Expertise
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
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Searched keyword : Escherichia coli
Related people (1)
Anđela DAVIDOVIĆ
I have a joint MSc degree in Mathematical Modelling from three European universities: University of L’Aquila (Italy), University of Nice-Sophia Antipolis (France) and Autonomous University of Barcelona (Spain). I also hold a PhD degree in Applied Mathematics and Scientific Computing from University of Bordeaux, France. I have done my PhD and one year of post-doc at INRIA Bordeaux Sud-Ouest, and partially at IHU-Liryc. During this time I studied how electrical signals propagate through the cardiac tissue under certain diseased conditions. My model of interest was the bidomain model, which is a system of partial differential equations that takes into account physiological properties of the cardiac cells and the spatial organization of the cardiac tissue. I worked on the mathematical multiscale analysis and numerical simulations of the problem to understand how structural changes of the tissue affect the propagation of the signal on the heart level. I collaborated with biologists and engineers of the IHU-Liryc to apply my model on a rat heart using high-resolution MRI data. For this I also worked on image analysis and image processing. I’ve joined the Institute Pasteur in February 2018 as a member of the HUB in Bioinformatics and Biostatistics. Currently I am working on stochastic mathematical modeling and inference for systems biology, gene expression, RNA transcription, etc.
KeywordsModelingScientific computingApplication of mathematics in sciencesGraphics and Image Processing
Organisms
BacteriaFungiInsect or arthropodEscherichia coliSaccharomyces cerevisiaeFly
Projects (2)
Related projects (11)
Genomic analyses of E. coli strains
Analyse de séquence 16S
Assemblage de novo d'une souche d'E. coli
Comparative analysis of the virulence plasmids of Shigella Spp. and entero-invasive Escherichia coli
Differentiation of Shigella species from Escherichia coli by MALDI-TOF mass spectrometry
Caractéristiques génomiques de souches d’Escherichia coli productrices de BLSE associées à un portage persistant après un voyage en zone tropicale
Genomic analysis of catheter-related Escherichia coli infection
Relationships between ESBL-producing Escherichia coli from food and healthy mothers in Phnom Penh, Cambodia
Extended spectrum β-lactamase (ESBL) genes encode resistance to penicillins and cephalosporins and can be horizontally transferred among Enterobacteriaceae. More than 60% of healthy humans living in southeast Asia are faecal carriers of ESBL-producing Enterobacteriaceae (ESBL-PE), compared to <10% in Western Europe, suggesting diverse exposure routes. In Cambodia, meat and fish consumption is high and food safety is poorly enforced. Thus, we hypothesized that meat and fish could be a source of exposure to ESBL-PE. From Sept-Nov 2016, we conducted a meat sampling study in Phnom Penh in collaboration with the BIRDY program (http://www.birdyprogram.org/), an ongoing study of neonatal health in low-income countries. We evaluated ESBL-PE contamination among pork, fish, and chicken from two markets and collected survey data from BIRDY mothers. We performed whole genome sequencing on 87 ESBL-producing E. coli recovered from meat and fish and from 91 BIRDY mothers who provided faecal swabs less than one year prior. Now, we will conduct a two-step exploratory analysis of these WGS data:
- First, we will estimate the pairwise evolutionary distance between E. coli isolates, in order to infer a phylogenetic tree. We will use this tree to investigate such epidemiological questions as “Do E. coli sequences from women who reported eating poultry 3+ times/week cluster more closely with E. coli recovered from poultry samples, compared to women who reported never eating poultry?” This phylogenetic tree may be re-constructed using a finer resolution, as needed.
- Second, we will annotate all E. coli genomes in order to identify genomic islands related to antibiotic resistance. We will subsequently use logistic regression to model associations between BIRDY mothers’ reported dietary patterns (i.e. exposure) and the presence or absence of these genomic islands among the ESBL-E. coli they were colonized with (i.e., outcome).
