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Summary Bioproduction of optical pure (R)‐citronellal from (E/Z)‐citral at high substrate loading remains challenging. Low catalytic efficiency of (R)‐stereoselective ene reductases towards crude citral mixture is one of the major bottlenecks. Herein, a structure‐based engineering strategy was adopted to enhance the catalytic efficiency and stereoselectivity of an ene reductase (OYE2p) from Saccharomyces cerevisiae YJM1341 towards (E/Z)‐citral. On basis of homologous modelling, molecular docking analysis and alanine scanning at the binding pocket of OYE2p, a mutant Y84A was obtained with simultaneous increase in catalytic efficiency and stereoselectivity. Furthermore, site‐saturation mutagenesis of Y84 yielded seven mutants with improved activity and stereoselectivity in the (E/Z)‐citral reduction. Among them, the variant Y84V exhibited an 18.3% and 71.3% rise in catalytic efficiency (kcat/Km) for (Z)‐citral and (E)‐citral respectively. Meanwhile, the stereoselectivity of Y84V was improved from 89.2% to 98.0% in the reduction in (E/Z)‐citral. The docking analysis and molecular dynamics simulation of OYE2p and its variants revealed that the substitution Y84V enabled (E)‐citral and (Z)‐citral to bind with a smaller distance to the key hydrogen donors at a modified (R)‐selective binding mode. The variant Y84V was then co‐expressed with glucose dehydrogenase from Bacillus megaterium in E. coli D4, in which competing prim‐alcohol dehydrogenase genes were deleted to prevent the undesired reduction in the aldehyde moiety of citral and citronellal. Employing this biocatalyst, 106 g l−1 (E/Z)‐citral was completely converted into (R)‐citronellal with 95.4% ee value and a high space‐time yield of 121.6 g l−1 day−1. The work highlights the synthetic potential of Y84V, which enabled the highest productivity of (R)‐citronellal from (E/Z)‐citral in high enantiopurity so far.

Abstract Background d-Xylonic acid is a versatile platform chemical with broad potential applications as a water reducer and disperser for cement and as a precursor for 1,4-butanediol and 1,2,4-tributantriol. Microbial production of d-xylonic acid with bacteria such as Gluconobacter oxydans from inexpensive lignocellulosic feedstock is generally regarded as one of the most promising and cost-effective methods for industrial production. However, high substrate concentrations and hydrolysate inhibitors reduce xylonic acid productivity. Results The d-xylonic acid productivity of G. oxydans DSM2003 was improved by overexpressing the mGDH gene, which encodes membrane-bound glucose dehydrogenase. Using the mutated plasmids based on pBBR1MCS-5 in our previous work, the recombinant strain G. oxydans/pBBR-R3510-mGDH was obtained with a significant improvement in d-xylonic acid production and a strengthened tolerance to hydrolysate inhibitors. The fed-batch biotransformation of d-xylose by this recombinant strain reached a high titer (588.7 g/L), yield (99.4%), and volumetric productivity (8.66 g/L/h). Moreover, up to 246.4 g/L d-xylonic acid was produced directly from corn stover hydrolysate without detoxification at a yield of 98.9% and volumetric productivity of 11.2 g/L/h. In addition, G. oxydans/pBBR-R3510-mGDH exhibited a strong tolerance to typical inhibitors, i.e., formic acid, furfural, and 5-hydroxymethylfurfural. Conclusion Through overexpressing mgdh in G. oxydans, we obtained the recombinant strain G. oxydans/pBBR-R3510-mGDH, and it was capable of efficiently producing xylonic acid from corn stover hydrolysate under high inhibitor concentrations. The high d-xylonic acid productivity of G. oxydans/pBBR-R3510-mGDH made it an attractive choice for biotechnological production.

Abstract Background Photocontrol of protein activity has become a helpful strategy for regulating biological pathways. Herein, a method for the precise and reversible photocontrol of oxidase activity was developed by using the conformational change of the AsLOV2 domain. Results The AsLOV2 domain was inserted into the nonconserved sites exposed on the surface of the AdhP protein, and the alov9 fusion was successfully screened for subsequent optical experiments under the assumption that neither of these actions affected the original activity of AdhP protein. The activity of alov9 was noticeably inhibited when the fusion was exposed to 470 nm blue light and recovered within 30 min. As a result, we could precisely and reversibly photocontrol alov9 activity through the optimization of several parameters, including cofactor concentration, light intensity, and illumination time. Conclusions An efficient method was developed for the photoinhibition of enzymatic activity based on the insertion of the light-sensitive AsLOV2 domain, providing new ideas for photocontrolling metabolic pathways without carriers in the future.

Background: A NAD(P)H-dependent enoate reductase (OYE2p) from Saccharomyces cerevisiae YJM1341 was discovered by genome data mining for asymmetric reduction of (E/Z)-citral to (R)-citronellal with high enantioselectivity. Methods: This enzyme was heterologously expressed in E. coli and characterized for its biocatalytic properties. OYE2p was identified with reduction activities toward a diverse range of ɑ,β-unsaturated compounds bearing conjugated aldehyde, ketone, imide, carboxylic acid and ester. Results: OYE2p showed the highest specific activity at 40 °C and a pH optimum at 7.0-8.0. The stability of OYE2p was rather pH-independent, and the half-life time values of the enzyme at pH 6.0-8.0 were more than 257 h. With regard to the reduction of (E)-citral and (Z)-citral, OYE2p exhibited different selectivity patterns. (E)-citral was exclusively reduced to (R)-citronellal by OYE2p in ≥ 99% ee, which was independent on pH. OYE2p produced both enantiomers of citronellal from (Z)-citral, but showed (R)-citronellal formation tendency, and the ee value of (R)-citronellal was affected by pH in the reaction system. Accordingly, the ee values for (R)-citronellal formation increased with the increasing levels of E-isomer in the (E/Z)-citral mixture as well as the increase of pH. Under the reaction conditions (30 °C and pH 8.6), using purified OYE2p as catalyst, 200 mM (E/Z)-citral (an approximately 10:9 mixture of geometric E-isomer and Z-isomer) was efficiently converted to (R)-citronellal with 88.8% ee and 87.2% yield. Conclusion: All these positive features demonstrate high potential of OYE2p for practical synthesis of (R)-citronellal and in asymmetric reduction of activated alkenes. [ABSTRACT FROM AUTHOR]

To address the NSGA-III algorithm's problems of low population diversity, high computational complexity, and slow convergence rate, in this paper an enhanced NSGAIII algorithm is proposed based on adaptive scheduling. The proposed algorithm increases the diversity of Pareto solutions by utilizing a crossover-mutation operator to adapt to dynamic changes of the population number during the population evolution stage. In addition, during the reference point generation process, the number of reference points is adjusted dynamically to avoid increasing the computational complexity under the conditions of numerous reference points and the screening function loss of population individuals caused by fewer reference points. The proposed algorithm is compared with the NSGA-III algorithm and the improved NSGA-III algorithm on the platEMO platform. Experimental results demonstrate that compared to the other algorithms, the proposed algorithm reduces the number of redundant reference points to a certain extent, increases the population diversity, and improves the convergence and distribution of the Pareto solution sets. [ABSTRACT FROM AUTHOR]

Traffic flow prediction has been essential for traffic management and road network planning. However, the complex urban road network and the strong spatialtemporal correlation of traffic flow data make this problem difficult. Existing prediction methods cannot fully utilize the spatial-temporal correlations in traffic flow data. Therefore, we propose a deep learning model called ResGAT-ABiGRU which combines Residual Network (ResNet), Graph Attention Network (GAT), Attention Mechanism, and the Bidirectional Gated Recurrent Unit (BiGRU). Firstly, GAT is used to capture the spatial correlations of traffic flow data, and then the time characteristics are extracted by Bidirectional GRU. Secondly, the ResNet module stacks multiple GAT layers and designs the attention mechanism to assign weights for different flow sequences to further capture spatial relations. Finally, we obtain the output through the fully connected layers. Validation traffic data from California, USA, is used for verification. The results show that the ResGAT-ABiGRU model proposed in this paper has higher prediction accuracy. Compared the model's performance with the Gated Recurrent Unit (GRU) baseline model, and the root means square error (RMSE) is reduced by 22.75%, and compared to the T-gcn model, the root mean square error is reduced by 3.29%. [ABSTRACT FROM AUTHOR]