An improved bind-n-seq strategy to determine protein-DNA interactions validated using the bacterial transcriptional regulator YipR
An improved bind-n-seq strategy to determine protein-DNA interactions validated using the bacterial transcriptional regulator YipR
BACKGROUND: Interactions between transcription factors and DNA lie at the centre of many biological processes including DNA recombination, replication, repair and transcription. Most bacteria encode diverse proteins that act as transcription factors to regulate various traits. Several technologies for identifying protein-DNA interactions at the genomic level have been developed. Bind-n-seq is a high-throughput in vitro method first deployed to analyse DNA interactions associated with eukaryotic zinc-finger proteins. The method has three steps (i) binding protein to a randomised oligonucleotide DNA target library, (ii) deep sequencing of bound oligonucleotides, and (iii) a computational algorithm to define motifs among the sequences. The classical Bind-n-seq strategy suffers from several limitations including a lengthy wet laboratory protocol and a computational algorithm that is difficult to use. We introduce here an improved, rapid, and simplified Bind-n-seq protocol coupled with a user-friendly downstream data analysis and handling algorithm, which has been optimized for bacterial target proteins. We validate this new protocol by showing the successful characterisation of the DNA-binding specificities of YipR (YajQ interacting protein regulator), a well-known transcriptional regulator of virulence genes in the bacterial phytopathogen Xanthomonas campestris pv. campestris (Xcc).
RESULTS: The improved Bind-n-seq approach identified several DNA binding motif sequences for YipR, in particular the CCCTCTC motif, which were located in the promoter regions of 1320 Xcc genes. Informatics analysis revealed that many of these genes regulate functions associated with virulence, motility, and biofilm formation and included genes previously found involved in virulence. Additionally, electromobility shift assays show that YipR binds to the promoter region of XC_2633 in a CCCTCTC motif-dependent manner.
CONCLUSION: We present a new and rapid Bind-n-seq protocol that should be useful to investigate DNA-binding proteins in bacteria. The analysis of YipR DNA binding using this protocol identifies a novel DNA sequence motif in the promoter regions of target genes that define the YipR regulon.
Bind-n-seq, Gene expression, Protein-DNA interactions, Transcription regulator, Virulence, Xanthomonas
An, Shi-Qi
0e05f480-cec1-4c0e-bc1d-359d30ea9a6e
Valvano, Miguel A.
860ad4ea-4e77-4265-a035-feafa60725f8
Yu, Yan-Hua
1f623444-d985-4329-9cf1-2d8cc345f1a0
Webb, Jeremy S.
ec0a5c4e-86cc-4ae9-b390-7298f5d65f8d
Campos, Guillermo Lopez
2f90d5b6-1801-40dd-8e1b-bcfbe0d335ae
2 January 2020
An, Shi-Qi
0e05f480-cec1-4c0e-bc1d-359d30ea9a6e
Valvano, Miguel A.
860ad4ea-4e77-4265-a035-feafa60725f8
Yu, Yan-Hua
1f623444-d985-4329-9cf1-2d8cc345f1a0
Webb, Jeremy S.
ec0a5c4e-86cc-4ae9-b390-7298f5d65f8d
Campos, Guillermo Lopez
2f90d5b6-1801-40dd-8e1b-bcfbe0d335ae
An, Shi-Qi, Valvano, Miguel A., Yu, Yan-Hua, Webb, Jeremy S. and Campos, Guillermo Lopez
(2020)
An improved bind-n-seq strategy to determine protein-DNA interactions validated using the bacterial transcriptional regulator YipR.
BMC Microbiology, 20 (1), [1].
(doi:10.1186/s12866-019-1672-7).
Abstract
BACKGROUND: Interactions between transcription factors and DNA lie at the centre of many biological processes including DNA recombination, replication, repair and transcription. Most bacteria encode diverse proteins that act as transcription factors to regulate various traits. Several technologies for identifying protein-DNA interactions at the genomic level have been developed. Bind-n-seq is a high-throughput in vitro method first deployed to analyse DNA interactions associated with eukaryotic zinc-finger proteins. The method has three steps (i) binding protein to a randomised oligonucleotide DNA target library, (ii) deep sequencing of bound oligonucleotides, and (iii) a computational algorithm to define motifs among the sequences. The classical Bind-n-seq strategy suffers from several limitations including a lengthy wet laboratory protocol and a computational algorithm that is difficult to use. We introduce here an improved, rapid, and simplified Bind-n-seq protocol coupled with a user-friendly downstream data analysis and handling algorithm, which has been optimized for bacterial target proteins. We validate this new protocol by showing the successful characterisation of the DNA-binding specificities of YipR (YajQ interacting protein regulator), a well-known transcriptional regulator of virulence genes in the bacterial phytopathogen Xanthomonas campestris pv. campestris (Xcc).
RESULTS: The improved Bind-n-seq approach identified several DNA binding motif sequences for YipR, in particular the CCCTCTC motif, which were located in the promoter regions of 1320 Xcc genes. Informatics analysis revealed that many of these genes regulate functions associated with virulence, motility, and biofilm formation and included genes previously found involved in virulence. Additionally, electromobility shift assays show that YipR binds to the promoter region of XC_2633 in a CCCTCTC motif-dependent manner.
CONCLUSION: We present a new and rapid Bind-n-seq protocol that should be useful to investigate DNA-binding proteins in bacteria. The analysis of YipR DNA binding using this protocol identifies a novel DNA sequence motif in the promoter regions of target genes that define the YipR regulon.
Text
s12866-019-1672-7
- Version of Record
More information
Accepted/In Press date: 3 December 2019
Published date: 2 January 2020
Keywords:
Bind-n-seq, Gene expression, Protein-DNA interactions, Transcription regulator, Virulence, Xanthomonas
Identifiers
Local EPrints ID: 437349
URI: http://eprints.soton.ac.uk/id/eprint/437349
ISSN: 1471-2180
PURE UUID: e9e644e2-54aa-4b2e-8b54-f9fc6c6e2f3a
Catalogue record
Date deposited: 24 Jan 2020 17:32
Last modified: 17 Mar 2024 03:07
Export record
Altmetrics
Contributors
Author:
Shi-Qi An
Author:
Miguel A. Valvano
Author:
Yan-Hua Yu
Author:
Guillermo Lopez Campos
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics