Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify “novel” genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method. The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (~30%) were located in genomic region unique to strain 2336 (~18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations.
References
[1]
Forst CV (2006) Host-pathogen systems biology. Drug Discov Today 11: 220–227.
[2]
Aderem A, Adkins JN, Ansong C, Galagan J, Kaiser S, et al. (2011) A systems biology approach to infectious disease research: innovating the pathogen-host research paradigm. MBio 2:
[3]
Peng X, Chan EY, Li Y, Diamond DL, Korth MJ, et al. (2009) Virus-host interactions: from systems biology to translational research. Curr Opin Microbiol 12: 432–438.
[4]
Kapil S, Basaraba RJ (1997) Infectious bovine rhinotracheitis, parainfluenza-3 and bovine respiratory coronavirus. Veterinary Clinics of North America: Food Animal Practice 13: 455–469.
[5]
Griffin D (1997) Economic impact associated with respiratory disease in beef cattle. Vet Clin North Am Food Anim Pract 3: 367–377.
[6]
Ellis JA (2001) The immunology of the bovine respiratory disease complex. Vet Clin North Am Food Anim Pract 17: 535–550, vi–vii.
[7]
Kuckleburg CJ, Sylte MJ, Inzana TJ, Corbeil LB, Darien BJ, et al. (2005) Bovine platelets activated by Haemophilus somnus and its LOS induce apoptosis in bovine endothelial cells. Microb Pathog 38: 23–32.
[8]
Salzberg SL, Delcher AL, Kasif S, White O (1998) Microbial gene identification using interpolated Markov models. Nucleic Acids Res 26: 544–548.
[9]
Besemer J, Lomsadze A, Borodovsky M (2001) GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 29: 2607–2618.
[10]
Palleja A, Harrington ED, Bork P (2008) Large gene overlaps in prokaryotic genomes: result of functional constraints or mispredictions? BMC Genomics 9: 335.
[11]
Kulkarni RV, Kulkarni PR (2007) Computational approaches for the discovery of bacterial small RNAs. Methods 43: 131–139.
[12]
Backofen R, Hess WR (2010) Computational prediction of sRNAs and their targets in bacteria. RNA Biol 7:
[13]
Tjaden B, Saxena RM, Stolyar S, Haynor DR, Kolker E, et al. (2002) Transcriptome analysis of Escherichia coli using high-density oligonucleotide probe arrays. Nucleic Acids Res 30: 3732–3738.
[14]
Akama T, Suzuki K, Tanigawa K, Kawashima A, Wu H, et al. (2009) Whole-genome tiling array analysis of Mycobacterium leprae RNA reveals high expression of pseudogenes and noncoding regions. J Bacteriol 191: 3321–3327.
[15]
Landt SG, Abeliuk E, McGrath PT, Lesley JA, McAdams HH, et al. (2008) Small non-coding RNAs in Caulobacter crescentus. Mol Microbiol 68: 600–614.
[16]
Liu JM, Livny J, Lawrence MS, Kimball MD, Waldor MK, et al. (2009) Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing. Nucleic Acids Res 37: e46.
[17]
Sittka A, Lucchini S, Papenfort K, Sharma CM, Rolle K, et al. (2008) Deep sequencing analysis of small noncoding RNA and mRNA targets of the global post-transcriptional regulator, Hfq. PLoS Genet 4: e1000163.
[18]
Guell M, van Noort V, Yus E, Chen WH, Leigh-Bell J, et al. (2009) Transcriptome complexity in a genome-reduced bacterium. Science 326: 1268–1271.
[19]
Livny J, Waldor MK (2007) Identification of small RNAs in diverse bacterial species. Curr Opin Microbiol 10: 96–101.
[20]
Norrby SR, Nord CE, Finch R (2005) Lack of development of new antimicrobial drugs: a potential serious threat to public health. Lancet Infect Dis 5: 115–119.
[21]
Bumann D (2010) Pathogen proteomes during infection: A basis for infection research and novel control strategies. J Proteomics 73: 2267–2276.
Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, et al. (2005) Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res 33: D121–124.
[24]
Mao F, Dam P, Chou J, Olman V, Xu Y (2008) DOOR: a database for prokaryotic operons. Nucleic Acids Res.
[25]
Nannini E, Murray BE, Arias CA (2010) Resistance or decreased susceptibility to glycopeptides, daptomycin, and linezolid in methicillin-resistant Staphylococcus aureus. Curr Opin Pharmacol 10: 516–521.
[26]
Tisserant E, Da Silva C, Kohler A, Morin E, Wincker P, et al. (2011) Deep RNA sequencing improved the structural annotation of the Tuber melanosporum transcriptome. New Phytol 189: 883–891.
[27]
Martin J, Zhu W, Passalacqua KD, Bergman N, Borodovsky M (2010) Bacillus anthracis genome organization in light of whole transcriptome sequencing. BMC Bioinformatics 11: Suppl 3S10.
[28]
Kumar R, Shah P, Swiatlo E, Burgess SC, Lawrence ML, et al. (2010) Identification of novel non-coding small RNAs from Streptococcus pneumoniae TIGR4 using high-resolution genome tiling arrays. BMC Genomics 11: 350.
[29]
Croucher NJ, Thomson NR (2010) Studying bacterial transcriptomes using RNA-seq. Curr Opin Microbiol 13: 619–624.
[30]
van Vliet AH (2010) Next generation sequencing of microbial transcriptomes: challenges and opportunities. FEMS Microbiol Lett 302: 1–7.
[31]
Perkins TT, Kingsley RA, Fookes MC, Gardner PP, James KD, et al. (2009) A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet 5: e1000569.
[32]
Yoder-Himes DR, Chain PS, Zhu Y, Wurtzel O, Rubin EM, et al. (2009) Mapping the Burkholderia cenocepacia niche response via high-throughput sequencing. Proc Natl Acad Sci U S A 106: 3976–3981.
[33]
Passalacqua KD, Varadarajan A, Ondov BD, Okou DT, Zwick ME, et al. (2009) Structure and complexity of a bacterial transcriptome. J Bacteriol 191: 3203–3211.
[34]
Wurtzel O, Sapra R, Chen F, Zhu Y, Simmons BA, et al. (2010) A single-base resolution map of an archaeal transcriptome. Genome Res 20: 133–141.
[35]
Toledo-Arana A, Repoila F, Cossart P (2007) Small noncoding RNAs controlling pathogenesis. Curr Opin Microbiol 10: 182–188.
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10: R25.
[42]
Boucher HW, Talbot GH, Bradley JS, Edwards JE, Gilbert D, et al. (2009) Bad bugs, no drugs: no ESKAPE! An update from the Infectious Diseases Society of America. Clin Infect Dis 48: 1–12.
[43]
Reese MG (2001) Application of a time-delay neural network to promoter annotation in the Drosophila melanogaster genome. Comput Chem 26: 51–56.
[44]
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.
[45]
Kozhenkov S, Sedova M, Dubinina Y, Gupta A, Ray A, et al. (2011) BiologicalNetworks–tools enabling the integration of multi-scale data for the host-pathogen studies. BMC Syst Biol 5: 7.
[46]
Sturdevant DE, Virtaneva K, Martens C, Bozinov D, Ogundare O, et al. (2010) Host-microbe interaction systems biology: lifecycle transcriptomics and comparative genomics. Future Microbiol 5: 205–219.