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Novel Genetic Techniques and Approaches in the Microbial Genomics Era

Identification and/or Validation of Targets for the Discovery of New Antibacterial Agents

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Abstract

The availability of microbial genome sequences has ushered in the genomics era and has led to numerous technical advancements over the past decade. These advances have been both in the bioinformatics field that has integrated computer-based approaches with biology and in research methods in the laboratory. The advances have assisted scientists in their study of bacterial gene complements and the roles of their gene products in the bacterial life cycle. Assignment of genes as essential to the bacterial cell nominated them as potential targets for antibacterial drugs and spurred attempts to exploit this information and convert it into drugs. At present, these efforts have met with minimal success. There are several possible reasons for these disappointing results including choice of targets and screen designs, compound libraries chosen for screens, and decreased commitment to antibacterial drug discovery by many large pharmaceutical companies. Structure-based approaches could become very effective in the future as methodologies continue to improve.

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References

  1. Armstrong GL, Conn LA, Pinner RW. Trends in infectious disease mortality in the United States during the 20th century. JAMA 1999 Jan 6; 281 (1): 61–6

    Article  PubMed  CAS  Google Scholar 

  2. Livermore DM. Bacterial resistance: origins, epidemiology, and impact. Clin Infect Dis 2003; 36 Suppl.: S11–23

    Article  PubMed  CAS  Google Scholar 

  3. Levy SB, Marshall, B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med 2004; 10 (12 Suppl.): S122–9

    Article  PubMed  CAS  Google Scholar 

  4. Projan SJ. Why is big Pharma getting out of antibacterial drug discovery? Curr Opin Microbiol 2003; 6 (5): 427–30

    Article  PubMed  Google Scholar 

  5. IDSA Report: Bad bugs, no drugs, as antibiotic discovery stagnates, a public health crisis brews: July 2004 [online]. Available from URL: http://www.idsociety.org [Accessed 2007 Jun 13]

    Google Scholar 

  6. Barrett CT, Barrett JF. Antibacterials: are the new entries enough to deal with the emerging resistance problems? Curr Opin Biotechnol 2003; 14 (6): 621–5

    Article  PubMed  CAS  Google Scholar 

  7. Fleischmann RD, Adams MD, White O, et al. Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 1995; 269 (5223): 496–512

    Article  PubMed  CAS  Google Scholar 

  8. Marguiles M, Egholm M, Altman WE, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature 2005; 437 (7057): 376–80

    Google Scholar 

  9. Fox JA, Butland SL, McMillan, et al. The Bioinformatics Links Directory: a compilation of molecular biology web servers. Nucleic Acids Res 2006; 34 (Web Server issue): W3–W24

    Article  PubMed  CAS  Google Scholar 

  10. Dharmadi Y, Gonzalez R. DNA microarrays: experimental issues, data analysis, and application to bacterial systems. Biotechnol Prog 2004; 20: 1309–24

    Article  PubMed  CAS  Google Scholar 

  11. Bandow JE, Brotz H, Leichert LI, et al. Proteomic approach to understanding antibiotic drug discovery. Antimicrob Agents Chemother 2003; 47 (3): 948–55

    Article  PubMed  CAS  Google Scholar 

  12. Barker JJ. Antibacterial drug discovery and structure-based design. Drug Discov Today 2006; 11 (9–10): 391–404

    Article  PubMed  CAS  Google Scholar 

  13. Clardy J, Fischbach MA, Walsh CT. New antibiotics from bacterial natural products. Nat Biotechnol 2006; 24 (12): 1541–50

    Article  PubMed  CAS  Google Scholar 

  14. Marra A. Targeting virulence for antibacterial chemotherapy. Drugs R D 2006; 7 (1): 1–16

    Article  PubMed  CAS  Google Scholar 

  15. Mazurkiewicz P, Tang CM, Boone C, et al. Signature-tagged mutagenesis: barcoding mutants for genome-wide screens. Nature Rev Genet 2006; 7 (12): 929–39

    Article  PubMed  CAS  Google Scholar 

  16. Raskin DM, Seshadri R, Pukatzki SU, et al. Bacterial genomics and pathogen evolution. Cell 2006; 124: 703–14

    Article  PubMed  CAS  Google Scholar 

  17. Web Server Issue. Nucleic Acids Res 2006; 34: W1–W752

    Article  Google Scholar 

  18. Chen YB, Chattopadhyay A, Bergen P, et al. The online bioinformatics resources collection at the University of Pittsburgh Health Sciences Library System: a one-step gateway to online bioinformatics databases and software tools. Nucleic Acids Res 2007; 35: D780–5

    Article  PubMed  CAS  Google Scholar 

  19. Altschul SF, Madden TL, Schäffer AA, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997; 25 (17): 3389–402

    Article  PubMed  CAS  Google Scholar 

  20. Chenna R, Sugawara H, Koike T, et al. Multiple sequence alignment with the Clustal series of programs. Nucleic Acids Res 2003; 31 (13): 3497–500

    Article  PubMed  CAS  Google Scholar 

  21. Morgenstern B, Frech K, Dress A, et al. DIALIGN: finding local similarities by multiple sequence alignment. Bioinformatics 1998; 14 (3): 290–4

    Article  PubMed  CAS  Google Scholar 

  22. Brudno M, Do CB, Cooper GM, et al. LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA. Genome Res 2003; 13 (4): 721–31

    Article  PubMed  CAS  Google Scholar 

  23. Bruccoleri RE, Dougherty TJ, Davison DB. Concordance analysis of microbial genomes. Nucleic Acids Res 1998; 26 (19): 4482–6

    Article  PubMed  CAS  Google Scholar 

  24. Dessimoz C, Boeckmann B, Roth AC, et al. Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits. Nucleic Acids Res 2006; 34 (11): 3309–16

    Article  PubMed  CAS  Google Scholar 

  25. Caspi R, Foerster H, Fulcher CA, et al. Meta Cyc: a multiorganism database of metabolic pathway enzymes. Nucleic Acids Res 2006; 34 (Database issue): D511–6

    Article  PubMed  CAS  Google Scholar 

  26. EcoCyc Kessler IM, Collado-Vides J, Gama-Castro S. EcoCyc: a comprehensive database resource for Escherichia coli. Nucleic Acids Res 2005; 33 (Database issue): D334–7

    Article  Google Scholar 

  27. Zhang R, Zhang C-T. The impact of comparative genomics on infectious disease research. Microbes Infect 2006; 8 (6): 1613–22

    Article  PubMed  CAS  Google Scholar 

  28. Alm RA, Ling LS, Moir DT, et al. Genomic-sequence comparison of two unrelated isolates of the human gastric pathogen Helicobacter pylori. Nature 1999; 397 (6715): 176–80

    Article  PubMed  Google Scholar 

  29. Hayashi T, Makino K, Ohnishi M, et al. Complete genome sequence of enterohemorrhagic Escherichia coli O157:H7 and genomic comparison with a laboratory strain K-12. DNA Res 2001; 8 (1): 11–22

    Article  PubMed  CAS  Google Scholar 

  30. Perna NT, Plunkett 3rd G, Burland V, et al. Genome sequence of enterohaemorrhagic Escherichia coli O157:H7. Nature 2001; 409 (6819): 529–33

    Article  PubMed  CAS  Google Scholar 

  31. Mau B, Glasner JD, Darling AE, et al. Genome-wide detection and analysis of homologous recombination among sequenced stains of Escherichia coli. Genome Biol 2006; 7 (5): R44

    Article  PubMed  Google Scholar 

  32. Lindsay JA, Holden MT. Understanding the rise of the superbug: investigation of the evolution and genomic variation of Staphylococcus aureus. Funct Integr Genomics 2006; 6 (3): 186–201

    Article  PubMed  CAS  Google Scholar 

  33. Holden MT, Feil RJ, Lindsay JA, et al. Complete genomes of two clinical Staphylococcus aureus strains: evidence for the rapid evolution of virulence and drug resistance. Proc Natl Acad Sci U S A 2004; 101 (26): 9786–91

    Article  PubMed  CAS  Google Scholar 

  34. Gill SR, Fouts DE, Archer GL, et al. Insights on evolution of virulence and resistance from the complete genome analysis of an early methicillin-resistant Staphylococcus aureus strain and a biofilm-producing methicillin-resistant Staphylococcus epidermidis strain. J Bacteriol 2005; 187 (7): 2426–38

    Article  PubMed  CAS  Google Scholar 

  35. Marri PR, Bannantine JP, Golding GB. Comparative genomics of metabolic pathways in Mycobacterium species: gene duplication, gene decay and lateral gene transfer. FEMS Microbiol Rev 2006; 30 (6): 906–25

    Article  PubMed  CAS  Google Scholar 

  36. Hain T, Steinweg C, Chakraborty T. Comparative and functional genomics of Listeria spp. J Biotechnol 2006; 126 (1): 37–51

    Article  PubMed  CAS  Google Scholar 

  37. Hotopp JC, Lin M, Madupu R, et al. Comparative genomics of emerging human ehrlichiosis agents. PLoS Genet 2006; 2 (2): e21

    Article  Google Scholar 

  38. Parkhill J, Sebaihia A, Preston A, et al. Comparative analysis of the genome sequences of Bordetella pertussis, Bordetella parapertussis and Bordetella bronchiseptica. Nat Genet 2003; 35 (1): 32–40

    Article  PubMed  Google Scholar 

  39. Rasko DA, Altherr MR, Han CS, et al. Genomics of the Bacillus cereus group of organisms. FEMS Microbiol Rev 2005; 29 (2): 303–29

    PubMed  CAS  Google Scholar 

  40. Anderson I, Sorokin A, Kapatrol V, et al. Comparative genome analysis of Bacillus cereus group genomes with Bacillus subtilis. FEMS Microbiol Lett 2005; 250 (2): 175–84

    Article  PubMed  CAS  Google Scholar 

  41. Payne DJ, Gywnn MN, Holmes DJ, et al. Drugs for bad drugs: confronting the challenges of antibacterial discovery. Nat Rev Drug Discov 2007; 6 (1): 29–40

    Article  PubMed  CAS  Google Scholar 

  42. Pucci MJ, Dougherty TD. Use of genomics to select antibacterial targets. Biochem Pharmacol 2006; 71 (7): 1066–72

    Article  PubMed  CAS  Google Scholar 

  43. Glass JI, Assad-Garcia N, Alperovich N, et al. Essential genes of a minimal bacterium. Proc Natl Acad Sci U S A 2006; 103 (2): 425–30

    Article  PubMed  CAS  Google Scholar 

  44. Freiberg C, Brotz-Oesterhelt H. Functional genomics in antibacterial drug discovery. Drug Discov Today 10 (13): 927–935

  45. Thanassi JA, Hartman-Neumann SL, Dougherty TJ, et al. Identification of 113 conserved essential genes using a high-throughput gene disruption system in Streptococcus pneumoniae. Nucleic Acids Res 2002; 30: 3152–62

    Article  PubMed  CAS  Google Scholar 

  46. Gerdes SY, Scholle MD, Campbell JW, et al. Experimental determination and system level analysis of essential genes in Escherichia coli MG1655. J Bacteriol 2003; 185 (19): 5673–84

    Article  PubMed  CAS  Google Scholar 

  47. Akerley BJ, Rubin EJ, Novick VL, et al. A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae. Proc Natl Acad Sci U S A 2002; 99 (2): 966–71

    Article  PubMed  CAS  Google Scholar 

  48. Forsyth RA, Haselbeck RJ, Ohlsen KL, et al. A genome-wide strategy for the identification of essential genes in Staphylococcus aureus. Mol Microbiol 2002; 43 (6): 1387–400

    Article  PubMed  CAS  Google Scholar 

  49. Ji Y, Zhang B, Van SF, et al. Identification of critical staphylococcal genes using conditional phenotypes generated by antisense RNA. Science 2001; 293 (5538): 2266–9

    Article  PubMed  CAS  Google Scholar 

  50. DeVito JA, Mills JA, Liu VG, et al. An array of target-specific screening strains for antibacterial discovery. Nat Biotechnol 2002 May; 20 (5): 478–83

    Article  PubMed  CAS  Google Scholar 

  51. Zhang L, Fan F, Palmer LM, et al. Regulated gene expression in Staphylococcus aureus for identifying conditional lethal phenotypes and antibiotic mode of action. Gene 2000; 255 (2): 297–305

    Article  PubMed  CAS  Google Scholar 

  52. Huang J, O’Toole PW, Shen W, et al. Novel chromosomally encoded multidrug efflux transporter MdeA in Staphylococcus aureus. Antimicrob Agents Chemother 2004; 48 (3): 909–17

    Article  PubMed  CAS  Google Scholar 

  53. Badger J, Sauder JM, Adams JM, et al. Structural analysis of a set of proteins resulting from a bacterial genomics project. Proteins: Struct Funct Bioinform 2005; 60: 787–96

    Article  CAS  Google Scholar 

  54. Fogg MJ, Alzari P, Bahar M, et al. Application of the use of high-throughput technologies to the determination of protein structures of bacterial and viral pathogens. Acta Crystallogr D Biol Crystallogr 2006; 62 (Pt 10): 1196–207

    Article  PubMed  CAS  Google Scholar 

  55. Au K, Berrow NS, Blagova E, et al. Application of high-throughput technologies to a structural proteomics-type analysis of Bacillus anthracis. Acta Crystallogr D Biol Crystallogr 2006; 62 (Pt 10): 1267–75

    Article  PubMed  CAS  Google Scholar 

  56. Su XD, Liang Y, Li L, et al. A large-scale, high-efficiency and low-cost platform for structural genomics studies. Acta Crystallogr D Biol Crystallogr 2006; 62 (Pt 8): 843–51

    Article  PubMed  Google Scholar 

  57. Hermann T. Drugs targeting the ribosome. Curr Opin Struct Biol 2005; 15 (3): 355–66

    Article  PubMed  CAS  Google Scholar 

  58. Sutcliffe JA. Improving on nature: antibiotics that target the ribosome. Curr Opin Microbiol 2005; 8 (5): 534–42

    Article  PubMed  CAS  Google Scholar 

  59. Franceschi F, Duffy EM. Structure-based drug design meets the ribosome. Biochem Pharmacol 2006; 71 (7): 1016–25

    Article  PubMed  CAS  Google Scholar 

  60. Grossman TH, Bartels DJ, Mullin S, et al. Dual targeting of GyrB and ParE by a novel aminobenzimidazole class of antibacterial compounds. Antimicrob Agents Chemother 2007; 51 (2): 657–66

    Article  PubMed  CAS  Google Scholar 

  61. Howard MH, Cenizal T, Gutteridge S, et al. A novel class of inhibitors of peptide deformylase discovered through high-throughput screening and virtual ligand screening. J Med Chem 2004; 47 (27): 6669–72

    Article  PubMed  CAS  Google Scholar 

  62. Nie Z, Perretta C, Lu J, et al. Structure-based design, synthesis, and study of potent inhibitors of beta-ketoacyl-acyl carrier protein synthase III as potential antimicrobial agents. J Med Chem 2005; 48 (5): 1596–609

    Article  PubMed  CAS  Google Scholar 

  63. Wang J, Soisson SM, Young K, et al. Platensimycin is a selective FabF inhibitor with potent antibiotic properties. Nature 2006; 441 (7091): 358–61

    Article  PubMed  CAS  Google Scholar 

  64. Seefeld MA, Miller WH, Newlander KA, et al. Indole naphthyridinones as inhibitors of bacterial enoyl-ACP reductases FabI and FabK. J Med Chem 2003; 46 (9): 1627–35

    Article  PubMed  CAS  Google Scholar 

  65. Reck F, Zhou F, Giradot M, et al. Identification of 4-substituted 1,2,3-triazoles as novel oxazolidinone antibacterial agents with reduced activity against monoamine oxidase A. J Med Chem 2005; 48 (2): 499–506

    Article  PubMed  CAS  Google Scholar 

  66. Depristo MA, deBakker PI, Blundell TL. Heterogeneity and inaccuracy in protein structures solved by x-ray crystallography. Structure 2004; 12 (5): 831–8

    Article  PubMed  CAS  Google Scholar 

  67. Erlanson DA, McDowell RS, O’Brien T. Fragment based drug discovery. J Med Chem 2004; 47 (14): 3463–82

    Article  PubMed  CAS  Google Scholar 

  68. Shuker SB, Hadjuk PJ, Meadows RP, et al. Discovering high-affinity ligands for proteins: SAR by NMR. Science 1996; 274 (5292): 1531–4

    Article  PubMed  CAS  Google Scholar 

  69. Tsao DH, Sutherland AG, Jennings LD, et al. Discovery of novel inhibitors of the ZipA/FtsZ complex by NMR fragment screening coupled with structure-based design. Bioorg Med Chem 2006; 14 (23): 7953–61

    Article  PubMed  CAS  Google Scholar 

  70. Chen D, Yuan Z. Therapeutic potential of peptide deformylase inhibitors. Expert Opin Investig Drugs 2005; 14 (9): 1107–16

    Article  PubMed  CAS  Google Scholar 

  71. Freiberg C, Brotz-Oesterhelt H. Functional genomics in antibacterial drug discovery. Drug Discov Today 2005; 10 (13): 927–35

    Article  PubMed  CAS  Google Scholar 

  72. Conway T, Schoolnik GK. Microarray expression profiling: capturing a genome-wide portrait of the transcriptome. Mol Microbiol 2003; 47 (4): 879–89

    Article  PubMed  CAS  Google Scholar 

  73. Schoolnik GK. Microarray analysis of bacterial pathogenicity. Adv Microb Physiol 2002; 46: 1–45

    Article  PubMed  CAS  Google Scholar 

  74. Petersohn A, Brigulla M, Haas S. Global analysis of the general stress response of Bacillus subtilis. J Bacteriol 2001; 183 (19): 5617–31

    Article  PubMed  CAS  Google Scholar 

  75. Van Bogelen RA, Schiller EE, Thomas JD, et al. Diagnosis of cellular states of microbial organisms using proteomics. Electrophoresis 1999; 20 (11): 2149–59

    Article  Google Scholar 

  76. Han MJ, Lee SY. The Escherichia coli proteome: past, present, and future prospects. Microbiol Mol Biol Rev 2006; 70 (2): 362–439

    Article  PubMed  CAS  Google Scholar 

  77. Hecker M, Volker U. Towards a comprehensive understanding of Bacillus subtilis cell physiology by physiological proteomics. Proteomics 2004; 4 (12): 3727–50

    Article  PubMed  CAS  Google Scholar 

  78. Mawuenyega KG, Forst CV, Dobos KM, et al. Mycobacterium tuberculosis functional network analysis by global subcellular protein profiling. Mol Biol Cell 2005; 16 (1): 396–404

    Article  PubMed  CAS  Google Scholar 

  79. Brazas MD, Hancock RE. Using microarray gene signatures to elucidate mechanisms of antibiotic action and resistance. Drug Discov Today 2005; 10 (18): 1245–52

    Article  PubMed  CAS  Google Scholar 

  80. Ng WL, Kazmierczak KM, Robertson GT. Transcriptional regulation and signature patterns revealed by microarray analyses of Streptococcus pneumoniae R6 challenged with sublethal concentrations of translation inhibitors. J Bacteriol 2003; 185 (1): 359–70

    Article  PubMed  CAS  Google Scholar 

  81. Lin JT, Connelly MB, Amolo C, et al. Global transcriptional response of Bacillus subtilis to treatment with subinhibitory concentrations of antibiotics that inhibit protein synthesis. Antimicrob Agents Chemother 2005; 49 (5): 1915–26

    Article  PubMed  CAS  Google Scholar 

  82. Freiberg C, Fischer HP, Brunner NA. Discovering the mechanism of action of novel antibacterial agents through transcriptional profiling of conditional mutants. Antimicrob Agents Chemother 2005; 49 (2): 749–59

    Article  PubMed  CAS  Google Scholar 

  83. Fraser CM, Rappouli R. Application of microbial genomic science to advanced therapeutics. Annu Rev Med 2005; 56: 459–74

    Article  PubMed  CAS  Google Scholar 

  84. Boshoff HIM, Manjunatha UH. The impact of genomics on discovering drugs against infectious diseases. Microbes Infect 2006; 8: 1654–61

    Article  PubMed  CAS  Google Scholar 

  85. Chen D, Yuan Z. Therapeutic potential of peptide deformylase inhibitors. Expert Opin Investig Drugs 2005; 14 (9): 1107–16

    Article  PubMed  CAS  Google Scholar 

  86. Chan PF, Holmes DJ, Payne DJ. Finding the gems using genomic discovery: antibacterial drug discovery strategies: the successes and the challenges. Drug Discov Today: Ther Strategies 2004; 1 (4): 519–27

    Article  CAS  Google Scholar 

  87. Dougherty TJ, Miller PF. Microbial genomics and drug discovery: exploring innovative routes of drug discovery in the postgenomic era. IDrugs 2006; 9 (6): 420–2

    PubMed  CAS  Google Scholar 

  88. Black MT, Hodgson J. Novel target sites in bacteria for overcoming antibiotic resistance. Adv Drug Deliv Rev 2005; 57: 1528–38

    Article  PubMed  CAS  Google Scholar 

  89. Li XZ, Nikaido H. Efflux-mediated drug resistance in bacteria. Drugs 2004; 64 (2): 159–204

    Article  PubMed  CAS  Google Scholar 

  90. Darvas F, Gorman G, Krajcsi P, et al. Recent advances in chemical genomics. Curr Med Chem 2004; 11 (23): 3119–45

    Article  PubMed  CAS  Google Scholar 

  91. Lipinski CA, Lombardo F, Dominy BW, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 2001; 46 (1–3): 3–26

    Article  Google Scholar 

  92. Singh SB, Barrett JF. Empirical antibacterial drug discovery: foundation in natural products. Biochem Pharmacol 2006; 71 (7): 1006–15

    Article  PubMed  CAS  Google Scholar 

  93. Young K, Jayasuriya H, Ondeyka JG, et al. Discovery of FabH/FabF inhibitors from natural products. Antimicrob Agents Chemother 2006; 50 (2): 519–26

    Article  PubMed  CAS  Google Scholar 

  94. Christoffersen RE. Antibiotics: an investment worth making? Nat Biotechnol 2006; 24 (12): 1512–4

    Article  PubMed  CAS  Google Scholar 

  95. Fox JL. The business of developing antibacterials. Nat Biotechnol 2006; 24 (12): 1521–8

    Article  PubMed  CAS  Google Scholar 

  96. Fernandes P. Antibacterial discovery and development: the failure of success? Nat Biotechnol 2006; 24 (12): 1497–503

    Article  PubMed  CAS  Google Scholar 

  97. Becker D, Selbach M, Rollenhagen C, et al. Robust Salmonella metabolism limits possibilities for new antimicrobials. Nature 2006; 440: 303–7

    Article  PubMed  CAS  Google Scholar 

  98. Leeds JA, Schmitt EK, Krastel P. Recent developments in antibacterial drug discovery: microbe-derived natural products: from collection to the clinic. Expert Opin Investig Drugs 2006; 15 (3): 211–26

    Article  PubMed  CAS  Google Scholar 

  99. Shoichet BK. Virtual screening of chemical libraries. Nature 2004; 432: 862–5

    Article  PubMed  CAS  Google Scholar 

  100. Congreve M, Murray CW, Blundell TL. Structural biology and drug discovery. Drug Discov Today 2005; 10 (13): 895–907

    Article  PubMed  CAS  Google Scholar 

  101. Vicente M, Hodgson J, Massidda O, et al. The fallacies of hope: will we discover new antibiotics to combat pathogenic bacteria in time? FEMS Microbiol Rev 2006; 30: 841–52

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

No sources of funding were used in the preparation of this review; although Dr Pucci wrote this review as an employee of Achillion Pharmaceuticals, they did not fund this in any way, nor did he use any data generated at Achillion.

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    Michael J. Pucci

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Pucci, M.J. Novel Genetic Techniques and Approaches in the Microbial Genomics Era. Drugs R D 8, 201–212 (2007). https://doi.org/10.2165/00126839-200708040-00001

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