Representative Targeted Molecular And Genomic Characterization Of Virulence Genes In Staphylococcus aureus From Diabetic Foot Infections

Summary

This study characterized the mechanisms of antimicrobial resistance, virulence determinants, and genomic features of Staphylococcus aureus isolates recovered from diabetic foot infections using antimicrobial susceptibility testing, PCR-based virulence profiling, and whole-genome sequencing.

Abstract

Diabetic foot infections (DFIs) represent a major public health concern, and methicillin-resistant Staphylococcus aureus (MRSA) is among the most clinically significant pathogens. This study investigated the prevalence of virulence genes (cna and hlg), antimicrobial resistance profiles, and representative genomic features of multidrug-resistant S. aureus isolates recovered from patients with DFIs. A cross-sectional observational study was conducted on 125 patients with diabetic foot infections between January and December 2024. Antimicrobial susceptibility testing was performed using the Kirby–Bauer disk diffusion method and cefoxitin screening according to Clinical and Laboratory Standards Institute (CLSI) guidelines, with S. aureus ATCC 25923 used as the quality-control strain. Vancomycin susceptibility was confirmed by minimum inhibitory concentration (MIC) testing. Polymerase chain reaction (PCR) was used to detect the virulence genes (cna and hlg) and blaOXA-group I genes. Whole-genome sequencing (WGS) was performed on two representative isolates, including one multidrug-resistant (MDR) isolate and one extensively drug-resistant (XDR) isolate, using a de novo sequencing approach to generate draft genome assemblies. Among 125 clinical specimens, bacterial growth was observed in 90 samples (72%), of which 45 isolates (50%) were identified as S. aureus. Among these isolates, 35/45 (77.78%) were classified as MRSA, and 36/45 (80%) were multidrug resistant. The hlg gene was detected in all isolates, whereas the cna gene was identified in 13/45 (28.89%) isolates. No blaOXA-group I genes were detected. Genomic analysis identified multiple resistance-associated genes, including blaZ, tet(38), norA, and vanT, together with CRISPR-Cas elements and plasmid-associated resistance determinants. These findings highlight the high prevalence of multidrug-resistant S. aureus in DFIs and support the importance of continued genomic surveillance of clinically relevant resistant strains.

Introduction

Numerous colonization and virulence characteristics render the gram-positive bacterium Staphylococcus aureus (S. aureus) a prevalent opportunistic pathogen capable of causing a wide range of infections, including impetigo, wound infections, furuncles, skin abscesses, bacteremia, and infective endocarditis¹. Some of these infections may progress to severe disease and require hospitalization, particularly in patients with diabetes mellitus, immunosuppression, malignancy, urinary catheterization, or human immunodeficiency virus infection¹.

Methicillin-resistant S. aureus (MRSA) strains are associated with substantial morbidity and mortality because of their ability to rapidly acquire antimicrobial resistance determinants and persist in healthcare environments¹. Patients with diabetes mellitus frequently develop diabetic foot ulcers because of neuropathy, vascular insufficiency, and impaired immune responses². Diabetic foot infections (DFIs) have a complex pathophysiology, and clinical outcomes are influenced by both microbial and host-associated factors, including bacterial virulence³. Although diabetic foot ulcers may contain polymicrobial communities composed of aerobic and anaerobic bacteria and fungi, S. aureus remains one of the predominant pathogens isolated from these infections⁴. The organism possesses several virulence determinants that facilitate immune evasion, tissue invasion, chronic colonization, and persistent infection. Furthermore, the acquisition of mecA/SCCmec-mediated methicillin resistance and other antimicrobial resistance determinants has considerably limited therapeutic options for DFI-associated infections^4,5. Previous studies have reported a high prevalence of multidrug-resistant (MDR) S. aureus isolates in diabetic foot infections, with resistance frequently associated with β-lactamase genes, including bla_TEM, bla_OXA, and bla_CTX-M variants⁶.

Several virulence-associated genes contribute to the pathogenicity and persistence of S. aureus in chronic wound infections. Among these, the hlg gene encodes γ-hemolysin, a cytotoxic factor associated with tissue destruction, inflammation, immune evasion, and persistence of community-acquired MRSA strains^7,8. The cna gene encodes a collagen-binding adhesin that facilitates bacterial adherence to collagen-rich tissues and contributes to chronic colonization and infection persistence⁸. Previous investigations identified a high prevalence of hlg among MRSA isolates recovered from diabetic foot infections, emphasizing the co-occurrence of virulence and antimicrobial resistance determinants in these infections⁹. Inappropriate antibiotic exposure, prolonged hospitalization, impaired tissue penetration of antimicrobial agents, and chronic wound progression further contribute to the emergence and dissemination of MDR organisms in patients with DFIs¹⁰. According to international definitions, multidrug-resistant (MDR) bacteria exhibit resistance to at least one antimicrobial agent in three or more antimicrobial classes, extensively drug-resistant (XDR) bacteria remain susceptible to only one or two antimicrobial classes, and pandrug-resistant (PDR) bacteria are resistant to all tested antimicrobial classes¹⁰. Despite the recognized clinical importance of S. aureus in diabetic foot infections, there remains limited integrated molecular and genomic information linking virulence determinants with antimicrobial resistance profiles in clinical isolates from this region.

Therefore, this study aimed to characterize antimicrobial resistance patterns, determine the prevalence of selected virulence genes (hlg and cna), investigate the occurrence of bla_OXA-group I genes, and perform representative whole-genome sequencing analysis of selected multidrug-resistant S. aureus isolates recovered from patients with diabetic foot infections.

Protocol

1. Study Patients

This study was approved by the Ethical Approval Committee of the University of Anbar, Ministry of Higher Education and Scientific Research, Iraq (Approval No. 145), Ramadi City, Anbar Governorate, Iraq, on December 24, 2023. All procedures involving human participants were performed in accordance with the institutional ethical guidelines of the University of Anbar. Written informed consent was obtained from all participants prior to enrollment.

A cross-sectional observational study was conducted from January to December 2024 at Ramadi Teaching Hospitals and affiliated private clinics in Anbar Governorate, Iraq. A total of 125 consecutive eligible patients with diabetic foot infections (DFIs) were enrolled during the study period. The sample size was determined according to the number of eligible patients available during the study period rather than by statistical calculation. Clinically, DFI was defined as the presence of a foot ulcer of any grade in patients with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM). Male and female patients with varying ulcer severities were included.

Patients were eligible if they had a clinically diagnosed diabetic foot ulcer, attended the participating healthcare facilities, and provided informed consent. Exclusion criteria included foot ulcers unrelated to diabetes mellitus (e.g., traumatic ulcers), referral from other healthcare facilities, inability to provide informed consent because of critical illness, receipt of antibiotic therapy within 48 h prior to specimen collection, and polymicrobial infections. Patients with polymicrobial infections were excluded to ensure accurate phenotypic, molecular, and genomic characterization of Staphylococcus aureus isolates. Demographic and clinical data, including age, sex, diabetic complications, duration of diabetes mellitus, antibiotic history, and comorbid conditions, were collected using a structured questionnaire.

Clinical specimens were transported to the microbiology laboratory within 2 h of collection under refrigerated conditions (4 °C) using sterile transport swabs containing Amies medium and processed immediately for microbiological analysis. All procedures involving clinical specimens, bacterial cultures, antimicrobial susceptibility testing, polymerase chain reaction (PCR), and ultraviolet (UV) visualization were conducted under Biosafety Level 2 (BSL-2) laboratory conditions according to institutional biosafety guidelines. Laboratory personnel used appropriate personal protective equipment (PPE), including laboratory coats, disposable gloves, surgical masks, and eye protection when required. Strict aseptic procedures were followed throughout all microbiological and molecular procedures to minimize contamination and exposure risks. Dedicated working areas were used for bacterial culture handling and DNA amplification procedures to prevent cross-contamination. Contaminated materials, including culture plates, swabs, pipette tips, and disposables, were autoclaved at 121 °C and 15 psi for 15–20 min before disposal. Sharps were discarded in designated puncture-resistant biohazard containers. Biological waste was managed according to institutional biomedical waste disposal protocols. These biosafety measures ensured the safe handling of multidrug-resistant organisms, including MRSA and vancomycin-resistant isolates (Figure 1).

Figure 1: Overview of the clinical, microbiological, molecular, whole-genome sequencing, and bioinformatics workflow used in the study. The figure summarizes specimen collection, microbiological culture, antimicrobial susceptibility testing, PCR-based molecular detection, whole-genome sequencing, and downstream bioinformatics analyses. This figure was generated with assistance from the AI-based design platform Gamma Pro (Gamma App) and subsequently reviewed, revised, and validated by the authors for scientific accuracy. Please click here to view a larger version of this figure.

Data were analyzed using SPSS software version 22.0. Descriptive statistics, including means and percentages, were calculated. Associations between categorical variables were analyzed using the chi-square test. A p-value <0.05 was considered statistically significant.

2. Processing and collection of samples

Specimens were collected from the deeper portion of diabetic foot ulcers using the deep-swab technique. Two sterile cotton swabs pre-moistened with sterile broth were rotated firmly over the wound base after debridement with a sterile scalpel and cleansing with sterile saline to minimize contamination by colonizing microorganisms. One swab was used for Gram staining, whereas the second swab was used for microbiological culture. Direct Gram-stained smears were examined microscopically.

Bone tissue specimens were obtained from patients with clinically suspected osteomyelitis under sterile conditions following surgical debridement. Prior to specimen collection, ulcer surfaces were cleansed with sterile normal saline to reduce superficial contamination. Bone tissue samples were aseptically collected using sterile surgical instruments and immediately transferred to sterile containers for microbiological processing.

Specimens were homogenized or finely minced under sterile conditions and inoculated onto blood agar, Mannitol Salt Agar (MSA), MacConkey agar, and nutrient agar. Plates were aerobically incubated at 37 °C for 18–24 h. Blood agar and nutrient agar supported the growth of gram-positive and gram-negative organisms, whereas MSA was used for selective isolation and differentiation of Staphylococcus species, including S. aureus. MacConkey agar was used for recovery of gram-negative bacteria. Culture plates were examined after incubation, and specimens without visible growth after 48 h were reported as “no growth.”

Preliminary bacterial identification was based on colony morphology, Gram staining, and biochemical characteristics, followed by molecular confirmation of S. aureus using PCR amplification of the nuc gene. Biochemical identification included catalase testing, slide and tube coagulase tests, mannitol fermentation, and DNase testing. Confirmed isolates were further identified using the VITEK 2 Compact system with the VITEK 2 GP identification card. Identification results were accepted only when the confidence level was ≥95%. Discordant or low-confidence results were retested using repeat biochemical analysis and repeat VITEK testing. Pure isolates were preserved in 20% glycerol prepared in brain heart infusion (BHI) broth for subsequent molecular and genomic analyses (Figure 1).

3. Antimicrobial susceptibility testing

Antimicrobial susceptibility testing was performed using the Kirby–Bauer disk diffusion method according to the Clinical and Laboratory Standards Institute (CLSI) 2022 guidelines. Testing was conducted on Mueller–Hinton agar with a standardized agar depth of 4 mm. Fresh bacterial cultures were adjusted to a 0.5 McFarland standard using a densitometer before inoculation. Sterile swabs were used to evenly inoculate agar surfaces.

The following antimicrobial disks were used: ampicillin (10 µg), gentamicin (10 µg), amikacin (30 µg), cefoxitin (30 µg), cefuroxime (30 µg), piperacillin/tazobactam (100/10 µg), meropenem (10 µg), amoxicillin–clavulanic acid (30 µg), oxacillin (1 µg), levofloxacin (5 µg), clindamycin (2 µg), tigecycline (15 µg), ciprofloxacin (5 µg), erythromycin (15 µg), trimethoprim–sulfamethoxazole (25 µg), linezolid (30 µg), and vancomycin (30 µg). Plates were incubated aerobically at 37 °C for 16–18 h. Zone diameters were interpreted according to CLSI breakpoints.

Methicillin-resistant Staphylococcus aureus (MRSA) was identified using cefoxitin (30 µg) screening according to CLSI recommendations. Quality-control testing was performed using S. aureus ATCC 25923. All experiments were performed in duplicate to ensure reproducibility. Multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) isolates were classified according to international standard definitions based on antimicrobial resistance profiles (Figure 1).

4. Detection of Methicillin-resistant S. aureus (MRSA)

A cefoxitin (30 µg) disk diffusion assay was used as a phenotypic method for MRSA detection. Isolates with inhibition zones ≥22 mm were classified as methicillin-sensitive S. aureus (MSSA), whereas isolates with inhibition zones ≤21 mm were classified as MRSA according to CLSI criteria (Figure 1).

5 Determination of Vancomycin Resistance by Minimum Inhibitory Concentration (MIC) Testing

Vancomycin minimum inhibitory concentrations (MICs) were determined by the broth microdilution method according to CLSI guidelines¹¹. Serial two-fold dilutions of vancomycin (4–512 µg/mL) were prepared in Mueller–Hinton broth. Bacterial suspensions were adjusted to a 0.5 McFarland standard and diluted to approximately 1 × 10⁵ CFU/mL.

After incubation at 37 °C for 24 h, the MIC was defined as the lowest concentration at which no visible bacterial growth was observed. Vancomycin susceptibility was interpreted according to CLSI criteria as follows: susceptible (≤2 µg/mL), intermediate (4–8 µg/mL), and resistant (≥16 µg/mL)^11,12 (Figure 1).

6. Molecular detection

6.1 DNA extraction

Staphylococcus aureus isolates were cultured in brain heart infusion (BHI) broth for 24 h at 37 °C. Bacterial genomic DNA was extracted using a commercial kit and an automated nucleic acid extraction system. Extracted DNA was stored at −20 °C until use. DNA concentration was measured using a fluorometer to evaluate suitability for PCR amplification. The mean DNA concentration was 85 ± 8.2 ng/µL.

Primers targeting the cna, hlg, and class D β-lactamase (bla_OXA-group I) genes were obtained commercially and used for PCR amplification as listed in Table 1^13,14,15,16.

Table 1: Primer sequences used for PCR amplification of target genes investigated in this study. The table summarizes the target genes, primer sequences, expected amplicon sizes, annealing temperatures, and references used for PCR amplification of nuc, mecA, hlg, cna, and bla_OXA-group I genes in Staphylococcus aureus isolates recovered from diabetic foot infections. Please click here to download this Table.

6.2 Molecular detection of virulence and class D β-Lactamase (bla_OXA-group I) genes by PCR

Primer sequences used in this study are listed in Table 1. PCR amplification of mecA, nuc, virulence-associated genes, and class D β-lactamase (bla_OXA-group I) genes was performed in 25 µL reaction mixtures containing 12.5 µL GoTaq Green Master Mix (2×), 0.5 µL MgCl₂, 3 µL genomic DNA template, 1 µL each of forward and reverse primers (10 pmol/µL), and 7 µL nuclease-free water.

Thermal cycling conditions consisted of an initial denaturation step at 95 °C for 5 min, followed by 30–35 amplification cycles including denaturation at 95 °C for 30 s–1 min, annealing at 50–62 °C for 30 s–1 min depending on the primer set, and extension at 72 °C for 30 s–1 min. Final extension was performed at 72 °C for 7–19 min.

Amplified PCR products were separated on 1.5%–2% agarose gels stained with Safe Red and visualized under ultraviolet illumination using a gel documentation system. Negative controls were included in each PCR run to confirm the validity of amplification.

7. Whole-genome sequencing (WGS)

Whole-genome sequencing (WGS) was performed on two representative clinical Staphylococcus aureus isolates recovered from bone tissue specimens obtained from patients with diabetic foot infections. The selected isolates included one multidrug-resistant (MDR) and one extensively drug-resistant (XDR) isolate, identified by phenotypic antimicrobial susceptibility testing and MIC-confirmed resistance profiles. This strategy enabled representative genomic characterization of clinically relevant resistant isolates (Figure 1).

Genomic DNA quality, concentration, and integrity were evaluated prior to sequencing to ensure suitability for library preparation and downstream bioinformatic analysis. DNA was quantified using a fluorometer, and integrity was verified by 1% agarose gel electrophoresis at 150 V for 40 min. DNA fragments approximately 200–400 bp in length were size-selected using magnetic bead purification, followed by end repair, 3′ adenylation, and adaptor ligation.

Single-stranded circular DNA molecules were generated by amplification, purification, and circularization of adaptor-ligated fragments using splint oligonucleotides. DNA nanoballs (DNBs) were subsequently generated through rolling-circle amplification. Sequencing was performed on the DNBSEQ platform using combinatorial Probe-Anchor Synthesis (cPAS) chemistry.

Raw sequencing reads underwent quality control procedures to remove low-quality reads, adaptor contamination, ambiguous reads, and duplicate sequences. Clean reads were used for downstream analyses. Genome assembly was performed to estimate genome size, GC content, and sequencing coverage depth. Final draft genome assemblies were generated in FASTA, GenBank, and NCBI submission formats.

Genome annotation identified coding sequences (CDS), transfer RNA (tRNA), ribosomal RNA (rRNA), and small RNA (sRNA) genes. Functional annotation of predicted genes was performed using multiple databases, including Swiss-Prot, COG, KEGG, CAZy, VFDB, ARDB, and CARD, for virulence- and antimicrobial-resistance-associated genes.

8. Bioinformatics analysis

Genome assembly and annotation were performed using the Bacterial and Viral Bioinformatics Resource Center (BV-BRC). Phylogenetic analyses were conducted using PATRIC tools. Circular genome visualization maps were generated to illustrate coding sequences, GC content, GC skew, antimicrobial resistance determinants, virulence-associated genes, and mobile genetic elements.

Phylogenetic relationships were determined using PATRIC global protein families (PGFams) identified from the closest reference genomes using Mash/MinHash analysis. Protein alignments were generated using MUSCLE, and corresponding nucleotide alignments were mapped to protein families. Phylogenetic trees were constructed using RAxML with fast bootstrapping analysis (Figure 1).

Genome contigs were additionally analyzed using Pathogenwatch for species confirmation and detection of antimicrobial resistance genes. Virulence-associated genes were analyzed using ABRicate. The PATRIC Genome Annotation Service used a k-mer-based approach to identify antimicrobial resistance genes and assign functional annotations, antimicrobial classes, and resistance mechanisms. Circular genome visualizations of representative MDR and methicillin-resistant S. aureus isolates were generated as described previously¹⁷. Supplementary Table 1 summarizes all bioinformatics tools, software versions, databases, and analytical parameters used in the genomic analyses.

Results

Specimen processing and culture positivity

A total of 125 clinical specimens were collected and analyzed in this study. Bacterial growth was observed in 90/125 samples (72%). These culture-positive specimens were subsequently processed for bacterial identification and antimicrobial susceptibility testing. Descriptive statistics, including frequencies and percentages, were used to summarize the distribution of bacterial isolates among all clinical specimens and culture-positive...

Discussion

Diabetic foot infections (DFIs) caused by multidrug-resistant (MDR) microorganisms are increasing globally, with poor glycemic control and inadequate foot hygiene contributing to increased morbidity and mortality^18,19,20,21. Although DFIs are frequently polymicrobial, Staphylococcus aureus remains one of the predominant pathogens isolated from these infections, with the prevalence of m...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Abricate Software	GitHub (T. Seemann)	Open-source	Virulence gene detection
Agarose	Invitrogen, USA	16500-500	Gel electrophoresis
Agencourt AMPure XP Kit	Beckman Coulter	A63881	DNA purification and size selection
Amikacin (30 µg) Disc	Oxoid, UK	CT0107B	AST
Antibiotic Discs (Ampicillin 20 µg)	Oxoid, UK	CT0003B	Antimicrobial susceptibility testing
Blood Agar Base	Oxoid, UK	CM0055	Isolation of Gram-positive and Gram-negative bacteria
Brain Heart Infusion (BHI) Broth	Oxoid, UK	CM1135	Culturing and storage of isolates
Cefoxitin (30 µg) Disc	Oxoid, UK	CT0119B	MRSA detection
Cefuroxime (30 µg) Disc	Oxoid, UK	CT0026B	AST
Ciprofloxacin (5 µg) Disc	Oxoid, UK	CT0425B	AST
Clindamycin (2 µg) Disc	Oxoid, UK	CT0064B	AST
DNBSEQ Platform	BGI, China	Various	Whole genome sequencing
Erythromycin (15 µg) Disc	Oxoid, UK	CT0020B	AST
FastQC	Simon Andrews at the Babraham Institute (Babraham Bioinformatics)	NA	queueing system
Gel Documentation System	Bio-Rad, USA	Gel Doc™ XR+	Imaging of electrophoresis gels
Gentamicin (10 µg) Disc	Oxoid, UK	CT0024B	AST
Glycerol (Molecular Grade)	Sigma-Aldrich	G5516	Used at 20% for long-term isolate preservation
GoTaq Green Master Mix (2×)	Promega, USA	M7122	PCR amplification mix
Levofloxacin (5 µg) Disc	Oxoid, UK	CT1587B	AST
Linezolid (30 µg) Disc	Oxoid, UK	CT1716B	AST
MacConkey Agar	Oxoid, UK	CM0007	Selective medium for Gram-negative bacteria
Mannitol Salt Agar (MSA)	Oxoid, UK	CM0085	Selective/differential medium for Staphylococcus spp.
Meropenem (10 µg) Disc	Oxoid, UK	CT0774B	AST
MgCl2 Solution	Promega, USA	Various	PCR reaction component
Mueller-Hinton Agar	Oxoid, UK	CM0337	Used for Kirby–Bauer disc diffusion testing
MUSCLE Alignment Tool	Open-source	Various	Protein sequence alignment
Nuclease-Free Water	Promega, USA	P1193	PCR reaction component
Nutrient Agar	Oxoid, UK	CM0003	General-purpose growth medium
Oxacillin (1 µg) Disc	Oxoid, UK	CT0159B	AST
PathogenWatch	Wellcome Sanger Institute	Online Tool	Species ID & AMR gene detection
PATRIC / BV-BRC	Bacterial Bioinformatics Resource Center	Online Platform	Genome assembly & annotation
Piperacillin/Tazobactam (100/10 µg) Disc	Oxoid, UK	CT1628B	AST
Proksee Genome Visualization Tool	University of Toronto	Online Tool	Genome map visualization
Quantus Fluorometer	Promega, USA	E6150	DNA quantification
Qubit Fluorometer	Thermo Fisher Scientific	Q33238	DNA quantification for WGS
RAxML Software	Open-source	Various	Phylogenetic analysis
S. aureus ATCC 25923	ATCC, USA	25923	Quality control strain for AST
Safe Red Stain	iNtRON Biotechnology	Various	DNA gel stain
SaMag Bacterial DNA Extraction Kit	Sacace Biotechnologies, Italy	Various	Genomic DNA extraction
SaMag-12 Automated Extraction System	Sacace Biotechnologies, Italy	SMG-12	Automated nucleic acid extractor
Sterile Cotton Swabs	Various manufacturers	Various	Used for deep swab technique sample collection
Sterile Normal Saline	Various manufacturers	Various	Used for washing ulcer surface before sampling
Sterile Scalpel Blades	Various manufacturers	Various	Used for ulcer debridement prior to sampling
Tigecycline (15 µg) Disc	Oxoid, UK	CT1849B	AST
Trimethoprim-Sulfamethoxazole (25 µg) Disc	Oxoid, UK	CT0052B	AST
UV Transilluminator	Various manufacturers	Various	Visualization of PCR products
Vancomycin (30 µg) Disc	Oxoid, UK	CT0588B	AST
VITEK 2 Compact	BioMérieux, France	Various	Automated identification system
VITEK 2 GN ID Cards	BioMérieux, France	Various	Identification of Gram-negative bacteria