Dataset Information

FRET monitoring of transcription factor activities in living bacteria

ABSTRACT: Abstract: Bacteria adapt to the constantly changing environments largely by transcriptional regulation through the activities of various transcription factors (TFs). However, techniques that monitor the in situ TF-promoter interactions in living bacteria are lacking. Herein, we developed a whole-cell TF-promoter binding assay based on the intermolecular Förster resonance energy transfer (FRET) between a fluorescent unnatural amino acid CouA which is genetically encoded into defined sites in TFs and the live cell fluorescent nucleic acid stain SYTO 9. We show that this new FRET pair monitors the intricate TF-promoter interactions elicited by various types of signal transduction systems with specificity and sensitivity. Furthermore, the assay is applicable to identify novel modulators of the regulatory systems of interest and monitor TF activities in bacteria colonized in C. elegans. In conclusion, we established a tractable and sensitive TF-promoter binding assay in living bacteria which not only complements currently available approaches for DNA-protein interactions but also provides novel opportunities for functional annotation of bacterial signal transduction systems and studies of the bacteria-host interface

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Escherichia Coli Bacteria

SUBMITTER: Pengchao Wang

LAB HEAD: Dr. Aixin Yan

PROVIDER: PXD030973 | Pride | 2022-10-13

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 5

Publications

Whole-cell FRET monitoring of transcription factor activities enables functional annotation of signal transduction systems in living bacteria.

Wang Pengchao P Zhang Guangming G Xu Zeling Z Chen Zhe Z Liu Xiaohong X Wang Chenyin C Zheng Chaogu C Wang Jiangyun J Zhang Hongmin H Yan Aixin A

The Journal of biological chemistry 20220714 8

Bacteria adapt to their constantly changing environments largely by transcriptional regulation through the activities of various transcription factors (TFs). However, techniques that monitor TF-promoter interactions in situ in living bacteria are lacking. Herein, we developed a whole-cell TF-promoter binding assay based on the intermolecular FRET between an unnatural amino acid, l-(7-hydroxycoumarin-4-yl) ethylglycine, which labels TFs with bright fluorescence through genetic encoding (donor flu ...[more]

PMID: 35839853

Similar Datasets

Project description:This model is from the article: A regulatory role for repeated decoy transcription factor binding sites in target gene expression. Lee TH, Maheshri N. Mol Syst Biol. 2012 Mar 27;8:576. 22453733 , Abstract: Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding. Note: This model corresponds to the basic model for gene expression in the presence of decoys, described in the paper. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

			Action	DRS
	01_CueR-F58CouA.raw	Raw
	02_PhoP-A182CouA_R.raw	Raw
	BasR.raw	Raw
	checksum.txt	Txt
	proteinGroups.txt	Txt