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Immunoinformatics pp 329–347Cite as

Dynamics of Mycobacteriophage—Mycobacterial Host Interaction

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2131))

Abstract

Mycobacterium sp. is exhibiting complex evolution of antimicrobial resistance (AMR) and can therefore be considered as a serious human pathogen. Many strategies were employed earlier to evade the pathogenesis but AMR became threatened. Molecular tools employing bacteriophage can be an alternative to effective treatment against Mycobacterium. Phage treatment using phage-encoded products, such as lysins, causes lysis of cells; particularly bacteria could be used instead of direct use of these bacteriophages. Modern technologies along with bacteriophage strategies such as in silico immunoinformatics approach, machine learning, and artificial intelligence have been described thoroughly to escape the pathogenesis. Therefore, understanding the molecular mechanisms could be a possible alternative to evade the pathogenesis.

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References

  1. Hatfull GF (2012) The secret lives of mycobacteriophages. Adv Virus Res 82:179–288

    Article  CAS  PubMed  Google Scholar 

  2. Chanishvili N (2012) Phage therapy – history from Twort and d’Herelle through Soviet experience to current approaches. Adv Virus Res 83:3–40

    Article  CAS  PubMed  Google Scholar 

  3. Hendrix RW (2003) Bacteriophage genomics. Curr Opin Microbiol 6:506–511

    Article  CAS  PubMed  Google Scholar 

  4. Hatfull GF (2008) Bacteriophage genomics. Curr Opin Microbiol 11:447–453

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Suttle CA (2007) Marine viruses – major players in the global ecosystem. Nat Rev Microbiol 5:801–812

    Article  CAS  PubMed  Google Scholar 

  6. Rybniker J, Kramme S, Small PL (2006) Host range of 14 mycobacteriophages in Mycobacterium ulcerans and seven other mycobacteria including Mycobacterium tuberculosis—application for identification and susceptibility testing. J Med Microbiol 55:37–42

    Article  CAS  PubMed  Google Scholar 

  7. Bowman BU (1969) Properties of mycobacteriophage DS6A. I. Immunogenicity in rabbits. Proc Soc Exp Biol Med 131:196–200

    Article  CAS  PubMed  Google Scholar 

  8. Jones WD Jr (1975) Differentiation of known strains of BCG from isolates of Mycobacterium bovis and Mycobacterium tuberculosis by using mycobacteriophage 33D. J Clin Microbiol 1:391–392

    Article  PubMed  PubMed Central  Google Scholar 

  9. Phillips LM, Sellers MI (1970) Effects of ethambutol, actinomycin D and mitomycin C on the biosynthesis of D29-infected mycobacterium smegmatis. In: Juhasz SE, Plummer G (eds) Host-virus relationships in mycobacterium, nocardia and actinomyces. Charles C. Thomas, Springfield, pp 80–102

    Google Scholar 

  10. David HL, Clavel S, Clement F, Moniz-Pereira J (1980) Effects of antituberculosis and antileprosy drugs on mycobacteriophage D29 growth. Antimicrob Agents Chemother 18:357–359

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Tokunaga T, Kataoka T, Suga K (1970) Phage inactivation by an ethanol-ether extract of Mycobacterium smegmatis. Am Rev Respir Dis 101:309–313

    CAS  PubMed  Google Scholar 

  12. Furuchi A, Tokunaga T (1972) Nature of the receptor substance of Mycobacterium smegmatis for D4 bacteriophage adsorption. J Bacteriol 111:404–411

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bisso G, Castelnuovo G, Nardelli MG, Orefici G, Arancia G, Lanéelle G, Asselineau C, Asselineau J (1976) A study on the receptor for a mycobacteriophage: phage phlei. Biochimie 58:87–97

    Article  CAS  PubMed  Google Scholar 

  14. Khoo KH, Suzuki R, Dell A, Morris HR, McNeil MR, Brennan PJ, Besra GS (1996) Chemistry of the lyxose-containing mycobacteriophage receptors of Mycobacterium phlei/Mycobacterium smegmatis. Biochemistry 35:11812–11819

    Article  CAS  PubMed  Google Scholar 

  15. Chen J, Kriakov J, Singh A, Jacobs WR Jr, Besra GS, Bhatt A (2009) Defects in glycopeptidolipid biosynthesis confer phage I3 resistance in Mycobacterium smegmatis. Microbiology 155:4050–4057

    Article  CAS  PubMed  Google Scholar 

  16. Hatfull GF (2013) Complete genome sequences of 63 mycobacteriophages. Genome Announc 1(6):e00847–e00813

    Article  PubMed  PubMed Central  Google Scholar 

  17. Hatfull GF (2014) Mycobacteriophages: windows into tuberculosis. PLoS Pathog 10(3):e1003953

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, Harris D (1998) Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393(6685):537e44

    Article  Google Scholar 

  19. Jacobs-Sera D, Marinelli LJ, Bowman C, Broussard GW, Guerrero Bustamante C, Boyle MM, Petrova ZO, Dedrick RM, Pope WH, Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Science Sea-Phages Program, Modlin RL, Hendrix RW, Hatfull GF (2012) On the nature of mycobacteriophage diversity and host preference. Virology 434:187–201

    Article  CAS  PubMed  Google Scholar 

  20. Court DL, Oppenheim AB, Adhya SL (2007) A new look at bacteriophage lambda genetic networks. J Bacteriol 189:298–304

    Article  CAS  PubMed  Google Scholar 

  21. Zumla A, George A, Sharma V, Herbert N, Baroness Masham of Ilton (2013) WHO’s 2013 global report on tuberculosis: successes, threats, and opportunities. Lancet 382(9907):1765e7

    Article  Google Scholar 

  22. Waites MJ, Morgan NL, Rockey JS, Higton G (2001) Industrial microbiology: an introduction. Blackwell Science Ltd, Hoboken, p 177

    Google Scholar 

  23. Fruciano DE, Bourne S (2007) Phage as an antimicrobial agent: d’Herelle’s heretical theories and their role in the decline of phage prophylaxis in the West. Can J Infect Dis Med Microbiol 18:19–26

    Article  PubMed  PubMed Central  Google Scholar 

  24. Herelle FD (1917) An invisible microbe that is antagonistic to the dysentery bacillus Cozzes rendus. Acad Sci 165:373–375

    Google Scholar 

  25. Levin BR, Bull JJ (2004) Population and evolutionary dynamics of phage therapy. Nat Rev Microbiol 2:166–173. https://doi.org/10.1038/nrmicro822

    Article  PubMed  Google Scholar 

  26. Lu TK, Koeris MS (2011) The next generation of bacteriophage therapy. Curr Opin Microbiol 14:524–531. https://doi.org/10.1016/j.mib.2011.07.028

    Article  PubMed  Google Scholar 

  27. Radetsky P (1996) The good virus. Discover. http://discovermagazine.com/1996/nov/thegoodvirus918

  28. Samaddar S, Grewal RK, Sinha S, Ghosh S, Roy S, Gupta SKD (2016) Dynamics of mycobacteriophage-mycobacterial host interaction: evidence for secondary mechanisms for host lethality. Appl Environ Microbiol 82:124–133

    Article  CAS  PubMed  Google Scholar 

  29. Berry M, Gurung A, Easty DL (1995) Toxicity of antibiotics and antifungals on cultured human corneal cells: effect of mixing, exposure and concentration. Eye 9(Part 1):110–115. https://doi.org/10.1038/eye.1995.17

    Article  PubMed  Google Scholar 

  30. Lees AW, Allan GW, Smith J, Tyrrell WF, Fallon RJ (1971) Toxicity form rifampicin plus isoniazid and rifampicin plus ethambutol therapy. Tubercle 52:182–190. https://doi.org/10.1016/0041-3879(71)90041-9

    Article  CAS  PubMed  Google Scholar 

  31. Fenton M, Ross P, McAuliffe O, O’Mahony J, Coffey A (2010) Recombinant bacteriophage lysins as antibacterials. Bioeng Bugs 1:9–16. https://doi.org/10.4161/bbug.1.1.9818

    Article  PubMed  PubMed Central  Google Scholar 

  32. Fischetti VA (2008) Bacteriophage lysins as effective antibacterials. Curr Opin Microbiol 11:393–400. https://doi.org/10.1016/j.mib.2008.09.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Matsuzaki S, Rashel M, Uchiyama J, Sakurai S, Ujihara T, Kuroda M, Ikeuchi M, Tani T, Fujieda M, Wakiguchi H, Imai S (2005) Bacteriophage therapy: a revitalized therapy against bacterial infectious diseases. J Infect Chemother 11:211–219. https://doi.org/10.1007/s10156-005-0408-9

    Article  PubMed  Google Scholar 

  34. Schuch R, Nelson D, Fischetti VA (2002) A bacteriolytic agent that detects and kills Bacillus anthracis. Nature 418:884–889. https://doi.org/10.1038/nature01026

    Article  CAS  PubMed  Google Scholar 

  35. Miller ES, Kutter E, Mosig G, Arisaka F, Kunisawa T, Ruger W (2003) Bacteriophage T4 genome. Microbiol Mol Biol Rev 67:86–156. https://doi.org/10.1128/MMBR.67.1.86-156.2003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Monk A, Rees C, Barrow P, Hagens S, Harper D (2010) Bacteriophage applications: where are we now? Lett. Appl. Microbiol 51:363–369. https://doi.org/10.1111/j.1472-765X.2010.02916.x

    Article  CAS  PubMed  Google Scholar 

  37. Williams MM, Yakrus MA, Arduino MJ, Cooksey RC, Crane CB, Banerjee SN, Hilborn ED, Donlan RM (2009) Structural analysis of biofilm formation by rapidly and slowly growing nontuberculous mycobacteria. Appl Environ Microbiol 75:2091–2098

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Colijn C, Cohen T, Ganesh A, Murray M (2011) Spontaneous emergence of multiple drug resistance in tuberculosis before and during therapy. PLoS One 6:e18327. https://doi.org/10.1371/journal.pone.0018327

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Gillespie SH (2002) Evolution of drug resistance in Mycobacterium tuberculosis: clinical and molecular perspective. Antimicrob Agents Chemother 46:267–274. https://doi.org/10.1128/AAC.46.2.267-274.2002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Trigo G, Martins TG, Fraga AG, Longatto-Filho A, Castro AG, Azeredo J, Pedrosa J (2013) Phage therapy is effective against infection by Mycobacterium ulcerans in a murine footpad model. PLoS Negl Trop Dis 7:e2183. https://doi.org/10.1371/journal.pntd.0002183

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ford ME, Stenstrom C, Hendrix RW, Hatfull GF (1998) Mycobacteriophage TM4: genome structure and gene expression. Tuber Lung Dis 79:63–73. https://doi.org/10.1054/tuld.1998.0007

    Article  CAS  PubMed  Google Scholar 

  42. Fullner KJ, Hatfull GF (1997) Mycobacteriophage L5 infection of Mycobacterium bovis BCG: implications for phage genetics in the slow-growing mycobacteria. Mol. Microbio. 26:755–766

    Article  CAS  Google Scholar 

  43. Hatfull GF, Sarkis GJ (1993) DNA sequence, structure and gene expression of mycobacteriophage L5: a phage system for mycobacterial genetics. Mol Microbiol 7:395–405. https://doi.org/10.1111/j.1365-2958.1993.tb01131.x

    Article  CAS  PubMed  Google Scholar 

  44. Piuri M, Hatfull GF (2006) A peptidoglycan hydrolase motif within the mycobacteriophage TM4 tape measure protein promotes efficient infection of stationary phase cells. Mol Microbiol 62:1569–1585. https://doi.org/10.1111/j.1365-2958.2006.05473.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Pedulla ML, Ford ME, Houtz JM, Karthikeyan T, Wadsworth C, Lewis JA, Jacobs-Sera D, Falbo J, Gross J, Pannunzio NR, Brucker W, Kumar V, Kandasamy J, Keenan L, Bardarov S, Kriakov J, Lawrence JG, Jacobs WR Jr, Hendrix RW, Hatfull GF (2003) Origins of highly mosaic mycobacteriophage genomes. Cell 113:171–182

    Article  CAS  PubMed  Google Scholar 

  46. Pena CE, Judy S, Hatfull Graham F (1998) Mycobacteriophage D29 integrase-mediated recombination: specificity of mycobacteriophage integration. Gene 225:143

    Article  CAS  PubMed  Google Scholar 

  47. Donnelly-Wu MK, Jacobs WR Jr, Hatfull GF (1993) Superinfection immunity of mycobacteriophage L5: applications for genetic transformation of mycobacteria. Mol Microbiol 7:407–417

    Article  CAS  PubMed  Google Scholar 

  48. Doke S (1960) Studies on mycobacteriophages and lysogenic mycobacteria. J Kumamoto Med Soc 34:1360–1373

    Google Scholar 

  49. Lee MH, Pascopella L, Jacobs WR Jr, Hatfull GF (1991) Site-specific integration of mycobacteriophage L5: integration-proficient vectors for Mycobacterium smegmatis, Mycobacterium tuberculosis, and bacille Calmette-Guerin. Proc Natl Acad Sci U S A 88:3111–3115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Chatterjee S, Mitra M, Das Gupta SK (2000) A high yielding mutant of mycobacteriophage L1 and its application as a diagnostic tool. FEMS Microbiol Lett 188:47–53

    Article  CAS  PubMed  Google Scholar 

  51. Chaudhuri B, Sau S, Datta HJ, Mandal NC (1993) Isolation, characterization, and mapping of temperature-sensitive mutations in the genes essential for lysogenic and lytic growth of the mycobacteriophage L1. Virology 194:166–172

    Article  CAS  PubMed  Google Scholar 

  52. Freitas-Vieira A, Anes E, Moniz-Pereira J (1998) The site-specific recombination locus of mycobacteriophage Ms6 determines DNA integration at the tRNA(Ala) gene of Mycobacterium spp. Microbiology 144:3397–3406

    Article  CAS  PubMed  Google Scholar 

  53. Bowman B Jr (1958) Quantitative studies on some mycobacterialphage host systems. J.Bacteriol 76:52–62

    Article  PubMed  PubMed Central  Google Scholar 

  54. Timme TL, Brennan PJ (1984) Induction of bacteriophage from members of the Mycobacterium avium, Mycobacterium intracellulare, Mycobacterium scrofulaceum serocomplex. J Gen Microbiol 130:2059–2066

    CAS  PubMed  Google Scholar 

  55. Young R (1992) Bacteriophage lysis: mechanism and regulation. Microbiol Rev 56:430–481

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Young R (2002) Bacteriophage holins: deadly diversity. J Mol Microbiol Biotechnol 4:21–36

    CAS  PubMed  Google Scholar 

  57. Loessner MJ (2005) Bacteriophage endolysins – current state of research and applications. Curr Opin Microbiol 8:480–487

    Article  CAS  PubMed  Google Scholar 

  58. Berry J, Rajaure M, Pang T, Young R (2012) The spanin complex is essential for lambda lysis. J Bacteriol 194:5667–5674

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Catalão MJ, Gil F, Moniz-Pereira J, São-José C, Pimentel M (2013) Diversity in bacterial lysis systems: bacteriophages show the way. FEMS Microbiol Rev 37:554–571

    Article  PubMed  CAS  Google Scholar 

  60. Capparelli R, Parlato M, Borriello G, Salvatore P, Iannelli D (2007) Experimental phage therapy against Staphylococcus aureus in mice. Antimicrob Agents Chemother 51:2765–2773

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Denou E, Bruttin A, Barretto C, Ngom-Bru C, Brüssow H, Zuber S (2009) T4 phages against Escherichia coli diarrhea: Potential and problems. Virology 388:21–30

    Article  CAS  PubMed  Google Scholar 

  62. Kaźmierczak Z, Górski A, Dąbrowska K (2014) Facing antibiotic resistance: Staphylococcus aureus phages as a medical tool. Viruses 6:2551–2570

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Pires DP, Vilas Boas D, Sillankorva S, Azeredo J (2015) Phage therapy: a Step forward in the treatment of Pseudomonas aeruginosa infections. J Virol 89:7449–7456

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Chhibber S, Kaur S, Kumari S (2008) Therapeutic potential of bacteriophage in treating Klebsiella pneumoniae B5055-mediated lobar pneumonia in mice. J Med Microbiol 57:1508–1513

    Article  PubMed  Google Scholar 

  65. Strój L, Weber-Dabrowska B, Partyka K, Mulczyk M, Wójcik M (1999) Successful treatment with bacteriophage in purulent cerebrospinal meningitis in a newborn. Neurol Neurochir Pol 33:693–698

    PubMed  Google Scholar 

  66. Cisło M, Dabrowski M, Weber-Dabrowska B, Woytoń A (1987) Bacteriophage treatment of suppurative skin infections. Arch Immunol Ther Exp (Warsz) 35:175–183

    Google Scholar 

  67. Kwarcinski W, Lazarkiewicz B, Weber-Dabrowska B, Rudnicki J, Kaminski K, Sciebura M (1994) Bacteriophage therapy in the treatment of repeated subphrenic abscess and subhepatic abscess with jejunal fistula after stomach resection. Pol Tyg Lek 49:535

    CAS  PubMed  Google Scholar 

  68. Shabalova IA, Karpanov NI, Krylov VN, Sharibjanova TO, Akhverdijan VZ (1995) Pseudomonas aeruginosa bacteriophage in treatment of p. aeruginosa infection in cystic fibrosis patients. In Proceedings of IX International Cystic Fibrosis Congress. International Cystic Fibrosis Association, Zurich, Switzerland, p. 443

    Google Scholar 

  69. Proskurov VA (1970) Use of staphylococcal bacteriophage for therapeutic and preventive purposes. Zh Mikrobiol Epidemiol Immunobiol 47:104–107

    CAS  PubMed  Google Scholar 

  70. Pavlenishvili I, Tsertsvadze T (1993) Bacteriophagotherapy and enterosrbtion in treatment of sepsis of newborns caused by gram negative bacteria. Pren Neon Infect 11:104

    Google Scholar 

  71. Perepanova TS, Darbeeva OS, Kotliarova GA, Kondrat’eva EM, Maĭskaia LM, Malysheva VF, Baĭguzina FA, Grishkova NV (1995) The efficacy of bacteriophage preparations in treating inflammatory urologic diseases. Urol Nefrol (Mosk) 5:14–17

    Google Scholar 

  72. D’hérelle F (1923) (1993) The Bacteriophage, Its Role in Immunity. Ind Med Gaz. 58(9):443–444

    Google Scholar 

  73. Brüssow H (2005) Phage therapy: the Escherichia coli experience. Microbiology 151:2133–2140

    Article  PubMed  CAS  Google Scholar 

  74. Kaur S, Harjai K, Chhibber S (2014) Bacteriophage-aided intracellular killing of engulfed methicillin-resistant Staphylococcus aureus (MRSA) by murine macrophages. Appl Microbiol Biotechnol 98:4653–4661

    Article  CAS  PubMed  Google Scholar 

  75. Gondil VS, Chhibber S (2017) Evading antibody mediated inactivation of bacteriophages using delivery systems. J Virol Curr Res 1:555–574

    Google Scholar 

  76. Levin B, Bull JJ (1996) Phage therapy revisited: the population biology of a bacterial infection and its treatment with bacteriophage and antibiotics. AM Nat 147:881–898

    Article  Google Scholar 

  77. Bansal S, Soni SK, Harjai K, Chhibber S (2014) Aeromonas punctata derived depolymerase that disrupts the integrity of Klebsiella pneumoniae capsule: optimization of depolymerase production. J Basic Microbiol 54:711–720

    Article  CAS  PubMed  Google Scholar 

  78. Ramsugit S, Guma S, Pillay B, Jain P, Larsen MH, Danaviah S, Pillay M (2013) Pili contribute to biofilm formation in vitro in Mycobacterium tuberculosis. Antonie Van Leeuwenhoek 104:725–735

    Article  PubMed  Google Scholar 

  79. Alteri CJ, Xicohténcatl-Cortes J, Hess S, Caballero-Olín G, Girón JA, Friedman RL (2007) Mycobacterium tuberculosis produces pili during human infection. Proc Natl Acad Sci U S A 104:5145–5150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Hall-Stoodley L, Brun OS, Polshyna G, Barker LP (2006) Mycobacterium marinum biofilm formation reveals cording morphology. FEMS Microbiol Lett 257:43–49

    Article  CAS  PubMed  Google Scholar 

  81. Ojha AK, Baughn AD, Sambandan D, Hsu T, Trivelli X, Guerardel Y, Alahari A, Kremer L, Jacobs WR Jr, Hatfull GF (2008) Growth of mycobacterium tuberculosis biofilms containing free mycolic acids and harbouring drug-tolerant bacteria. Mol Microbiol 69:164–174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Broxmeyer L, Sosnowska D, Miltner E, Chacón O, Wagner D, McGarvey J, Barletta RG, Bermudez LE (2002) Killing of Mycobacterium avium and Mycobacterium tuberculosis by a mycobacteriophage delivered by a nonvirulent mycobacterium: a model for phage therapy of intracellular bacterial pathogens. J Infect Dis 186:1155–1160

    Article  PubMed  Google Scholar 

  83. Liu J, Dehbi M, Moeck G, Arhin F, Bauda P, Bergeron D, Callejo M, Ferretti V, Ha N, Kwan T, McCarty J, Srikumar R, Williams D, Wu JJ, Gros P, Pelletier J (2004) Antimicrobial drug discovery through bacteriophage genomics. Nat Biotechnol 22:185–191

    Article  CAS  PubMed  Google Scholar 

  84. Poranen MM, Ravantti JJ, Grahn AM, Gupta R, Auvinen P, Bamford DH (2006) Global changes in cellular gene expression during bacteriophage PRD1 infection. J Virol 80:8081–8088

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Ravantti JJ, Ruokoranta TM, Alapuranen AM, Bamford DH (2008) Global transcriptional responses of Pseudomonas aeruginosa to phage PRR1 infection. J Virol 82:2324–2329

    Article  CAS  PubMed  Google Scholar 

  86. Fallico V, Ross RP, Fitzgerald GF, McAuliffe O (2011) Genetic response to bacteriophage infection in Lactococcus lactisreveals a four-strand approach involving induction of membrane stress proteins, D-alanylation of the cell wall, maintenance of proton motive force, and energy conservation. J Virol 85:12032–12042

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Garber M, Grabherr MG, Guttman M, Trapnell C (2011) Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods 8:469–477

    Article  CAS  PubMed  Google Scholar 

  88. Pan Y, Yang X, Duan J, Lu N, Leung AS, Tran V, Hu Y, Wu N, Liu D, Wang Z, Yu X, Chen C, Zhang Y, Wan K, Liu J, Zhu B (2011) Whole-genome sequences of four Mycobacterium bovis BCG vaccine strains. J Bacteriol 193(12):3152e3

    Google Scholar 

  89. Zvi A, Ariel N, Fulkerson J, Sadoff JC, Shafferman A (2008) Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformatics analyses. BMC Med Genomics 1:18

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Barrangou R, Fremaux C, Deveau H, Richards M, Boyaval P, Moineau S, Romero DA, Horvath P (2007) CRISPR provides acquired resistance against viruses in prokaryotes. Science 315:1709–1712

    Article  CAS  PubMed  Google Scholar 

  91. Lefranc MP, Giudicelli V, Ginestoux C et al (1999) IMGT, the international ImMunoGeneTics database. Nucleic Acids Res. 27(1):209–212

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Singh H, Raghava GPS (2001) ProPred: prediction of HLA-DR binding sites. Bioinformatics 17:1236e7

    Article  Google Scholar 

  93. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Dönnes P, Elofsson A (2002) Prediction of MHC class I binding peptides, using SVMHC. BMC Bioinformatics 3:25

    Article  PubMed  PubMed Central  Google Scholar 

  95. Noguchi H, Kato R, Hanai T, Matsubara Y, Honda H, Brusic V, Kobayashi T (2002) Hidden Markov model-based prediction of antigenic peptides that interact with MHC class II molecules. J Biosci Bioeng 94(3):264–270

    Article  CAS  PubMed  Google Scholar 

  96. Lundegaard C, Lund O, Nielsen MJ (2011) Prediction of epitopes using neural network based methods. Immunol Methods 374(1-2):26–34

    Article  CAS  Google Scholar 

  97. Erlich H (2012) HLA DNA typing: past, present, and future. Tissue Antigens 80(1):1–11

    Article  CAS  PubMed  Google Scholar 

  98. Zhang L, Chen Y, Wong HS, Zhou S, Mamitsuka H, Zhu S (2012) TEPITOPEpan: extending TEPITOPE for peptide binding prediction covering over 700 HLA-DR molecules. PLoS One 7(2):e30483

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA (2012) An integrated map of genetic variation from 1,092 human genomes. 1000 Genomes Project Consortium. Nature 491(7422):56–65

    Article  PubMed  CAS  Google Scholar 

  100. Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50:213–219

    Article  CAS  PubMed  Google Scholar 

  101. Reche PA, Glutting JP, Reinherz EL (2002) Prediction of MHC class I binding peptides using profile motifs. Human Immunol 63:701–709

    Article  CAS  Google Scholar 

  102. Parker KC, Bednarek MA, Coligan JE (1994) Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. J Immunol 152:163–175

    CAS  PubMed  Google Scholar 

  103. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O (2008) NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Res 36(Web Server issue):509–512

    Article  CAS  Google Scholar 

  104. Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S et al (2007) NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence. PLoS ONE 2(8):e796

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  105. Bian H, Hammer J (2004) Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE. Methods 34:468–475

    Article  CAS  PubMed  Google Scholar 

  106. Jojic N, Reyes-Gomez M, Heckerman D, Kadie C, Schueler-Furman O (2006) Learning MHC I–peptide binding. Bioinformatics 22:227–235

    Article  Google Scholar 

  107. Toussaint NC, Feldhahn M, Ziehm M, Stevanovic S, Kohlbacher O (2011) T-cell epitope prediction based on self-tolerance. In: Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB ’11. New York: ACM Press, p. 584

    Google Scholar 

  108. Jacob L, Vert JP (2008) Efficient peptide-MHC-I binding prediction for alleles with few known binders. Bioinformatics 24:358–366

    Article  CAS  PubMed  Google Scholar 

  109. Singh H, Raghava GP (2001) ProPred: prediction of HLA-DR binding sites. Bioinformatics 17:1236–1237

    Article  CAS  PubMed  Google Scholar 

  110. Wan J, Liu W, Xu Q, Ren Y, Flower DR, Li T (2006) SVRMHC prediction server for MHC-binding peptides. BMC Bioinformatics 7:463

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, Wheeler DK, Gabbard JL, Hix D, Sette A, Peters B (2015) The immune epitope database (IEDB) 3.0. Nucleic Acids Res 43(Database issue):405–412

    Article  CAS  Google Scholar 

  112. Doytchinova IA, Guan P, Flower DR (2006) EpiJen: a server for multistep T cell epitope prediction. BMC Bioinformatics 7:131. https://doi.org/10.1186/1471-2105-7-131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Donnes P, Kohlbacher O (2005) Integrated modeling of the major events in the MHC class I antigen processing pathway. Protein Sci 4:2132–2140

    Article  CAS  Google Scholar 

  114. Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M (2007) Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics 8:424

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  115. Tung CW, Ho SY (2007) POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties. Bioinformatics 23:942–949

    Article  CAS  PubMed  Google Scholar 

  116. Sweredoski MJ, Baldi P (2008) (2008). COBEpro: a novel system for predicting continuous B-cell epitopes. Protein Eng Des Sel 22(3):113–120

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  117. EL-Manzalawy Y, Dobbs D, Honavar V (2008) Predicting linear B-cell epitopes using string kernels. J Mol Recognit 21:243–255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

Authors are grateful to the Indian Science and Technology Foundation, Delhi, and the Department of Biotechnology, Govt. of India, for giving the Bioinformatics Infrastructure Facility (BIF) at the Center for Biotechnology and Bioinformatics, Dibrugarh University in which the manuscript was completed. Authors are additionally grateful to DeLCON facility provided by DBT, Govt. of India.

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Authors and Affiliations

  1. Microbiology Division, Department of Botany, Gauhati University, Guwahati, Assam, India

    Arabinda Ghosh & Tridip Phukan

  2. Institute of Management Studies (IMSUC), Ghaziabad, Uttar Pradesh, India

    Surabhi Johari & Abha Vashista

  3. Biopredic International, Parc d’activité de la Bretèche Bâtiment A4, Saint Grégoire, France

    Ashwani Sharma

  4. Centre for Biotechnology and Bioinformatics, Dibrugarh University, Dibrugarh, Assam, India

    Subrata Sinha

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  1. Arabinda Ghosh
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  2. Tridip Phukan
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  3. Surabhi Johari
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  4. Ashwani Sharma
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  5. Abha Vashista
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  6. Subrata Sinha
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Editors and Affiliations

  1. Department of BioMedical Engineering, Medical College of Wisconsin, Milwaukee, WI, USA

    Namrata Tomar

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Ghosh, A., Phukan, T., Johari, S., Sharma, A., Vashista, A., Sinha, S. (2020). Dynamics of Mycobacteriophage—Mycobacterial Host Interaction. In: Tomar, N. (eds) Immunoinformatics. Methods in Molecular Biology, vol 2131. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0389-5_19

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  • DOI: https://doi.org/10.1007/978-1-0716-0389-5_19

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0388-8

  • Online ISBN: 978-1-0716-0389-5

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