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Published September 21, 2020 | Supplemental Material + Submitted + Published
Journal Article Open

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time

Abstract

Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈ 65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively-parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than 100 E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.

Additional Information

© 2020 Ireland et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. Received: 20 January 2020; Accepted: 18 September 2020; Published: 21 September 2020. We are grateful to Rachel Banks, Stephanie Barnes, Curt Callan, Griffin Chure, Ana Duarte, Vahe Galstyan, Hernan Garcia, Soichi Hirokawa, Thomas Lecuit, Heun Jin Lee, Madhav Mani, Muir Morrison, Steve Quake, Manuel Razo-Mejia, Gabe Salmon, and Guillaume Urtecho for useful discussion and feedback on the manuscript. Guillaume Urtecho and Sri Kosuri have been instrumental in providing key advice and protocols at various stages in the development of this work. We would like to thank Jost Vielmetter and Nina Budaeva for providing access to their Cell Disruptor. Brett Lomenick provided crucial help and advice with protein preparation. We also thank Igor Antoshechkin for his help with sequencing at the Caltech Genomics Facility. We are deeply grateful for support from NIH Grants DP1 OD000217 (Director's Pioneer Award) and 1R35 GM118043-01 Maximizing Investigators Research Award) which made it possible to undertake this multi-year project. N.M.B. was supported by an HHMI International Student Research Fellowship. S.M.B was supported by the NIH Institutional National Research Service Award (5T32GM007616-38) provided through Caltech. The Proteome Exploration Laboratory is supported by, the Beckman Institute, and NIH 1S10OD02001301. Author contributions: William T Ireland, Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing; Suzannah M Beeler, Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing; Emanuel Flores-Bautista, Software, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing; Nicholas S McCarty, Resources, Software, Writing - review and editing; Tom Röschinger, Data curation, Software, Writing - review and editing; Nathan M Belliveau, Conceptualization, Methodology, Writing - review and editing; Michael J Sweredoski, Formal analysis, Methodology, Writing - review and editing; Annie Moradian, Methodology, Writing - review and editing; Justin B Kinney, Software, Methodology, Writing - review and editing; Rob Phillips, Conceptualization, Resources, Supervision, Funding acquisition, Validation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing. Data availability: Sequencing data has been deposited in the SRA under accession no.PRJNA599253 and PRJNA603368. Mass spectrometry data is deposited in the CalTech data repository at doi:10.22002/d1.1336. Model files and inferred information footprints are deposited in the CalTech data repository at doi:10.22002/D1.1331. Processed sequencing data sets and analysis software are available in the GitHub repository available at https://doi.org/10.5281/zenodo.3953312.

Attached Files

Published - elife-55308-v2.pdf

Submitted - 2001.07396.pdf

Submitted - 2020.01.18.910323v3.full.pdf

Supplemental Material - elife-55308-app2-fig2-data1-v2.xlsx

Supplemental Material - elife-55308-app2-fig3-data1-v2.xlsx

Supplemental Material - elife-55308-app2-fig4-data1-v2.csv

Supplemental Material - elife-55308-app3-fig1-data1-v2.txt

Supplemental Material - elife-55308-app4-fig2-data1-v2.csv

Supplemental Material - elife-55308-code1-v2.tar.gz

Supplemental Material - elife-55308-supp1-v2.xlsx

Supplemental Material - elife-55308-supp2-v2.xlsx

Supplemental Material - elife-55308-supp3-v2.xlsx

Supplemental Material - elife-55308-transrepform-v2.docx

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