ABSTRACT
Doxycycline targets the 16S rRNA and is widely used for the treatment of sexually transmitted infections. While it is not highly effective at eradicating Mycoplasma genitalium infections, it can reduce organism load. The aim of this study was to investigate the association between single nucleotide polymorphisms (SNPs) in the 16S rRNA gene of M. genitalium and change in organism load. M. genitalium samples were collected from 56 men prior to commencing doxycycline and at a median of 13 of 14 doses. These were sequenced for the 16S rRNA, and the association between 16S rRNA SNPs and change in organism load was determined. 16S rRNA sequences were available for 52/56 (92.9%) M. genitalium-infected men, of which 20 (38.5%) had an undetectable load, 26 (50.0%) had a decrease in M. genitalium load (median change of 105-fold), and 6 (11.5%) had an increase in load (median change of 5-fold). The most common SNPs identified were A742G (10/52 [19.2%]), GG960-961TT/C (7/52 [13.5%]), and C1435T (28/52 [53.8%]) (M. genitalium numbering). None were associated with a change in organism load (P = 0.76, 0.16, and 0.98, respectively). Using pooled published data from 28 isolates, no clear relationship between the SNPs and doxycycline MIC was identified. In conclusion, the low efficacy of doxycycline against M. genitalium does not appear to be due to variation in the 16S rRNA gene.
KEYWORDS: doxycycline, antibiotic resistance, 16S rRNA gene, Mycoplasma genitalium
INTRODUCTION
Mycoplasma genitalium infections are often asymptomatic but can present as nongonococcal urethritis in men and cervicitis and pelvic inflammatory disease in women (1, 2). Due to the absence of a cell wall, only antimicrobial classes that target protein synthesis or DNA replication have efficacy against M. genitalium (3). Current Australian, British, and the U.S. Centers for Disease Control and Prevention M. genitalium treatment guidelines (4–6) recommend presumptive treatment with doxycycline followed by either azithromycin or moxifloxacin, depending on the outcome of resistance testing, as part of resistance-guided sequential therapy (RGT) (7, 8).
In vitro, doxycycline MICs range between ≤0.008 and 2.5 μg/mL, suggesting that some isolates may be highly susceptible (9). However, in vivo, doxycycline is not very effective, with a 7-day regimen eradicating less than 50% of M. genitalium infections (10–14) and a 2-week regimen achieving microbiological cure of less than 60% (15). Despite the low level of microbiological cure, doxycycline can reduce the M. genitalium load, which is likely to facilitate clearance with a second antibiotic (7). This property is exploited in the RGT strategy. Doxycycline has also been trialed in combination therapy with levofloxacin, curing all macrolide-resistant infections in a preliminary analysis (16). Combining doxycycline with either pristinamycin or azithromycin (17–19) did not improve efficacy compared to that of pristinamycin or azithromycin alone (7, 8, 18). The addition of doxycycline to moxifloxacin (19) did not improve cure rates compared to those with moxifloxacin alone (8), but higher levels of fluoroquinolone resistance were present in the study of combination therapy.
Doxycycline belongs to the tetracycline class of antimicrobials, which inhibit protein synthesis by binding to the 16S rRNA molecule of the bacterial ribosome (20). The primary binding site (Tet-1) is formed by specific nucleotide bases in helix 31 (H31) and H34 (Fig. 1), while several secondary binding sites of unknown significance are located elsewhere on the 30S ribosomal subunit (21, 22). Single nucleotide polymorphisms (SNPs) in the 16S rRNA gene have been shown to confer tetracycline resistance in some organisms (23–27); however, this is uncommon (28). More often, the mechanism of resistance to tetracyclines is conferred through tet or otr genes, which encode efflux pumps, ribosomal protection proteins, or tetracycline-modifying enzymes (20). These genes have not been reported for M. genitalium.
FIG 1.
Representation of the 16 rRNA gene. The primary tetracycline binding site (Tet-1) is shaded and is formed by nucleotides 964 to 967 of helix 31 (H31) and nucleotides H31, H34 and H34 (boxed nucleotides). Two regions of interest discussed in this study are indicated. Alignments with sequences from other bacteria are presented. Single nucleotide polymorphisms (SNPs) identified in tetracycline-resistant bacterial isolates (23–27, 29, 30, 39, 46, 47) are highlighted in blue and labeled (Escherichia coli numbering). The three major SNPs observed in this study and those within or near the primary binding site in this study and other M. genitalium studies (36–38) are highlighted in pink and labeled (E. coli numbering). GenBank accession numbers for sequences are as follows: E. coli K-12, NC_000913.3; Mycoplasma genitalium G37, NC_000908.2; Mycoplasma pneumoniae FH, NR_041751.1; Mycoplasma hominis PG21, NR_041881.1; Mycoplasma bovis PG45, NR_102850.2; Propionibacterium acnes, M61903.1; Brachyspira hyodysenteriae, U14930.1; Brachyspira intermedia, NR_102932.1; and Helicobacter pylori 43504, NR_044761.1. The diagram is not drawn to scale.
In other Mycoplasma species, specific mutations in the Tet-1 region of the 16S rRNA gene have been acquired by in vitro selection with tetracyclines (29) or identified in tetracycline-resistant isolates (25, 30). The contribution of SNPs in the 16S rRNA gene to doxycycline resistance in M. genitalium is unknown. In this study, the association between SNPs in the 16S rRNA gene of M. genitalium and change in organism load with doxycycline treatment was investigated.
RESULTS
Sample availability and organism load.
In total, urine samples from 52/56 (92.9%) men were available for analysis (Fig. 2). At a median of 13 doses of doxycycline, 20/52 (38.5%) had an undetectable M. genitalium load, 26/52 (50.0%) experienced a decrease in organism load, and 6/52 (11.5%) experienced an increase in organism load. The median log10 change in organism load with doxycycline was −1.86 (72-fold decrease) (95% confidence interval [CI], −2.23 to −1.23; interquartile range [IQR], −2.61 to −1.02). For the 26 patients with a decrease in organism load, the median reduction was −2.02 (105-fold decrease) (95% CI, −2.37 to −1.42; IQR, −2.75 to −1.20), while for the 6 patients with an increase in organism load, the median increase was 0.73 (5-fold increase) (95% CI, 0.10 to 1.38; IQR, 0.13 to 1.09).
FIG 2.
Summary of sample availability categorized by change in organism load as determined in the original study (7).
16S rRNA gene single nucleotide polymorphisms.
Sequencing was available for 43/52 (82.7%) pretreatment samples and 31/32 (96.9%) treatment samples (i.e., samples taken at a median of 13 of 14 doses). A total of 22/52 (42.3%) patients had both pretreatment and treatment sequences available. The 16S rRNA sequence did not differ between the two samples; thus, pretreatment sequences were used for SNP identification unless unavailable, in which case the treatment sequence was used (nine samples). M. genitalium numbering is used unless stated otherwise.
SNPs within the 16S rRNA gene observed in this study are shown in Table 1. The most common SNPs were C1435T (28/52 [53.8%]), A742G (10/52 [19.2%]), and GG960-961TT/C (7/52 [13.5%]). Some SNPs occurred together, mostly in conjunction with one of the three main SNPs, including one sample with both GG960-961TT and C1435T. The six patients with an increase in organism load had the following mutations: C452T (in conjunction with C1435T), T1147C, C1435T, and GG960-961TT.
TABLE 1.
Summary of 16S rRNA gene SNPs identified in Mycoplasma genitalium from 52 patients from Melbourne, Australia, from 2016 to 2017
| 16S rRNA gene SNP in M. genitalium | Equivalent Escherichia coli base and position | No. (%) of patients (n = 52) |
|---|---|---|
| G69A | G69 | 1 (1.9) |
| C150T | G165 | 1 (1.9)b |
| C202T | (Insertion) | 1 (1.9)c |
| C323T | C328 | 1 (1.9)b |
| G411A | G416 | 1 (1.9)d |
| G450T | G445 | 4 (7.7)b |
| C452T | A456 | 1 (1.9)b |
| G682A | T686 | 1 (1.9) |
| A742G | A746 | 10 (19.2) |
| GG960-961TTa | GC966-967 | 7 (13.5)d |
| G1054T | G1063 | 1 (1.9)b |
| T1147C | T1172 | 1 (1.9) |
| C1166T | C1192 | 1 (1.9)b |
| C1435T | C1460 | 28 (53.8)e |
| Wild type (i.e., G37) | 5 (9.6) |
One sample included in this group had a GG960-961TC mutation.
Present in conjunction with A742G.
Present in conjunction with GG960-961TT.
Present in conjunction with C1435T. One sample contained GG960-961TT and C1435T.
One sample included in this group had an A1276 insertion.
Correlation of single nucleotide polymorphisms with change in organism load.
The change in organism load for the three main SNPs, A742G, GG960-961TT/C, and C1435T, was visualized using boxplots (Fig. 3). None of the three SNPs were associated with a significant difference in organism load compared to cases without the SNPs (P values ranging from 0.16 to 0.98, Mann-Whitney U test). To test the possibility that multiple SNPs may independently contribute to resistance, the load changes in the presence of combinations of the three SNPs were analyzed. While there was a slight increase in median change in load associated with each SNP combination, no significant associations were observed (Fig. 4).
FIG 3.
Boxplots comparing the changes in organism loads of samples with and without A742G, GG960-961TT/C, and C1435T (Mycoplasma genitalium numbering, with equivalent Escherichia coli base and position in parentheses). P values were determined to examine the association between change in organism load and the presence of each SNP (0.76, 0.16, and 0.98, respectively; Mann-Whitney U test).
FIG 4.
Boxplots comparing the changes in organism loads of samples with and without combinations of A742G, GG960-961TT/C, and C1435T (Mycoplasma genitalium numbering). P values were determined to examine the correlation between change in organism load and the presence of each mutation combination (0.193, 0.75, 0.34, and 0.11, respectively; Mann-Whitney U test).
Relationship between 16S rRNA single nucleotide polymorphisms and doxycycline MIC.
The 16S rRNA sequences were extracted for 28 M. genitalium strains from publicly available genome sequences (31, 32). Doxycycline MIC values for the corresponding strains, determined using either a cell culture or a broth dilution method, were also obtained from the literature (31, 33–35). Only the C1435T SNP was frequently present among published isolates (9/28 [32.1%]) (see Table SA1 in the supplemental material). The distribution of doxycycline MIC according to SNP is shown in Fig. 5. No association was observed between the presence of C1435T and doxycycline MIC (P values of 0.25 and 0.81 for cell culture and broth dilution, respectively). The median MICs for strains with a C1435T SNP were 0.25 to 0.5 μg/mL, while the median MICs for strains without a C1435T SNP were 0.125 to 0.25 μg/mL. The median MICs for strains with a wild-type 16S rRNA were 0.125 to 0.5 μg/mL. Other SNPs were not present in high enough numbers for analysis.
FIG 5.
Graphs examining the difference in MIC of Mycoplasma genitalium strains with the C1435T SNP or wild-type 16S rRNA sequence. Data were extracted from published literature (31–35, 48). MIC was determined by either the cell culture (A) or broth dilution (B) method. P values were determined to examine the association between doxycycline MIC and strains with and without the C1435T SNP (0.25 and 0.81 for cell culture and broth dilution, respectively; Mann-Whitney U test).
DISCUSSION
This study analyzed the association between the 16S rRNA gene of M. genitalium and changes in bacterial load with doxycycline. Three SNPs were predominant in this study: C1435T (53.8% of samples), A742G (19.2%), and GG960-961TT/C (13.5%). No associations were observed between the presence of these SNPs and change in organism load with doxycycline, including when SNPs were analyzed in combination. Analysis of the 16S rRNA gene with doxycycline MIC, obtained from published literature, also showed no clear association between C1435T and doxycycline MIC. Other SNPs were rare.
For other Mycoplasma species, sequence variations in the 16S rRNA Tet-1 region have been identified in tetracycline-resistant isolates. Previous studies have reported SNPs within or near M. genitalium Tet-1 (GG966-967TT, C1192G/T, and G1193A; Escherichia coli numbering) (Fig. 1) (36–38). However, these SNPs were uncommon and not examined in relation to doxycycline resistance (36–38). In this study, two SNPs in this region, GG960-961TT/C, and C1166T (equivalent E. coli numbering, GG966-967TT/C and C1192T), were detected but were not clearly associated with resistance. The other common SNPs detected in this study (A742G and C1435T) are located outside the Tet-1 region. A742G was also commonly identified in another study (37). Both of these mutations were not significantly associated with resistance in this study, suggesting that they are a result of natural variation and have no impact on doxycycline resistance.
Tetracycline resistance mediated by SNPs in the 16S rRNA gene have been identified in other bacteria, but this is a rare phenomenon (28). Changes at base positions 965 to 967 (E. coli numbering) of H31 of Helicobacter pylori and Mycoplasma bovis have been associated with tetracycline resistance (24, 25, 30, 39, 40). Single, double, and triple base changes have been observed, with triple base changes conferring higher tetracycline resistance. In the current study, only a double base change (i.e., GG960-961TT/C) was observed in H31, but this was not significantly associated with a change in organism load. In H34, a C1054T SNP was identified in Mycoplasma hominis and resulted in a 4-fold increase in doxycycline MIC (29). This nucleotide contacts the A-site of the ribosome; hence, it may be implicated in tetracycline resistance (22), but only one SNP was observed at H34 in the current study. SNPs located outside Tet-1 have also been identified in tetracycline-resistant bacteria (Fig. 1) but have not been reported for M. genitalium.
Few studies have examined the low efficacy of doxycycline against M. genitalium in the context of resistance. A recent study (41) found no relationship between in vitro doxycycline MIC and microbiological cure. Collectively, these data suggest that other factors are likely to contribute to low doxycycline efficacy for treatment of M. genitalium. One such factor may be the dosage. Doxycycline is recommended at 100 mg twice daily for 7 days (4–6, 42). One study extended the treatment to 14 days and observed a higher level of cure than for the 7-day regimen (15). Another factor could be the pharmacokinetics of doxycycline. Minocycline, another tetracycline which has been used for multidrug-resistant M. genitalium (43, 44), has higher efficacy than doxycycline, with 71% microbiological cure (17); this may be a consequence of minocycline being more lipophilic (45). Whether similar SNPs are present in M. genitalium samples from patients treated with minocycline should be investigated. Alternatively, M. genitalium may be intrinsically resistant to doxycycline or harbor other mechanisms of resistance not yet identified.
The ability of an antibiotic to clear infection may be impacted by the selection or development of resistance during treatment. Examination of the 22 patients with both pretreatment and treatment-treatment samples available showed no change in 16S rRNA sequence. Previous studies reporting SNPs in the 16S rRNA gene of M. genitalium have also identified SNPs in patients with and without prior exposure to doxycycline; however, the sample sizes were too small to perform statistical analyses (36–38). Therefore, doxycycline does not seem to induce or select for resistant strains during treatment, but more studies are required to confirm this.
There are limitations to this study. No control group was present in the parent study (7); thus, change in organism load may have been due to reinfection or natural variation in bacterial load or may have been a consequence of the immune response, rather than the direct effect of doxycycline treatment. However, patients at high risk of reinfection were excluded from the study. All samples were urine collected from men, so this may limit the generalizability of findings. The rarity of GG960-961TT/C and the small sample size may affect the statistical power in the current study, limiting the ability to draw conclusions. Additionally, analysis of 16S rRNA SNPs and doxycycline MIC did not report a GG960-961TT/C SNP; hence, whether this SNP correlates with an increase in MIC could not be concluded in this study.
In conclusion, no significant associations were observed between SNPs in the 16S rRNA gene and change in M. genitalium organism load with doxycycline or with doxycycline MIC. The lack of associations suggests that the low efficacy of doxycycline for M. genitalium treatment is not due to SNPs in the 16S rRNA gene. Other factors, such as the intrinsic properties of doxycycline, may contribute to the low efficacy of doxycycline for treating M. genitalium infections.
MATERIALS AND METHODS
Sample collection.
Samples were obtained from a previous study (7). Briefly, men were included if they were diagnosed with M. genitalium using the ResistancePlus MG assay (SpeeDx Pty Ltd., Australia), had not previously received azithromycin, and were prescribed 100 mg of doxycycline twice daily for 7 days, followed by either azithromycin or sitafloxacin depending on their macrolide susceptibility results.
For the current assessment, the study population constituted samples collected from 56 men recruited into a substudy examining the impact of doxycycline on M. genitalium load (7). Men at high risk of infection had been excluded based on their response to questions on a clinical template, provided as part of the parent study (7). Risk of reinfection was based on whether the patient had (i) no sex since treatment, (ii) sex with 100% condom use, (iii) any condomless sex with a fully treated partner, (iv) any condomless sex with a new partner, or (v) any condomless sex with a partner who had not completed treatment. Urine samples were obtained prior to starting doxycycline, defined as the pretreatment sample, and at a median of 13 of 14 doses (interquartile range [IQR], 11 to 14 doses), defined as the treatment sample. M. genitalium load was previously determined using quantitative PCR (7).
In this study, change in organism load was calculated by dividing the treatment load by the pretreatment load. Values were log10 transformed. Treatment samples that tested negative for M. genitalium were assigned a value at the limit of detection (35 copies/mL). Ethical approval was provided by the Alfred Hospital Ethics Committee (approval number 232/16).
Analysis of the 16S rRNA gene.
The 16S rRNA gene was amplified by PCR (7) using the primers MG-16Sminus59 (5′-GCGCTGTTAACACCTTTGTTAACG-3′) and MG-16Splus80 (5′-CTGACCAAATGTGTTAGTTGTGAGACC-3′) to produce a 1,684-bp amplicon. DNA was extracted as part of the previous study (7). Briefly, 1 mL of urine was centrifuged and resuspended in 200 μL of phosphate-buffered saline. Extraction was performed using the MagNA Pure 96 System (Roche Life Science) and the MagNA Pure 96 DNA and Viral Nucleic Acid Small-Volume Kit (Roche Life Science) with a 100-μL elution volume. Each PCR reaction mixture consisted of 0.5 μM (each) forward and reverse primers, SuperFi Taq master mix (1×; Invitrogen, Texas), nuclease-free water, and 5 μL of the eluate was used as the DNA template. G37 DNA and nuclease-free water were used as the positive and negative controls, respectively. PCR conditions were as follows: denaturation at 98°C for 30 s, then 35 cycles at 98°C for 10 s, 60°C for 10 s, and 72°C for 45 s, and a final extension at 72°C for 5 min. Sanger sequencing was performed by either Macrogen Inc. (South Korea) or Australian Genome Research Facility (Melbourne, Australia).
Sequence reads were processed and aligned to the M. genitalium type strain G37 (GenBank accession number NC_000908.2) using Geneious Prime version 2021.2.2. All samples were bidirectionally sequenced; however, the length of the reads only reached approximately 1,100 to 1,200 bp. Consequently, only the middle 600- to 700-bp portion of a read had bidirectional sequencing (approximately bases between positions 400 and 1200, which covers Tet-1). All SNPs identified in the 16S rRNA gene were determined. For patients with both pretreatment and treatment sequences available (n = 22), the sequences were identical; thus, only the pretreatment sequence was used for analysis. For 21 samples, only the pretreatment sequence was available. For nine samples, only the treatment sequence was available.
Association between 16S rRNA single nucleotide polymorphisms and MIC.
To examine the relationship between 16S rRNA SNPs and doxycycline MIC, 16S rRNA gene sequences were extracted from 28 M. genitalium genomes (GenBank accession numbers NC_000908.2, NC_018495, and CP003770) from two published studies (31, 32), and corresponding doxycycline MIC data were extracted from existing literature (33–35).
Statistical analysis.
Statistical analyses were performed using Stata version 17.0 (StataCorp). The Mann-Whitney U test was performed to determine the association between SNPs in the 16S rRNA gene and change in organism load or doxycycline MIC. Data were visualized using boxplots.
Data availability.
16S rRNA gene sequences are available in GenBank (accession numbers OM509887 to OM509960).
ACKNOWLEDGMENTS
This work was supported by the Department of Health and Human Services Victorian Medical Research Acceleration Fund (G.L.M., C.S.B., and S.M.G.), Australian Research Council Research Hub to Combat Antimicrobial Resistance (project identifier IH190100021; G.L.M. and C.S.B.), and National Health and Medical Research Council Investigator Grant APP1197951 (S.M.G.).
Footnotes
Supplemental material is available online only.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table SA1. Download aac.00243-22-s0001.pdf, PDF file, 0.08 MB (86.7KB, pdf)
Data Availability Statement
16S rRNA gene sequences are available in GenBank (accession numbers OM509887 to OM509960).