AIDmut-Seq: a Three-Step Method for Detecting Protein-DNA Binding Specificity

被引:0
|
作者
Li, Feixuan [1 ]
Liu, Xiao-Yu [3 ]
Ni, Lei [2 ]
Jin, Fan [2 ]
机构
[1] Univ Sci & Technol China, Hefei Natl Res Ctr Phys Sci Microscale, Dept Polymer Sci & Engn, Hefei, Peoples R China
[2] Chinese Acad Sci, Shenzhen Inst Synthet Biol, Shenzhen Inst Adv Technol, CAS Key Lab Quantitat Engn Biol, Shenzhen, Peoples R China
[3] Southern Univ Sci & Technol, Sch Med, Shenzhen, Peoples R China
来源
MICROBIOLOGY SPECTRUM | 2023年 / 11卷 / 01期
关键词
activation induced cytidine deaminase; Pseudomonas aeruginosa; protein-DNA interactions; PSEUDOMONAS-AERUGINOSA; GLOBAL REGULATOR; GENE-EXPRESSION; STRANDED-DNA; TRANSCRIPTION; GENOME; RSAL; FLEQ; IDENTIFICATION; HYPERMUTATION;
D O I
10.1128/spectrum.03783-22
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Transcriptional factors (TFs) and their regulons make up the gene regulatory networks. Here, we developed a method based on TF-directed activation-induced cytidine deaminase (AID) mutagenesis in combination with genome sequencing, called AIDmut-Seq, to detect TF targets on the genome. AIDmut-Seq involves only three simple steps, including the expression of the AID-TF fusion protein, whole-genome sequencing, and single nucleotide polymorphism (SNP) profiling, making it easy for junior and interdisciplinary researchers to use. Using AIDmut-Seq for the major quorum sensing regulator LasR in Pseudomonas aeruginosa, we confirmed that a few TF-guided C-T (or G-A) conversions occurred near their binding boxes on the genome, and a number of previously characterized and uncharacterized LasR-binding sites were detected. Further verification of AIDmut-Seq using various transcriptional regulators demonstrated its high efficiency for most transcriptional activators (FleQ, ErdR, GacA, ExsA). We confirmed the binding of LasR, FleQ, and ErdR to 100%, 50%, and 86% of their newly identified promoters by using in vitro protein-DNA binding assay. And real-time RT-PCR data validated the intracellular activity of these TFs to regulate the transcription of those newly found target promoters. However, AIDmut-Seq exhibited low efficiency for some small transcriptional repressors such as RsaL and AmrZ, with possible reasons involving fusion-induced TF dysfunction as well as low transcription rates of target promoters. Although there are false-positive and false-negative results in the AIDmut-Seq data, preliminary results have demonstrated the value of AIDmut-Seq to act as a complementary tool for existing methods.IMPORTANCE Protein-DNA interactions (PDI) play a central role in gene regulatory networks (GRNs). However, current techniques for studying genome-wide PDI usually involve complex experimental procedures, which prevent their broad use by scientific researchers. In this study, we provide a in vivo method called AIDmut-Seq. AIDmut-Seq involves only three simple steps that are easy to operate for researchers with basic skills in molecular biology. The efficiency of AIDmut-Seq was tested and confirmed using multiple transcription factors in Pseudomonas aeruginosa. Although there are still some defects regarding false-positive and false-negative results, AIDmut-Seq will be a good choice in the early stage of PDI study. Protein-DNA interactions (PDI) play a central role in gene regulatory networks (GRNs). However, current techniques for studying genome-wide PDI usually involve complex experimental procedures, which prevent their broad use by scientific researchers.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets
    Wei, Yingying
    Li, Xia
    Wang, Qian-fei
    Ji, Hongkai
    BMC GENOMICS, 2012, 13
  • [22] Efficient Double Fragmentation ChIP-seq Provides Nucleotide Resolution Protein-DNA Binding Profiles
    Mokry, Michal
    Hatzis, Pantelis
    de Bruijn, Ewart
    Koster, Jan
    Versteeg, Rogier
    Schuijers, Jurian
    van de Wetering, Marc
    Guryev, Victor
    Clevers, Hans
    Cuppen, Edwin
    PLOS ONE, 2010, 5 (11):
  • [23] Dynamic and Structural Modeling of the Specificity in Protein-DNA Interactions Guided by Binding Assay and Structure Data
    Tan, Cheng
    Takada, Shoji
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2018, 14 (07) : 3877 - 3889
  • [24] New insights into protein-DNA binding specificity from hydrogen bond based comparative study
    Lin, Maoxuan
    Guo, Jun-tao
    NUCLEIC ACIDS RESEARCH, 2019, 47 (21) : 11103 - 11113
  • [25] Protein-DNA binding specificity: a grid-enabled computational approach applied to single and multiple protein assemblies
    Zakrzewska, Krystyna
    Bouvier, Benjamin
    Michon, Alexis
    Blanchet, Christophe
    Lavery, Richard
    PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2009, 11 (45) : 10712 - 10721
  • [26] MixChIP: a probabilistic method for cell type specific protein-DNA binding analysis
    Sini Rautio
    Harri Lähdesmäki
    BMC Bioinformatics, 16
  • [27] MixChIP: a probabilistic method for cell type specific protein-DNA binding analysis
    Rautio, Sini
    Lahdesmaki, Harri
    BMC BIOINFORMATICS, 2015, 16
  • [28] Chemical control of protein-DNA interactions: Step-binding of modified glucose oxidase to double helical DNA
    Baveghems, Clive L.
    Deshapriya, Inoka
    Pattammattel, Ajith
    Kumar, Challa V.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2014, 247
  • [29] Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data
    Jothi, Raja
    Cuddapah, Suresh
    Barski, Artem
    Cui, Kairong
    Zhao, Keji
    NUCLEIC ACIDS RESEARCH, 2008, 36 (16) : 5221 - 5231
  • [30] Genome-Wide Localization of Protein-DNA Binding and Histone Modification by a Bayesian Change-Point Method with ChIP-seq Data
    Xing, Haipeng
    Mo, Yifan
    Liao, Will
    Zhang, Michael Q.
    PLOS COMPUTATIONAL BIOLOGY, 2012, 8 (07)