Rice(Oryza sativa)is a staple food for more than half of the world's population and a critical crop for global agriculture.Understanding the regulatory mechanisms that control gene expression in the rice genome is...Rice(Oryza sativa)is a staple food for more than half of the world's population and a critical crop for global agriculture.Understanding the regulatory mechanisms that control gene expression in the rice genome is fundamental for advancing agricultural productivity and food security.In mechanism,cis-regulatory elements(including promoters,enhancers,silencers,and insulators)are key DNA sequences whose activities determine the spatial and temporal expression patterns of nearby genes(Yocca and Edger,2022;Schmitz et al.,2022).展开更多
Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories.However,when regulatory...Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories.However,when regulatory sequence expression strengths are characterized using only a few reporter genes,they may not be applicable across diverse genes.This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels.To address this,our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels.We combined 41 commonly-used metabolic genes with 15 regulatory sequences,yielding an expression dataset encompassing 520 unique combinations.This dataset highlighted substantial variation in protein expression level under identical regulatory sequences,with relative expression levels ranging from 2.8 to 176-fold.It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins.Utilizing this dataset,we have developed various machine learning models and discovered that the integration of promoter regions,ribosome binding sites,and coding sequences significantly improves the accuracy of predicting protein expression levels,with a Spearman correlation coefficient of 0.72,where the promoter sequence exerts a predominant influence.Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.展开更多
OBJECTIVE: To screen the 5' regulatory region of the aldose reductase (AR) gene for genetic variabilities causing changes in protein expression and affecting the promoter function. METHODS: The screenings were car...OBJECTIVE: To screen the 5' regulatory region of the aldose reductase (AR) gene for genetic variabilities causing changes in protein expression and affecting the promoter function. METHODS: The screenings were carried out by polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP). All SSCP variants were submitted for DNA sequencing and inserted into the plasmid chloromycetin acetyl transferase (CAT) enhancer vector. The constructs were used to transfect Hela cells, and CAT assays were performed to assess promoter activity. Gel mobility shift and footprinting assays were also performed to determine the interaction between the DNA and nuclear proteins. RESULTS: Two polymorphisms, C (-106) T and C (-12) G, were identified in the regulatory region in 123 Chinese control subjects and 145 patients with type 2 diabetes mellitus. The frequencies of genotypes WT/WT, WT/C (-12) G and WT/C (-106) T were not significantly different between the subjects and patients. In the patients with and without retinopathy, frequencies of WT/C (-106) T were 31.5% and 17.5% (P 0.05) respectively. The total frequency of WT/C (-12) G and WT/C (-106) T in patients with retinopathy was 41.8%, significantly higher than that (20.0%) in patients without retinopathy (P展开更多
基金supported by the National Natural Science Foundation of China(32070656)。
文摘Rice(Oryza sativa)is a staple food for more than half of the world's population and a critical crop for global agriculture.Understanding the regulatory mechanisms that control gene expression in the rice genome is fundamental for advancing agricultural productivity and food security.In mechanism,cis-regulatory elements(including promoters,enhancers,silencers,and insulators)are key DNA sequences whose activities determine the spatial and temporal expression patterns of nearby genes(Yocca and Edger,2022;Schmitz et al.,2022).
基金supported by the National Key Research and Development Program of China(2021YFC2100200)the National Natural Science Foundation of China(12326611,32101186)Tianjin Synthetic Biotechnology Innovation Capacity Improvement Projects(TSBICIP-PTJJ-007,TSBICIP-PTJS-003,TSBICIP-PTJJ-012).
文摘Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories.However,when regulatory sequence expression strengths are characterized using only a few reporter genes,they may not be applicable across diverse genes.This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels.To address this,our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels.We combined 41 commonly-used metabolic genes with 15 regulatory sequences,yielding an expression dataset encompassing 520 unique combinations.This dataset highlighted substantial variation in protein expression level under identical regulatory sequences,with relative expression levels ranging from 2.8 to 176-fold.It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins.Utilizing this dataset,we have developed various machine learning models and discovered that the integration of promoter regions,ribosome binding sites,and coding sequences significantly improves the accuracy of predicting protein expression levels,with a Spearman correlation coefficient of 0.72,where the promoter sequence exerts a predominant influence.Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.
文摘OBJECTIVE: To screen the 5' regulatory region of the aldose reductase (AR) gene for genetic variabilities causing changes in protein expression and affecting the promoter function. METHODS: The screenings were carried out by polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP). All SSCP variants were submitted for DNA sequencing and inserted into the plasmid chloromycetin acetyl transferase (CAT) enhancer vector. The constructs were used to transfect Hela cells, and CAT assays were performed to assess promoter activity. Gel mobility shift and footprinting assays were also performed to determine the interaction between the DNA and nuclear proteins. RESULTS: Two polymorphisms, C (-106) T and C (-12) G, were identified in the regulatory region in 123 Chinese control subjects and 145 patients with type 2 diabetes mellitus. The frequencies of genotypes WT/WT, WT/C (-12) G and WT/C (-106) T were not significantly different between the subjects and patients. In the patients with and without retinopathy, frequencies of WT/C (-106) T were 31.5% and 17.5% (P 0.05) respectively. The total frequency of WT/C (-12) G and WT/C (-106) T in patients with retinopathy was 41.8%, significantly higher than that (20.0%) in patients without retinopathy (P
