Bio-informatique | EPFL Graph Search

La bioinformatique (ou bio-informatique), est un champ de recherche multidisciplinaire de la biotechnologie où travaillent de concert biologistes, médecins, informaticiens, mathématiciens, physiciens et bioinformaticiens, dans le but de résoudre un problème scientifique posé par la biologie. Plus généralement, la bio-informatique est l'application de la statistique et de l'informatique à la science biologique. Le spécialiste qui travaille à mi-chemin entre ces sciences et l'informatique est appelé bioinformaticien ou bionaute. Le terme bio-informatique peut également décrire, par abus de langage, toutes les applications informatiques résultant de ces recherches. L'utilisation du terme bio-informatique est documentée pour la première fois en 1970 dans une publication de Paulien Hogeweg et Ben Hesper (université d'Utrecht, Pays-Bas), en référence à l'étude des processus d'information dans les systèmes biotiques. Ce domaine s'étend de l'analyse du génome à la modélisation de l'évolut

Development of an interactive genome browser to visualize and analyse large scale genomic data

Lucas Sinclair

Genomic bioinformatics is a growing and developing field. Indeed, data analysis is becoming an integrative and essential part of any quantitative biological experiment as the technologies evolve and the wet lab methods used generate larger and larger quantities of data. Yet few standards have emerged and a plethora of analytical tools exist, none of which are established as a standard. The difficulties arise early on, even before processing any genomic data, as one first needs to visualize it. Several visualization methods exist, such as the UCSC genome browser, IGB or Argo, but none offer a satisfying interface or set of tools. Stemming from a pre-existing project at the bioinformatics and biostatistics core facility, this study presents a new solution to the multiple difficulties that at present beleaguer the field. A novel genome visualization tool is proposed where the user interface remains simple and incorporates a set of common statistical analysis functions. The software produced, entitled gFeatMiner, is capable of processing large scale genomic datasets for computing descriptive statistics and manipulate them in several ways. The program makes use of modern technologies and infrastructure paving the way for its development into an advanced data mining tool. In the second part of this study, a practical application is worked out. Examining the genes coding for ribosomal proteins in the model organism yeast (Saccharomyces cerevisiae) and using several available sets of data including multiple transcription factor binding profiles in vivo and in vitro, RNA polymerase activity and nucleosome enrichment, we attempt to better understand and reveal cellular mechanisms by clustering the numerous genes together using different criteria and machine learning strategies

2010

Role of RIP4 in lung adenocarcinoma differentiation

Jawahar Kopparam

Various studies have attributed NF-kB activation to promote KRAS mediated non-small cell lung cancer progression. In order to identify key genes regulating NF-kB activation and cell survival in lung adenocarcinoma, a synthetic lethal partner screen for KRAS was conducted in cell lines expressing mutant or wildtype KRAS. This screen identified an important role of Receptor-interacting serine/threonine protein kinase 4 (RIP4) in KRAS mediated oncogenesis. But altering RIP4 expression did not affect the viability of KRAS mutant cells, however a novel role of RIP4 in maintaining tumor differentiation was observed. Loss of epithelial differentiation and extracellular matrix remodeling are known to facilitate cancer progression and are associated with poor prognosis in patients with lung cancer. Bioinformatics analyses of human lung adenocarcinoma samples showed that poorly differentiated tumors express low levels of RIP4, whereas high levels are associated with better overall survival. Interleukin 6 (IL6) signaling is activated in lung adenocarcinoma expressing oncogenic KRAS and contributes to cancer invasiveness. Knockdown of RIP4 using shRNA in vitro enhanced activation of IL-6 signaling and also the ability of the cells to invade through collagen. In contrast, overexpression of RIP4 inhibited IL6-mediated Signal Transducer and activator of Transcription 3 (STAT3) activation, which abrogated IL6-dependent induction of lysyl oxidase, a collagen cross-linking enzyme. Tumor-specific Rip4 knockdown in an autochthonous mouse model of lung adenocarcinoma initiated by Kras(G12D) expression with loss of p53, progressed to a poorly differentiated state marked by an increase in Hmga2, reduced Ttf1 and enrichment of genes regulating extracellular matrix (ECM) remodeling and JAK-STAT signaling. Activated STAT3 can enhance NF-kB activation by interacting with NF-kB and promoting its nuclear retention. Tumors with RIP4 knockdown also exhibited enhanced STAT3- NF-kB interaction suggesting a cross talk between the two pathways. Tail vein injections of cells overexpressing RIP4 showed a reduced potential to invade and form tumors. Analysis of factors regulating RIP4 expression revealed that RIP4 is induced in a p53 dependent manner in response to chemotherapy. Altering the induced RIP4 levels in vitro had a modest effect on chemotherapy induced cell death. Our work has identified that loss of RIP4 enhances IL6 signaling in lung cancer cells, promoting the expression of ECM remodeling genes and cancer dedifferentiation.

EPFL2016

Evidence for a neuromuscular circuit involving hypothalamic interleukin-6 in the control of skeletal muscle metabolism

Ludger Jan Elzuë Goeminne, Vera Monica Lemos Da Silva, Barbara Moreira Crisol, Eduardo Rochete Ropelle

Hypothalamic interleukin-6 (IL6) exerts a broad metabolic control. Here, we demonstrated that IL6 activates the ERK1/2 pathway in the ventromedial hypothalamus (VMH), stimulating AMPK/ACC signaling and fatty acid oxidation in mouse skeletal muscle. Bioinformatics analysis revealed that the hypothalamic IL6/ERK1/2 axis is closely associated with fatty acid oxidation– and mitochondrial-related genes in the skeletal muscle of isogenic BXD mouse strains and humans. We showed that the hypothalamic IL6/ERK1/2 pathway requires the α2-adrenergic pathway to modify fatty acid skeletal muscle metabolism. To address the physiological relevance of these findings, we demonstrated that this neuromuscular circuit is required to underpin AMPK/ACC signaling activation and fatty acid oxidation after exercise. Last, the selective down-regulation of IL6 receptor in VMH abolished the effects of exercise to sustain AMPK and ACC phosphorylation and fatty acid oxidation in the muscle after exercise. Together, these data demonstrated that the IL6/ERK axis in VMH controls fatty acid metabolism in the skeletal muscle.

2022

Role of RIP4 in lung adenocarcinoma differentiation

Jawahar Kopparam

EPFL2016