RNase E is an essential enzyme that has a global role in RNA metabolism. It functions as part of a large macromolecular complex known as the RNA degradosome. In 2008, the group of A.J. Carpousis (coordinator) published experimental work demonstrating that RNase E is localized at the periphery of the cell and bound to the inner cytoplasmic membrane by a membrane targeting sequence (MTS). RNase E localization is important for normal cell growth. The slow growth of the rne-delta-MTS strain suggests an alteration of RNase E activity in the cell that could involve accessibility to substrates or interactions with other membrane-bound machinery. The aim of our proposal is to explore the physiological role of the localization of RNase E to the inner cytoplasmic membrane. Over the past decade, the application of fluorescence microscopy to localize bacterial machineries involved in transcription, translation, RNA processing and mRNA degradation has toppled the long held myth that these processes occur in an aqueous ‘soup’ of freely diffusible macromolecules. Despite the lack of internal membranes, the machineries involved in transcription, translation and RNA processing and degradation are separated spatially. RNA polymerase is associated with the nucleoid at the center of the cell, freely diffusible polyribosomes are localized to a cytoplasmic space between the nucleoid and the inner cytoplasmic membrane, and key components in RNA processing and degradation are localized to the inner cytoplasmic membrane. Corollaries to the spatial separation of the transcription and degradation machineries are the prediction that mRNA degradation is initiated at the inner cytoplasmic membrane and that key steps in the maturation of transfer and ribosomal RNA also occur there. Our working hypothesis is that the membrane localization of the RNase E limits destructive interactions with functional RNA. We will focus mainly on the influence of RNase E membrane localization on the degradation of mRNA and the action of regulatory noncoding RNAs, but this work will also impact our understanding of RNA processing and RNA surveillance. Systematic approaches will be used to decipher the global regulatory functions of RNase E in a whole genome expression profile, in the stability of every cellular transcript, and in the processing events within the whole transcriptome. Our strategy will produce data with resolution at the nucleotide level. Global maps of RNase E direct targets when localized either at the membrane or displaced in the cytoplasm will be produced. A comparison of both data sets will give information on substrate accessibility depending on the cellular localization of RNase E. The rne-delta-MTS strain will be characterized at the molecular level. The physiological role of the localization of RNase E will also be addressed by a classical approach genetic approach involving a screen for suppressors of the growth defect in the rne-delta-MTS strain. This work will have major impact on our understanding the spatial organization of the bacterial cell regarding RNA processing, RNA surveillance and mRNA degradation. The complementary expertise of each of the 3 partners is essential for the achievement of the project. Partner 1, the group of A.J. Carpousis, has extensive experience in the field of bacterial mRNA degradation and was at the origin of the discovery of a multienzyme mRNA degrading complex known as the RNA degradosome. Partner 2, the group of M. Cocaign-Bousquet, has extensive expertise using systematic approaches to decipher bacterial physiology and metabolism. Partner 3, the group of C. Gaspin, has recognized expertise for their work on bioinformatic studies in the RNA field.

The exploitation of evolutionary information, and more particularly of residue coevolution, has revolutionized protein structure predictions. Adaptation of the methods issued from these analyses to the prediction and design of enzymatic functions remains an open problem. Enzymatic functions are indeed characterized by an internal dynamics of proteins that is difficult to model and study experimentally. In this project, we tackle this problem by studying in detail the capacity of certain hydroxylases of the flavin-containing monooxygenase (FMO) protein family to realize their reaction at different positions of the aromatic cycle of ubiquinone (UQ), a molecule key to the production of cellular energy. More precisely, UQ biosynthesis pathway involves three hydroxylation reactions occurring on three carbons of the UQ aromatic ring. Partner 1 has shown that different proteobacteria species use different combinations of (UQ-)FMOs to hydroxylate these three positions: some bacteria use a single enzyme able to hydroxylate all three positions, while other bacteria use three distinct enzymes that hydroxylate a single position each. The UQ-FMO family is thus characterized by a broad diversity of regioselectivities, with enzymes capable of hydroxylating one, two or three positions of the UQ aromatic cycle. In this context, our objective is to develop a methodology that combines molecular modeling (Partner 2) and evolutionary information of enzymes (Partner 1) to elucidate the molecular mechanisms underlying this diversity of regioselectivities. Our preliminary results show that in alphaproteobacteria, a family of homologous enzymes named UbiL displays the entire diversity of UQ-FMO regioselectivities, with UbiLs hydroxylating one, two or three positions in different organisms. In addition, an analysis of amino acid coevolution suggests that this diversity is controlled by a sector, i.e., a network of coevolving residues connected in the 3D space (forming a cavity around the active site). In this context, our first objective is to decipher the molecular mechanisms responsible for the variations of the UbiL regioselectivity. To this end, we will use a combination of molecular modeling (Partner 2), of phylogenomics (Partner 1) and of statistical analyses of amino acid coevolution (Partner 1). Moreover, the predicted regioselectivities of natural, artificial and ancestral enzymes (we will resurrect the latter) will be systematically tested using biochemistry experiments (Partner 1). Next, we will apply our methodology to the full set of UQ-FMOs (~1000 sequences) in order to highlight the evolution of mechanisms associated with the hydroxylation stages of the UQ pathway. Finally, we will analyze the entire family of FMOs (~18000 sequences) in order to recapitulate the evolution of this protein family by identifying both commonalities and differences between metabolic pathways. In particular, our objective is to identify the sector(s) responsible for the variations of regioselectivity of UQ-FMOs and, more generally, the variations of regioselectivity of FMOs, and to use this information to refactor enzymatic functions. In this regard, as a proof of concept of the generality of our methodology, we will aim at modifying the regioselectivity of a FMO unrelated to the UQ pathway. Altogether, this truly interdisciplinary project thus aims at integrating molecular modeling (from 3D modeling of enzymes to the analysis of the internal dynamics of the enzyme in interaction with the substrate) and evolutionary information (from the reconstruction of the evolutionary history of metabolic pathways to the coevolution of amino acids) of enzymes whose functionality can be tested at the bench (using biochemistry experiments) in order to improve our understanding of the functioning and evolution of enzymes, and to propose novel principles for enzyme design.

FeFe-hydrogenases (H2ases) are large and complex metallo-enzymes which catalyse H2 oxidation and production at a conserved inorganic active-site, the so-called H-cluster. They are studied in various contexts, ranging from bioenergetics to inorganic catalysis, but the main motivation is certainly that both these enzymes and the knowledge we might acquire by studying them will prove useful for designing the catalysts we need to produce hydrogen from water in a clean process. Yet understanding why these enzymes cease to work under adverse conditions, and designing H2ases that are best suited for biotechnological applications, remain major challenges which we plan to tackle using a multidisciplinary approach that combines state-of-the-art electrochemistry, molecular biology, biochemistry and theoretical methods. The current attempts to use the photosynthetic alga Chlamydomonas reinhardtii to produce H2 from water and light are hampered by the inactivation of this enzyme by the oxygen coming from photosynthetic water oxidation, and also by the fact that the H-cluster is destroyed by light in the UV-Vis range. This photodamage has hardly been characterized yet, and the problem of O2 sensitivity has not been approached by taking advantage of the fact that FeFe-H2ases isolated from various organisms react very differently with O2; yet the latter observation implies that it should be possible to use molecular biology to modify H2ases and make them more O2 tolerant, provided the molecular basis of oxygen sensitivity is understood. We will combine direct electrochemistry and theoretical chemistry to understand the inhibition of theses enzymes by oxygen and light. Our approach is unique in that we intend to learn about the molecular determinants of inhibition by studying and comparing the properties of artificial hydrogenases and of a number of FeFe H2ases isolated from different microorganisms prepared by the two teams of biochemists and molecular biologists. (See confidential documents & summaries for details.) Recent, joint publications in JACS, Angewandte chemie, Nat. Chem. Biol. etc. show that the five teams have already collaborated very fruitfully, and preliminary results presented in the scientific document attest to the feasibility of the project. Combining genetic engineering and appropriate electrochemical, photoelectrochemical and theoretical investigations will bring an entire set of new data that will increase greatly our understanding of the reactivity and vulnerability of these biological catalysts. It should also take us closer to the Graal of biohydrogen research: an H2-production biological catalyst that remains active both in the presence of O2 and upon strong illumination.

This project aims at studying the role of gene expression variability (due to the stochastic fluctuations at the molecular level) in stress response and genetic instability. The impact of this variability on population dynamics is now well-studied, and increase of stochasticity (or noise) in gene expression is considered as a relevant evolutionary strategy in fluctuating environments. Here we want to determine if such an increase for some genes has been a way for technological yeast strains to adapt to the stressful fluctuating conditions they have to deal with. Indeed these strains are well-adapted to many environmental stress compared to laboratory strains. In the first part of this project, we will focus on the recently sequenced oenological strain of Saccharomyces cerevisiae EC1118 (NOVO et al. 2009) to detect promoters that are noisier in this strain compared to the standard non-adapted laboratory strain S288c. If such differences of noise are detected, we will study their impact on stress response and adaptation in stressful environments, especially in terms of fitness. This original stragety should enable the identification of new determinants of stress resistance and tolerance. At the moment no study has linked noise in gene expression to genetic variability. But, like any other phenotype, maintenance of genome integrity is under the influence of genes expressed with stochastic fluctuations. The rate of genetic-variant generation (RGVG) could be variable as a consequence of stochastic fluctuations in the expression of DNA repair and maintenance genes from cell-to-cell. High noise in the expression of genes involved in Double-Strand Break repair or DNA replication for instance, could confer a broad range RGVG from cell-to-cell in the population, and favour the emergence of sub-populations with higher genetic variability in times of stress, thanks to a second-order selection process (indirect selection of mutator strains along with favourable mutations they generate which counterbalance possible deleterious mutations) (CAPP, 2010). The aim of this project is to determine if industrial strains have evolved towards such a high noise in the expression of genes involved in DNA repair and maintenance. If this is the case, we will study the impact of different noise levels in the xepression of these genes on genetic variability under selective conditions. Capp, J. P. (2010). Noise-driven heterogeneity in the rate of genetic-variant generation as a basis for evolvability. Genetics 185, 395-404 Novo, M., et al. (2009). Eukaryote-to-eukaryote gene transfer events revealed by the genome sequence of the wine yeast Saccharomyces cerevisiae EC1118. Proc Natl Acad Sci U S A 106, 16333-16338.

Nowadays, a multiplicity of wines is proposed on the international market. The main characteristic that enables to discriminate these wines is their sensorial profile. In recent years, the “international” taste of wine consumers is rather focused on the fruity aromas. As a consequence, to maintain its competitiveness and to conquer new markets in the intensive international competition, the French winemaking industry is constantly requesting solutions to enhance the aromatic quality of its wines. To address this question, the overall objective of the STARWINE research project is to control the fruity flavour of wine through the development of innovative real-time control strategies of the winemaking fermentation process, using a predictive mathematical model. This aim will be reached through a multidisciplinary approach based on the following scientific competences: bioprocess management, yeast metabolism, experimental design, bioprocess modelling, control theory and implementation of sensors. Nitrogen and temperature have been recently identified as the main parameters impacting on aroma synthesis. Nevertheless, winemakers lack methods to monitor and adjust these parameters because their relative contributions and interactions have never been evaluated. Therefore, in the first part of the project, done on a laboratory scale, we will assess the impact on aroma production of a combined management of: (1) nitrogen addition during the fermentation process and (2) anisothermal profile of temperature. The obtained data will be used both to better understand the yeast physiology and to build a mechanistic mathematical model (representative of the main reactions of yeast metabolism). Then, a real-time control strategy based on this model will be proposed and validated on a laboratory scale using an online GC (gas chromatography) laboratory equipment. In parallel to this first part, we will assess the performances of a physical sensor based on photoacoustic spectroscopy to evaluate the industrial feasibility of an online monitoring of key aroma compounds. Finally, we will combine the results obtained on a laboratory scale and the calibrated physical sensor to test the control strategy in industrial conditions. The project STARWINE will contribute to the wine industry renewal through the optimization of the production process and the adaptation to consumer demands. The objective is not to maximize the final aroma content of the wine but to reach a predefined aroma profile through a constant adjustment of the control parameters of the fermentation process. Such a management of the fermentation will be very innovative because, using the real-time control law that will be developed in STARWINE, it will be possible for a winemaker to define his unique wine “style” and to adapt to consumer demands. As a consequence, the project STARWINE can be considered as a proof of concept of both the implementation of new online devices and breakthrough strategies for a better management of aromas in wineries and the real-time control of fermentation processes using microorganisms. The concepts and methods developed in the project will be generic enough to be applied, after adaptation, to other bioprocesses.