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Nucleic Acids Res. 2018 Nov 16;46(20):10682-10696. doi: 10.1093/nar/gky752.

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655.

Author information

1
Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
2
Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.
3
Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA.
4
School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
5
Department of Genetic Engineering and Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin, Republic of Korea.
6
Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Center for Bioinformatics Tübingen (ZBIT), 72076 Tübingen, Germany.
7
Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany.
8
Novo Nordisk Foundation Center for Biosustainability, 2800 Kongens Lyngby, Denmark.
9
Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
10
School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
11
School of Biological Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
12
Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA.

Abstract

Transcriptional regulation enables cells to respond to environmental changes. Of the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, 185 have been experimentally identified, but ChIP methods have been used to fully characterize only a few dozen. Identifying these remaining TFs is key to improving our knowledge of the E. coli transcriptional regulatory network (TRN). Here, we developed an integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments. We applied this workflow to (i) identify 16 candidate TFs from over a hundred uncharacterized genes; (ii) capture a total of 255 DNA binding peaks for ten candidate TFs resulting in six high-confidence binding motifs; (iii) reconstruct the regulons of these ten TFs by determining gene expression changes upon deletion of each TF and (iv) identify the regulatory roles of three TFs (YiaJ, YdcI, and YeiE) as regulators of l-ascorbate utilization, proton transfer and acetate metabolism, and iron homeostasis under iron-limited conditions, respectively. Together, these results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.

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