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Taxadiene is an important precursor in taxol biosynthesis pathway, but its biosynthesis in eukaryotic cell factories is limited, which seriously hinders the biosynthesis of taxol. In this study, it is found that there was the catalysis compartmentalization between two key exogenous enzymes of geranylgeranyl pyrophosphate synthase and taxadiene synthase (TS) for taxadiene synthesis progress, due to their different subcellular localization. Firstly, the enzyme-catalysis compartmentalization was overcome by means of the intracellular relocation strategies of taxadiene synthase, including N-terminal truncation of taxadiene synthase and enzyme fusion of GGPPS-TS. With the help of two strategies for enzyme relocation, the taxadiene yield was increased by 21% and 54% respectively, among them the GGPPS-TS fusion enzyme is more effective. Further, the expression of GGPPS-TS fusion enzyme was improved via the multi-copy plasmid, resulting that the taxadiene titer was increased by 38% to 21.8 mg/L at shake-flask level. Finally, the maximum taxadiene titer of 184.2 mg/L was achieved by optimization of the fed-batch fermentation conditions in 3 L bioreactor, which is the highest reported titer of taxadiene biosynthesis accomplished in eukaryotic microbes. This study provides a successful example for improving biosynthesis of complex natural products by solving the critical problem of multistep enzymes catalysis compartmentalization.

As the main product of livestock, muscle itself plays an irreplaceable role in maintaining animal body movement and regulating metabolism. Therefore, it is of great significance to explore its growth, development and regeneration to improve the meat yield and quality of livestock. In this study, we attempted to use RNA-seq and ATAC-seq techniques to identify differentially expressed genes (DEGs) specifically expressed in bovine skeletal muscle as potential candidates for studying the regulatory mechanisms of muscle development. Microarray data from 8 tissue samples were selected from the GEO database for analysis. First, we obtained gene modules related to each tissue through WGCNA analysis. Through Gene Ontology (GO) functional annotation, the module of lightyellow (MElightyellow) was closely related to muscle development, and 213 hub genes were screened as follow-up research targets. Further, the difference analysis showed that, except for PREB, all other candidate hub genes were up-regulated (muscle group vs. other-group). ATAC-seq analysis showed that muscle-specific accessible chromatin regions were mainly located in promoter of genes related to muscle structure development (GO:0061061), muscle cell development (GO:0055001) and muscle system process (GO:0003012), which were involved in cAMP, CGMP-PKG, MAPK, and other signaling pathways. Next, we integrated the results of RNA-seq and ATAC-seq analysis, and 54 of the 212 candidate hub genes were identified as key regulatory genes in skeletal muscle development. Finally, through motif analysis, 22 of the 54 key genes were found to be potential target genes of transcription factor MEF2C. Including CAPN3, ACTN2, MB, MYOM3, SRL, CKM, ALPK3, MAP3K20, UBE2G1, NEURL2, CAND2, DOT1L, HRC, MAMSTR, FSD2, LRRC2, LSMEM1, SLC29A2, FHL3, KLHL41, ATXN7L2, and PDRG1. This provides a potential reference for studying the molecular mechanism of skeletal muscle development in mammals.

Polyethylene terephthalate (PET) biodegradation is regarded as an environmentally friendly degradation method. In this study, an artificial microbial consortium composed of Rhodococcus jostii, Pseudomonas putida and two metabolically engineered Bacillus subtilis was constructed to degrade PET. First, a two-species microbial consortium was constructed with two engineered B. subtilis that could secrete PET hydrolase (PETase) and monohydroxyethyl terephthalate hydrolase (MHETase), respectively; it could degrade 13.6% (weight loss) of the PET film within 7 days. A three-species microbial consortium was further obtained by adding R. jostii to reduce the inhibition caused by terephthalic acid (TPA), a breakdown product of PET. The weight of PET film was reduced by 31.2% within 3 days, achieving about 17.6% improvement compared with the two-species microbial consortium. Finally, P. putida was introduced to reduce the inhibition caused by ethylene glycol (EG), another breakdown product of PET, obtaining a four-species microbial consortium. With the four-species consortium, the weight loss of PET film reached 23.2% under ambient temperature. This study constructed and evaluated the artificial microbial consortia in PET degradation, which demonstrated the great potential of artificial microbial consortia in the utilization of complex substrates, providing new insights for biodegradation of complex polymers.

Lactic acid, a metabolic by-product of host and intestinal microbiota, has been recovered as an active signal molecule in the immune system. In this study, a lactic acid biosynthesis pathway that directly produces lactic acid from glucose rather than ethanol with high production was reconstructed in Saccharomyces cerevisiae. The engineered S. cerevisiae showed anti-inflammatory activity in dextran sulfate sodium (DSS)-induced mice with improved histological damage, increased mucosal barrier, and decreased intestinal immune response. Lactic acid regulated the macrophage polarization state and inhibited the expression of pro-inflammatory cytokines in vivo and in vitro. Increasing the macrophage monocarboxylic acid transporter-mediated active lactic acid uptake suppressed the excessive activation of the NLRP3 inflammasome and the downstream caspase-1 pathway in macrophages. Moreover, lactic acid promoted histone H3K9 acetylation and histone H3K18 lactylation. Meanwhile, the engineered S. cerevisiae altered the diversity and composition of the intestinal microbiota and changed the abundance of metabolic products in mice with colitis. In conclusion, this study shows that the application of engineered S. cerevisiae attenuated DSS-induced colitis in mice via suppressing macrophage pyroptosis and modulating the intestinal microbiota, which is an effective and safe treatment strategy for ulcerative colitis.

Deep learning is progressively emerging as a vital tool for image reconstruction in light field microscopy. The present review provides a comprehensive examination of the latest advancements in light field image reconstruction techniques based on deep learning algorithms. First, the review briefly introduced the concept of light field and deep learning techniques. Following that, the application of deep learning in light field image reconstruction was discussed. Subsequently, we classified deep learning-based light field microscopy reconstruction algorithms into three types based on the contribution of deep learning, including fully deep learning-based method, deep learning enhanced raw light field image with numerical inversion volumetric reconstruction, and numerical inversion volumetric reconstruction with deep learning enhanced resolution, and comprehensively analyzed the features of each approach. Finally, we discussed several challenges, including deep neural approaches for increasing the accuracy of light field microscopy to predict temporal information, methods for obtaining light field training data, strategies for data enhancement using existing data, and the interpretability of deep neural networks.