurately, automatically, and at a large scale, is currently available. We report here the design and production of Clone Mapper, an online suite of tools specifically adapted to the analysis pipeline typical for RNAi experiments with C. elegans. We show that Clone Mapper overcomes the limitations of existing techniques and provide examples illustrating its potential for the identification of biologically relevant genes. The Clone Mapper tools are freely available via http://www.ciml.univ-mrs.fr/EWBANK_jonathan/software.html.

Designing optimal- and fast-on-average pattern matching algorithms

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ICeE an interface for C. elegans experiments

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Random walk with restart on multiplex and heterogeneous biological networks

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Dynamical modeling and analysis of large cellular regulatory networks

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Dynamical modeling and analysis of large cellular regulatory networks.: D. Bérenguier, C. Chaouiya, P. T. Monteiro, A. Naldi, E. Remy, D. Thieffry and L. Tichit

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Logical modelling of cellular decision processes with GINsim

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