Genomic Epidemiology of Gonococcal Resistance to Extended-Spectrum Cephalosporins, Macrolides, and Fluoroquinolones in the United States, 2000–2013
Genomic Epidemiology of Gonococcal Resistance to Extended-Spectrum Cephalosporins, Macrolides, and Fluoroquinolones in the United States, 2000-2013
Yonatan H. Grad 0 2
Simon R. Harris 4
Robert D. Kirkcaldy 5
Anna G. Green 6
Debora S. Marks 6
Stephen D. Bentley 3 4
David Trees 5
Marc Lipsitch 1 2
0 Division of Infectious Diseases, Brigham and Women's Hospital and Harvard Medical School
1 Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health
2 Department of Immunology and Infectious Diseases
3 Department of Medicine, University of Cambridge and Addenbrookes Hospital , Cambridge , United Kingdom
4 Wellcome Trust Sanger Institute , Hinxton
5 Centers for Disease Control and Prevention , Atlanta , Georgia
6 Department of Systems Biology, Harvard Medical School , Boston, Massachusetts
Background. Treatment of Neisseria gonorrhoeae infection is empirical and based on population-wide susceptibilities. Increasing antimicrobial resistance underscores the potential importance of rapid diagnostic tests, including sequence-based tests, to guide therapy. However, the usefulness of sequence-based diagnostic tests depends on the prevalence and dynamics of the resistance mechanisms. Methods. We define the prevalence and dynamics of resistance markers to extended-spectrum cephalosporins, macrolides, and fluoroquinolones in 1102 resistant and susceptible clinical N. gonorrhoeae isolates collected from 2000 to 2013 via the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project. Results. Reduced extended-spectrum cephalosporin susceptibility is predominantly clonal and associated with the mosaic penA XXXIV allele and derivatives (sensitivity 98% for cefixime and 91% for ceftriaxone), but alternative resistance mechanisms have sporadically emerged. Reduced azithromycin susceptibility has arisen through multiple mechanisms and shows limited clonal spread; the basis for resistance in 36% of isolates with reduced azithromycin susceptibility is unclear. Quinolone-resistant N. gonorrhoeae has arisen multiple times, with extensive clonal spread. Conclusions. Quinolone-resistant N. gonorrhoeae and reduced cefixime susceptibility appear amenable to development of sequence-based diagnostic tests, whereas the undefined mechanisms of resistance to ceftriaxone and azithromycin underscore the importance of phenotypic surveillance. The identification of multidrug-resistant isolates highlights the need for additional measures to respond to the threat of untreatable gonorrhea.
Previously, we used a population-based genome sequencing
analysis to investigate the genetic basis of reduced susceptibility
to the oral extended-spectrum cephalosporin (ESC) cefixime in
Neisseria gonorrhoeae . That initial study covered a narrow
time window (2009–2010) and a single antimicrobial agent.
Here, we extend our analysis to include 1102 gonococcal isolates
drawn from across the United States and over 14 years (2000–
2013) and resistance to 3 of the most clinically relevant
antimicrobial classes: the ESCs, including cefixime and ceftriaxone;
macrolides, specifically azithromycin; and fluoroquinolones,
specifically ciprofloxacin. We focus on these 3 classes because
the current recommendation for treatment of gonorrhea is
dual therapy with ceftriaxone and azithromycin  and because
advances in development of molecular diagnostic tests may
prompt reconsideration of treatment with fluoroquinolones
[3, 4], which has not been recommended since the population
prevalence of quinolone resistance exceeded 5% .
For each of the antimicrobials—the ESCs, azithromycin, and
ciprofloxacin—several questions pertain: how much do known
resistance mutations explain observed phenotypic resistance?
To what extent does resistance appear de novo versus spread
through clonal expansion of a resistant strain? How many times
has resistance appeared? These questions have implications for
the study of the dynamics of resistance, for the development of
public health surveillance and intervention strategies, and for
the development and use of molecular diagnostic tests that
rely on genotype to predict resistance.
Specimen Collection and Phenotypic Antimicrobial Susceptibility
We obtained isolates of N. gonorrhoeae from the Centers for
Disease Control and Prevention’s Gonococcal Isolate Surveil
lance Project (GISP), with samples collected as described .
Minimum inhibitory concentrations (MICs) were determined
by agar dilution susceptibility testing, with some measurements
confirmed by the Etest. Antimicrobial susceptibility was
interpreted according to Clinical and Laboratory Standards Institute
for ciprofloxacin , and according to Centers for Disease and
Control and Prevention’s guidelines for cefixime, ceftriaxone,
and azithromycin, for which Clinical and Laboratory Standards
Institute resistance criteria have not been established . See the
Supplementary Methods for further details.
DNA Sequencing and Analysis
DNA was prepared from single colonies and sequenced with the
Illumina HiSeq platform according to standard protocols .
Illumina reads were mapped to a reference strain, FA1090
(GenBank accession number AE004969) using BWA MEM .
Single-nucleotide polymorphisms (SNPs) were called (ie, filtered
to determine the working set of SNPs from all candidate sites)
according to previous parameters . Each Illumina read set was
assembled with velvet (version 1.0.12)  and VelvetOptimiser
the Supplementary Methods for further details of analysis of
NG-MAST, recombination, and population structure.
The 1102 isolates include 270 with reduced ESC susceptibility
(ESCRS), 294 AziRS, and 594 quinolone-resistant N.
gonorrhoeae (QRNG); these totals include multidrug-resistant
isolates. The collection spans 2000–2013 and 36 sexually
transmitted diseases (STD) clinics from across the United States
(Supplementary Methods, Supplementary Table 1, and
Supplementary Figure 1).
In the phylogeny, many of the isolates group into clades,
reflected by Bayesian analysis of population structure (BAPS)
clusters and corresponding to antimicrobial susceptibility
patterns (Figure 1A). This clade structure likely reflects the
expansion of resistant lineages. Plotting the cumulative fraction of
total resistant isolates by the number of BAPS clusters reveals
that ESC and ciprofloxacin resistances are primarily
attributable to the expansion of a small number of BAPS groups,
whereas azithromycin resistance is more distributed
throughout the phylogeny (Figure 1B). Numerous isolates on long
terminal branches suggest existence of substantial unsampled
Reduced Susceptibility to the ESCs
The whole-genome phylogeny reveals that the majority of
ESCRS is due to expansion of 2 clades possessing the mosaic
penA XXXIV allele (Figures 1 and 2), previously seen in our
analysis of isolates from 2009 to 2010  and confirming that
this is the predominant penA allele associated with resistance
in the sampled time frame (2005–2013). We additionally
identify sporadic isolates with ESCRS that do not possess the mosaic
penA XXXIV allele (Figure 2 and Supplementary Table 1).
Parsimony reconstruction infers 13 independent acquisitions
(range, 10–16 acquisitions) and 35 losses (range, 32–35 loss)
leading to the 270 ESCRS isolates in this data set.
ESCRS is primarily explained by the presence of the mosaic
penA XXXIV and derivative alleles (Figures 2 and 3), with
98% of isolates with reduced susceptibility to cefixime (MIC
≥0.25 µg/mL) and 91% of isolates with reduced susceptibility
to ceftriaxone (MIC ≥0.125 µg/mL) possessing these alleles
(Supplementary Table 1). A less stringent MIC cutoff suggests
that other pathways may contribute to low-level reduced
cephalosporin susceptibility, as the percentage of isolates possessing
the mosaic penA XXXIV and derivative alleles at a cefixime
MIC of ≥0.125 µg/mL and a ceftriaxone MIC of ≥0.06 µg/mL
decreases to 91% and 76%, respectively (Supplementary
The presence of a mosaic penA XXXIV allele does not confer
resistance equally to cefixime and ceftriaxone (Figure 2C). While
only 1% of isolates with mosaic penA XXXIV alleles have a
cefixime MIC of ≤0.125 µg/mL, 21% of mosaic penA XXXIV allele–
containing isolates have a ceftriaxone MIC of ≤0.03 µg/mL.
Several of the ESCRS isolates, including 2 with cefixime MICs
among the highest observed in this data set (GCGS1095 and
GCGS1014, with MICs of 1 and 0.5 µg/mL, respectively),
share identical penA alleles to those in susceptible isolates
(Figure 2B), indicating the involvement of other loci in some ESCRS
Several other loci have been previously associated with
βlactam resistance, including pilQ, ponA, porB, and
plasmidborne TEM β-lactamases . pilQ mutations can confer ESC
resistance in vitro , but pilQ mutations have not been
associated with ESC resistance in clinical isolates . We observe
several pilQ and ponA alleles that have a high negative predictive
value for resistance (Figure 3). Mutations at amino acid
positions 120 and 121 in the porin-encoding porB have been
associated with β-lactam resistance , but neither the 120K
(Figure 3) nor the 120D/121D genotypes are associated with
reduced ESC susceptibility in this data set (only 2 isolates have the
120D/121D genotypes, and both are ESC susceptible). The 7
ESCRS isolates lacking a mosaic penA do not share a porB allele
or amino acids at positions 120 and 121 (Supplementary
Figure 2), and no porB sites are exclusively shared by these 7
isolates. A TEM β-lactamase is present in 35 isolates, but only 3 of
these are ESCRS (Supplementary Table 1).
Previously, a model based on samples from 2009 to 2010 that
ESCRS circulated primarily among men who have sex with men
(MSM), on the West Coast, with an uncertain number of entries
into the United States . With this larger data set, we observe
that the earliest cluster of mosaic penA XXXIV containing
ESCRS appeared in 2005 in 2 isolates (GCGS0920 and
GCGS0944) from men who have sex with women (MSW), in
Miami and Portland (Supplementary Table 1 and
Supplementary Figure 3), and subsequently circulated in MSW. The
bicoastal appearance and spread of this sublineage of clade 1
among MSW is in contrast with circulation of clade 1 after
2009 predominantly in MSM (n = 146 [69%]) and in the
western United States (n = 147 [69%], comprising clinic sites
Honolulu, Las Vegas, Los Angeles/Orange County, Phoenix,
Portland, San Diego, San Francisco, and Seattle). Further, the
existence of long branches separating several subclades within
clade 1 is consistent with multiple introductions of clade 1
lineages into the United States (Supplementary Figure 3).
While clade 1 includes isolates from 2013, the last clade 2
isolate was observed in 2011 (Supplementary Table 1),
suggesting that this clade no longer circulates in the United States.
Given that isolates from clade 2 were identified in cases from
6 STD clinics (Supplementary Table 1), it seems unlikely that
disappearance of this clade is due solely to entry into dead-end
sex contact networks. Instead, the disappearance may have
resulted from relative lack of fitness in the context of the
increased treatment dose of ceftriaxone from 125 to 250 mg in
2010–2011 [15, 16], as all clade 2 isolates have a ceftriaxone
MIC of ≤0.06 µg/mL.
The 2 ESCRS isolates with the mosaic penA XXXIV that are
not part of larger clades (Figure 2A)—GCGS0099 and
GCGS0926—appear in 2010 and 2012, without evidence of
continued spread. The nonmosaic penA ESCRS (GCGS0870,
GCGS0627, GCGS1029, GCGS1035, GCGS1013, GCGS1095,
and GCGS1014) have appeared sporadically (during 2000 in
Birmingham, during 2003 in Orange County, during 2007 in
Cleveland, during 2007 in Detroit, during 2011 in Baltimore,
during 2012 in Oklahoma City, and during 2012 in Chicago,
respectively), and, other than the closely related isolates of
GCGS1095 and GCGS1014, have no evidence of propagation.
Reduced Susceptibility to Azithromycin
In contrast with ESCRS, reduced azithromycin susceptibility
appears sporadically across the phylogeny (Figure 1), with 75
episodes (range, 69–84 episodes) of acquisition of resistance
through de novo mutation or horizontal gene transfer inferred
by ancestral state reconstruction. Azithromycin resistance has
less clonal expansion (Figure 1B) and evidence of frequent
reversion to susceptibility, with an inferred 42 episodes (range,
33–48 episodes) of loss of resistance.
The 23S ribosomal RNA (rRNA) mutations C2611T (164
isolates with ≥2 mutated 23S rRNA alleles) and A2059G (2
isolates, in which all 4 alleles are mutant) are highly associated with
resistance (Figures 3 and 4), as are interspecies mosaics in the
mtr operon (across both mtrCDE and mtrR; Figures 3, 4, and
Supplementary Figure 4) encoding the Mtr efflux pump. We
observe 7 events of likely interspecies recombination (Figure 4A
and 4B), each of which is associated with acquisition of
azithromycin resistance. This includes a set of 4 isolates from Kansas
City collected in 2000 that possess an mtr mosaic with an mtrR
sequence that matches perfectly to N. meningitidis, with
presence of a Correia element corresponding with a reported
outbreak of AziRS in Missouri in 1999 . The subset of 5
isolates that contain both 23S rRNA C2611T mutations and mtr
locus mosaics have higher MICs (8–16 µg/mL) than those
that contain the mtr locus mosaics alone (1–4 µg/mL).
In contrast, coding and promoter mutations in the mtrR
locus that have been associated with increased MICs to
macrolides  are not associated here with AziRS (Figure 5),
suggesting that genomic background may influence the impact of these
variants on azithromycin resistance. A single nucleotide
promoter variant upstream of the mtrC start codon that is
associated with resistance  was not observed in this data set.
Mutations in ribosomal proteins L4 (rplD) and L22 (rplV)
yield macrolide resistance [19–21] in other bacteria but have
not been previously reported in gonococcus. We identify 2
AziRS isolates (GCGS0838 and GCGS1026; MIC = 16 µg/mL)
that have 6 and 4 amino acid tandem duplications, respectively,
in the 3′ end of rplV and are predicted to interact with the
azithromycin binding site, similar to resistance-conferring
insertions described in other organisms (Supplementary Figure 5)
[20, 21]. We identify isolates with mutations at G68 (n = 9)
and G70 (n = 57) in an rplD region previously associated with
macrolide resistance. However, only 58% of isolates with either
mutation are AziRS, and these have MICs at or just above the
resistance threshold, with the exception of those that
additionally possess 23S rRNA or mtr mosaic variants.
Together, the 23S rRNA mutations, mtr locus mosaics, and
rplV variants account for 188 of 294 isolates (64%) with reduced
azithromycin susceptibility (Figure 4C). The mechanisms
accounting for AziRS in the remaining 36% are unclear. None of
the other genes known or postulated to be involved in resistance
that we evaluated (including mtrA, norM, or macA/B [11, 22])
were highly associated with azithromycin resistance
(Supplementary Table 2), and we did not observe ermB, ermC, or
ermF in our data set. Notably, unexplained resistance appears
primarily in isolates with low-level resistance, with 81% of
isolates with unexplained resistance having an MIC at the
threshold (Figure 4C).
Intriguingly, 17 of 19 isolates (89%) containing the rplD 70
mutation, with porB 121D and macA 99N but lacking known
23S rRNA or mosaic mtr variants, have reduced azithromycin
susceptibility. We hypothesize that these mutations may reflect
multiple mechanisms that additively contribute to elevated
MICs. While experiments would be required to test this
hypothesis, its plausibility is enhanced by the fact that this resistant
phenotype with the trio of mutations described appears in 2
separate clonal groups.
The temporal and geographic patterns together with the
phylogeny suggest that the azithromycin resistance variants appear
frequently, although only some propagate enough to leave
multiple descendants in our data set (Figure 4A). The mtr mosaics,
for example, represent 7 distinct recombination episodes
(Supplementary Figure 3), each present for 1–2 years in our
sampling period, with cluster 3 the only cluster present in 2013
(Supplementary Table 3). Only the largest cluster has spread
beyond 2 cities, with expansion in Miami, Philadelphia, and
Dallas. The C2611T 23S rRNA variants have expanded clonally but
also show multiple instances of no detectable propagation.
Phylogenetic analysis and ancestral state reconstruction indicate
that quinolone resistance has emerged 11 times (range, 10–12
times) through de novo mutation or recombination (Figures 1
and 5). The few instances of inferred loss of resistance (7; range,
5–8 instances) despite the number of QRNG in this data set is
consistent with the observation that most quinolone resistance
mutations are associated with limited, if any, fitness cost .
In N. gonorrhoeae, quinolone resistance has been attributed
to variants in gyrA and parC, including GyrA amino acid
positions 91 and 95 and ParC position 87. Specific amino acid
residues at these sites are highly predictive of resistance phenotype
in our data set (Figure 3). ParC sites 86, 88, and 91 have been
reported as varying in QRNG . In our data set, ParC-86
variant D86N appears only 7 times and S88P only once. E91G
appears 28 times and only in the context of QRNG with ParC-87S;
there is 1 isolate with E91K.
We evaluated the association between haplotypes at the
ParC-87, GyrA-91, and GyrA-95 loci and ciprofloxacin MIC
(Figure 5B). The 3 most common resistant haplotypes are
ParC-97N/GyrA-91F/GyrA-95A (“NFA”; n = 16), ParC-87S/
GyrA-91F/GyrA-95G (“SFG”; n = 40), and
ParC-87R/GyrA91F/GyrA-95G (“RFG”; n = 515). The geometric mean MIC
for SFG is 5.2, whereas for RFG it is 11.9; in contrast, the
NFA haplotype is associated with low-level resistance (MICs
predominantly 1–2 µg/mL; Figure 5B).
Five resistant isolates do not have the characteristic GyrA
or ParC variants (GCGS1019, GCGS0850, GCGS1043,
GCGS0807, and GCGS0641; starred in Figure 5), suggesting
that variants at other loci can also yield quinolone resistance.
The rare appearance of these isolates and their lack of
propagation suggest that they carry a high fitness cost.
Multidrug Resistance and Interactions Among Resistance Mechanisms
Five isolates have reduced susceptibility to the ESCs and to
azithromycin, and 4 of these isolates exceed the MIC cutoffs for
resistance to quinolones (Supplementary Table 1). While
these cases have not come to attention as treatment failures, it
is possible that, with treatment, (1) the bacterial burden was
decreased to the extent that the infections were no longer
symptomatic, (2) the infections were cured despite the MICs, and (3)
there was no ongoing transmission.
The apparent anticorrelation between azithromycin and
ESC resistance in Figure 1 raises the hypothesis that the
mechanism for resistance to azithromycin might impact MICs to
other antibiotics. Therefore, we tested whether resistance to
other drugs was altered in the context of the 23S rRNA
C2611T mutation as the most common mechanism of
azithromycin resistance. To account for varying genomic background,
we performed these tests within BAPS groups; 3 had >10
isolates with the 23S rRNA C2611T mutation (BAPS-4, n = 64;
BAPS-7, n = 41; and BAPS-11, n = 18). In BAPS-4, the MICs
for cefixime, ceftriaxone, and ciprofloxacin (P < .01 for each,
by the Mann–Whitney U test including Bonferroni correction)
and in BAPS-7 the MICs for cefixime and ceftriaxone (P = .008
and P = .02, respectively) were significantly lower in the
presence of the 23S rRNA C2611T mutation; however, in BAPS-7
the ciprofloxacin MIC and in BAPS-11 cefixime, ceftriaxone,
and ciprofloxacin MICs were not significantly different.
These results could result from the sampling strategy or
could represent biological interactions among resistance
Application of genotype-based resistance prediction tools
depends on the prevalence and reliability of the genetic markers
of resistance. Here, we used a retrospective longitudinal
phylogenomic approach to define the distribution of resistance
markers to the 3 most clinically relevant classes of antimicrobials for
treatment of gonococcal infections.
The observation that ESCRS is highly although not exclusively
associated with the mosaic penA XXXIV allele and its
derivatives affirms previous results from data from gonococcal
populations in the United States and Canada [1, 25]. We note several
additional findings. First, resistance mechanisms that yield
ESCRS in the absence of a mosaic penA XXXIV–type allele
have appeared sporadically (Figure 2B). The mechanism for
resistance in these isolates is not clear; they do not share penA or
porB alleles (Figure 2B and Supplementary Figure 2). Second,
we do not observe mosaic penA alleles other than XXXIV and
derivatives that are associated with ESC resistance in this
population (Figure 2B). Third, in contrast with cefixime, resistance
to ceftriaxone appears to involve loci in addition to penA,
although these loci remain to be identified (Figure 2C).
ESCRS has spread predominantly through clonal expansion,
with 97% of ESCRS isolates belonging to one of two BAPS
groups and possessing the mosaic penA XXXIV type (Figures 1B
and 2). Of the 7 ESCRS that do not possess a mosaic penA
XXXIV–type allele, 2 appear closely related phylogenetically,
suggesting at least 6 episodes of de novo emergence over the
sampling period (2005–13).
AziRS is associated with multiple mechanisms of resistance.
We identify variants of the ribosome, including known 23S
rRNA mutations (C2611T [n = 163] and A2059G [n = 2];
total, 56% of all isolates with reduced azithromycin
susceptibility) and previously unreported rplV mutations (n = 2 [<1%]).
We also identify interspecies mosaic variants of the efflux
pump–encoding mtr locus (n = 29 [10%]), with 5 isolates
containing both the mosaic mtr locus and C2611T mutations.
Demczuk et al recently found ermB and ermC in 3 AziRS isolates
in Canada , but we found neither of these genes. Notably,
many of the mtrR variants reported in the literature to result
in AziRS were not highly associated with resistance in this
data set. As 36% of AziRS isolates did not possess alleles that
were highly associated with resistance, it is possible that these
isolates contain as yet undefined mechanisms of resistance or
combinations of loci that additively yield resistance. That
multiple loci can combine to yield higher levels of resistance is
suggested by MICs for isolates that possess both mtr mosaic alleles
and 23S rRNA mutations as compared to MICs of the isolates
containing the mtr mosaics alone. Further, co-occurring alleles
of rplD, porB, and macA that are associated with reduced
azithromycin susceptibility suggest another possible set of loci
that may combinatorially influence azithromycin MIC.
AziRS appears sporadically more often than the other
phenotypes we studied, perhaps indicating that treatment readily selects
for AziRS variants. Likewise, the limited clonal spread as
compared to ESCRS and quinolone resistance (Figure 1), as well as
the inferred frequent return to susceptibility, implies that
azithromycin resistance often incurs significant fitness costs. However,
recent reports of an outbreak of azithromycin-resistant
gonorrhea in England  and an increase in azithromycin resistance
in the United States  raise concern that these fitness costs may
be mitigated in some genomic backgrounds.
Quinolone resistance in this data set is primarily clonal and is
highly correlated with gyrA and parC mutations. Haplotypes of
key GyrA and ParC amino acids yield distinct MIC
distributions, suggesting that genotype may be used in predicting the
extent of resistance. While the vast majority of QRNG possess
materials are not copyedited and are the sole responsibility of the author, so
questions or comments should be addressed to the author.
Acknowledgments. We thank A. Jeanine McLean, John Cartee, and
Sean Lucking for laboratory support.
Disclaimer. The findings and conclusions in this report are those of the
authors and do not necessarily represent the official position of the Centers
for Disease Control and Prevention (CDC), the National Institute of General
Medical Sciences, or the National Institutes of Health (NIH).
Financial support. This work was supported by the Wellcome Trust
(grant 098051 to the Wellcome Trust Sanger Institute), the NIH (grant
K08-AI104767 to Y. H. G. and grant GM106303 to D. S. M.), the National
Institute of General Medical Sciences (cooperative agreement
U54GM088558 to M. L.), the National Science Foundation (graduate
research fellowship DGE1144152 to A. G. G.), and the CDC and the CDC’s
Office of Advanced Molecular Detection (support AMD-18 to D. L. T. and
R. D. K.).
Potential conflicts of interest. All authors: No reported conflicts. All
authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the
content of the manuscript have been disclosed.
gyrA or parC mutations associated with resistance (589 of 594
[>99%]), 5 QRNG do not; the mechanisms of resistance in these
instances are unclear.
There are several limitations to this study. As GISP isolates
are collected only from men with gonococcal urethritis, it is
unclear to what extent the specimens studied here are
representative of those from other mucosal sites of infection. Although
GISP clinics are distributed across the United States, their
representativeness of all cases of gonorrhea in the United States is
unclear. The selection for this study of isolates on the basis of
their antimicrobial susceptibility profile may skew prevalence
estimates, particularly as susceptible comparators for any
given drug were usually available for study because they were
resistant to another antimicrobial; pan-susceptible isolates are
not typically frozen for storage following isolation in GISP.
Additionally, susceptibility testing has a margin of error of ±1
dilution, although the very high positive predictive values for
genetic markers for resistance to each of the antibiotics suggest
a limited impact of MIC error.
The identification of isolates with reduced susceptibility to
both azithromycin and the ESCs underscores the imminent
risk of treatment-resistant infections and the importance of
novel strategies to diagnose and treat gonococcal infections,
including use of rapid sequence-based assays to determine
antibiotic susceptibility and allow for reintroduction of quinolones and
other antibiotics into practice guidelines. The observed diversity
and change over time in the mechanisms of resistance, with some
remaining to be described, also emphasize the critical need for
continued surveillance of phenotypic antibiotic resistance.
Supplementary materials are available at http://jid.oxfordjournals.org.
Consisting of data provided by the author to benefit the reader, the posted
1. Grad YH , Kirkcaldy RD , Trees D , et al. Genomic epidemiology of Neisseria gonorrhoeae with reduced susceptibility to cefixime in the USA: a retrospective observational study . Lancet Infect Dis 2014 ; 14 : 220 - 6 .
2. Workowski KA , Bolan GA , Centers for Disease Control and Prevention. Sexually transmitted diseases treatment guidelines , 2015 . MMWR Recomm Rep 2015 ; 64 : 1 - 137 .
3. Siedner MJ , Pandori M , Castro L , et al. Real-time PCR assay for detection of quinolone-resistant Neisseria gonorrhoeae in urine samples . J Clin Microbiol 2007 ; 45 : 1250 - 4 .
4. Hemarajata P , Yang S , Soge OO , Humphries RM , Klausner JD. Performance and verification of a real-time PCR assay targeting the gyrA gene for prediction of ciprofloxacin resistance in Neisseria gonorrhoeae . J Clin Microbiol 2016 ; 54 : 805 - 8 .
5. Update to CDC's sexually transmitted diseases treatment guidelines, 2006: fluoroquinolones no longer recommended for treatment of gonococcal infections . MMWR Morb Mortal Wkly Rep 2007 ; 56 : 332 - 6 .
6. CDC. Gonococcal Isolate Surveillance Project (GISP) protocol . http://www.cdc. gov/std/gisp/gisp-protocol-feb-2015_v3 .pdf. Accessed 10 April 2016 .
7. Clinical Laboratory Standards Institute (CLSI). Performance Standards for Antimicrobial Susceptibility Testing; Twenty-sixth Informational Supplement . CLSI document M100-S26 . CLSI: Wayne, PA, 2016 .
8. Kirkcaldy RD , Harvey A , Papp JR , et al. Neisseria gonorrhoeae antimicrobial susceptibility surveillance - the Gonococcal Isolate Surveillance Project , 27 Sites, United States , 2014 . MMWR Surveill Summ 2016 ; 65 : 1 - 19 .
9. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWAMEM . arXiv 2013 ; 1303 .3997v1.
10. Zerbino DR , Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs . Genome Res 2008 ; 18 : 821 - 9 .
11. Unemo M , Shafer WM . Antimicrobial resistance in Neisseria gonorrhoeae in the 21st century: past, evolution, and future . Clin Microbiol Rev 2014 ; 27 : 587 - 613 .
12. Johnson SR , Grad Y , Ganakammal SR , et al. In vitro selection of Neisseria gonorrhoeae mutants with elevated MIC values and increased resistance to cephalosporins . Antimicrob Agents Chemother 2014 ; 58 : 6986 - 9 .
13. Whiley DM , Jacobsson S , Tapsall JW , Nissen MD , Sloots TP , Unemo M. Alterations of the pilQ gene in Neisseria gonorrhoeae are unlikely contributors to decreased susceptibility to ceftriaxone and cefixime in clinical gonococcal strains . J Antimicrob Chemother 2010 ; 65 : 2543 - 7 .
14. Olesky M , Hobbs M , Nicholas RA . Identification and analysis of amino acid mutations in porin IB that mediate intermediate-level resistance to penicillin and tetracycline in Neisseria gonorrhoeae . Antimicrob Agents Chemother 2002 ; 46 : 2811 - 20 .
15. CDC. Primary Antimicrobial Drugs Used to Treat Gonorrhea Among Participants, Gonococcal Isolate Surveillance Project (GISP) , 1988 - 2014 . http://www. cdc.gov/std/stats14/figures/30.htm. Accessed 22 April 2016 .
16. Workowski KA , Berman S , Centers for Disease Control and Prevention. Sexually transmitted diseases treatment guidelines , 2010 . MMWR Recomm Rep 2010 ; 59 : 1 - 110 .
17. Johnson SR , Sandul AL , Parekh M , Wang SA , Knapp JS , Trees DL . Mutations causing in vitro resistance to azithromycin in Neisseria gonorrhoeae . Int J Antimicrob Agents 2003 ; 21 : 414 - 9 .
18. Ohneck EA , Zalucki YM , Johnson PJ , et al. A novel mechanism of high-level, broad-spectrum antibiotic resistance caused by a single base pair change in Neisseria gonorrhoeae . MBio 2011 ; 2 :pii: e00187 - 11 .
19. Gregory ST , Dahlberg AE . Erythromycin resistance mutations in ribosomal proteins L22 and L4 perturb the higher order structure of 23 S ribosomal RNA . J Mol Biol 1999 ; 289 : 827 - 34 .
20. Franceschi F , Kanyo Z , Sherer EC , Sutcliffe J. Macrolide resistance from the ribosome perspective . Curr Drug Targets Infect Disord 2004 ; 4 : 177 - 91 .
21. Zaman S , Fitzpatrick M , Lindahl L , Zengel J. Novel mutations in ribosomal proteins L4 and L22 that confer erythromycin resistance in Escherichia coli . Mol Microbiol 2007 ; 66 : 1039 - 50 .
22. Golparian D , Shafer WM , Ohnishi M , Unemo M. Importance of multidrug efflux pumps in the antimicrobial resistance property of clinical multidrug-resistant isolates of Neisseria gonorrhoeae . Antimicrob Agents Chemother 2014 ; 58 : 3556 - 9 .
23. Kunz AN , Begum AA , Wu H , et al. Impact of fluoroquinolone resistance mutations on gonococcal fitness and in vivo selection for compensatory mutations . J Infect Dis 2012 ; 205 : 1821 - 9 .
24. Shultz TR , Tapsall JW , White PA. Correlation of in vitro susceptibilities to newer quinolones of naturally occurring quinolone-resistant Neisseria gonorrhoeae strains with changes in GyrA and ParC . Antimicrob Agents Chemother 2001 ; 45 : 734 - 8 .
25. Demczuk W , Lynch T , Martin I , et al. Whole-genome phylogenomic heterogeneity of Neisseria gonorrhoeae isolates with decreased cephalosporin susceptibility collected in Canada between 1989 and 2013 . J Clin Microbiol 2015 ; 53 : 191 - 200 .
26. Demczuk W , Martin I , Peterson S , et al. Genomic epidemiology and molecular resistance mechanisms of azithromycin resistant Neisseria gonorrhoeae in Canada from 1997 to 2014 . J Clin Microbiol 2016 ; 54 : 1304 - 13 .
27. Chisholm SA , Wilson J , Alexander S , et al. An outbreak of high-level azithromycin resistant Neisseria gonorrhoeae in England . Sex Transm Infect 2016 ; 92 : 365 - 7 .