DNA structural and physical properties reveal peculiarities in promoter sequences of the bacterium Escherichia coli K-12

被引:0
作者
Gustavo Sganzerla Martinez
Scheila de Ávila e Silva
Aditya Kumar
Ernesto Pérez-Rueda
机构
[1] Universidade de Caxias Do Sul,Programa de Pós
[2] Tezpur University,Graduação Em Biotecnologia
[3] Universidad Nacional Autónoma de México,Department of Molecular Biology and Biotechnology
[4] Unidad Académica de Yucatán. Mérida,Instituto de Investigaciones en Matemáticas Aplicadas Y en Sistemas
来源
SN Applied Sciences | 2021年 / 3卷
关键词
Gene transcription; Transcription factors; Bacteria; Enthalpy; Free-stability; Base-pair stacking;
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摘要
The gene transcription of bacteria starts with a promoter sequence being recognized by a transcription factor found in the RNAP enzyme, this process is assisted through the conservation of nucleotides as well as other factors governing these intergenic regions. Faced with this, the coding of genetic information into physical aspects of the DNA such as enthalpy, stability, and base-pair stacking could suggest promoter activity as well as protrude differentiation of promoter and non-promoter data. In this work, a total of 3131 promoter sequences associated to six different sigma factors in the bacterium E. coli were converted into numeric attributes, a strong set of control sequences referring to a shuffled version of the original sequences as well as coding regions is provided. Then, the parameterized genetic information was normalized, exhaustively analyzed through statistical tests. The results suggest that strong signals in the promoter sequences match the binding site of transcription factor proteins, indicating that promoter activity is well represented by its conversion into physical attributes. Moreover, the features tested in this report conveyed significant variances between promoter and control data, enabling these features to be employed in bacterial promoter classification. The results produced here may aid in bacterial promoter recognition by providing a robust set of biological inferences.
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