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Volume 9, Issue 5

Genomic analysis of 1710 surveillance-based isolates from the USA in 2019 identifies predominant strain types and chromosomal antimicrobial-resistance determinants Open Access

Abstract

This study characterized high-quality whole-genome sequences of a sentinel, surveillance-based collection of 1710 (GC) isolates from 2019 collected in the USA as part of the Gonococcal Isolate Surveillance Project (GISP). It aims to provide a detailed report of strain diversity, phylogenetic relationships and resistance determinant profiles associated with reduced susceptibilities to antibiotics of concern. The 1710 isolates represented 164 multilocus sequence types and 21 predominant phylogenetic clades. Common genomic determinants defined most strains’ phenotypic, reduced susceptibility to current and historic antibiotics (e.g. plasmid for penicillin, plasmid for tetracycline, for ciprofloxacin, 23S rRNA and/or mosaic operon for azithromycin, and mosaic for cefixime and ceftriaxone). The most predominant phylogenetic clade accounted for 21 % of the isolates, included a majority of the isolates with low-level elevated MICs to azithromycin (2.0 µg ml), carried a mosaic operon and variants in PorB, and showed expansion with respect to data previously reported from 2018. The second largest clade predominantly carried the GyrA S91F variant, was largely ciprofloxacin resistant (MIC ≥1.0 µg ml), and showed significant expansion with respect to 2018. Overall, a low proportion of isolates had medium- to high-level elevated MIC to azithromycin ((≥4.0 µg ml), based on C2611T or A2059G 23S rRNA variants). One isolate carried the 60.001 allele resulting in elevated MICs to cefixime and ceftriaxone of 1.0 µg ml. This high-resolution snapshot of genetic profiles of 1710 GC sequences, through a comparison with 2018 data (1479 GC sequences) within the sentinel system, highlights change in proportions and expansion of select GC strains and the associated genetic mechanisms of resistance. The knowledge gained through molecular surveillance may support rapid identification of outbreaks of concern. Continued monitoring may inform public health responses to limit the development and spread of antibiotic-resistant gonorrhoea.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): (3-6) antimicrobial resistance , molecular epidemiology , Neisseria gonorrhoeae , surveillance and whole-genome sequencing
© 2023 Crown Copyright
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2023-05-12
2024-05-03
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References

  1. CDC Sexually Transmitted Disease Surveillance 2019 Atlanta, GA, USA: Centers for Disease Control and Prevention, Department of Health and Human Services; 2021
     [Google Scholar]
  2. Dolange V, Churchward CP, Christodoulides M, Snyder LAS. The growing threat of gonococcal blindness. Antibiotics 2018; 7:59 [View Article] [PubMed]
     [Google Scholar]
  3. Weston EJ, Heidenga BL, Farley MM, Tunali A, D’Angelo MT et al. Surveillance for disseminated gonococcal infections, Active Bacterial Core Surveillance (ABCs)-United States, 2015-2019. Clin Infect Dis 2022; 75:953–958 [View Article] [PubMed]
     [Google Scholar]
  4. Rowley J, Vander Hoorn S, Korenromp E, Low N, Unemo M et al. Chlamydia, gonorrhoea, trichomoniasis and syphilis: global prevalence and incidence estimates, 2016. Bull World Health Organ 2019; 97:548–562P [View Article] [PubMed]
     [Google Scholar]
  5. Unemo M, Shafer WM. Antimicrobial resistance in Neisseria gonorrhoeae in the 21st century: past, evolution, and future. Clin Microbiol Rev 2014; 27:587–613 [View Article] [PubMed]
     [Google Scholar]
  6. Cohen MS, Hoffman IF, Royce RA, Kazembe P, Dyer JR et al. Reduction of concentration of HIV-1 in semen after treatment of urethritis: implications for prevention of sexual transmission of HIV-1. AIDSCAP Malawi Research Group. Lancet 1997; 349:1868–1873 [View Article] [PubMed]
     [Google Scholar]
  7. CDC Sexually Transmitted Disease Surveillance 2019: Gonococcal Isolate Surveillance Project (GISP) Supplement and Profiles Atlanta, GA, U.S.A: Centers for Disease Control and Prevention, Department of Health and Human Services; 2021
     [Google Scholar]
  8. CDC Antibiotic Resistance Threats in the United States, 2019 Atlanta, GA: U.S. Department of Health and Human Services, CDC; 2019
     [Google Scholar]
  9. St Cyr S, Barbee L, Workowski KA, Bachmann LH, Pham C et al. Update to CDC’s treatment guidelines for gonococcal infection, 2020. MMWR Morb Mortal Wkly Rep 2020; 69:1911–1916 [View Article] [PubMed]
     [Google Scholar]
  10. Golparian D, Unemo M. Antimicrobial resistance prediction in Neisseria gonorrhoeae: current status and future prospects. Expert Rev Mol Diagn 2022; 22:29–48 [View Article] [PubMed]
     [Google Scholar]
  11. Fiore MA, Raisman JC, Wong NH, Hudson AO, Wadsworth CB. Exploration of the Neisseria resistome reveals resistance mechanisms in commensals that may be acquired by N. gonorrhoeae through horizontal gene transfer. Antibiotics 2020; 9:656 [View Article] [PubMed]
     [Google Scholar]
  12. Ameyama S, Onodera S, Takahata M, Minami S, Maki N et al. Mosaic-like structure of penicillin-binding protein 2 Gene (penA) in clinical isolates of Neisseria gonorrhoeae with reduced susceptibility to cefixime. Antimicrob Agents Chemother 2002; 46:3744–3749 [View Article] [PubMed]
     [Google Scholar]
  13. Thomas JC, Joseph SJ, Cartee JC, Pham CD, Schmerer MW et al. Phylogenomic analysis reveals persistence of gonococcal strains with reduced-susceptibility to extended-spectrum cephalosporins and mosaic penA-34. Nat Commun 2021; 12:3801 [View Article] [PubMed]
     [Google Scholar]
  14. Wadsworth CB, Arnold BJ, Sater MRA, Grad YH. Azithromycin resistance through Interspecific acquisition of an epistasis-dependent efflux pump component and transcriptional regulator in Neisseria gonorrhoeae. mBio 2018; 9:e01419-18 [View Article] [PubMed]
     [Google Scholar]
  15. Rouquette-Loughlin CE, Reimche JL, Balthazar JT, Dhulipala V, Gernert KM et al. Mechanistic basis for decreased antimicrobial susceptibility in a clinical isolate of Neisseria gonorrhoeae possessing a mosaic-like mtr efflux pump locus. mBio 2018; 9:e02281-18 [View Article] [PubMed]
     [Google Scholar]
  16. Schwarcz SK, Zenilman JM, Schnell D, Knapp JS, Hook EW et al. National surveillance of antimicrobial resistance in Neisseria gonorrhoeae. The gonococcal isolate surveillance project. JAMA 1990; 264:1413–1417 [PubMed]
     [Google Scholar]
  17. Kersh EN, Pham CD, Papp JR, Myers R, Steece R et al. Expanding U.S. Laboratory capacity for Neisseria gonorrhoeae antimicrobial susceptibility testing and whole-genome sequencing through the CDC’S antibiotic resistance laboratory network. J Clin Microbiol 2020; 58:e01461-19 [View Article] [PubMed]
     [Google Scholar]
  18. Gernert KM, Seby S, Schmerer MW, Thomas JC, Pham CD et al. Azithromycin susceptibility of Neisseria gonorrhoeae in the USA in 2017: a genomic analysis of surveillance data. Lancet Microbe 2020; 1:e154–e164 [View Article] [PubMed]
     [Google Scholar]
  19. Reimche JL, Chivukula VL, Schmerer MW, Joseph SJ, Pham CD et al. Genomic analysis of the predominant strains and antimicrobial resistance determinants within 1479 Neisseria gonorrhoeae isolates from the US gonococcal isolate surveillance project in 2018. Sex Transm Dis 2021; 48:S78–S87 [View Article] [PubMed]
     [Google Scholar]
  20. CLSI M100 - Performance Standards for Antimicrobial Susceptibility Testing, 32nd edition. Clinical and Laboratory Standards Institute; 2022
     [Google Scholar]
  21. Thomas JC, Seby S, Abrams AJ, Cartee J, Lucking S et al. Evidence of recent genomic evolution in gonococcal strains with decreased susceptibility to cephalosporins or azithromycin in the United States, 2014-2016. J Infect Dis 2019; 220:294–305 [View Article] [PubMed]
     [Google Scholar]
  22. Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 2014; 15:R46 [View Article] [PubMed]
     [Google Scholar]
  23. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet j 2011; 17:10 [View Article]
     [Google Scholar]
  24. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article] [PubMed]
     [Google Scholar]
  25. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
     [Google Scholar]
  26. Gupta A, Jordan IK, Rishishwar L. stringMLST: a fast k-mer based tool for multilocus sequence typing. Bioinformatics 2017; 33:119–121 [View Article] [PubMed]
     [Google Scholar]
  27. Kwong JC, Gonçalves da Silva A, Dyet K, Williamson DA, Stinear TP et al. NGMASTER: in silico multi-antigen sequence typing for Neisseria gonorrhoeae. Microb Genom 2016; 2: [View Article]
     [Google Scholar]
  28. Demczuk W, Sidhu S, Unemo M, Whiley DM, Allen VG et al. Neisseria gonorrhoeae sequence typing for antimicrobial resistance, a novel antimicrobial resistance multilocus typing scheme for tracking global dissemination of N. gonorrhoeae strains. J Clin Microbiol 2017; 55:1454–1468 [View Article] [PubMed]
     [Google Scholar]
  29. Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics 2009; 25:1754–1760 [View Article] [PubMed]
     [Google Scholar]
  30. 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] [PubMed]
     [Google Scholar]
  31. Croucher NJ, Page AJ, Connor TR, Delaney AJ, Keane JA et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res 2015; 43:e15 [View Article] [PubMed]
     [Google Scholar]
  32. 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]
  33. Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander J. Fast hierarchical Bayesian analysis of population structure. Nucleic Acids Res 2019; 47:5539–5549 [View Article] [PubMed]
     [Google Scholar]
  34. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article] [PubMed]
     [Google Scholar]
  35. Yu G, Smith DK, Zhu H, Guan Y, Tsan-Yuk Lam T. GGTREE: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol 2017; 8:28–36
     [Google Scholar]
  36. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 2013; 30:772–780 [View Article] [PubMed]
     [Google Scholar]
  37. Chaguza C, Tonkin-Hill G, Lo SW, Hadfield J, Croucher NJ et al. RCandy: an R package for visualizing homologous recombinations in bacterial genomes. Bioinformatics 2022; 38:1450–1451 [View Article] [PubMed]
     [Google Scholar]
  38. 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]
  39. Unemo M, Dillon J-AR. Review and international recommendation of methods for typing neisseria gonorrhoeae isolates and their implications for improved knowledge of gonococcal epidemiology, treatment, and biology. Clin Microbiol Rev 2011; 24:447–458 [View Article] [PubMed]
     [Google Scholar]
  40. Sánchez-Busó L, Golparian D, Corander J, Grad YH, Ohnishi M et al. The impact of antimicrobials on gonococcal evolution. Nat Microbiol 2019; 4:1941–1950 [View Article] [PubMed]
     [Google Scholar]
  41. Lyu M, Moseng MA, Reimche JL, Holley CL, Dhulipala V et al. Cryo-EM structures of a gonococcal multidrug efflux pump illuminate a mechanism of drug recognition and resistance. mBio 2020; 11:e00996-20 [View Article] [PubMed]
     [Google Scholar]
  42. Golparian D, Bazzo ML, Golfetto L, Gaspar PC, Schörner MA et al. Genomic epidemiology of Neisseria gonorrhoeae elucidating the gonococcal antimicrobial resistance and lineages/sublineages across Brazil, 2015-16. J Antimicrob Chemother 2020; 75:3163–3172 [View Article] [PubMed]
     [Google Scholar]
  43. Ma KC, Mortimer TD, Hicks AL, Wheeler NE, Sánchez-Busó L et al. Adaptation to the cervical environment is associated with increased antibiotic susceptibility in Neisseria gonorrhoeae. Nat Commun 2020; 11:4126 [View Article] [PubMed]
     [Google Scholar]
  44. Picker MA, Knoblock RJ, Hansen H, Bautista I, Griego R et al. Notes from the field: first case in the United States of Neisseria gonorrhoeae harboring emerging mosaic penA60 allele, conferring reduced susceptibility to Cefixime and Ceftriaxone. MMWR Morb Mortal Wkly Rep 2020; 69:1876–1877 [View Article] [PubMed]
     [Google Scholar]
  45. CDC Sexually Transmitted Disease Surveillance 2018: Gonococcal Isolate Surveillance Project (GISP) Supplement and Profiles Atlanta, GA, USA: Centers for Disease Control and Prevention, U.S. Department of Health and Human Services; 2020
     [Google Scholar]
  46. Joseph SJ, Thomas JC, Schmerer MW, Cartee JC, St Cyr S et al. Global emergence and dissemination of Neisseria gonorrhoeae ST-9363 isolates with reduced susceptibility to Azithromycin. Genome Biol Evol 2022; 14:evab287 [View Article] [PubMed]
     [Google Scholar]
  47. Chitsaz M, Booth L, Blyth MT, O’Mara ML, Brown MH. Multidrug resistance in Neisseria gonorrhoeae: identification of functionally important residues in the MtrD efflux protein. mBio 2019; 10:e02277-19 [View Article] [PubMed]
     [Google Scholar]
  48. Zhang J, van der Veen S. Neisseria gonorrhoeae 23S rRNA A2059G mutation is the only determinant necessary for high-level azithromycin resistance and improves in vivo biological fitness. J Antimicrob Chemother 2019; 74:407–415 [View Article] [PubMed]
     [Google Scholar]
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Genomic analysis of 1710 surveillance-based Neisseria gonorrhoeae isolates from the USA in 2019 identifies predominant strain types and chromosomal antimicrobial-resistance determinants
M Gen 9, 001006 (2023); https://doi.org/10.1099/mgen.0.001006
/content/journal/mgen/10.1099/mgen.0.001006
/content/journal/mgen/10.1099/mgen.0.001006
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