In the context of climate change and increasing energy needs of the world population, the global interest for sustainable sources to produce energy is growing. One promising resource for biofuel production is microalgae, although their industrial use is limited by the lack of efficient harvesting techniques. Assisted flotation represents a promising harvesting technique that consists in air dispersed into microbubbles rising through a microalgae suspension. As a result, microalgae cells get attached to gaz-liquid interfaces and are carried out and accumulated on the surface, without being damaged. Flotation is thus a relatively rapid operation that needs low space, has moderate operational costs, and that could thus overcome the bottleneck of feasible microalgal biofuel production. However, the efficiency of this method is limited by the fact that the interaction between the bubbles and the cells is generally repulsive, due to the negative surface charge of the cells and the bubbles in water, and the low hydrophobicity of the algal cells. The goal of this project is to improve the efficiency of flotation, in order to better exploit the potential of the microalgal bioressource. Fundamental knowledge at the molecular and cellular scales will be acquired on the cell wall of microalgae and on the molecular mechanisms underlying its adhesion to gaz/liquid interfaces, using advanced force spectroscopy techniques such as optical tweezers and FluidFM technology. These data will then be further used to identify adhesive components promoting cell aggregation at the cells interface, and functionalize them at the surface of bubbles, thus improving flotation efficiency without altering the cells. Finally the overall evaluation of the efficiency of the functionalized bubbles for microalgae flotation will be evaluated and compared to other harvesting techniques. The results obtained in this project will allow to generate fundamental knowledge on the cell wall of microalgae and on the molecular mechanisms underlying their adhesion to gaz-liquid interfaces. These are not the only benefits of this project, as it will also provide a new technological solution to measure the interactions between fluid and biological interfaces, as well as a way to increase the efficiency of flotation process. Therefore, understanding the biophysics of microalgae flotation will open up new strategies to transform the microalgal biomass into 3rd generation biofuels.

The overall aim of this project is use a synthetic biology approach to develop a consolidated bioprocess (CBP) that will be built around a novel bacterial strain, possessing both high cellulolytic potency and the ability to produce valuable chemicals at high yield. To our knowledge, a fully bi-functional microorganism of this type, able to degrade pretreated cellulosic feedstocks and create useful products (other than ethanol), has so far never been made. Therefore, SYNBIOCHEM proposes to drive biorefining towards hitherto unreached targets. It is now widely recognized that the future bio-economy will rely on cellulosic feedstocks, and that these feedstocks will necessarily be drawn from the abundant non-food, lignocellulosic plant matter (or LC biomass) or from wastes coming from agriculture or recycled papers and cardboards. The use of these cellulosic feedstocks presents a number of challenges for today’s panoply of technologies. These include the initial cracking (pretreatment) of the feedstocks and also the enzymatic hydrolysis of the resultant cellulose, both of which are operations that weigh heavily in the cost balance. One route towards reducing the cost of cellulosic feedstocks processing is to aim for maximum integration, eliminating enzyme production costs, enzyme end-product inhibition and separate hydrolysis and fermentation steps. These elements are all present in a concept known as consolidated bioprocessing (or CBP), which employs a single cellulolytic microorganism as the catalyst for both hydrolysis, leading to the production of glucose from cellulose, and fermentation, leading to the production of target compounds. So far, all the natural cellulolytic organisms produced only limited number of chemicals (namely ethanol, lactate, butyrate and acetate) while the microorganisms engineered to produce higher value chemicals (like Escherichia coli or Saccharomyces cerevisiae) are naturally non-cellulolytic. Furthermore, the production at high yield of some oxidized chemicals derived from acetyl-coA would require the use of a growth associated non-oxidative glycolytic pathway (NOG) under anaerobic conditions but so far all the attempts to develop such a strain have been unsuccessful. In SYNBIOCHEM Clostridum acetobutylicum will form the basis for a sophisticated synthetic biology approach. This bacterium is a very suitable candidate for CBP, owing to its previous industrial history (used in the ABE process), its ability to produce useful chemicals and the presence in its genome of the vital elements necessary to construct a cellulosome. To achieve this goal, we will first repair the cellulosome of C. acetobutylicum and maximize the expression of its encoding genes to degrade efficiently pretreated cellulosic feedstocks and provide fermentable sugars for the production of targeted chemicals. In addition to the creation of a CBP microorganism, SYNBIOCHEM will also provide new knowledge to implement a growth associated and still functional synthetic NOG pathway that will allow the production acetyl-coA derived molecules at higher yield when less NADH is consumed in their formation than produced in the glycolytic pathway. Furthermore, C. acetobutylicum will be metabolically engineered to produce the targeted molecules of industrial interest using as a platform strain, an hydrogenase minus strain previously patented by the applicant. Finally a novel CBP bioreactor will be developed in collaboration with the partners companies. To achieve all of the above targets, SYNBIOCHEM will use a powerful set of synthetic biology tools that have been previously developed during the last four years. Furthermore, in term of knowledge transmission, the professors involved in SYNBIOCHEM will share the expertise gained from this project with the students enrolled in the Master of Biochemical Engineering at INSA and the future International Master of Industrial Biotechnology in collaboration with AgroParisTech.

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.

Synthetic biology continuously demands the development of novel biotechnology tools for the optimization of engineered metabolic cascades. This, in part, can be tackled by optimizing the three-dimensional relative emplacement of designed enzymes. SPACEHex seeks to develop novel protein-based platforms for such purposes. They will be based on the highly modular and assembly-prone hexamer bricks that compose the shells of bacterial micro-compartments (BMC). Taking into account that BMC are structures that host varied types of metabolic processes in vivo, and are therefore naturally adapted for synthetic biology purposes, the novel platforms should be optimal bricks for the conception of future nano-reactors for the encapsulation of engineered metabolic routes. To reach its main goal, SPACEHex intends to master the relative emplacement within those hexamers of each individual monomer, the attachment points for future engineered domains. After setting up appropriate high-throughput screening methods, optimized to maximize readings of monomer-monomer associations within hexamers, we will first evaluate monomer-monomer interface compatibilities by confronting all possible pairs of homologous isoforms in libraries of sequences selected from genomic databases. Gathered information will be important for the design of hexameric platforms, but is also expected to contribute to our understanding of BMC function. Thus, compatibilities between isoforms of given bacteria could permit to anticipate mechanisms of regulation preventing the formation of hybrid BMC in organisms capable of producing several compartment types. Experimental data will be exploited to guide the computer-aided design of monomer-monomer interfaces. Rapid and efficient artificial intelligence algorithms for automated reasoning (“cost function networks”) combined with molecular modeling approaches that have been developed by members of this consortium, will be exploited to model and estimate binding affinities for huge numbers of pairs of sequences. Comparison to experimental data is expected to permit the amelioration of theoretical parameters, thus leading to more reliable predictions when studying sequences present in genomic databases. Such feedbacks should permit in fine to define residue determinants for association at monomer-monomer interfaces, guiding decisions for the reconstitution of orthogonal interfaces based on natural sequences. The same computational methods will be also extended to allow multistate decisions, thus allowing the automatic rejection of monomer sequences that would cause promiscuous associations with several other monomer sequences. In that manner, SPACEHex will also pursue the reconstitution of hexameric platforms from orthogonal monomers based on de novo sequences. After validating the structural design of final delivered hexamer platforms, their structural viability and compatibility with BMC shell environment will be evaluated in vitro and in vivo. Moreover, the potential of resulting platforms for synthetic biology will be tested using a tripartite enzymatic model.

Lignocellulosic biomass (LCB) is a renewable and inexhaustible carbon source on Earth and its valorization will drive sustainable bioeconomy. Microorganisms produce a huge repertoire of carbohydrate active enzymes in order to utilize LCB as carbon source. Bacteroides, encode fine-tuned gene clusters dedicated to polysaccharide metabolism called Polysaccharide Utilization Loci (PUL). We recently discovered a xylan PUL from termite gut whose enzymes showed promising activity on different LCB. In this project an original co-evolution strategy will be deployed to simultaneously engineer PUL’s enzymes towards different biomasses. In addition, the evolved enzymes will be used to create artificial enzyme assemblies to further maximize the synergy between the catalysts. All this work will be backed up by a thorough structure analysis to identify key amino-acids and spatial organization necessary to develop more efficient enzyme cocktails usable in bioeconomy.