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November 15, 2019

Nonribosomal peptide synthetases (NRPSs) are microbial megaenzymes that make a wide variety of small-molecule products, including many that are clinically used as antitumors, antibiotics, or immunosuppressants. Peptide synthesis proceeds with assembly-line logic, where each station on the NRPS assembly line is a multidomain unit called a module. While the function of single modules is well studied, much less is known how they work together. Researchers from the Schmeing lab at McGill University have resolved several dimodular NRPS structures, which show coordinated interactions between modules, and large conformational changes between catalytically relevant states. Martin Weigt from the “Statstical Genomics and Biological Physics” team has performed complementary coevolutionary analyses using the direct coupling analysis (DCA), which confirm the biological relevance and evolutionary conservation of the observed inter-modular interactions. DCA analysis has also allowed to suggest mutations in a module-swapped chimeric NRPS protein, which significantly increased the activity of the protein, a result of direct relevance toward the longstanding goal of NRPS bioengineering for production of new-to-nature bioactive small molecules.

Link to article in Science

September 23, 2019

GEMME is a fast, scalable and simple method to predict mutational landscapes from natural sequences. It demonstrates how deleterious effects of a protein mutation are identified by looking at the closest known sequence accepting the mutation in the evolutionary tree of sequences and at its epistatic changes.  The article just appeared in Molecular Biology and Evolution.

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July 24, 2019

We propose the concept of "interacting region" and the dynJET2 method toward deciphering the complexity underlying protein surface usage and deformability. Interacting regions account for the multiple usage of a protein's surface residues by several partners and for the variability of protein interfaces coming from molecular flexibility. dynJET2 predicts interacting patches by crossing evolutionary, physico‐chemical and geometrical properties of the protein surface with information coming from complete cross‐docking (CC‐D) simulations. 

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June 10, 2019

The Team of Diatom Functional Genomics (R. Annunziata, A. Ritter, A.E. Fortunato, A. Manzotti, S. Cheminant Navarro, J.P. Bouly and A. Falciatore), in collaboration with the team of Biology of Genomes (Nicolas Agier) and Marco Cosentino Lagomarsino at the LCQB characterized the circadian rhythms of the marine diatom Phaeodactylum tricornutum and identified the bHLH-PAS protein RITMO1 as the first known regulator of these rhythms in these algae. This study, published on Proceedings of the National Academy of Sciences (PNAS) adds new elements to our understanding of diatom biology and offers new perspectives to elucidate timekeeping mechanisms in marine algae.

December 18, 2018

Phenotypic diversity can arise from changes in the gene content of the genomes but also from modifications in the regulation of gene expression. The "genetic networks" team compared gene expression in 8 yeast species to find "regulatory outliers", i.e. conserved genes with special expression profiles compared to their orthologues. The combination of this approach with other functional genomics data (transcriptomics analyses and chromatine immunoprecipitation followed by deep sequencing) led us to identify two genes which are involved in the survival of the human pathogen Candida glabrata upon iron starvation conditions. Iron starvation being a key challenge for C. glabrata survival in blood, this discovery may help us to better understand the invasive strategy of this emerging pathogen.

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December 6, 2018

The latest publication of the new LCQB team "Telomere and Genome Stability" (Héloïse Coutelier and Zhou Xu) makes the cover of the December issue of Genes & Development!    The article (Coutelier et al. 2018 Genes Dev.) shows that telomere-induced senescent cells can adapt to the DNA damage checkpoint safeguard mechanism to force cell division, leading to increased genome instability, with important ramifications for aging and cancer. The cover displays cells bearing a fluorescent reporter construct monitoring of the checkpoint status in single cells.

September 10, 2018

The group Evolution and immunology of pathogens ( Rouzine, Pedruzzi, Barlukova) published the article "Evolutionary Footprint of Epistasis" on PLOS Computational Biology.

June 22, 2018

Pierre Louis Blaiseau of the Genetic Networks team recently published « Monod and the phenomenon of diauxie » in the Bulletin d’Histoire et d’Epistémologie des Sciences de la vie. This article described a part of the scientific activity of the Jacques Monod until then neglected by the historians: its interest during all its career for the mechanisms of enzymatic inhibition. Besides, it showed that, contrary to the standard narratives, the phenomenon of « diauxie » (double growth) was discovered by Monod during his thesis and not by the previous Frederic Diénert’s work

June 6, 2018

The Diatom Functional Genomics Team (L Taddei, GR Stella, JP Bouly, M. Jaubert and A. Falciatore) reported novel strategies to deal with environmental light stress in marine diatoms.  Their results recently published on Plant Physiology reveal that diatoms modulate non-photochemical quenching of excess excitation by activating different members of the LHCX protein family, with different light intensity activation thresholds and different patterns of association with photosystem II. This leads to mechanistically different and physically segregated excess energy quenching processes, as required for proper light-stress acclimation in the extremely variable conditions of the oceans.

June 5, 2018

Local Interaction Signal Analysis (LISA) is an empirical function designed to estimate protein-protein binding affinities. It explores the geometry of contact distributions at protein-protein interfaces and enables to identify hot-sites of favorable contacts playing a major contribution in binding affinity. LISA applies to a large variety of complexes resulting in a very stable behavior. It outperforms all existing comparable predictor methods predicting binding affinity.

The Analytical Genomics team.
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