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Outcomes of weight bands exercise regarding weak seniors: A deliberate assessment and meta-analysis regarding randomised governed research.
8 less then |R| less then 1). Nintedanib By using the flow cytometer, high-yielding P. pastoris cells were efficiently screened from a mixture of cells. The expression level of phytase of the selected high-fluorescence strains was 4.09 times higher than that of the low-fluorescence strains after 120 h of methanol induction. By detecting the EGFP fluorescence intensity instead of detecting the expression level and activity of the recombinant proteins in the recombinant strains, the method developed by the present study possesses the greatly improved performance of convenience and versatility in screening high-yielding P. pastoris strains. Combining the method with high-throughput screening instruments and technologies, such as flow cytometer and droplet microfluidics, the speed and throughput of this method will be further increased. This method will provide a simple and rapid approach for screening and obtaining P. pastoris with high abilities to express recombinant proteins.Bacillus subtilis is a model strain for studying the physiological and biochemical mechanisms of microorganism, and is also a good chassis cell for industrial application to produce biological agents such as small molecule compounds, bulk chemicals, industrial enzymes, precursors of drugs and health product. In recent years, studies on metabolic engineering methods and strategies of B. subtilis have been increasingly reported, providing good tools and theoretical references for using it as chassis cells to produce biological agents. This review provides information on systematically optimizing the Bacillus subtilis chassis cell by regulating global regulatory factors, simplifying and optimizing the genome, multi-site and multi-dimensional regulating, dynamic regulating through biosensors, membrane protein engineering. For producing the protein reagent, the strain is optimized by optimizing the promoters, signal peptides, secretion components and building the expression system without chemical inducers. In addition, this review also prospects the important issues and directions that need to be focused on in the further optimization of B. subtilis in industrial production.Transcription factor-based biosensors (TFBs) play an essential role in metabolic engineering and synthetic biology. TFBs sense the metabolite concentration signals and convert them into specific signal output. They hold high sensitivity, strong specificity, brief analysis speed, and are widely used in response to target metabolites. Here we reviewe the principles of TFBs, the application examples, and challenges faced in recent years in microbial cells, including detecting target metabolite concentrations, high-throughput screening, adaptive laboratory evolutionary selection, and dynamic control. Simultaneously, to overcome the challenges in the application, we also focus on reviewing the performance tuning strategies of TFBs, mainly including traditional and computer-aided tuning strategies. We also discuss the opportunities and challenges that TFBs may face in practical applications, and propose the future research trend.The development and implement of microbial chassis cells can provide excellent cell factories for diverse industrial applications, which help achieve the goal of environmental protection and sustainable bioeconomy. The synthetic biology strategy of Design-Build-Test-Learn (DBTL) plays a crucial role on rational and/or semi-rational construction or modification of chassis cells to achieve the goals of "Building to Understand" and "Building for Applications". In this review, we briefly comment on the technical development of the DBTL cycle and the research progress of a few model microorganisms. We mainly focuse on non-model bacterial cell factories with potential industrial applications, which possess unique physiological and biochemical characteristics, capabilities of utilizing one-carbon compounds or of producing platform compounds efficiently. We also propose strategies for the efficient and effective construction and application of synthetic microbial cell factories securely in the synthetic biology era, which are to discover and integrate the advantages of model and non-model industrial microorganisms, to develop and deploy intelligent automated equipment for cost-effective high-throughput screening and characterization of chassis cells as well as big-data platforms for storing, retrieving, analyzing, simulating, integrating, and visualizing omics datasets at both molecular and phenotypic levels, so that we can build both high-quality digital cell models and optimized chassis cells to guide the rational design and construction of microbial cell factories for diverse industrial applications.Genome-scale metabolic network model (GSMM) is an extremely important guiding tool in the targeted modification of industrial microbial strains, which helps researchers to quickly obtain industrial microbes with specific traits and has attracted increasing attention. Here we reviewe the development history of GSMM and summarized the construction method of GSMM. Furthermore, the development and application of GSMM in industrial microorganisms are elaborated by using four typical industrial microorganisms (Bacillus subtilis, Escherichia coli, Corynebacterium glutamicum, and Saccharomyces cerevisiae) as examples. In addition, prospects in the development trend of GSMM are proposed.Microbial oils are potential resources of fuels and food oils in the future. In recent years, with the rapid development of systems biology technology, understanding the physiological metabolism and lipid accumulation characteristics of oleaginous microorganisms from a global perspective has become a research focus. As an important tool for systems biology research, omics technology has been widely used to reveal the mechanism of high-efficiency production of oils by oleaginous microorganisms. This provides a basis for rational genetic modification and fermentation process control of oleaginous microorganisms. In this article, we summarize the application of omics technology in oleaginous microorganisms, introduced the commonly used sample pre-processing and data analysis methods for omics analysis of oleaginous microorganisms, reviewe the researches for revealing the mechanism of efficient lipid production by oleaginous microorganisms based on omics technologies including genomics, transcriptomics, proteomics (modification) and metabolomics (lipidomics), as well as mathematical models based on omics data.
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