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Noncoding RNA in Mycobacteria

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  • Authors: Kristine B. Arnvig1, Teresa Cortes2, Douglas B. Young3
  • Editors: Graham F. Hatfull4, William R. Jacobs Jr.5
  • VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: National Institute for Medical Research, Mycobacterial Research Division, London, NW7 1AA, United Kingdom; 2: National Institute for Medical Research, Mycobacterial Research Division, London, NW7 1AA, United Kingdom; 3: National Institute for Medical Research, Mycobacterial Research Division, London, NW7 1AA, United Kingdom; 4: University of Pittsburgh, Pittsburgh, PA; 5: Howard Hughes Medical Institute, Albert Einstein College of Medicine, Bronx, NY
    • Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0029-2013
  • Received 17 August 2013 Accepted 25 September 2013 Published 14 March 2014
  • KB Arnvig, [email protected]
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  • Abstract:

    Efforts to understand the molecular basis of mycobacterial gene regulation are dominated by a protein-centric view. However, there is a growing appreciation that noncoding RNA, i.e., RNA that is not translated, plays a role in a wide variety of molecular mechanisms. Noncoding RNA comprises rRNA, tRNA, 4.5S RNA, RnpB, and transfer-messenger RNA, as well as a vast population of regulatory RNA, often dubbed “the dark matter of gene regulation.” The regulatory RNA species comprise 5′ and 3′ untranslated regions and a rapidly expanding category of transcripts with the ability to base-pair with mRNAs or to interact with proteins. Regulatory RNA plays a central role in the bacterium's response to changes in the environment, and in this article we review emerging information on the presence and abundance of different types of noncoding RNA in mycobacteria.

  • Citation: Arnvig K, Cortes T, Young D. 2014. Noncoding RNA in Mycobacteria. Microbiol Spectrum 2(2):MGM2-0029-2013. doi:10.1128/microbiolspec.MGM2-0029-2013.

References

1. Gripenland J, Netterling S, Loh E, Tiensuu T, Toledo-Arana A, Johansson J. 2010. RNAs: regulators of bacterial virulence. Nat Rev Microbiol 8:857–866. [PubMed][CrossRef]
2. Sorek R, Cossart P. 2010. Prokaryotic transcriptomics: a new view on regulation, physiology and pathogenicity. Nat Rev Genet 11:9–16. [PubMed][CrossRef]
3. Yus E, Guell M, Vivancos AP, Chen WH, Lluch-Senar M, Delgado J, Gavin AC, Bork P, Serrano L. 2012. Transcription start site associated RNAs in bacteria. Mol Syst Biol 8:585. [PubMed][CrossRef]
4. Kang SM, Choi JW, Lee Y, Hong SH, Lee HJ. 2013. Identification of microRNA-size, small RNAs in Escherichia coli. Curr Microbiol 67:609–613. [PubMed][CrossRef]
5. Vanderpool CK, Balasubramanian D, Lloyd CR. 2011. Dual-function RNA regulators in bacteria. Biochimie 93:1943–1949. [PubMed][CrossRef]
6. Waters LS, Storz G. 2009. Regulatory RNAs in bacteria. Cell 136:615–628. [PubMed][CrossRef]
7. Arnvig KB, Comas I, Thomson NR, Houghton J, Boshoff HI, Croucher NJ, Rose G, Perkins TT, Parkhill J, Dougan G, Young DB. 2011. Sequence-based analysis uncovers an abundance of non-coding RNA in the total transcriptome of Mycobacterium tuberculosis. PLoS Pathog 7:e1002342. [PubMed][CrossRef]
8. Arnvig KB, Young DB. 2009. Identification of small RNAs in Mycobacterium tuberculosis. Mol Microbiol 73:397–408. [PubMed][CrossRef]
9. DiChiara JM, Contreras-Martinez LM, Livny J, Smith D, McDonough KA, Belfort M. 2010. Multiple small RNAs identified in Mycobacterium bovis BCG are also expressed in Mycobacterium tuberculosis and Mycobacterium smegmatis. Nucleic Acids Res 38:4067–4078. [PubMed][CrossRef]
10. Li SK, Ng PK, Qin H, Lau JK, Lau JP, Tsui SK, Chan TF, Lau TC. 2013. Identification of small RNAs in Mycobacterium smegmatis using heterologous Hfq. RNA 19:74–84. [PubMed][CrossRef]
11. McGuire AM, Weiner B, Park ST, Wapinski I, Raman S, Dolganov G, Peterson M, Riley R, Zucker J, Abeel T, White J, Sisk P, Stolte C, Koehrsen M, Yamamoto RT, Iacobelli-Martinez M, Kidd MJ, Maer AM, Schoolnik GK, Regev A, Galagan J. 2012. Comparative analysis of Mycobacterium and related Actinomycetes yields insight into the evolution of Mycobacterium tuberculosis pathogenesis. BMC Genomics 13:120. [PubMed][CrossRef]
12. Miotto P, Forti F, Ambrosi A, Pellin D, Veiga DF, Balazsi G, Gennaro ML, Di Serio C, Ghisotti D, Cirillo DM. 2012. Genome-wide discovery of small RNAs in Mycobacterium tuberculosis. PloS One 7:e51950. [PubMed][CrossRef]
13. Pellin D, Miotto P, Ambrosi A, Cirillo DM, Di Serio C. 2012. A genome-wide identification analysis of small regulatory RNAs in Mycobacterium tuberculosis by RNA-Seq and conservation analysis. PloS One 7:e32723. [PubMed][CrossRef]
14. Pelly S, Bishai WR, Lamichhane G. 2012. A screen for non-coding RNA in Mycobacterium tuberculosis reveals a cAMP-responsive RNA that is expressed during infection. Gene 500:85–92. [PubMed][CrossRef]
15. Lamichhane G, Arnvig KB, McDonough KA. 2013. Definition and annotation of (myco)bacterial non-coding RNA. Tuberculosis (Edinb) 93:26–29. [PubMed][CrossRef]
16. Cortes T, Schubert OT, Rose G, Arnvig KB, Comas I, Aebersold R, Young DB. 2013. Genome-wide mapping of transcriptional start sites defines an extensive leaderless transcriptome in Mycobacterium tuberculosis. Cell Rep 5:1121–1131. [PubMed][CrossRef]
17. Carver T, Harris SR, Berriman M, Parkhill J, McQuillan JA. 2012. Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data. Bioinformatics 28:464–469. [PubMed][CrossRef]
18. Chaudhuri RR, Loman NJ, Snyder LA, Bailey CM, Stekel DJ, Pallen MJ. 2008. xBASE2: a comprehensive resource for comparative bacterial genomics. Nucleic Acids Res 36:D543–546. [PubMed][CrossRef]
19. Reddy TB, Riley R, Wymore F, Montgomery P, DeCaprio D, Engels R, Gellesch M, Hubble J, Jen D, Jin H, Koehrsen M, Larson L, Mao M, Nitzberg M, Sisk P, Stolte C, Weiner B, White J, Zachariah ZK, Sherlock G, Galagan JE, Ball CA, Schoolnik GK. 2009. TB database: an integrated platform for tuberculosis research. Nucleic Acids Res 37:D499–D508. [PubMed][CrossRef]
20. Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, Harris D, Gordon SV, Eiglmeier K, Gas S, Barry CE, 3rd, Tekaia F, Badcock K, Basham D, Brown D, Chillingworth T, Connor R, Davies R, Devlin K, Feltwell T, Gentles S, Hamlin N, Holroyd S, Hornsby T, Jagels K, Krogh A, McLean J, Moule S, Murphy L, Oliver K, Osborne J, Quail MA, Rajandream MA, Rogers J, Rutter S, Seeger K, Skelton J, Squares R, Squares S, Sulston JE, Taylor K, Whitehead S, Barrell BG. 1998. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393:537–544. [PubMed][CrossRef]
21. Abramovitch RB, Rohde KH, Hsu FF, Russell DG. 2011. aprABC: a Mycobacterium tuberculosis complex-specific locus that modulates pH-driven adaptation to the macrophage phagosome. Mol Microbiol 80:678–694. [PubMed][CrossRef]
22. Dejesus MA, Sacchettini JC, Ioerger TR. 2013. Reannotation of translational start sites in the genome of Mycobacterium tuberculosis. Tuberculosis (Edinb) 93:18–25. [PubMed][CrossRef]
23. Bell C, Smith GT, Sweredoski MJ, Hess S. 2012. Characterization of the Mycobacterium tuberculosis proteome by liquid chromatography mass spectrometry-based proteomics techniques: a comprehensive resource for tuberculosis research. J Proteome Res 11:119–130. [PubMed][CrossRef]
24. Kruh NA, Troudt J, Izzo A, Prenni J, Dobos KM. 2010. Portrait of a pathogen: the Mycobacterium tuberculosis proteome in vivo. PloS One 5:e13938. [PubMed][CrossRef]
25. Schubert OT, Mouritsen J, Ludwig C, Rost HL, Rosenberger G, Arthur PK, Claassen M, Campbell DS, Sun Z, Farrah T, Gengenbacher M, Maiolica A, Kaufmann SH, Moritz RL, Aebersold R. 2013. The Mtb Proteome Library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis. Cell Host Microbe 13:602–612. [PubMed][CrossRef]
26. Unniraman S, Prakash R, Nagaraja V. 2001. Alternate paradigm for intrinsic transcription termination in eubacteria. J Biol Chem 276:41850–41855. [PubMed][CrossRef]
27. Mohanty BK, Kushner SR. 2011. Bacterial/archaeal/organellar polyadenylation. Wiley Interdiscip Rev RNA 2:256–276. [PubMed][CrossRef]
28. Adilakshmi T, Ayling PD, Ratledge C. 2000. Polyadenylylation in mycobacteria: evidence for oligo(dT)-primed cDNA synthesis. Microbiology 146(Pt 3) :633–638. [PubMed]
29. Gardner PP, Barquist L, Bateman A, Nawrocki EP, Weinberg Z. 2011. RNIE: genome-wide prediction of bacterial intrinsic terminators. Nucleic Acids Res 39:5845–5852. [PubMed][CrossRef]
30. Gorna MW, Carpousis AJ, Luisi BF. 2012. From conformational chaos to robust regulation: the structure and function of the multi-enzyme RNA degradosome. Q Rev Biophys 45:105–145. [PubMed][CrossRef]
31. Argaman L, Hershberg R, Vogel J, Bejerano G, Wagner EG, Margalit H, Altuvia S. 2001. Novel small RNA-encoding genes in the intergenic regions of Escherichia coli. Curr Biol 11:941–950. [PubMed]
32. Sharma CM, Hoffmann S, Darfeuille F, Reignier J, Findeiss S, Sittka A, Chabas S, Reiche K, Hackermuller J, Reinhardt R, Stadler PF, Vogel J. 2010. The primary transcriptome of the major human pathogen Helicobacter pylori. Nature 464:250–255. [PubMed][CrossRef]
33. Narberhaus F, Waldminghaus T, Chowdhury S. 2006. RNA thermometers. FEMS Microbiol Rev 30:3–16. [PubMed][CrossRef]
34. Nechooshtan G, Elgrably-Weiss M, Sheaffer A, Westhof E, Altuvia S. 2009. A pH-responsive riboregulator. Genes Dev 23:2650–2662. [PubMed][CrossRef]
35. Nahvi A, Sudarsan N, Ebert MS, Zou X, Brown KL, Breaker RR. 2002. Genetic control by a metabolite binding mRNA. Chem Biol 9:1043. [PubMed]
36. Breaker RR. 2012. Riboswitches and the RNA world. Cold Spring Harbor Perspect Biol 4.
37. Lindahl L, Zengel JM. 1986. Ribosomal genes in Escherichia coli. Annu Rev Genet 20:297–326. [PubMed][CrossRef]
38. Arnvig KB, Pennell S, Gopal B, Colston MJ. 2004. A high-affinity interaction between NusA and the rrn nut site in Mycobacterium tuberculosis. Proc Natl Acad Sci USA 101:8325–8330. [PubMed][CrossRef]
39. Arnvig KB, Zeng S, Quan S, Papageorge A, Zhang N, Villapakkam AC, Squires CL. 2008. Evolutionary comparison of ribosomal operon antitermination function. J Bacteriol 190:7251–7257. [PubMed][CrossRef]
40. Condon C, Squires C, Squires CL. 1995. Control of rRNA transcription in Escherichia coli. Microbiol Rev 59:623–645. [PubMed]
41. Quan S, Zhang N, French S, Squires CL. 2005. Transcriptional polarity in rRNA operons of Escherichia colinus A and nusB mutant strains. J Bacteriol 187:1632–1638. [PubMed][CrossRef]
42. Vogel U, Jensen KF. 1995. Effects of the antiterminator BoxA on transcription elongation kinetics and ppGpp inhibition of transcription elongation in Escherichia coli. J Biol Chem 270:18335–18340. [PubMed]
43. Beuth B, Pennell S, Arnvig KB, Martin SR, Taylor IA. 2005. Structure of a Mycobacterium tuberculosis NusA-RNA complex. EMBO J 24:3576–3587. [PubMed][CrossRef]
44. Bubunenko M, Court DL, Al Refaii A, Saxena S, Korepanov A, Friedman DI, Gottesman ME, Alix JH. 2013. Nus transcription elongation factors and RNase III modulate small ribosome subunit biogenesis in Escherichia coli. Mol Microbiol 87:382–393. [PubMed][CrossRef]
45. Tucker BJ, Breaker RR. 2005. Riboswitches as versatile gene control elements. Curr Opinion Struct Biol 15:342–348. [PubMed][CrossRef]
46. Gardner PP, Daub J, Tate J, Moore BL, Osuch IH, Griffiths-Jones S, Finn RD, Nawrocki EP, Kolbe DL, Eddy SR, Bateman A. 2011. Rfam: Wikipedia, clans and the “decimal” release. Nucleic Acids Res 39:D141–D145. [PubMed][CrossRef]
47. Weinberg Z, Barrick JE, Yao Z, Roth A, Kim JN, Gore J, Wang JX, Lee ER, Block KF, Sudarsan N, Neph S, Tompa M, Ruzzo WL, Breaker RR. 2007. Identification of 22 candidate structured RNAs in bacteria using the CMfinder comparative genomics pipeline. Nucleic Acids Res 35:4809–4819. [PubMed][CrossRef]
48. Weinberg Z, Regulski EE, Hammond MC, Barrick JE, Yao Z, Ruzzo WL, Breaker RR. 2008. The aptamer core of SAM-IV riboswitches mimics the ligand-binding site of SAM-I riboswitches. RNA 14:822–828. [PubMed][CrossRef]
49. Loh E, Dussurget O, Gripenland J, Vaitkevicius K, Tiensuu T, Mandin P, Repoila F, Buchrieser C, Cossart P, Johansson J. 2009. A trans-acting riboswitch controls expression of the virulence regulator PrfA in Listeria monocytogenes. Cell 139:770–779. [PubMed][CrossRef]
50. Rodionov DA, Vitreschak AG, Mironov AA, Gelfand MS. 2003. Comparative genomics of the vitamin B12 metabolism and regulation in prokaryotes. J Biol Chem 278:41148–41159. [PubMed][CrossRef]
51. Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS. 2003. Regulation of the vitamin B12 metabolism and transport in bacteria by a conserved RNA structural element. RNA 9:1084–1097. [PubMed]
52. Warner DF, Savvi S, Mizrahi V, Dawes SS. 2007. A riboswitch regulates expression of the coenzyme B12-independent methionine synthase in Mycobacterium tuberculosis: implications for differential methionine synthase function in strains H37Rv and CDC1551. J Bacteriol 189:3655–3659. [PubMed][CrossRef]
53. Akhter Y, Ehebauer MT, Mukhopadhyay S, Hasnain SE. 2012. The PE/PPE multigene family codes for virulence factors and is a possible source of mycobacterial antigenic variation: perhaps more? Biochimie 94:110–116. [PubMed][CrossRef]
54. Gopinath K, Venclovas C, Ioerger TR, Sacchettini JC, McKinney JD, Mizrahi V, Warner DF. 2013. A vitamin B12 transporter in Mycobacterium tuberculosis. Open Biol 3:120175. [PubMed][CrossRef]
55. Dann CE, 3rd, Wakeman CA, Sieling CL, Baker SC, Irnov I, Winkler WC. 2007. Structure and mechanism of a metal-sensing regulatory RNA. Cell 130:878–892. [PubMed][CrossRef]
56. Barrick JE, Corbino KA, Winkler WC, Nahvi A, Mandal M, Collins J, Lee M, Roth A, Sudarsan N, Jona I, Wickiser JK, Breaker RR. 2004. New RNA motifs suggest an expanded scope for riboswitches in bacterial genetic control. Proc Natl Acad Sci USA 101:6421–6426. [PubMed][CrossRef]
57. Walters SB, Dubnau E, Kolesnikova I, Laval F, Daffe M, Smith I. 2006. The Mycobacterium tuberculosis PhoPR two-component system regulates genes essential for virulence and complex lipid biosynthesis. Mol Microbiol 60:312–330. [PubMed][CrossRef]
58. Vitreschak AG, Mironov AA, Lyubetsky VA, Gelfand MS. 2008. Comparative genomic analysis of T-box regulatory systems in bacteria. RNA 14:717–735. [PubMed][CrossRef]
59. Biketov S, Potapov V, Ganina E, Downing K, Kana BD, Kaprelyants A. 2007. The role of resuscitation promoting factors in pathogenesis and reactivation of Mycobacterium tuberculosis during intra-peritoneal infection in mice. BMC Infect Dis 7:146. [PubMed][CrossRef]
60. Keep NH, Ward JM, Cohen-Gonsaud M, Henderson B. 2006. Wake up! Peptidoglycan lysis and bacterial non-growth states. Trends Microbiol 14:271–276. [PubMed][CrossRef]
61. Telkov MV, Demina GR, Voloshin SA, Salina EG, Dudik TV, Stekhanova TN, Mukamolova GV, Kazaryan KA, Goncharenko AV, Young M, Kaprelyants AS. 2006. Proteins of the Rpf (resuscitation promoting factor) family are peptidoglycan hydrolases. Biochemistry (Mosc) 71:414–422. [PubMed]
62. Block KF, Hammond MC, Breaker RR. 2010. Evidence for widespread gene control function by the ydaO riboswitch candidate. J Bacteriol 192:3983–3989. [PubMed][CrossRef]
63. Nelson JW, Sudarsan N, Furukawa K, Weinberg Z, Wang JX, Breaker RR. 2013. Riboswitches in eubacteria sense the second messenger c-di-AMP. Nature Chemical Biol 9:834–839. [PubMed][CrossRef]
64. Breaker RR. 2011. Prospects for riboswitch discovery and analysis. Mol Cell 43:867–879. [PubMed][CrossRef]
65. Storz G, Vogel J, Wassarman KM. 2011. Regulation by small RNAs in bacteria: expanding frontiers. Mol Cell 43:880–891. [PubMed][CrossRef]
66. Babitzke P, Romeo T. 2007. CsrB sRNA family: sequestration of RNA-binding regulatory proteins. Curr Opin Microbiol 10:156–163. [PubMed]
67. Wassarman KM. 2007. 6S RNA: a regulator of transcription. Mol Microbiol 65:1425–1431. [PubMed]
68. Wassarman KM. 2007. 6S RNA: a small RNA regulator of transcription. Curr Opin Microbiol 10:164–168. [PubMed][CrossRef]
69. Thomason MK, Storz G. 2010. Bacterial antisense RNAs: how many are there, and what are they doing? Annu Rev Genet 44:167–188. [PubMed][CrossRef]
70. Sesto N, Wurtzel O, Archambaud C, Sorek R, Cossart P. 2013. The excludon: a new concept in bacterial antisense RNA-mediated gene regulation. Nat Rev Microbiol 11:75–82. [PubMed][CrossRef]
71. Brantl S, Wagner EG. 2000. Antisense RNA-mediated transcriptional attenuation: an in vitro study of plasmid pT181. Mol Microbiol 35:1469–1482. [PubMed]
72. Stork M, Di Lorenzo M, Welch TJ, Crosa JH. 2007. Transcription termination within the iron transport-biosynthesis operon of Vibrio anguillarum requires an antisense RNA. J Bacteriol 189:3479–3488. [PubMed][CrossRef]
73. Opdyke JA, Fozo EM, Hemm MR, Storz G. 2011. RNase III participates in GadY-dependent cleavage of the gadX-gadW mRNA. J Mol Biol 406:29–43. [PubMed][CrossRef]
74. Opdyke JA, Kang JG, Storz G. 2004. GadY, a small-RNA regulator of acid response genes in Escherichia coli. J Bacteriol 186:6698–6705. [PubMed][CrossRef]
75. Stazic D, Lindell D, Steglich C. 2011. Antisense RNA protects mRNA from RNase E degradation by RNA-RNA duplex formation during phage infection. Nucleic Acids Res 39:4890–4899. [PubMed][CrossRef]
76. Lasa I, Toledo-Arana A, Dobin A, Villanueva M, de Los Mozos IR, Vergara-Irigaray M, Segura V, Fagegaltier D, Penades JR, Valle J, Solano C, Gingeras TR. 2011. Genome-wide antisense transcription drives mRNA processing in bacteria. Proc Natl Acad Sci USA 108:20172–20177. [PubMed][CrossRef]
77. Rose G, Cortes T, Comas I, Coscolla M, Gagneux S, Young DB. 2013. Mapping of genotype-phenotype diversity amongst clinical isolates of Mycobacterium tuberculosis by sequence-based transcriptional profiling. Genome Biol Evol 5:1849–1862.
78. Movahedzadeh F, Smith DA, Norman RA, Dinadayala P, Murray-Rust J, Russell DG, Kendall SL, Rison SC, McAlister MS, Bancroft GJ, McDonald NQ, Daffe M, Av-Gay Y, Stoker NG. 2004. The Mycobacterium tuberculosis ino1 gene is essential for growth and virulence. Mol Microbiol 51:1003–1014. [PubMed]
79. Jager D, Pernitzsch SR, Richter AS, Backofen R, Sharma CM, Schmitz RA. 2012. An archaeal sRNA targeting cis- and trans-encoded mRNAs via two distinct domains. Nucleic Acids Res 40:10964–10979. [PubMed][CrossRef]
80. Hotter GS, Collins DM. 2011. Mycobacterium bovis lipids: virulence and vaccines. Vet Microbiol 151:91–98. [PubMed][CrossRef]
81. Sassetti CM, Boyd DH, Rubin EJ. 2003. Genes required for mycobacterial growth defined by high density mutagenesis. Mol Microbiol 48:77–84. [PubMed]
82. Sassetti CM, Rubin EJ. 2003. Genetic requirements for mycobacterial survival during infection. Proc Natl Acad Sci USA 100:12989–12994. [PubMed][CrossRef]
83. Schnappinger D, Ehrt S, Voskuil MI, Liu Y, Mangan JA, Monahan IM, Dolganov G, Efron B, Butcher PD, Nathan C, Schoolnik GK. 2003. Transcriptional adaptation of Mycobacterium tuberculosis within macrophages: insights into the phagosomal environment. J Exp Med 198:693–704. [PubMed][CrossRef]
84. Matsunaga I, Bhatt A, Young DC, Cheng TY, Eyles SJ, Besra GS, Briken V, Porcelli SA, Costello CE, Jacobs WR, Jr, Moody DB. 2004. Mycobacterium tuberculosis pks12 produces a novel polyketide presented by CD1c to T cells. J Exp Med 200:1559–1569. [PubMed][CrossRef]
85. Eggenhofer F, Tafer H, Stadler PF, Hofacker IL. 2011. RNApredator: fast accessibility-based prediction of sRNA targets. Nucleic Acids Res 39:W149–W154. [PubMed][CrossRef]
86. Tjaden B. 2008. TargetRNA: a tool for predicting targets of small RNA action in bacteria. Nucleic Acids Res 36:W109–W113. [PubMed][CrossRef]
87. Arnvig K, Young D. 2012. Non-coding RNA and its potential role in Mycobacterium tuberculosis pathogenesis. RNA Biol 9:427–436. [PubMed][CrossRef]
88. Bardill JP, Hammer BK. 2012. Non-coding sRNAs regulate virulence in the bacterial pathogen Vibrio cholerae. RNA Biol 9:392–401. [PubMed]
89. Papenfort K, Vogel J. 2010. Regulatory RNA in bacterial pathogens. Cell Host Microbe 8:116–127. [PubMed][CrossRef]
90. Bossi L, Schwartz A, Guillemardet B, Boudvillain M, Figueroa-Bossi N. 2012. A role for Rho-dependent polarity in gene regulation by a noncoding small RNA. Genes Dev 26:1864–1873. [PubMed][CrossRef]
91. Beisel CL, Storz G. 2010. Base pairing small RNAs and their roles in global regulatory networks. FEMS Microbiol Rev 34:866–882. [PubMed][CrossRef]
92. Gottesman S, Storz G. 2011. Bacterial small RNA regulators: versatile roles and rapidly evolving variations. Cold Spring Harbor Perspect Biol 3. [PubMed][CrossRef]
93. Battesti A, Majdalani N, Gottesman S. 2011. The RpoS-mediated general stress response in Escherichia coli. Annu Rev Microbiol 65:189–213. [PubMed][CrossRef]
94. Geisinger E, Adhikari RP, Jin R, Ross HF, Novick RP. 2006. Inhibition of rot translation by RNAIII, a key feature of agr function. Mol Microbiol 61:1038–1048. [PubMed][CrossRef]
95. Svenningsen SL, Tu KC, Bassler BL. 2009. Gene dosage compensation calibrates four regulatory RNAs to control Vibrio cholerae quorum sensing. EMBO J 28:429–439. [PubMed][CrossRef]
96. Panek J, Krasny L, Bobek J, Jezkova E, Korelusova J, Vohradsky J. 2011. The suboptimal structures find the optimal RNAs: homology search for bacterial non-coding RNAs using suboptimal RNA structures. Nucleic Acids Res 39:3418–3426. [PubMed][CrossRef]
97. Chao Y, Vogel J. 2010. The role of Hfq in bacterial pathogens. Curr Opin Microbiol 13:24–33. [PubMed][CrossRef]
98. Bohn C, Rigoulay C, Bouloc P. 2007. No detectable effect of RNA-binding protein Hfq absence in Staphylococcus aureus. BMC Microbiol 7:10. [PubMed][CrossRef]
99. Liu Y, Wu N, Dong J, Gao Y, Zhang X, Mu C, Shao N, Yang G. 2010. Hfq is a global regulator that controls the pathogenicity of Staphylococcus aureus. PloS One 5. [PubMed][CrossRef]
100. Otaka H, Ishikawa H, Morita T, Aiba H. 2011. PolyU tail of rho-independent terminator of bacterial small RNAs is essential for Hfq action. Proc Natl Acad Sci USA 108:13059–13064. [PubMed][CrossRef]
101. Vogel J, Luisi BF. 2011. Hfq and its constellation of RNA. Nat Rev Microbiol 9:578–589. [PubMed][CrossRef]
102. Gaballa A, Antelmann H, Aguilar C, Khakh SK, Song KB, Smaldone GT, Helmann JD. 2008. The Bacillus subtilis iron-sparing response is mediated by a Fur-regulated small RNA and three small, basic proteins. Proc Natl Acad Sci USA 105:11927–11932. [PubMed][CrossRef]
103. Bandyra KJ, Said N, Pfeiffer V, Gorna MW, Vogel J, Luisi BF. 2012. The seed region of a small RNA drives the controlled destruction of the target mRNA by the endoribonuclease RNase E. Mol Cell 47:943–953. [PubMed][CrossRef]
104. Said N, Rieder R, Hurwitz R, Deckert J, Urlaub H, Vogel J. 2009. In vivo expression and purification of aptamer-tagged small RNA regulators. Nucleic Acids Res 37:e133. [PubMed][CrossRef]
105. Hartkoorn RC, Sala C, Uplekar S, Busso P, Rougemont J, Cole ST. 2012. Genome-wide definition of the SigF regulon in Mycobacterium tuberculosis. J Bacteriol 194:2001–2009. [PubMed][CrossRef]
106. England K, Crew R, Slayden RA. 2011. Mycobacterium tuberculosis septum site determining protein, Ssd encoded by rv3660c, promotes filamentation and elicits an alternative metabolic and dormancy stress response. BMC Microbiol 11:79. [PubMed][CrossRef]
107. Geissmann T, Chevalier C, Cros MJ, Boisset S, Fechter P, Noirot C, Schrenzel J, Francois P, Vandenesch F, Gaspin C, Romby P. 2009. A search for small noncoding RNAs in Staphylococcus aureus reveals a conserved sequence motif for regulation. Nucleic Acids Res 37:7239–7257. [PubMed]
108. Sherman DR, Voskuil M, Schnappinger D, Liao R, Harrell MI, Schoolnik GK. 2001. Regulation of the Mycobacterium tuberculosis hypoxic response gene encoding alpha -crystallin. Proc Natl Acad Sci USA 98:7534–7539. [PubMed][CrossRef]
109. Garton NJ, Waddell SJ, Sherratt AL, Lee SM, Smith RJ, Senner C, Hinds J, Rajakumar K, Adegbola RA, Besra GS, Butcher PD, Barer MR. 2008. Cytological and transcript analyses reveal fat and lazy persister-like bacilli in tuberculous sputum. PLoS Med 5:e75. [PubMed][CrossRef]
110. Voskuil MI, Schnappinger D, Visconti KC, Harrell MI, Dolganov GM, Sherman DR, Schoolnik GK. 2003. Inhibition of respiration by nitric oxide induces a Mycobacterium tuberculosis dormancy program. J Exp Med 198:705–713. [PubMed][CrossRef]
111. Beste DJ, Peters J, Hooper T, Avignone-Rossa C, Bushell ME, McFadden J. 2005. Compiling a molecular inventory for Mycobacterium bovis BCG at two growth rates: evidence for growth rate-mediated regulation of ribosome biosynthesis and lipid metabolism. J Bacteriol 187:1677–1684. [PubMed][CrossRef]
112. Pieters J. 2008. Mycobacterium tuberculosis and the macrophage: maintaining a balance. Cell Host Microbe 3:399–407. [PubMed][CrossRef]
113. Tan S, Sukumar N, Abramovitch RB, Parish T, Russell DG. 2013. Mycobacterium tuberculosis responds to chloride and pH as synergistic cues to the immune status of its host cell. PLoS Pathog 9:e1003282. [PubMed][CrossRef]
114. Betts JC, Lukey PT, Robb LC, McAdam RA, Duncan K. 2002. Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling. Mol Microbiol 43:717–731. [PubMed]
115. Keren I, Minami S, Rubin E, Lewis K. 2011. Characterization and transcriptome analysis of Mycobacterium tuberculosis persisters. mBio 2:e00100–e00111. [PubMed][CrossRef]
116. Barrick JE, Sudarsan N, Weinberg Z, Ruzzo WL, Breaker RR. 2005. 6S RNA is a widespread regulator of eubacterial RNA polymerase that resembles an open promoter. RNA 11:774–784. [PubMed][CrossRef]
117. Rustad TR, Minch KJ, Brabant W, Winkler JK, Reiss DJ, Baliga NS, Sherman DR. 2013. Global analysis of mRNA stability in Mycobacterium tuberculosis. Nucleic Acids Res 41:509–517. [PubMed][CrossRef]
118. Marcaida MJ, DePristo MA, Chandran V, Carpousis AJ, Luisi BF. 2006. The RNA degradosome: life in the fast lane of adaptive molecular evolution. Trends Biochem Sci 31:359–365. [PubMed][CrossRef]
119. Lehnik-Habrink M, Lewis RJ, Mader U, Stulke J. 2012. RNA degradation in Bacillus subtilis: an interplay of essential endo- and exoribonucleases. Mol Microbiol 84:1005–1017. [PubMed][CrossRef]
120. Deveau H, Garneau JE, Moineau S. 2010. CRISPR/Cas system and its role in phage-bacteria interactions. Annu Rev Microbiol 64:475–493. [PubMed]
121. Supply P, Marceau M, Mangenot S, Roche D, Rouanet C, Khanna V, Majlessi L, Criscuolo A, Tap J, Pawlik A, Fiette L, Orgeur M, Fabre M, Parmentier C, Frigui W, Simeone R, Boritsch EC, Debrie AS, Willery E, Walker D, Quail MA, Ma L, Bouchier C, Salvignol G, Sayes F, Cascioferro A, Seemann T, Barbe V, Locht C, Gutierrez MC, Leclerc C, Bentley SD, Stinear TP, Brisse S, Medigue C, Parkhill J, Cruveiller S, Brosch R. 2013. Genomic analysis of smooth tubercle bacilli provides insights into ancestry and pathoadaptation of Mycobacterium tuberculosis. Nat Genet 45:172–179. [PubMed][CrossRef]
122. Driscoll JR. 2009. Spoligotyping for molecular epidemiology of the Mycobacterium tuberculosis complex. Methods Mol Biol 551:117–128. [PubMed]
123. Makarova KS, Haft DH, Barrangou R, Brouns SJ, Charpentier E, Horvath P, Moineau S, Mojica FJ, Wolf YI, Yakunin AF, van der Oost J, Koonin EV. 2011. Evolution and classification of the CRISPR-Cas systems. Nat Rev Microbiol 9:467–477. [PubMed][CrossRef]
124. Marraffini LA, Sontheimer EJ. 2008. CRISPR interference limits horizontal gene transfer in staphylococci by targeting DNA. Science 322:1843–1845. [PubMed][CrossRef]
125. Hanekom M, Gey van Pittius NC, McEvoy C, Victor TC, Van Helden PD, Warren RM. 2011. Mycobacterium tuberculosis Beijing genotype: a template for success. Tuberculosis (Edinb) 91:510–523. [PubMed][CrossRef]
126. Tsolaki AG, Hirsh AE, DeRiemer K, Enciso JA, Wong MZ, Hannan M, Goguet de la Salmoniere YO, Aman K, Kato-Maeda M, Small PM. 2004. Functional and evolutionary genomics of Mycobacterium tuberculosis: insights from genomic deletions in 100 strains. Proc Natl Acad Sci USA 101:4865–4870. [PubMed][CrossRef]
127. Fenner L, Malla B, Ninet B, Dubuis O, Stucki D, Borrell S, Huna T, Bodmer T, Egger M, Gagneux S. 2011. “Pseudo-Beijing”: evidence for convergent evolution in the direct repeat region of Mycobacterium tuberculosis. PloS One 6:e24737. [PubMed][CrossRef]
128. Wassarman KM, Zhang A, Storz G. 1999. Small RNAs in Escherichia coli. Trends Microbiol 7:37-45.
129. Vogel J. 2009. A rough guide to the non-coding RNA world of Salmonella. Mol Microbiol 71:1–11. [PubMed][CrossRef]
130. Macke TJ, Ecker DJ, Gutell RR, Gautheret D, Case DA, Sampath R. 2001. RNAMotif, an RNA secondary structure definition and search algorithm. Nucleic Acids Res 29:4724–4735. [PubMed]
131. Chen Y, Indurthi DC, Jones SW, Papoutsakis ET. 2011. Small RNAs in the genus Clostridium. mBio 2:e00340–e00310. [PubMed][CrossRef]
132. Liang H, Zhao YT, Zhang JQ, Wang XJ, Fang RX, Jia YT. 2011. Identification and functional characterization of small non-coding RNAs in Xanthomonas oryzae pathovar oryzae. BMC Genomics 12:87. [PubMed][CrossRef]
133. Panek J, Bobek J, Mikulik K, Basler M, Vohradsky J. 2008. Biocomputational prediction of small non-coding RNAs in Streptomyces. BMC Genomics 9:217. [PubMed][CrossRef]
134. Schluter JP, Reinkensmeier J, Daschkey S, Evguenieva-Hackenberg E, Janssen S, Janicke S, Becker JD, Giegerich R, Becker A. 2010. A genome-wide survey of sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti. BMC Genomics 11:245. [PubMed][CrossRef]
135. Voss B, Georg J, Schon V, Ude S, Hess WR. 2009. Biocomputational prediction of non-coding RNAs in model cyanobacteria. BMC Genomics 10:123. [PubMed][CrossRef]
136. Rivas E, Klein RJ, Jones TA, Eddy SR. 2001. Computational identification of noncoding RNAs in E. coli by comparative genomics. Curr Biol 11:1369–1373. [PubMed]
137. Gautheret D, Lambert A. 2001. Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles. J Mol Biol 313:1003–1011. [PubMed][CrossRef]
138. Pichon C, Felden B. 2003. Intergenic sequence inspector: searching and identifying bacterial RNAs. Bioinformatics 19:1707–1709. [PubMed]
139. Nawrocki EP, Kolbe DL, Eddy SR. 2009. Infernal 1.0: inference of RNA alignments. Bioinformatics 25:1335–1337. [PubMed]
140. Coventry A, Kleitman DJ, Berger B. 2004. MSARI: multiple sequence alignments for statistical detection of RNA secondary structure. Proc Natl Acad Sci USA 101:12102–12107. [PubMed][CrossRef]
141. Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander ES, Kent J, Miller W, Haussler D. 2006. Identification and classification of conserved RNA secondary structures in the human genome. PLoS Comput Biol 2:e33. [PubMed][CrossRef]
142. Gruber AR, Findeiss S, Washietl S, Hofacker IL, Stadler PF. 2010. RNAz 2.0: improved noncoding RNA detection. Pac Symp Biocomput 2010:69–79. [PubMed]
143. Washietl S, Hofacker IL, Stadler PF. 2005. Fast and reliable prediction of noncoding RNAs. Proc Natl Acad Sci USA 102:2454–2459. [PubMed][CrossRef]
144. Livny J, Fogel MA, Davis BM, Waldor MK. 2005. sRNAPredict: an integrative computational approach to identify sRNAs in bacterial genomes. Nucleic Acids Res 33:4096–4105. [PubMed][CrossRef]
145. Kingsford CL, Ayanbule K, Salzberg SL. 2007. Rapid, accurate, computational discovery of Rho-independent transcription terminators illuminates their relationship to DNA uptake. Genome Biol 8:R22. [PubMed][CrossRef]
146. Wingender E, Chen X, Hehl R, Karas H, Liebich I, Matys V, Meinhardt T, Pruss M, Reuter I, Schacherer F. 2000. TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res 28:316–319. [PubMed]
147. Livny J, Teonadi H, Livny M, Waldor MK. 2008. High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs. PloS One 3:e3197. [PubMed]
148. Sridhar J, Sambaturu N, Sabarinathan R, Ou HY, Deng Z, Sekar K, Rafi ZA, Rajakumar K. 2010. sRNAscanner: a computational tool for intergenic small RNA detection in bacterial genomes. PloS One 5:e11970. [PubMed][CrossRef]
149. Carter RJ, Dubchak I, Holbrook SR. 2001. A computational approach to identify genes for functional RNAs in genomic sequences. Nucleic Acids Res 29:3928–3938. [PubMed]
150. Klein RJ, Misulovin Z, Eddy SR. 2002. Noncoding RNA genes identified in AT-rich hyperthermophiles. Proc Natl Acad Sci USA 99:7542–7547. [PubMed][CrossRef]
151. Ott A, Idali A, Marchais A, Gautheret D. 2012. NAPP: the Nucleic Acid Phylogenetic Profile Database. Nucleic Acids Res 40:D205–D209. [PubMed][CrossRef]
152. Griffin BE. 1971. Separation of 32P-labelled ribonucleic acid components. The use of polyethylenimine-cellulose (TLC) as a second dimension in separating oligoribonucleotides of “4.5 S” and 5 S from E. coli. FEBS Lett 15:165–168. [PubMed]
153. Hindley J. 1967. Fractionation of 32P-labelled ribonucleic acids on polyacrylamide gels and their characterization by fingerprinting. J Mol Biol 30:125–136. [PubMed]
154. Ikemura T, Dahlberg JE. 1973. Small ribonucleic acids of Escherichia coli. I. Characterization by polyacrylamide gel electrophoresis and fingerprint analysis. J Biol Chem 248:5024–5032. [PubMed]
155. Altuvia S, Weinstein-Fischer D, Zhang A, Postow L, Storz G. 1997. A small, stable RNA induced by oxidative stress: role as a pleiotropic regulator and antimutator. Cell 90:43–53. [PubMed]
156. Romeo T. 1998. Global regulation by the small RNA-binding protein CsrA and the non-coding RNA molecule CsrB. Mol Microbiol 29:1321–1330. [PubMed]
157. Mizuno T, Chou MY, Inouye M. 1984. A unique mechanism regulating gene expression: translational inhibition by a complementary RNA transcript (micRNA). Proc Natl Acad Sci USA 81:1966–1970. [PubMed]
158. Sledjeski D, Gottesman S. 1995. A small RNA acts as an antisilencer of the H-NS-silenced rcsA gene of Escherichia coli. Proc Natl Acad Sci USA 92:2003–2007. [PubMed]
159. Vogel J, Sharma CM. 2005. How to find small non-coding RNAs in bacteria. Biol Chem 386:1219–1238. [PubMed][CrossRef]
160. Chen S, Lesnik EA, Hall TA, Sampath R, Griffey RH, Ecker DJ, Blyn LB. 2002. A bioinformatics based approach to discover small RNA genes in the Escherichia coli genome. Biosystems 65:157–177. [PubMed]
161. Wassarman KM, Repoila F, Rosenow C, Storz G, Gottesman S. 2001. Identification of novel small RNAs using comparative genomics and microarrays. Genes Dev 15:1637–1651. [PubMed][CrossRef]
162. Livny J, Brencic A, Lory S, Waldor MK. 2006. Identification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNA Predict2. Nucleic Acids Res 34:3484–3493. [PubMed][CrossRef]
163. Toledo-Arana A, Dussurget O, Nikitas G, Sesto N, Guet-Revillet H, Balestrino D, Loh E, Gripenland J, Tiensuu T, Vaitkevicius K, Barthelemy M, Vergassola M, Nahori MA, Soubigou G, Regnault B, Coppee JY, Lecuit M, Johansson J, Cossart P. 2009. The Listeria transcriptional landscape from saprophytism to virulence. Nature 459:950–956. [PubMed][CrossRef]
164. Pichon C, Felden B. 2005. Small RNA genes expressed from Staphylococcus aureus genomic and pathogenicity islands with specific expression among pathogenic strains. Proc Natl Acad Sci USA 102:14249–14254. [PubMed][CrossRef]
165. Silvaggi JM, Perkins JB, Losick R. 2006. Genes for small, noncoding RNAs under sporulation control in Bacillus subtilis. J Bacteriol 188:532–541. [PubMed][CrossRef]
166. Patenge N, Billion A, Raasch P, Normann J, Wisniewska-Kucper A, Retey J, Boisguerin V, Hartsch T, Hain T, Kreikemeyer B. 2012. Identification of novel growth phase- and media-dependent small non-coding RNAs in Streptococcus pyogenes M49 using intergenic tiling arrays. BMC Genomics 13:550. [PubMed][CrossRef]
167. Akama T, Suzuki K, Tanigawa K, Kawashima A, Wu H, Nakata N, Osana Y, Sakakibara Y, Ishii N. 2009. Whole-genome tiling array analysis of Mycobacterium leprae RNA reveals high expression of pseudogenes and noncoding regions. J Bacteriol 191:3321–3327. [PubMed][CrossRef]
168. Oliver HF, Orsi RH, Ponnala L, Keich U, Wang W, Sun Q, Cartinhour SW, Filiatrault MJ, Wiedmann M, Boor KJ. 2009. Deep RNA sequencing of L. monocytogenes reveals overlapping and extensive stationary phase and sigma B-dependent transcriptomes, including multiple highly transcribed noncoding RNAs. BMC Genomics 10:641. [PubMed][CrossRef]
169. Passalacqua KD, Varadarajan A, Ondov BD, Okou DT, Zwick ME, Bergman NH. 2009. Structure and complexity of a bacterial transcriptome. J Bacteriol 191:3203–3211. [PubMed][CrossRef]
170. Yoder-Himes DR, Chain PS, Zhu Y, Wurtzel O, Rubin EM, Tiedje JM, Sorek R. 2009. Mapping the Burkholderia cenocepacia niche response via high-throughput sequencing. Proc Natl Acad Sci USA 106:3976–3981. [PubMed][CrossRef]
171. Guell M, van Noort V, Yus E, Chen WH, Leigh-Bell J, Michalodimitrakis K, Yamada T, Arumugam M, Doerks T, Kuhner S, Rode M, Suyama M, Schmidt S, Gavin AC, Bork P, Serrano L. 2009. Transcriptome complexity in a genome-reduced bacterium. Science 326:1268–1271. [PubMed][CrossRef]
172. Perkins TT, Kingsley RA, Fookes MC, Gardner PP, James KD, Yu L, Assefa SA, He M, Croucher NJ, Pickard DJ, Maskell DJ, Parkhill J, Choudhary J, Thomson NR, Dougan G. 2009. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet 5:e1000569. [PubMed]
173. Sittka A, Lucchini S, Papenfort K, Sharma CM, Rolle K, Binnewies TT, Hinton JC, Vogel J. 2008. Deep sequencing analysis of small noncoding RNA and mRNA targets of the global post-transcriptional regulator, Hfq. PLoS Genet 4:e1000163. [PubMed][CrossRef]
174. Dugar G, Herbig A, Forstner KU, Heidrich N, Reinhardt R, Nieselt K, Sharma CM. 2013. High-resolution transcriptome maps reveal strain-specific regulatory features of multiple Campylobacter jejuni isolates. PLoS Genet 9:e1003495.
175. Pichon C, Felden B. 2007. Proteins that interact with bacterial small RNA regulators. FEMS Microbiol Rev 31:614–625. [PubMed][CrossRef]
176. Brennan RG, Link TM. 2007. Hfq structure, function and ligand binding. Curr Opin Microbiol 10:125–133. [PubMed][CrossRef]
177. Uzzau S, Figueroa-Bossi N, Rubino S, Bossi L. 2001. Epitope tagging of chromosomal genes in Salmonella. Proc Natl Acad Sci USA 98:15264–15269. [PubMed][CrossRef]
178. Sonnleitner E, Sorger-Domenigg T, Madej MJ, Findeiss S, Hackermuller J, Huttenhofer A, Stadler PF, Blasi U, Moll I. 2008. Detection of small RNAs in Pseudomonas aeruginosa by RNomics and structure-based bioinformatic tools. Microbiology 154:3175–3187. [PubMed][CrossRef]
179. Christiansen JK, Nielsen JS, Ebersbach T, Valentin-Hansen P, Sogaard-Andersen L, Kallipolitis BH. 2006. Identification of small Hfq-binding RNAs in Listeria monocytogenes. RNA 12:1383–1396. [PubMed][CrossRef]
180. Dambach M, Irnov I, Winkler WC. 2013. Association of RNAs with Bacillus subtilis Hfq. PloS One 8:e55156. [PubMed]
181. Sittka A, Sharma CM, Rolle K, Vogel J. 2009. Deep sequencing of Salmonella RNA associated with heterologous Hfq proteins in vivo reveals small RNAs as a major target class and identifies RNA processing phenotypes. RNA Biol 6:266–275. [PubMed]
182. Zuker M, Stiegler P. 1981. Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 9:133–148. [PubMed]
183. McCaskill JS. 1990. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 29:1105–1119. [PubMed][CrossRef]
184. Schuster P, Fontana W, Stadler PF, Hofacker IL. 1994. From sequences to shapes and back: a case study in RNA secondary structures. Proc Biol Sci 255:279–284. [PubMed][CrossRef]
185. Sato K, Hamada M, Asai K, Mituyama T. 2009. CENTROIDFOLD: a web server for RNA secondary structure prediction. Nucleic Acids Res 37:W277–W280. [PubMed][CrossRef]
186. Hamada M, Sato K, Kiryu H, Mituyama T, Asai K. 2009. Predictions of RNA secondary structure by combining homologous sequence information. Bioinformatics 25:i330–i338. [PubMed][CrossRef]
187. Timmermans J, Van Melderen L. 2010. Post-transcriptional global regulation by CsrA in bacteria. Cell Mol Life Sci 67:2897–2908. [PubMed][CrossRef]
188. Trotochaud AE, Wassarman KM. 2005. A highly conserved 6S RNA structure is required for regulation of transcription. Nat Struct Mol Biol 12:313–319. [PubMed][CrossRef]
189. Lioliou E, Sharma CM, Caldelari I, Helfer AC, Fechter P, Vandenesch F, Vogel J, Romby P. 2012. Global regulatory functions of the Staphylococcus aureus endoribonuclease III in gene expression. PLoS Genetics 8:e1002782. [PubMed][CrossRef]
190. Houghton J, Cortes T, Schubert OT, Rose G, Rodgers A, De Ste Croix M, Aebersold R, Young DB, Arnvig KB. 2013. A small RNA encoded in the Rv2660c locus of Mycobacterium tuberculosis is induced during starvation and infection. PloS One 8(12) :e80047. doi:10.1371/journal.pone.0080047. [PubMed][CrossRef]
191. Smollett KL, Smith KM, Kahramanoglou C, Arnvig KB, Buxton RS, Davis EO. 2012. Global analysis of the regulon of the transcriptional repressor LexA, a key component of SOS response in Mycobacterium tuberculosis. J Biol Chem 287:22004–22014. [PubMed][CrossRef]
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/content/journal/microbiolspec/10.1128/microbiolspec.MGM2-0029-2013
2014-03-14
2019-03-24

Abstract:

Efforts to understand the molecular basis of mycobacterial gene regulation are dominated by a protein-centric view. However, there is a growing appreciation that noncoding RNA, i.e., RNA that is not translated, plays a role in a wide variety of molecular mechanisms. Noncoding RNA comprises rRNA, tRNA, 4.5S RNA, RnpB, and transfer-messenger RNA, as well as a vast population of regulatory RNA, often dubbed “the dark matter of gene regulation.” The regulatory RNA species comprise 5′ and 3′ untranslated regions and a rapidly expanding category of transcripts with the ability to base-pair with mRNAs or to interact with proteins. Regulatory RNA plays a central role in the bacterium's response to changes in the environment, and in this article we review emerging information on the presence and abundance of different types of noncoding RNA in mycobacteria.

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Noncoding RNA in Mycobacteria
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Citation: Arnvig K, Cortes T, Young D. 2014. Noncoding rna in mycobacteria. microbiolspec 2(2): doi:10.1128/microbiolspec.MGM2-0029-2013
/content/microbiolspec/10.1128/microbiolspec.MGM2-0029-2013.fig1
FIGURE 1
Venn diagram illustrating how the (nomenclature of) different types of ncRNA and regulatory RNAs overlap and, in particular, how sRNAs can be assigned to more than one category. The sRNA subcategories shown are sRNA (purely regulatory function), sRNA (dual function, i.e., regulatory potential as well as encoding small peptide), sRNA (purely coding, i.e., no function as ribo-regulator). Thus, sRNAs can be coding or noncoding, regulatory or not regulatory. Figure modified from reference 15 .
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FIGURE 1

Venn diagram illustrating how the (nomenclature of) different types of ncRNA and regulatory RNAs overlap and, in particular, how sRNAs can be assigned to more than one category. The sRNA subcategories shown are sRNA (purely regulatory function), sRNA (dual function, i.e., regulatory potential as well as encoding small peptide), sRNA (purely coding, i.e., no function as ribo-regulator). Thus, sRNAs can be coding or noncoding, regulatory or not regulatory. Figure modified from reference 15 .

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FIGURE 2
Transcription termination in mycobacteria. The top panel illustrates the consensus sequence and structure of the mycobacterial terminator, TRIT (tuberculosis rho-independent terminator). TRIT is a novel rho-independent terminator with high sequence conservation identified in and specific for mycobacteria ( 29 ). The bottom panel illustrates the expression of two converging genes in , according to RNA-seq and visualized in the Artemis genome browser; blue represents expression from the forward strand (), and red represents expression from the reverse strand (); the height of the trace represents the normalized expression level (reads) over the entire region. The traces demonstrate the termination efficiency exerted by TRIT between the two converging genes.
microbiolspec/2/2/MGM2-0029-2013-fig2_thmb.gif
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FIGURE 2

Transcription termination in mycobacteria. The top panel illustrates the consensus sequence and structure of the mycobacterial terminator, TRIT (tuberculosis rho-independent terminator). TRIT is a novel rho-independent terminator with high sequence conservation identified in and specific for mycobacteria ( 29 ). The bottom panel illustrates the expression of two converging genes in , according to RNA-seq and visualized in the Artemis genome browser; blue represents expression from the forward strand (), and red represents expression from the reverse strand (); the height of the trace represents the normalized expression level (reads) over the entire region. The traces demonstrate the termination efficiency exerted by TRIT between the two converging genes.

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FIGURE 3
Ribo-regulation associated with methionine biosynthesis in . At least three enzymes synthesize methionine in ; the expression of two of these is regulated by riboswitches. expression is regulated by a SAM-IV riboswitch, and the MetC enzyme uses homoserine as substrate. expression is regulated by a B riboswitch, and the MetE enzyme uses homocysteine as substrate. The third enzyme, MetH, is a B-dependent isoform of MetE, and MetH also uses homocysteine as substrate; the mRNA of this gene belongs to the category of naturally leaderless mRNAs, which are unusually widespread in ( 16 ). Riboswitch ligands and enzyme cofactors are shown as “stars,” genes are shown in blue, and enzymes are shown as green/yellow “clouds.”
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FIGURE 3

Ribo-regulation associated with methionine biosynthesis in . At least three enzymes synthesize methionine in ; the expression of two of these is regulated by riboswitches. expression is regulated by a SAM-IV riboswitch, and the MetC enzyme uses homoserine as substrate. expression is regulated by a B riboswitch, and the MetE enzyme uses homocysteine as substrate. The third enzyme, MetH, is a B-dependent isoform of MetE, and MetH also uses homocysteine as substrate; the mRNA of this gene belongs to the category of naturally leaderless mRNAs, which are unusually widespread in ( 16 ). Riboswitch ligands and enzyme cofactors are shown as “stars,” genes are shown in blue, and enzymes are shown as green/yellow “clouds.”

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FIGURE 4
Magnesium-sensing riboswitches in . The figure illustrates the genomic context of the two identified Mboxes (magnesium-sensing riboswitches) in . Genes shown in green are conserved hypotheticals, those in orange are information pathways, gray represents PE-PPE genes, and genes in blue are cell wall associated. Black arrows indicate relevant transcription start sites.
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FIGURE 4

Magnesium-sensing riboswitches in . The figure illustrates the genomic context of the two identified Mboxes (magnesium-sensing riboswitches) in . Genes shown in green are conserved hypotheticals, those in orange are information pathways, gray represents PE-PPE genes, and genes in blue are cell wall associated. Black arrows indicate relevant transcription start sites.

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FIGURE 5
The RNA is highly expressed during exponential growth and significantly downregulated in stationary phase in H37Rv. The RNA is expressed in the majority of lineage 4 strains (here represented by H37Rv) and in some lineage 1 strains (represented by N0157), but not in other lineages (N0052—lineage 2—has been shown for comparison). RNA-seq data is visualized in Artemis. All reads are normalized to total reads and adjusted to the same scale.
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FIGURE 5

The RNA is highly expressed during exponential growth and significantly downregulated in stationary phase in H37Rv. The RNA is expressed in the majority of lineage 4 strains (here represented by H37Rv) and in some lineage 1 strains (represented by N0157), but not in other lineages (N0052—lineage 2—has been shown for comparison). RNA-seq data is visualized in Artemis. All reads are normalized to total reads and adjusted to the same scale.

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FIGURE 6
-encoded RNAs with -regulating potential. A transcript encoded opposite (antisense) to the gene (ASpks) shows high complementarity to three other mRNAs, namely , , and . The figure illustrates the predicted base-pairing between ASpks and the three mRNAs. From reference 8 .
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FIGURE 6

-encoded RNAs with -regulating potential. A transcript encoded opposite (antisense) to the gene (ASpks) shows high complementarity to three other mRNAs, namely , , and . The figure illustrates the predicted base-pairing between ASpks and the three mRNAs. From reference 8 .

Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0029-2013
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FIGURE 7
RNA-seq data (visualized in Artemis) of the CRISPR locus. The upper trace records TSS mapping (i.e., enriched for primary transcripts) from the right-hand side of the CRISPR locus, showing overlapping start sites for the Rv2816c antisense transcript (forward direction in blue) and the single CRISPR-RNA (crRNA) transcript (reverse, in red). The lower trace records sequencing of total RNA, showing the antisense transcript covering Rv2816c and Rv2817c (blue) and illustrating how the single crRNA transcript is processed into a series of mature, smaller crRNAs (red). A similar crRNA profile is seen on the left-hand side of the CRISPR locus, upstream of the Rv2614c/Rv2615c IS6110 insertion sequence (not shown).
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microbiolspec/2/2/MGM2-0029-2013-fig7.gif
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FIGURE 7

RNA-seq data (visualized in Artemis) of the CRISPR locus. The upper trace records TSS mapping (i.e., enriched for primary transcripts) from the right-hand side of the CRISPR locus, showing overlapping start sites for the Rv2816c antisense transcript (forward direction in blue) and the single CRISPR-RNA (crRNA) transcript (reverse, in red). The lower trace records sequencing of total RNA, showing the antisense transcript covering Rv2816c and Rv2817c (blue) and illustrating how the single crRNA transcript is processed into a series of mature, smaller crRNAs (red). A similar crRNA profile is seen on the left-hand side of the CRISPR locus, upstream of the Rv2614c/Rv2615c IS6110 insertion sequence (not shown).

Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0029-2013
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Tables

Noncoding RNA in Mycobacteria
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Citation: Arnvig K, Cortes T, Young D. 2014. Noncoding rna in mycobacteria. microbiolspec 2(2): doi:10.1128/microbiolspec.MGM2-0029-2013
/content/microbiolspec/10.1128/microbiolspec.MGM2-0029-2013.T1
TABLE 1
Intergenic sRNAs
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TABLE 1

Intergenic sRNAs

Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0029-2013

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