https://orcid.org/0009-0007-8345-5666
Figures
Abstract
Background
Pseudomonas aeruginosa remains a major cause of hospital- and community-acquired infections, with increasing ciprofloxacin resistance driven by mutations in quinolone resistance–determining regions (QRDRs) and plasmid-mediated mechanisms. This study aimed to determine the prevalence of key virulence genes (oprI, toxA, lasB, nan1) and ciprofloxacin resistance determinants (gyrA, parC, qnrA, qnrB, qnrS) in clinical isolates from Khartoum State, Sudan, and to explore associations with demographic and clinical variables.
Methods
This cross-sectional study, which was conducted from January to April 2023, included eighty-six clinical isolates of P.aeruginosa that were collected from various hospitals in Khartoum State. The isolates were reidentified via standard microbiological techniques, and DNA was extracted via the boiling method. Multiplex polymerase chain reaction was utilized to detect the presence of virulence and ciprofloxacin resistance genes. Data analysis was performed via IBM SPSS software (version 20).
Results
All the isolates carried one or more virulence genes, with oprI being the most prevalent (88.4%), followed by lasB (80.2%), toxA (57%), and nan1 (6.98%). Among the isolates, 30 (34.9%) were resistant to ciprofloxacin, whereas 56 (65.1%) were susceptible. All resistant isolates carried at least one of the resistance genes studied. The parC gene was the most prevalent (40.7%), followed by gyrA (20.9%) and qnrS (19.8%). qnrA and qnrB each had a prevalence of 17.4%. This investigation revealed the coexistence of the gyrA and parC genes in seven isolates (23.3%), and we also reported that the qnrA, qnrB, and qnrS genes coexisted in 11 (36.7%) of the ciprofloxacin resistant P. aeruginosa isolates. A significant association was detected between ciprofloxacin resistance and the presence of the gyrA, qnrS, qnrA, and qnrB genes (p < 0.001) but not the parC gene (p = 0.6). There was no significant association between ciprofloxacin resistance genes and virulence genes (p > 0.05).
Conclusions
The prudent use of ciprofloxacin is vital in managing P.aeruginosa infections amid rising resistance. Detection of gyrA and parC in susceptible isolates signals potential for future resistance through future mutations, highlighting the need for ongoing monitoring. The coexistence of resistance and virulence genes highlights the pathogen’s combined threat. These findings reinforce the public health importance of continuous molecular surveillance and genetic profiling, not only to guide effective treatment but also to inform targeted infection control strategies and antimicrobial stewardship programs.
Citation: Abdallah ASI, Mohamed O, Merghani MM, Abdalla Ali M (2025) Molecular genetic portrait of virulence and ciprofloxacin resistance genes in clinical Pseudomonas aeruginosa Isolates from Khartoum, Sudan. PLoS One 20(10): e0335269. https://doi.org/10.1371/journal.pone.0335269
Editor: Hope Onohuean, Kampala International University - Western Campus, UGANDA
Received: April 25, 2025; Accepted: October 8, 2025; Published: October 31, 2025
Copyright: © 2025 Abdallah et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations:: P. aeruginosa, Pseudomonas aeruginosa; QRDR, Quinolone Resistance Determining Region; PMQR, Plasmid-mediated quinolone resistance; DNA, Deoxyribonucleic Acid; PCR, polymerase chain reaction
Introduction
Pseudomonas aeruginosa is a Gram-negative bacterium commonly found in places like soil and water, as well as on hospital surfaces and medical devices [1]. Although it rarely causes illness in healthy people, it can pose a serious risk to those with weakened immune systems. P. aeruginosa is a common source of serious healthcare-associated infections such as ventilator-acquired pneumonia, urinary tract infections, bloodstream infections, and surgical wound infections.
P. aeruginosa can be particularly dangerous for people with cystic fibrosis because it often causes long-lasting lung infections that are hard to treat, making it harder for patients to stay healthy and impacting their overall quality of life and long-term outlook. Its ability to quickly develop resistance to many antibiotics makes managing these infections even more challenging for doctors. It occurs through a variety of mechanisms, including biofilm formation, active efflux pumps, and the production of drug-inactivating enzymes [1]. What makes things even more complicated is P. aeruginosa’s genetic flexibility, which means it can easily pick up new resistance genes including those that cause resistance to fluoroquinolones such as ciprofloxacin, like mutations in gyrA and parC [2]. This makes treating these infections even more challenging. These features have led to its classification as a critical-priority pathogen by global health authorities, emphasizing the urgent need for improved infection control measures and novel therapy alternatives [1,3]
In P.aeruginosa, ciprofloxacin resistance arises through three main mechanisms: mutations in quinolone resistance-determining regions (QRDRs), such as DNA gyrase (gyrA) and topoisomerase IV (parC); increased membrane permeability due to the upregulation of efflux pumps; and the presence of plasmid-mediated quinolone resistance genes (PMQRs) [2]. PMQR includes various mechanisms, such as quinolone resistance proteins (encoded by qnr genes such as qnrA, qnrB, qnrC, qnrD, and qnrS), which protect DNA gyrase and topoisomerase IV from the effects of fluoroquinolones (FQs) [4].
The pathogenicity of P.aeruginosa is due to various extracellular and cell-associated virulence factors. Examples of genes that encode and contribute to these virulence factors include toxA, oprI, lasB, and nan1. Exotoxin A, encoded by the toxA gene, inhibits protein production in host cells and generates redox-active phenazines that are toxic to human cells. [5]. The lasB gene encodes elastase B, a zinc-dependent metalloprotease that plays a key role in the virulence of P. aeruginosa. The presence of lasB is commonly associated with increased tissue damage and immune system evasion, contributing significantly to the pathogen’s ability to cause severe infections. Its activity supports the persistence and spreads of P. aeruginosa in both acute and chronic infections, making it a critical factor in the organism’s pathogenic profile [6]. Neuraminidase, produced by the nan1 gene, aids in bacterial adhesion to epithelial cells. Additionally, the oprI genes in the outer membrane facilitate the efficient detection of Pseudomonas aeruginosa. [7].
Key virulence genes (oprL, oprI, lasB, toxA, nan1) and resistance genes (gyrA, parC, qnrA, qnrB, qnrS) were chosen because of their well-known importance in clinical settings. The selected virulence genes play roles in helping the bacteria evade the immune system, cause tissue damage, and establish infections in the body. The resistance genes, on the other hand, are linked to either chromosomal mutations or plasmid-mediated mechanisms that give the bacteria resistance to ciprofloxacin. Their inclusion was also driven by the limited molecular data available on P. aeruginosa isolates from Sudan. By studying these isolates, this work aims to help fill that gap and shed light on the local patterns of virulence and resistance genes.
We hypothesized that clinical isolates of Pseudomonas aeruginosa from Khartoum would carry a variety of virulence and ciprofloxacin resistance genes. We also thought that ciprofloxacin resistance would be tied to certain resistance genes, and that the presence of virulence genes might also have an impact possibly making these bacteria more capable of causing disease. Additionally, we aimed to identify the most prevalent virulence and ciprofloxacin resistance genes in all P.aeruginosa isolates. Given what’s been shown in previous studies and what we found, we expected that virulence genes wouldn’t have a strong link to resistance.
The purpose of this study was to detect and determine the prevalence of virulence genes (toxA, lasB, nan1, and oprI), as well as resistance genes (gyrA, parC, qnrA, qnrB, and qnrS), and to determine whether there is an association between ciprofloxacin resistance and the detection of resistance and virulence genes in P. aeruginosa strains.
Materials and methods
Study design and sample collection
This study was a descriptive cross-sectional study of P. aeruginosa isolates isolated from various clinical samples, including urine, wound swabs, sputum, ear swabs, blood cultures, tracheal aspirates, eye swabs, pus, cough swabs, and tissue and body fluid samples collected between
January 2023 and April 2023 from hospitals in Khartoum State, Sudan. Only non-duplicate P. aeruginosa isolates from both hospitalized patients and outpatients were included. Isolates were confirmed as P. aeruginosa using standard biochemical tests. The sampling period may have been influenced by environmental factors that affect the prevalence and resistance patterns of bacterial pathogens. Samples were included regardless of the infection site to ensure a broad representation of circulating strains. Environmental samples, surveillance specimens, repeat isolates from the same patient, and isolates lacking essential metadata (e.g., source or antibiotic susceptibility profile) were excluded.
Phenotypic characterization
A standard scheme for identifying all Pseudomonas aeruginosa strains was used [8]. Clinical isolates of P. aeruginosa were subcultured on nutrient agar and MacConkey agar, then incubated at 37°C for 24 hours to ensure purity and optimal growth.
Gram-negative bacteria were isolated, and non-lactose fermenting organisms were distinguished via MacConkey agar media. Colonial morphology and pigment formation were distinguished on nutrient agar. Gram-negative rods with positive oxidase tests were identified via conventional biochemical tests (KIA, urease, citrate, motility and indole). All these reagents were imported from Oxoid (Bactident Co.). [8]
Antimicrobial susceptibility testing
Ciprofloxacin (5 μg) susceptibility testing was performed on all the verified P. aeruginosa isolates. It was examined on Mueller‒Hinton agar via the Kirby‒Bauer disk diffusion method. We placed ciprofloxacin disks on each inoculated Mueller‒Hinton agar plate and incubated them at 37°C for 24 hours. The plates were examined for zones of inhibition around the disk. These strains were evaluated and compared to an interpretation table to determine sensitive and resistant strains. [8]
Multiplex PCR for the detection of virulence genes (toxA, oprI, nan1 and lasB) and antibiotic resistance genes (gyrA, parC, qnrA, qnrB & qnrS)
DNA extraction.
Bacterial DNA was extracted from pure cultures of P. aeruginosa isolates via the boiling method. Briefly, 2–3 colonies of a pure culture of P. aeruginosa were suspended in 50 µL of nuclease-free water. The suspension was heated to 95°C for 10 minutes, incubated at −20°C for 10 minutes, and then centrifuged at 10,000 rpm for 5 minutes. 5 µL of the supernatant was used as a template in the PCR assay [9].
Multiplex PCR for detection of virulence and resistance genes.
Multiplex PCR was conducted to confirm the presence of P. aeruginosa resistance and virulence genes via specific primers in three tubes: first, toxA, oprI, nan1 and lasB; second, gyrA and parC; and finally, qnrA, qnrB and qnrS. The reaction mixture was 20 μl in total, containing 4 μl of a mixture with Taq polymerase, reaction buffer, MgCl₂, and dNTPs (Solis Biodyne, Estonia), 1 μl each of forward and reverse primers (10 pmol/μl) for the target genes, 5 μl of DNA template, and water to reach a final volume of 20 μl. PCR was performed with the following thermal cycling conditions: initial denaturation at 95°C for 5 minutes; 35 cycles of denaturation at 95°C for 1 minute, annealing at 60°C for 1 minute, and extension at 72°C for 1 minute; followed by a final extension at 72°C for 5 minutes.. The PCR products were analysed using agarose gel electrophoresis, stained with ethidium bromide visualized under UV light, and compared to a 100 bp DNA ladder using the Bio-Rad Gel Doc System. The National Public Health Laboratory (NPHL), Department of Microbiology, Sudan, prepared and provided a mixed positive control consisting of known P. aeruginosa strains harboring target resistance and virulence genes. To ensure assay specificity and rule out contamination, each PCR run included both a positive control and a no-template negative control. These controls were essential for validating the accuracy and reliability of the amplification results. The primers used for each gene are listed in Table 1 and Table 2.
Statistical analysis
All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM Corp., Armonk, NY), selected for its reliability and suitability for categorical data analysis and logistic regression. The chi-square test was applied to assess associations between categorical variables, such as the presence of resistance or virulence genes and ciprofloxacin susceptibility. To address the issue of multiple testing, we applied the Benjamini–Hochberg false discovery rate (FDR) correction, setting the significance threshold (Q) at 0.05. We reported FDR-adjusted p-values and considered any results with adjusted p-values less than 0.05 to be statistically significant.
We described the distribution of resistance and virulence genes, as well as CIP susceptibility, using basic descriptive statistics. For categorical variables, we reported frequencies and percentages. To better understand the findings, we calculated odds ratios (ORs) with 95% confidence intervals (CIs) as our measure of effect size. However, for genes that were extremely rare or had the same result across all samples (like the qnr genes), we reported relative risks (RRs) instead. To explore things in more depth, we built a multivariable binary logistic regression model to examine the independent effects of specific genes on CIP resistance. We included all genes that showed enough variability. Results are shown as FDR-adjusted p-values, together with the corresponding ORs and 95% CIs. Genes that were only present in CIP-resistant isolates and absent in all sensitive ones couldn’t be included, since it wasn’t possible to statistically model their effects.
Ethics statement
This study was approved by the Ethical Review Committee at the National University Biomedical Research Institute in Khartoum, Sudan (Approval Number: NU-RECG276) in January 2023. The research was originally titled “Genetic Portrait of Virulence and Resistance in Pseudomonas aeruginosa Isolates from Khartoum, Sudan.” The title was later updated to “ Molecular Genetic Portrait of Virulence and Ciprofloxacin Resistance Genes in Clinical Pseudomonas aeruginosa Isolates from Khartoum, Sudan “ to enhance clarity and specificity. We obtained written informed consent from all adult participants and from parents or legal guardians for minors before the study began. The research followed the principles of the Declaration of Helsinki. Participation was voluntary, with samples collected as part of routine clinical care and minimal risk to participants. We took care to maintain strict confidentiality for everyone involved.
Result
A total of 86 non duplicate P. aeruginosa isolates were collected from different clinical samples in several hospitals throughout Khartoum State, Sudan. Most of these isolates came from urine samples (31 cases, 36.0%), followed by wound swabs (17 cases, 19.7%), sputum samples (12 cases, 14.0%), and ear swabs (9 cases, 10.5%). The remaining isolates were obtained from blood, tracheal aspirates, eye swabs, pus, and tissue samples (see Table 3).Regarding hospital distribution, Soba University Hospital contributed the highest number of isolates (n = 59, 68.6%), followed by Fedail Hospital (n = 9, 10.5%), Royal Hospital (n = 6, 7.0%), and other participating hospitals, including Military, Bahri, and Alribat (Table 4). The samples were collected from a variety of hospital units, with the largest share coming from the Intensive Care Unit (ICU) and its different sections. In total, 33 isolates (38.4%) were from the general ICU, 15 (17.4%) from the male ICU, and 5 (5.8%) from the ICU specializing in respiratory therapy. The outpatient departments contributed 13 isolates (15.1%), while 7 (8.1%) came from the Emergency Room. Additional isolates were gathered from the Neonatal Intensive Care Unit (NICU), Pediatric Unit, and surgical wards (see Table 5).
Ciprofloxacin susceptibility patterns
A total of 86 P.aeruginosa samples were tested to see how they responded to ciprofloxacin. Out of these, 30 samples (34.9%) showed resistance to the antibiotic, while 56 (65.1%) were still susceptible. The samples were collected from both male (50) and female (36) patients.
Association with patient gender
This study examined whether there was a connection between a patient’s gender and their resistance to ciprofloxacin. While resistance was a bit more common among male patients (60%) than female patients (40%), this difference wasn’t statistically significant (P = 0.798). More details about the distribution and odds ratio can be found in Table 6.
Association with Hospital units
A significant association was found between hospital unit and ciprofloxacin (CIP) resistance among Pseudomonas aeruginosa isolates (p = 0.015) (Table 7). The highest proportion of ciprofloxacin-sensitive isolates was recovered from the ICU (35.7%) and the outpatient unit (23.2%), while ciprofloxacin-resistant strains were predominantly found in the ICU (43.3%) and ICU-M (30.0%). Notably, no ciprofloxacin-resistant isolates were observed in the emergency room (ER), outpatient (OUT), pediatric, or operating room (OR) units. Conversely, resistant strains were identified in ICU subunits such as ICU-ERP (6.7%), ICU-RT (10.0%), ICU-CNT (3.3%), and PICU-RT (3.3%), suggesting a concentration of resistance in intensive and critical care settings.
Multiplex PCR for virulence gene detection
All the isolates possessed one or a combination of virulence genes, except for one isolate Fig 1. OprI was the most prevalent virulence gene; it was detected in 76 (88.4%) of the isolates; the lasB gene was detected in 69 (80.2%) isolates; the toxA gene was detected in 49 (57%) isolates; and the nan 1 gene was detected in 6 (6.98%) isolates. (Fig 2). Representative amplification results are shown in Fig 1.
Multiplex PCR for resistance gene detection
Multiplex PCR was performed to detect QRDR genes in P. aeruginosa isolates. The amplified products of the gyrA and parC genes (194 bp and 395 bp, respectively) are shown in Fig 3. Similarly, amplification of the qnrA (516 bp), qnrB (476 bp), and qnrS (428 bp) genes is demonstrated in Fig 4. All the isolates that were resistant to ciprofloxacin harboured either one or a mixture of resistance genes.
Among all the 86 P. aeruginosa isolates, parC was the most prevalent resistance gene, detected in 35 isolates (40.7%), followed by gyrA in 18 isolates (20.9%), qnrS in 17 isolates (19.8%), and both qnrA and qnrB in 15 isolates each (17.4%) as demonstrated in Fig 5.
This investigation revealed the coexistence of the gyrA and parC genes in seven (23.3%) of the P.aeruginosa isolates. We also found that the PMQR genes under study (gnrA, qnrB, and qnrS) coexisted in 11 (36.7%) of all P. aeruginosa isolates.
Association between resistance genes and ciprofloxacin resistance
After performing Pearson’s chi-square test, followed by Benjamini–Hochberg (FDR) correction with a significance threshold set at Q = 0.05 for the possibility of false positives, we found that the genes gyrA, qnrA, qnrB, and qnrS were all strongly associated with CIP resistance(P < 0.001 for all). These associations remained significant even after further statistical corrections, indicating a strong connection between these genes and resistance to the ciprofloxacin. In contrast, we did not find any significant link between the parC gene and CIP resistance (P = 0.600). More detailed data and effect estimates can be found in Tables 8 and 9.
Logistic regression analysis of gene associations with ciprofloxacin resistance
Logistic regression was used to assess the association between individual genes and ciprofloxacin (CIP) resistance. After applying Benjamini–Hochberg correction for multiple comparisons (FDR), only gyrA remained statistically significant (adjusted P < 0.001), showing a strong association with resistance (OR = 33.535; 95% CI: 5.974–188.237) as illustrated in Table 10. None of the tested virulence genes (toxA, lasB, nan1, and oprI) showed a statistically significant association with CIP resistance (adjusted P > 0.05). The genes qnrA, qnrB, and qnrS were excluded from the logistic regression analysis due to lack of variability; they were absent in all CIP-sensitive isolates (100%), preventing model estimation.
Distribution of resistance and virulence genes by sample type
The types of resistance and virulence genes we found in P. aeruginosa depended on where the samples came from (Table 11). In urine samples—the largest group in our study—the most common virulence genes were oprI (23.5%), lasB (20.0%), and toxA (13.0%), The nan1 gene was present at a lower frequency (3.5%). while parC (11.3%), gyrA (10.4%), and qnrA (7.0%) were the main resistance genes.
For wound swabs, lasB (30.8%), oprI (26.9%), and toxA (21.2%) were again the most frequently found virulence genes, resistance genes were much less common in wound swabs. parC was the most frequently detected (11.5%), while gyrA was found in 3.8% of isolates. The plasmid-mediated resistance genes qnrA, qnrB, and qnrS were each detected in only 1.9% of isolates.
Sputum samples also had virulence genes, especially lasB (24.4%), oprI (22.2%), and toxA (20.0%). Resistance genes such as gyrA (4.4%) and parC (11.1%) were detected, with qnrA and qnrB each appearing in 6.7% of isolates, and qnrS in 4.4%.
Other sample types—including blood, tracheal aspirates, eye swabs, pus, tissue, body fluids, and cough swabs—showed a variable distribution of resistance and virulence genes. Among these, oprI, lasB, and toxA were detected sporadically across most sample types, with the highest frequencies observed in eye swabs (oprI 40.0%) and fluids (oprI and lasB, each 50.0%). The nan1 gene was generally absent in these samples, except for tracheal aspirates (8.3%) and blood (6.2%). Qnr genes were largely absent or rare in these samples: they were entirely undetected in blood, eye swabs, fluids, pus, and tissue samples, and appeared only occasionally in tracheal aspirates (qnrB and qnrS, each 8.3%) and RF samples (qnrB and qnrS, each 20.0%).
Discussion
This study offers a detailed examination of the prevalence and distribution of virulence and ciprofloxacin resistance genes in clinical P. aeruginosa isolates and their implications for ciprofloxacin resistance.
The oprI gene had been identified in 88.4% of our isolates, which is in line with previous studies reporting prevalence rates between 55% and 91.1% [14,15]. This range of results might be due to differences in location, the types of clinical samples, or the diagnostic methods used to determine the gene. Still, the fact that oprI is consistently found at high rates shows that it is a common and conserved virulence factor in P. aeruginosa.
In our investigation, 80.2% of isolates had the lasB gene, which is a bit lower than the rates seen in earlier studies (93.3% to 100%) [16,17]. These differences could be due to variations in where the isolates came from, differences in the patient population, or environmental factors that affect how the gene is expressed and maintained. Even so, the high detection rate in our study highlights how important elastase B is in the pathogenicity of P. aeruginosa.
For the toxA gene, the 57% prevalence observed is in line with some studies that reported higher rates (92% and 69.4%) [17,18] but contrasts with reports that reported lower rates (15% and 32.4%) [14,15]. This variability highlights the complexity of P. aeruginosa pathogenicity and underscores the need for standardized approaches in gene prevalence reporting.
6.98% of the isolates demonstrated the nan1 gene, so it’s significantly lower than the prevalence reported by Hassan Abdulaali Al-Saeedi et al. [19]. This difference may be due to regional, patient, or methodological factors. The presence of multiple virulence factors in a single isolate supports the notion that P. aeruginosa can harbor several virulence determinants, increasing its pathogenic potential [17,18]. However, it is important to interpret these findings with caution, particularly those involving rare genes such as nan1. Because there were only a few isolates in these subgroups, our analyses may not have had sufficient statistical power, and other factors may still be influencing the results. Future studies with larger and more diverse samples will be necessary to confirm these findings and gain a deeper understanding of the clinical significance of these rare genetic markers
The observed ciprofloxacin resistance rate of 34.9% aligns with several studies (44.19%, 41.37%, and 59.4%) [20–22] but contrasts with the lower resistance rate (20.6%) reported in a previous Sudanese study and the significantly higher rate (97%) reported in another study [23,24]. This variability reflects the dynamic nature of antimicrobial resistance and suggests that local factors and differences in study design may play a role. In our study, gender was not significantly associated with ciprofloxacin resistance in P.aeruginosa (p = 0.798), with an odds ratio of 0.889 (95% CI: 0.361–2.191). These findings are consistent with previous research indicating that gender does not independently predict resistance in P. aeruginosa infections [25]. Antimicrobial resistance in P. aeruginosa is more commonly influenced by antibiotic exposure history, genetic resistance determinants, and hospital-acquired factors rather than patient demographics [26]. However, further large-scale studies are warranted to explore potential gender-specific trends in resistance patterns.
We noticed a strong connection between the hospital unit and ciprofloxacin resistance in P.aeruginosa isolates (p = 0.015). Resistance was most common in intensive care units, with the main ICU showing 43.3% and the male ICU 30.0% of strains resistant to ciprofloxacin. On the other hand, we didn’t find any resistant strains in the emergency room, outpatient clinics, pediatric, or operating room units. It’s not surprising to see resistance clustering in critical care settings, since these areas often involve more invasive treatments, frequent use of broad-spectrum antibiotics, and longer hospital stays all of which can encourage resistance to develop. Our findings are in line with local studies showing that P. aeruginosa from hospital-acquired infections in Sudan tends to be more resistant than strains picked up in the community. For example, Omer et al. [23] found that isolates from diabetic wound infections in two Khartoum hospitals were often resistant to ciprofloxacin and other antibiotics, highlighting just how common resistant strains are in clinical settings.
Finding resistant strains in different ICU subunits—such as ICU-ERP, ICU-RT, ICU-CNT, and PICU-RT—shows just how important it is to have strong antibiotic stewardship and infection control in these high-risk hospital areas.
Overall, these findings highlight the need for targeted monitoring of antibiotic resistance in intensive care units. This can help guide treatment choices and help prevent the spread of multidrug-resistant bacteria.
Ciprofloxacin resistance was significantly associated with the genes gyrA, qnrA, qnrB, and qnrS (p < 0.001), but not parC. We detected the gyrA and parC genes together in 7 (23.3%) P. aeruginosa ciprofloxacin-resistant isolates, which is consistent with findings from other investigations [27–29].
We found the gyrA and parC genes in isolates that were still sensitive to ciprofloxacin. However, just having these genes doesn’t mean the bacteria are resistant. Usually, resistance occurs when there are specific mutations in QRDRs of these genes. Finding these genes in susceptible isolates suggests that these important mutations haven’t happened, or that the genes haven’t changed in a way that would cause resistance. Since we didn’t perform sequencing or expression analysis, the phenotypic relevance of these findings remains inconclusive. [2]. Alternatively, resistance may be linked to the concurrent existence of gyrA and parC mutations. [21]. These findings highlight the critical role of these genes in ciprofloxacin resistance.
In our study, qnrS had higher rates in the qnr genes than did qnrA and qnrB, while both had the same lowest rates. In contrast, Ataei B et al. and Abdelrahim SS et al. reported that qnrA was more prevalent than qnrB and qnrS in all samples and that most samples contained at least one qnr gene [30,31]. Our findings are consistent with the study in which qnrS was also detected, whereas qnrA and qnrB were absent, in contrast to our findings [32]. Additionally, all the resistance genes identified in our study were also reported in earlier reports, although prevalence varied [22,33]. Notably, qnrB was more prevalent than qnrA and qnrS in those studies. We also reported that the three PMQR genes under investigation (gnrA, qnrB, and qnrS) coexist in 11 (36.7%) of the resistant P. aeruginosa isolates.
Our multivariable logistic regression analysis showed a strong and statistically significant link between the presence of the gyrA gene and ciprofloxacin resistance (OR = 33.5, 95% CI: 5.97–188.2, FDR-adjusted p < 0.001), highlighting the key role that chromosomal changes play in the development of resistance. This finding matches what other PCR-based study have reported, with high rates of gyrA found in ciprofloxacin-resistant P. aeruginosa from clinical samples in Iran [34].
On the other hand, the qnrA, qnrB, and qnrS genes were found only in resistant isolates and not at all in sensitive ones. Because of this perfect split, we couldn’t include these genes in our multivariable models a challenge that’s also been noted in other studies that look at gene presence or absence [22,35].
Overall, our findings suggest that ciprofloxacin resistance in these isolates is mainly linked to chromosomal changes especially the presence of the gyrA gene, which showed a strong connection to resistance. While we also found plasmid-mediated resistance genes (qnrA, qnrB, qnrS) only in resistant isolates, their consistent presence made it hard to analyze them further. Therefore, while our findings strongly support the role of chromosomal resistance, they also point to a possible contribution from plasmid-based genes that warrants further investigation.
While virulence genes such as toxA, lasB, nan1, and oprI were frequently detected among our isolates, they did not show a statistically significant association with ciprofloxacin resistance after adjusting for multiple comparisons. This suggests that these genes may contribute more to pathogenicity than to antimicrobial resistance. Similar findings have been reported by Edward et al. [36], who found no clear link between virulence gene carriage and ciprofloxacin resistance in P. aeruginosa isolates from burn patients.
The types of resistance and virulence genes we found in P. aeruginosa depended on the source of the clinical samples, with urine specimens exhibiting the highest combined prevalence of both virulence and resistance genes. In our study, oprI (23.5%), lasB (20.0%), and toxA (13.0%) were the most frequently detected virulence genes in urinary P.aeruginosa isolates far more common than nan1 (3.5%). This aligns with previous work demonstrating that lasB and toxA genes are universally present in urinary P.aeruginosa isolates, reinforcing the idea of site-specific virulence enrichment in urine-derived strains [37].
We also found that urine samples had relatively high rates of the resistance genes parC (11.3%), gyrA (10.4%), and qnrA (7.0%) indicating that urinary isolates can act as reservoirs for both plasmid-mediated quinolone resistance (PMQR) and chromosomal QRDR resistance. This is consistent with previous observations: Tehran-based research confirmed frequent co-occurrence of gyrA and parC mutations in urinary P. aeruginosa isolates [38], and a multicenter analysis found that qnrA, qnrS, and qnrB were prevalent among fluoroquinolone-resistant strains, particularly from urinary sources [39].
In contrast, wound swabs showed a high prevalence of virulence genes such as lasB (30.8%), oprI (26.9%), and toxA (21.2%), findings consistent with previous reports linking these determinants to proteolytic tissue damage, immune evasion, and persistence of P. aeruginosa in skin and soft tissue infections [40]. Resistance genes were much less common—parC (11.5%), gyrA (3.8%), and qnr genes (1.9% each for qnrA, qnrB, and qnrS), which aligns with earlier findings showing that plasmid-mediated quinolone resistance genes are uncommon in P. aeruginosa [41], This pattern may reflect localized antibiotic pressure in skin and soft tissue infections. Previous studies on wound isolates especially from burn wounds highlight have identified the gyrA gene as the predominant ciprofloxacin resistance mechanism in such settings [42].
Sputum samples also showed notable levels of virulence genes, with lasB (24.4%), oprI (22.2%), and toxA (20.0%) being the most common. This matches previous reports that highlight toxA as a frequent virulence factor and note the presence of lasB in clinical P. aeruginosa isolates [43]. Resistance genes appeared less common overall, although parC (11.1%) and qnrA/qnrB (6.7% each) were detected more often than gyrA (4.4%). This predominance of parC over gyrA contrasts with findings from a regional survey of clinical P. aeruginosa isolates including a substantial number derived from pus and sputum specimens where the gyrA were the most frequently observed mechanism of fluoroquinolone resistance. In that survey, alterations in parC were less common, and plasmid-mediated qnr genes were notably absent [44].
Samples from other sources—such as blood, tracheal aspirates, pus, tissue, body fluids, and cough swabs—displayed a variety of gene patterns. Notably, oprI was found in 40.0% of eye swabs and 50.0% of fluid samples. The nan1 gene was mostly absent, except in tracheal aspirates (8.3%) and blood (6.2%). qnr genes were rarely detected outside of urine and sputum, only appearing in tracheal aspirates (qnrB and qnrS, 8.3% each) and RF samples (20.0% each), and entirely undetected in blood, eye swabs, fluids, pus, and tissue.
Interestingly, no single sample type had all the resistance or all the virulence genes at once, highlighting how much gene patterns can vary depending on the infection site. This underlines the importance of specimen-specific surveillance and intervention strategies.
These findings have important real-world implications, especially for hospital infection control and how doctors choose antibiotics to start treatment. Notably, the fact that ciprofloxacin-resistant P. aeruginosa strains were mostly found in intensive care units highlights the urgent need for stronger antibiotic stewardship in these high-risk areas. Intensive care units often involve more invasive procedures, longer patient stays, and frequent use of broad-spectrum antibiotics—factors that all make it easier for resistant bacteria to take hold and spread. This study set out to explore ciprofloxacin resistance as well as the presence of resistance and virulence genes, to gain a clearer picture of the molecular factors that influence clinical outcomes.
We also noticed that certain resistance and virulence genes like gyrA, qnrS, and toxA were more common in specific types of samples, such as tracheal aspirates and wound swabs. This points to the possibility of site-specific genetic adaptation, which could help make surveillance and monitoring efforts more targeted and effective.
Understanding these patterns can help healthcare teams spot high-risk infections sooner and choose better initial treatments, which in turn can lead to better patient outcomes and help slow the spread of multidrug-resistant bacteria.
A major limitation of this study is the lack of sequencing of the gyrA and parC genes, which prevents confirmation of resistance-conferring mutations. Additionally, we didn’t perform minimum inhibitory concentration (MIC) testing, which would have given us a more precise way to classify resistance. Our sample size was relatively small just 86 isolates which may affect how well our results can be applied to a broader population. In addition, we didn’t analyze gene expression, so we don’t know how active these resistance genes really are. Another important limitation is that some genes, like nan1, were only found in a small number of isolates. Because of these small group sizes, our statistical analysis power is reduced, and there’s a chance that some associations could be misleading. So, these findings should be taken with a grain of salt. While they do give us useful clues especially about how resistance and virulence traits can exist together—they are still exploratory at this stage. We recognize these limitations and plan to address them in future research.
Conclusion
In summary, our study shows that the patterns of virulence and resistance genes in P. aeruginosa isolates are quite complicated. The differences seen across various studies make it clear that factors like location and research methods can really influence the results, so it’s important to keep these in mind when interpreting the findings. Continued monitoring and more advanced research are key to better understanding how resistance develops and how we can best manage P. aeruginosa infections. Based on what we found especially the concentration of ciprofloxacin-resistant strains in intensive care units and the links between certain genes and specific types of samples, we suggest putting targeted antibiotic stewardship programs and gene-based surveillance in place for high-risk hospital units. These findings are crucial for enhancing infection control and antibiotic use, enabling healthcare teams to respond more effectively to the challenges posed by this adaptable pathogen.
Supporting information
S1 Data. Raw dataset of gene presence/absence and clinical metadata used for statistical analysis.
Provided as an Excel spreadsheet prior to statistical processing.
https://doi.org/10.1371/journal.pone.0335269.s001
(XLSX)
Acknowledgments
Acknowledgments: We would like to express our deepest appreciation to the Exon Molecular Laboratory and National University Biomedical Research Institute (NUBRI), for their support and assistance with the molecular processes.
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