title: Relationship between promoter sequence and its strength in gene expression.
abstract: Promoter strength, or activity, is important in genetic engineering and synthetic biology. A constitutive promoter with a certain strength for one given RNA can often be reused for other RNAs. Therefore, the strength of one promoter is mainly determined by its nucleotide sequence. One of the main difficulties in genetic engineering and synthetic biology is how to control the expression of a certain protein at a given level. One usually used way to achieve this goal is to choose one promoter with a suitable strength which can be employed to regulate the rate of transcription, which then leads to the required level of protein expression. For this purpose, so far, many promoter libraries have been established experimentally. However, theoretical methods to predict the strength of one promoter from its nucleotide sequence are desirable. Such methods are not only valuable in the design of promoter with specified strength, but also meaningful to understand the mechanism of promoter in gene transcription. In this study, through various tests, a theoretical model is presented to describe the relationship between promoter strength and nucleotide sequence. Our analysis shows that promoter strength is greatly influenced by nucleotide groups with three adjacent nucleotides in their sequences. Meanwhile, nucleotides in different regions of promoter sequence have different effects on promoter strength. Based on experimental data for E. coli promoters, our calculations indicate that nucleotides in the -10 region, the -35 region, and the discriminator region of a promoter sequence are more important for determining promoter strength than those in the spacing region. With model parameter values obtained by fitting to experimental data, four promoter libraries are theoretically built for the corresponding experimental environments under which data for promoter strength in gene expression has been measured previously.
authors.affiliation: Shanghai Key Laboratory for Contemporary Applied Mathematics, Centre for Computational Systems Biology, School of Mathematical Sciences, Fudan University, 200433, Shanghai, China.
authors.forename: Jingwei
authors.initials: J
authors.lastname: Li
authors.forename: Yunxin
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D004269:DNA, Bacterial / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D012321:DNA-Directed RNA Polymerases / Q000378:metabolism; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D015870:Gene Expression; D005818:Genetic Engineering; D008954:Models, Biological; D011401:Promoter Regions, Genetic; D058615:Synthetic Biology; D013816:Thermodynamics
chemical_list: D004269:DNA, Bacterial; D012321:DNA-Directed RNA Polymerases