Prevalence and associations of antibiotic resistance and biofilm formation with molecular determinants in clinical Acinetobacter baumannii isolates

Abstract

Acinetobacter baumannii is a notorious opportunistic pathogen commonly associated with healthcare-associated infections and multidrug resistance. Its survival in hospital environments, biofilm formation, and iron acquisition systems complicate treatment. Understanding virulence factors and resistance mechanisms is crucial for developing effective control strategies. This study investigates genetic determinants of virulence and antibiotic resistance in selected MDR/XDR clinical A. baumannii isolates and explores their relationship with phenotypic traits. The selected MDR/XDR clinical A. baumannii isolates were identified using standard microbiological methods. Antimicrobial susceptibility followed CLSI guidelines. Biofilm formation was assessed using the tissue culture plate method. Molecular confirmation and detection of the selected genes were performed by multiplex PCR. In this study, 150 non-duplicate MDR/XDR clinical A. baumannii isolates were selectively collected from routine laboratory records based on their resistance profiles. Among the selected isolates, (84%) were XDR and (16%) were MDR. bla_OXA-51 and adeA gene were present in all selected MDR/XDR isolates (100%). Among MBL genes, bla_IMP, bla_NDM, and bla_VIM were detected in 82%, 64%, and 52% of the selected studied isolates, respectively, with each isolate carrying at least one or more of these genes, while bla_KPC was absent. Biofilm formation was observed in 96% of the selected MDR/XDR studied isolates, including 36% strong, 44% moderate, and 16% weak producers. Virulence genes basD, surA1, and bfmR were present in all selected MDR/XDR isolates, while csuE, ompA, and bap were detected in 94%, 80%, and 46%, respectively. The high detection rates of metallo-β-lactamases, biofilm formation, and iron acquisition genes among the selected MDR/XDR clinical isolates, highlight the importance of continuous surveillance and infection control measures. Notably, a significant association was observed between biofilm formation and antimicrobial susceptibility profile for most tested antibiotics. Additionally, the antimicrobial susceptibility profile of the selected MDR/XDR A. baumannii showed statistically significant and non-significant associations with both antibiotic resistance genes and biofilm genes.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-64464-1.

Introduction

Acinetobacter baumannii is an alarming pathogen that poses a serious global health threat due to its ability to withstand most antibiotics. The World Health Organization (WHO) classifies it as one of the most dangerous ESKAPE pathogens^1,2, and infections caused by it are associated with high morbidity and mortality. As a result, both the WHO and the Centers for Disease Control and Prevention (CDC) have identified A. baumannii as a high-priority pathogen in antimicrobial resistance research, highlighting the urgent need for new therapeutic strategies and deeper scientific investigation³.

This pathogen is an opportunistic agent commonly associated with severe infections that are often difficult to treat due to limited therapeutic options. It is frequently associated with healthcare-associated infections, as it can colonize and persist on medical devices and hospital surfaces such as ventilators, humidifiers, dialysis machines, and washbasins⁴. This persistence contributes to its involvement in hospital-acquired infections, including ventilator-associated pneumonia (VAP), bloodstream infections, urinary tract infections, wound and skin infections, endocarditis, osteomyelitis, septicemia, and meningitis and chronic kidney disease (CKD)⁵.

Initially, A. baumannii was sensitive to most antibiotics until the early 1970s. However, throughout the 1980s and 1990s⁶, it rapidly acquired resistance to multiple antibiotic classes, creating a significant burden on global healthcare systems. Carbapenems, such as meropenem and imipenem, were once the most effective treatments, but the emergence of carbapenem-resistant A. baumannii (CRAb) has greatly reduced their efficacy. As a result, treatment has become increasingly difficult and often relies on last-resort antibiotics such as colistin or tigecycline, guided by susceptibility testing⁷.

The growing challenge in treatment is largely driven by the diverse resistance mechanisms of A. baumannii, which are broadly classified into enzymatic and non-enzymatic mechanisms. Enzymatic mechanisms include class A β-lactamases (KPC, GES, SHV, TEM, CTX-M, and PER) that hydrolyze a wide range of β-lactams⁸, class B metallo-β-lactamases (IMP, VIM, NDM, SIM) that require zinc ions and confer high-level carbapenem resistance and most other β-lactams⁹, class C β-lactamases, also referred to as cephalosporinases, allow A. baumannii to hydrolyze third-generation cephalosporins, contributing to β-lactam resistance¹⁰. Additionally, class D β-lactamases, including the intrinsic OXA-51 and acquired variants such as OXA-23-like, OXA-58-like, OXA-24/40-like, OXA-235-like, and OXA-143-like, play a major role in carbapenem resistance¹¹. Beyond enzymatic activity, A. baumannii also utilizes non-enzymatic resistance mechanisms, including reduced outer membrane permeability, modifications in penicillin-binding proteins (PBPs) that lower β-lactam affinity¹², and overexpression of multidrug efflux pumps. Among these, the AdeABC efflux pump system of the RND family is highly significant¹³. Acinetobacter baumannii’s capacity to form biofilms may enhance its persistence in clinical environments and contributes to treatment failure. Biofilm formation is a multifactorial process regulated by several key genes that collectively enhance bacterial adherence, colonization, and persistence on biotic and abiotic surfaces. Among these genes, the bap (biofilm-associated protein) gene encodes a cell-surface adhesion protein essential for biofilm architectural organization¹⁴. The surface antigen protein 1 (SurA1) has been shown to contribute to the pathogenicity of A. baumannii. It promotes bacterial adhesion and supports the early stages of biofilm formation¹⁵. The OmpA outer membrane protein, one of the most abundant in A. baumannii, acts as a major virulence factor. It plays a central role in adhesion to host epithelial cells via fibronectin binding and to abiotic surfaces, supporting colonization and biofilm establishment. Additionally, OmpA promotes immune evasion by increasing resistance to serum-mediated killing. It can also localize to host cell mitochondria, where it disrupts membrane potential and induces caspase-mediated apoptosis, contributing to tissue damage during infection¹⁶.

The CsuA/BABCDE chaperone–usher (Csu) pilus system is essential during the initial attachment phase of biofilm formation on abiotic surfaces, particularly medical devices. Within this system, CsuE functions as the tip adhesin required for pilus assembly and initial surface contact¹⁷. Regulation of the csu operon is mediated by the BfmRS two-component system, where BfmS serves as the sensor kinase and BfmR as the response regulator controlling expression of pilus biogenesis genes¹⁸. This regulatory cascade links environmental signals to surface adhesion, promoting biofilm initiation and persistence. The basD gene is required for the biosynthesis of the siderophore acinetobactin, which enables iron acquisition in iron-limited host environments¹⁹. This system enhances survival, virulence, and indirectly contributes to biofilm formation and long-term persistence²⁰.

This study aimed to characterize selected MDR/XDR clinical A. baumannii isolates at both molecular and phenotypic levels. This would be performed by detecting and evaluating relationships between antibiotic resistance and biofilm forming genes.

Materials and methods

Specimen collection and processing

In this descriptive cross-sectional investigation, a total of 150 non-duplicate clinical A. baumannii isolates exhibiting MDR or XDR phenotypes (one per patient) were selectively obtained from different patients aged between 12 and 73 years. The isolates were selected based on their antimicrobial resistance profiles (MDR/XDR) from routine clinical laboratory records. Sampling was conducted at local clinical labs in Mansoura and Damietta governorates, Egypt, during the period from July 2024 to September 2025. Written informed consent had been obtained from patients or their legal guardians (for participants under 18 years of age) at the time of original sample collection as part of routine clinical diagnostic procedures. Clinical specimens were collected from various sources including urine, wound swabs, sputum, and bloodstream samples. The study was conducted in accordance with the declaration of Helsinki. The experimental protocol was approved by the local ethical committee (Research Ethics for Basic Sciences Committee, Damietta University, Egypt).

All selected MDR/XDR samples were cultured on conventional bacteriological media, including Brain Heart Infusion agar (Oxoid, UK) as a non-selective enrichment medium, CHROMagar Acinetobacter (CHROMagar, France) as a selective medium, blood agar base (Oxoid, UK) supplemented with 5% defibrinated sheep blood, MacConkey agar (Oxoid, UK) as a differential and selective medium, and cysteine electrolyte-deficient (CLED) agar (Oxoid, UK). The plates were incubated aerobically at 37 °C and examined for growth after 24 and 48 h. Pure isolates were stored in 30% glycerol at − 80 °C for further investigations. The clinical isolates were initially identified using conventional microbiological and biochemical methods^21,22. Subsequently, species identification was confirmed using the VITEK®2 microbial identification system (bioMérieux, France) with VITEK®2 GN ID cards (bioMérieux, France), according to the manufacturer’s instructions²³.

The antimicrobial susceptibility testing

Antimicrobial susceptibility testing of the selected MDR/XDR isolates was performed using the VITEK®2 automated system (bioMérieux, France) with AST-GN73 susceptibility cards, designated for Gram-negative bacteria. Quality control strains were Escherichia coli ATCC 10536, Pseudomonas aeruginosa ATCC 27853, and Klebsiella pneumoniae ATCC 700603. All quality control results were within the acceptable ranges recommended by CLSI and were appropriate for the tested methods. Bacterial suspensions were prepared from overnight nutrient agar cultures and adjusted to a turbidity equivalent to 0.5 McFarland standard before card inoculation, following the manufacturer’s instructions. The antibiotics tested included ampicillin/sulbactam (SAM), piperacillin/tazobactam (TZP), ceftazidime (CAZ), ceftriaxone (CRO), cefepime (FEP), meropenem (MEM), gentamicin (GEN), tobramycin (TOB), ciprofloxacin (CIP), levofloxacin (LEV), and trimethoprim/sulfamethoxazole (SXT). The system measured bacterial growth across a range of antibiotic concentrations to determine the minimum inhibitory concentrations (MICs). The MIC (µg/mL) susceptibility breakpoints for all tested antimicrobial agents are presented in Supplementary Table S1 and were interpreted according to CLSI 2021 (M100, 31st Edition) criteria²⁴, as the VITEK®2 system software was validated and calibrated to this version, which was the current interpretive standard available at the testing facility during the study period. Each isolate was classified as susceptible, intermediate, or resistant based on these criteria. For association analyses, intermediate and resistant categories were combined and considered non-susceptible.

Metallo-ß-lactamase (MBL) production test

The production of metallo-β-lactamase (MBL) was assessed using the combined disk test on Mueller–Hinton agar (MHA) plates. In this method, imipenem and imipenem–EDTA (Ethylene diamine tetra acetic acid) disks were used, with 0.5 M EDTA serving as the chelating inhibitor, following established protocols²⁵.

Detection of biofilm formation using tissue culture plate method

Biofilm formation was evaluated using the tissue culture plate (TCP) method, a widely used quantitative in vitro assay for biofilm detection, as previously described by Christensen et al.²⁶. Fresh bacterial colonies were inoculated into Tryptic Soy Broth (TSB) supplemented with 1% glucose and incubated at 37 °C for 24 h. The cultures were then diluted 1:100, and 200 µL of each bacterial suspension was transferred into sterile flat-bottom 96-well microtiter plates. Negative control wells containing sterile broth only supplemented with 1% glucose without bacterial inoculation, were included in each experiment. Following incubation at 37 °C for 24 h, non-adherent cells were removed by washing with phosphate-buffered saline (PBS). Adherent biofilms were fixed with 99% methanol for 15 min and stained with 0.1% crystal violet. Excess stain was removed by washing with deionized water, and the bound dye was resolubilized using 160 µL of 33% glacial acetic acid. Optical density (OD) was measured at 570 nm using a microplate ELISA reader (Model 680, Bio-Rad, UK). All experiments were performed in triplicate. Mean OD₅₇₀ values obtained from replicate wells were used for biofilm classification. The optical density cut-off value (mean ODc: 0.11) was calculated as the mean OD₅₇₀ of the negative control wells plus three standard deviations. Biofilm production was classified as follows: strong biofilm producer (OD₅₇₀ > 4 × ODc), moderate biofilm producer (2 × ODc < OD₅₇₀ ≤ 4 × ODc), weak biofilm producer (ODc < OD₅₇₀ ≤ 2 × ODc), and non-biofilm producer (OD₅₇₀ ≤ ODc). The observed OD ranges for each biofilm category in the selected MDR/XDR isolates are provided in Supplementary Table S2.

Genomic DNA extraction

Genomic DNA was extracted using the phenol–chloroform method as described by²⁷. Then the DNA quality and integrity was assessed by electrophoresis on 1% agarose gel. All procedures were performed under aseptic conditions to minimize contamination.

Multiplex PCR

In this study, two distinct multiplex PCR assays were performed to characterize the virulence and antibiotic-resistance determinants of the selected MDR/XDR clinical A. baumannii isolates. PCR amplification was performed using a thermal cycler (Mastercycler Nexus Thermal Cycler, Eppendorf, Germany). Multiplex PCR was carried out to detect the virulence genes (ompA, bap, csuE, surA1, bfmR, and basD) under the following cycling conditions: initial denaturation at 94 °C for 5 min; 30 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 1 min; followed by a final extension at 72 °C for 5 min. To evaluate the presence of class A β-lactamase (bla_KPC), carbapenemase genes MBLs (bla_IMP, bla_VIM, and bla_NDM), class D β-lactamase (bla_OXA-51): a species-specific molecular confirmation marker, and adeA gene, multiplex PCR was performed under the following cycling conditions: initial denaturation at 94 °C for 5 min; 30 cycles of denaturation at 94 °C for 30 s, annealing at 54 °C for 30 s, and extension at 72 °C for 1min; followed by a final extension at 72 °C for 5 min. All PCR reactions were carried out using 2X PCR master mix (Bioline, UK) and all primers used in this study were purchased from macrogen (Seoul, South Korea) and listed in Table 1.

Table 1.

The primers used for the amplification of antibiotic-resistance and virulence genes.

Type of genes	Function	Primer code	Primer Sequence (5′ → 3′)	PCR product size (bp)	Annealing Tm. (°C)	Refs.
Antibiotic-resistance genes	Class A β-lactamase	KPC-F	CGTCTAGTTCTGCTGTCTTG	798	54	28
		KPC-R	CTTGTCATCCTTGTTAGGG
	Class B or metallo β-lactamase (MBLs)	NDM-F	GGTTTGGCGATCTGGTTTTC	621	54	28
		NDM-R	CGGAATGGCTCATCACGATC
		VIM-F	GATGGTGTTTGGTCGCATA	390	54	28
		VIM-R	CGAATGCGCAGCACCAG
		IMP-F	GGAATAGAGTGGCTTAATTCTC	232	54	28
		IMP-R	GGTTTAACAAAACAACCACC
	Class D β-lactamase	OXA 51-F	TAATGCTTTGATCGGCCTTG	353	54	29
		OXA 51-R	TGGATTGCACTTCATCTTGG
	Efflux pumps	AdeA-F	GCCACCACCGGCTAAAGTCA	654	54	30
		AdeA-R	GGTTGCCCGTGGCTATTGGT
Virulence genes	Biofilm formation	CsuE-F	ACCAATGCTCAGACCGGAG	751	55	30
		CsuE-R	CTTGTACCGTGACCGTATCTTG
		OmpA-F	CGCTTCTGCTGGTGCTGAAT	531	55	31
		OmpA-R	CGTGCAGTAGCGTTAGGGTA
		Bap-F	ATGCCTGAGATACAAATTAT	1449	55	32
		Bap-R	GTCAATCGTAAAGGTAACG
		SurA1-F	CAATTGGTAGCTGGCGATCA	241	55	33
		SurA1-R	TTAGGCGGGACTCAGCTTTT
	Biofilm regulatory system	BfmR-F	GGATCTTGTGGTCTTGGATGTC	384	55	34
		BfmR-R	GATAAAATACGGCCAGCGTTTG
	Siderophore production	BasD-F	CTCTTGCATGGCAACACCAC	868	55	35
		BasD-R	CCAACGAGACCGCTTATGGT

PCR products were separated on 3% agarose gel prepared with 5μg/mL ethidium bromide (Thermo Fisher Scientific, USA) in TAE buffer. Electrophoresis was performed at 100 V for 45 min, and DNA bands were visualized under UV illumination. A 100 bp DNA ladder (GDSBio, China) was used as a molecular size marker.

Statistical analysis

Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 25. Associations between variables were analyzed using the Chi-square test or Fisher’s exact test when appropriate. Fisher’s exact test was applied when the expected frequency in any cell of the contingency table was small. A p value ≤ 0.05 was considered statistically significant.

Results

Demographic characteristics of the study population

In the present study, a total of 150 non-duplicate MDR/XDR clinical A. baumannii isolates were selectively recovered from clinical specimens obtained from patients aged between 12 and 75 years. The age distribution of the studied patients is illustrated in (Fig. 1A). Patients were categorized into seven age groups. The highest frequencies were observed among patients aged 50–59 years and 60–69 years, with 33 patients in each group. This was followed by the 20–29 and 30–39 age groups, each comprising 21 patients. Eighteen patients belonged to the 40–49 age group, while 15 patients were aged 70–79 years. The lowest number of patients was recorded in the 10–19 age group (n = 9). A higher proportion of the selected MDR/XDR isolates was obtained from female patients (n = 87, 58%) compared to male patients (n = 63, 42%), as illustrated in (Fig. 1B). The distribution of the selected MDR/XDR clinical specimens is shown in (Fig. 1C). The majority of the selected MDR/XDR isolates were obtained from urine specimens (n = 102, 68%), followed by sputum samples (n = 30, 20%), while bloodstream and wound specimens represented the least common sources of isolation, with 9 isolates each (6%).

Fig. 1.

Demographic characteristics of the study population. (A) Age group percentage, (B) Gender percentage, (C) Clinical specimens’ percentage.

Antimicrobial susceptibility test

Multidrug-resistant (MDR) and extensively drug-resistant (XDR) A. baumannii isolates were classified based on antimicrobial category-level nonsusceptibility according to the international standard definitions proposed by Magiorakos et al.³⁶. MDR was defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories, whereas XDR was defined as non-susceptibility to at least one agent in all but two or fewer antimicrobial categories (i.e. bacterial isolates remain susceptible to only one or two categories).

In the present study, among the selected MDR/XDR clinical A. baumannii isolates, 126 (84%) were classified as XDR, and 24 (16%) were MDR. The antimicrobial susceptibility testing revealed widespread resistance across multiple antibiotic classes. Among penicillin and β-lactam/β-lactamase inhibitor combinations, high resistance rates were observed for piperacillin–tazobactam (72%) and ampicillin–sulbactam (68%). Within the cephalosporin group, cefepime (84%), ceftazidime (76%), and ceftriaxone (76%) showed substantial resistance. For carbapenems, meropenem resistance was observed in 64% of isolates. Among aminoglycosides, resistance affected 78% of isolates for tobramycin and 70% for gentamicin. Fluoroquinolones also showed significant resistance, with ciprofloxacin at 82% and levofloxacin at 70%. Finally, trimethoprim–sulfamethoxazole displayed the lowest resistance among all tested agents, affecting 60% of isolates. These findings are summarized in Table 2 and illustrated in Fig. 2, which shows the antimicrobial susceptibility profile of the selected MDR/XDR clinical A. baumannii isolates.

Table 2.

Antimicrobial susceptibility profile of 150 selected MDR/XDR clinical A. baumannii isolates.

Antibiotic class	Antibiotic (abbreviation)	(S) n (%)	(I) n (%)	(R) n (%)
Penicillins + β-lactamase inhibitor	Ampicillin–sulbactam (SAM)	36 (24%)	12 (8%)	102 (68%)
	Piperacillin–tazobactam (TZP)	18 (12%)	24 (16%)	108 (72%)
Cephalosporins	Ceftazidime (CAZ)	27 (18%)	9 (6%)	114 (76%)
	Ceftriaxone (CRO)	15 (10%)	21 (14%)	114 (76%)
	Cefepime (FEP)	18 (12%)	6 (4%)	126 (84%)
Carbapenems	Meropenem (MEM)	51 (34%)	3 (2%)	96 (64%)
Aminoglycosides	Gentamicin (GEN)	45 (30%)	0 (0%)	105 (70%)
	Tobramycin (TOB)	27 (18%)	6 (4%)	117 (78%)
Fluoroquinolones	Ciprofloxacin (CIP)	27 (18%)	0 (0%)	123 (82%)
	Levofloxacin (LEV)	30 (20%)	15 (10%)	105 (70%)
Others (Folate pathway inhibitor)	Trimethoprim–sulfamethoxazole (SXT)	60 (40%)	0 (0%)	90 (60%)

S sensitive, I intermediate, R resistant, n number of isolates.

Fig. 2.

Antimicrobial susceptibility testing of 150 selected MDR/XDR clinical A. baumannii isolates, SAM (ampicillin/sulbactam), TZP (piperacillin/tazobactam), CAZ (ceftazidime), CRO (ceftriaxone), FEP (cefepime), MEM (meropenem), GEN (gentamicin), TOB (tobramycin), CIP (ciprofloxacin), LEV (levofloxacin), SXT (trimethoprim/sulfamethoxazole), S (sensitive), I (intermediate), R (resistant).

Metallo-ß-lactamase (MBL) test

All 150 selected MDR/XDR clinical A. baumannii isolates were MBL-positive by the combined disk test, showing an increase of ≥ 7 mm in inhibition zones with imipenem-EDTA disks (Fig. 3). The phenotypic and genotypic comparison of MBL detection among the studied Acinetobacter baumannii isolates is presented in Supplementary Table S3.

Fig. 3.

Representative A. baumannii isolate for Metallo-ß-lactamase test. (A) EDTA-IMP disc showing a clear inhibition zone ≥ 7 mm, indicating a positive result for Metallo-β-lactamase production. (B) IMP disc alone, reflecting resistance of the isolate to imipenem.

Molecular detection of antibiotic resistance genes

Previously identified and characterized Acinetobacter baumannii isolates harboring the targeted resistance genes (unpublished data), were obtained from the culture collection of the Microbiology Laboratory, Botany and Microbiology Department, Faculty of Science, Damietta University. These isolates were used as positive controls for optimization of multiplex PCR conditions and determination of the expected amplicon sizes for each gene (Fig. 4A). No-template controls (nuclease-free water instead of DNA) to detect contamination in reagents, consumables, or the laboratory environment were included in each PCR run to ensure assay specificity and exclude contamination. The multiplex PCR analysis of antibiotic resistance genes revealed six distinct profiles among the selected MDR/XDR studied isolates (Fig. 4B). Each profile was defined according to the observed amplification pattern of the investigated genes as summarized in Table 3. Subsequently, PCR screening was analyzed to determine the distribution of individual antibiotic resistance genes among the 150 selected MDR/XDR clinical A. baumannii isolates. The intrinsic class D β-lactamase gene bla_OXA-51 was detected in all selected MDR/XDR isolates (150/150, 100%). Similarly, the adeA gene was identified in all studied isolates (150/150, 100%). Among MBL genes, bla_IMP was detected in 123 isolates (82.0%), followed by bla_NDM in 96 isolates (64.0%) and bla_VIM in 78 isolates (52.0%). In contrast, the class A carbapenemase gene bla_KPC was not detected in any of the selected MDR/XDR studied isolates (Fig. 5).

Fig. 4.

PCR products of the amplified antibiotic resistance genes on agarose gel electrophoresis. (A) Optimization of the PCR using previously characterized A. baumannii isolate, Lane 1: multiplex PCR for all antibiotic resistance genes. Lanes 2–6: uniplex PCR for adeA, bla_NDM, bla_VIM, bla_OXA-51 and bla_IMP, respectively. Lane 7: negative control (B) The multiplex PCR for the selected MDR/XDR clinical A. baumannii isolates showing different six profiles (see Table 3) for the antibiotic resistance gene among the selected MDR/XDR clinical A. baumannii isolates. M (100 bp DNA marker).

Table 3.

Resistance gene profiles and their frequency resulting in multiplex PCR for antibiotic resistance genes of 150 selected MDR/XDR clinical A. baumannii isolates.

Pattern	Gene profile	No. of genes	No. of isolates	(%)
P I	adeA—blaNDM—blaVIM—blaOXA-51—blaIMP	5	48	32
P II	adeA—blaNDM—blaOXA-51—blaIMP	4	27	18
P III	adeA—blaVIM—blaOXA-51—blaIMP	4	24	16
P IV	adeA—blaNDM—blaOXA-51	3	21	14
P V	adeA—blaVIM—blaOXA-51	3	6	4
P VI	adeA—blaOXA-51—blaIMP	3	24	16

Fig. 5.

Frequency of antibiotic resistance genes among the selected MDR/XDR clinical A. baumannii isolates.

Biofilm formation strength

Out of the selected MDR/XDR clinical A. baumannii isolates, 144 (96.0%) demonstrated the ability to form biofilm, whereas only six isolates (4.0%) were classified as non-biofilm producers. Among the biofilm-forming selected MDR/XDR isolates, 54 (36.0%) were identified as strong, 66 (44.0%) as moderate and 24 (16.0%) as weak biofilm producers (Fig. 6), indicating that moderate biofilm formation was the most prevalent phenotype.

Fig. 6.

Biofilm formation strength of the 150 selected MDR/XDR A. baumannii isolates, S (strong), M (moderate), W (weak).

Molecular detection of virulence-associated genes

Multiplex PCR was performed to investigate the presence and distribution of virulence-associated genes among the selected MDR/XDR clinical A. baumannii isolates. The previously characterized A. baumannii isolate carrying the targeted virulence genes was used to optimize the multiplex PCR conditions and to determine the expected amplicon size for each gene (Fig. 7A). No-template controls (nuclease-free water instead of DNA) to detect contamination in reagents, consumables, or the laboratory environment were included in each PCR run to ensure assay specificity and exclude contamination. The multiplex PCR analysis of virulence genes revealed six distinct profiles among the selected MDR/XDR studied isolates (Fig. 7B). Each profile was defined according to the observed amplification pattern of the investigated genes as summarized in Table 4. Molecular analysis revealed a high detection rate of biofilm-related determinants among the selected studied isolates, with most of the studied isolates harboring multiple biofilm-associated genes. Specifically, bfmR and surA1 were detected in all selected isolates (150/150, 100%). The csuE gene was identified in 141 isolates (94%), while ompA was detected in 120 isolates (80%). The bap gene showed the lowest frequency among the studied biofilm-associated genes, being present in 69 isolates (46%). Additionally, the siderophore-associated gene basD was detected in all selected isolates (150/150, 100%) (Fig. 8).

Fig. 7.

PCR products of the amplified virulence associated genes on agarose gel electrophoresis. (A) Optimization of the PCR using previously characterized A. baumannii isolate, Lane 1: multiplex PCR for all virulence associated genes. Lanes 2–7: uniplex PCR for bap, basD, csuE, ompA, bfmR and surA1, respectively. lane 8: negative control (B) The multiplex PCR for the selected MDR/XDR A. baumannii isolates showing different six profiles, (see Table 4) for the virulence associated genes among the selected MDR/XDR clinical A. baumannii isolates.

Table 4.

Virulence associated gene profiles identified by multiplex PCR in the selected MDR/XDR A. baumannii isolate.

Profile	Gene profile	No. of genes	No. of isolates	%
P I	bap—basD—csuE—ompA—bfmR—surA1	6	63	42
P II	bap—basD—csuE—bfmR—surA1	5	6	4
P III	basD—csuE—ompA—bfmR—surA1	5	51	34
P IV	basD—csuE—bfmR—surA1	4	21	14
P V	basD—ompA—bfmR—surA1	4	6	4
P VI	basD—bfmR—surA1	3	3	2

Fig. 8.

Frequency of virulence genes among the selected MDR/XDR A. baumannii isolates.

Correlation between antimicrobial resistance pattern (MDR & XDR) and biofilm formation

A statistically significant association was observed between biofilm formation and antimicrobial resistance pattern. However, this finding should be interpreted with caution due to the small number of non-biofilm-producing isolates (n = 6), all of which were MDR, and the preselection of isolates based on MDR/XDR phenotypes, as shown in Table 5.

Table 5.

Correlation between antimicrobial resistance pattern (MDR & XDR) and biofilm formation.

XDR-MDR (No. of isolates)	Biofilm formation (No. of isolates)		P value
	Biofilm forming (144)	Non-Biofilm forming (6)
XDR (126)	126	0	< 0.001
MDR (24)	18	6
Total (150)	144	6

(P ≤ 0.05) is considered statistically significant.

Correlation between biofilm formation and antimicrobial susceptibility profile

As shown in Table 6, a significant association was observed between biofilm formation and antimicrobial susceptibility profile for most tested antibiotics. Significant associations were detected for ampicillin/sulbactam (SAM), ceftazidime (CAZ), cefepime (FEP), meropenem (MEM), gentamicin (GEN), tobramycin (TOB), ciprofloxacin (CIP), levofloxacin (LEV), and trimethoprim/sulfamethoxazole (SXT), while no significant association was observed for piperacillin/tazobactam (TZP) and ceftriaxone (CRO).

Table 6.

Correlation between biofilm formation and antimicrobial susceptibility profile.

Type of antibiotic	Antibiotic susceptibility profile	Biofilm formation (No. of isolates)		P value
		Biofilm forming (144)	Non-biofilm forming (6)
SAM	S (36)	30	6	< 0.001
	NS (114)	114	0
TZP	S (18)	18	0	1.000
	NS (132)	126	6
CAZ	S (27)	21	6	< 0.001
	NS (123)	123	0
CRO	S (15)	15	0	1.000
	NS (135)	129	6
FEP	S (18)	12	6	< 0.001
	NS (132)	132	0
MEM	S (51)	45	6	0.001
	NS (99)	99	0
GEN	S (45)	39	6	0.001
	NS (105)	105	0
TOB	S (27)	21	6	< 0.001
	NS (123)	123	0
CIP	S (27)	21	6	< 0.001
	NS (123)	123	0
LEV	S (30)	24	6	< 0.001
	NS (120)	120	0
SXT	S (60)	54	6	0.004
	NS (90)	90	0

(P ≤ 0.05) is considered statistically significant.

S susceptible, Ns non-susceptible.

Correlation between antibiotic resistance genes and antimicrobial susceptibility profile

As shown in Table 7, the association between antimicrobial susceptibility profile and β-lactamase genes was evaluated. For bla_IMP, significant associations were observed with ceftazidime (CAZ), ceftriaxone (CRO), meropenem (MEM), and ciprofloxacin (CIP) (P < 0.05), while no significant associations were detected for the remaining antibiotics. For bla_NDM, significant associations were observed with ampicillin/sulbactam (SAM), ceftazidime (CAZ), and meropenem (MEM) (p ≤ 0.05), whereas no significant associations were observed for the other antibiotics. Regarding bla_VIM, significant associations were observed with cefepime (FEP), tobramycin (TOB), and trimethoprim/sulfamethoxazole (SXT) (p < 0.05), while no significant associations were detected for the remaining antibiotics. Overall, gene distribution showed variable associations across different antimicrobial classes.

Table 7.

Correlation between antibiotic resistance genes and antimicrobial susceptibility profile.

Types of antibiotics	Antibiotic susceptibility profile	Antibiotic resistance genes (No. of isolates)								p value
		blaIMP (123)		p value	blaNDM (96)		p value	blaVIM (78)
		Yes	No		Yes	No		Yes	No
SAM	S (36)	27	9	0.220	18	18	0.049	21	15	0.446
	NS (114)	96	18		78	36		57	57
TZP	S (18)	12	6	0.098	12	6	1.000	9	9	1.000
	NS (132)	111	21		84	48		69	63
CAZ	S (27)	15	12	< 0.001	12	15	0.026	12	15	0.404
	NS (123)	108	15		84	39		66	57
CRO	S (15)	9	6	0.031	12	3	0.258	9	6	0.593
	NS (135)	114	21		84	51		69	66
FEP	S (18)	12	6	0.098	9	9	0.200	3	15	0.002
	NS (132)	111	21		87	45		75	57
MEM	S (51)	36	15	0.013	27	24	0.050	27	24	1.000
	NS (99)	87	12		69	30		51	48
GEN	S (45)	36	9	0.651	30	15	0.713	21	24	0.476
	NS (105)	87	18		66	39		57	48
TOB	S (27)	21	6	0.581	18	9	0.827	6	21	0.001
	NS (123)	102	21		78	45		72	51
CIP	S (27)	15	12	< 0.001	15	12	0.377	12	15	0.404
	NS (123)	108	15		81	42		66	57
LEV	S (30)	21	9	0.066	15	15	0.090	15	15	0.840
	NS (120)	102	18		81	39		63	57
SXT	S (60)	45	15	0.084	39	21	0.864	39	21	0.012
	NS (90)	78	12		57	33		39	51

(p ≤ 0.05) is considered statistically significant.

S susceptible, Ns non-susceptible.

Correlation between antibiotic resistance genes and biofilm formation

A significant association was observed between biofilm formation and bla_VIM gene, while no significant associations were detected for bla_IMP or bla_NDM, as shown in Table 8.

Table 8.

Correlation between antibiotic resistance genes and biofilm formation.

Biofilm formation (No. of isolates)	Antibiotic resistance genes (No. of isolates)								p value
	blaIMP (123)		p value	blaNDM (96)		p value	blaVIM (78)
	Yes	No		Yes	No		Yes	No
Biofilm forming (144) Non-Biofilm forming (6)	120	24	0.072	93	51	0.668	78	66	0.011
	3	3		3	3		0	6

(p ≤ 0.05) is considered statistically significant.

Correlation between virulence genes and biofilm formation

A significant association was observed between biofilm formation and csuE gene, while no significant associations were detected for ompA or bap genes, as shown in Table 9.

Table 9.

Correlation between virulence genes and biofilm formation.

Biofilm formation (No. of isolates)	Virulence genes (No. of isolates)
	csuE (141)		p value	ompA (120)		p value	Bap (69)		p value
	Yes	No		Yes	No		Yes	No
Biofilm forming (144) Non-Biofilm forming (6)	138	6	0.003	117	27	0.095	66	78	1.000
	3	3		3	3		3	3

(p ≤ 0.05) is considered statistically significant.

Correlation between virulence genes and antimicrobial susceptibility profile

The association between antibiotic susceptibility phenotypes and virulence genes (csuE, ompA, and bap) was evaluated. For csuE, significant correlations were observed with ampicillin/sulbactam (SAM), ceftazidime (CAZ), meropenem (MEM), ciprofloxacin (CIP), and levofloxacin (LEV), while no significant correlations were observed with the remaining antibiotics. For ompA, significant correlations were identified with ceftazidime (CAZ), gentamicin (GEN), and trimethoprim/sulfamethoxazole (SXT), while no significant correlations were observed with the remaining antibiotics. Regarding bap, significant correlations were observed with tobramycin (TOB) and trimethoprim/sulfamethoxazole (SXT), while no significant correlations were observed with the remaining antibiotics as shown in Table 10.

Table 10.

Correlation between virulence genes and antimicrobial susceptibility profile.

Types of antibiotics	Antibiotic Susceptibility profile	Virulence genes (No. of isolates)
		csuE (141)		p value	ompA (120)		P value	Bap (69)		p value
		Yes	No		Yes	No		Yes	No
SAM	S (36)	27	9	< 0.001	27	9	0.473	18	18	0.702
	NS (114)	114	0		93	21		51	63
TZP	S (18)	15	3	0.077	12	6	0.204	6	12	0.317
	NS (132)	126	6		108	24		63	69
CAZ	S (27)	21	6	0.001	15	12	0.001	9	18	0.201
	NS (123)	120	3		105	18		60	63
CRO	S (15)	15	0	0.599	9	6	0.080	3	12	0.053
	NS (135)	126	9		111	24		66	69
FEP	S (18)	15	3	0.077	12	6	0.204	12	6	0.078
	NS (132)	126	6		108	24		57	75
MEM	S (51)	42	9	< 0.001	36	15	0.052	24	27	0.864
	NS (99)	99	0		84	15		45	54
GEN	S (45)	42	3	1.000	30	15	0.013	24	21	0.285
	NS (105)	99	6		90	15		45	60
TOB	S (27)	24	3	0.206	21	6	0.792	18	9	0.020
	NS (123)	117	6		99	24		51	72
CIP	S (27)	21	6	0.001	18	9	0.066	12	15	1.000
	NS (123)	120	3		102	21		57	66
LEV	S (30)	24	6	0.002	24	6	1.000	15	15	0.685
	NS (120)	117	3		96	24		54	66
SXT	S (60)	54	6	0.157	42	18	0.021	21	39	0.031
	NS (90)	87	3		78	12		48	42

(p ≤ 0.05) is considered statistically significant.

S susceptible, Ns non-susceptible.

Co-occurrence between virulence genes and antibiotic resistance genes

The association between β-lactamase genes and virulence genes was evaluated. For bla_IMP, significant associations were observed with csuE and ompA, while no significant association was detected with bap. For bla_NDM, no significant associations were observed with any of the virulence genes. Regarding bla_VIM, a significant association was observed with bap, whereas no significant associations were detected with csuE or ompA. as illustrated in Table 11.

Table 11.

Co-occurrence between virulence genes and antibiotic resistance genes.

Virulence genes (No. of isolates)		Antibiotic resistance genes (No. of isolates)
		blaIMP (123)		p value	blaNDM (96)		p value	blaVIM (78)		p value
		+	−		+	−		+	−
bap (69)	+	60	9	0.201	42	27	0.498	24	45	< 0.001
	−	63	18		54	27		54	27
csuE (141)	+	120	21	0.001	93	48	0.071	72	69	0.498
	−	3	6		3	6		6	3
ompA (120)	+	105	15	0.001	72	48	0.055	63	57	0.840
	−	18	12		24	6		15	15

(p ≤ 0.05) is considered statistically significant. + (positive), − (negative).

Association between sample source and virulence genes

The association between sample source and biofilm genes (csuE, ompA, and bap) was evaluated. No significant association was observed for csuE and ompA with sample source, while bap showed a significant association, with higher distribution in urine and respiratory isolates compared to blood and wound samples.as showed in Table 12.

Table 12.

Association between sample source and virulence genes.

Sample source (No. of isolates)	virulence genes (No. of isolates)
	csuE (141)		p value	ompA (120)		p value	Bap (69)		p value
	Yes	No		Yes	No		Yes	No
Urine (102)	93	9	0.362	78	24	0.103	48	54	0.014
Sputum (30)	30	0		27	3		15	15
Blood (9)	9	0		9	0		0	9
Wound (9)	9	0		6	3		6	3

(p ≤ 0.05) is considered statistically significant.

Association between sample source and antibiotic resistance genes

The association between sample source and β-lactamase genes was evaluated. No significant associations were observed for bla_IMP and bla_VIM, while bla_NDM showed a significant association with sample source as showed in Table 13.

Table 13.

Association between sample source and antibiotic resistance genes.

Sample source (No. of isolates)	Antibiotic resistance genes (No. of isolates)
	blaIMP (123)		p value	blaNDM (96)		p value	blaVIM (78)		p value
	Yes	No		Yes	No		Yes	No
Urine (102)	84	18	0.325	57	45	0.006	54	48	0.571
Sputum (30)	24	6		24	6		15	15
Blood (9)	9	0		6	3		6	3
Wound (9)	6	3		9	0		3	6

(p ≤ 0.05) is considered statistically significant.

Discussion

Over the past decades, A. baumannii has gained increasing attention as a critical priority pathogen in healthcare settings worldwide. The global rise of multidrug-resistant A. baumannii represents a significant clinical challenge. Its combined capacity for antimicrobial resistance acquisition and biofilm formation might play a pivotal role in therapeutic failure and persistent hospital transmission. In the present study, a higher proportion of the selected MDR/XDR A. baumannii isolates was observed among females compared to males. Similar findings regarding the predominance of female patients have been reported in Egypt, Jordan, and India^37–39. Notably, urine samples were the most frequent source of the selected MDR/XDR isolates in this study, consistent with previous reports^38,40. However, since detailed clinical data were not available to distinguish between true infection and colonization, particularly for urine and sputum samples, these isolates are referred to as clinical isolates obtained from various specimen types rather than as causative agents of confirmed infections. Among the selected isolates, XDR isolates were more frequent than MDR isolates, consistent with reports from several Egyptian healthcare settings⁴¹. Carbapenem resistance remains a major clinical concern, as these agents are among the most effective therapeutic options against A. baumannii. Meropenem resistance rates have been documented in previous studies, ranging from approximately 52–98% depending on the geographic region and study population^42–44. In addition to carbapenem resistance, high resistance was observed for several antibiotic classes in our study. Higher resistance rates, up to 100%, have been reported for certain antibiotics in some studies, including piperacillin/tazobactam, cefepime, ceftazidime, ceftriaxone, gentamicin, ciprofloxacin, and levofloxacin^39,45,46, ampicillin-sulbactam resistance in other study reached 71.7%⁴⁷, tobramycin resistance in other study reached 78%⁴⁵, and trimethoprim-sulfamethoxazole from 53.3 to 98%^45–47. These variations in resistance patterns likely reflect differences in antibiotic usage, geographic location, infection control practices, and patient populations.

Regarding metallo-β-lactamase (MBL) production, all selected MDR/XDR A. baumannii isolates were positive by the combined disc test, and PCR confirmed that each isolate carried at least one MBL gene, with some harboring multiple genes. This widespread distribution may reflect clonal dissemination or horizontal gene transfer and is consistent with previous reports of high MBLdetection³⁹. It is important to note that EDTA-based phenotypic methods have limitations, including possible false-positive results due to non-MBL mechanisms, and should therefore be interpreted alongside molecular findings.

Molecular screening demonstrated widespread distribution of resistance-associated genes among the selected MDR/XDR A. baumannii isolates. The intrinsic bla_OXA-51 gene was detected in all selected isolates, consistent with previous studies^39,48, which further supports its role as a reliable molecular marker for species identification within the A. calcoaceticus–baumannii complex, as it is intrinsic to A. baumannii and rarely found in other members of the complex. Similarly, the adeA gene was detected in all selected isolates, in agreement with several reports^49,50, although lower frequencies have also been described³⁷. A recent global systematic review identified bla_IMP, bla_NDM, and bla_VIM as the most commonly detected MBL genes among A. baumannii worldwide⁵¹. This study revealed that bla_IMP was the predominant gene followed by bla_NDM and bla_VIM consistent with Sharma et al.⁵². In contrast, bla_KPC was not detected, in agreement with Mahmood et al.⁵³, although it has been reported in other regions in all isolates⁴⁴. These findings reflect the geographical variability of carbapenemase genes among the selected MDR/XDR clinical A. baumannii isolates.

Biofilm production is an important virulence and survival mechanism in A. baumannii, which might contribute to antimicrobial tolerance⁵⁴. In the present study, most of the selected MDR/XDR clinical isolates were biofilm producers, with moderate biofilm formation being the predominant phenotype. Similar findings have been reported in previous studies^55,56, although lower rates were described elsewhere⁵⁷.

Multiplex PCR analysis revealed that all selected MDR/XDR clinical A. baumannii isolates harbored the basD gene, consistent with previous studies reporting similarly high detection rates^45,58, although lower frequencies have also been described⁵⁹. In addition, surA1 and bfmR genes were detected in all selected MDR/XDR clinical isolates, supporting their strong conservation among the studied clinical A. baumannii isolates and aligning with some previous reports^59,60. The csuE gene showed a higher detection rate than ompA, while bap exhibited the lowest frequency, consistent with previous studies^61,62. High detection rates of csuE have also been widely reported^56,61,63. In agreement with Zeighami et al., the ompA gene was detected in most of the selected studied isolates⁶⁴, although lower frequencies were described elsewhere^47,59. The bap gene showed the lowest frequency among the other studied genes, consistent with several studies^47,64,65, while higher rates have also been reported in all isolates^45,63. These findings reflect the variability in genes distribution among the selected MDR/XDR clinical A. baumannii isolates from different clinical and geographic settings. Interestingly, some of the selected MDR/XDR clinical A. baumannii isolates lacking some of the investigated biofilm–associated genes were still able to produce biofilm. This might be attributed to the presence of other biofilm-related genes that were not included in the current study, such as pgaABCD operon and abaI. Conversely, some of the selected isolates harboring one or more biofilm–associated genes didn’t exhibit biofilm formation, indicating that gene presence does not demonstrate overexpression or functional activity, and biofilm formation is a complex and multifactorial process⁶⁶.

A significant association between biofilm formation and the selected MDR/XDR status was observed in this selected subset, consistent with some previous studies^67,68. However, this finding should be interpreted cautiously, as all six non-biofilm producers were MDR, while all XDR isolates produced biofilm. The small non-biofilm group, group imbalance, and preselection of resistant isolates limit this correlation. Notably, a non-significant correlation was reported by Da Silva et al.⁶⁹, highlighting the variability of such associations across different study populations. Additionally, biofilm formation showed a significant association with antimicrobial non-susceptibility to most tested antibiotics in this exploratory analysis, possibly reflecting biofilm-associated antibiotic tolerance, as the biofilm matrix may impair antibiotic penetration and enhance bacterial survival independently of inherited resistance mechanisms. These findings are consistent with previous studies^55,70. However, no significant association was observed for TZP and CRO likely reflecting differences in resistance mechanisms and sample distribution. The antimicrobial susceptibility profile of A. baumannii was observed in relation to resistance-related genes, with both significant and non-significant associations across different antibiotics. It is important to emphasize that the association between MBL carriage and non-susceptibility to ciprofloxacin, tobramycin and trimethoprim-sulfamethoxazole is correlative, not causative, as MBL enzymes specifically degrade carbapenems and other β-lactams. Although, the underlying mechanisms were not directly examined, the observed statistical associations could be explained by possible co-carriage of resistance genes on mobile genetic elements or the dissemination of high-risk clones carrying multiple resistance determinants. Nevertheless, these interpretations require further investigation. In addition, variable statistical associations were noted between biofilm-related genes and antimicrobial susceptibility profile in the selected MDR/XDR A. baumannii isolates, with both significant and non-significant associations across different antibiotics, highlighting the multifactorial nature of this relationship. Biofilm formation also showed variable statistically significant and non-significant associations with both resistance and virulence genes, possibly indicating a complex and non-uniform relationship between phenotypic traits and genetic determinants. These findings are exploratory and do not imply direct causative links. The presence of genetic determinants does not always correlate with their corresponding phenotypic expression. Statistically significant and non-significant associations were also observed between virulence determinants and antibiotic resistance genes in the selected MDR/XDR A. baumannii isolates. Although the specific mechanisms underlying these associations were not investigated in the present study, several hypotheses could be considered. For instance, the coexistence of these determinants on mobile genetic elements (such as plasmids, integrons, or transposons) might facilitate their co-transfer. Alternatively, clonal dissemination of strains carrying combined resistance and virulence traits could contribute to their persistence in clinical settings. However, these interpretations remain speculative and require further experimental validation. Importantly, all association analyses in this study are exploratory and should be interpreted with caution due to the large number of comparisons performed.

Limitations

The isolates were selectively collected based on MDR/XDR resistance profiles and therefore may not represent the overall distribution of clinical A. baumannii isolates, which may limit the generalizability and comparison with susceptible isolates. In addition, lack of clinical outcome data prevented correlation with patient outcomes, and lack of MIC distributions. Clonal relatedness was not assessed, and whole-genome sequencing was not performed. Sequencing confirmation of representative PCR amplicons was not performed. The study also included an incomplete carbapenemase gene panel, as it did not investigate major bla_OXA-type carbapenemase genes that are important in carbapenem-resistant A. baumannii, particularly bla_OXA-23-like, bla_OXA-24/40-like, and bla_OXA-58-like. Additionally, gene expression levels were not evaluated. Furthermore, biofilm-specific antibiotic tolerance testing was not performed.

Conclusions

This study revealed a high frequency of antibiotic resistance, biofilm formation, and virulence-associated genes among selectively collected MDR/XDR A. baumannii isolates, indicating widespread distribution of resistance and virulence determinants in the studied population. The study underscores the importance of infection control strategies and further research to elucidate the mechanisms underlying resistance and biofilm formation.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

CLSI

Clinical and Laboratory Standards Institute

WHO

The World Health Organization

CDC

Centers for Disease Control and Prevention

VAP

Ventilator-associated pneumonia

CKD

Chronic kidney disease

CRAb

Carbapenem-resistant A. baumannii

PBPs

Penicillin-binding proteins

RND

Resistance–nodulation–division

MICs

The minimum inhibitory concentrations

MHA

Mueller–Hinton agar

TSB

Tryptic soy broth

EDTA

Ethylene diamine tetra acetic acid

TAE

Tris–acetate–EDTA

DNA

Deoxyribonucleic acid

ESKAPE

Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter Species

MBL

Metallo-β-lactamase

IMP

Imipenemase

KPC

Klebsiella pneumoniae Carbapenemase

NDM

New Delhi MBL

VIM

Verona integron-encoded MBL

OXA

Oxacillinase

PCR

Polymerase chain reaction

SurA1

Surface antigen protein 1

OmpA1

Outer membrane protein

Bap

Biofilm associated protein

MDR

Multidrug-resistant

XDR

Extensively drug-resistant

S

Susceptible

I

Intermediate

R

Resistant

μg

Microgram

Author contributions

AKE, MIA designed the study and outlined the research plan. HHS collected the bacterial isolates and contributed in data analysis. AMA conducted laboratory experiments and performed statistical analysis. AKE, AMA carried out the molecular work and writing the manuscript. All authors revised the manuscript and approved the final form.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Data availability

All data generated or analysed during this study are included in this published article.

Declarations

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

The study was conducted on retrospectively collected clinical isolates obtained from routine diagnostic laboratory records between July 2024 and September 2025. Ethical approval was obtained retrospectively from the Subcommittee on Research Ethics for Basic Sciences, Damietta University, Egypt (DU-REC No. 372, approved on March 16, 2026), which specifically authorized the use of previously collected clinical isolates and associated data for research purposes. Written informed consent had been obtained from all patients or their legal guardians (for participants under 18 years of age) at the time of original sample collection as part of routine clinical diagnostic procedures in the participating clinical laboratories. All procedures were conducted in accordance with the Declaration of Helsinki."