Literature DB >> 21601690

Mapping E. coli RNA polymerase and associated transcription factors and identifying promoters genome-wide.

Sarah E Davis1, Rachel A Mooney, Elenita I Kanin, Jeff Grass, Robert Landick, Aseem Z Ansari.   

Abstract

The ability to examine gene regulation in living cells has been greatly enabled by the development of chromatin immunoprecipitation (ChIP) methodology. ChIP captures a snapshot of protein-DNA interactions in vivo and has been used to study interactions in bacteria, yeast, and mammalian cell culture. ChIP conditions vary depending upon the organism and the nature of the DNA-binding proteins under study. Here, we describe a customized ChIP protocol to examine the genome-wide distribution of a mobile DNA-binding enzyme, Escherichia coli RNA Polymerase (RNAP) as well as the factors that dynamically associate with RNAP during different stages of transcription. We describe new data analysis methods for determining the association of a broadly distributed DNA-binding complex. Further, we describe our approach of combining small molecules and antibiotics that perturb specific cellular events with ChIP and genomic platforms to dissect mechanisms of gene regulation in vivo. The chemical genomic methods can be leveraged to map natural and cryptic promoters and transcription units, annotate genomes, and reveal coupling between different processes in regulation of genes. This approach provides the framework for engineering gene networks and controlling biological output in a desired manner.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21601690     DOI: 10.1016/B978-0-12-385120-8.00020-6

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  15 in total

Review 1.  Defining bacterial regulons using ChIP-seq.

Authors:  Kevin S Myers; Dan M Park; Nicole A Beauchene; Patricia J Kiley
Journal:  Methods       Date:  2015-05-29       Impact factor: 3.608

Review 2.  Nucleolus-like compartmentalization of the transcription machinery in fast-growing bacterial cells.

Authors:  Ding Jun Jin; Carmen Mata Martin; Zhe Sun; Cedric Cagliero; Yan Ning Zhou
Journal:  Crit Rev Biochem Mol Biol       Date:  2016-12-23       Impact factor: 8.250

3.  Regulated Stochasticity in a Bacterial Signaling Network Permits Tolerance to a Rapid Environmental Change.

Authors:  Jeffrey N Carey; Erin L Mettert; Manuela Roggiani; Kevin S Myers; Patricia J Kiley; Mark Goulian
Journal:  Cell       Date:  2018-03-01       Impact factor: 41.582

4.  Crucial role and mechanism of transcription-coupled DNA repair in bacteria.

Authors:  Binod K Bharati; Manjunath Gowder; Fangfang Zheng; Khaled Alzoubi; Vladimir Svetlov; Venu Kamarthapu; Jacob W Weaver; Vitaly Epshtein; Nikita Vasilyev; Liqiang Shen; Yu Zhang; Evgeny Nudler
Journal:  Nature       Date:  2022-03-30       Impact factor: 69.504

5.  Genome-wide promoter assembly in E. coli measured at single-base resolution.

Authors:  Jordan John; Javaid Jabbar; Nitika Badjatia; Matthew J Rossi; William K M Lai; B Franklin Pugh
Journal:  Genome Res       Date:  2022-04-28       Impact factor: 9.438

Review 6.  The dynamic nature and territory of transcriptional machinery in the bacterial chromosome.

Authors:  Ding J Jin; Cedric Cagliero; Carmen M Martin; Jerome Izard; Yan N Zhou
Journal:  Front Microbiol       Date:  2015-05-21       Impact factor: 5.640

7.  Genome-wide proximity between RNA polymerase and DNA topoisomerase I supports transcription in Streptococcus pneumoniae.

Authors:  María-José Ferrándiz; Pablo Hernández; Adela G de la Campa
Journal:  PLoS Genet       Date:  2021-04-30       Impact factor: 5.917

8.  Candida albicans: A Model Organism for Studying Fungal Pathogens.

Authors:  M Anaul Kabir; Mohammad Asif Hussain; Zulfiqar Ahmad
Journal:  ISRN Microbiol       Date:  2012-09-29

9.  Genome-scale analysis of escherichia coli FNR reveals complex features of transcription factor binding.

Authors:  Kevin S Myers; Huihuang Yan; Irene M Ong; Dongjun Chung; Kun Liang; Frances Tran; Sündüz Keleş; Robert Landick; Patricia J Kiley
Journal:  PLoS Genet       Date:  2013-06-20       Impact factor: 5.917

10.  dPeak: high resolution identification of transcription factor binding sites from PET and SET ChIP-Seq data.

Authors:  Dongjun Chung; Dan Park; Kevin Myers; Jeffrey Grass; Patricia Kiley; Robert Landick; Sündüz Keleş
Journal:  PLoS Comput Biol       Date:  2013-10-17       Impact factor: 4.475

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