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Genome-wide Identification of DNA-protein Interaction to Reconstruct Bacterial Transcription Regulatory Network

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Abstract

The development and innovative use of next-generation sequencing technologies have opened the doors for genetic and epigenetic research at the next level. These technologies can be used to study gene expression regulation at the transcriptional and post-transcriptional levels in both prokaryotic and eukaryotic systems. In this review, we focused on the various tools and techniques for DNA-binding proteins such as RNA polymerase, sigma factors, nucleoid-associated proteins, and transcription factors in bacteria. Descriptions on series of Chromatin ImmunoPrecipitation (ChIP) technologies, including ChIP followed by microarray hybridization (ChIP-chip), ChIP followed by deep sequencing (ChIP-seq), and ChIP with exonuclease digestion and deep sequencing (ChIP-exo) has been given. Furthermore, recent investigations on transcriptional regulatory networks of a wide range of bacteria with ChIP technologies are discussed for the model bacteria Escherichia coli followed by pathogenic and other non-pathogenic bacteria. In conclusion, ChIP technologies have proven effective and efficient to reconstruct and to delineate transcriptional regulatory network in a variety of bacteria.

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References

  1. Erill, I., M. Jara, N. Salvador, M. Escribano, S. Campoy, and J. Barbe (2004) Differences in LexA regulon structure among Proteobacteria throug. in vivo assisted comparative genomics. Nucleic Acids Res. 32: 6617–6626.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Ravcheev, D. A., A. A. Best, N. V. Sernova, M. D. Kazanov, P. S. Novichkov, and D. A. Rodionov (2013) Genomic reconstruction of transcriptional regulatory networks in lactic acid bacteria. BMC Genomics. 14: 94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Martinez-Antonio, A. and J. Collado-Vides (2003) Identifying global regulators in transcriptional regulatory networks in bacteria. Curr. Opin. Microbiol. 6: 482–489.

    Article  CAS  PubMed  Google Scholar 

  4. Herrgard, M. J., M. W. Covert, and B. O. Palsson (2004) Reconstruction of microbial transcriptional regulatory networks. Curr. Opin. Biotechnol. 15: 70–77.

    Article  CAS  PubMed  Google Scholar 

  5. Lozada-Chavez, I., S. C. Janga, and J. Collado-Vides (2006) Bacterial regulatory networks are extremely flexible in evolution. Nucleic Acids Res. 34: 3434–3445.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cho, B. K., B. Palsson, and K. Zengler (2011) Deciphering the regulatory codes in bacterial genomes. Biotechnol. J. 6: 1052–1063.

    Article  CAS  PubMed  Google Scholar 

  7. Kroger, C., S. C. Dillon, A. D. S. Cameron, K. Papenfort, S. K. Sivasankaran, K. Hokamp, Y. Chao, A. Sittka, M. Hebrard, K. Handler, A. Colgan, P. Leekitcharoenphon, G. C. Langridge, A. J. Lohan, B. Loftus, S. Lucchini, D. W. Ussery, C. J. Dorman, N. R. Thomson, J. Vogel, and J. C. D. Hinton (2012) The transcriptional landscape and small RNAs o. Salmonella enterica serovar Typhimurium. Proc. Natl. Acad. Sci. USA. 109: E1277–E1286.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Seo, S. W., D. Kim, H. Latif, E. J. O’Brien, R. Szubin, and B. O. Palsson (2014) Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism i. Escherichia coli. Nature Commun. 5: 4910.

    Article  CAS  Google Scholar 

  9. Jeong, Y., H. Shin, S. W. Seo, D. Kim, S. Cho, and B. K. Cho (2017) Elucidation of bacterial translation regulatory networks. Curr. Opin. Syst. Biol. 2: 84–90.

    Article  Google Scholar 

  10. Cho, B. K., K. Zengler, Y. Qiu, Y. S. Park, E. M. Knight, C. L. Barrett, Y. Gao, and B. O. Palsson (2009) The transcription unit architecture of th. Escherichia coli genome. Nat. Biotechnol. 27: 1043–1049.

    Article  CAS  PubMed  Google Scholar 

  11. O’Brien, E. J., J. A. Lerman, R. L. Chang, D. R. Hyduke, and B. O. Palsson (2013) Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction. Mol. Syst. Biol. 9: 693.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Liu, J. K., E. J. O’Brien, J. A. Lerman, K. Zengler, B. O. Palsson, and A. M. Feist (2014) Reconstruction and modeling protein translocation and compartmentalization i. Escherichia coli at the genome-scale. BMC Syst. Biol. 8: 110.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Mardis, E. R. (2008) The impact of next-generation sequencing technology on genetics. Trends Genet. 24: 133–141.

    Article  CAS  PubMed  Google Scholar 

  14. Blais, A. and B. D. Dynlacht (2005) Constructing transcriptional regulatory networks. Genes Dev. 19: 1499–1511.

    Article  CAS  PubMed  Google Scholar 

  15. Alwine, J. C., D. J. Kemp, and G. R. Stark (1977) Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes. Proc. Natl. Acad. Sci. USA. 74: 5350–5354.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Liang, P. and A. B. Pardee (2003) Analysing differential gene expression in cancer. Nat. Rev. Cancer. 3: 869–876.

    Article  CAS  PubMed  Google Scholar 

  17. Sargent, T. D. (1987) Isolation of differentially expressed genes. Methods Enzymol. 152: 423–432.

    Article  CAS  PubMed  Google Scholar 

  18. Liang, P. and A. B. Pardee (1992) Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. Science. 257: 967–971.

    Article  CAS  PubMed  Google Scholar 

  19. Velculescu, V. E., L. Zhang, B. Vogelstein, and K. W. Kinzler (1995) Serial analysis of gene expression. Science. 270: 484–487.

    Article  CAS  PubMed  Google Scholar 

  20. Hoheisel, J. D. (2006) Microarray technology: beyond transcript profiling and genotype analysis. Nat. Rev. Genet. 7: 200–210.

    Article  CAS  PubMed  Google Scholar 

  21. Schena, M., R. A. Heller, T. P. Theriault, K. Konrad, E. Lachenmeier, and R W. Davis (1998) Microarrays: biotechnology’s discovery platform for functional genomics. Trends Biotechnol. 16: 301–306.

    Article  CAS  PubMed  Google Scholar 

  22. Southern, E., K. Mir, and M. Shchepinov (1999) Molecular interactions on microarrays. Nat. Genet. 21: 5–9.

    Article  CAS  PubMed  Google Scholar 

  23. Cheung, V. G., M. Morley, F. Aguilar, A. Massimi, R. Kucherlapati, and G. Childs (1999) Making and reading microarrays. Nat. Genet. 21: 15–19.

    Article  CAS  PubMed  Google Scholar 

  24. Siebenlist, U., R. B. Simpson, and W. Gilbert (1980) E. coli RNA polymerase interacts homologously with two different promoters. Cell. 20: 269–281.

    Article  CAS  PubMed  Google Scholar 

  25. Kovacic, R. T. (1987) The 0 degree C closed complexes betwee. Escherichia coli RNA polymerase and two promoters, T7-A3 and lacUV5. J. Biol. Chem. 262: 13654–13661.

    Article  CAS  PubMed  Google Scholar 

  26. Cartwright, I. L., R. P. Hertzberg, P. B. Dervan, and S. C. Elgin (1983) Cleavage of chromatin with methidiumpropyl-EDTA. iron(II). Proc. Natl. Acad. Sci. USA. 80: 3213–3217.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Gilmour, D. S. and J. T. Lis (1984) Detecting protein-DNA interaction. in vivo: distribution of RNA polymerase on specific bacterial genes. Proc. Natl. Acad. Sci. USA. 81: 4275–4279.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Karpov, V. L., O. V. Preobrazhenskaya, and A. D. Mirzabekov (1984) Chromatin structure o. hsp 70 genes, activated by heat shock: selective removal of histones from the coding region and their absence from the 5’ region. Cell. 36: 423–431.

    Article  CAS  PubMed  Google Scholar 

  29. Solomon, M. J. and A. Varshavsky (1985) Formaldehyde-mediated DNA-protein crosslinking: a probe fo. in vivo chromatin structures. Proc. Natl. Acad. Sci. USA. 82: 6470–6474.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lee, T. I., N. J. Rinaldi, F. Robert, D. T. Odom, Z. Bar-Joseph, G. K. Gerber, N. M. Hannett, C. T. Harbison, C. M. Thompson, I. Simon, J. Zeitlinger, E. G. Jennings, H. L. Murray, D. B. Gordon, B. Ren, J. J. Wyrick, J. B. Tagne, T. L. Volkert, E. Fraenke, D. K. Gifford, and R. A. Young (2002) Transcriptional regulatory networks i. Saccharomyces cerevisiae. Science. 298: 799–804.

    CAS  PubMed  Google Scholar 

  31. Ren, B., F. Robert, J. J. Wyrick, O. Aparicio, E. G. Jennings, I. Simon, J. Zeitlinger, J. Schreiber, N. Hannett, E. Kanin, T. L. Volkert, C. J. Wilson, S. P. Bell, and R. A. Young (2000) Genome-wide location and function of DNA binding proteins. Science. 290: 2306–2309.

    Article  CAS  PubMed  Google Scholar 

  32. Johnson, D. S., A. Mortazavi, R. M. Myers, and B. Wold (2007) Genome-wide map** o. in vivo protein-DNA interactions. Science. 316: 1497–1502.

    Article  CAS  PubMed  Google Scholar 

  33. Cho, B. K., D. Kim, E. M. Knight, K. Zengler, and B. O. Palsson (2014) Genome-scale reconstruction of the sigma factor network i. Escherichia coli: topology and functional states. BMC Biol. 12: 4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Kaufmann, K., J. M. Muino, M. Østerås, L. Farinelli, P. Krajewski, and G. C. Angenent (2010) Chromatin immunoprecipitation (ChIP) of plant transcription factors followed by sequencing (ChIP-SEQ) or hybridization to whole genome arrays (ChIPCHIP). Nat. Protoc. 5: 457–472.

    Article  CAS  PubMed  Google Scholar 

  35. Nal, B., E. Mohr, and P. Ferrier (2001) Location analysis of DNA-bound proteins at the whole-genome level: untangling transcriptional regulatory networks. Bioessays. 23: 473–476.

    Article  CAS  PubMed  Google Scholar 

  36. Hanlon, S. E. and J. D. Lieb (2004) Progress and challenges in profiling the dynamics of chromatin and transcription factor binding with DNA microarrays. Curr. Opin. Gene Dev. 14: 697–705.

    Article  CAS  Google Scholar 

  37. Sikder, D. and T. Kodadek (2005) Genomic studies of transcription factor-DNA interactions. Curr. Opin. Chem. Biol. 9: 38–45.

    Article  CAS  PubMed  Google Scholar 

  38. Lei, E. P., H. Krebber, and P. A. Silver (2001) Messenger RNAs are recruited for nuclear export during transcription. Genes Dev. 15: 1771–1782.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ishii, K., G. Arib, C. Lin, G. Van Houwe, and U. K. Laemmli (2002) Chromatin boundaries in budding yeast: the nuclear pore connection. Cell. 109: 551–562.

    Article  CAS  PubMed  Google Scholar 

  40. Lee, T. I., S. E. Johnstone, and R. A. Young (2006) Chromatin immunoprecipitation and microarray-based analysis of protein location. Nat. Protoc. 1: 729–748.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Cho, B. K., S. A. Federowicz, M. Embree, Y. S. Park, D. Kim, and B. Ø. Palsson (2011) The PurR regulon i. Escherichia coli K-12 MG1655. Nucleic Acids Res. 39: 6456–6464.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Cho, B. K., C. L. Barrett, E. M. Knight, Y. S. Park, and B. Ø. Palsson (2008) Genome-scale reconstruction of the Lrp regulatory network i. Escherichia coli. Proc. Natl. Acad. Sci. USA. 105: 19462–19467.

    Article  CAS  PubMed  Google Scholar 

  43. Conrad, T. M., M. Frazier, A. R. Joyce, B. K. Cho, E. M. Knight, N. E. Lewis, R. Landick, and B. Ø. Palsson (2010) RNA polymerase mutants found through adaptive evolution reprogra. Escherichia coli for optimal growth in minimal media. Proc. Natl. Acad. Sci. USA. 107: 20500–20505.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Cho, B. K., E. M. Knight, C. L. Barrett, and B. Ø. Palsson (2008) Genome-wide analysis of Fis binding i. Escherichia coli indicates a causative role for A-/AT-tracts. Genome Res. 18: 900–910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Rhee, H. S. and B. F. Pugh (2012) ChIP-exo method for identifying genomic location of DNA-binding proteins with near-single-nucleotide accuracy. Curr. Protoc. Mol. Biol. 100: 21.24.1–21.24.14.

    Google Scholar 

  46. Rhee, H. S. and B. F. Pugh (2011) Comprehensive genome-wide protein-DNA interactions detected at single-nucleotide resolution. Cell. 147: 1408–1419.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Cho, S., Y. B. Cho, T. J. Kang, S. C. Kim, B. Palsson, and B. K. Cho (2015) The architecture of ArgR-DNA complexes at the genome-scale i. Escherichia coli. Nucleic Acids Res. 43: 3079–3088.

    Article  CAS  PubMed  Google Scholar 

  48. Rossi, M. J., W. K. M. Lai, and B. F. Pugh (2018) Simplified ChIP-exo assays. Nat. Commun. 9: 2842.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Li, J., C. C. Overall, E. S. Nakayasu, A. S. Kidwai, M. B. Jones, R. C. Johnson, N. T. Nguyen, J. E. McDermott, C. Ansong, F. Heffron, E. D. Cambronne, and J. N. Adkins (2015) Analysis of th. Salmonella regulatory network suggests involvement of SsrB and H-NS in σE-regulated SPI-2 gene expression. Front. Microbiol. 6: 27.

    PubMed  PubMed Central  Google Scholar 

  50. Serandour, A. A., G. D. Brown, J. D. Cohen, and J. S. Carroll (2013) Development of an Illumina-based ChIP-exonuclease method provides insight into FoxA1-DNA binding properties. Genome Biol. 14: R147.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Chu, Y. and D. R. Corey (2012) RNA sequencing: platform selection, experimental design, and data interpretation. Nucleic Acid Ther. 22: 271–274.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wang, Z., M. Gerstein, and M. Snyder (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10: 57–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Ghosh, S. and C. K. K. Chan (2016) Analysis of RNA-Seq data using TopHat and Cufflinks. pp. 339–361. In: D. Edwards (ed.). Plant Bioinformatics. Humana Press, New York, NY, USA.

    Chapter  Google Scholar 

  54. Anders, S. (2010) Analysing RNA-Seq data with the “DESeq” package. https://www.bioconductor.org/packages//2.7/bioc/vignettes/DESeq/inst/doc/DESeq.pdf.

  55. Trapnell, C., L. Pachter, and S. L. Salzberg (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 25: 1105–1111.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Kim, D., S. W. Seo, Y. Gao, H. Nam, G. I. Guzman, B. K. Cho, and B. O. Palsson (2018) Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP. Nucleic Acids Res. 46: 2901–2917.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Seo, S. W., D. Kim, R. Szubin, and B. O. Palsson (2015) Genome-wide reconstruction of OxyR and SoxRS transcriptional regulatory networks under oxidative stress i. Escherichia coli K-12 MG1655. Cell Rep. 12: 1289–1299.

    Article  CAS  PubMed  Google Scholar 

  58. Seo, S. W., Y. Gao, D. Kim, R. Szubin, J. Yang, B. K. Cho, and B. O. Palsson (2017) Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655. 7: 2181.

    Google Scholar 

  59. Federowicz, S., D. Kim, A. Ebrahim, J. Lerman, H. Nagarajan, B. K. Cho, K. Zengler, and B. Palsson (2014) Determining the control circuitry of redox metabolism at the genome-scale. PLoS Genet. 10: e1004264.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Singh, S. S., N. Singh, R. P. Bonocora, D. M. Fitzgerald, J. T. Wade, and D. C. Grainger (2014) Widespread suppression of intragenic transcription initiation by H-NS. Genes Dev. 28: 214–219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zere, T. R., C. A. Vakulskas, Y. Leng, A. Pannuri, A. H. Potts, R. Dias, D. Tang, B. Kolaczkowski, D. Georgellis, B. M. M. Ahmer, and T. Romeo (2015) Genomic targets and features of BarA-UvrY (-SirA) signal transduction systems. PLoS One. 10: e0145035.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Kahramanoglou, C., A. S. N. Seshasayee, A. I. Prieto, D. Ibberson, S. Schmidt, J. Zimmermann, V. Benes, G. M. Fraser, and N. M. Luscombe (2011) Direct and indirect effects of H-NS and Fis on global gene expression control i. Escherichia coli. Nucleic Acids Res. 39: 2073–2091.

    Article  CAS  PubMed  Google Scholar 

  63. Lee, N., S. Hwang, Y. Lee, S. Cho, B. Palsson, and B. K. Cho (2019) Synthetic biology tools for novel secondary metabolite discovery i. Streptomyces. J. Microbiol. Biotechnol. 29: 667–686.

    Article  CAS  PubMed  Google Scholar 

  64. Fitzgerald, D. M., R. P. Bonocora, and J. T. Wade (2014) Comprehensive map** of the Escherichia coli flagellar regulatory network. PLoS Genet. 10: e1004649.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Zhou, X., Q. Yan, and N. Wang (2017) Deciphering the regulon of a GntR family regulator via transcriptome and ChIP-exo analyses and its contribution to virulence i. Xanthomonas citri. Mol. Plant Pathol. 18: 249–262.

    Article  CAS  PubMed  Google Scholar 

  66. Seo, S. W., D. Kim, E. J. O’Brien, R. Szubin, and B. O. Palsson (2015) Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress i. Escherichia coli. Nat. Commun. 6: 7970.

    Article  CAS  PubMed  Google Scholar 

  67. Grainger, D. C., D. Hurd, M. D. Goldberg, and S. J. W. Busby (2006) Association of nucleoid proteins with coding and non-coding segments of th. Escherichia coli genome. Nucleic Acids Res. 34: 4642–4652.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Erhardt, M. and P. Dersch (2015) Regulatory principles governin. Salmonella and Yersinia virulence. Front. Microbiol. 6: 949.

    PubMed  Google Scholar 

  69. Yang, D., Y. Kong, W. Sun, W. Kong, and Y. Shi (2019) A Dopamine-responsive signal transduction controls transcription o. Salmonella enterica serovar Typhimurium virulence genes. mBio. 10: e02772–18.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Wang, H., B. Liu, Q. Wang, and L. Wang (2013) Genome-wide analysis of the salmonella Fis regulon and its regulatory mechanism on pathogenicity islands. PLoS One. 8: e64688.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Dillon, S. C., E. Espinosa, K. Hokamp, D. W. Ussery, J. Casadesus, and C. J. Dorman (2012) LeuO is a global regulator of gene expression i. Salmonella enterica serovar Typhimurium. Mol. Microbiol. 85: 1072–1089.

    Article  CAS  PubMed  Google Scholar 

  72. Hermans, K., S. Roberfroid, I. M. Thijs, G. Kint, D. De Coster, K. Marchal, J. Vanderleyden, S. C. J. De Keersmaecker, and H. P. Steenackers (2016) FabR regulate. Salmonella biofilm formation via its direct target FabB. BMC Genomics. 17: 253.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  73. Brzostek, K., K. Skorek, and A. Raczkowska (2012) OmpR a central integrator of several cellular responses i. Yersinia enterocolitica. Adv. Exp. Med. Biol. 954: 325–334.

    Article  CAS  PubMed  Google Scholar 

  74. Dorman, C. J., S. Chatfield, C. F. Higgins, C. Hayward, and G. Dougan (1989) Characterization of porin and ompR mutants of a virulent strain o. Salmonella typhimurium: ompR mutants are attenuated in vivo. Infect. Immun. 57: 2136–2140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Perkins, T. T., M. R. Davies, E. J. Klemm, G. Rowley, T. Wileman, K. James, T. Keane, D. Maskell, J. C. D. Hinton, G. Dougan, and R. A. Kingsley (2013) ChIP-seq and transcriptome analysis of the OmpR regulon o. Salmonella enterica serovars Typhi and Typhimurium reveals accessory genes implicated in host colonization. Mol. Microbiol. 87: 526–538.

    Article  CAS  PubMed  Google Scholar 

  76. Stringer, A. M., S. Currenti, R. P. Bonocora, C. Baranowski, B. L. Petrone, M. J. Palumbo, A. A. Reilly, Z. Zhang, I. Erill, and J. T. Wade (2014) Genome-scale analyses o. Escherichia coli and Salmonella enterica AraC reveal noncanonical targets and an expanded core regulon. J. Bacteriol. 196: 660–671.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Balasubramanian, D., S. K. Murugapiran, E. Silva-Herzog, L. Schenper, X. Yang, G. Tatke, G. Narasimhan, and K. Mathee (2013) Transcriptional regulatory network in Pseudomonas aeruginosa. pp. 195–248. In: M. M. Babu (ed.). Bacterial Gene Regulation and Transcriptional Networks. Caister Academic Press, Poole, UK.

    Google Scholar 

  78. Jones, C. J., D. Newsom, B. Kelly, Y. Irie, L. K. Jennings, B. Xu, D. H. Limoli, J. J. Harrison, M. R. Parsek, P. White, and D. J. Wozniak (2014) ChIP-Seq and RNA-Seq reveal an AmrZ-mediated mechanism for cyclic di-GMP synthesis and biofilm development b. Pseudomonas aeruginosa. PLoS Pathog. 10: e1003984.

    Article  PubMed  CAS  Google Scholar 

  79. Balasubramanian, D., H. Kumari, M. Jaric, M. Fernandez, K. H. Turner, S. L. Dove, G. Narasimhan, S. Lory, and K. Mathee (2014) Deep sequencing analyses expands th. Pseudomonas aeruginosa AmpR regulon to include small RNA-mediated regulation of iron acquisition, heat shock and oxidative stress response. Nucleic Acids Res. 42: 979–998.

    Article  CAS  PubMed  Google Scholar 

  80. Dorman, M. J. and C. J. Dorman (2018) Regulatory hierarchies controlling virulence gene expression i. Shigella flexneri and Vibrio cholerae. Front. Microbiol. 9: 2686.

    Article  PubMed  Google Scholar 

  81. Gao, X., Y. Liu, H. Liu, Z. Yang, Q. Liu, Y. Zhang, and Q. Wang (2017) Identification of the regulon of AphB and its essential roles in LuxR and exotoxin Asp expression in the pathoge. Vibrio alginolyticus. J. Bacteriol. 199: e00252–17.

    CAS  PubMed  Google Scholar 

  82. van Kessel, J. C., L. E. Ulrich, I. B. Zhulin, and B. L. Bassler (2013) Analysis of activator and repressor functions reveals the requirements for transcriptional control by LuxR, the master regulator of quorum sensing i. Vibrio harveyi. MBio. 4: e00378–13.

    PubMed  Google Scholar 

  83. Ayala, J. C., H. Wang, J. A. Benitez, and A. J. Silva (2015) RNA-Seq analysis and whole genome DNA-binding profile of th. Vibrio cholerae histone-like nucleoid structuring protein (H-NS). Genom. Data. 5: 147–150.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Davies, B. W., R. W. Bogard, and J. J. Mekalanos (2011) Map** the regulon o. Vibrio cholerae ferric uptake regulator expands its known network of gene regulation. Proc. Natl. Acad. Sci. USA. 108: 12467–12472.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Takano, E., R. Chakraburtty, T. Nihira, Y. Yamada, and M. J. Bibb (2001) A complex role for the gamma-butyrolactone SCB1 in regulating antibiotic production i. Streptomyces coelicolor A3(2). Mol. Microbiol. 41: 1015–1028.

    Article  CAS  PubMed  Google Scholar 

  86. Hanh, N. P. K., J. Y. Hwang, and D. H. Nam (2019) Biosynthesis of methoxymalonyl-acyl carrier protein (ACP) as an extender unit for bafilomycin polyketide i. Streptomyces griseus DSM 2608. Biotechnol. Bioprocess Eng. 23: 693–703.

    Article  CAS  Google Scholar 

  87. Tran, N. T., D. N. Pham, and C. J. Kim (2019) Production of 5-aminolevulinic acid by recombinan. Streptomyces coelicolor expressing hemA from Rhodobacter sphaeroides. Biotechnol. Bioprocess Eng. 24: 488–499.

    CAS  Google Scholar 

  88. Freyre-Gonzalez, J. A. and L. Treviño-Quintanilla (2010) Analyzing regulatory networks in bacteria. Nat. Edu. 3: 24.

    Google Scholar 

  89. Partridge, J. D., D. M. Bodenmiller, M. S. Humphrys, and S. Spiro (2009) NsrR targets in th. Escherichia coli genome: new insights into DNA sequence requirements for binding and a role for NsrR in the regulation of motility. Mol. Microbiol. 73: 680–694.

    Article  CAS  PubMed  Google Scholar 

  90. Barroso, R., S. M. Garcia-Maurino, L. Tomas-Gallardo, E. Andujar, M. Perez-Alegre, E. Santero, and I. Canosa (2018) The CbrB Regulon: Promoter dissection reveals novel insights into the CbrAB expression network in Pseudomonas putida. PLoS One. 13: e0209191.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. den Hengst, C. D., N. T. Tran, M. J. Bibb, G. Chandra, B. K. Leskiw, and M. J. Buttner (2010) Genes essential for morphological development and antibiotic production i. Streptomyces coelicolor are targets of BldD during vegetative growth. Mol. Microbiol. 78: 361–379.

    Article  CAS  PubMed  Google Scholar 

  92. Munnoch, J. T., M. T. Martinez, D. A. Svistunenko, J. C. Crack, N. E. Le Brun, and M. I. Hutchings (2016) Characterization of a putative NsrR homologue in Streptomyces venezuelae reveals a new member of the Rrf2 superfamily. Sci. Rep. 6: 31597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Swiatek-Polatynska, M. A., G. Bucca, E. Laing, J. Gubbens, F. Titgemeyer, C. P. Smith, S. Rigali, and G. P. van Wezel (2015) Genome-wide analysis o. in vivo binding of the master regulator DasR in Streptomyces coelicolor identifies novel non-canonical targets. PLoS One. 10: e0122479.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. Qian, Z., A. Trostel, D. E. A. Lewis, S. J. Lee, X. He, A. M. Stringer, J. T. Wade, T. D. Schneider, T. Durfee, and S. Adhya (2016) Genome-wide transcriptional regulation and chromosome structural arrangement by GalR i. E. coli. Front. Mol. Biosci. 3: 74.

    PubMed  Google Scholar 

  95. Salekin, S., J. M. Zhang, and Y. Huang (2017) A deep learning model for predicting transcription factor binding location at single nucleotide resolution. Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). February 16–19. Orlando, USA.

  96. Yang, J., A. Ma, A. D. Hoppe, C. Wang, Y. Li, C. Zhang, Y. Wang, B. Liu, and Q. Ma (2019) Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework. Nucleic Acids Res. 47: 7809–7824.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Massie, C. E. and I. G. Mills (2011) Global identification of androgen response elements. pp. 255–273. In: F. Saatcioglu (ed.). Androgen Action. Humana Press, New York, NY, USA.

    Chapter  Google Scholar 

  98. Ji, H., H. Jiang, W. Ma, D. S. Johnson, R. M. Myers, and W. H. Wong (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol. 26: 1293–1300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Ji, H. and W. H. Wong (2005) TileMap: create chromosomal map of tiling array hybridizations. Bioinformatics. 21: 3629–3636.

    Article  CAS  PubMed  Google Scholar 

  100. Zhu, L. J., C. Gazin, N. D. Lawson, H. Pagès, S. M. Lin, D. S. Lapointe, and M. R. Green (2010) ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data. BMC Bioinformatics. 11: 237.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  101. Zhang, Y., T. Liu, C. A. Meyer, J. Eeckhoute, D. S. Johnson, B. E. Bernstein, C. Nusbaum, R. M. Myers, M. Brown, W. Li, and X. S. Liu (2008) Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9: R137.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Spyrou, C., R. Stark, A. G. Lynch, and S. Tavaré (2009) BayesPeak: Bayesian analysis of ChIP-seq data. BMC Bioinformatics. 10: 299.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Yu, G, L. G. Wang, and Q. Y. He (2015) ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 31: 2382–2383.

    Article  CAS  PubMed  Google Scholar 

  104. Wang, L., J. Chen, C. Wang, L. Uusküla-Reimand, K. Chen, A. Medina-Rivera, E. J. Young, M. T. Zimmermann, H. Yan, Z. Sun, Y. Zhang, S. T. Wu, H. Huang, M. D. Wilson, J. P. A. Kocher, and W. Li (2014) MACE: model based analysis of ChIP-exo. Nucleic Acids Res. 42: e156.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

This work was funded by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded from the Ministry of Education (NRF-2017R1C1B2002441), from the Strategic Initiative for Microbiomes in Agriculture and Food, MAFRA, Republic of Korea as part of the (multi-ministerial) Genome Technology to Business Translation Program (918020-4).

The authors declare no conflict of interest.

Neither ethical approval nor informed consent was required for this study.

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Park, J.Y., Rimal, H., Bang, I. et al. Genome-wide Identification of DNA-protein Interaction to Reconstruct Bacterial Transcription Regulatory Network. Biotechnol Bioproc E 25, 944–954 (2020). https://doi.org/10.1007/s12257-020-0030-9

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