The ancient phylum Apicomplexa includes many of the world’s pre-eminent protozoan pathogens. Most deadly to humans is Plasmodium, the agent of malaria, which kills around a million people annually. As obligate intracellular parasites, they establish intimate interactions with their hosts. Toxoplasma gondii is an extreme example of this adaptation, able to replicate within nearly every cell type in any warm-blooded host. Not only the developmental program of this parasite in wildlife and livestock animals can result in potentially negative socio-economic impact, but remarkably, in about a third of the human population Toxoplasma also experiences prolonged quasi-silent persistence in tissues such as brain and retina. While the asymptomatic parasitism that proceeds typically offers life-long equilibrium and protection in immune competent hosts, sustained immune dysfunction is known to break parasite dormancy, promoting bradyzoite to tachyzoite transition and further T. gondii tachyzoite population expansion, these combined processes eventually resulting in encephalitis and meningitis as major damages. The strategy of T. gondii as a parasite is based on a quest for avirulence, a capacity to attenuate but not to fully counteract the immune defense of the host, thus securing the permanent residence required to await transmission. HostQuest focuses on elucidating the molecular mechanisms by which T. gondii is orchestrating immune evasion and lifelong persistence in hosts. Once intracellular, parasites actively reprogram gene expression of the immune cells they infect by subverting host transcription factors activity or by modulating the epigenetic status of target genes. Secreted effectors are involved. Those are singularly exported beyond the vacuole-containing parasites and reach the host cell nucleus to reshape the host genetic program. The discovery of new exported Toxoplasma effectors and the characterization of their activities, or the mechanisms by which they are recognized by the host immune system, continues to gather pace. Much has been learnt in recent years but we have only been chipping at the tip of the iceberg. We aim to study the modus operandi of these effectors and particularly their possible implications in immune evasion and parasite persistence. These effectors may adopt at least three alternative, although not mutually exclusive, strategies to subvert host gene expression. They may (i) modulate upstream signaling pathways (ii) directly target host transcription factor protein levels/activity and/or (iii) affect histone packing and chromatin configuration. HostQuest is an interdisciplinary project that aims to: i) Determine the full repertoire of GRA effectors and the magnitude of the changes they are eliciting in the infected cell; ii) Explore their synergistic and/or antagonist effects on gene regulation; iii) Decipher the extent to which they contribute to immune evasion and/or sustained parasitism; iv) Gain knowledge of the three-dimensional structure of effectors in complex with host cell factors in order to understand the protein function or to guide further experiments to investigate function. Studies of effectors also continue to offer opportunities for the development of tools to probe host cell biology in the absence of disease. In this respect, HostQuest is also poised to exploit Toxoplasma molecular intelligence developed over million years of co-evolution with its hosts to learn new lessons on the mechanisms regulating cell homeostasis and their alterations in host cells, including cancer cells.

The goal of this project is to use the resurrection of ancestral proteins for investigating the genesis of allosteric regulation. As now accepted, a protein is not a static entity, on the contrary its structure fluctuates, and continuously explores a range of conformations. The relative occupancy of each state as well as their interconversions are controlled by the free energy landscape. The finest details of the conformational landscape depend on the primary sequence of the protein, and therefore are critically altered by amino-acid substitutions as they can occur along the molecular evolution. Determining the evolvability potential of each amino acid replacement, or in other words, determining the magnitude of its impact on the protein conformational landscape, is a key point to clearly understand the evolution of proteins, and of their functions, and most importantly of the mechanism underlying activity regulation. In the project AlloAnc, we will use a synergetic approach based on various experimental and theoretical methods: ancestral sequence reconstruction and protein resurrection together with biochemical, structural and dynamical investigations. Using this approach, we propose to reconstruct the genesis of the allosteric regulation in a superfamily of dehydrogenases. This superfamily is divided into several enzymatic groups: the Lactate dehydrogenases (LDHs), which are in great majority allosteric and the Malate and hydroxyacid dehydrogenases (MalDHs and HincDH) which are not. Allosteric regulation in LDHs is due to the binding of an allosteric effector: the fructose bis-phosphate (FBP) that is an intermediate of the glycolytic cascade. FBP strongly activates catalytic efficiency of allosteric LDH. Since the family divergence, contemporary LDHs, MalDHs and HincDH differ by three main properties: their functions, their capacity of regulation and their conformational flexibility. Our working hypothesis is that the genesis of the allosteric properties in LDHs is the result of the critical effect of mutations cumulated outside the catalytic site. These mutations had long-range effects on the catalytic site, namely by inducing enhanced flexibility would cause its distortion from the functional structure and therefore knocked-out the activity. However, this loss of activity can be viewed as an efficient strategy to ensure its control if other mutations are able to restore the correct catalytic site geometry by promoting, for example, the binding of a ligand which will suppress the un-functional flexibility and ultimately restoring the activity. This is the essential principle of regulation by allosteric activation. In the case of LDHs, the substitutions allowing the binding of the FBP were able to create conditions for a balance between inactive (too flexible) and active conformers (less flexible) within a single molecule. The objective of our project is to trace by phylogenetic approaches the evolutionary pathways that led to modern LDHs and to experimentally characterize the ancestral enzymes occupying the key positions along the divergence pathways and therefore to reconstruct the main steps in the genesis of allostery. Our approach is the only one that allows both a determination of the respective order of fixation of amino acid substitutions and a measurement of the magnitude of their dynamical effects in an evolutionary process. This will allow us to dissect not only the local effects of mutations but also to understand how their long-distance effects propagate. The results obtained will provide major advances not only in fundamentals science but also in the design of therapeutic enzyme inhibitors. Indeed, thanks to high throughput screening of bioactive compounds we will identify “allosteric inhibitor like” molecules and we will analyze the results with respect to the library of dynamical structures obtained by molecular dynamics simulation.

Modern information systems become more and more complex, and so do the data they have to handle. This is the case, for example, of protein functions prediction, information retrieval from big data bases of documents, recommending items or actions from few preferences, diagnosing and monitoring the state of complex systems such as planes, energy networks, … This means that accurate data and models are respectively harder to obtain and harder to learn. Hence, available data are often noisy and incomplete (e.g., pairwise instead of full preferences). Dealing with such data while preserving the computational efficiency of the learning methods often means a drop in the accuracy of model predictions. While some loss of accuracy for a gain of efficiency is affordable in some applications such as recommender systems or web crawlers, such a loss is a tremendous drawback in other applications such as medical diagnosis, risk analysis or autonomous vehicles. For these latter applications, recent and very promising trends of research consist in fully acknowledging this uncertainty in the learning process, possibly sacrificing some efficiency for more reliable results, for instance by allowing models to make partial and cautious but more accurate predictions, or by treating data uncertainty in a conservative way. The goal of this project is to foster collaborations between French laboratories and European research groups following this trend from different perspectives, to exchange views, establish a common understanding of this emerging field and develop a European network focusing on this specific topic. The aim of this project if to lay down the first corner stones of this long-term goal, notably through the orgnization of events (workshops, special sessions or journal special issues) and the exchange of researchers and students between the different involved groups and the Heudiasyc Laboratory. The network will focus on two main topics. The first topic addressed by the network the one learning from uncertain data, either in the input features or the observed (structured) output. In particular, it will explore the recent trend recommending to learn sets of models from the uncertain data, thereby producing partial but more reliable prediction, and will compare it to the more usual requirement of learning one model giving a precise prediction. The second explored topic will concern cautiousness in models and in decision-making, more specifically when cautiousness is understood as the fact of producing sets of models or sets of predictions when uncertainty is too important. Two problems related to this we expect to discuss are how this cautiousness should be exploited in learning methods, and how to handle this cautiousness in a computationally efficient way.

Obstructive Sleep Apnea (OSA) is one of the most frequent chronic disease affecting nearly one billion people worldwide. OSA corresponds to the repetitive occurrence of complete (apneas) and incomplete (hypopneas) pharyngeal collapses during sleep leading to cycling hypoxia-re-oxygenation sequences called intermittent hypoxia. OSA is a growing health concern, highlighted by a societal and economic burden close to hypertension or stroke. OSA is associated and modulate severity of various chronic diseases including metabolic syndrome, nonalcoholic fatty liver diseases and cardiovascular disease. The landmark feature of OSA is a chronic intermittent hypoxia (CIH) associated with apneas/hypopneas leading to activation of the hypoxia-inducible transcription factors (HIF) directly responsible for multiple organ damages including liver disease. The interconnections between hypoxia and circadian rhythms has become a hot research topic in physiological science. This link is largely explained by transcriptional and epigenetic mechanisms. However, data are limited regarding these interactions in OSA, a particularly relevant disease since it induces intermittent hypoxia during a specific circadian time period (sleep). This is therefore an important emerging area to explore and the main goal of this project is to demonstrate that reprogramming of circadian homeostasis by CIH is a key mechanism underlying OSA-related organ injury with a specific focus on liver disease. Given the intimate link between hypoxia, circadian rhythms and chromatin dynamics, by understanding how these components act as a coordinated network TEMPORISE may provide novel insight into how these factors contribute to liver disease in general and more specifically in OSA. First, we aim to explore the kinetics of liver disease evolution under intermittent hypoxia exposure and to characterize the timing of circadian rhythm perturbation by CIH. Second, we wish to understand molecular mechanisms underlying circadian clock dysregulation at the onset of liver disease, through a molecular study of the interaction between the circadian clock and HIF-1 and the associated transcriptional and epigenetics consequences. Third, we want to analyze the effect of circadian clock and HIF-1 disruption on CIH-induced liver disease development through histological characterization and the use of appropriate knockout mouse models. The combined expertise of the coordinator and the partners are major assets for the TEMPORISE project. This project will take advantage of state-of-the art technics such as epigenomics, transcriptomics, proteomics and bioinformatics approaches. Altogether, we expect that unraveling novel mechanisms interconnecting CIH and circadian clock defects will provide new insight in the understanding of liver diseases development and pave new avenues towards pharmacological interventions.

Galdieria sulphuraria is a cosmopolitan photosynthetic microalga isolated in volcanic zones. This acidophilic and thermophilic alga is characterized by a high metabolic flexibility as well as by a high biomass productivity. G sulphuraria is able to grow in phototrophic regime (exclusive use of light as a source of energy), heterotrophy (fermentation or reduced carbon respiration) as well as in mixotrophic conditions (simultaneous use of light and reduced carbon). G. sulphuraria is considered as an emerging system for Biotech applications. On the other hand, the molecular bases of these unique performances are still largely unknown. For this reason, we propose a project to understand the molecular mechanisms of Galdieria mixotrophic growth as a step towards achieving maximum biomass for biotechnological applications. This will be achieved by high-throughput screening (photosynthesis, growth) of different strains under photo / mixotrophic conditions. Comparative genomics, proteomics as well as metabolic analyses will make it possible to reconstruct in silico the metabolism of G. sulphuraria, thanks to a new bioinformatic tool designed for detailed reconstruction and visualization and system-wide analyses of metabolic networks. This will make it possible to carry out metabolic modelling as well as flux balance analysis, and thus to identify the constraints and the limiting steps in the conversion of light and carbon sources. To achieve these goals, we have assembled a consortium of three partners (LPCV, HHU, BGE) with a solid record in the study of the metabolism of photosynthetic organisms, all leaders of research in their scientific fields. The partner laboratories contributed to the first studies of G. sulphuraria (HHU), including the sequencing of its genome, and the identification of the mechanism of mixotrophy in microalgae (LPCV). The three partners will study the key steps of mixotrophic metabolism with complementary methodological expertise (LPCV: physiology, respiration and metabolic reconstruction; BGE: proteomics, bioinformatics; HHU: comparative genomics and metabolic fluxes). This project will provide knowledge on how to optimize the productivity of this alga and will identify targets for improved biomass productivity in the perspective of future metabolic engineering.