A TARGETED CURRICULUM DEVELOPED BY THE COMPUTATIONAL BIOLOGY DEPARTMENT
In accordance with a request in 2016 from the former General Board of Directors, the Computational Biology Department has developed this training program dedicated to Institut Pasteur PhD students. Each and every student at the institute must attend at least 50 hours of training. At the minimum, he or she is required to validate the statistical modules (which, depending on their background, some students may skip), and possibly choose additional modules according to his or her background and field of research.
A CORE FOUNDATION AND THE OPTION TO SPECIALIZE
This 50-hour training program required for all Institut Pasteur PhD students begins with a group of common core courses including a knowledge base in reproducible research, R Programming and Statistics. Each student then chooses a track of additional modules— Bioinformatics or Image Analysis—according to their background and field of research. Students already proficient in R programming and statistics can skip certain modules or the entire track.
This 6h course is mandatory for all PhD students. They will learn how to get help and assistance from the Department of Computational Biology and from the Hubs for questions in programming, experimental design, data analysis and image analysis. They will attend three short lectures in programming and reproducible resaerch. Finally, they will have the opportunity to assess their level in R programming and statistics and to register to the modules of their choice in the R programming and statistics, Bioinformatics and Image analysis tracks.
Program of the mandatory common core module
Other modules
The figure below shows all the available modules. To attend these lectures you need to bring your own laptop. No special configuration is required. Just avoid to come with your grandma’s machine.
To attend these lectures you need to bring your own laptop. No special configuration is required. Just avoid to come with your grandma’s machine.
Description of the Bioinformatics program
A detailed description of all modules can be found here.
To attend these lectures you need to bring your own laptop. No special configuration is required. Just avoid to come with your grandma’s machine.
SUPPORT
This PhD program is supported by the INCEPTION project.
There is a wide gap between the generation of large-scale biological data sets and more-detailed, structural and mechanistic studies. However, recent work that explicitly combine data from systems and structural biological approaches is having a profound effect on our ability to predict how mutations and small molecules affect atomic-level mechanisms, disrupt systems-level networks and ultimately lead to changes in organismal fitness. Our group aims to create a stronger bridge between these areas primarily using three types of data: genetic interactions, protein-protein interactions and post-translational modifications. Protein structural information helps to prioritize and functionally understand these large-scale datasets; conversely global, unbiasedly collected datasets helps inform the more mechanistic studies. Our efforts in this respect have been focused on three disease areas: cancer, infectious diseases and neuropsychiatric disorders. Our work has found remarkable similarities between these and other disease areas which are leading to novel therapeutic strategies.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Proteins are the workhorses of the cell and, over billions of years,
they have evolved an amazing plethora of extremely diverse and versatile
structures with equally diverse functions. Therefore, their evolution
echoes the evolution of all forms of life. Evolutionary emergence of
new proteins and transitions between existing ones are widely believed
to be rare or even impossible.
However, recent advances in comparative genomics have repeatedly called
some 10%-30% of all genes without any detectable similarity to existing
proteins. Even after careful scrutiny, some of those “orphan” genes
contain protein coding reading frames with detectable transcription and
translation. Thus some proteins seem to have emerged from previously
non-coding ‘dark genomic matter’. These ‘de novo’ proteins tend to be
disordered, fast evolving, weakly expressed but also rapidly assuming
novel and physiologically important functions. I will review mechanisms
by which ‘de novo’ proteins might be created, under which circumstances
they may become fixed and why they are elusive. I will present a couple
of studies which mostly focus on metazoan genomes.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Real-time whole-genome sequencing for surveillance of Listeria monocytogenes, France.
Main speaker : , from Date : 19/07/2017 at
Location : ,Institut Pasteur, Paris
During 2015-2016, we evaluated the performance of whole-genome sequencing (WGS) as a routine typing tool. Its added value for microbiological and epidemiologic surveillance of listeriosis was compared with that for pulsed-field gel electrophoresis (PFGE), the current standard method. A total of 2,743 Listeria monocytogenes isolates collected as part of routine surveillance were characterized in parallel by PFGE and core genome multilocus sequence typing (cgMLST) extracted from WGS. We investigated PFGE and cgMLST clusters containing human isolates. Discrimination of isolates was significantly higher by cgMLST than by PFGE (p<0.001). cgMLST discriminated unrelated isolates that shared identical PFGE profiles and phylogenetically closely related isolates with distinct PFGE profiles. This procedure also refined epidemiologic investigations to include only phylogenetically closely related isolates, improved source identification, and facilitated epidemiologic investigations, enabling identification of more outbreaks at earlier stages. WGS-based typing should replace PFGE as the primary typing method for L. monocytogenes.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Proteome remodelling by the stress sigma factor RpoS/σS in Salmonella: identification of small proteins and evidence for post-transcriptional regulation
Main speaker : , from Date : 01/05/2016 at
Location : ,Institut Pasteur, Paris
The RpoS/σS sigma subunit of RNA polymerase is the master regulator of the general stress response in many Gram-negative bacteria. Extensive studies have been conducted on σS-regulated gene expression at the transcriptional level. In contrast, very limited information regarding the impact of σS on global protein production is available. In this study, we used a mass spectrometry-based proteomics approach to explore the wide σS-dependent proteome of the human pathogen Salmonella enterica serovar Typhimurium. Our present goals were twofold: (1) to survey the protein changes associated with the ΔrpoS mutation and (2) to assess the coding capacity of σS-dependent small RNAs. Our proteomics data, and complementary assays, unravelled the large impact of σS on the Salmonella proteome, and validated expression and σS regulation of twenty uncharacterized small proteins of 27 to 96 amino acids. Furthermore, a large number of genes regulated at the protein level only were identified, suggesting that post-transcriptional regulation is an important component of the σS response. Novel aspects of σS in the control of important catabolic pathways such as myo-inositol, L-fucose, propanediol, and ethanolamine were illuminated by this work, providing new insights into the physiological remodelling involved in bacterial adaptation to a non-actively growing state.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Listeriomics: an Interactive Web Platform for Systems Biology of Listeria.
Main speaker : , from Date : 13/03/2017 at
Location : ,Institut Pasteur, Paris
As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes
Main speaker : , from Date : 11/10/2016 at
Location : ,Institut Pasteur, Paris
Listeria monocytogenes (Lm) is a major human foodborne pathogen. Numerous Lm outbreaks have been reported worldwide and associated with a high case fatality rate, reinforcing the need for strongly coordinated surveillance and outbreak control. We developed a universally applicable genome-wide strain genotyping approach and investigated the population diversity of Lm using 1,696 isolates from diverse sources and geographical locations. We define, with unprecedented precision, the population structure of Lm, demonstrate the occurrence of international circulation of strains and reveal the extent of heterogeneity in virulence and stress resistance genomic features among clinical and food isolates. Using historical isolates, we show that the evolutionary rate of Lm from lineage I and lineage II is low (∼2.5 × 10−7 substitutions per site per year, as inferred from the core genome) and that major sublineages (corresponding to so-called ‘epidemic clones’) are estimated to be at least 50–150 years old. This work demonstrates the urgent need to monitor Lm strains at the global level and provides the unified approach needed for global harmonization of Lm genome-based typing and population biology.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Web-based tools to analyse and interpret high-throughput biological data
Main speakers : Dr. Hedi Peterson and Dr. Priit Adler, from University of Tartu, ELIXIR Estonia Date : 18/10/2016 at 02:00 pm
Location : Bime meeting room 28-01-01A – BIME (28) ,Institut Pasteur, Paris
Overview. In this course we introduce web-based tools to analyse and interpret high-throughput biological data. In the main focus will be g:Profiler – a toolset for finding most significant functional groups for a given gene or protein list; MEM – a query engine allowing to mine hundreds of public gene expression datasets to find most co-expressed genes based on a query gene; and ClustVis – a web tool for visualizing clustering of multivariate data using Principal Component Analysis plot and heatmap.
Audience. Biologists and bioinformaticians who are dealing with high-throughput gene expression data or other high-throughput data and would like to learn state-of-the-art methods for mining and analysing such data.
Learning objectives.
g:Profiler – learn how to perform gene set enrichments analysis and find what are the most significant functional groups in your gene or protein list (for example interesting genes/proteins from Q-RT-PCR or RNA-seq experiment results). To learn how to convert gene and protein IDs from one namespace into another or find corresponding gene/protein IDs from another organism.
MEM – learn to perform and interpret MEM co-expression queries. Given a query gene, MEM performs co-expression analysis across hundreds of public datasets and returns ordered list of globally similar genes. We’ll learn how MEM can be used to infer potential function for a gene based on other genes that are globally similar. For a gene pair we’ll learn how to identify the datasets and conditions where they behave similarly and where they do not.
ClustVis – learn how to make exploratory data analysis plots using ClustVis web tool. How to prepare a dataset for uploading the data or search among publicly available datasets. We learn how to filter a chosen dataset using ClustVis and how to choose pre-processing options. We will learn how PCA plot and heatmap can be modified and how to interpret and export the results.
Prerequisites.
Common understanding of high-throughput technologies does help to follow the lectures. Access to web browser is required.
Please bring a laptop, to be able to use the tools. Participants are very welcome to bring their own gene/gene list of interest, to analyse them during the session.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
Phylogenomic analysis supports the ancestral presence of LPS-outer membranes in the Firmicutes.
Main speaker : , from Date : 01/09/2016 at
Location : ,Institut Pasteur, Paris
One of the major unanswered questions in evolutionary biology is when and how the transition between diderm (two membranes) and monoderm (one membrane) cell envelopes occurred in Bacteria. The Negativicutes and the Halanaerobiales belong to the classically monoderm Firmicutes, but possess outer membranes with lipopolysaccharide (LPS-OM). Here, we show that they form two phylogenetically distinct lineages, each close to different monoderm relatives. In contrast, their core LPS biosynthesis enzymes were inherited vertically, as in the majority of bacterial phyla. Finally, annotation of key OM systems in the Halanaerobiales and the Negativicutes shows a puzzling combination of monoderm and diderm features. Together, these results support the hypothesis that the LPS-OMs of Negativicutes and Halanaerobiales are remnants of an ancient diderm cell envelope that was present in the ancestor of the Firmicutes, and that the monoderm phenotype in this phylum is a derived character that arose multiple times independently through OM loss.
Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting
