Molecular Epidemiology of Different Bacterial Pathogens and Their Antimicrobial Resistance Genes Among Patients Suffering from Surgical Site Infections in Lebanon

Abstract

Background: Antimicrobial resistance (AMR) is a major global health threat, particularly in surgical site infections (SSIs), where multidrug-resistant (MDR) pathogens complicate treatment. Objective: This study aimed to identify antimicrobial resistance genes and assess their prevalence in bacterial species causing SSIs in Lebanon. Materials and Methods: The present research is a multicenter and prospective study that included patients who developed SSIs after surgery in seven hospitals, within the period of January 2024–September 2024. Bacterial isolates from wound swabs or tissue samples were identified using standard microbiological methods. Antimicrobial susceptibility was tested by disk diffusion, and resistance genes were detected by PCR. Data were analyzed using Statistical Package for the Social Sciences (SPSS). Results: Among 6933 surgical patients, 63 developed SSIs (0.91%; 95% CI [0.70–1.15]). Gram-negative bacteria predominated (73%), mainly Escherichia coli and Pseudomonas aeruginosa, while Gram-positive isolates accounted for 27%, mostly Staphylococcus aureus. MDR was observed in 71% of Gram-positive and 61% of Gram-negative isolates. The most frequent genes were mecA in S. aureus (100%) and coagulase-negative staphylococci (83.3%); bla_CTX-M in E. coli, Klebsiella pneumoniae, and Enterobacter cloacae (100%); and bla_NDM in E. cloacae (100%) and Acinetobacter baumannii (60%). bla_KPC was less common, and no isolates carried Imipenemase (IMP), Verona integron-encoded metallo-β-lactamase (VIM), and Oxacillinase-48-like β-lactamase (OXA-48). Conclusions: This study highlights the high prevalence of antibiotic resistance in agents causing SSIs in Lebanese hospitals. Resistance genes, particularly mecA, bla_CTX-M, and blaNDM, were highly prevalent in SSI pathogens, underscoring the urgent need for surveillance and judicious antibiotic use in Lebanese hospitals.

1. Introduction

Antimicrobial resistance (AMR) is a growing global problem that poses a major threat to humans worldwide [1]. It is driven by the ability of bacteria to develop new mechanisms to evade drugs, ensuring their survival [2]. Its impact extends beyond human health to healthcare, veterinary, and agricultural sectors, with misuse and overuse of antimicrobials being the main cause of resistance spread, making infections harder to treat and increasing the risk of disease transmission and mortality [3]. Despite the revolutionary effect of antibiotics in modern medicine, AMR was associated with an estimated 1.27 million deaths in 2019, and projections suggest that mortality could reach 10 million by 2050, with significant economic losses and added healthcare costs [4,5].

The severe impact of antimicrobial resistance (AMR) on patient outcomes is clearly illustrated by surgical site infections (SSIs), a common type of hospital-acquired infection (HAI). These infections not only delay patient recovery but also increase healthcare costs and directly contribute to the spread of multidrug resistance (MDR) [6]. SSIs may result from the patient’s own flora (endogenous), from contaminated surgical instruments or the hospital environment, or through cross-transmission from healthcare workers [7,8,9]. In such settings, the misuse or overuse of antibiotics further creates selective pressure, enabling bacteria to adapt and survive [9].

Understanding the genetic basis of resistance and its distribution among pathogens is crucial for devising effective strategies to combat this growing crisis. The prevalence of resistance genes in bacterial isolates from SSI patients’ needs to be investigated thoroughly, providing insights into the molecular epidemiology of AMR in hospital settings [10]. Among the highly resistant bacterial species, certain extensively drug-resistant Gram-negative bacteria (XDR-GNB) carry plasmid genes that make them resistant to carbapenems, one of the most critical groups of antibiotics [11]. Major antimicrobial-resistant pathogens include Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii, which commonly produce enzymes such as New Delhi Metallo-β-lactamase (NDM), Oxacillinase-48- like β-lactamase (OXA 48), K. pneumoniae carbapenemase (KPC), Imipenemase (IMP), Verona Integron-encoded Metallo-β-lactamase (VIM) [12,13,14,15,16].

In addition to carbapenem resistance, these bacteria often co-harbor multiple β-lactamase enzymes, including extended-spectrum β-lactamases (ESBLs) such as those encoded by bla_TEM (Temorina Escherichia coli mutant), bla_SHV (Sulfhydryl variant), and bla_CTX-M (Cefotaximase-Munich) genes, as well as AmpC β-lactamases. They also frequently carry resistance genes against other antibiotic classes, including fluoroquinolones and tetracyclines, further limiting treatment options and contributing to a multidrug-resistant phenotype. These genes are most commonly found in Escherichia coli and Klebsiella pneumoniae, which are the leading producers of ESBL enzymes. Their combined resistance mechanisms significantly reduce the effectiveness of β-lactam antibiotics. Due to their high transmission potential, these pathogens pose a serious global health threat, making infections increasingly difficult to treat and limiting effective therapeutic options. [16,17].

Moreover, methicillin-resistant strains of Staphylococcus, particularly Staphylococcus aureus and Staphylococcus Coagulase-negative species, also play a significant role in HAIs [18]. The presence of mecA gene in these bacteria is a major factor in β-lactam resistance, as it encodes penicillin-binding protein 2a (PBP2a), which prevents β-lactam antibiotics from effectively inhibiting bacterial growth [19]. In addition to mecA, a homologous gene known as mecC has been identified in certain Staphylococcus aureus isolates, particularly those from animal and environmental sources. mecC encodes a similar protein (PBP2c) and contributes to methicillin resistance, although it is less frequently detected in clinical human isolates [20]. These resistant strains contribute to the increasing burden of AMR in healthcare settings, often leading to treatment failures and complications in infected patients [18].

In addition to β-lactam and carbapenem resistance, vancomycin resistance remains a critical concern, particularly among Enterococcus species. This resistance is primarily mediated by the vanA and vanB genes which poses a significant clinical challenge. These genes enable the spread of vancomycin-resistant enterococci (VRE), particularly in hospital settings, complicating treatment in vulnerable patient populations [21].

In the present study, we aimed to identify, for the first time in Lebanon, the antimicrobial resistance genes and assess their prevalence and distribution in bacterial species causing SSIs.

2. Materials and Methods

2.1. Study Design

Seven hospitals from various regions in Lebanon, including Tyre, Beirut, Nabatieh, Saida, and Mount Lebanon, participated in this multicenter prospective study. This study was conducted in the period between January 2024 and September 2024. Samples were collected from Al-Zahraa Hospital starting on 10 March 2024, Sheikh Ragheb Harb Hospital on 2 January 2024, Al-Sahel Hospital on 30 March 2024, Hammoud Hospital on 8 March 2024, Al-Hayat Hospital on 27 February 2024, Jabal Amel Hospital on 1 February 2024, and Italy Hospital from 5 January 2024 to 29 September 2024 across all hospitals. The Lebanese University provided a formal recommendation letter to the hospital, granting approval for our research team to collect data in compliance with institutional and ethical requirements.

2.2. Study Population and Sample Size

During the period of our study, 6933 patients underwent surgery in the participating seven hospital centers. These hospitals were private analyzing between 100 and 315 numbers of bed. Out of the total number of patients, 63 cases were diagnosed with SSI and therefore, considered relevant for this study. Among them, 35 cases involved MDR pathogens.

2.3. Sample Collection and Patient Assessment

By standardizing the patient data collection process, the following demographic information was drawn from patients through an oral interview: age, gender, nationality, educational background, occupational background, and blood type. In addition, the following clinical characteristics were collected: Type of admission, general surgery unit that conducted the procedure, the nature of the procedure, type of surgery, duration of surgery, classification of wound inflected during the surgery, type of infection, the timing of infection, details regarding the prophylaxis administered, and length of stay. Medical history information of each patient was also collected, including diabetes, hypertension, cardiovascular diseases, and other chronic diseases. Data was confirmed from patients’ medical files.

2.4. Laboratory Procedures

For analysis, the samples gathered using a sterile swab from infected surgical sites were promptly transported to the microbiology laboratory. Those samples underwent the following procedures:

2.5. Bacterial Culture and Identification

All specimens were cultured on Blood agar and Macconkey agar within one hour of collection. The inoculated agar plates were incubated aerobically at a temperature of 35–37 °C. After a period of 24 h, the plates were examined for the presence of bacterial growth. If no growth is observed, the plates were incubated for an additional 24 h.

The bacterial isolates that grew on the agar plates were identified through a series of standard microbiological techniques. This includes the morphology of colonies and Gram staining to classify the bacteria as either Gram-positive or Gram-negative. Further identification was achieved through different biochemical tests. For Gram-positive bacteria, tests such as catalase, coagulase, oxidase, and mannitol fermentation were conducted. For Gram-negative bacteria, tests including urease, indole, citrate, and sugar utilization were performed.

2.6. Antibiotic Susceptibility Testing

The antibiotic susceptibility of bacterial isolates was evaluated using the Kirby-Bauer disk diffusion method, adhering to the guidelines of the Clinical Laboratory Standards Institute (CLSI) [22]. Selected bacterial colonies (3 to 5) from a pure culture were transferred into a tube containing 5 mL of sterile distilled water and mixed gently until the turbidity matched the 0.5 McFarland standard.

A sterile cotton swab was used to evenly spread the bacteria across the surface of Mueller-Hinton agar. The plates were left to air-dry at room temperature for 3 to 5 min before placing antibiotic discs on the agar surface. Both Gram-positive and Gram-negative isolates was tested against ampicillin (10 µg), gentamicin (10 µg), ciprofloxacin (5 µg), cefotaxime (30 µg), cefepime (30 µg), tetracycline (30 µg), trimethoprim-sulfamethoxazole (1.25/23.75 µg), cefoxitin (30 µg), nitrofurantoin (300 µg), fosfomycin (200 µg), tigecyline (15 µg), Gram-positive isolates were tested against penicillin (10 units), vancomycin (30 µg), erythromycin (15 µg), clindamycin (30 µg), oxacillin (5 µg), ceftriaxone (30 μg), teicoplanin (30 µg), rifampin (5 µg) and linezolid (30 µg). Gram-negative isolates were tested against amikacin (30 µg), ceftazidime (30 µg), cefuroxime (30 µg), amoxycillin + clavulanate (20/10 μg), aztreonam (30 µg), meropenem (10 µg), imipenem (10 µg), ertapenem (30 µg), piperacillin- tazobactam (100/10 µg), cefixime (5 µg), ceftolozane-tazobactam (40 µg) and ceftazidine-avibactam (30/20 µg). The plates were then incubated at 35–37 °C for 18 to 24 h.

After incubation, the diameter of the inhibition zones around the antibiotic discs was measured, and the results were interpreted as sensitive, intermediate, or resistant based on established protocols by CLSI [22].

After analyzing the antimicrobial resistance profiles of the bacterial isolates, those classified as MDR, that showing resistance to three or more distinct classes of antibiotics, were selected for further molecular analysis. These MDR isolates were transported to the Lebanese Diagnostic Center (LDC) laboratory in Tyre, South Lebanon, for molecular detection of antimicrobial resistance genes. To identify the specific genes responsible for AMR in our isolates, each strain underwent nucleic acid extraction followed by qRT-PCR analysis.

2.7. Nucleic Acid Extraction

DNA was extracted using the Bosphore Versatile Spin Kit (Anatolia, Turkey). Bacterial colonies were pretreated with proteinase K and lysis buffers to break down cell walls, particularly in Gram-positive species. The extraction involved four main steps: lysis of cells, DNA binding to the silica membrane, removal of impurities via ethanol-based washing, and elution of purified DNA with a low-salt buffer. An internal control (IC) was added during extraction to monitor DNA quality and potential PCR inhibition, detected with the Cy5 filter. Final DNA samples were stored at –20 °C for later use. Buffer pH and salt concentrations were optimized to ensure effective nucleic acid recovery and removal of contaminants.

2.8. PCR Analysis (Bosphore ABR Screening Kit)

The extracted DNA was analyzed using the Bosphore ABR Screening kit (Anatolia, Turkey), a real-time PCR assay designed to detect resistance genes associated with carbapenemase production, beta-lactam resistance, and vancomycin resistance.

The targeted genes include bla_NDM, bla_OXA-48, bla_KPC, bla_IMP, bla_VIM, bla_CTX-M, MCR-1, Van A, Van B, and mec A coding for New Delhi Metallo-β-lactamase (NDM), Oxacillinase-48- like β-lactamase (OXA 48), K. pneumoniae carbapenemase (KPC), Imipenemase (IMP), Verona Integron-encoded Metallo-β-lactamase (VIM), Cefotaximase-M β-lactamase (CTX-M), Mobilized colistin resistance-1 (MCR-1), Vancomycin Resistance Gene A (Van A), Vancomycin Resistance Gene B (Van B) and Methicillin Resistance Gene A (mec A). PCR amplification and real-time analysis was performed using the QuantStudio Real-Time PCR system by Thermo Fisher Scientific to ensure high sensitivity and specificity in detecting resistance determinants.

2.9. Data Analysis

The data collected during this study were carefully entered into the Statistical Package for Social Sciences (SPSS) version 26 by one dedicated researcher. After entering the data, statistical analysis was performed using SPSS. Various descriptive statistics were calculated, including average values and frequency counts of bacterial distribution and AMR profile, to provide a comprehensive overview of the data. The prevalence of resistance genes was also studied, in addition to the prevalence of each gene expressed in our samples.

2.10. Ethics Approval and Consent to Participate

The Ethical approval was granted from the ethics committee and review board of the different hospitals (Al-Zahraa hospital (reference number: 7/2024), Sheikh Ragheb Harb Hospital (reference number: 10/2023), Al-Sahel hospital (reference number: 5/2024), Hammoud Hospital (reference number: 4/2024).

Al-Hayat Hospital and Italy Hospital do not have an ethical committee; we obtained approval through a signed permission letter sent from our university. In Jabal Amel Hospital, we received verbal approval, as they do not have an ethical committee.

Informed consent was obtained from all participants before sample collection. Written consent was obtained from patients in hospitals with an ethical committee. In hospitals without an ethical committee, approval was granted through a signed permission letter from our university. Verbal consent was obtained in hospitals without a formal ethical review process and was documented in the medical records by the attending physician or study investigator.

3. Results

The prevalence of SSIs in our study was 0.91%. SSIs were common among females (63.5%) and older patients (ages 61–75 and 75+ years). Orthopedic surgeries accounted for the highest proportion of SSIs (42.9%), with most infections occurring in surgeries lasting less than one hour (52.5%). The majority of infections were superficial (63.5%), with clean wounds being the most frequent type (74.6%).

3.1. Bacterial Isolates

Microbiological identification results show that the prevalence of Gram-negative bacteria was higher than that of Gram-positive bacteria (73% “95% CI [60.3%, 83.4%]” vs. 27%) as shown in

Table 1. Bacterial Isolate Information.

Bacterial Isolate	n	Percentage (%)
Gram-positive    Staphylococcus aureus    Streptococcus pneumoniae    Enterococcus spp.    Coagulase Negative Staphylococcus	17 8 1 2 6	27% 12.7% 1.6% 3.2% 9.5%
Gram-negative    Escherichia coli    Klebsiella pneumoniae    Acinetobacter baumannii    Pseudomonas aeruginosa    Proteus mirabilis    Enterobacter cloacae	46 13 10 6 12 4 1	73% 20.6% 15.9% 9.5% 19% 6.3% 1.6%
Total	63	100%

. Regarding bacterial species, Escherichia coli (E. coli) was the most prevalent isolated bacterium from SSI patients (20.6%, 95% CI [11.5%, 32.7%]) followed by Pseudomonas aeruginosa (P. aeruginosa) (19%, 95% CI [10.2%, 30.9%]), Klebsiella pneumoniae (K. pneumoniae) (15.9%), Staphylococcus aureus (S. aureus) (12.7%) Acinetobacter baumannii (A. baumannii) (9.5%), Coagulase negative Staphylococcus (CoNS) (9.5%) accounting for 87.2% of all isolates (Table 1). All other bacterial species (Streptococcus, Enterococcus, Proteus mirabilis and Enterobacter cloacae) were detected in 12.8% of patients (Table 1).

3.2. Resistance of Bacterial Isolates

For the Gram-positive bacteria, a total of 17 isolates were reported, forming 27% of the entire isolates. Regarding the resistance patterns of these isolates,

Table 2. Resistance of Bacterial Isolates.

Bacterial Isolate	Total Number	Antimicrobial Resistant Pattern: Total Number (%)
		R0	R1	R2	R3	R4	R5	R6
Gram-Positive	17	2 (11.8)	1 (5.9)	2 (11.8)	2 (11.8)	5 (29.4)	3 (17.6)	2 (11.8)
S. aureus	8	1 (12.5)	0 (0)	1 (12.5)	0 (0)	3 (37.5)	3 (37.5)	0 (0)
CoNS	6	0 (0)	1 (16.7)	0 (0)	1 (16.7)	2 (33.3)	0 (0)	2 (33.3)
Streptococcus	1	1 (100)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
Enterococcus	2	0 (0)	0 (0)	1 (50)	1 (50)	0 (0)	0 (0)	0 (0)
Gram-Negative	46	8 (17.4)	5 (10.9)	5 (10.9)	5 (10.9)	11 (23.9)	7 (15.2)	5 (10.9)
E. coli	13	4 (30.8)	0 (0)	4 (30.8)	1 (7.7)	2 (15.4)	1 (7.7)	1 (7.7)
K. pneumonia	10	0 (0)	2 (20)	0 (0)	1 (10)	5 (50)	0 (0)	2 (20)
A. baumannii	6	0 (0)	1 (16.7)	0 (0)	1 (16.7)	0 (0)	3 (50)	1 (16.7)
P. aeruginosa	12	4 (33.3)	2 (16.7)	1 (8.3)	1 (8.3)	3 (25)	1 (8.3)	0 (0)
P. mirabilis	4	0 (0)	0 (0)	0 (0)	1 (25)	1 (25)	2 (50)	0 (0)
E. cloacae	1	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	1 (100)

R0: no resistance, R1: resistance to one drug, R2: resistance to two drugs, R3: resistance to three drugs, R4: resistance to four drugs, R5: resistance to five drugs, R6: resistance to six drugs.

shows that 2 bacterial isolates had no resistance against antibiotics (R0), representing 11.8% of the Gram-positive isolates. On the other hand, just 2 isolates (11.8%) of Gram-positive isolates were resistant to all antibiotics (R6). Interestingly, 70.6%, 95% CI [44%, 89.7%], of Gram-positive isolates can be considered MDR strains (resistance to 3 different families of antibiotics or more: R3, R4, R5, or R6). Regarding S. aureus pathogens, 1 isolate (12.5%) showed no resistance (R0), while most isolates of S. aureus reported a significant proportion of MDR (75%, 95% CI [34.9%, 96.8%]). Furthermore, out of the 6 CoNS isolates, one isolate (16.7%) showed resistance to 1 antibiotic (R1), and most isolates reported a significant proportion of MDR (83.3%, 95% CI [35.9%, 99.6%]). For Streptococcus, only 1 isolate (1.6%) was identified, which exhibited no resistance against antibiotics (R0). As for Enterococcus, 2 isolates (3.2%) were identified, one of which showed resistance to 2 antibiotics (R2) and another one showed a resistance to 3 antibiotics (R3).

For the Gram-negative bacteria, a total of 46 Gram-negative bacterial isolates were identified, representing 73% of the total isolates. The resistance patterns indicated that 8 isolates (17.4%) showed no resistance against antibiotics (R0). On the other hand, five isolates (10.9%) of Gram-negative isolates were resistant to all tested antibiotics (R6). Remarkably, 60.9%, 95% CI [45.4%, 74.9%], of Gram-negative isolates were classified as MDR strains. Concerning E. coli, out of 13 isolates, 4 isolates (30.8%) showed no resistance (R0). Notably, 4 isolates (30.8%) were resistant to 2 antibiotics (R2), and 5 (38.5%, 95% CI [13.9%, 68.4%]) of E. coli isolates were MDR strains. Concerning K. pneumoniae, a total of 10 isolates (15.9%) were identified, with 2 isolates (20%) showing resistance to 1 antibiotic (R1), and 8 isolates (80%, 95% CI [44.4%, 97.5%]) were MDR strains. For A. baumannii, out of 6 isolates, none showed no resistance (R0), one isolate (16.7%) showed resistance to 1 antibiotic (R1), and 5 isolates (83.3%, 95% CI [35.9%, 99.6%]) reported a significant proportion of MDR strains. For P. aeruginosa, out of 12 isolates, 4 isolates (33.3%) showed no resistance (R0), 2 isolates (16.7%) reported resistance to 1 antibiotic (R1), 1 isolate (8.3%) to 2 antibiotics (R2), and 5 isolates (41.7%, 95% CI [15.2%, 72.3%]) can be considered MDR strains. For P. mirabilis, a total of 4 isolates were identified, with none showing no resistance (R0) while 100% of P. mirabilis isolates were MDR strains. Concerning E. cloacae, only 1 isolate was identified, making it an MDR strain.

3.3. Resistance Gene Profiles of Multidrug-Resistant Bacterial Isolates

Regarding the molecular detection of antimicrobial resistance (AMR) genes in multidrug-resistant (MDR) bacterial isolates,

Table 3. Distribution of Antimicrobial Resistance Genes Among Multidrug-Resistant Bacterial Isolates.

Resistance Gene		MDR Isolates: Number (%)
		S. aureus (6)	CoNS (6)	E. coli (5)	K. pneumonia (8)	A. baumannii (5)	P. aeruginosa (4)	P. mirabilis (4)	E. cloacae (1)
mec A	Yes	6 (100)	5 (83.3)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
Van B	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
Van A	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
MCR-1	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
blaCTX-M	Yes	0 (0)	0 (0)	5 (100)	8 (100)	0 (0)	3 (75)	3 (75)	1 (100)
blaVIM	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
blaIMP	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
blaKPC	Yes	0 (0)	0 (0)	0 (0)	1 (12.5)	0 (0)	0 (0)	0 (0)	0 (0)
blaOXA48	Yes	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)
blaNDM	Yes	0 (0)	0 (0)	2 (40)	1 (12.5)	3 (60)	0 (0)	0 (0)	1 (100)

Numbers in parentheses indicate the number of isolates tested for each bacterial species.

shows distinct resistance patterns across different species.

Methicillin resistance (mecA gene) was present in 100% of MRSA isolates and 83.3% of MRCoNS isolates, confirming their resistance to beta-lactam antibiotics.

Regarding vancomycin resistance (vanA and vanB genes), neither gene was detected in any bacterial isolates, indicating no vancomycin-resistant strains in our study. Similarly, the mobilized colistin resistance gene (mcr-1) was not found in any isolates, suggesting that colistin resistance was not a contributing factor to MDR in this dataset.

In terms of Cefotaximase-M β-lactamase (bla_CTX-M) genes, 100% of E. coli, K. pneumoniae and E. cloacae isolates, 75% of P. aeruginosa and P. mirabilis isolates carried this resistance gene. However, it was absent in A. baumannii. This confirms the high prevalence of ESBL-producing bacteria in certain species, particularly in E. coli and K. pneumoniae.

For carbapenemase genes (bla_NDM, bla_OXA-48, bla_KPC, bla_IM, bla_VIM), bla_NDM was detected in 100% of E. Cloacae isolates, 60% of A. baumannii isolates, 40% of E. coli and 12.5% of K. pneumoniae isolates, bla_KPC was found in 12.5% of K. pneumoniae isolates, while bla_IMP, bla_VIM, and bla_OXA-48 genes were completely absent across all species.

4. Discussion

The prevalence of SSIs in our study was 0.91%, SSIs were common among females (63.5%) and older patients (ages 61–75 and 75+ years). Orthopedic surgeries accounted for the highest proportion of SSIs (42.9%), with most infections occurring in surgeries lasting less than one hour (52.5%). The majority of infections were superficial (63.5%), with clean wounds being the most frequent type (74.6%).

The microbiological profile showed a predominance of Gram-negative bacteria (73%), with E. coli (20.6%), P. aeruginosa (19%), and K. pneumoniae (15.9%) being the most common. Gram-positive bacteria, including S. aureus (12.7%), were also present. Antibiotic resistance varied, with high resistance observed for ampicillin, cefuroxime, and fluoroquinolones, reinforcing the need for strict antibiotic stewardship and continuous surveillance. Some newer antibiotics demonstrated strong efficacy, such as ceftolozane-tazobactam and ceftazidime-avibactam (100% sensitivity in E. coli and P. aeruginosa).

MDR strains were highly prevalent in both Gram-positive (70.6%) and Gram-negative (60.9%) isolates, reflecting an important antimicrobial resistance challenge.

The molecular detection of AMR genes in MDR bacterial isolates revealed distinct patterns across species. The mecA gene was identified in 100% of MRSA and 83.3% of MRCoNS. Neither vancomycin resistance genes (vanA or vanB) nor the mobilized colistin resistance gene (mcr-1) were detected in any isolates.

The bla_CTX-M gene was found in 100% of ESBL E. coli, K. pneumoniae, and E. cloacae isolates, and in 75% of P. aeruginosa and P. mirabilis isolates. It was not detected in A. baumannii.

As for carbapenemase genes, bla_NDM was detected in 100% of E. cloacae, 60% of A. baumannii, 40% of E. coli, and 12.5% of K. pneumoniae isolates. bla_KPC was found in 12.5% of K. pneumoniae, while bla_IMP, bla_VIM, and bla_OXA-48 genes were not detected in any of the tested isolates.

The prevalence of SSI in our study was 0.91%, which is notably lower than the rates reported in other studies, such as the 10.9% incidence observed in a tertiary care hospital in Rwanda, 3.5% in Mogadishu Somalia Turkish Training and Research Hospital [23,24,25]. This discrepancy may be attributed to differences in healthcare infrastructure, surgical protocols, and infection control measures.

The microbiological profile in our study revealed a higher prevalence of Gram-negative bacteria (73%) compared to Gram-positive bacteria (27%). The commonly identified pathogens were E. coli at 20.6%, followed by P. aeruginosa at 19%, and K. pneumoniae at 15.9%. Among Gram-positive bacteria, S. aureus represented the largest group with 12.7%. which is consistent with findings from the study in Mogadishu, Somalia, Turkish Training and Research Hospital, where E. coli was the predominant pathogen (35.8%), followed by S. aureus (21.8%) [24]. We demonstrate identical distribution of the bacterial species, which is consistent with their established pathogenic and virulent behavior as seen in research documents. E. coli shows the pathogenicity characteristics through its adhesions to the tissues, capsules, and toxins, as well as iron acquisition mechanisms [26]. We attribute the metallophores of S. aureus to its major Gram-positive pathogenic and virulence properties. Bacterial metallophores allow bacteria to capture iron required for bacterial development as well as virulence factor expression [27].

Since this study revealed a high prevalence of P. aeruginosa, the virulence factors such as pyoverdine, pyochelin, and pseudopaline metallophores enable it to live in wound environments and resist host defense mechanisms [28]. K. pneumoniae is a bacterial isolate that has biofilm formation abilities that enable it to spread the disease as well as to develop antimicrobial resistance [29]. Our isolates also included P. mirabilis, that have known pathogenicity and virulence mechanisms, including metal usage ability to maintain survival in the host environment [30]. A. baumannii isolates in our study have a key disease pathogenic characteristic of biofilm formation that sustains its antimicrobial resistance development [31]. Our identification of Streptococcus pneumoniae is supported by recent epidemiological data, which reflects established infection patterns in healthcare settings and its antibiotic resistance characteristics, in addition to a clinical case report indicating a surgical wound infection caused by a multi drug resistant Streptococcus pneumoniae [32]. The virulence of S. pneumoniae is primarily driven by its polysaccharide capsule, pneumolysin, IgA protease, surface proteins, and autolysin, which enable it to evade immune defenses, adhere to host tissues, and cause severe infections [33]. Virulence and resistant characteristics of the Enterococcus strains that we identified in our study allow them to survive in the hospital environment, and therefore, SSIs are very difficult to prevent. The expression of different virulence factors, including biofilm-forming ability and its capacity of trading genetic information, makes this bacterial genus more capable of surviving harsh environmental conditions [34].

Within the examination of the patterns of resistance, MDR strains were prevalent in both Gram-positive and Gram-negative isolates, with 70.6% of Gram-positive and 60.9% of Gram-negative isolates classified as MDR. This aligns with the study in Ethiopia, which reported high rates of MDR strains [35].

The molecular profiling of AMR genes among MDR isolates revealed notable gene–species associations, underscoring the diversity and clinical significance of resistance mechanisms circulating in SSIs. The complete detection of the mecA gene in all MRSA isolates and the majority of MRCoNS isolates (83.3%) confirms the prevalence of methicillin resistance among Gram-positive cocci in the clinical setting. These findings align with global trends indicating widespread mecA-mediated β-lactam resistance in staphylococcal infections, reinforcing the need for strict infection control and decolonization measures [36].

In contrast, the absence of vancomycin resistance genes (vanA and vanB) in all isolates suggests that vancomycin remains an effective therapeutic option against Gram-positive organisms in the current cohort. Similarly, the lack of detection of the mcr-1 gene across Gram-negative isolates provides some reassurance, indicating that colistin resistance was not a contributing factor to MDR in this population, though its continued surveillance remains essential given its role as a last-resort agent.

The bla_CTX-M gene, encoding extended-spectrum β-lactamases (ESBLs), was highly prevalent among Gram-negative bacilli, with universal detection in E. coli, K. pneumoniae, and E. cloacae. This aligns with the global epidemiological burden of ESBL-producing Enterobacterales and reflects the heavy selective pressure imposed by cephalosporin use. Notably, its absence in A. baumannii suggests species-specific patterns of resistance dissemination. The partial presence of bla_CTX-M in P. aeruginosa (75%) and P. mirabilis (75%) further highlights the expanding spectrum of ESBL producers beyond classical Enterobacterales.

Carbapenemase-producing organisms were particularly alarming, with bla_NDM emerging as the predominant gene. Its detection in 100% of E. cloacae and the majority of A. baumannii (60%), along with its presence in E. coli (40%) and K. pneumoniae (12.5%), underscores the high burden of carbapenem resistance in these critical species. These data suggest ongoing dissemination of plasmid-encoded NDM in hospital settings. The limited occurrence of bla_KPC (12.5% in K. pneumoniae) and the complete absence of bla_IMP, bla_VIM, and bla_OXA-48 genes in the sample could reflect local resistance ecology or testing limitations, though their known global spread warrants continued genomic surveillance.

Overall, these results highlight the species-specific distribution of resistance genes and point to the dominance of mecA, bla_CTX-M, and bla_NDM in shaping MDR profiles in Lebanese hospitals. The absence of certain high-risk resistance genes (vanA and vanB, mcr-1, bla_OXA-48) is encouraging, yet the high prevalence of ESBLs and carbapenemases, particularly in E. cloacae, A. baumannii, and K. pneumoniae, emphasizes the need for targeted antimicrobial stewardship, routine molecular surveillance, and strict adherence to infection control protocols.

mec-A gene develops methicillin resistance by generating an altered penicillin-binding protein (PBP2a), and its detection confirms the presence of methicillin-resistant S. aureus (MRSA) [36]. The concentration of mecA solely in S. aureus isolates indicates its role as the primary source of β-lactam resistance among SSIs in our setting. This highlights the necessity of incorporating anti-MRSA coverage (vancomycin or linezolid) into antibiotic therapy in suspected S. aureus infection.

The prevalence of bla_CTX-M in K. pneumoniae isolates highlights its role as a major reservoir for extended-spectrum β-lactamase (ESBL) production in surgical infections [37,38,39]. CTX-M enzymes are extended-spectrum β-lactamases that confer resistance to third-generation cephalosporins, and can also affect penicillins and some first- and second-generation cephalosporins. They frequently co-exist with resistance genes for fluoroquinolones and aminoglycosides, further complicating infection treatment and eradication. This result support the need to consider ESBL-producing K. pneumoniae when selecting empirical therapies for suspected Gram-negative SSIs, especially in high-risk patients or settings with elevated resistance rates. In such cases, the use of carbapenems or β-lactam/β-lactamase inhibitor combinations (ceftazidime-avibactam) may be required to effectively treating these infections. Infection control measures should also emphasize environmental decontamination and contact precautions to prevent nosocomial transmission of ESBL-producing strains.

The absence of significant post hoc associations suggests that bla_NDM-mediated carbapenem resistance is uniformly distributed among many Gram-negative pathogens in SSI cases, rather than being dominated by a single bacterial species. This is consistent with the known behavior of NDM (New Delhi metallo-β-lactamase), which tends to be horizontally transferred through plasmids and rapidly disseminate across Enterobacterales [40]. Clinically, this is relevant to pointing towards a demand for broad-spectrum testing in the early diagnosis of carbapenemase-producing organisms (CPOs), as species identification may not efficiently indicate the occurrence of NDM. Empirical management of assumed CPO-related SSIs should take into account local prevalence patterns and may include agents such as ceftazidime-avibactam plus aztreonam or cefiderocol where available.

As limitations for this study, we should mention the low number of SSI-positive isolates (63 isolates); in addition, our molecular umbrella for resistance genes was limited to specific genes related to resistance towards specific families of antibiotics (Methicillin, Carbapenem and Beta-Lactams); and we did not perform molecular searching for genes that encode for permeability and efflux.

5. Conclusions

This study provides a comprehensive overview of SSIs in Lebanon, focusing on their prevalence, bacterial causes, and resistance patterns. The infection rate was 0.91%, which is lower than reported in many international studies. This difference may be linked to good surgical practices and effective infection control in the participating hospitals.

Gram-negative bacteria were the most common pathogens, especially E. coli, P. aeruginosa, and K. pneumoniae, while S. aureus was the leading Gram-positive species. Many of these isolates showed resistance to commonly used antibiotics, and MDR strains were frequently found, emphasizing the need for responsible antibiotic use.

Molecular testing showed that different resistance genes were present across species. The mecA gene was common in staphylococcal isolates, confirming methicillin resistance. The bla_CTX-M gene, linked to resistance to extended-spectrum β-lactams, was widespread in Enterobacterales. The bla_NDM gene, which confers carbapenem resistance, was mainly detected in E. cloacae and A. baumannii. No resistance genes for vancomycin or colistin were found, indicating these antibiotics remain effective against the strains studied.

Overall, these results show how resistance genes vary by bacterial species and reinforce the importance of continuous microbiological monitoring, careful antibiotic use, and strong infection control policies to manage and prevent SSIs caused by drug-resistant bacteria.