Submitted:
10 December 2024
Posted:
11 December 2024
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Abstract
Objectives: We aimed to, for the first time, characterize the antimicrobial susceptibilities of commensal Neisseria species in the general population in Japan. We assessed if the tetracycline MICs of these isolates where changing over time and given the recent interest in doxycycline post exposure prophylaxis if the tetracycline MICs were associated with those of the other antimicrobials. Methods: Neisseria spp. were isolated from 1,679 patients visiting dental clinics in Japan, between 2018-2023. The MICs of tetracycline, ceftriaxone, cefixime, penicillin, azithromycin and ciprofloxacin against Neisseria spp. were determined using agar dilution. Linear regression was used to assess if there was an association between MIC and the year the isolate was obtained from, controlling for species identity. Results: Neisseria spp. were detected in 424 of 1,679 individuals sampled. Of these, 417 (98.3%) were identified as Neisseria subflava, and the remaining 7 (1.7%) as Neisseria mucosa. The median tetracycline MIC was 0.5 mg/L (IQR 0.5-1 mg/L). The MICs of penicillin, cefixime, ceftriaxone and ciprofloxacin were lower in N. mucosa than N. subflava. The tetracycline MICs of Neisseria spp. were positively correlated with penicillin, azithromycin and ciprofloxacin. No significant correlations were found with cefixime or ceftriaxone. Conclusions: Our results suggest that the intensive use of doxycycline in populations could select for Neisseria spp. with higher tetracycline MICs and in so doing select for higher penicillin, azithromycin and ciprofloxacin MICs. This could in turn increase the probability of resistance associated mutations being passed on to the pathogenic Neisseria spp.
Keywords:
Neisseria
; commensals
; Japan
; DOXY-PEP
; Antimicrobial resistance
Izumo Kanesaka 1,2,*, Sheeba Santhini Manoharan-Basil 1, Tessa De Block 1, Chris Kenyon 1,3, Masahiro Morita 2, Takamitsu Ito 4, Natsue Yamane 5, Akiko Katsuse Kanayama 2 and Intetsu Kobayashi 2
1 STI unit, Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Nationalestraat 155, 2000 Antwerp, Belgium
2 Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
3 University of Cape Town, Rondebosch, Cape Town, 7700 South Africa
4 Higashiosaka City Medical Center, 3-4-5, Nishiiwata, Higashiosaka-shi, Osaka 578-8588, Japan
5 Natsu Dental Clinic, 4-31-10, Ikegami, Ota-ku, Tokyo 146-0082, Japan
Introduction
Doxycycline is a second-generation tetracycline with a broad antibacterial spectrum. [1] Studies have found that doxycycline post-exposure prophylaxis (PEP) reduces the incidence of bacterial sexually transmitted infections (STIs) among men who have sex with men (MSM) .[2,3,4] However, two recent in silico studies have found that tetracycline resistance was associated with cross-resistance to multiple antimicrobials in various bacterial species including Neisseria gonorrhoeae, suggesting that doxycycline could inadvertently select for broader antimicrobial resistance (AMR).[5,6] This association means that the widespread use of doxycycline PEP could select for resistance to other antimicrobials in these other species. [7,8,9]
A single RCT has evaluated the impact of doxycycline PEP on commensal Neisseria species and found that doxycycline PEP was associated with an increase in the prevalence of tetracycline resistance.[4,10] This finding is important because commensal Neisseria species, can be cultured from the oral cavity of almost all individuals, which means they are more exposed to the effects of high antimicrobial consumption than species such as N. gonorrhoeae that have a typical prevalence of closer to 1%.[11] Furthermore, commensal Neisseria spp. have played an important role in the genesis of cephalosporin, macrolide, fluoroquinolone and sulphonamide resistance in N. gonorrhoeae and N. meningitidis. This effect was initially mediated by high antimicrobial consumption selecting for antimicrobial resistance in the commensal Neisseria spp. The resistance conferring mutations were then taken up by the pathogenic Neisseria spp.. Thus, acquisition of sections of the penA, parC, gyrA, mtrCDE, rplB, rplD, and rplV genes from commensal Neisseria spp. has played an important role in the development of resistance to penicillins, cephalosporins, macrolides, and fluoroquinolones in N. meningitidis and N. gonorrhoeae.[12,13,14]
These findings have led various authors to call for the use of commensal Neisseria spp. as an early warning system of excessive antimicrobial consumption.[11,15] They also mean that it is important to consider the impacts of an antimicrobial intervention on AMR in commensal Neisseria spp..[15] Studies have revealed that the introduction of doxycycline PEP in MSM taking PrEP could lead to an 88-fold increase in tetracycline consumption.[16] Because we know that this increased consumption will likely lead to an increase in tetracycline resistance in commensal Neisseria spp., it is important to know if tetracycline resistance in these species is linked to resistance to other antimicrobials. If it were, then doxycycline PEP could select for resistance to these other classes of antimicrobials which could then be transformed into the pathogenic Neisseria species.
The aims of this study were therefore to, for the first time, (1) characterize the tetracycline, ceftriaxone, cefixime, penicillin, azithromycin and ciprofloxacin susceptibilities of commensal Neisseria species in the general population in Japan, (2) assess if tetracycline MICs of these isolates are associated with the MICs of the other antimicrobials and (3) evaluate if there was a change in these MICs over a six year period.
Materials and methods
- Bacterial isolates
Commensal Neisseria spp. (n=424) were isolated from 1,679 patients visiting dental clinics in Tokyo, Japan, between 2018-2023. Sampling was carried out from October to December each year. If a patient was isolated more than once from the same patient in the same year, only the first case was included. The samples were obtained by soaking sterile cotton swabs with patient saliva and inserting them into a Brain Heart Infusion (BHI) soft agar medium. The saliva-soaked swabs were plated onto TSAⅡ5% sheep blood agar (BD) and chocolateⅡagar (BD) media and incubated at 35 ℃ 5% CO2 for 48 hours. After incubation, colonies suspected to be Neisseria spp. were purified by sub-culturing on the same agar medium and incubated at 35 ℃ for 24 hours. The purified strains were Gram-stained and Neisseria spp. identification was carried out using a deoxyribonuclease (DNase) test (Eiken Chemical), followed by MALDI-TOF MS using a VITEK MS v3.2 system (bioMérieux Ltd., Japan).
- Ethics
The research protocol was reviewed by the Ethical Review Committee of Toho University School of Nursing (No.2024006). Informed consent was obtained from all participants by dentist.
- Antimicrobial susceptibility testing
The minimum inhibitory concentrations (MICs) of penicillin (PCG), cefixime (CFIX), ceftriaxone (CTRX), tetracycline (TC), ciprofloxacin (CPFX) and azithromycin (AZM) against Neisseria spp. were determined using the agar plate dilution method according to the Clinical and Laboratory Standards Institute (CLSI) guidelines.[17] The test strains were suspended in sterile saline to obtain a 0.5 McFarland suspension (approximately 1-2 × 108 CFU/mL) and further diluted with the same solution to obtain the bacterial inoculum. The inoculum was spotted (104 CFU/spot) onto Mueller-Hinton agar supplemented with sheep blood (5%) containing a 2-fold dilution series concentration of each antimicrobial agent using a micro planter. The plates were incubated at 35 ℃ and 5% CO2 for 20-24 hours. Resistance to each antimicrobial agent was classified using the CLSI M100-31ed breakpoints for N. gonorrhoeae (Penicillin S:≦0.06 µg/mL, I:0.12-1 µg/mL, R:≧2 µg/mL, Cefixime S:≦0.25 µg/mL, Ceftriaxone S:≦0.25 µg/mL, Tetracycline:≦0.25 µg/mL, I:0.5-1 µg/mL, R:≧2 µg/mL, Ciprofloxacin S:≦0.06 µg/mL, I:0.12-0.5 µg/mL, R:≧1 µg/mL, Azithromycin S:≦2 µg/mL).
- Comparison with Furuya et al
For a longer-term comparison of susceptibilities, we compared the MICs of N. subflava from our study with those obtained from a previous study in 2005/6 by Furuya et al., from Fukuoka, Japan. In their study, Furuya et al, used the CLSI agar dilution method to ascertain the penicillin, cefixime, ceftriaxone, ciprofloxacin and tetracycline MICs of 45 N. subflava isolates obtained from the oral cavities from 40 men with urethritis and 5 women who were sex workers.[18] They did not provide the individual MIC values and thus we could not formally test for statistical differences in MIC distribution. We therefore compared MICs between the studies descriptively.
- Data
- ata analysis
When MICs were reported as less or more than the lowest or highest concentration tested, these were replaced with the lowest or highest concentrations tested, respectively. The MICs were log transformed to create more-normal distributions for the regression analyses. Linear regression was used to assess if there was an association between MIC (log transformed) and the year the isolate was obtained from, controlling for species identity. Spearman’s rank correlation was used to assess the relationship between the MIC values of tetracycline and other antibiotics (penicillin G, ciprofloxacin, azithromycin, cefixime, and ceftriaxone) of commensal Neisseria spp. Wilcoxon rank-sum test was used to compare tetracycline MIC between years and species. Isolates identified as Neisseria flava/perflava/subflava by MALDITOF-MS were classified as N. subflava and isolates identified as Neisseria mucosa/sicca were classified as N. mucosa. [19] A p-value of 0.05 was regarded as statistically significant. Statistical analyses were conducted using STATA MP v16.1 (StataCorp, LLC, College Station, TX).
Results
- Identification of Neisseria spp.
The median age of the participants was 53 (IQR 38-70). Sixty five percent of the participants were female and 35% male. Neisseria spp. were detected in 424 (25.3%) of 1,679 individuals sampled. Of these, 417 (98.3%) were identified as N. subflava, and the remaining 7 (1.7%) as N. mucosa.
- Antimicrobial susceptibilities between 2015 and 2022
The annual Neisseria spp. MIC results for various antimicrobials are provided in Table 1. The median tetracycline MIC increased from 0.5mg/L (IQR 0.12-32mg/L) in 2018, to 1mg/L (IQR 0.5-64mg/L) in 2023 (Table 1; P<0.0001). None of the isolates from 2023 were susceptible to tetracycline. Linear regression did not, however, reveal a significant increase in the MIC of tetracycline or any other antimicrobial between 2018 and 2023 (Table 2). The median MICs for ciprofloxacin (0.375mg/L [IQR 0.25-1mg/L]) and azithromycin (2mg/L [IQR 1-4mg/L]) remained high throughout this period (Table 1).
The MICs of penicillin, cefixime, ceftriaxone and ciprofloxacin were lower in Neisseria mucosa/sicca than Neisseria flava/perflava/subflava (Table 3).
- Comparison of antimicrobial susceptibilities with Furuya et al. survey
The penicillin, cefixime, ceftriaxone and ciprofloxacin MICs of N. subflava from our survey were numerically higher than those described by Furuya et al. in 2005/6 (Table 4). There was no difference in the tetracyline or azithromycin MICs.
- Correlation between MICs of tetracycline and other antibiotics
The tetracycline MICs of commensal Neisseria spp. were positively correlated with those of penicillin (ρ = 0.1548, P = 0.0014), azithromycin (ρ = 0.1889, P = 0.0001) and ciprofloxacin (ρ = 0.1823, P = 0.0002). No significant correlations were found with cefixime (ρ = -0.0308, P = 0.5269) or ceftriaxone (ρ = 0.0818, P = 0.0924). These results were similar when restricted to N. flava/perflava/subflava, the main oral Neisseria spp. species isolated in the present study.
Discussion
Whilst previous studies have evaluated the tetracycline MICs of commensal Neisseria spp. these have either been very small and limited to high-risk groups, such as the study by Furuya et al., [18] or limited to measuring the proportion of individuals with tetracycline resistant commensal Neisseria spp..[4] Our study is the first to characterize the tetracycline MICs of commensal Neisseria spp. from the general population. We found surprisingly low tetracycline MICs. Of concern, we found that tetracycline MICs were strongly associated with penicillin, azithromycin and ciprofloxacin MICs. Also of concern were the apparent increases in MICs for penicillin, cefixime, ceftriaxone and ciprofloxacin since the Furuya et al., survey from 2005/6.
Our results raise the concern that intensive use of doxycycline in populations could select for commensal Neisseria spp. with higher tetracycline MICs and in so doing select for higher penicillin, azithromycin and ciprofloxacin MICs. This could in turn increase the probability of resistance associated mutations being passed on to the pathogenic Neisseria spp..[12,15] Excessive use of antimicrobials in the general population is a plausible explanation for the increased MICs observed in N. subflava.[20] The use of antimicrobials in outpatient care is high in Japan.[21] More than half of antimicrobials in prescribed in outpatient care are innapropriate, and broad-spectrum antimicrobials are frequently used.[22] The implementation of the Japanese AMR National Action Plan, has, however, led to reductions in the sales of third-generation cephalosporins, fluoroquinolones, and macrolides from 2015 to 2021 of 44.8%, 45.4%, and 40.7%, respectively.[23] Our results provide further impetus to strengthen these stewardship initiatives.
Low-level tetracycline resistance in N. gonorrhoeae is conferred by chromosomal mutations in rpsJ, porB and mtrR.[24] High-level resistance is typically due to the acquisition of the tetM gene on a plasmid.[25] Whilst the mechanisms underpinning tetracycline resistance in commensal Neisseria spp. have not been established with certainty, they are likely to be similar. One analysis of the CDC panel of commensal Neisseria spp. found that the isolate with the highest tetracycline MIC (48 µg/mL) was an isolate of N. subflava which was also the only commensal Neisseria isolate with the tetM gene.[26] Other studies have found the tetM and tetB genes to be present in a high proportion of N. subflava isolates. porB mutations associated with tetracycline resistance have also detected in a number of commensal Neisseria spp..[27]
We were not able to conduct whole genome sequencing of these isolates and therefore cannot assess the genetic determinants of reduced susceptibility to tetracyclines. Our analysis is also limited by the single centre study design and having limited metadata such as antimicrobial consumption. Our comparison with the Furuya et al. study is also limited due to regional and sampling differences, patient backgrounds and the fact that the Furuya et al., study was limited to N. subflava. We intend to sequence a subset of this collection to address some of these shortcomings. This will include the twelve isolates with low susceptibility (0.5-2 µg/mL) to ceftriaxone detected in the present study. These strains, identified as N. subflava, were resistant to penicillin and showed low susceptibility to cefixime, another third-generation cephalosporin, suggesting that they were β-lactam resistant strains due to polymorphisms in the penA gene .
This study is the first to characterize the MICs of tetracycline and other antimicrobials in oral commensal Neisseria spp. in the general population in Japan. Despite the overall decline in antimicrobial use in Japan, MICs for a number of antimicrobials appear to have increased over time. A significant positive correlation between tetracycline MICs and ciprofloxacin, penicillin G and azithromycin MICs suggests intensive use of doxycycline-PEP could select for AMR against these antimicrobial. These results suggest the need to include surveillance of this tetracycline MICs of commensal Neisseria spp. in doxycycline PEP studies and implementation projects.
Transparency Declarations
The authors declare that they have no conflicts of interest.
Author Contributions
IzK,InK and CK contributed to the conception and design of the project. IzK, TDB, SSMB, MM, TI, NY, AKK, InK and CK contributed to the acquisition, analysis, and interpretation of the data. IzK, TDB, SSMB and CK contributed to the writing of the manuscript. The first draft of the manuscript was written by IzK, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
This research was supported by the Japan Agency for Medical Research and Development (JP21fk0108605).
Acknowledgments
None.
References
- Cunha BA, Sibley CM, Ristuccia AM. Doxycycline. Ther Drug Monit. 1982; 4: 115-35. [CrossRef]
- Molina JM, Charreau I, Chidiac C et al. Post-exposure prophylaxis with doxycycline to prevent sexually transmitted infections in men who have sex with men: an open-label randomised substudy of the ANRS IPERGAY trial. Lancet Infect Dis. 2018; 18: 308–17. [CrossRef]
- Bolan RK, Beymer MR, Weiss RE et al. Doxycycline prophylaxis to reduce incident syphilis among HIV-infected men who have sex with men who continue to engage in high-risk sex: a randomized, controlled pilot study. Sex Transm Dis. 2015; 42: 98–103. [CrossRef]
- Luetkemeyer AF, Donnell D, Dombrowski JC et al. Postexposure Doxycycline to Prevent Bacterial Sexually Transmitted Infections. N Engl J Med. 2023; 388: 1296-1306. [CrossRef]
- Gestels Z, Manoharan-Basil SS, Kenyon C. Doxycycline post exposure prophylaxis could select for cross-resistance to other antimicrobials in various pathogens: An in silico analysis. Int J STD AIDS. 2023; 34: 962-68. [CrossRef]
- Kenyon C. Doxycycline post exposure prophylaxis could theoretically select for resistance to various antimicrobials in 19 pathobionts: an in silico analysis. Int J Infect Dis. 2024; 142: 106974. [CrossRef]
- Grossman TH, Tetracycline Antibiotics and Resistance. Cold Spring Harb Perspect Me. 2016; 26: a025387. [CrossRef]
- Vanbaelen T, Manoharan-Basil SS, Kenyon C. Doxycycline Postexposure Prophylaxis Could Induce Cross-Resistance to Other Classes of Antimicrobials in Neisseria gonorrhoeae : An In Silico Analysis. Sex Transm Dis. 2023; 50: 490-93. [CrossRef]
- George AM, Levy SB. Amplifiable resistance to tetracycline, chloramphenicol, and other antibiotics in Escherichia coli: involvement of a non-plasmid-determined efflux of tetracycline. J Bacteriol. 1983; 155: 531-40. [CrossRef]
- Vanbaelen T, Manoharan-Basil SS, Kenyon C. 45 years of tetracycline post exposure prophylaxis for STIs and the risk of tetracycline resistance: a systematic review and meta-analysis. BMC Infect Dis. 2024; 24: 376. [CrossRef]
- Kenyon C, Laumen J, Manoharan-Basil S, Choosing New Therapies for Gonorrhoea: We Need to Consider the Impact on the Pan-Neisseria Genome. A Viewpoint. Antibiotics. 2021; 10: 515. [CrossRef]
- Wadsworth CB, Arnold BJ, Sater MRA et al. Azithromycin Resistance through Interspecific Acquisition of an Epistasis-Dependent Efflux Pump Component and Transcriptional Regulator in Neisseria gonorrhoeae. mBio. 2018; 9: e01419-e01418. [CrossRef]
- Chen ML, Zhang C, Zhang X et al. Meningococcal Quinolone Resistance Originated from Several Commensal Neisseria Species. Antimicrob Agents Chemother. 2020; 64: e01494-01519. [CrossRef]
- Manoharan-Basil SS, Laumen JGE, Dijck CV et al. Evidence of Horizontal Gene Transfer of 50S Ribosomal Genes rplB, rplD, and rplY in Neisseria gonorrhoeae. Front Microbiol. 2021; 12: 683901. [CrossRef]
- Goytia M, Wadsworth CB. Canary in the Coal Mine: How Resistance Surveillance in Commensals Could Help Curb the Spread of AMR in Pathogenic Neisseria. mBio. 2022; 13: e01991-01922. [CrossRef]
- Vanbaelen T, Tsoumanis A, Kenyon C. Total Antimicrobial Consumption in Doxycycline Postexposure Prophylaxis Cohorts and the Intensity of Screening for Bacterial Sexually Transmitted Infections. Clin Infect Dis. 2024; 78: 803-805. [CrossRef]
- Clinical and laboratory standards institute. In: Anonymous Performance Standards for Antimicrobial Susceptibility Testing—Thirtieth Edition: M100. 2020. Wyne, PA19087 USA: .
- Furuya R, Onoye Y, Kanayama A et al. Antimicrobial resistance in clinical isolates of Neisseria subflava from the oral cavities of a Japanese population. J Infect Chemother. 2007; 13: 302-304. [CrossRef]
- Maiden MCJ, Harrison OB. Population and Functional Genomics of Neisseria Revealed with Gene-by-Gene Approaches. J Clin Microbiol. 2016; 54: 1949-55. [CrossRef]
- Vanbaelen T, Dijck CV, Laumen J et al. Global epidemiology of antimicrobial resistance in commensal Neisseria species: A systematic review. Int J Med Microbiol. 2022; 312: 151551. [CrossRef]
- Yamazaki D, Tanabe M, Kato G et al. The first report of Japanese antimicrobial use measured by national database based on health insurance claims data (2011–2013): comparison with sales data, and trend analysis stratified by antimicrobial category and age group. Infection. 2018; 46: 207-14. [CrossRef]
- Hashimoto H, Saito M, Sato J et al. Indications and classes of outpatient antibiotic prescriptions in Japan: A descriptive study using the national database of electronic health insurance claims, 2012-2015. Int J Infect Dis. 2020; 91: 1-8. [CrossRef]
- Tsuzuki S, Koizumi R, Matsunaga N et al. Decline in Antimicrobial Consumption and Stagnation in Reducing Disease Burden due to Antimicrobial Resistance in Japan. Infect Dis Ther. 2023; 12: 1823-34. [CrossRef]
- Unemo M, Shafer WM. Antimicrobial resistance in Neisseria gonorrhoeae in the 21st century: past, evolution, and future. Clin Microbiol Rev. 2014; 27: 587-613. [CrossRef]
- Morse SA, Johnson SR, Biddle JW et al. High-level tetracycline resistance in Neisseria gonorrhoeae is result of acquisition of streptococcal tetM determinant. Antimicrob Agents Chemother. 1986; 30: 664-70. [CrossRef]
- Fiore MA, Raisman JC, Wong NH et al. 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. [CrossRef]
- Block TD, Laumen JGE, Dijck CV et al. WGS of Commensal Neisseria Reveals Acquisition of a New Ribosomal Protection Protein (MsrD) as a Possible Explanation for High Level Azithromycin Resistance in Belgium. Pathogens. 2021; 10: 384. [CrossRef]
Table 1.
Minimum inhibitory concentration (MIC) of various antimicriobials of commensal Neisseria spp.
Table 1.
Minimum inhibitory concentration (MIC) of various antimicriobials of commensal Neisseria spp.
| Antimicrobial | MIC (µg/mL) | No. of Isolates (%) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| range | MIC50 | MIC90 | S | I | R | |||||
| Penicillin | 2018 | ( n = 66) | 0.12-4 | 0,5 | 2 | 0 (0) | 57 (86) | 9 (14) | ||
| 2019 | ( n = 41 ) | 0.5-4 | 1 | 2 | 0 (0) | 32 (78) | 9 (22) | |||
| 2020 | ( n = 69 ) | 0.25-16 | 1 | 4 | 0 (0) | 46 (67) | 23 (33) | |||
| 2021 | ( n = 72 ) | 0.25-4 | 1 | 2 | 0 (0) | 69 (83) | 12 (17) | |||
| 2022 | ( n = 50 ) | 0.25-16 | 1 | 2 | 0 (0) | 28 (56) | 22 (44) | |||
| 2023 | ( n = 126) | 0.12-8 | 1 | 2 | 0 (0) | 95 (75) | 31 (25) | |||
| Cefixime | 2018 | ( n = 66) | ≦0.008-4 | 0,06 | 0,25 | 61 (92) | - | - | ||
| 2019 | ( n = 41 ) | 0.015-4 | 0,06 | 0,25 | 37 (90) | - | - | |||
| 2020 | ( n = 69 ) | ≦0.008-4 | 0,06 | 0,5 | 61 (88) | - | - | |||
| 2021 | ( n = 72 ) | ≦0.008-4 | 0,06 | 1 | 58 (81) | - | - | |||
| 2022 | ( n = 50 ) | ≦0.008-4 | 0,06 | 0,12 | 45 (90) | - | - | |||
| 2023 | ( n = 126) | ≦0.008-4 | 0,03 | 0,12 | 118 (94) | - | - | |||
| Ceftriaxone | 2018 | ( n = 66) | ≦0.008-0.25 | 0,015 | 0,06 | 66 (100) | - | - | ||
| 2019 | ( n = 41 ) | 0.015-2 | 0,03 | 0,12 | 39 (95) | - | - | |||
| 2020 | ( n = 69 ) | ≦0.008-0.5 | 0,03 | 0,25 | 66 (96) | - | - | |||
| 2021 | ( n = 72 ) | ≦0.008-1 | 0,03 | 0,12 | 69 （96) | - | - | |||
| 2022 | ( n = 50 ) | ≦0.008-0.5 | 0,03 | 0,12 | 49 (98) | - | - | |||
| 2023 | ( n = 126) | ≦0.008-1 | 0,03 | 0,06 | 123 (98) | - | - | |||
| Tetracycline | 2018 | ( n = 66) | 0.12-32 | 0,5 | 16 | 26 (39) | 25 (38) | 15 (23) | ||
| 2019 | ( n = 41 ) | 0.25-32 | 0,5 | 32 | 4 (10) | 27 (66) | 10 (24) | |||
| 2020 | ( n = 69 ) | 0.25-64 | 0,5 | 16 | 2 (3) | 54 (78) | 13 (19) | |||
| 2021 | ( n = 72 ) | 0.12-64 | 0,5 | 16 | 6 (8) | 52 (72) | 14 (19) | |||
| 2022 | ( n = 50 ) | 0.12-32 | 0,5 | 16 | 4 (8) | 36 (72) | 20 (10) | |||
| 2023 | ( n = 126) | 0.5-64 | 1 | 16 | 0(0) | 102 (81) | 24 (19) | |||
| Ciprofloxacin | 2018 | ( n = 66) | ≦0.06-16 | 0,25 | 4 | 2 (3) | 45 (68) | 19 (29) | ||
| 2019 | ( n = 41 ) | ≦0.06-8 | 0,5 | 4 | 1 (3) | 30 (73) | 10 (24) | |||
| 2020 | ( n = 69 ) | ≦0.06-32 | 0,5 | 8 | 3 (4) | 45 (65) | 21 (30) | |||
| 2021 | ( n = 72 ) | ≦0.06-8 | 0,5 | 4 | 8 (11) | 39 (54) | 25 (35) | |||
| 2022 | ( n = 50 ) | ≦0.06-16 | 0,25 | 8 | 6 (12) | 28 (56) | 16 (32) | |||
| 2023 | ( n = 126) | ≦0.06-16 | 0,25 | 4 | 8 (6) | 87 (69) | 31 (25) | |||
| Azithromycin | 2018 | ( n = 66) | ≦0.06-8 | 2 | 4 | 16(24) | - | - | ||
| 2019 | ( n = 41 ) | ≦0.06-8 | 2 | 4 | 15 (37) | - | - | |||
| 2020 | ( n = 69 ) | ≦0.06-64 | 2 | 8 | 31 (45) | - | - | |||
| 2021 | ( n = 72 ) | 0.25-128 | 2 | 16 | 14 (19) | - | - | |||
| 2022 | ( n = 50 ) | 0.5-32 | 2 | 4 | 19 (38) | - | - | |||
| 2023 | ( n = 126) | 0.12-64 | 2 | 8 | 60 (48) | - | - | |||
Table 2.
Changes in minimum inhbitory concentrations (MICs-log transformed) over time (year) for various antibiotics controlling for species.
Table 2.
Changes in minimum inhbitory concentrations (MICs-log transformed) over time (year) for various antibiotics controlling for species.
| Antibiotic | No. of Observations | Regression Coefficient (95% CI) | P-Value |
|---|---|---|---|
| Azithromycin | 424 | -0.018 (-0.081-0.044) | 0.563 |
| Cefixime | 424 | -0.037 (-0.107-0.032) | 0.292 |
| Ceftriaxone | 424 | 0.027 (-0.029-0.084) | 0.342 |
| Ciprofloxacin | 424 | 0.012 (-0.066-0.089) | 0.770 |
| Penicillin | 424 | 0.017 (-0.022-0.057) | 0.377 |
| Tetracycline | 424 | 0.054 (-0.022-0.131) | 0.160 |
Table 3.
Minimum inhibitory concentration (MIC) of various antimicriobials of N. subflava and N. mucosa.
Table 3.
Minimum inhibitory concentration (MIC) of various antimicriobials of N. subflava and N. mucosa.
| Antimicrobial | Median N. subflava MIC mg/L (IQR) | Median N. mucosa MIC mg/L (IQR) | P-Value |
|---|---|---|---|
| Penicillin | 1 (0.5-2) | 0.5 (0.25-0.5) | 0.0014 |
| Cefixime | 0.06 (0.03-0.12) | 0.03 (0.015-0.03) | 0.0141 |
| Ceftriaxone | 0.03 (0.015-0.03) | 0.015 (0.015-0.015) | 0.0443 |
| Tetracycline | 0.5 (0.5-1) | 0.5 (0.25-0.5) | 0.0542 |
| Ciprofloxacin | 0.5 (0.25-1) | 0.12 (0.12-0.25) | 0.0109 |
| Azithromycin | 2 (1-4) | 2 (1-2) | 0.4358 |
Table 4.
Comparison of N. subflava MICs from the current study with those from the Furuya et al. survey of Japan in 2005/6.
Table 4.
Comparison of N. subflava MICs from the current study with those from the Furuya et al. survey of Japan in 2005/6.
| Antimicrobial | This study | Furuya et al. 2005/6 | ||
|---|---|---|---|---|
| Range | MIC50/90 | Range | MIC50/90 | |
| Penicillin | 0.25-4 | 1/2 | 0.06-2 | 0.5/1 |
| Cefixime | 0.008-4 | 0.06/0.5 | 0.001-1 | 0.03/0.12 |
| Ceftriaxone | 0.004-1 | 0.03/0.03 | 0.001-0.12 | 0.03/0.06 |
| Tetracycline | 0.25-64 | 0.5/32 | 0.25-32 | 0.5/32 |
| Ciprofloxacin | 0.015-16 | 0.5/4 | 0.008-8 | 0.25/4 |
| Azithromycin | 0.06-64 | 2/4 | NA | NA |
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