Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: Application Domains

Application fields in biology

In terms of transfer and societal impact, we consider that our role is to develop fruitful collaborations with laboratories of biology in order to consolidate their studies by a smart use of our tools and prototypes and to generate new biological hypotheses to be tested experimentally.

Marine Biology: seaweed enzymes and metabolism & sea-urchin cell-cycle. Our main field of study is marine biology, as it is a transversal field covering challenges in integrative biology, dynamical systems and sequence analysis. Our methods based on combinatorial optimization for the reconstruction of genome-scale metabolic networks and on classification of enzyme families based on local and partial alignments allowed the seaweed metabolism E. Siliculosus to be deciphered [62], [53]. The study of the HAD superfamily of proteins thanks to partial local alignments, produced by Protomata tools, allows sub-families to be deciphered and classified, and the metabolic map reconstructed with Meneco enabled the reannotation of 56 genes within the E. siliculosus genome. These approaches also shed light on evolution of metabolic processes. As a further study, we reconstructed the metabolic network of a symbiot bacterium Ca. P. ectocarpi [55] and used this reconstructed network to decipher interactions within the algal-bacteria holobiont, revealing several candidates metabolic pathways for algal-bacterial interactions. Similarily, our analyses suggest that the bacterium Ca. P. ectocarpi is able to provide both β-alanine and vitamin B5 to the seaweed via the phosphopantothenate biosynthesis pathway [63].

Micro-biology: elucidating the functioning of extremophile consortiums of bacteria. In this application field, our main issue is the understanding of bacteria living in extreme environments, mainly in collaboration with the group of bioinformatics at Universidad de Chile (co-funded by the Center of Mathematical Modeling, the Center of Regulation Genomics and Inria-Chile). In order to elucidate the main characteristics of these bacteria, our integrative methods were developed to identify the main groups of regulators for their specific response in their living environment. The integrative biology tools Meneco, Lombarde and Shogen have been designed in this context. In particular, genome-scale metabolic network been recently reconstructed and studied with the Meneco and Shogen approaches, especially on bacteria involved in biomining processes [48] and in Salmon pathogenicity [52].

Agriculture and environmental sciences: upstream controllers of cow, pork and pea-aphid metabolism and regulation. In this application field, our goal is to propose methods to identify regulators of very complex phenotypes related to environmental issues. Our work on the identification of upstream regulators within large-scale knowledge databases (prototype KeyRegulatorFinder) [47] and on semantic-based analysis of metabolic networks [45] was very valuable for interpreting differences of gene expression in pork meat [60] and figure out the main gene-regulators of the response of porks to several diets [59]. In addition, constraints-based programming also allows us to decipher regulators of reproduction for the pea aphid, an insect that is a pest on plants. In terms of biological output of the network studies on the pea aphid microRNAs, we have identified one new microRNA (apmir-3019, not present in any known species other than the pea aphid) who has more than 900 putative mRNA targets.

Health: deciphering pathways involved in the TGF-β signalling network. TGF-β is a multifunctional cytokine that regulates mammalian development, differentiation, and homeostasis with both benefical anti-tumor effect [49] and pro-tumor effect [61]. Deciphering protumor versus antitumor signaling requires to take into account a system-wide view and develop predictive models for therapeutic benefit. For that purpose we developed Cadbiom and identified gene networks associated with innate immune response to viral infection that combine TGF-β and interleukine signaling pathways [43], [51].