Abstract
Background Fluoroquinolone resistance in Escherichia coli is increasingly associated with the dissemination of high-risk lineages such as ST131. However, data integrating resistance phenotypes with molecular characteristics remain limited in local clinical settings. This study aimed to describe the distribution of ST131 and associated resistance determinants in a single-center cohort.
Methods We analyzed 90 non-duplicate clinical E. coli isolates collected at a tertiary-care hospital in Turkey. Fluoroquinolone resistance was assessed using ciprofloxacin and pefloxacin. Molecular assays targeted phylogenetic groups, ST131 (including H30-Rx), ESBL genes (blaCTX-M with group assignment), plasmid-mediated quinolone resistance (PMQR) markers, and selected virulence genes. ERIC-PCR was used for genotyping and clustering. Comparative analyses were performed between ciprofloxacin-resistant and -susceptible isolates using appropriate categorical and non-parametric tests.
Results Ciprofloxacin resistance was detected in 35/90 isolates (38.9%). Overall, presumptive ST131 (PCR-defined) was identified in 10/90 isolates (11.1%) and was strongly enriched among ciprofloxacin-resistant isolates (25.7% vs. 1.8%, p < 0.001); H30-Rx was also more frequent in ciprofloxacin-resistant isolates (14.3% vs. 1.8%, p = 0.031). CTX-M was detected in 31/90 isolates (34.4%) and was significantly associated with ciprofloxacin resistance (65.7% vs. 14.5%, p < 0.001). Among CTX-M-positive isolates (n = 31), group 1 predominated (87.1%), followed by group 2 (41.9%) and group 9 (6.5%); group 1 + 2 co-detection occurred in 38.7%, and 6.5% remained untypeable. PMQR markers included qnrS (11.1%), qnrB (4.4%), and aac(6′)-Ib-cr (8.9%). Phylogroup B2 was dominant (76.7%). ERIC-PCR identified 59 profiles with high diversity (Simpson’s index 0.9898); 60.0% of isolates belonged to clusters (largest cluster n = 4), indicating high fingerprint diversity inconsistent with a single dominant outbreak clone.
Conclusion Presumptive ST131 isolates were enriched among ciprofloxacin-resistant E. coli in this single-center cohort. These findings reflect local molecular surveillance patterns rather than population-level prevalence. The high ERIC-PCR diversity suggests multiple lineages rather than a single outbreak clone, underscoring the need for sustained molecular surveillance and antimicrobial stewardship.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12879-026-13957-5.
Keywords: Escherichia coli, ST131, H30-Rx, Fluoroquinolone resistance, Ciprofloxacin, CTX-M, PMQR, ERIC-PCR
Introduction
The most prevalent Gram-negative pathogen that causes bloodstream infections and both nosocomial and community-acquired urinary tract infections (UTIs) worldwide is Escherichia coli [1]. Although first-line antibiotics have historically been effective against extraintestinal pathogenic E. coli (ExPEC) strains, the quick development of fluoroquinolone and extended-spectrum cephalosporin resistance has complicated clinical management and reduced treatment options [2].
The spread of certain “high-risk clones” has been a major factor in the epidemiology of multidrug-resistant (MDR) E. coli over the past 20 years. The global spread of CTX-M-type extended-spectrum beta-lactamases (ESBLs) has been attributed in large part to Sequence Type 131 (ST131), which has been identified as a predominant pandemic lineage [3]. In contrast to many other resistant lineages, ST131 strains are usually found in the virulent phylogenetic group B2 and have a special ability to combine multidrug resistance with high virulence potential, which enables them to spread and persist in both community and hospital settings [4].
Allelic differences in the type 1 fimbriae adhesin gene (fimH) and particular chromosomal mutations in the quinolone resistance-determining regions (QRDRs) of gyrA and parC are strongly associated with the evolutionary success of ST131. Globally, the most common cause of fluoroquinolone-resistant E. coli infections is the H30 subclone, which carries the fimH30 allele. Additionally, the production of CTX-M-15 ESBLs is closely linked to a subset of this lineage called the H30-Rx clade, which represents a “perfect storm” of virulence and resistance [5, 6]. These isolates often carry plasmid-mediated quinolone resistance (PMQR) genes, such as qnr determinants and aac(6’)-Ib-cr, which increase resistance levels in addition to chromosomal resistance.
Local epidemiological data are crucial for guiding empirical therapy and infection control strategies. Accordingly, we conducted a single-center descriptive molecular surveillance study to investigate clinical E. coli isolates from a tertiary-care hospital in Rize, Turkey, focusing on (i) ascertaining the distribution of phylogenetic groups among isolates that are resistant to and susceptible to ciprofloxacin; (ii) detecting the presence of the ST131 clone and its H30/H30-Rx subclones; (iii) screening for PMQR and ESBL genes; and (iv) using molecular fingerprinting techniques to examine the isolates’ clonal relationships.
Methods
Study design and ethics
This was a single-center, laboratory-based, retrospective descriptive study conducted at a tertiary-care hospital in Rize, Turkey. All non-duplicate Escherichia coli isolates recovered from routine clinical specimens between May and July 2021 were included. Non-duplicate was defined as one isolate per patient per infection episode. No additional inclusion or exclusion criteria were applied. The study protocol was approved by the Recep Tayyip Erdoğan University Non-Interventional Clinical Research Ethics Committee (12 May 2022; decision no. 2022/118). All procedures were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Declaration of Helsinki and its later amendments.
As this study was based on retrospective analysis of bacterial isolates and anonymized laboratory data, the requirement for informed consent was waived by the Ethics Committee.
Study isolates and identification
A total of 90 Escherichia coli isolates were included (urine, n = 74; blood, n = 10; respiratory specimens, n = 3; wound/abscess samples, n = 2; other specimen types, n = 1). Non-consecutive isolate numbering reflects the exclusion of duplicate or ineligible samples during data curation (Supplementary Table S1). Isolates were identified using routine microbiological methods and stored at − 80 °C in 20% glycerol until analysis.
Antimicrobial susceptibility testing
Antimicrobial susceptibility was determined by the Kirby–Bauer disk diffusion method on Mueller–Hinton agar (Merck, Germany) and interpreted according to EUCAST guidelines (version 11.0, 2021) [7]. For urine isolates, the following antibiotic disks were tested: ampicillin (AMP, 10 µg), piperacillin (PIP, 30 µg), piperacillin/tazobactam (PIP/TZP, 30/6 µg), ampicillin/sulbactam (SAM, 10/10 µg), amoxicillin/clavulanate (AMC, 20/10 µg), cefuroxime (CXM, 30 µg), ceftazidime (CAZ, 10 µg), ceftriaxone (CRO, 30 µg), cefepime (FEP, 30 µg), cefoxitin (FOX, 30 µg), aztreonam (AZT, 30 µg), meropenem (MEM, 10 µg), imipenem (IMP, 10 µg), tigecycline (TIG, 15 µg), gentamicin (GN, 10 µg), amikacin (AK, 30 µg), ciprofloxacin (CIP, 5 µg), pefloxacin (PEF, 5 µg), nitrofurantoin (F, 100 µg), and trimethoprim/sulfamethoxazole (SXT, 1.25/23.75 µg). For non-urine isolates, disks included PIP, PIP/TZP, CAZ, FEP, FOX, MEM, IMP, TIG, GN, AK, CIP, and SXT. Isolates were categorized based on ciprofloxacin and pefloxacin susceptibility testing according to EUCAST interpretive criteria [7]. Escherichia coli ATCC 25,922 was used for quality control.
Phenotypic ESBL detection
Extended-spectrum β-lactamase (ESBL) production was screened by the Double-Disk Synergy Test (DDST) as described by Jarlier et al. (1988) [8]. Briefly, ceftazidime (30 µg), cefotaxime (30 µg), and amoxicillin/clavulanic acid (20/10 µg) disks were placed on Mueller–Hinton agar, following EUCAST recommendations [7]. ESBL production was interpreted as a clear enhancement of the inhibition zone toward the amoxicillin/clavulanic acid disk (clavulanate synergy).
MAR index
The multiple antibiotic resistance (MAR) index was calculated as described by Krumperman (1983) [9]: MAR = A/B, where A is the number of antibiotics to which the isolate is resistant and B is the total number of antibiotics tested. An MAR index > 0.2 was interpreted as suggestive of exposure to high-risk environments with frequent antibiotic use [10].
DNA extraction and PCR assays
Chromosomal DNA was extracted according to Chen and Kuo (1993) [11] and stored at − 20 °C until PCR analysis. All isolates were screened by PCR for the following targets: (i) β-lactamase genes (blaTEM, blaSHV, and blaCTX−M) [12, 13] and blaCTX−M phylogroups (groups 1, 2, 8, and 9) [14]; (ii) plasmid-mediated quinolone resistance (PMQR) determinants (qnrA, qnrB, qnrS, qepA, and aac(6′)-Ib-cr) [15–18]; (iii) virulence-associated genes (sfa, hly, cnf, pap1/2, pap3/4, aer, fimA, afa, iutA, and iroN) [19–22]; and (iv) ST131 lineage and subclone markers (O25b-pabB, trpA, fimH30, and H30-Rx) [23]. PCR products were separated on 1–1.5% agarose gels containing ethidium bromide (0.5 µg/mL) and visualized under UV illumination. Primer sequences, expected amplicon sizes, detailed PCR cycling conditions are provided in original references in Supplementary Table S2.
Phylogenetic grouping
Phylogenetic grouping was performed using the triplex PCR method described by Clermont et al. (2000) [24], enabling assignment to the major phylogroups (A, B1, B2, and D). Primer details for chuA, yjaA, and TspE4.C2 are included in Supplementary Table S2.
ERIC-PCR and cluster analysis.
Clonal relatedness was assessed by ERIC-PCR targeting enterobacterial repetitive intergenic consensus sequences using ERIC1R (5′-ATGTAAGCTCCTGGGGATTCAC-3′) and ERIC2 (5′-AAGTAAGTGACTGGTGAGCG-3′) primers as described by Versalovic et al. (1991) [25]. ERIC-PCR reaction composition, cycling conditions, and electrophoresis procedures followed Ardakani and Ranjbar (2016) [26]. Banding profiles were analyzed in BioNumerics v7.6 (Applied Maths, Sint-Martens-Latem, Belgium). ERIC-PCR profiles were analyzed using the Dice similarity coefficient and UPGMA clustering (optimization 1.5%, band tolerance 2%).
A similarity threshold of ≥ 90% was used as an operational cutoff to define isolates sharing similar ERIC-PCR fingerprint profiles; however, this threshold does not imply confirmed clonal relatedness [27].
Statistical analysis
Statistical analyses were performed using SPSS 25.0. Categorical variables are presented as counts and percentages and were compared using Pearson’s chi-square or Fisher’s exact test, as appropriate. Continuous variables are reported as median (interquartile range) and were compared using the Mann–Whitney U test. All tests were two-sided, and p values < 0.05 were considered statistically significant.
Results
Study isolates
A total of 90 non-duplicate clinical Escherichia coli isolates were included. Most isolates were recovered from urine specimens (n = 74, 82.2%), followed by blood (n = 10, 11.1%), respiratory specimens (n = 3, 3.3%), wound/abscess samples (n = 2, 2.2%), and bile (n = 1, 1.1%) (Table 1).
Table 1.
Specimen distribution of clinical Escherichia coli isolates
| Specimen | n (%) |
|---|---|
| Urine | 74 (82.2) |
| Blood | 10 (11.1) |
| Sputum | 2 (2.2) |
| Tracheal aspirate | 1 (1.1) |
| Abscess | 1 (1.1) |
| Pus | 1 (1.1) |
| Bile | 1 (1.1) |
Antimicrobial susceptibility
Resistance rates for tested agents stratified by specimen category (urine vs. non-urine) are summarized in Table 2. Key microbiological characteristics according to ciprofloxacin susceptibility are provided in Table 3.
Table 2.
Antimicrobial susceptibility of isolates by specimen category (disk diffusion; EUCAST v11.0)
| Antibiotic | Urine (n = 74) Susceptible n (%) | Urine (n = 74) Resistant n (%) | Non-urine (n = 16) Susceptible n (%) | Non-urine (n = 16) Resistant n (%) |
|---|---|---|---|---|
| AMP | 33 (44.6) | 41 (55.4) | — | — |
| PIP | 35 (47.3) | 39 (52.7) | 5 (31.2) | 11 (68.8) |
| PIP/TZP | 66 (89.2) | 8 (10.8) | 9 (56.2) | 7 (43.8) |
| SAM | 55 (74.3) | 19 (25.7) | — | — |
| AMC | 50 (67.6) | 24 (32.4) | — | — |
| CXM | 49 (66.2) | 25 (33.8) | — | — |
| CAZ | 50 (67.6) | 24 (32.4) | 7 (43.8) | 9 (56.2) |
| CRO | 50 (67.6) | 24 (32.4) | — | — |
| FEP | 50 (67.6) | 24 (32.4) | 9 (56.2) | 7 (43.8) |
| FOX | 74 (100.0) | 0 (0.0) | 15 (93.8) | 1 (6.2) |
| AZT | 50 (67.6) | 24 (32.4) | — | — |
| MEM | 74 (100.0) | 0 (0.0) | 16 (100.0) | 0 (0.0) |
| IMP | 74 (100.0) | 0 (0.0) | 16 (100.0) | 0 (0.0) |
| TIG | 74 (100.0) | 0 (0.0) | 16 (100.0) | 0 (0.0) |
| GN | 65 (87.8) | 9 (12.2) | 15 (93.8) | 1 (6.2) |
| AK | 74 (100.0) | 0 (0.0) | 16 (100.0) | 0 (0.0) |
| CIP | 48 (64.9) | 26 (35.1) | 7 (43.8) | 9 (56.2) |
| PEF | 74 (100.0) | 0 (0.0) | — | — |
| F | 74 (100.0) | 0 (0.0) | — | — |
| SXT | 49 (66.2) | 25 (33.8) | 10 (62.5) | 6 (37.5) |
Ampicillin, AMP; Piperacillin, PIP; Piperacillin/tazobactam, PIP/TZP; Ampicillin/sulbactam, SAM; Amoxicillin/clavulanate, AMC; Cefuroxime, CXM; Ceftazidime, CAZ; Ceftriaxone, CRO; Cefepime, FEP; Cefoxitin, FOX; Aztreonam, AZT; Meropenem, MEM; Imipenem, IMP; Tigecycline, TIG; Gentamicin, GN; Amikacin, AK; Ciprofloxacin, CIP; Nitrofurantoin, F; Trimethoprim/sulfamethoxazole, SXT; Antibiotics not tested for non-urine isolates are indicated by ‘—‘
Table 3.
Key microbiological characteristics by ciprofloxacin susceptibility
| Characteristic | Overall (n = 90) | CIP-R (n = 35) | CIP-S (n = 55) | p value |
|---|---|---|---|---|
| Urine source | 74/90 (82.2) | 26/35 (74.3) | 48/55 (87.3) | 0.116 |
| Phylogroup B2 | 69/90 (76.7) | 30/35 (85.7) | 39/55 (70.9) | 0.105 |
| CTX-M detected | 31/90 (34.4) | 23/35 (65.7) | 8/55 (14.5) | < 0.001 |
| ST131 | 10/90 (11.1) | 9/35 (25.7) | 1/55 (1.8) | < 0.001 |
| H30-Rx (among all isolates) | 6/90 (6.7) | 5/35 (14.3) | 1/55 (1.8) | 0.031 |
| qnrS | 10/90 (11.1) | 2/35 (5.7) | 8/55 (14.5) | 0.305 |
| qnrB | 4/90 (4.4) | 1/35 (2.9) | 3/55 (5.5) | 1.000 |
| aac(6′)-Ib-cr | 8/90 (8.9) | 4/35 (11.4) | 4/55 (7.3) | 0.706 |
| MAR index > 0.2 | 42/90 (46.7) | 31/35 (88.6) | 11/55 (20.0) | < 0.001 |
| MAR index, median (IQR) | 0.15 (0.00–0.42) | 0.42 (0.32–0.54) | 0.00 (0.00–0.15) | < 0.001 |
Fluoroquinolone resistance and MAR index
Based on ciprofloxacin susceptibility, 35/90 isolates (38.9%) were classified as ciprofloxacin-resistant (CIP-R) and 55/90 (61.1%) as ciprofloxacin-susceptible (CIP-S) (Table 3). An MAR index > 0.2 was observed in 42/90 isolates (46.7%) and was significantly more common among CIP-R than CIP-S isolates (88.6% vs. 20.0%, p < 0.001) (Fig. 1; Table 3). The maximum MAR index was 0.68 (Supplementary Table S1).
Fig. 1.
Distribution of the multiple antibiotic resistance (MAR) index by ciprofloxacin susceptibility (CIP-R vs. CIP-S). The dashed horizontal line indicates the MAR index threshold of 0.2
Phylogenetic grouping
Phylogroup B2 predominated (n = 69, 76.7%), followed by group D (n = 16, 17.8%), B1 (n = 3, 3.3%), and A (n = 2, 2.2%) (Table 3).
Resistance determinants
CTX-M genes were detected in 31/90 isolates (34.4%) and were significantly associated with ciprofloxacin resistance (CIP-R: 65.7% vs. CIP-S: 14.5%, p < 0.001) (Table 3). Among CTX-M-positive isolates (n = 31), group 1 was most common (n = 27, 87.1%), followed by group 2 (n = 13, 41.9%) and group 9 (n = 2, 6.5%); co-detection of group 1 and group 2 occurred in 12/31 isolates (38.7%) (Supplementary Table S2). Two isolates were positive with universal blaCTX-M primers but negative in group-specific assays and were classified as CTX-M untyped. Detailed distributions of resistance-associated genes are presented in Supplementary Table S3.
ST131 lineage
The presumptive ST131 (PCR-defined) lineage was identified in 10/90 isolates (11.1%) and was enriched among CIP-R isolates (25.7% vs. 1.8%, p < 0.001) (Table 3; Supplementary Table S4). Among presumptive ST131 isolates, 6/10 (60.0%) were classified as H30-Rx (Table 3; Supplementary Table S4).
Virulence genes
The most frequently detected virulence-associated genes were fimA (n = 78), iutA (n = 49), aer (n = 42), and iroN (n = 38) (Supplementary Table S5). The median number of virulence genes per isolate was 3.00 (IQR 1.00–4.00) and did not differ significantly between CIP-R and CIP-S isolates (3.00 (2.00–4.00) vs. 2.00 (1.00–4.00); p = 0.115) (Table 3).
ERIC-PCR typing
ERIC-PCR identified 59 distinct profiles among 90 isolates, indicating high genetic diversity (Simpson’s index of diversity 0.9898) (Fig. 2; Supplementary Table S6). Thirty-six profiles were singletons, whereas 54 isolates (60.0%) belonged to clusters (group size > 1); the largest cluster size was n = 4 (groups: G15 and G51) (Fig. 2; Supplementary Table S6). Piperacillin/tazobactam resistance was more frequent among singleton than clustered isolates (27.8% vs. 9.3%, p = 0.021), whereas ciprofloxacin resistance and CTX-M detection did not differ significantly by clustering status (Supplementary Table S7).
Fig. 2.
ERIC-PCR dendrogram of clinical Escherichia coli isolates. Clustering was performed using the Dice similarity coefficient and the UPGMA algorithm. A ≥ 90% similarity threshold was used as an operational cutoff to define shared ERIC-PCR fingerprint profiles
Discussion
In this single-center descriptive study, we observed a clear enrichment of presumptive ST131 isolates among ciprofloxacin-resistant E. coli. These findings should be interpreted within the context of a limited sample size and a short sampling period and therefore primarily reflect local molecular surveillance data rather than broader epidemiological trends.
Ciprofloxacin resistance was common (38.9%) and was associated with broader multidrug resistance. CIP-R isolates had markedly higher MAR index values than CIP-S isolates (Fig. 1; Table 3), consistent with a higher overall resistance burden among ciprofloxacin-resistant isolates.
These findings are compatible with recent European surveillance reports showing substantial and geographically heterogeneous fluoroquinolone resistance in invasive Escherichia coli, with higher resistance levels reported in southern parts of the WHO European Region [28, 29]. Local molecular data remain essential for empirical therapy and stewardship decisions.
ST131 accounted for 11.1% overall but was enriched among CIP-R isolates (25.7% in CIP-R vs. 1.8% in CIP-S; Table 3). Most ST131 isolates were H30-Rx (60.0%) (Table 3; Supplementary Table S4), a sublineage previously associated with global dissemination, fluoroquinolone resistance and ESBL carriage [30–32].
The observed association between CTX-M positivity and ciprofloxacin resistance likely reflects co-occurrence within multidrug-resistant lineages rather than a direct causal relationship. CTX-M group 1 predominated, and group 1 plus group 2 co-detection was frequent (Supplementary Table S4), consistent with the global dominance of CTX-M group 1 in ExPEC epidemiology [33].
Two isolates were positive with universal blaCTX−M primers but negative in group-specific assays and were classified as CTX-M untyped. This may reflect less common CTX-M variants, primer mismatch, or lower template quality; targeted sequencing would resolve the underlying allele(s) and strengthen inference.
PMQR determinants were detected at low-to-moderate frequency but were not enriched among ciprofloxacin-resistant isolates, suggesting that they may act as facilitators rather than primary drivers of resistance in this cohort (Table 3; Supplementary Table S4). PMQR elements can raise quinolone MICs modestly and promote stepwise selection of higher-level chromosomal resistance under antibiotic pressure [34].
ERIC-PCR analysis demonstrated high fingerprint diversity (59 profiles; Simpson’s diversity index 0.9898), which is inconsistent with a single dominant outbreak clone (Fig. 2; Supplementary Table S7). Although 60.0% of isolates were assigned to clusters, the largest cluster included only four isolates. These findings suggest genetic heterogeneity within the study population; however, given the limited resolution of ERIC-PCR, the results should be interpreted as fingerprint-based clustering rather than definitive evidence of clonal relatedness or transmission pathways. Resistance patterns appeared to be broadly distributed across fingerprint profiles; the observed difference in piperacillin/tazobactam resistance between singleton and clustered isolates should be interpreted cautiously due to small sample sizes.
A major limitation of this study is the absence of sequencing of quinolone resistance-determining regions (QRDRs), including gyrA and parC, which are known to be the primary determinants of high-level fluoroquinolone resistance, particularly in ST131/H30 lineages. Therefore, the molecular basis of ciprofloxacin resistance could not be directly assessed, and the contribution of chromosomal mutations versus plasmid-mediated mechanisms could not be distinguished. Future studies incorporating QRDR sequencing or whole-genome sequencing are required to clarify the genetic basis of resistance and to validate subclone classification. Limitations include the single-center design and short sampling window. In addition, ERIC-PCR was used instead of whole-genome sequencing for assessing genetic relatedness and plasmid characterization. Future work incorporating WGS would better resolve ST131 subclades, mobile genetic elements, and transmission routes, and would clarify the genetic basis of CTX-M untyped isolates.
Taken together, our findings suggest an association between ciprofloxacin resistance, multidrug resistance, and the presence of CTX-M enzymes and high-risk lineages such as ST131 in this local clinical setting.
Conclusion
In conclusion, this single-center study demonstrates an enrichment of presumptive ST131 isolates among ciprofloxacin-resistant E. coli within a local clinical setting. These findings highlight the co-occurrence of multidrug resistance and high-risk lineages; however, mechanistic inferences are limited by the absence of QRDR sequencing and high-resolution genomic analysis. Continued molecular surveillance incorporating whole-genome approaches is needed to better define resistance mechanisms and transmission dynamics.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
Use of artificial intelligence tools: Large language model assistance (ChatGPT, OpenAI) was used for English language editing and stylistic suggestions. All scientific content, data interpretation, and conclusions were determined and verified by the authors, who take full responsibility for the manuscript.
Abbreviations
- DDST
Double-disc synergy test
- ERIC-PCR
Enterobacterial repetitive intergenic consensus polymerase chain reaction
- ESBL
Extended-spectrum beta lactamase
- EUCAST
European committee on antimicrobial susceptibility testing
- ExPEC
Extraintestinal pathogenic E. coli
- MAR
Multiple antibiotic resistance index
- MDR
Multiple drug resistance
- PMQR
Plasmid mediated quinolone resistance
- QRDR
Quinolone resistance determining region
- UTI
Urinary tract infections
Author contributions
ER: Research, Experimental studies, Verification, Writing-Original Draft, References, Writing-Review & Editing. MO: Research, Experimental studies, Writing-Original Draft. NE: Research, Experimental studies. OA: Dendogram analysis, evaluation and interpretation. OBO: Project management, Conceptualization, Formal analysis, Writing-Original Draft, Writing-Revision & Editing.
Funding
This work was financially supported by the Recep Tayyip Erdogan University Scientific Research Projects Coordination Unit (Project Number TTU-2022-1386).
Data availability
The datasets generated and analysed during the current study are available in the Zenodo repository: https://doi.org/10.5281/zenodo.18465113.
Declarations
Ethics approval
This study was approved by the Recep Tayyip Erdoğan University Faculty of Medicine Non-Interventional Research Ethics Committee (Date: 12/05/2022, Decision number: 2022/118). All procedures were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Declaration of Helsinki and its later amendments. As this study was based on retrospective analysis of bacterial isolates and anonymized laboratory data, the requirement for informed consent was waived by the Ethics Committee.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated and analysed during the current study are available in the Zenodo repository: https://doi.org/10.5281/zenodo.18465113.