1887

Microbial Genomics logo

Volume 6, Issue 1

Comparative genomic analysis identifies X-factor (haemin)-independent : a formal re-classification of '' Open Access

Abstract

The heterogeneous and highly recombinogenic genus comprises several species, some of which are pathogenic to humans. All share an absolute requirement for blood-derived factors during growth. Certain species, such as the pathogen and the commensal , are thought to require both haemin (X-factor) and nicotinamide adenine dinucleotide (NAD, V-factor), whereas others, such as the informally classified ‘ subsp. ’, and , only require V-factor. These differing growth requirements are commonly used for species differentiation, although a number of studies are now revealing issues with this approach. Here, we perform large-scale phylogenomics of 240 spp. genomes, including five ‘’ genomes generated in the current study, to reveal that strains of the ‘’ group are in fact haemin-independent (hi). Closer examination of these hi strains revealed that they encode an intact haemin biosynthesis pathway, unlike haemin-dependent and , which lack most haemin biosynthesis genes. Our results suggest that the common ancestor of modern-day and lost key haemin biosynthesis loci, likely as a consequence of specialized adaptation to otorhinolaryngeal and respiratory niches during their divergence from . Genetic similarity analysis demonstrated that the haemin biosynthesis loci acquired in the hi lineage were likely laterally transferred from a ancestor, and that this event probably occurred only once in hi. This study further challenges the validity of phenotypic methods for differentiating among species, and highlights the need for whole-genome sequencing for accurate characterization of species within this taxonomically challenging genus.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): 'Haemophilus intermedius' , comparative genomics , haemin biosynthesis , haemin-independent Haemophilus haemolyticus and Haemophilus haemolyticus
Funding
This study was supported by the:
  • Advance Queensland (Award AQRF13016-17RD2)
    • Principle Award Recipient: Derek S Sarovich
  • Advance Queensland (Award AQIRF0362018)
    • Principle Award Recipient: Erin P Price
  • National Health and Medical Research Council (Award 1079557)
    • Principle Award Recipient: Anne B Chang
  • National Health and Medical Research Council (Award 1042601)
    • Principle Award Recipient: Anne B Chang
  • National Health and Medical Research Council (Award 1023781)
    • Principle Award Recipient: Anne B Chang
  • National Health and Medical Research Council (Award 1100310)
    • Principle Award Recipient: Heidi C Smith-Vaughan
  • Channel 7 Children's Research Foundation (Award 151068)
    • Principle Award Recipient: Erin P Price
© 2020 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000303
2019-12-20
2024-05-06
Loading full text...

Full text loading...

/deliver/fulltext/mgen/6/1/mgen000303.html?itemId=/content/journal/mgen/10.1099/mgen.0.000303&mimeType=html&fmt=ahah

References

  1. Nørskov-Lauritsen N. Classification, identification, and clinical significance of Haemophilus and Aggregatibacter species with host specificity for humans. Clin Microbiol Rev 2014; 27:214–240 [View Article]
     [Google Scholar]
  2. Burbach S. Reclassification of the genus Haemophilus Winslow, et al. 1917 based on nucleotide sequence homology. Inaugural Dissertation Philipps-Universität Marburg; Marburg, Germany: 1987
     [Google Scholar]
  3. Nørskov-Lauritsen N, Overballe MD, Kilian M. Delineation of the species Haemophilus influenzae by phenotype, multilocus sequence phylogeny, and detection of marker genes. J Bacteriol 2009; 191:822–831 [View Article]
     [Google Scholar]
  4. Thjötta T, Avery OT. Studies on bacterial nutrition: II. Growth accessory substances in the cultivation of hemophilic bacilli. J Exp Med 1921; 34:97–114 [View Article]
     [Google Scholar]
  5. Wurzel DF, Marchant JM, Yerkovich ST, Upham JW, Petsky HL et al. Protracted bacterial bronchitis in children: natural history and risk factors for bronchiectasis. Chest 2016; 150:1101–1108 [View Article]
     [Google Scholar]
  6. Goyal V, Grimwood K, Byrnes CA, Morris PS, Masters IB et al. Amoxicillin–clavulanate versus azithromycin for respiratory exacerbations in children with bronchiectasis (BEST-2): a multicentre, double-blind, non-inferiority, randomised controlled trial. The Lancet 2018; 392:1197–1206 [View Article]
     [Google Scholar]
  7. Kilian M. A taxonomic study of the genus Haemophilus, with the proposal of a new species. J Gen Microbiol 1976; 93:9–62 [View Article]
     [Google Scholar]
  8. Munson EL, Doern GV. Comparison of three commercial test systems for biotyping Haemophilus influenzae and Haemophilus parainfluenzae . J Clin Microbiol 2007; 45:4051–4053 [View Article]
     [Google Scholar]
  9. Barbé G, Babolat M, Boeufgras JM, Monget D, Freney J. Evaluation of API NH, a new 2-hour system for identification of Neisseria and Haemophilus species and Moraxella catarrhalis in a routine clinical laboratory. J Clin Microbiol 1994; 32:187–189
     [Google Scholar]
  10. Valenza G, Ruoff C, Vogel U, Frosch M, Abele-Horn M. Microbiological evaluation of the new VITEK 2 Neisseria-Haemophilus identification card. J Clin Microbiol 2007; 45:3493–3497 [View Article]
     [Google Scholar]
  11. Rennie RP, Brosnikoff C, Shokoples S, Reller LB, Mirrett S et al. Multicenter evaluation of the new Vitek 2 Neisseria-Haemophilus identification card. J Clin Microbiol 2008; 46:2681–2685 [View Article]
     [Google Scholar]
  12. McCrea KW, Xie J, LaCross N, Patel M, Mukundan D et al. Relationships of nontypeable Haemophilus influenzae strains to hemolytic and nonhemolytic Haemophilus haemolyticus strains. J Clin Microbiol 2008; 46:406–416 [View Article]
     [Google Scholar]
  13. Witherden EA, Bajanca-Lavado MP, Tristram SG, Nunes A. Role of inter-species recombination of the ftsI gene in the dissemination of altered penicillin-binding-protein-3-mediated resistance in Haemophilus influenzae and Haemophilus haemolyticus . J Antimicrob Chemother 2014; 69:1501–1509 [View Article]
     [Google Scholar]
  14. Connor TR, Corander J, Hanage WP. Population subdivision and the detection of recombination in non-typable Haemophilus influenzae . Microbiology 2012; 158:2958–2964 [View Article]
     [Google Scholar]
  15. Binks MJ, Temple B, Kirkham LA, Wiertsema SP, Dunne EM et al. Molecular surveillance of true nontypeable Haemophilus influenzae: an evaluation of PCR screening assays. PLoS One 2012; 7:e34083 [View Article]
     [Google Scholar]
  16. Frickmann H, Christner M, Donat M, Berger A, Essig A et al. Rapid discrimination of Haemophilus influenzae, H. parainfluenzae, and H. haemolyticus by fluorescence in situ hybridization (FISH) and two matrix-assisted laser-desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) platforms. PLoS One 2013; 8:e63222 [View Article]
     [Google Scholar]
  17. Price EP, Sarovich DS, Nosworthy E, Beissbarth J, Marsh RL et al. Haemophilus influenzae: using comparative genomics to accurately identify a highly recombinogenic human pathogen. BMC Genomics 2015; 16:641 [View Article]
     [Google Scholar]
  18. Price EP, Harris TM, Spargo J, Nosworthy E, Beissbarth J et al. Simultaneous identification of Haemophilus influenzae and Haemophilus haemolyticus using real-time PCR. Future Microbiol 2017; 12:585–593 [View Article]
     [Google Scholar]
  19. Pickering J, Binks MJ, Beissbarth J, Hare KM, Kirkham LAS et al. A PCR-high-resolution melt assay for rapid differentiation of nontypeable Haemophilus influenzae and Haemophilus haemolyticus . J Clin Microbiol 2014; 52:663–667 [View Article]
     [Google Scholar]
  20. Latham R, Zhang B, Tristram S. Identifying Haemophilus haemolyticus and Haemophilus influenzae by SYBR Green real-time PCR. J Microbiol Methods 2015; 112:67–69 [View Article]
     [Google Scholar]
  21. Osman KL, Jefferies JMC, Woelk CH, Devos N, Pascal TG et al. Patients with chronic obstructive pulmonary disease harbour a variation of Haemophilus species. Sci Rep 2018; 8:14734 [View Article]
     [Google Scholar]
  22. Jordan IK, Conley AB, Antonov IV, Arthur RA, Cook ED, Cooper GP et al. Genome sequences for five strains of the emerging pathogen Haemophilus haemolyticus . J Bacteriol 2011; 193:5879–5880 [View Article]
     [Google Scholar]
  23. Ormerod KL, George NM, Fraser JA, Wainwright C, Hugenholtz P. Comparative genomics of non-pseudomonal bacterial species colonising paediatric cystic fibrosis patients. PeerJ 2015; 3:e1223 [View Article]
     [Google Scholar]
  24. Roach DJ, Burton JN, Lee C, Stackhouse B, Butler-Wu SM et al. A year of infection in the intensive care unit: prospective whole genome sequencing of bacterial clinical isolates reveals cryptic transmissions and novel microbiota. PLoS Genet 2015; 11:e1005413 [View Article]
     [Google Scholar]
  25. Post DMB, Ketterer MR, Coffin JE, Reinders LM, Munson RS et al. Comparative analyses of the lipooligosaccharides from nontypeable Haemophilus influenzae and Haemophilus haemolyticus show differences in sialic acid and phosphorylcholine modifications. Infect Immun 2016; 84:765–774 [View Article]
     [Google Scholar]
  26. Zhang L, Xie J, Patel M, Bakhtyar A, Ehrlich GD et al. Nontypeable Haemophilus influenzae genetic islands associated with chronic pulmonary infection. PLoS One 2012; 7:e44730 [View Article]
     [Google Scholar]
  27. Hogg JS, Hu FZ, Janto B, Boissy R, Hayes J et al. Characterization and modeling of the Haemophilus influenzae core and supragenomes based on the complete genomic sequences of Rd and 12 clinical nontypeable strains. Genome Biol 2007; 8:R103 [View Article]
     [Google Scholar]
  28. Harrison A, Dyer DW, Gillaspy A, Ray WC, Mungur R et al. Genomic sequence of an otitis media isolate of nontypeable Haemophilus influenzae: comparative study with H. influenzae serotype D, strain KW20. J Bacteriol 2005; 187:4627–4636 [View Article]
     [Google Scholar]
  29. Strouts FR, Power P, Croucher NJ, Corton N, van Tonder A et al. Lineage-specific virulence determinants of Haemophilus influenzae biogroup aegyptius. Emerg Infect Dis 2012; 18:449–457 [View Article]
     [Google Scholar]
  30. Garmendia J, Viadas C, Calatayud L, Mell JC, Martí-Lliteras P et al. Characterization of nontypable Haemophilus influenzae isolates recovered from adult patients with underlying chronic lung disease reveals genotypic and phenotypic traits associated with persistent infection. PLoS One 2014; 9:e97020 [View Article]
     [Google Scholar]
  31. Mussa HJ, VanWagoner TM, Morton DJ, Seale TW, Whitby PW et al. Draft genome sequences of eight nontypeable Haemophilus influenzae strains previously characterized using an electrophoretic typing scheme. Genome Announc 2015; 3:e01374-15 [View Article]
     [Google Scholar]
  32. VanWagoner TM, Morton DJ, Seale TW, Mussa HJ, Cole BK et al. Draft genome sequences of six nontypeable Haemophilus influenzae strains that establish bacteremia in the infant rat model of invasive disease. Genome Announc 2015; 3:e00899-15 [View Article]
     [Google Scholar]
  33. Giufrè M, De Chiara M, Censini S, Guidotti S, Torricelli G et al. Whole-genome sequences of nonencapsulated Haemophilus influenzae strains isolated in Italy. Genome Announc 2015; 3:e00110-15 [View Article]
     [Google Scholar]
  34. Su YC, Hörhold F, Singh B, Riesbeck K. Complete genome sequence of encapsulated Haemophilus influenzae type f KR494, an invasive isolate that caused necrotizing myositis. Genome Announc 2013; 1:e00470-13
     [Google Scholar]
  35. Langen H, Takács B, Evers S, Berndt P, Lahm HW et al. Two-dimensional map of the proteome of Haemophilus influenzae . Electrophoresis 2000; 21:411–429 [View Article]
     [Google Scholar]
  36. De Chiara M, Hood D, Muzzi A, Pickard DJ, Perkins T et al. Genome sequencing of disease and carriage isolates of nontypeable Haemophilus influenzae identifies discrete population structure. Proc Natl Acad Sci USA 2014; 111:5439–5444 [View Article]
     [Google Scholar]
  37. Chapple SNJ, Sarovich DS, Holden MTG, Peacock SJ, Buller N et al. Whole-genome sequencing of a quarter-century melioidosis outbreak in temperate Australia uncovers a region of low-prevalence endemicity. Microb Genom 2016; 2:e000067 [View Article]
     [Google Scholar]
  38. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article]
     [Google Scholar]
  39. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829 [View Article]
     [Google Scholar]
  40. Boetzer M, Pirovano W. Toward almost closed genomes with GapFiller. Genome Biol 2012; 13:R56 [View Article]
     [Google Scholar]
  41. Assefa S, Keane TM, Otto TD, Newbold C, Berriman M. ABACAS: algorithm-based automatic contiguation of assembled sequences. Bioinformatics 2009; 25:1968–1969 [View Article]
     [Google Scholar]
  42. Tsai IJ, Otto TD, Berriman M. Improving draft assemblies by iterative mapping and assembly of short reads to eliminate gaps. Genome Biol 2010; 11:R41 [View Article]
     [Google Scholar]
  43. Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics 2011; 27:578–579 [View Article]
     [Google Scholar]
  44. Otto TD, Sanders M, Berriman M, Newbold C. Iterative correction of reference nucleotides (iCORN) using second generation sequencing technology. Bioinformatics 2010; 26:1704–1707 [View Article]
     [Google Scholar]
  45. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article]
     [Google Scholar]
  46. Sarovich DS, Price EP. SPANDx: a genomics pipeline for comparative analysis of large haploid whole genome re-sequencing datasets. BMC Res Notes 2014; 7:618 [View Article]
     [Google Scholar]
  47. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009; 25:1754–1760 [View Article]
     [Google Scholar]
  48. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25:2078–2079 [View Article]
     [Google Scholar]
  49. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010; 20:1297–1303 [View Article]
     [Google Scholar]
  50. Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods) version 4 Sunderland, MA: Sinauer Associates; 1998
     [Google Scholar]
  51. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9:5114 [View Article]
     [Google Scholar]
  52. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J et al. BLAST+: architecture and applications. BMC Bioinformatics 2009; 10:421 [View Article]
     [Google Scholar]
  53. Lu CL, Chen KT, Huang SY, Chiu HT. CAR: contig assembly of prokaryotic draft genomes using rearrangements. BMC Bioinformatics 2014; 15:381 [View Article]
     [Google Scholar]
  54. Darling AE, Mau B, Perna NT. progressiveMauve: multiple genome alignment with gene gain, loss and rearrangement. PLoS One 2010; 5:e11147 [View Article]
     [Google Scholar]
  55. Carver TJ, Rutherford KM, Berriman M, Rajandream MA, Barrell BG et al. ACT: the Artemis comparison tool. Bioinformatics 2005; 21:3422–3423 [View Article]
     [Google Scholar]
  56. Huson DH, Scornavacca C. Dendroscope 3: an interactive tool for rooted phylogenetic trees and networks. Syst Biol 2012; 61:1061–1067 [View Article]
     [Google Scholar]
  57. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article]
     [Google Scholar]
  58. Kosakovsky Pond SL, Frost SDW. Not so different after all: a comparison of methods for detecting amino acid sites under selection. Mol Biol Evol 2005; 22:1208–1222 [View Article]
     [Google Scholar]
  59. Weaver S, Shank SD, Spielman SJ, Li M, Muse SV et al. Datamonkey 2.0: a modern web application for characterizing selective and other evolutionary processes. Mol Biol Evol 2018; 35:773–777 [View Article]
     [Google Scholar]
  60. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article]
     [Google Scholar]
  61. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81:559–575 [View Article]
     [Google Scholar]
  62. Sahl JW, Caporaso JG, Rasko DA, Keim P. The large-scale BLAST score ratio (LS-BSR) pipeline: a method to rapidly compare genetic content between bacterial genomes. PeerJ 2014; 2:e332 [View Article]
     [Google Scholar]
  63. Dailey HA, Dailey TA, Gerdes S, Jahn D, Jahn M et al. Prokaryotic heme biosynthesis: multiple pathways to a common essential product. Microbiol Mol Biol Rev 2017; 81:e00048-16 [View Article]
     [Google Scholar]
  64. Blattner FR, Plunkett G, Bloch CA, Perna NT, Burland V et al. The complete genome sequence of Escherichia coli K-12. Science 1997; 277:1453–1462 [View Article]
     [Google Scholar]
  65. Dailey HA, Gerdes S, Dailey TA, Burch JS, Phillips JD. Noncanonical coproporphyrin-dependent bacterial heme biosynthesis pathway that does not use protoporphyrin. Proc Natl Acad Sci USA 2015; 112:2210–2215 [View Article]
     [Google Scholar]
  66. Warren MJ, Stolowich NJ, Santander PJ, Roessner CA, Sowa BA et al. Enzymatic synthesis of dihydrosirohydrochlorin (precorrin-2) and of a novel pyrrocorphin by uroporphyrinogen III methylase. FEBS Lett 1990; 261:76–80 [View Article]
     [Google Scholar]
  67. Avissar YJ, Moberg PA. The common origins of the pigments of life-early steps of chlorophyll biosynthesis. Photosynth Res 1995; 44:221–242 [View Article]
     [Google Scholar]
  68. Hansson M, Rutberg L, Schröder I, Hederstedt L. The Bacillus subtilis hemAXCDBL gene cluster, which encodes enzymes of the biosynthetic pathway from glutamate to uroporphyrinogen III. J Bacteriol 1991; 173:2590–2599 [View Article]
     [Google Scholar]
  69. Hansson M. Tetrapyrrole synthesis in Bacillus subtilis. Doctoral Thesis Lund University; Lund, Sweden: 1994
     [Google Scholar]
  70. Moberg PA, Avissar YJ. A gene cluster in Chlorobium vibrioforme encoding the first enzymes of chlorophyll biosynthesis. Photosynth Res 1994; 41:253–259 [View Article]
     [Google Scholar]
  71. Takahata S, Ida T, Senju N, Sanbongi Y, Miyata A et al. Horizontal gene transfer of ftsI, encoding penicillin-binding protein 3, in Haemophilus influenzae . Antimicrob Agents Chemother 2007; 51:1589–1595 [View Article]
     [Google Scholar]
  72. Søndergaard A, Witherden EA, Nørskov-Lauritsen N, Tristram SG. Interspecies transfer of the penicillin-binding protein 3-encoding gene ftsI between Haemophilus influenzae and Haemophilus haemolyticus can confer reduced susceptibility to β-lactam antimicrobial agents. Antimicrob Agents Chemother 2015; 59:4339–4342 [View Article]
     [Google Scholar]
  73. Mell JC, Shumilina S, Hall IM, Redfield RJ. Transformation of natural genetic variation into Haemophilus influenzae genomes. PLoS Pathog 2011; 7:e1002151 [View Article]
     [Google Scholar]
  74. Murphy TF, Brauer AL, Sethi S, Kilian M, Cai X et al. Haemophilus haemolyticus: a human respiratory tract commensal to be distinguished from Haemophilus influenzae . J Infect Dis 2007; 195:81–89 [View Article]
     [Google Scholar]
  75. Morton DJ, Hempel RJ, Whitby PW, Seale TW, Stull TL. An invasive Haemophilus haemolyticus isolate. J Clin Microbiol 2012; 50:1502–1503 [View Article]
     [Google Scholar]
  76. Anderson R, Wang X, Briere EC, Katz LS, Cohn AC et al. Haemophilus haemolyticus isolates causing clinical disease. J Clin Microbiol 2012; 50:2462–2465 [View Article]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000303
Loading
Comparative genomic analysis identifies X-factor (haemin)-independent Haemophilus haemolyticus: a formal re-classification of 'Haemophilus intermedius'
M Gen 6, e000303 (2020); https://doi.org/10.1099/mgen.0.000303
/content/journal/mgen/10.1099/mgen.0.000303
/content/journal/mgen/10.1099/mgen.0.000303
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error