Efflux-Mediated Macrolide Resistance in Clinical Streptococcus Isolates: A Comparative Molecular Study

Abstract

Background: Efflux-mediated macrolide resistance represents an emerging threat in Streptococcus infections globally. However, molecular epidemiological data from the Gulf region, particularly the United Arab Emirates (UAE), remain limited. This study addresses this knowledge gap by investigating efflux pump resistance mechanisms in clinical Streptococcus isolates.

Methods: A cross-sectional study analyzed 100 clinical isolates (99 Streptococcus and 1 Enterococcus) from Thumbay Hospital, Ajman, UAE (October-December 2024). Antimicrobial susceptibility testing for minimum inhibitory concentration (MIC) determination was performed using the DxM 1096 MicroScan WalkAway system (Beckman Coulter Inc., Brea, CA, USA; LabProv4.42). PCR detected mef(A/E), msr(D), and tet(K) resistance genes with sequencing confirmation. Comparative genomic analysis was performed using a total of 30 publicly available Streptococcus genomes: 15 from India and 15 from Saudi Arabia. Statistical analysis employed chi-square tests, Fisher's exact tests, and multivariate logistic regression with Bonferroni correction (α = 0.05).

Results: Among the isolates, erythromycin resistance occurred in 39 isolates (39%, 95% CI: 29.4-49.2%) and clindamycin resistance in 31 isolates (31%, 95% CI: 22.1-40.9%). The mef(A/E) gene was detected in 31 isolates (31%, 95% CI: 22.1-40.9%), and msr(D) in 3 isolates (3%, 95% CI: 0.6-8.5%), with co-occurrence in 3 isolates (3%). No isolates harbored tet(K). Multivariate analysis identified mef(A/E) as the strongest predictor of macrolide resistance (OR = 18.7, 95% CI: 7.9-44.2, p < 0.001). Regional comparison revealed significant differences: mef(A/E) prevalence was 31% (UAE), 87% (India), and 0% (Saudi Arabia) (p < 0.001).

Conclusions: This study provides the first molecular characterization of efflux-mediated macrolide resistance in UAE Streptococcus isolates. The predominance of mef(A/E)-mediated resistance with confirmed efflux activity highlights the clinical significance of active surveillance and targeted antimicrobial stewardship in the region.

Keywords: Streptococcus; antimicrobial resistance; efflux pump; macrolide resistance; mef(A); msr(D).

Figure 1

Gender-based comparison of Streptococcus resistance to multiple antibiotics. The proportion of resistant isolates among male (n = 41) and female (n = 59) patients. Abbreviations: ERY, erythromycin; CD, clindamycin; PEN, penicillin; OX, oxacillin; LEV, levofloxacin; TET, tetracycline; CIP, ciprofloxacin; COT, cotrimoxazole; RIF, rifampin; TEI, teicoplanin. Numbers above the bars indicate the number of resistant cases per gender. * Only clindamycin resistance differed significantly between genders (χ² = 4.327, p = 0.038).

Figure 2

Age distribution of Streptococcus antimicrobial resistance profiles. Age-stratified distribution of antimicrobial resistance profiles across four age groups: 0–18 years, 19–35 years, 36–50 years, and 51–60 years. Resistance profiles on the x-axis include single-drug resistance (ERY: erythromycin; CD: clindamycin; PEN: penicillin; OX: oxacillin; LEV: levofloxacin; TET: tetracycline; CIP: ciprofloxacin; COT: cotrimoxazole; RIF: rifampin; TEI: teicoplanin) and multidrug combinations. Numbers on top of the bars indicate the count of resistant isolates per age group. Overall comparison across age groups was statistically significant (χ² = 18.445, p = 0.018 *), with the 19–35-year group exhibiting the highest cumulative resistance burden. Data represents the distribution of resistance patterns among 100 isolates (99 Streptococcus, 1 Enterococcus).

Figure 3

Ethidium bromide (EtBr) accumulation assay in sensitive and resistant Streptococcus isolates. Fluorescence increased with EtBr concentration in sensitive isolates (0.5 μg/mL: ~14,500 RFU; 4.0 μg/mL: 32,150 ± 2840 RFU) but plateaued and declined in resistant isolates (0.5 μg/mL: ~15,000 RFU; 4.0 μg/mL: 16,420 ± 2650 RFU). Background fluorescence (EtBr + PBS) was 11,395 RFU. Statistical significance was assessed by Mann–Whitney U test: 0.5 μg/mL (p = 0.024, *), 1.0 μg/mL (p = 0.003, **), 2.0 μg/mL and 4.0 μg/mL (p < 0.001, ***), indicating progressively greater differences at higher EtBr concentrations, consistent with inducible efflux pump activity.

Figure 4

mef(A) gene electrophoresis result Detection of the mef(A) gene (350 bp) on a 1.5% agarose gel. Lanes 1, 4, 6, and 7: positive samples. Lanes 2, 3, 5, 8, 9, 10 and 13: Negative samples; Lane 11: positive control; Lane 12: Negative control; M: 100 bp molecular marker.

Figure 5

msr(D) gel electrophoresis result msr(D) gene detection (482 bp) on a 1.5% agarose gel. Lane M: 100 bp DNA ladder; Lanes 1–3: positive samples; Lane −ve: Negative control; Lane +ve: positive control.

Figure 6

(A): Distribution of Resistance Genes in UAE Streptococcus Isolates. The macrolide resistance gene mef(A) was frequently detected, while msr(D) was observed in only a few isolates. The tetracycline resistance gene tet(K) was absent in all UAE isolates (ERY: erythromycin; CD: clindamycin; PEN: penicillin; OX: oxacillin; LEV: levofloxacin; TET: tetracycline; CIP: ciprofloxacin; COT: cotrimoxazole; RIF: rifampin; TEI: teicoplanin). Heatmaps illustrate the presence (Red) and absence (Green) of antibiotic classes across tested drug. (B): Distribution of Antibiotic Resistance Classes in UAE Streptococcus Isolates. Macrolide resistance was the most prevalent, followed by resistance to β-lactams, while tetracycline resistance was detected only in a single group. Resistance was distributed across various antibiotic combinations, mainly involving macrolides, lincosamides, and β-lactams (ERY: erythromycin; CD: clindamycin; PEN: penicillin; OX: oxacillin; LEV: levofloxacin; TET: tetracycline; CIP: ciprofloxacin; COT: cotrimoxazole; RIF: rifampin; TEI: teicoplanin).

Figure 7

(A): Distribution of antibiotic resistance genes in Streptococcus isolates from India. Presence of mef(A) and msr(D) genes, confirming macrolide resistance against erythromycin, azithromycin, and clarithromycin. In addition, the Indian dataset displayed a broader resistance profile with tet(M), rpoC, and liaS, associated with resistance to tetracycline, rifampin, and daptomycin, respectively, indicating a diverse distribution of resistance determinants in Indian clinical isolates. (B): Distribution of antibiotic classes in Streptococcus isolates from India. Several antibiotic classes including macrolides, peptide antibiotics, rifamycins, and tetracyclines are represented among the Indian isolates, reflecting a broad spectrum of resistance determinants.

Figure 8

(A): Distribution of antibiotic resistance genes in Streptococcus isolates from Saudi Arabia. Presence of erm(B) and tet(M), conferring resistance to lincosamides and tetracyclines, respectively. Additional genes detected included gyrB and folP (fluoroquinolone and sulfonamide resistance) as well as liaS and mprF (cell envelope and peptide antibiotic resistance). Notably, none of the isolates carried mef(A), msr(D), or tet(K), indicating the absence of efflux-mediated resistance mechanisms in the Saudi Arabian dataset. (B): Distribution of antibiotic classes in Streptococcus isolates from Saudi Arabia. Resistance was observed in lincosamides and tetracyclines, supported by the presence of erm(B) and tet(M). Additional resistance was noted in fluoroquinolones and sulfonamides through gyrB and folP, as well as peptide antibiotics via liaS and mprF. Notably, none of the isolates showed efflux-mediated resistance, as mef(A), msr(D), and tet(K) were absent.