1887

Abstract

causes over one million deaths from lower respiratory infections per annum worldwide. Although mortality is very high in Southeast Asian countries, molecular epidemiological information remains unavailable for some countries. In this study, we report, for the first time, the whole-genome sequences and genetic profiles of pneumococcal strains isolated in Myanmar. We isolated 60 streptococcal strains from 300 children with acute respiratory infection at Yangon Children’s Hospital in Myanmar. We obtained whole-genome sequences and identified the species, serotypes, sequence types, antimicrobial resistance (AMR) profiles, virulence factor profiles and pangenome structure using sequencing-based analysis. Average nucleotide identity analysis indicated that 58 strains were and the other 2 strains were . The major serotype was 19F (11 strains), followed by 6E (6B genetic variant; 7 strains) and 15 other serotypes; 5 untypable strains were also detected. Multilocus sequence typing analysis revealed 39 different sequence types, including 11 novel ones. In addition, genetic profiling indicated that AMR genes and mutations spread among pneumococcal strains in Myanmar. A minimum inhibitory concentration assay indicated that several pneumococcal strains had acquired azithromycin and tetracycline resistance, whereas no strains were found to be resistant against levofloxacin and high-dose penicillin G. Phylogenetic and pangenome analysis showed various pneumococcal lineages and that the pneumococcal strains contain a rich and mobile gene pool, providing them with the ability to adapt to selective pressures. This molecular epidemiological information can help in tracking global infection and supporting AMR control in addition to public health interventions in Myanmar.

Funding
This study was supported by the:
  • Naito Foundation
    • Principle Award Recipient: ShigetadaKawabata
  • Kobayashi International Scholarship Foundation
    • Principle Award Recipient: ShigetadaKawabata
  • MSD Life Science Foundation, Public Interest Incorporated Foundation
    • Principle Award Recipient: MasayaYamaguchi
  • Takeda Science Foundation (JP)
    • Principle Award Recipient: MasayaYamaguchi
  • Japan Science and Technology Agency (JP) (Award S2019F0304157)
    • Principle Award Recipient: ShigetadaKawabata
  • Secom Science and Technology Foundation
    • Principle Award Recipient: MasayaYamaguchi
  • Japan Agency for Medical Research and Development (Award 20wm0325001h0001)
    • Principle Award Recipient: MasayaYamaguchi
  • Japan Society for the Promotion of Science (Award 20K21675)
    • Principle Award Recipient: ShigetadaKawabata
  • Japan Society for the Promotion of Science (Award 19K22710)
    • Principle Award Recipient: MasayaYamaguchi
  • Japan Society for the Promotion of Science (Award 19H03825)
    • Principle Award Recipient: ShigetadaKawabata
  • Japan Society for the Promotion of Science (Award 18K19643)
    • Principle Award Recipient: ShigetadaKawabata
  • Japan Society for the Promotion of Science (Award 17K11666)
    • Principle Award Recipient: YujiroHirose
  • Japan Society for the Promotion of Science (Award 17H05103)
    • Principle Award Recipient: MasayaYamaguchi
  • Japan Society for the Promotion of Science (Award 16H05847)
    • Principle Award Recipient: ShigetadaKawabata
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2021-02-10
2024-12-09
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References

  1. CDC Antibiotic Resistance Threats in the United States Atlanta, GA: US: Department of Health and Human Services, CDC; 2019
    [Google Scholar]
  2. GBD 2016 Lower Respiratory Infections Collaborators Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990-2016: a systematic analysis for the global burden of disease study 2016. Lancet Infect Dis 2018; 18:1191–1210 [View Article][PubMed]
    [Google Scholar]
  3. Salvadori G, Junges R, Morrison DA, Petersen FC. Competence in Streptococcus pneumoniae and close commensal relatives: mechanisms and implications. Front Cell Infect Microbiol 2019; 9:94 [View Article][PubMed]
    [Google Scholar]
  4. Briles DE, Paton JC, Mukerji R, Swiatlo E, Crain MJ. Pneumococcal vaccines. Microbiol Spectr 2019; 7:GPP3-0028-2018 [View Article]
    [Google Scholar]
  5. Kim L, McGee L, Tomczyk S, Beall B. Biological and Epidemiological Features of Antibiotic-Resistant Streptococcus pneumoniae in Pre- and Post-Conjugate Vaccine Eras: a United States Perspective. Clin Microbiol Rev 2016; 29:525–552 [View Article][PubMed]
    [Google Scholar]
  6. Golubchik T, Brueggemann AB, Street T, Spencer CCA, Spencer CCA et al. Pneumococcal genome sequencing tracks a vaccine escape variant formed through a multi-fragment recombination event. Nat Genet 2012; 44:352–355 [View Article][PubMed]
    [Google Scholar]
  7. Flasche S, Van Hoek AJ, Sheasby E, Waight P, Andrews N et al. Effect of pneumococcal conjugate vaccination on serotype-specific carriage and invasive disease in England: a cross-sectional study. PLoS Med 2011; 8:e1001017 [View Article][PubMed]
    [Google Scholar]
  8. GBD 2015 LRI Collaborators Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the global burden of disease study 2015. Lancet Infect Dis 2017; 17:1133–1161 [View Article][PubMed]
    [Google Scholar]
  9. Chereau F, Opatowski L, Tourdjman M, Vong S. Risk assessment for antibiotic resistance in South East Asia. BMJ 2017; 358:j3393 [View Article][PubMed]
    [Google Scholar]
  10. Holloway KA, Kotwani A, Batmanabane G, Puri M, Tisocki K. Antibiotic use in South East Asia and policies to promote appropriate use: reports from country situational analyses. BMJ 2017; 358:j2291 [View Article][PubMed]
    [Google Scholar]
  11. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018; 34:i884–i890 [View Article][PubMed]
    [Google Scholar]
  12. Souvorov A, Agarwala R, Lipman DJ. SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biol 2018; 19:153 [View Article][PubMed]
    [Google Scholar]
  13. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article][PubMed]
    [Google Scholar]
  14. Rodriguez-R LM, Gunturu S, Harvey WT, Rosselló-Mora R, Tiedje JM et al. The microbial genomes atlas (MiGA) webserver: taxonomic and gene diversity analysis of archaea and bacteria at the whole genome level. Nucleic Acids Res 2018; 46:W282–W288 [View Article][PubMed]
    [Google Scholar]
  15. Epping L, van Tonder AJ, Gladstone RA. The global pneumococcal sequencing C, Bentley SD, et al. SeroBA: rapid high-throughput serotyping of Streptococcus pneumoniae from whole genome sequence data. Microb Genom 2018; 4:
    [Google Scholar]
  16. Hunt M, Mather AE, Sánchez-Busó L, Page AJ, Parkhill J et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom 2017; 3:e000131 [View Article][PubMed]
    [Google Scholar]
  17. Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res 2018; 3:124 [View Article][PubMed]
    [Google Scholar]
  18. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. Card 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517–D525 [View Article][PubMed]
    [Google Scholar]
  19. Liu B, Zheng D, Jin Q, Chen L, Yang J. VFDB 2019: a comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res 2019; 47:D687–D692 [View Article][PubMed]
    [Google Scholar]
  20. Hadfield J, Croucher NJ, Goater RJ, Abudahab K, Aanensen DM et al. Phandango: an interactive viewer for bacterial population genomics. Bioinformatics 2018; 34:292–293 [View Article]
    [Google Scholar]
  21. Yamaguchi M, Nakata M, Sumioka R, Hirose Y, Wada S et al. Zinc metalloproteinase ZmpC suppresses experimental pneumococcal meningitis by inhibiting bacterial invasion of central nervous systems. Virulence 2017; 8:1516–1524 [View Article][PubMed]
    [Google Scholar]
  22. Kang S, Watanabe M, Jacobs JC, Yamaguchi M, Dahesh S et al. Synthesis of mevalonate- and fluorinated mevalonate prodrugs and their in vitro human plasma stability. Eur J Med Chem 2015; 90:448–461 [View Article][PubMed]
    [Google Scholar]
  23. Lin L, Nonejuie P, Munguia J, Hollands A, Olson J et al. Azithromycin synergizes with cationic antimicrobial peptides to exert bactericidal and therapeutic activity against highly multidrug-resistant gram-negative bacterial pathogens. EBioMedicine 2015; 2:690–698 [View Article][PubMed]
    [Google Scholar]
  24. CLSI Performance Standards for Antimicrobial Susceptibility Testing, CLSI supplement M100S. PA, USA: Clinical and Laboratory Standards Institute; 2016
    [Google Scholar]
  25. 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][PubMed]
    [Google Scholar]
  26. Yamaguchi M, Hirose Y, Nakata M, Uchiyama S, Yamaguchi Y et al. Evolutionary inactivation of a sialidase in group B Streptococcus . Sci Rep 2016; 6:28852 [View Article][PubMed]
    [Google Scholar]
  27. Yamaguchi M, Goto K, Hirose Y, Yamaguchi Y, Sumitomo T et al. Identification of evolutionarily conserved virulence factor by selective pressure analysis of Streptococcus pneumoniae . Commun Biol 2019; 2:96 [View Article][PubMed]
    [Google Scholar]
  28. Yamaguchi M, Hirose Y, Takemura M, Ono M, Sumitomo T et al. Streptococcus pneumoniae evades host cell phagocytosis and limits host mortality through its cell wall anchoring protein PfbA. Front Cell Infect Microbiol 2019; 9:301 [View Article][PubMed]
    [Google Scholar]
  29. Yamaguchi M, Takemura M, Higashi K, Goto K, Hirose Y et al. Role of BgaA as a pneumococcal virulence factor elucidated by molecular evolutionary analysis. Front Microbiol 2020; 11:582437 [View Article][PubMed]
    [Google Scholar]
  30. Page AJ, Taylor B, Delaney AJ, Soares J, Seemann T et al. SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments. Microb Genom 2016; 2:e000056 [View Article][PubMed]
    [Google Scholar]
  31. Tanabe AS. Kakusan4 and Aminosan: two programs for comparing nonpartitioned, proportional and separate models for combined molecular phylogenetic analyses of multilocus sequence data. Mol Ecol Resour 2011; 11:914–921 [View Article][PubMed]
    [Google Scholar]
  32. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 2012; 61:539–542 [View Article][PubMed]
    [Google Scholar]
  33. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article][PubMed]
    [Google Scholar]
  34. Letunic I, Bork P. Interactive tree of life (iTOL) V4: recent updates and new developments. Nucleic Acids Res 2019; 47:W256–W259 [View Article][PubMed]
    [Google Scholar]
  35. Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P et al. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 2007; 57:81–91 [View Article][PubMed]
    [Google Scholar]
  36. Burton RL, Geno KA, Saad JS, Nahm MH. Pneumococcus with the "6E" cps locus produces serotype 6B capsular polysaccharide. J Clin Microbiol 2016; 54:967–971 [View Article][PubMed]
    [Google Scholar]
  37. Bergmann S, Hammerschmidt S. Versatility of pneumococcal surface proteins. Microbiology 2006; 152:295–303 [View Article][PubMed]
    [Google Scholar]
  38. Lees JA, Ferwerda B, Kremer PHC, Wheeler NE, Serón MV et al. Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis. Nat Commun 2019; 10:2176 [View Article][PubMed]
    [Google Scholar]
  39. Davies MR, McIntyre L, Mutreja A, Lacey JA, Lees JA et al. Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics. Nat Genet 2019; 51:1035–1043 [View Article][PubMed]
    [Google Scholar]
  40. Ikryannikova LN, Lapin KN, Malakhova MV, Filimonova AV, Ilina EN et al. Misidentification of alpha-hemolytic streptococci by routine tests in clinical practice. Infect Genet Evol 2011; 11:1709–1715 [View Article][PubMed]
    [Google Scholar]
  41. Kaleta EJ, Clark AE, Cherkaoui A, Wysocki VH, Ingram EL et al. Comparative analysis of PCR-electrospray ionization/mass spectrometry (MS) and MALDI-TOF/MS for the identification of bacteria and yeast from positive blood culture bottles. Clin Chem 2011; 57:1057–1067 [View Article][PubMed]
    [Google Scholar]
  42. Ganaie F, Saad JS, McGee L, van Tonder AJ, Bentley SD et al. A new pneumococcal capsule type, 10D, is the 100th serotype and has a large cps fragment from an oral Streptococcus . mBio 2020; 11: [View Article]
    [Google Scholar]
  43. Kilian M, Tettelin H. Identification of virulence-associated properties by comparative genome analysis of Streptococcus pneumoniae, S. pseudopneumoniae, S. mitis, three S. oralis subspecies, and S. infantis . mBio 2019; 10:e01985–01919 [View Article][PubMed]
    [Google Scholar]
  44. Cherazard R, Epstein M, Doan T-L, Salim T, Bharti S et al. Antimicrobial resistant Streptococcus pneumoniae: prevalence, mechanisms, and clinical implications. Am J Ther 2017; 24:e361–e369 [View Article][PubMed]
    [Google Scholar]
  45. Boolchandani M, D'Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet 2019; 20:356–370 [View Article][PubMed]
    [Google Scholar]
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