An interdisciplinary data-driven approach to resolve sigma-factor-specific promoter dependency in bacteria.

DNA is the hereditary material that exists in all living organisms. DNA consists of coding and non-coding regions. While the coding regions of DNA contain genes that encode for proteins; the non-coding regions harbour DNA elements that provide the regulatory information. The transfer of information from genes to proteins happens in two stages: In the first stage (transcription), the genes are 'transcribed' to a molecule called mRNA; and in the second stage (translation), the information in mRNA is 'translated' into proteins. Promoters are one of the DNA elements that are close to the start of genes and provide the transcription-specific regulatory information determining when and how much genes will be transcribed. In SiD, our aim is to improve our understanding of transcriptional regulation in bacteria. We will carry out experiments to understand how DNA sequence compositions in promoters lead to different promoter functions. The experiments will be conducted in three bacterial species, that are of importance both for academia and industry; and under in vitro conditions, using purified proteins from these bacteria. SiD is an interdisciplinary project and integrates the synthetic and computational biology expertise from NTNU, Norway with research partners from the fields of biophysics (NTNU, Norway); genomics (UNIBI, Germany); biochemistry (UU, Sweden); and synthetic biology (CSIC, Spain).

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We propose an interdisciplinary data-driven experimental study, SiD, that will enable improved understanding of transcriptional regulation in bacteria. In SiD, we will develop a high-throughput microfluidics-based in vitro transcription method, coupled to in vivo screening efforts with DNA and RNA sequencing. The experimental efforts will allow us to determine the cis-acting DNA sequences for 21 sigma-factors, belonging to three bacterial species, Escherichia coli, Pseudomonas putida and Bacillus subtilis, at the single-nucleotide resolution. With the large-scale data, we will perform in silico data analysis, using statistics and machine learning, to develop algorithms that can infer sigma-factor-specific cis-binding motifs within bacterial promoters. The proposed methodology can be applied to any host of interest, and thus opens up the possibility to expand our knowledge on transcriptional regulation to a wide range of microorganisms. The generated big data will be stored on Norwegian nationwide Sigma2 platform, and the metadata will be made accessible to all interested parties based on the four principles of Findability, Accessibility, Interoperability and Reusability. A project-specific website will also be established following Open Science practices, making scientific research, data and dissemination output of SiD easily and openly accessible. To meet these ambitious goals, SiD requires an interdisciplinary approach, and therefore it integrates the fields of synthetic and computational biology (NTNU,Norway) with research partners from the fields of biophysics (NTNU, Norway), genomics (UNIBI, Germany), biochemistry (UU, Sweden) and synthetic biology (CSIC, Spain).