Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

CanB is a metabolic mediator of antibiotic resistance in Neisseria gonorrhoeae

Nature Microbiology volume 8, pages 28–39 (2023)Cite this article

Subjects

Abstract

The evolution of the obligate human pathogen Neisseria gonorrhoeae has been shaped by selective pressures from diverse host niche environments and antibiotics. The varying prevalence of antibiotic resistance across N. gonorrhoeae lineages suggests that underlying metabolic differences may influence the likelihood of acquisition of specific resistance mutations. We hypothesized that the requirement for supplemental CO2, present in approximately half of isolates, reflects one such example of metabolic variation. Here, using a genome-wide association study and experimental investigations, we show that CO2 dependence is attributable to a single substitution in a β-carbonic anhydrase, CanB. CanB19E is necessary and sufficient for growth in the absence of CO2, and the hypomorphic CanB19G variant confers CO2 dependence. Furthermore, ciprofloxacin resistance is correlated with CanB19G in clinical isolates, and the presence of CanB19G increases the likelihood of acquisition of ciprofloxacin resistance. Together, our results suggest that metabolic variation has affected the acquisition of fluoroquinolone resistance.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: A SNP in ngo2079, encoding a β-carbonic anhydrase, is necessary and sufficient to explain the dependence on supplemental CO2 in N. gonorrhoeae.
Fig. 2: The 19 G variant of CanB is a functional hypomorph.
Fig. 3: The CanB19G variant is associated with ciprofloxacin resistance.
Fig. 4: CanB19G provides a fitness advantage in the context of gyrase mutations.

Similar content being viewed by others

Data availability

The data sets generated during and/or analysed in this study can be found in the source data associated with this work. RNA-seq reads are available publicly at SRA Bioproject PRJNA869861. The NCCP11945 genome is accessible via RefSeq accession NC_011035.1. Genomic data, metadata and accession numbers are publicly available in previously published work69. Source data are provided with this paper.

Code availability

Code used in this study has been published69.

References

  1. Rowley, J. et al. Chlamydia, gonorrhoea, trichomoniasis and syphilis: global prevalence and incidence estimates, 2016. Bull. World Health Organ. 97, 548–562P (2019).

    Article  Google Scholar 

  2. Marazzo, J. M. & Apicella, M. A. in Principles and Practice of Infectious Disease (eds. Bennett, J. E. et al.) Ch. 214 (Saunders, 2015).

  3. Ma, K. C. et al. Adaptation to the cervical environment is associated with increased antibiotic susceptibility in Neisseria gonorrhoeae. Nat. Commun. 11, 4126 (2020).

    Article  CAS  Google Scholar 

  4. Lewis, L. A. & Ram, S. Complement interactions with the pathogenic Neisseriae: clinical features, deficiency states, and evasion mechanisms. FEBS Lett. 594, 2670–2694 (2020).

    Article  CAS  Google Scholar 

  5. Golparian, D. et al. Genomic evolution of Neisseria gonorrhoeae since the preantibiotic era (1928-2013): antimicrobial use/misuse selects for resistance and drives evolution. BMC Genomics 21, 116 (2020).

    Article  CAS  Google Scholar 

  6. Gransden, W. R., Warren, C. A., Phillips, I., Hodges, M. & Barlow, D. Decreased susceptibility of Neisseria gonorrhoeae to ciprofloxacin. Lancet (Lond., Engl.) 335, 51 (1990).

    Article  CAS  Google Scholar 

  7. Unemo, M. & Shafer, W. M. Antimicrobial resistance in Neisseria gonorrhoeae in the 21st century: past, evolution, and future. Clin. Microbiol. Rev. 27, 587–613 (2014).

    Article  Google Scholar 

  8. Sexually Transmitted Disease Surveillance – 2020 (CDC, 2020).

  9. WHO Gonococcal AMR Surveillance Programme. WHO https://www.who.int/data/gho/data/themes/topics/who-gonococcal-amr-surveillance-programme-who-gasp (2022).

  10. Rubin, D. H. F., Ross, J. D. C. & Grad, Y. H. The frontiers of addressing antibiotic resistance in Neisseria gonorrhoeae. Transl. Res.https://doi.org/10.1016/j.trsl.2020.02.002 (2020).

    Article  Google Scholar 

  11. Ito, M. et al. Emergence and spread of Neisseria gonorrhoeae clinical isolates harboring mosaic-like structure of penicillin-binding protein 2 in Central Japan. Antimicrobial Agents Chemother. 49, 137–143 (2005).

    Article  CAS  Google Scholar 

  12. Sánchez-Busó, L. et al. The impact of antimicrobials on gonococcal evolution. Nat. Microbiol. 4, 1941–1950 (2019).

    Article  Google Scholar 

  13. Mortimer, T. D. et al. The distribution and spread of susceptible and resistant Neisseria gonorrhoeae across demographic groups in a major metropolitan center. Clin. Infect. Dis.: Off. Publ. Infect. Dis. Soc. Am. 73, e3146–e3155 (2021).

    Article  CAS  Google Scholar 

  14. Williamson, D. A. et al. Bridging of Neisseria gonorrhoeae lineages across sexual networks in the HIV pre-exposure prophylaxis era. Nat. Commun. 10, 3988 (2019).

    Article  Google Scholar 

  15. Lopatkin, A. J. et al. Clinically relevant mutations in core metabolic genes confer antibiotic resistance. Sci. (N. Y., N. Y.) 371, eaba0862 (2021).

    Article  CAS  Google Scholar 

  16. Pinheiro, F., Warsi, O., Andersson, D. I. & Lässig, M. Metabolic fitness landscapes predict the evolution of antibiotic resistance. Nat. Ecol. Evol. 5, 677–687 (2021).

    Article  Google Scholar 

  17. Spence, J. M., Wright, L. & Clark, V. L. Laboratory maintenance of Neisseria gonorrhoeae. Curr. Protoc. Microbiol. 4, Unit 4A.1 (2008); https://doi.org/10.1002/9780471729259.mc04a01s8

  18. Platt, D. J. Carbon dioxide requirement of Neisseria gonorrhoeae growing on a solid medium. J. Clin. Microbiol 4, 129–132 (1976).

    Article  CAS  Google Scholar 

  19. Huang, S. et al. Crystal structure of carbonic anhydrase from Neisseria gonorrhoeae and its complex with the inhibitor acetazolamide. J. Mol. Biol. 283, 301–310 (1998).

    Article  CAS  Google Scholar 

  20. Elleby, B., Chirica, L. C., Tu, C., Zeppezauer, M. & Lindskog, S. Characterization of carbonic anhydrase from Neisseria gonorrhoeae. Eur. J. Biochem 268, 1613–1619 (2001).

    Article  CAS  Google Scholar 

  21. Hewitt, C. S. et al. Structure-activity relationship studies of acetazolamide-based carbonic anhydrase inhibitors with activity against Neisseria gonorrhoeae. ACS Infect. Dis. 7, 1969–1984 (2021).

    Article  CAS  Google Scholar 

  22. Remmele, C. W. et al. Transcriptional landscape and essential genes of Neisseria gonorrhoeae. Nucleic Acid Res. 42, 10579–10595 (2014).

    Article  CAS  Google Scholar 

  23. Merlin, C., Masters, M., McAteer, S. & Coulson, A. Why is carbonic anhydrase essential to Escherichia coli? J. Bacteriol. 185, 6415–6424 (2003).

    Article  CAS  Google Scholar 

  24. Teufel, F. et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat. Biotechnol. https://doi.org/10.1038/s41587-021-01156-3 (2022).

    Article  Google Scholar 

  25. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article  CAS  Google Scholar 

  26. Burghout, P. et al. A single amino acid substitution in the MurF UDP-MurNAc-pentapeptide synthetase renders Streptococcus pneumoniae dependent on CO2 and temperature. Mol. Microbiol. 89, 494–506 (2013).

    Article  CAS  Google Scholar 

  27. Dillard, J. P. Genetic manipulation of Neisseria gonorrhoeae. Curr. Protoc. Microbiol. 23, Unit 4A.2 (2011); https://doi.org/10.1002/9780471729259.mc04a02s23

  28. Tuttle, D. M. & Scherp, H. W. Studies on the carbon dioxide requirement of Neisseria meningitidis. J. Bacteriol. 64, 171–182 (1952).

    Article  CAS  Google Scholar 

  29. Fan, S. H. et al. MpsAB is important for Staphylococcus aureus virulence and growth at atmospheric CO(2) levels. Nat. Commun. 10, 3627 (2019).

    Article  Google Scholar 

  30. Linhares, I. M., Summers, P. R., Larsen, B., Giraldo, P. C. & Witkin, S. S. Contemporary perspectives on vaginal pH and lactobacilli. Am. J. Obstet. Gynecol. 204, 120.e121–125 (2011).

    Article  Google Scholar 

  31. Muir, A. et al. Construction of a complete set of Neisseria meningitidis mutants and its use for the phenotypic profiling of this human pathogen. Nat. Commun. 11, 5541 (2020).

    Article  CAS  Google Scholar 

  32. Kampmeier, R. H. Introduction of sulfonamide therapy for gonorrhea. Sex. Trans. Dis. 10, 81–84 (1983).

    Article  CAS  Google Scholar 

  33. Zampieri, M. et al. Metabolic constraints on the evolution of antibiotic resistance. Mol. Syst. Biol. 13, 917 (2017).

    Article  Google Scholar 

  34. Yao, J., Bruhn, D. F., Frank, M. W., Lee, R. E. & Rock, C. O. Activation of exogenous fatty acids to acyl-acyl carrier protein cannot bypass FabI inhibition in Neisseria. J. Biol. Chem. 291, 171–181 (2016).

    Article  CAS  Google Scholar 

  35. Kitzenberg, D. A. et al. Adenosine awakens metabolism to enhance growth-independent killing of tolerant and persister bacteria across multiple classes of antibiotics. mBio 13, e0048022 (2022).

    Article  Google Scholar 

  36. Firestine, S. M., Poon, S. W., Mueller, E. J., Stubbe, J. & Davisson, V. J. Reactions catalyzed by 5-aminoimidazole ribonucleotide carboxylases from Escherichia coli and Gallus gallus: a case for divergent catalytic mechanisms. Biochem. 33, 11927–11934 (1994).

    Article  CAS  Google Scholar 

  37. Andersson, D. I. & Hughes, D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nat. Rev. Microbiol. 8, 260–271 (2010).

    Article  CAS  Google Scholar 

  38. MacLean, R. C. & San Millan, A. The evolution of antibiotic resistance. Sci. (N. Y., N. Y.) 365, 1082–1083 (2019).

    Article  CAS  Google Scholar 

  39. Sousa, A., Magalhães, S. & Gordo, I. Cost of antibiotic resistance and the geometry of adaptation. Mol. Biol. Evol. 29, 1417–1428 (2012).

    Article  CAS  Google Scholar 

  40. Sommer, M. O. A., Munck, C., Toft-Kehler, R. V. & Andersson, D. I. Prediction of antibiotic resistance: time for a new preclinical paradigm? Nat. Rev. Microbiol. 15, 689–696 (2017).

    Article  CAS  Google Scholar 

  41. Vincent, L. R. et al. In vivo-selected compensatory mutations restore the fitness cost of mosaic pena alleles that confer ceftriaxone resistance in Neisseria gonorrhoeae. mBio 9, e01905–e01917 (2018).

    Article  CAS  Google Scholar 

  42. Kohler, P. L., Hamilton, H. L., Cloud-Hansen, K. & Dillard, J. P. AtlA functions as a peptidoglycan lytic transglycosylase in the Neisseria gonorrhoeae type IV secretion system. J. Bacteriol. 189, 5421–5428 (2007).

    Article  CAS  Google Scholar 

  43. Ramsey, M. E., Hackett, K. T., Kotha, C. & Dillard, J. P. New complementation constructs for inducible and constitutive gene expression in Neisseria gonorrhoeae and Neisseria meningitidis. Appl. Environ. Microbiol 78, 3068–3078 (2012).

    Article  CAS  Google Scholar 

  44. Norrander, J., Kempe, T. & Messing, J. Construction of improved M13 vectors using oligodeoxynucleotide-directed mutagenesis. Gene 26, 101–106 (1983).

    Article  CAS  Google Scholar 

  45. Edwards, R. A., Keller, L. H. & Schifferli, D. M. Improved allelic exchange vectors and their use to analyze 987P fimbria gene expression. Gene 207, 149–157 (1998).

    Article  CAS  Google Scholar 

  46. Maness, M. J. & Sparling, P. F. Multiple antibiotic resistance due to a single mutation in Neisseria gonorrhoeae. J. Infect. Dis. 128, 321–330 (1973).

    Article  CAS  Google Scholar 

  47. Cohen, M. S. et al. Human experimentation with Neisseria gonorrhoeae: rationale, methods, and implications for the biology of infection and vaccine development. J. Infect. Dis. 169, 532–537 (1994).

    Article  CAS  Google Scholar 

  48. Faruki, H. & Sparling, P. F. Genetics of resistance in a non-beta-lactamase-producing gonococcus with relatively high-level penicillin resistance. Antimicrobial. Agents. Chemother. 30, 856–860 (1986).

    Article  CAS  Google Scholar 

  49. Johnson, S. R., Steiner, B. M. & Perkins, G. H. Cloning and characterization of the catalase gene of Neisseria gonorrhoeae: use of the gonococcus as a host organism for recombinant DNA. Infect. Immun. 64, 2627–2634 (1996).

    Article  CAS  Google Scholar 

  50. Guyer, M. S., Reed, R. R., Steitz, J. A. & Low, K. B. Identification of a sex-factor-affinity site in E. coli as gamma delta. Cold Spring Harb. Symp. Quant. Biol. 45 Pt 1, 135–140 (1981).

    Article  CAS  Google Scholar 

  51. Palace, S. G. et al. RNA polymerase mutations cause cephalosporin resistance in clinical Neisseria gonorrhoeae isolates. eLife 9, e51407 (2020).

    Article  CAS  Google Scholar 

  52. Kellogg, D. S. Jr., Peacock, W. L. Jr., Deacon, W. E., Brown, L. & Pirkle, D. I. Neisseria gonorrhoeae. I. virulence genetically linked to cloncal variation. J. Bacteriol. 85, 1274–1279 (1963).

    Article  Google Scholar 

  53. Heng, L. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at arXiv.1303.3997 (2013).

  54. García-Alcalde, F. et al. Qualimap: evaluating next-generation sequencing alignment data. Bioinformatics 28, 2678–2679 (2012).

    Article  Google Scholar 

  55. Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).

    Article  Google Scholar 

  56. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    Article  CAS  Google Scholar 

  57. Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

    Article  CAS  Google Scholar 

  58. Page, A. J. et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 31, 3691–3693 (2015).

    Article  CAS  Google Scholar 

  59. Thorpe, H. A., Bayliss, S. C., Sheppard, S. K. & Feil, E. J. Piggy: a rapid, large-scale pan-genome analysis tool for intergenic regions in bacteria. Gigascience 7, 1–11 (2018).

    Article  Google Scholar 

  60. Croucher, N. J. et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 43, e15 (2015).

    Article  Google Scholar 

  61. Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–w296 (2021).

    Article  CAS  Google Scholar 

  62. Lees, J. A., Galardini, M., Bentley, S. D., Weiser, J. N. & Corander, J. pyseer: a comprehensive tool for microbial pangenome-wide association studies. Bioinformatics 34, 4310–4312 (2018).

    Article  CAS  Google Scholar 

  63. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  64. Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Article  CAS  Google Scholar 

  65. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Article  CAS  Google Scholar 

  66. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  67. Stein, D. C., Danaher, R. J. & Cook, T. M. Characterization of a gyrB mutation responsible for low-level nalidixic acid resistance in Neisseria gonorrhoeae. Antimicrobial Agents Chemother. 35, 622–626 (1991).

    Article  CAS  Google Scholar 

  68. Bushnell, B., Rood, J. & Singer, E. BBMerge – accurate paired shotgun read merging via overlap. PLoS ONE 12, e0185056 (2017).

    Article  Google Scholar 

  69. Ma, K. C. et al. Increased antibiotic susceptibility in Neisseria gonorrhoeae through adaptation to the cervical environment. Preprint at bioRxiv https://doi.org/10.1101/2020.01.07.896696 (2020).

  70. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    Article  CAS  Google Scholar 

  71. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).

    Article  CAS  Google Scholar 

  72. Wade, J. J. & Graver, M. A. A fully defined, clear and protein-free liquid medium permitting dense growth of Neisseria gonorrhoeae from very low inocula. FEMS Microbiol. Lett. 273, 35–37 (2007).

    Article  CAS  Google Scholar 

  73. Mazoyer, A., Drouilhet, R., Despréaux, S. & Ycart, B. flan: an R package for inference on mutation models. R J. 9, 334–351 (2017).

    Article  Google Scholar 

Download references

Acknowledgments

We thank the members of the Grad Laboratory and the Waldor Laboratory for their invaluable feedback; the members of the gonococcal subgroup, particularly A. Bandekar, for their invaluable contributions; S. Palace for her thoughts on experimental design; and the Microbial Genome Sequencing Center (https://www.migscenter.com/) and SeqCenter (https://www.seqcenter.com/) for their work on sequencing strains. This work was supported by grants NIH R01 AI132606 and R01 AI153521 and by the Smith Family Foundation Odyssey award (Y.H.G.) and R01 AI 042347-24 (M.K.W.). Authors are further funded by grants NIH F30 AI160911-01 (D.H.F.R.), NIH T32 GM007753 (D.H.F.R.), NIH F31 AI156949-01 (K.H.) and NIH T32 AI132120-01.

Author information

Authors and Affiliations

  1. Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Daniel H. F. Rubin, Kevin C. Ma, Kathleen A. Westervelt, Matthew K. Waldor & Yonatan H. Grad

  2. Division of Infectious Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Karthik Hullahalli, Matthew K. Waldor & Yonatan H. Grad

  3. Department of Microbiology, Harvard Medical School, Boston, MA, USA

    Karthik Hullahalli & Matthew K. Waldor

Authors
  1. Daniel H. F. Rubin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin C. Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kathleen A. Westervelt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Karthik Hullahalli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matthew K. Waldor
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yonatan H. Grad
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.H.F.R. and K.C.M. performed the GWAS and statistical analyses. D.H.F.R. and K.A.W. performed the anaerobic experiments. D.H.F.R. and K.H. performed the macrophage experiments. D.H.F.R. performed the remainder of the experimental work. All authors (D.H.F.R., K.C.M., K.A.W., K.H., M.K.W. and Y.H.G.) contributed to data interpretation. Y.H.G. supervised and managed the study. D.H.F.R. and Y.H.G. wrote the manuscript. All authors reviewed and edited the final manuscript. All authors were responsible for the decision to submit for publication.

Corresponding author

Correspondence to Yonatan H. Grad.

Ethics declarations

Competing interests

Y.H.G. is on the scientific advisory board of Day Zero Diagnostics and consulted for GlaxoSmithKline. Y.H.G. has received funding from Merck and Pfizer. None of these competing interests has a bearing on this project. The other authors declare no competing interests.

Peer review

Peer review information

Nature Microbiology thanks Jukka Corander, Zeynep Baharoglu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Undirected genetic approaches identify a variant of CanB as causative for CO2-dependence.

(a) Schematic of undirected transformation of FA19 (parental CanB19G) to identify causative factors for CO2-dependence. (b) Plating efficiency in the presence and absence of CO2 following undirected transformation of gDNA from N. gonorrhoeae strain FA6140 into the N. gonorrhoeae lab strain FA19 (N = 10, 10, 9 from left to right from two independent experiments, error bars represent SEM). Significance (from left to right, p = 0.00018, p = 0.00028) determined by two-sided Mann-Whitney U test. (c) Putative reaction catalyzed by NGO2079/CanB and downstream metabolic products. (d) SNPs present in whole-genome sequencing of two transformants in (b). Arrow indicates the SNP identified in Fig. 1. (e) (Top) Alphafold predicted homodimeric structures of the CanB19E variant (teal) and the CanB19G variant (green). (Bottom) Magnified Alphafold predicted structures overlaying the glutamate (maroon) and glycine (red) at position 19. (f) Proportion of sequenced isolates by year with the CanB19G variant. *p < 0.05, **p < 0.01, ***p < 0.001. Figure created with BioRender.com.

Source data

Extended Data Fig. 2 The CanB19E variant has an advantage in the absence of CO2.

(a) Plating efficiency at different CO2 concentrations for N. gonorrhoeae strains 28BL (parental CanB19E) and FA19 (parental CanB19G) with isogenic CanB mutants (N = 6 for 0.1% CO2, N = 3 for air, from two independent experiments, error bars represent SEM). (b) Competition experiment in the presence of CO2 between FA19 CanB19G and FA19 CanBE19G with (left) the FA19 CanB19G strain kanamycin-labeled and (right) the FA19 CanBE19G kanamycin-labeled. The proportion of colony forming units (CFUs) that are kanamycin resistant is graphed against time (N = 3, representative of two independent experiments, error bars represent SEM). (c) Similar to (b), timecourse of competition between isogenic CanB FA19 strains in the presence of media supplementation and the absence of supplemental CO2 (N = 3, representative of two independent experiments, error bars represent SEM). (d) As in (c), competition between unlabeled FA19 CanBG19E and kanamycin-labeled FA19 CanB19G with selected metabolite supplementation assayed at 16 hours in the absence of supplemental CO2 (N = 6, from two independent experiments, error bars represent SEM). (e) Western blot of E. coli MG1655Δcan complemented with IPTG-inducible CanB variants C-terminally FLAG-tagged with G6PD as loading control (representative of two independent experiments).

Source data

Extended Data Fig. 3 The 19E variant of NGO2079 is not advantaged at moderately low pH or within macrophages.

The 19E variant of NGO2079 is not advantaged at moderately low pH or within macrophages. (a) Gentamicin intracellular protection assay in RAW 264.7 macrophages as measured by CFUs (N = 3/timepoint, representative of two independent experiments, error bars represent SEM). (b) Competition experiment as in Extended Data Fig. 2b in pH-adjusted Graver-Wade media (N = 3, error bars represent SEM).

Source data

Extended Data Fig. 4 CanB19E and CanB19G isogenic pairs have similar MICs.

(a) MICs for sulfamethoxazole, trimethoprim, and trimethoprim/sulfamethoxazole for the FA19 and 28BL pairs isogenic CanB variants. (b) Sulfamethoxazole susceptibility of MG1655Δcan complemented with isogenic CanB variants and induced with IPTG. (c) MICs for clinically relevant antibiotics for FA19 CanB19G and FA19 CanBE19G as determined by E-test and agar dilution plating. (d) gyrA mutations for spontaneous ciprofloxacin escapees or clean mutants of FA19 CanB19G and FA19 CanB19E, along with associated ciprofloxacin MIC.

Source data

Extended Data Fig. 5 Loss of CanB does not appear to confer a loss of natural competence.

Loss of CanB does not appear to confer a loss of natural competence. (a) Plating efficiency in the presence and absence of CO2 for a knockout of CanB in the N. gonorrhoeae lab strain FA1090 (N = 6, from two independent experiments, error bars represent SEM). Significance (p = 0.0006) by two-sided Mann-Whitney U. (b) Natural competence of strains of N. gonorrhoeae as measured by uptake of a nalidixic acid resistance-conferring integrating plasmid (N = 3, representative of two independent experiments, error bars represent SEM). (c and d) As in (b), natural competence as measured by (c) uptake of KanR-conferring plasmid DR1 and (d) a PCR product containing the allele encoding for GyrA91F/95G (N = 6, representative of two independent experiments, error bars represent SEM). *p < 0.05, **p < 0.01, ***p < 0.001.

Source data

Extended Data Fig. 6 The CanB19G variant is associated with ciprofloxacin resistance across countries and does not lead to a hypermutator phenotype.

(a) Violin plots of drug MICs for ~10,000 N. gonorrhoeae clinical isolates. Black bar represents median, dotted lines represent 25th/75th percentiles. (b) Average log2 of ciprofloxacin MIC in µg/mL by country and by allele of CanB. Weighted average of all datasets is represented by black dots/line. Size of data point represents size of dataset. Error bars represent standard deviation as determined by weighted variance. Significance (p = 0.0120) by unpaired two-sided t-test. (c) Calculated mutation rates of resistance acquisition for to rifampin by fluctuation analysis of isogenic CanB strains. (N = 192, representative of two independent experiments, error bars represent 95% confidence interval). Significance (p = 0.029) by unpaired two-sided t-test (N = 192, representative of two independent experiments, error bars represent SD). (d) Cumulative distribution of mutants in experiments in (c) along with data on the inoculum size and final population size. *p < 0.05, **p < 0.01, ***p < 0.001.

Source data

Extended Data Fig. 7 The CanB19G variant does not affect killing by ciprofloxacin, but CanB19G provides an advantage in the presence of gyrA mutations across multiple gyrA alleles and strain backgrounds.

The CanB19G variant does not affect killing by ciprofloxacin, but CanB19G provides an advantage in the presence of gyrA mutations across multiple gyrA alleles and strain backgrounds. (a) Kill curve of isogenic CanB FA19 at 2x MIC and 32x MIC (N = 3, representative of two independent experiments). (b) Doubling time of replicates in Fig. 3e as determined by linear regression on log-transformed CFU/mL counts from 2–10 hours of growth (N = 12, from two independent experiments, error bars represent SEM). Significance (p = 1.9e-5) by unpaired two-sided t-test. (c) Growth of CanB isogenic isogenic 28BL strains bearing ciprofloxacin resistance-determining GyrA91F/95G (N = 3, representative of two independent experiments). Significance determined by unpaired two-sided t-test. (d) Competition between spontaneously ciprofloxacin resistant isogenic CanB strains (see Extended Data Fig. 2) and susceptible parental strains (N = 3, representative of two independent experiments). (e) Growth curves of CanB isogenic FA19 strains with spontaneous ciprofloxacin resistance-determining gyrA alleles (N = 3, representative of two independent experiments). (f and g) Competition between (f) FA19 CanBG19E and FA19 CanBG19E GyrA91F (N = 6, except UMP and 100 µM Adenosine, N = 4) and (g) FA19 CanB19G and FA19 CanB19G GyrA91F (N = 3) after 16 hours along with media supplementation in liquid GCP-K (representative of two independent experiments, error bars represent SEM). Significance (from left to right, p = 0.0002, p = 5.7e-13, p = 3.86e-5), by one-way ANOVA with Dunnett’s multiple comparisons test. *p < 0.05, **p < 0.01, ***p < 0.001.

Source data

Extended Data Fig. 8 The relationship between CanB19E and CO2-dependence depends on the acyl-ACP synthetase AasN in the PenA34 lineage of N. gonorrhoeae.

(a) Plating efficiency in the absence and presence of supplemental CO2 of clinical N. gonorrhoeae isolate NY0195 following the introduction of mutations in CanB and AasN (N = 6, from two independent experiments, error bars represent SEM). Significance (from left to right, p = 0.00034 p = 0.00028) by two-sided Mann-Whitney U test. (b) Maximum-likelihood tree as in Fig. 1a overlaid with tracks indicating AasN allele and the ceftriaxone resistance determinant mosaic PenA34 allele. *p < 0.05, **p < 0.01, ***p < 0.001.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

RNA-seq DESeq2 results.

Supplementary Table 2

Strains, plasmids and primers in this study.

Source data

Source Data Fig. 1

Statistical source sata.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rubin, D.H.F., Ma, K.C., Westervelt, K.A. et al. CanB is a metabolic mediator of antibiotic resistance in Neisseria gonorrhoeae. Nat Microbiol 8, 28–39 (2023). https://doi.org/10.1038/s41564-022-01282-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-022-01282-x

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology