Despite the growing number of chemicals successfully engineered in host organisms, bioproduction R&D is slow and expensive, as the process is mostly based on trial-and-error. To overcome this critical hindrance, we propose to implement a generic automated design-build-test and learn cyclic pipeline for the production of targeted chemicals. As an illustration, we will apply the pipeline for the metabolic engineering of a library of new antimicrobials against Gram-positive bacteria. The pipeline comprises state-of-the-art bioproduction pathway design tools, robotized strain engineering, and high throughput product quantification via biosensors. The whole process is driven by an original computational machine learning component that determines the next set of constructions that needs to be processed by the pipeline with the goal of increasing product yield. In the specific approach we will be using, named active learning, a growing training set of experimental results is acquired on the fly in an iterative process between learning and measurements. The remarkable advantage of active learning is to yield performances comparable to classical machine learning with training sets sizes that can be several orders of magnitude smaller. Active learning can thus drastically reduce the cost of performing measurements, and in the present application significantly reduce the number of iterations for strain optimization. We propose to apply the pipeline for the production of nutritional and antimicrobial flavonoids. Precisely, the pipeline will be run for four research objectives that complement each other: (RO1) to learn enzyme sequences that maximize flavonoid titers, (RO2) to determine enzyme expression levels limiting intermediates accumulation and increasing final product yields, (RO3) to regulate the expression of the genes of the host strain to optimize both growth and flavonoid titers, and (RO4) to produce novel flavonoid structures with maximal toxicity against Gram-positive bacteria. While moving toward optimizing strains and producing novel flavonoids, our project will offer a technological rupture to industrial biotechnology where machine learning is driving experimental implementation and measurement. We anticipate this innovative solution will bring tremendous gains in throughput and speed. The project will be illustrated with the production of a library of flavonoids, but the design-build-test-learn pipeline is general enough to be applied to other molecules of interest to the health, food, chemistry and energy industrial sectors, including commodity chemicals, and fine and specialty chemicals. Our approach could for instance be extended to other pharmaceutical applications beyond the search for antimicrobial activity, as long as there exists a screening method relevant to the problem. Beyond small molecule bioproduction a similar pipeline could also be implemented to metabolize alternative but commercially attractive feedstock and to develop biosensors for environmental pollutants. The expertise gained in the project will drastically improve our SME partner strain development platform and in return the SME partner will bring the technology to the market seeking for industrial collaborations through a specific exploitation task. While we plan to release our computational methods to the academic community through web services, for specific applications, our know-how and software products will be packaged in an integrated pipeline and commercialized as a service. We foresee large industrial groups will want to customize development of the pipeline for their own application. The service we will provide to the industry will generate revenues and will also be a source for job creation.

In the context of climate change, it appears essential to unravel the mechanisms governing abiotic stress tolerance in higher plants, in order to build predictive models and use this knowledge to assist selection and design of stress tolerant crops. We have previously uncovered remarkable adaptations in seed mitochondria, which because of the ability of seeds to survive desiccation, display impressive tolerance to abiotic stress. In particular, seed mitochondria accumulate high levels of small heat shock proteins (sHSP) and late embryogenesis abundant proteins (LEA). The sHSP are the most widespread but less conserved HSP. They contribute to the molecular chaperone network that assists protein biogenesis and homeostasis under stress conditions (sHSPs are stress inducible). In eukaryotes, mitochondrial sHSP (M-sHSP) have only been identified in plants and insects. LEA proteins are highly hydrophilic proteins, generally intrinsically disordered, which accumulate in desiccation tolerant organisms, and whose functions still remain largely enigmatic. The MITOZEN project aims at deciphering the molecular function and physiological role of the mitochondrial sHSP and LEA proteins (M-sHSP and M-LEA) in the model plant Arabidopsis thaliana. The genome of Arabidopsis harbors 17 sHSP genes (including 3 M-sHSP) and more that 50 LEA genes, among which we have recently identified 5 M-LEA genes. The molecular functions of the M-sHSP and M-LEA will be explored using biochemical and biophysical approaches to study recombinant proteins produced in Escherichia coli. Their structural features and protective activities (oligomerisation, secondary structure, chaperone activities, membrane protection) will be examined in the context of temperature stress and dehydration using a large panel of techniques and in vitro assays. The goal is to determine the potential molecular functions of the different M-sHSP and M-LEA in the context of stress tolerance (desiccation in seeds, high temperature in seeds and plants). A reverse genetics approach will be developed in Arabidopsis to explore the role of M-M-sHSPs and M-LEAs in the physiology and development of plants. Single and multiple knock-out mutant lines will be constructed, as well as overexpressors using an inducible system. Their phenotypic characterization will focus on seed development and abiotic stress tolerance of plants, including mitochondrial function. The integration of data provided by these multidisciplinary approaches (bioinformatics, biochemistry and biophysics, genetics, physiology) will shed light on the function and importance of the different M-sHSP and M-LEA in the development and stress tolerance of plants. It will also increase knowledge about molecular chaperones and in particular with respect to their yet unexplored role in the context of dehydration, and will shed novel light on the function of LEA proteins.

Microalgae and plant leaves are promising sources of fatty acids and triacylglycerol (TAG) for alternative energies or for green chemistry. A major biological bottleneck is the inverse correlation between proliferation and oil accumulation, which compromises productivity. Therefore it is imperative to take an integrated approach and investigate potential signaling pathways that regulates the balance between proliferation and TAG accumulation. Increasing evidence from our work and others indicates that the TOR (Target Of Rapamycin) pathway is essential for regulating growth and TAG accumulation in response to nutrient availability in both plants and algae. Moreover, recent independent genetic screens from two partners of this project and other groups suggest that members of the small family (3 to 5 members) of DYRK (dual-specificity tyrosine-phosphorylation-regulated kinases) could be essential effectors of TOR-dependent regulation of proliferation and lipid accumulation in plant and algae. First, TOR was shown to control cell growth and proliferation in Arabidopsis by phosphorylating DYRK kinase YAK1 which is a growth repressor acting downstream of TOR. Second, two DYRKs, TAR1 and DYRKP were reported to regulate the accumulation of reserve compounds (starch and oil) in the green algae Chlamydomonas. Our central hypothesis is that interactions between DYRK and TOR coordinate lipid accumulation and cell growth in response to environmental cues (e.g., nutrient, light). This will be addressed in parallel in plant and algal models Arabidopsis and Chlamydomonas where large numbers of genetic and molecular tools and mutants are available. This project is organized in three work-packages (WPs) and built on key preliminary results. WP1 will use state of the art biochemistry methods to identify DYRKs that are phosphorylated in a TOR-dependent manner and are therefore acting downstream of TOR. WP2 is dedicated to the functional relationship between TOR and DYRK kinases. Mutants in DYRKs, TOR, and their doubles mutant will be generated and phenotypes in regards to lipid, protein and starch content relative to biomass, with a particular focus on lipids (Heliobiotec lipidomic platform). Recently developed genome editing methods using CAS9 variant will be used to generate some of these mutants, particularly Chlamydomonas mutants carrying new point mutations in the TOR gene that we have identified in Arabidopsis and modulate TOR activity. Finally, during WP3, we will develop genetic screens of suppressors of dyrk mutants, in order to identify effectors of DYRK functions related to proliferation and TAG accumulation. The TOR-DYRKcontrol project brings together three partners with complementary expertise in TOR signaling, biochemistry, lipid metabolism, genetics, genome editing and plant and algal biology. The use of both plant and algae should shed light on the evolutionary aspects of the TOR regulation, and bridging gaps on the lack of knowledge across different evolutionary lineages. This project will advance our knowledge in the understanding of synergy between TOR pathway, cell growth and carbon storage, and allow the further use of this knowledge to create algal/plant prototypes for improved lipid production. Therefore, this project addresses two urgent societal issues, energy shortage and global warming. It should contribute to the emergency of a greener economy, replacing fossil fuels by renewable sources for the production of lipids for food, transportation and chemical industry, while lowering impact of CO2 overproduction on global warming.

The future challenge in animal production will be to provide food to a growing human population by respecting a balance between quality products, consumer acceptance and safety, as well as animal welfare. In a perspective of safe and sustainable food systems, reducing the use of antibiotics in livestock is a major concern. In fact, antibiotic resistance is one of the major medical challenges of the 21st century. The transfer of genes conferring resistance through the environment and the food chain, the potential for development of resistant bacteria and the appearance of therapeutic failures in human medicine, notably due to zoonotic bacteria, constitute major health issues for livestock farming sectors. In the pig breeding industry, the weaning period is often accompanied by a decreased growth rate caused by disparate food intake and diarrhoea due to digestive disorders that might be associated with bacterial population disequilibrium (i.e. dysbiosis) and/or opportunistic intestinal infections. Alarmingly, during this transition period the prophylactic use of antibiotics is still very frequent in order to limit piglet morbidity and mortality. Thus, reducing the prophylactic use of antibiotics in weaning pigs is a main issue and there is a strong need for alternatives. In this context, we have built a public-private partnership that gathers INRA scientists and industries from economic sectors of both animal feeding and pig breeding. PigletBiota is a precompetitive project that will study the physiological and genetic bases of the piglet sensitivity at weaning, as a prerequisite to identify innovative actions to adapt animals and pig production systems to a reduction of antibiotic use. The global aim of the PIGLETBIOTA project is to develop research that will contribute to adapt pig production systems to a reduction of antibiotics. The project proposes an integrative biology approach to determine the main factors influencing the variability of the individual’s robustness at weaning. We will monitor piglets for health, immune, stress and zootechnical traits and will characterize the intestinal microbiota diversity and composition as well as the contribution of host’s genotypes. The experimental design will combine various environments, including experimental and commercial farms, and ages at weaning and all animals will be fed without antibiotics. Animals (n~1000) will be clinically surveyed, measured for various traits related to production, immunity and stress, and genotyped with high-density SNP chips. The genetic parameters of the sensitivity at weaning will be estimated and genetic association studies performed. Faecal samples before and after the weaning date will be collected for characterizing the dynamics of the gut microbiota and studying its influence on the individual sensitivity at weaning. Animal and microbiota data will be vertically integrated in order to better understand the interplay between the these two levels of this biological system, and to develop robust indicators of weaning sensitivity. Finally, a functional screening using INRA platforms dedicated to human studies will be performed in order to detect active molecules to be tested in vivo and by using an axenic pigs model. The PigletBiota public-private consortium will favor translational research and innovation.

This project will explore how augmented reality (AR) systems can reduce the spatial and temporal distance between people’s choices and their environmental consequences, in order to reveal the impact of both individual habits and global policies. More concretely, we will design interactive visualizations that integrate concrete environmental consequences (e.g. waste accumulation, rare earth mining) directly into user's surroundings. This interdisciplinary research will be informed and validated by incentivized and controlled behavioral economics experiments based on game-theoretical models, and guided by real environmental scenarios