Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Listeria
Related people (1)
CV Senior Bioinformatician August 2015 – Present : Institut Pasteur, Paris PostDoc fellow 2011 – 2015 : Pascale Cossart’s laboratory, Unité des Interactions Bactéries-Cellules, Institut Pasteur, Paris Phd fellow 2007 – 2010 : Institut des Hautes Etudes Scientifiques, ann Ecole Normale Supérieure, Paris Magister of Science, Theoretical Physics 2003 – 2007 : Dynamical systems and statistics of complex matter, Université Paris 7 and Université Paris 6
BiophysicsMachine learningModelingProteomicsBiostatisticsDatabases and ontologiesHost-pathogen interactions
- Analysis of DNA methylation in the presence and absence of antibiotics in wt and mutant V. cholerae(Baharoglu ZEYNEP - Bacterial Genome Plasticity) - Closed
- Finding and Predicting CRISPR-Cas9 Efficiency(Jerome WONG NG - Synthetic Biology) - Closed
- Characterization of a Salmonella mutant carrying a single amino-acid substitution in the stress sigma factor RpoS(Françoise NOREL - Biochemistry of Macromolecular Interactions) - Closed
Related projects (10)
In the context of the swiss consortion InfectX (www.infectx.ch), we performed siRNA and drug screens to investigate the invasion of host cells by the bacterial pathogen Listeria monocytogenes. As a primary readout for infection we detected by fluorescence microscopy the presence of the bacterially-secreted protein InlC, which accumulates in the cytoplasm of infected cells (Kühbacher et al. 2013). A first manuscript concerning the analysis of a kinome-wide siRNA library and a drug library has been published recently (Rämö et al. 2014) and the analysis of a genome-wide siRNA screen has been submitted for publication (Kühbacher et al. In Revision), in which major signaling pathways subverted by L. monocytogenes are identified. However, besides the presence of InlC, many other features have been measured in infected cells including InlC intensity, bacterial distribution in host cells, actin morphology and distribution, cellular replication state, cellular context of infected cells, etc. We intend to analyze the full set of measured parameters in order to identify global signaling cascades subverted by L. monocytogenes for infection or used by the cell to control bacterial proliferation.
Listeria monocytogenes is a gram positive facultative intracellular foodborne bacterium responsible for serious clinical manifestations including febrile gastroenteritis, meningitis, encephalitis and maternofetal infections in humans and livestock. Intestinal microbiota plays fundamental roles in the resistance to foodborne infections. Intestinal microbiota commensals protect against pathogens by direct antimicrobial activity through production of bacteriocins, competition for nutrients or binding sites, stimulation of epithelial barrier function, immunomodulation and inhibition of virulence factors expression in gastrointestinal pathogens. On the other side, pathogens have developed tools to avoid commensal-mediated resistance to colonization. Thus, the interplay between gut commensals and L. monocytogenes is critical for the infection and the development of the disease. We have identified a Listeria monocytogenes toxin which modifies the intestinal host microbiota and allows Listeria survival in the intestinal content to later invade the intestine and deeper organs.
Analysis of host epitranscriptional modifications upon colonisation with commensals and infection by bacterial pathogens
The colonisation of the murine gut by commensal bacteria has been shown to profoundly influence the host physiology. We would like to investigate if these effects are in part mediated by changes in epitranscriptomics, i.e. mRNA modifications influencing the stability and degradation of mRNA (Dominissini et al. Cell 2012, Meyer et al. Nature 2012). To this end, we aim to investigate the levels of the m6A modification of mRNA and differentially methylated targets in organs derived from mice with a conventional flora, germ-free mice and gnotobiotic mice colonized with a specific commensal, Akkermansia muciniphila, known for benificial effects on host metabolism (Everard et al. PNAS 2012, Shin et al. Gut 2014). Since also pathogenic bacteria have been shown to influence the host cells on many levels, including the dysregulation of transcription in the host, we would like to extend our study of host mRNA methylation patterns to mice that have been intra-gastrically infected with Listeria monocytogenes in the presence or absence of commensal bacteria.
Over the past three decades Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields including virulence-factor regulation, cell biology, and bacterial pathophysiology. More recently, the number of Listeria “omics” data produced has increased exponentially, not only in term of number, but also in term of heterogeneity of data. There are now more than 40 published Listeria genomes, around 400 different transcriptomics data and 10 proteomics studies available. The capacity to analyze these data through a systems biology approach and generate tools for biologists to analyze these data themselves is a challenge for bioinformaticians. To tackle these challenges we are developing a web-based platform named Listeriomics which integrates different type of tools for “omics” data manipulation, the two most important being: 1) a genome viewer for displaying gene expression array, tiling array, and RNASeq data along with proteomics and genomics data. 2) An expression atlas, which is a query based tool which connects every genomics elements (genes, smallRNAs, antisenseRNAs) to the most relevant “omics” data. Our platform integrates already all genomics, and transcriptomics data ever published on Listeria and will thus allow biologists to analyze dynamically all these data, and bioinformaticians to have a central database for network analysis. Finally, it has been used already several times in our laboratory for different types of studies, including transcriptomics analysis in different biological conditions, and whole genome analysis of Listeria proteins N-termini. This project is funded by an ANR Investissement d'avenir: BACNET 10-BINF-02-01
In the context of the Swiss consortium InfectX (www.infectx.ch), Javier PIZARRO-CERDA previously performed siRNA, microRNA, drug screens and proteomic analyses to investigate signaling pathways modulating invasion of host cells by the bacterial pathogen Listeria monocytogenes. In a first consortium study, based on results from drug and siRNA screens targeting the human kinome, we identified major kinases which up- or down-regulate cell invasion by L. monocytogenes and by 7 additional bacterial and viral pathogens (Rämö et al. 2014). Subsequently, a siRNA genome-wide screen allowed us to revisit and redefine the role of cytoskeletal complexes required for L. monocytogenes cellular invasion and actin-based motility (Kühbacher et al. 2015). Applying a proteomic ‘surfaceome’ analysis, we also revealed that late endosomal compartments are recruited to L. monocytogenes infection foci to promote invasion (Kühbacher et al. Submitted). More recently, we have started the analysis of a microRNA screen which highlights novel gene clusters associated to regulation of phosphoinositide metabolism during L. monocytogenes cell entry (Kühbacher et al. Unpublished Results). These different projects have generated vast amounts of data that have been until now only independently analyzed. However, this information can now be exploited from a systems biology perspective to identify hidden connections between relevant signaling cascades and gene networks which may highlight novel cellular functions exploited by pathogens in the context of infection. The team of Benno SCHWIKOWSKI will perform two types of analysis on the data generated by Javier PIZARRO-CERDA. In both cases, p-values will be aggregated across gene sets using suitable statistical approaches. We will then
- Pathway-based analysis. This type of analysis considers genes in sets that have been recognized to operate together to perform certain biological functions (e.g.,
Listeria monocytogenes is a gram-positive bacterium responsible for the food-borne disease listeriosis. This pathogen can invade and replicate in the cytoplasm of both macrophages and non-professional phagocytes. In order to better characterize the host response to Listeria, we are using microarrays to identify genes and cytokines up or downregulated during infection.
One of the best models for the study of bacteria-host interactions is Listeria monocytogenes. One interesting facet of this bacterium is its ability to modify host chromatin. Recently, we have shown that Listeria causes a drastic deacetylation of histone H3 on lysine 18 (H3K18dc). Interestingly, to impose this modification, Listeria highjacks previously undescribed host machinery: the host protein sirtuin 2 (SIRT2) is relocalized to the nucleus where it causes genes repression during infection. SIRT2 is a NAD-dependent deacetylase that has been implicated in the regulation of complex processes such as aging and cancer. This protein had been mainly studied in the cytoplasm, and although SIRT2 had been show to shuttle between the cytoplasm and the nucleus, the mechanism and its biological role remained unknown. In order to further characterize the role of SIRT2 during infection and identify all the genes at which it is recruited, we are performing ChIP-seq analysis. These studies are expected to bring new insights into the function and regulation of SIRT2 by characterizing this new phosphorylation site.
We are analyzing a Listeria protein secreted in the supernatant. From cells transfected with this protein, after crosslinking, we have isolated RNA and found the protein in the RNA fraction. In addition, the protein binds several splicing factors in RNA dependent manner. Furthemore, the protein localizes to the nucleus. In this project, we have isolated the protein from the supernatant and from bacterial extract after growth in BHI. We have extracted the RNA from the supernatant fraction containing the protein and from the bacterial extract containing the protein. We want to alalyze the RNA in these different fractions.
- The Institut Pasteur genomic taxonomy database of microbial strains (“Pasteur MLST”) is a free, publicly-accessible resource that hosts nucleotide sequence-based definitions of microbial strains, al
The CRBIP, Centre de Ressources Biologiques de l’Institut Pasteur, is a structure created in 2001 that encompasses the Pasteurian culture collections: the CIP (bacteria collection), the PCC (cyanobact