Computational protein design to accelerate the conception of fine-tuned biocatalysts

The remarkable properties of enzymes (high catalytic efficiency, regio- and stereo-selectivity) have been recognized and largely exploited in biocatalysis. Accordingly, enzyme-driven processes should play an increasing role in the next decades, potentially substituting chemical processes and contributing to the raise of bioeconomy. However, to foresee a viable future to biocatalysis, advances in R&D are required to accelerate the delivery of fine-tuned enzymes displaying high chemical specificity on non-cognate substrates, high efficiency and better stability in reaction conditions. To this end, structure-based Computational Protein Design (CPD) is a promising strategy to fully rationalize and speed-up the conception of new enzymes while reducing associated human and financial costs. By combining physico-chemical models governing relations between protein amino-acid composition and their 3D structure with optimization algorithms, CPD seeks to identify sequences that fold into a given 3D-scaffold and possess the targeted biochemical properties. Starting from a huge search space, the protein sequence-conformation space, this in silico pre-screening aims to considerably narrow down the number of mutants tested at experimental level while substantially increasing the chances of reaching the desired enzyme. While CPD is still a very young and rapidly evolving field, success stories of computationally designed proteins highlight future prospects of this field. Nonetheless, despite landmark achievements, the success rate of the current computational approaches remains low, and designed enzymes are often way less efficient than their natural counterparts. Therefore, several limitations of the CPD still need to be addressed to improve its efficiency, predictability and reliability. Herein, we present our methodological advances in the CPD field that enabled overcoming technological bottlenecks and hence propose innovative CPD methods to explore large sequence-conformation spaces while providing more accuracy and robustness than classical approaches. Our CPD methods speed-up search across vast sequence-conformation spaces by several orders of magnitude, find the minimum energy enzyme design and generate exhaustive lists of near-optimal sequences, defining small mutant libraries. These new methods, in rupture with classical approaches are based on efficient algorithms issued from recent research in artificial intelligence. The performance and accuracy of our computer-aided enzyme design methods have been evaluated and validated on various types of protein design problems. This work was partially funded by INRA/Région Midi-Pyrénées, IDEX Toulouse, Agreenskills and the French National Research Agency (PROTICAD, ANR-12-MONU-0015-03)

Production of medium chain fatty acid by Yarrowia lipolytica: Combining molecular design and TALEN to engineer the fatty acid synthase

Yarrowia lipolytica is a promising organism for the production of lipids of biotechnological interest and particularly for biofuel. In this study, we engineered lipid biosynthesis through rational engineering of the giant multifunctional Fatty Acid Synthase (FAS) enzyme to modulate fatty acid chain length and produce shorter fatty acids. Based on the hypothesis that the Ketoacyl Synthase (KS) domain, responsible for chain elongation in Yarrowia lipolytica, is directly involved in chain length specificity, a computer-based strategy was undertaken to re-design mutants of the Ketoacyl Synthase. Molecular modelling of this domain in interaction with a C16-acyl substrate enabled identification of a key residue from the fatty acid binding site. This site was then targeted by mutagenesis in order to modify KS fatty acid chain length specificity. To introduce point mutations in this essential gene, we applied, for the first time, the TALEN technology to Yarrowia lipolytica and demonstrated the efficiency of the technique to perform site-directed mutagenesis at a specific genomic locus. Some mutants led to a significant increase of C14 fatty acid. Thanks to the use of an elegant combination of genome editing technology and molecular modelling, this study provides for the first time, evidences that the KS domain of the fungal FASI system is directly involved in fatty acid chain length specificity

Crystal structures of bacterial peptidoglycan amidase AmpD and an unprecedented activation mechanism

9 pags, 5 figs, 2 tabsAmpD is a cytoplasmic peptidoglycan (PG) amidase involved in bacterial cell-wall recycling and in induction of β-lactamase, a key enzyme of β-lactam antibiotic resistance. AmpD belongs to the amidase-2 family that includes zinc-dependent amidases and the peptidoglycan-recognition proteins (PGRPs), highly conserved pattern-recognition molecules of the immune system. Crystal structures of Citrobacter freundii AmpD were solved in this study for the apoenzyme, for the holoenzyme at two different pH values, and for the complex with the reaction products, providing insights into the PG recognition and the catalytic process. These structures are significantly different compared with the previously reported NMR structure for the same protein. TheNMRstructure does not possess an accessible active site and shows the protein in what is proposed herein as an inactive "closed" conformation. The transition of the protein from this inactive conformation to the active "open" conformation, as seen in the x-ray structures, was studied by targeted molecular dynamics simulations, which revealed large conformational rearrangements (as much as 17 Å ) in four specific regions representing one-third of the entire protein. It is proposed that the large conformational change that would take the inactive NMR structure to the active x-ray structure represents an unprecedented mechanism for activation of AmpD. Analysis is presented to argue that this activation mechanism might be representative of a regulatory process for other intracellular members of the bacterial amidase-2 family of enzymes. © 2011 by The American Society for Biochemistry and Molecular Biology, Inc.This work was supported, in whole or in part, by the National Institutes of Health. This work was also supported by grants from the Spanish Ministry of Science and Technology (BFU2008-01711), EU-CP223111 (CARE-PNEUMO, European Union), and the COMBACT program (S-BIO-0260/2006). We acknowledge the Spanish Ministerio de Ciencia e Innovación (PI201060E013) and Consejo Superior de Investigaciones Científicas for financial support and for provision of synchrotron radiation facilitie

The Cyst-Dividing Bacterium Ramlibacter tataouinensis TTB310 Genome Reveals a Well-Stocked Toolbox for Adaptation to a Desert Environment

Ramlibacter tataouinensis TTB310T (strain TTB310), a betaproteobacterium isolated from a semi-arid region of South Tunisia (Tataouine), is characterized by the presence of both spherical and rod-shaped cells in pure culture. Cell division of strain TTB310 occurs by the binary fission of spherical “cyst-like” cells (“cyst-cyst” division). The rod-shaped cells formed at the periphery of a colony (consisting mainly of cysts) are highly motile and colonize a new environment, where they form a new colony by reversion to cyst-like cells. This unique cell cycle of strain TTB310, with desiccation tolerant cyst-like cells capable of division and desiccation sensitive motile rods capable of dissemination, appears to be a novel adaptation for life in a hot and dry desert environment. In order to gain insights into strain TTB310's underlying genetic repertoire and possible mechanisms responsible for its unusual lifestyle, the genome of strain TTB310 was completely sequenced and subsequently annotated. The complete genome consists of a single circular chromosome of 4,070,194 bp with an average G+C content of 70.0%, the highest among the Betaproteobacteria sequenced to date, with total of 3,899 predicted coding sequences covering 92% of the genome. We found that strain TTB310 has developed a highly complex network of two-component systems, which may utilize responses to light and perhaps a rudimentary circadian hourglass to anticipate water availability at the dew time in the middle/end of the desert winter nights and thus direct the growth window to cyclic water availability times. Other interesting features of the strain TTB310 genome that appear to be important for desiccation tolerance, including intermediary metabolism compounds such as trehalose or polyhydroxyalkanoate, and signal transduction pathways, are presented and discussed

Utilisation et évaluation économique des milieux chromogènes pour le diagnostic des infections urinaires en milieu hospitalier

TOURS-BU Sciences Pharmacie (372612104) / SudocSudocFranceF

Effect of contextual knowledge on spatial layout extrapolation

International audienceBoundary extension (BE) refers to the tendency to remember a previously perceived scene with a greater spatial expanse. This phenomenon is described as resulting from different sources of information: external (i.e., visual) and internally driven (i.e., amodal, conceptual, and contextual) information. Although the literature has emphasized the role of top-down expectations to account for layout extrapolation, their effect has rarely been tested experimentally. In this research, we attempted to determine how visual context affects BE, as a function of scene exposure duration (long, short). To induce knowledge about visual context, the memorization phase of the camera distance paradigm was preceded by a preexposure phase, during which each of the to-be-memorized scenes was presented in a larger spatial framework. In an initial experiment, we examined the effect of contextual knowledge with presentation duration, allowing for in-depth processing of visual information during encoding (i.e., 15 s). The results indicated that participants exposed to the preexposure showed decreased BE, and displayed no directional memory error in some conditions. Because the effect of context is known to occur at an early stage of scene perception, in a second experiment we sought to determine whether the effect of a preview occurs during the first fixation on a visual scene. The results indicated that BE seems not to be modulated by this factor at very brief presentation durations. These results are discussed in light of current visual scene representation theories

Novel proteases and uses thereof

The present invention relates to novel proteases, more particularly to protease variants having improved thermostability compared to the protease of SEQ ID N°1 and the uses thereof for degrading polyester containing material, such as plastic products. The proteases of the invention are particularly suited to degrade polylactic acid, and material containing polylactic acid

Deterministic search methods for computational protein design

One main challenge in Computational Protein Design (CPD) lies in the exploration of the amino-acid sequence space, while considering, to some extent, side chain flexibility. The exorbitant size of the search space urges for the development of efficient exact deterministic search methods enabling identification of low-energy sequence-conformation models, corresponding either to the global minimum energy conformation (GMEC) or an ensemble of guaranteed near-optimal solutions. In contrast to stochastic local search methods that are not guaranteed to find the GMEC, exact deterministic approaches always identify the GMEC and prove its optimality in finite but exponential worst-case time. After a brief overview on these two classes of methods, we discuss the grounds and merits of four deterministic methods that have been applied to solve CPD problems. These approaches are based either on the Dead-End-Elimination theorem combined with A* algorithm (DEE/A*), on Cost Function Networks algorithms (CFN), on Integer Linear Programming solvers (ILP) or on Markov Random Fields solvers (MRF). The way two of these methods (DEE/A* and CFN) can be used in practice to identify low-energy sequence-conformation models starting from a pairwise decomposed energy matrix is detailed in this review