Engineering Escherichia coli for high-yielding 2,5-Dimethylpyrazine synthesis from L-Threonine by reconstructing metabolic pathways and enhancing cofactors regeneration.

2,5-Dimethylpyrazine (2,5-DMP) is important pharmaceutical raw material and food flavoring agent. Recently, engineering microbes to produce 2,5-DMP has become an attractive alternative to chemical synthesis approach. In this study, metabolic engineering strategies were used to optimize the modified Escherichia coli BL21 (DE3) strain for efficient synthesis of 2,5-DMP using L-threonine dehydrogenase (EcTDH) from Escherichia coli BL21, NADH oxidase (EhNOX) from Enterococcus hirae, aminoacetone oxidase (ScAAO) from Streptococcus cristatus and L-threonine transporter protein (EcSstT) from Escherichia coli BL21, respectively. We further optimized the reaction conditions for synthesizing 2,5-DMP. In optimized conditions, the modified strain can convert L-threonine to obtain 2,5-DMP with a yield of 2897.30 mg/L. Therefore, the strategies used in this study contribute to the development of high-level cell factories for 2,5-DMP.

The role of cellular senescence-related genes in Asthma: Insights from bioinformatics and animal experiments.

BACKGROUND: Asthma is a heterogeneous chronic respiratory disease, affecting about 10% of the global population. Cellular senescence is a multifaceted phenomenon defined as the irreversible halt of the cell cycle, commonly referred to as the senescence-associated secretory phenotype. Recent studies suggest that cellular senescence may play a role in asthma. This study aims to dissect the role and biological mechanisms of CSRGs in asthma, enhancing our understanding of the progression of asthma. METHODS: The study utilized the GSE147878 dataset, employing methods like WGCNA, Differential analysis, Cibersort, GO, KEGG, unsupervised clustering, and GSVA to explore CSRGs functions and immune cell patterns in asthma. Machine learning identified key diagnostic genes, validated externally with the GSE165934 dataset and through qRT-PCR and WB experiments in animal models. RESULT: From the GSE147878 dataset, 24 CSRGs were identified, highlighting their role in immune and inflammatory processes in asthma. Differences in CD4 naive T cells and activated dendritic cells between asthma and control groups underscored CSRGs' role in immune regulation. Cluster analysis revealed two distinct asthma patient groups with unique immune microenvironments. Machine learning identified five genes, leading to a TF-miRNA-mRNA network and singling out RHOA and RBM39 as key diagnostic genes, which were experimentally validated. Finally, a nomogram was created based on these genes. CONCLUSION: This study, utilizing bioinformatics and animal experiments, identified RHOA and RBM39 as key diagnostic genes for asthma, providing new insights into the potential role and biological mechanisms of CSRGs in asthma.

Efficient expression of novel glutamate decarboxylases and high level production of γ-aminobutyric acid catalyzed by engineered Escherichia coli.

Glutamate decarboxylase (GAD) has the potential of converting L-glutamate to gamma-aminobutyric acid (GABA), which is an important non-proteinogenic amino acid that has a potential use as food additive or dietary supplement for its physiological functions. A novel pyridoxal 5'-phosphate (PLP)-dependent glutamate decarboxylase (LsGAD) was cloned from GRAS (generally recognized as safe) Lactobacillus senmaizukei by genome mining and efficiently expressed in Escherichia coli BL21. The LsGAD displayed excellent temperature property, pH property and kinetic parameters compared with the probe LbGAD and the other GADs. By increasing the copy number of the LsGAD encoding gene, the expression level of LsGAD and the biosynthesis yield of GABA were increased, which was near to 2 times of that was expressed in single copy. These results established a solid foundation for increasing the added value of L-glutamate and the biosynthesis of GABA.

Association of meteorological factors with pediatric acute appendicitis in China: A 7-year retrospective analysis.

Acute appendicitis (AA) affects between 7% and 8% of the world population and is one of the most common general surgical emergencies. The concept of seasonal patterns in the incidence of AA remains controversial. Thus, this study aimed to investigate whether meteorological factors are related to variations in the rate of pediatric AA cases at the Children's Hospital in Chongqing, China.In total, in this retrospective survey, 3436 children younger than 18 years who had been hospitalized with AA from January 1, 2008 to December 31, 2013 were enrolled, and the meteorological factors during this period were collected.Patients with AA showed a male/female ratio of 1.81:1; the highest incidence age ranged from 6 to 12 years old (P < .0001). The highest incidences of pediatric AA occurred in summer and autumn, with a peak in September and a trough in February. Pearson correlation analysis showed that the monthly mean temperature (r = 0.357, P = .001), monthly mean relative humidity (r = -0.357, P = .001), and monthly mean sunshine duration (r = 0.235, P = -0.031) were relatively weak correlated with pediatric AA. Multiple linear regression analysis indicated that pediatric AA occurrence was positively affected by monthly mean temperature (P < .0001) and negatively affected by monthly mean humidity (P < .0001) and monthly sum of sunshine (P < .0001), while monthly mean air pressure (P = .092), monthly wind speed (P = .143) and monthly precipitation (P = .297) were marginally associated with pediatric AA.Pediatric AA is associated with climatic factors. Specifically, pediatric AA is more likely related to the following meteorological conditions of: high temperature (20 °C-30 °C), low humidity, and less sunshine.