Deciphering gene regulation in Bacteria

破译细菌的基因调控

• 批准号: RGPIN-2019-05247
• 负责人: PeñaCastillo, Lourdes
• 金额: $ 2.33万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715286
• 关键词: Deciphering; gene; regulation; Bacteria

Recent studies in bacteria using next-generation RNA sequencing technology have found that gene regulation is more complex than previously thought in these organisms. For example, bacteria have: 1) a large number of regulatory non-coding small RNAs (sRNAs) analogous to micro-RNAs in eukaryotes, 2) operons with multiple and overlapping genes and transcripts, and 3) promoter structures that vary among bacterial species. Although large amounts of RNA sequencing data are being generated, there is a lack of computational approaches for effectively integrating data generated from high-throughput technologies to gain deeper understanding of how bacteria control gene expression. The ultimate goal of this proposal is to develop smart computational methods to decipher gene regulation in bacteria. Control of transcription initiation is the first step in gene regulation. A promoter is a genomic region that determines when and how transcription of a gene is initiated. Gene expression in bacteria is also regulated by stopping gene transcription in response to specific signals. A terminator is a sequence that can stop transcription. For the duration of this research grant, we will focus on developing machine learning-based approaches to 1) find out what genes are regulated by which sRNAs, 2) identify bacterial promoter regions, and 3) identify bacterial terminators. To facilitate the uptake of our methods by the bacterial research community we will distribute these methods as containerized computational pipelines so that the approaches will be easily used by natural sciences researchers. A containerized pipeline is one that can be executed without having to install all the extra software used by the pipeline. This research is important not only to facilitate microbiology research so that our understanding of gene regulation in bacteria improves, but outcomes of this research could also potentially be exploited by a variety of industries (e.g., food, pharmaceutical, and biotechnology). For example, identified sRNAs could be used as switches to control the bacterial production of certain substances in the food industry, or as targets for the development of novel antibiotics.

最近利用下一代RNA测序技术对细菌进行的研究发现，这些生物的基因调控比以前认为的要复杂得多。例如，细菌有：