Designing an optimal microbial cell factory often requires overexpression, knock-down, and knock-out of multiple gene targets. Unfortunately, such rewiring of cellular metabolism is often carried out ...sequentially and with low throughput. Here, we report a combinatorial metabolic engineering strategy based on an orthogonal tri-functional CRISPR system that combines transcriptional activation, transcriptional interference, and gene deletion (CRISPR-AID) in the yeast Saccharomyces cerevisiae. This strategy enables perturbation of the metabolic and regulatory networks in a modular, parallel, and high-throughput manner. We demonstrate the application of CRISPR-AID not only to increase the production of β-carotene by 3-fold in a single step, but also to achieve 2.5-fold improvement in the display of an endoglucanase on the yeast surface by optimizing multiple metabolic engineering targets in a combinatorial manner.
In this paper, an improved ant colony optimization(ICMPACO) algorithm based on the multi-population strategy, co-evolution mechanism, pheromone updating strategy, and pheromone diffusion mechanism is ...proposed to balance the convergence speed and solution diversity, and improve the optimization performance in solving the large-scale optimization problem. In the proposed ICMPACO algorithm, the optimization problem is divided into several sub-problems and the ants in the population are divided into elite ants and common ants in order to improve the convergence rate, and avoid to fall into the local optimum value. The pheromone updating strategy is used to improve optimization ability. The pheromone diffusion mechanism is used to make the pheromone released by ants at a certain point, which gradually affects a certain range of adjacent regions. The co-evolution mechanism is used to interchange information among different sub-populations in order to implement information sharing. In order to verify the optimization performance of the ICMPACO algorithm, the traveling salesmen problem (TSP) and the actual gate assignment problem are selected here. The experiment results show that the proposed ICMPACO algorithm can effectively obtain the best optimization value in solving TSP and effectively solve the gate assignment problem, obtain better assignment result, and it takes on better optimization ability and stability.
Conspectus Harnessing biocatalysts for novel abiological transformations is a longstanding goal of synthetic chemistry. Combining the merits of biocatalysis and photocatalysis allows for selective ...transformations fueled by visible light and offers many advantages including new reactivity, high enantioselectivity, greener syntheses, and high yields. Photoinduced electron or energy transfer enables synthetic methodologies that complement conventional two electron processes or offer orthogonal pathways for developing new reactions. Enzymes are well suited and can be tuned by directed evolution to exert control over open-shell intermediates, thereby suppressing undesirable reactions and delivering high chemo- and stereoselectivities. Within the past decade, the combination of biocatalysis and photocatalysis was mainly focused on exploiting light-regenerated cofactors to function native enzymatic activity. However, recent developments have demonstrated that the combination can unlock new-to-nature chemistry. Particularly, the discovery and application of new strategies are well poised to expand the applications of photobiocatalysis. In the past five years, our lab has been studying the combinations of photocatalysis and biocatalysis that can be applied to create new synthetic methodologies and solve challenges in synthetic organic chemistry. Our efforts have expanded the strategies for combining external photocatalysts with enzymes through the construction of a synergistic cooperative stereoconvergent reduction system consisting of photosensitized energy transfer and ene-reductase-catalyzed alkene reduction. Additionally, our efforts have also extended the capability of cofactor-dependent photoenzymatic systems to include enantioselective bimolecular radical hydroalkylations of alkenes by irradiating electron donor–acceptor complexes comprised of enzymatic redox active cofactors and unnatural substrates. In this Account, we highlight strategies developed by our group and others for combining biocatalysis and photocatalysis with the aim of introducing non-natural reactivity to enzymes. Presently, strategies applied to achieve this goal include the repurposing of natural photoenzymes, the elucidation of new photoreactivity within cofactor-dependent enzymes, the combination of external photocatalysts with enzymes, and the construction of artificial photoenzymes. By demonstrating the successful applications of these strategies for achieving selective new-to-nature transformations, we hope to spur interest in expanding the scope of photobiocatalytic systems through the use and extension of these strategies and creation of new strategies. Additionally, we hope to elucidate the intuition in synergizing the unique capabilities of biocatalysis and photocatalysis so that photobiocatalysis can be recognized as a potential solution to difficult challenges in synthetic organic chemistry.
Multi-modal multi-objective optimization problem (MMOPs) has attracted more and more attention in evolutionary computing recently. It is not easy to solve these problems using the existing ...evolutionary algorithms. The non-dominated solution sorting genetic algorithm (NSGA-II) has poor PS distribution and convergence. In this paper, an enhanced fast NSGA-II based on a special congestion strategy and adaptive crossover strategy, namely ASDNSGA-II is proposed. In the ASDNSGA-II, the strategy with a special congestion degree is used to improve the selection strategy. Then a new adaptive crossover strategy is designed by evaluating the advantages and disadvantages of the SBX crossover strategy with the ability to solve high dimensions and the BLX-α with the ability of Pareto solution to produce offspring solutions. These can ensure the generation of offspring solutions around individuals with large crowding degrees and balance the convergence and diversity of decision space and object space. It can improve PS distribution and convergence and maintain PF precision. Eight functions of MMF1-MMF8 from the CEC2020 are selected to prove the effectiveness of the ASDNSGA-II. By comparing several latest multi-modal multi-objective evolutionary algorithms, the results show that the ASDNSGA-II can effectively find the global Pareto solution set and improve the distribution and convergence of PS.
Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and ...entertainment settings. MI data is generated when a subject imagines the movement of a limb. This paper reviews state-of-the-art signal processing techniques for MI EEG-based BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used. It also summarizes the main applications of EEG-based BCIs, particularly those based on MI data, and finally presents a detailed discussion of the most prevalent challenges impeding the development and commercialization of EEG-based BCIs.
•Carbon-felt addition increased the methane production in anaerobic sludge digestion.•Hydrolysis and acidification process was enhanced in the MEC reactor.•A voltage on electrode further improved the ...performance of the anaerobic digestion.•DIET between VFA-oxidizing bacteria and methanogens was promoted in MEC reactor.
Increase of methanogenesis in methane-producing microbial electrolysis cells (MECs) is frequently believed as a result of cathodic reduction of CO2. Recent studies indicated that this electromethanogenesis only accounted for a little part of methane production during anaerobic sludge digestion. Instead, direct interspecies electron transfer (DIET) possibly plays an important role in methane production. In this study, anaerobic digestion of sludge were investigated in a single-chamber MEC reactor, a carbon-felt supplemented reactor and a common anaerobic reactor to evaluate the effects of DIET on the sludge digestion. The results showed that adding carbon felt into the reactor increased 12.9% of methane production and 17.2% of sludge reduction. Imposing a voltage on the carbon felt further improved the digestion. Current calculation showed that the cathodic reduction only contributed to 27.5% of increased methane production. Microbial analysis indicated that DIET played an important role in the anaerobic sludge digestion in the MEC.
Differential evolution (DE) algorithm is prone to premature convergence and local optimization in solving complex optimization problems. In order to solve these problems, the belief space strategy, ...generalized opposition-based learning strategy and parameter adaptive strategy are introduced into DE to propose an improved adaptive DE algorithm, namely ACDE/F in this paper. In the ACDE/F, the idea of cultural algorithm and different mutation strategies are introduced into belief space to balance the global exploration ability and local optimization ability. A generalized opposition-based learning strategy is designed to improve the convergence speed of local optimization and increase the population diversity. A parameter adaptive adjustment strategy is developed to reasonably adjust the mutation factor and crossover factor to avoid to fall into local optimum. In order to test and verify the optimization performance of the ACDE/F, the unimodal functions and multimodal functions from CEC 2005 and CEC 2017 are selected in here. The experiment results show that the ACDE/F has better optimization performance than the DE with different strategies, WMSDE, DE2/F, GOAL-RNADE and DE/best/1. In addition, the actual gate allocation problem is selected to verify the practical application ability of the ACDE/F. The ACDE/F obtains the maximum allocation rate and average allocation rate of 98% and 96.8%, respectively. Therefore, the experimental results show that the ACDE/F can effectively solve the gate allocation problem and obtain ideal gate allocation results.
Classification is a frequently encountered data mining problem. Decision tree techniques have been widely used to build classification models as such models closely resemble human reasoning and are ...easy to understand. Many real-world classification problems are cost-sensitive, meaning that different types of misclassification errors are not equally costly. Since different decision trees may excel under different cost settings, a set of non-dominated decision trees should be developed and presented to the decision maker for consideration, if the costs of different types of misclassification errors are not precisely determined. This paper proposes a multi-objective genetic programming approach to developing such alternative Pareto optimal decision trees. It also allows the decision maker to specify partial preferences on the conflicting objectives, such as false negative vs. false positive, sensitivity vs. specificity, and recall vs. precision, to further reduce the number of alternative solutions. A diabetes prediction problem and a credit card application approval problem are used to illustrate the application of the proposed approach.
Enzymes are increasingly explored for use in asymmetric synthesis
, but their applications are generally limited by the reactions available to naturally occurring enzymes. Recently, interest in ...photocatalysis
has spurred the discovery of novel reactivity from known enzymes
. However, so far photoinduced enzymatic catalysis
has not been used for the cross-coupling of two molecules. For example, the intermolecular coupling of alkenes with α-halo carbonyl compounds through a visible-light-induced radical hydroalkylation, which could provide access to important γ-chiral carbonyl compounds, has not yet been achieved by enzymes. The major challenges are the inherent poor photoreactivity of enzymes and the difficulty in achieving stereochemical control of the remote prochiral radical intermediate
. Here we report a visible-light-induced intermolecular radical hydroalkylation of terminal alkenes that does not occur naturally, catalysed by an 'ene' reductase using readily available α-halo carbonyl compounds as reactants. This method provides an efficient approach to the synthesis of various carbonyl compounds bearing a γ-stereocentre with excellent yields and enantioselectivities (up to 99 per cent yield with 99 per cent enantiomeric excess), which otherwise are difficult to access using chemocatalysis. Mechanistic studies suggest that the formation of the complex of the substrates (α-halo carbonyl compounds) and the 'ene' reductase triggers the enantioselective photoinduced radical reaction. Our work further expands the reactivity repertoire of biocatalytic, synthetically useful asymmetric transformations by the merger of photocatalysis and enzyme catalysis.
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