Deciphering gene regulation in Bacteria

最近使用下一代RNA测序技术对细菌进行的研究发现，在这些生物中，基因调控比之前认为的要复杂得多。例如，细菌有：*1)大量类似于真核生物微型RNA的调控非编码小RNA(SRNA)，*2)具有多个重叠基因和转录本的操纵子，以及*3)不同细菌物种的启动子结构。*尽管产生了大量的RNA测序数据，但缺乏有效整合高通量技术产生的数据以更深入地理解细菌如何控制基因表达的计算方法。这项提议的最终目标是开发智能计算方法来破译细菌中的基因调控。转录调控是基因调控的第一步。启动子是决定何时以及如何启动基因转录的基因组区域。细菌中的基因表达也是通过停止基因转录来响应特定信号来调节的。终止子是一种可以停止转录的序列。在这项研究拨款期间，我们将专注于开发基于机器学习的方法，以*1)找出哪些基因受哪些sRNA调控，*2)识别细菌启动子区域，以及*3)识别细菌终止子。*为了促进细菌研究社区采用我们的方法，我们将以集装箱计算管道的形式分发这些方法，以便自然科学研究人员可以轻松地使用这些方法。集装箱化管道是一种无需安装管道使用的所有额外软件即可执行的管道。这项研究不仅对促进微生物学研究以提高我们对细菌中基因调控的理解很重要，而且这项研究的结果也可能被各种行业(如食品、制药和生物技术)所利用。例如，已识别的sRNA可用作控制食品工业中某些物质的细菌生产的开关，或用作开发新抗生素的目标。

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.**