Molecular detection of Incidence MRSA isolates from Skin and Soft Tissue Infections

Molecular detection of Incidence MRSA isolates from Skin and Soft Tissue Infections | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular detection href="https://link.springer.com/article/10.1186/s13054-017-1801-3">of Incidence MRSA isolates from Skin and Soft Tissue Infections Mohammed Ejresh, Alya A.Rahi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9076229/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction : MRSA is a global health concern due to its antibiotic resistance and its role in severe, often fatal skin and soft tissue infections in healthcare and community settings. Objective: The study focuses on detecting MRSA and assessing virulence-associated Cas genes in clinical isolates from skin and soft tissue infections. Method Among 100 SSTI patients studied, 20% had Staphylococcus aureus , 55% had other bacteria, and 25% showed no growth based on standard laboratory identification methods. Antimicrobial susceptibility testing by Viteck-2 system was done, and Molecular analysis by PCR showed diverse CRISPR-Cas subtypes. HRM spa genotyping recognised. Results and Discussion: Among the 20 cases, males were more frequently affected than females, with the highest infection rates observed in the 16–20 and 6–10 year age groups, although no significant association with sex or age was found. Antimicrobial susceptibility testing revealed high resistance to oxacillin, confirming the prevalence of MRSA, along with resistance to multiple other antibiotics, indicating widespread multidrug resistance. Molecular analysis showed diverse CRISPR-Cas subtypes, with significant associations between Cas subtypes and resistance to gentamicin and tetracycline. HRM spa typing demonstrated marked genetic diversity, identifying seven clonal complexes with predominant local lineages, highlighting endemic circulation and potential for increased virulence and antimicrobial resistance. Conclusion: The isolates showed high MRSA occurrence (100% oxacillin resistance) and resistance to some antibiotics. CRISPR-Cas analysis discovered genetic heterogeneity, with Cas4 most common, and specific links between Cas subtypes and resistance (gentamicin–Cas4, tetracycline–Cas10).HRM spa genotyping recognized seven clonal complexes, representing both local endemic motion and significant genetic variety, which may influence virulence and resistance patterns. The findings highlight the high MRSA burden, the diverse genetic landscape of S. aureus, and the probable role of CRISPR-Cas in resistance, the necessity for incessant surveillance and informed antimicrobial therapy. Bacteriology MRSA Skin and Soft Tissue Infections SSTIs Vitek2 Compact Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Skin and Soft Tissue Infections (SSTIs) are among the most common infections worldwide, affecting patients across all age groups( 1 ). SSTIs can be classified based on anatomical location, clinical severity, or microbial aetiology. They encompass a wide spectrum of severity, ranging from minor, self-limiting superficial infections, such as impetigo and folliculitis, to severe, life-threatening conditions, including necrotising fasciitis and deep abscesses, which may require intensive medical intervention and surgical management( 2 ). Clinically, they are often categorised as uncomplicated, involving superficial skin layers without systemic involvement, or complicated, involving deeper tissues, requiring hospitalisation or specialised care( 3 ). Epidemiological studies have reported a rising incidence of S. aureus infections not only in healthcare settings but also in the community, highlighting the growing public health concern of methicillin-resistant S. aureus (MRSA) in both settings( 4 ). Among causative pathogens, Staphylococcus aureus is the predominant agent in both community-acquired (CA) and healthcare-associated (HA) SSTIs, although virtually any bacterial species, including Streptococcus spp. and Gram-negative bacteria, can induce inflammation in soft tissues( 5 ). Mild to moderate SSTIs are typically managed with oral antibiotics, while severe or complicated infections often require parenteral therapy, surgical drainage, and supportive care( 6 ). Appropriate antimicrobial selection is increasingly critical due to the high prevalence of multidrug-resistant S. aureus strains( 7 ). The host immune response to SSTIs is initiated by innate immune cells, primarily keratinocytes and neutrophils, which provide rapid containment of infection, followed by adaptive immune components, including dendritic cells and T-lymphocytes, that contribute to pathogen clearance and immune memory( 8 ).. Treatment strategies depend on infection severity.Its pathogenicity is attributed to a wide array of virulence factors, including surface proteins that promote adhesion, toxins that damage host tissues, and enzymes that facilitate immune evasion( 9 ).The spa gene is widely used as a molecular marker for strain typing and epidemiological studies due to its high variability in the X-region, which consists of short tandem repeats (STRs)( 10 ). The number and sequence of these repeats vary among strains, providing a reliable method to differentiate clonal lineages( 11 ). Spa typing allows researchers and clinicians to track outbreaks, monitor the spread of methicillin-resistant S. aureus (MRSA), and study genetic diversity within populations. Modern techniques, such as high-resolution melting (HRM) analysis, have enhanced the ability to rapidly genotype S. aureus strains based on spa gene variability( 12 ). Staphylococcus aureus is a Gram-positive, facultative anaerobic bacterium that is a major cause of skin and soft tissue infections (SSTIs), bloodstream infections, pneumonia, and device-associated infections( 13 ). Among these, protein A, encoded by the spa gene, plays a crucial role in immune modulation by binding to the Fc region of immunoglobulin G (IgG), thereby interfering with opsonisation and phagocytosis. HRM detects subtle differences in melting temperature (Tm) and amplicon size, enabling discrimination between spa types without the need for sequencing( 14 ).In addition to its epidemiological significance, variations in the spa gene may correlate with virulence and resistance profiles, providing insights into the behaviour of different S. aureus strains. This approach has been particularly valuable for identifying endemic lineages, clonal complexes, and potential sources of infection in both community and healthcare settings( 15 ). The combination of spa typing with antimicrobial susceptibility testing and CRISPR-Cas profiling offers a comprehensive view of the genetic landscape and potential pathogenicity of clinical isolates( 16 ). Overall, the spa gene serves as both a virulence element and a molecular epidemiology tool, making it central to understanding the transmission, evolution, and clinical impact of S. aureus infections( 17 ). 2. Methodology 2.1.Design of the study & Ethical Considerations A cross-sectional study was conducted on 100 specimens taken overall between July and October 2025. Approved for this study in line with ethical norms by the Al-Hilla Teaching Hospital. Hospital ethics committee under document number [ IRB: 5–26, 7/8/2023]. Apart from that, every person involved in the research was briefed regarding the study before the sample gathering, and their permission was obtained concerning the test administration as well as the publishing of the results. 2.2.Isolation, & The Identification of Isolates Under sterile conditions, a total of 100 clinical specimens, including abscesses, boils, and wound infections, were collected from patients who were infected with the pathogen. Prior to swabbing, the swab was soaked in a sterile saline solution in order to increase its moisture content for patients who had dry wounds. After the samples were obtained, they were moved to the research unit of Microbiology and Antimicrobial Substances, which is located inside the Department of Microbiology at the Al-Hilla teaching hospital. It was determined that the Staph aureus isolate was identified through the utilisation of conventional microbiological and biochemical techniques, which included inoculation on a medium consisting of mannitol salt agar. Staph aureus isolates were characterised by the colony morphology as well as the bacterium's capacity to make oxidase, catalase, citrate, and urease tests. Each of these characteristics was taken into consideration. 2.3.Antibiotic Susceptibility Test by Vitek-2 system The Viteck-2 system is an automated system used for the identification of bacterial species and the determination of their antibiotic susceptibility profiles. The stages involved in the identification process were as follows: bacterial isolates were inoculated on MacConkey agar plates and then incubated at temperatures ranging from 48 to 72 degrees Celsius for a period of 24 hours. In a sterile tube, a single colony that was completely pure was suspended in 3 mm of normal saline. With the help of VITEK Densichek (bioMérieux ), the turbidity of the bacterial suspension was adjusted so that it was in accordance with the McFarland standard, which was between 0.5 and 0.7, in 0.45% sodium chloride. It was necessary to manually load the suspension tubes and the VITEK 2 ID(Gram Negative) card into the machine. A computer that is connected to the VITEK-2 system receives rustle as data for each sample after approximately six to eight hours have passed since the instrument was first used. According to the VITEK2 Compact System, the identification of Staph aureus is dependent on the biochemical reactions that take place between the bacterial isolates that are suspended in their solutions and the medium that is included within the VITEK-2 Identification cards. 2.4.DNA isolation and amplification : Genomic DNA of Isolated bacteria was extracted using the classical protocol by Presto Mini gDNA Bacteria Kit (Geneaid, USA). 2.5.Primers: The primers utilized in this study were produced by Macrogen Company, located in Korea. To prepare the working solution, the primers were diluted from stock using TE buffer to achieve a concentration of 10 picomoles per microliter, after which they were stored at -20°C. The oligonucleotide primers for all genes investigated in this research were sourced from prior studies and are detailed in Table (1). This table includes the primer sequences for each studied gene, along with their corresponding amplicon size in base pairs (bp) and the respective reference. These PCR primers were employed for detecting subtypes of the system in clinical isolates of Staph aureus. Table (1): The primers, their sequences, annealing temperatures, and the amplicons used in this study. Primer-Names Sequences ( 5` − 3`) Annealing-Tem. Amplicon Cas1 GTAGAAAAYCATTACTTTGTTACYG CRAATCCATGWAWAGCTARYTC 53°C 370 Cas4 CTAAAYTWGAACGTMRRRTBGC GYTTWGGTTCTTTKYKSACARC 54°C 255 Cas6 TTTAGGAAGTRTTTTACATGGYGTG CCWGAAAATTCRCCAAACTTYA 55°C 630 Cas9 GGKAAAATTATMTATCGRAGTRRYG CWGTRTAYAAAAGATTTGCTCGTGY 52°C 883 Spa AGACGATCCTTCGGTGAGC GCTTTTGCAATGTCATTTACTG 56°C for 20 s, 2.6.Molecular detection of CRISPR/Cas systems : Molecular identification of subtypes of system (Cas1, Cas4, Cas6, Cas9) was conducted using conventional PCR, following the protocol outlined by Soliman et al . (2022). PCR amplification of DNA was carried out in a final mixture volume of 25 µl using GoTaq® G2 Green Master Mix from Promega, USA. The PCR mixtures and conditions are detailed in Table 2 of the study. After PCR amplification, the products were subjected to agarose gel electrophoresis using 1.5% gels containing green star stain, running at 100V for 35 minutes. Visualisation of the PCR products was performed using a gel documentation system. 2.7.CRISPR Analysis The final gel images were analyzed by BioNumerics (version 7) software (Applied-Maths, Saint-Martens-Latem, Belgium) to identify the size PCR products and to build a phylogenetic tree using UPGMA (unweighted pair group method with arithmetic mean) method. 2.8Statistical analysis : Frequency data analysis was conducted using Pearson's chi-squared test and Fisher's exact test. The data were processed and analyzed using the Statistical Package for the Social Sciences (SPSS) version 22. Results were presented as percentages. 3. Results 3.1.Distribution of Staph aureus among different specimens During this study conducted between July and October 2025 in Al-Hilla teaching Hospital,, a total of 100 clinical specimens were collected from patients with various infections, including abscesses, boils, and wound infections. These specimens underwent aerobic culturing on different media. Out of 100 clinical samples, 20% were positive for Staphylococcus aureus, 55% yielded other bacterial species, and 25% showed no bacterial growth, as in Fig(1). 3.2.Biochemical tests for identification In the present study, all these results confirm that the isolates are S. aureus , because they are Gram-positive cocci that are catalase-positive, coagulase-positive, ferment mannitol, produce hemolysin, and are oxidase-negative. 3.3.Distribution of Cases by Sex and Age Groups In the present study,6 females (30%) and 14 males (70%) were studied, and males predominate in all groups except G1. P-values (0.383, 0.865, 0.439) > 0.05 ( no significant difference )between sexes across age groups. Sex differences are not statistically significant. As in table2. 3.4.Antibiotic Susceptibility Test Systems by the Vitek-2 system In the Table3, showed All isolates are methicillin-resistant ( MRSA ). Traditional β-lactams (penicillin, oxacillin) show very high resistance. Glycopeptides (vancomycin, teicoplanin) and linezolid remain largely effective. Tigecycline and trimethoprim/sulfamethoxazole are the most effective antibiotics against these isolates. Table (3): Percentage of Antibiotics Sensitive and Resistance by S. aureus clinical isolates. Against 13 types of Antibiotics by Vitek2 Compact According to CLSI (2025)(n=20). Isolate N. Benzyl pencillin Oxacillin Gentamicin Ciprofloxacin Erythromycin Clindamycin Linezolid Teicoplanin Vancomycin Teteacycline Tigecycline Rifampicin Trimethoprim / sulfamethoxazole S1 R R S R R R S S S R S S S S2 R R S S S R S S S R S S S S3 R R R R R S S S S S S S S S4 R R S S S S S S S S S S S S5 S R S R R R S S S R R S S S6 R R R R R R S S S R S S S S7 R R S S S S S R S R S S S S8 R R S I R S S S S R S S S S9 R R S S S S S S S S S S S S10 R R S I R R S S S R S S S S11 R R S R R R S S S S S S S S12 R R R R R R R R I R S R R S13 R R R R R R S S S R S S S S14 R R S I R R R R R R S R S S15 R R R R R S S R I S S S S S16 R R R R R S S R R R S S R S17 R R R R R S S R R R S R S S18 R R R R R S S S R R R S S S19 R R R R R S S S R R S R S S20 R R R R R S S S R R S S R R% 93.3 100 33.3 53.3 73.3 60 13.3 26.7 6.7 66.7 6.7 13.3 6.7 S% 6.7 0 66.7 26.7 26.7 40 86.7 73.7 80 33.3 93.3 86.7 93.3 I% 0 0 0 20 0 0 0 0 13.3 0 0 0 0 P value 0.01* 1.0 0.197 0.247 0.071 0.439 0.005* 0.071 0.001* 0.197 0.001* 0.005* 0.001* * represents a significant difference at p<0.05. R, resistant; S, sensitive; I, intermediate. 3.5.Genetic detection of CRISPR/Cas systems by PCR In the present study, the detection of Cas-1 by PCR in 20 isolates showed that about 5(25%) carried this gene, as in Fig(2).WhileCas-4in 13(65%)isolates carried this gene in Fig(3).Detection about 6(30%) out of 20 isolates carried Cas-6 in Fig(4)and Cas-9 in8( 40%)as in Fig(4). 4. Correlation between antimicrobial susceptibility of S. aureus clinical isolates and the presence of CRISPR/Cas types . In the present study, Table 4 shows the antimicrobial susceptibility patterns of Staphylococcus aureus clinical isolates were analysed in relation to the presence of different CRISPR-Cas subtypes (Cas1, Cas4, Cas6, and Cas90). CRISPR-Cas systems are adaptive immune mechanisms in bacteria that protect against foreign genetic elements, such as plasmids and phages, and have been implicated in influencing horizontal gene transfer, including the acquisition of antibiotic resistance genes. Among the 20 S. aureus isolates, the distribution of CRISPR-Cas subtypes was as follows: Cas1 (5 isolates), Cas4 (13 isolates), Cas6 (6 isolates), and Cas9 (8 isolates). The antibiotic resistance patterns varied across these subtypes, indicating a possible, though selective, association between CRISPR-Cas presence and antimicrobial resistance. Cas1-positive isolates exhibited high resistance to β-lactams (benzyl penicillin and oxacillin), tetracycline, and gentamicin, while remaining mostly sensitive to vancomycin, linezolid, teicoplanin, tigecycline, and trimethoprim/sulfamethoxazole. This pattern suggests that Cas1 may coexist with resistance factors for certain antibiotics but does not broadly confer multidrug resistance . Cas4-positive isolates , the most prevalent subtype, demonstrated extensive resistance to β-lactams, ciprofloxacin, and tetracycline, alongside partial resistance to macrolides and aminoglycosides. Statistical analysis exposed a significant association between Cas4 presence and gentamicin resistance (p = 0.032) , suggesting that Cas4 may contribute to or co-occur with mechanisms that mediate aminoglycoside resistance. Cas6-positive isolates mirrored the resistance pattern of Cas1, with notable resistance to β-lactams and some macrolides but high susceptibility to glycopeptides, linezolid, tigecycline, and trimethoprim/sulfamethoxazole. No statistically significant correlations were observed between Cas6 and any specific antibiotic resistance (p > 0.05), indicating a limited influence of this subtype on the antimicrobial phenotype. Cas90-positive isolates displayed moderate resistance to tetracycline, erythromycin, and gentamicin, while maintaining sensitivity to vancomycin, linezolid, teicoplanin, and tigecycline. Importantly, Cas90 presence was significantly associated with tetracycline resistance (p = 0.003) , highlighting a potential role in modulating resistance to this antibiotic class. Overall, while β-lactam resistance (penicillin, oxacillin) remained universally high across all CRISPR-Cas subtypes, glycopeptides (vancomycin, teicoplanin), linezolid, tigecycline, and trimethoprim/sulfamethoxazole retained high effectiveness regardless of Cas type. These findings indicate that CRISPR-Cas systems do not universally confer resistance but may be linked selectively to resistance against certain antibiotics , particularly aminoglycosides and tetracyclines in Cas4 and Cas9 isolates. Table (4): Correlation between antimicrobial susceptibility of S. aureus isolates and the presence of CRISPR/Cas Types. Table (5): Distribution of Cas Genes among pathogenic S. aureus isolates Cas- genes PCR Product Positive (N, %) Negative (N, %) Total P value Cas1 370bp 5 (25%) 15 (75%) 20 0.197 Cas4 255 bp 13 (65%) 7 (35%) 20 0.005 Cas6 630 bp 6 (30%) 14 (70%) 20 0.439 Cas9 883 bp 8 (40%) 12 (60%) 20 0.796 5.High – Resolution melting of S. aureus Isolates (–dRn/dT ): In the present study, the figure presents derivative high-resolution melting (HRM) curves (–dRn/dT) of the amplified PCR products, where each peak represents the melting temperature (Tm) of an individual sample. The melting peaks are closely clustered but not identical, with Tm values distributed approximately between 84 and 86 °C. These small yet reproducible shifts in Tm indicate the presence of sequence variations among the tested samples, such as single-nucleotide polymorphisms (SNPs) or minor differences in GC content. Each sample exhibits a single, sharp, and symmetrical peak, suggesting. High specificity of PCR amplification. Absence of non-specific products or primer-dimer formation. The comparable peak heights further indicate similar amplicon concentrations across samples. The distinct positions of the melting peaks allow the samples to be classified into different melting profiles, demonstrating genetic heterogeneity within the amplified region. This confirms the ability of HRM analysis to differentiate closely related variants without the need for sequencing. These results highlight HRM as a rapid, sensitive, and cost-effective molecular tool for genotyping, strain discrimination, and detection of minor genetic variations in molecular epidemiological studies. In this figure( 7 ),–dRn/dT difference plot showing melting profile variations of Staphylococcus aureus isolates relative to reference Isolate 1. Distinct curve patterns indicate genetic diversity among the analysed isolates. Table (6) : (–dRn/dT)spa typing results of 20 Staphylococcus aureus clinical isolates. Isolate N. CC group HRM Tm (°C) Product size pb Spa type Repeat of spa types S.A1 CC7 82.041 278 t304 11-10-21-17-34-24-34-22-25 S.A2 CC6 82.420 278 t078 04-21-12-41-20-17-12-12-17 S.A3 CC2 85.210 223 t037 15-12-16-02-25-17-24 S.A4 CC7 82.044 278 t304 11-10-21-17-34-24-34-22-25 S.A5 CC7 82.040 278 t304 11-10-21-17-34-24-34-22-25 S.A6 CC5 83.430 326 t491 26-23-12-34-34-12-12-23-02-12-23 S.A7 CC7 82.043 278 t304 11-10-21-17-34-24-34-22-25 S.A8 CC6 82.410 278 t078 04-21-12-41-20-17-12-12-17 S.A9 CC4 83.950 158 t14870 11-10-13-25 S.A10 CC5 83.441 326 t491 26-23-12-34-34-12-12-23-02-12-23 S.A11 CC3 84.501 134 t059 11-19-25 S.A12 CC5 83.440 326 t491 26-23-12-34-34-12-12-23-02-12-23 S.A13 CC6 82.421 278 t078 04-21-12-41-20-17-12-12-17 S.A14 CC3 84.503 134 t059 11-19-25 S.A15 CC1 86.201 206 t030 15-12-16-02-24-24 S.A16 CC3 84.501 134 t059 11-19-25 S.A17 CC5 83.440 326 t491 26-23-12-34-34-12-12-23-02-12-23 S.A18 CC6 82.421 278 t078 04-21-12-41-20-17-12-12-17 S.A19 CC3 84.503 134 t059 11-19-25 S.A20 CC1 86.201 206 t030 15-12-16-02-24-24 CC= clonal complex Discussion In the present study, 20 (20%) were positive for S. aureus out of 100 different clinical specimens (40 boils,35wound,25 abscesses ) agree with the study by [18], who found common S. aureus in skin and soft tissue, while the study by [19] found that A total of 79 S. aureus isolates were recovered from 54(57.4%) patients out of the 94 involved in the study. Forty isolates were from wound swabs and 39 from abscesses. In this study population (n = 20), there were 6 females (30%) and 14 males (70%). Males predominated across all age groups except the youngest (G1). Statistical analysis showed that sex differences across age groups were not significant, as indicated by P-values > 0.05 (0.383, 0.865, 0.439), suggesting that neither sex was disproportionately affected by the condition under investigation. These findings align with several community-based studies where S. aureus infection rates did not significantly differ by sex [19],Some studies report mild male predominance in specific age ranges, but without statistical significance when confounding variables such as exposure risk and health-seeking behaviours are controlled (19). The age distribution in the present study revealed more male cases in older age groups (G4: 16–20 years). Age-related patterns of S. aureus colonisation and infection have been reported in the literature, with complex interactions between immunity, exposure, and comorbidities influencing prevalence(20),A large multicenter analysis documented a slight male predominance in invasive disease, but differences often did not reach statistical significance (21), Similarly, age-specific trends are dependent, with community settings showing more pediatric cases and hospital-based studies showing older adult preponderance (22),In the present study, CRISPR/Cas-associated genes were investigated among 20 clinical Staphylococcus aureus isolates using PCR. The results demonstrated a variable distribution of Cas genes. Cas1 was detected in 5 isolates (25%), Cas4 in 13 isolates (65%), Cas6 in 6 isolates (30%), and Cas9 in 8 isolates (40%). These findings indicate that CRISPR/Cas elements are present in a proportion of pathogenic S. aureus strains, although not universally distributed. The relatively low prevalence of Cas1 and Cas6 compared with Cas4 suggests heterogeneity in CRISPR/Cas system carriage among clinical isolates. Similar variability has been reported in recent studies, where CRISPR-Cas systems were found inconsistently across S. aureus populations, reflecting differences in strain lineage, geographic distribution, and exposure to mobile genetic elements (MGEs) such as plasmids and bacteriophages. Cas4 was the most frequent gene detected (65%) and showed a statistically significant association (p = 0.005). Cas4 is often linked with spacer acquisition and adaptation phases of CRISPR immunity, which may explain its higher detection rate in strains exposed to foreign genetic material. Previous genomic surveys have similarly reported Cas4 enrichment in certain bacterial pathogens as part of active CRISPR defence modules. The present study also evaluated the relationship between CRISPR/Cas subtype carriage and antimicrobial susceptibility patterns. CRISPR/Cas systems function as adaptive immune mechanisms that protect bacteria against invasion by MGEs, which frequently carry antibiotic resistance determinants (23), Therefore, CRISPR presence may influence horizontal gene transfer and indirectly affect resistance acquisition.Cas1-positive isolates exhibited high resistance to β-lactam antibiotics (benzyl penicillin and oxacillin), tetracycline, and gentamicin, while remaining largely susceptible to vancomycin, linezolid, teicoplanin, tigecycline, and trimethoprim/sulfamethoxazole. This pattern suggests coexistence of Cas1 with certain resistance determinants but does not indicate broad multidrug resistance. This study showed that the Cas4 subtype was common among isolates and was linked to high levels of resistance to β-lactam antibiotics, ciprofloxacin, and tetracycline, with a statistically significant correlation between Cas4 and gentamicin resistance (p = 0.032). Isolates positive for Cas6 exhibited resistance patterns similar to those observed in Cas1 isolates, showing high resistance to β-lactam antibiotics while remaining susceptible to glycopeptides and linezolid, with no statistically significant correlations with any of the tested antibiotics (p > 0.05). These results indicate cas is inactive or incomplete in clinical isolates.Cas9- isolates exhibited moderate resistance to tetracycline, erythromycin, and gentamicin, with a statistically significant correlation between Cas9 presence and tetracycline resistance (p = 0.003). Cas9 is a key component of type II CRISPR systems, which may influence bacterial genomes and play a role in resistance acquisition. However, CRISPR-Cas systems may coexist with resistance genes rather than completely suppress them. The differential melting curves (-dRn/dT) of the PCR reaction products showed single, sharp, and symmetrical peaks in all isolates, indicating high specificity of the amplification process and the absence of nonspecific products or primer dipoles. The similarity in peak height also suggests homogeneity in the concentrations of the amplification products among the samples, further enhancing the reliability of the assay. Melting temperatures ranged from 82 to 86°C with slight and reproducible variations, reflecting subtle genetic differences such as single nucleotide polymorphisms (SNPs) or minor variations in base content within the amplified region of the spa gene—differences sufficient to produce distinct melting patterns.Spa-HRM analysis classified the isolates into seven clonal complexes (CC1–CC7). The spa gene is an important molecular marker in epidemiological studies due to the polymorphism of its X region, which is rich in repeats. HRM analysis allowed for the differentiation of several spa subtypes, including t304, t078, t037, t491, t059, t030, and t14870, demonstrating significant genetic diversity among the clinical isolates studied. The t304 (CC7) subtype was the most frequent, appearing in multiple isolates, suggesting potential clonal expansion or local spread of this strain. The t078 (CC6) subtype was also frequently observed, consistent with previous reports linking these subtypes to hospital- and community-acquired infections and their role in ongoing transmission. The HRM variation plot further confirmed genetic diversity by showing distinct fusion patterns compared to the reference isolate, highlighting the effectiveness of this technique in differentiating isolates with subtle genetic differences and supporting its use in epidemiological outbreak surveillance. Statistical analysis also revealed a significant correlation between higher melting temperature and belonging to the high Tm clonal complexes. Melting temperature remained a statistically significant independent predictor even after adjusting for the size of the spa output, while fragment size showed no significant effect. The high Nagelkerke R² value supports the model's efficiency, confirming the reliability of HRM-Tm as a molecular marker for lineage differentiation. Conclusion The present findings confirm that (–dRn/dT )spa typing is an effective method for identifying genetic heterogeneity among S. aureus clinical isolates. The observed variation in melting temperatures and spa types reflects the presence of multiple clonal lineages circulating in the study population. (–dRn/dT) represents a rapid, sensitive, and cost-effective approach for genotyping, strain discrimination, and detection of minor genetic variations, supporting its value in molecular epidemiological investigations of S. aureus infections. Declarations Competing interests The authors declare no competing interests Funding No funding was received to assist with the preparation of this Research Acknowledgement The hospital staff who deserve our sincere gratitude. Financial support and sponsorship .Nil Conflict of interests No conflicts of interest. References Asadollahi, P., Farahani, N.N., Mirzaii, M., Khoramrooz, S.S., van Belkum, A., Asadollahi, K. and Dadashi, M. (2018) ‘Distribution of the most prevalent spa types among clinical isolates of methicillin-resistant and -susceptible Staphylococcus aureus around the world: a review’, Frontiers in Microbiology , 9, Article 163. Balasubramanian, D., Harper, L., Shopsin, B. and Torres, V.J. (2017) ‘ Staphylococcus aureus pathogenesis in diverse host environments’, Pathogens and Disease , 75(1), ftx005. Chow, A., Htun, H.L., Hon, P.Y., Ang, B., Kanagasabai, K., Koh, J. and Hsu, L.Y. 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(1964) ‘Resistance to methicillin, isoxazolyl penicillins, and cephalothin in Staphylococcus aureus ’, Acta Pathologica et Microbiologica Scandinavica , 62, pp. 255–275. Hille, F., Richter, H., Wong, S.P., Bratovic, M., Ressel, S. and Charpentier, E. (2018) ‘The biology of CRISPR–Cas: backward and forward’, Cell , 172(6), pp. 1239–1259. Hong, F., Salmon, S., Ong, X.Y., Liew, K., Koh, Y., Young, A. and Fisher, D. (2021) ‘Routine antiseptic baths and MRSA decolonisation: diverse approaches across Singapore’s acute-care hospitals’, Journal of Hospital Infection , 112, pp. 87–91. Klein, E.Y., Mojica, N., Jiang, W., Cosgrove, S.E. and Septimus, E. (2022) ‘Trends in invasive Staphylococcus aureus infections by age and sex’, The Lancet Infectious Diseases , 22(4), pp. 567–576. Klein, S., Morath, B., Weitz, D., Schweizer, P.A., Sähr, A., Heeg, K. and Nurjadi, D. 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(2023) ‘In silico approaches for prediction of anti-CRISPR proteins’, Journal of Molecular Biology , 435(7), 168036. Montoya-Urrego, D., Vanegas, J.M., Jiménez, J.N. and González-Gómez, D. (2025) ‘Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models’, F1000Research , 13, 837. Nyman, J.A., Lees, C.H., Bockstedt, L.A., Filice, G.A., Lexau, C., Lesher, L.J. and Lynfield, R. (2011) ‘Cost of screening intensive care unit patients for methicillin-resistant Staphylococcus aureus ’, American Journal of Infection Control , 39(1), pp. 27–34. Pinilla-Redondo, R., Russel, J., Mayo-Muñoz, D., Shah, S.A., Garrett, R.A. and Sørensen, S.J. (2022) ‘CRISPR–Cas systems are widespread accessory elements across bacterial and archaeal plasmids’, Nucleic Acids Research , 50(8), pp. 4315–4328. Pinilla-Redondo, R., Mayo-Muñoz, D., Russel, J. and Shah, S.A. (2022) ‘Diversity and evolution of CRISPR–Cas systems in bacterial pathogens’, Trends in Microbiology , 30(4), pp. 364–378. Pinilla-Redondo, R., Russel, J., Mayo-Muñoz, D., Shah, S.A., Sørensen, S.J. and Garrett, R.A. (2022) ‘Type IV CRISPR–Cas systems are highly diverse and involved in competition between plasmids’, Molecular Ecology , 31(5), pp. 1595–1608. Rahi, A.A. and Al-Hasnawy, H.H. (2024) ‘Expression of genes associated with efflux pumps and porins in Acinetobacter baumannii isolates recovered from different clinical specimens’, Biomedical and Biotechnology Research Journal , 8(4), pp. 464–473. Salmanov, A.G., Shchehlov, D.V., Mamonova, M., Shcheholkov, Y.E., Litus, V.I., Burakov, O.V. and Brodskaya, A. (2025) ‘Healthcare-associated infections in patients with combat wounds and antimicrobial resistance of the responsible pathogens in Ukraine’, Wiadomości Lekarskie , 8, pp. 1624–1634. Tong, S.Y.C., Davis, J.S., Eichenberger, E., Holland, T.L. and Fowler, V.G. (2015) ‘ Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management’, Clinical Microbiology Reviews , 28(3), pp. 603–661. Turner, N.A., Sharma-Kuinkel, B.K., Maskarinec, S.A., Eichenberger, E.M., Shah, P.P., Carugati, M., Holland, T.L. and Fowler, V.G. (2019) ‘Methicillin-resistant Staphylococcus aureus : an overview of basic and clinical research’, Nature Reviews Microbiology , 17(4), pp. 203–218. Watson, D.W., Iglesias, S.L., Vasarhelyi, E.M. and Heinrichs, D.E. (2021) ‘GraXRS-dependent resistance of Staphylococcus aureus to human osteoarthritic synovial fluid’, mSphere , 6(2), e01128-20. Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9076229","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":603351708,"identity":"8b7c9780-5cd2-40bb-a6c8-f4bc6586b4c2","order_by":0,"name":"Mohammed Ejresh","email":"","orcid":"","institution":"Training and Human Development Center","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Ejresh","suffix":""},{"id":603351933,"identity":"a4d8f622-bb7f-45d1-b934-f571087c8733","order_by":1,"name":"Alya A.Rahi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDACdijNxszY+ABI8/AR1MIMpfnYmw8bgLSwEa1FjudYmgTYOkI6+Jt5DD/8zLHJZ5PIMav8mmMnw8bA/PDRDTxaJA7zGEv2bkuzbANquS27LRnoMDZj4xx81hzmMZDg3XbYAGTLbcltzEAtPGzS+LTIA235+Xfbf7CWYslt9YS1GBzmMZPm3XbAgA3ofcaP2w4T1mJ4mK3MGugFAzZgIEszbjvOw8ZMwC9yx5s333y7zc5Avpmx8ePPbdX2/OzNDx/j9T4DhwGcycwDJvEqBwH2B3Am4w+CqkfBKBgFo2AkAgCaZkAf/GSE1QAAAABJRU5ErkJggg==","orcid":"","institution":"Department Center, Quality Management Division","correspondingAuthor":true,"prefix":"","firstName":"Alya","middleName":"","lastName":"A.Rahi","suffix":""}],"badges":[],"createdAt":"2026-03-09 18:52:32","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9076229/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9076229/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104405907,"identity":"28819575-f290-419f-91a3-1414de022b61","added_by":"auto","created_at":"2026-03-11 12:24:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43429,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Staphylococcus aureus 20% and Other Bacteria25% while 55% negative bacterial culture in SSTI Samples(N=100).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/106854fff0723e51fb779bbe.png"},{"id":104376274,"identity":"0956d2df-7219-4d2b-bd15-e73b9f69dc10","added_by":"auto","created_at":"2026-03-11 06:29:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":177255,"visible":true,"origin":"","legend":"\u003cp\u003eGel electrophoresis for the PCR product of (\u003cem\u003eCas-1\u003c/em\u003e\u003csub\u003e \u003c/sub\u003egene) shows a 370bp band, which was performed at 60 volts for 2 hr. (100-1500bp ladder). Lanes (6,8,11,12,14) of \u003cem\u003e\u003cstrong\u003eS. aureus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eisolates show positive results.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/681da625f07268d786ef3dd1.png"},{"id":104780029,"identity":"e412542b-cf8a-4c55-a332-ef175053f27a","added_by":"auto","created_at":"2026-03-17 07:49:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":223151,"visible":true,"origin":"","legend":"\u003cp\u003eGel electrophoresis for the PCR product of (\u003cem\u003eCas-4\u003c/em\u003e\u003csub\u003e \u003c/sub\u003egene) shows a 255bp band, which was performed at 60 volts for 2 hr. (100-1500bp ladder). Lanes (1-12,14) of \u003cem\u003e\u003cstrong\u003eS. aureus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eisolates show positive results.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/e3805d18b8a77adb75d09e98.png"},{"id":104779906,"identity":"a141053e-45ab-4fa1-90a9-5964a592309e","added_by":"auto","created_at":"2026-03-17 07:47:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":220084,"visible":true,"origin":"","legend":"\u003cp\u003eGel electrophoresis for the PCR product of (\u003cem\u003eCas-6 \u003c/em\u003egene) shows a 630bp band, which was performed at 60 volts for 2 hr. (100-1500bp ladder). Lanes (3,5,6.10,12,14) of \u003cem\u003e\u003cstrong\u003eS. aureus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eisolates show positive results.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/e45feb281755170a715bac7e.png"},{"id":104376283,"identity":"0eed16c8-22e6-413d-8a6d-6a6a965406b9","added_by":"auto","created_at":"2026-03-11 06:29:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":178538,"visible":true,"origin":"","legend":"\u003cp\u003eGel electrophoresis for the PCR product of (\u003cem\u003eCas-9\u003c/em\u003e\u003csub\u003e \u003c/sub\u003egene) shows a 838bp band, which was performed at 60 volts for 2 hr. (100-1500bp ladder). Lanes (1,2,5,7,8,10,12,14) of \u003cem\u003eS. aureus\u003c/em\u003e isolates show positive results\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/ddea78a50a6c01f71e4605b8.png"},{"id":104376278,"identity":"8cac4c79-5c7c-4bf3-b476-f88d111b5e21","added_by":"auto","created_at":"2026-03-11 06:29:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":101198,"visible":true,"origin":"","legend":"\u003cp\u003eNormalised melting curves of spa-–dRn/dT typing among the 20 Staphylococcus aureus isolates by using –dRn/dT v0.0.2. Numbers (1-7) represent the clonal complexes (CC).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/00beea733340999838989108.png"},{"id":104406183,"identity":"f13b89fd-dd51-42c8-b879-ad98e28ceb7c","added_by":"auto","created_at":"2026-03-11 12:24:59","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110063,"visible":true,"origin":"","legend":"\u003cp\u003eRaw melting curves of spa-–dRn/dT typing among the 20 studied \u003cem\u003eStaphylococcus aureus \u003c/em\u003eisolates. Numbers (1-7) represent the clonal complexes (CC).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/b311f298060de53b94995f63.png"},{"id":104376280,"identity":"1d2fb790-7453-457e-b53f-2f62b2d59286","added_by":"auto","created_at":"2026-03-11 06:29:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":698211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot of logistic regression analysis for HRM parameter.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/78b7cc6f37f6baeffc959790.png"},{"id":104784137,"identity":"68c903d5-fc2d-4d13-bb16-6c1505c7d7e4","added_by":"auto","created_at":"2026-03-17 08:05:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3775184,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/f342f9bc-3c01-402b-a4fe-476743d38f5f.pdf"},{"id":104376276,"identity":"5571059f-9899-416d-a2a7-0a8d3b636484","added_by":"auto","created_at":"2026-03-11 06:29:20","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2217697,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary files\u003c/p\u003e","description":"","filename":"supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/7af16ed6d27bee17dba85da2.docx"},{"id":104405596,"identity":"2abfc080-853f-4bfc-8787-b65c6de19bf1","added_by":"auto","created_at":"2026-03-11 12:23:22","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2217697,"visible":true,"origin":"","legend":"","description":"","filename":"supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/6f708f702f74992a97e966b0.docx"},{"id":104376282,"identity":"c84ab873-ec7b-477a-a8ed-4705b6440e9e","added_by":"auto","created_at":"2026-03-11 06:29:21","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2217697,"visible":true,"origin":"","legend":"","description":"","filename":"supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-9076229/v1/ecafe4d21761530b2af7c689.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eMolecular detection \u003c/strong\u003e\u003ca href=\"https://link.springer.com/article/10.1186/s13054-017-1801-3\"\u003e\u003cstrong\u003eof Incidence\u003c/strong\u003e\u003c/a\u003e \u003cstrong\u003eMRSA isolates from Skin and Soft Tissue Infections\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSkin and Soft Tissue Infections (SSTIs) are among the most common infections worldwide, affecting patients across all age groups(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). SSTIs can be classified based on anatomical location, clinical severity, or microbial aetiology. They encompass a wide spectrum of severity, ranging from minor, self-limiting superficial infections, such as impetigo and folliculitis, to severe, life-threatening conditions, including necrotising fasciitis and deep abscesses, which may require intensive medical intervention and surgical management(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Clinically, they are often categorised as uncomplicated, involving superficial skin layers without systemic involvement, or complicated, involving deeper tissues, requiring hospitalisation or specialised care(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Epidemiological studies have reported a rising incidence of S. aureus infections not only in healthcare settings but also in the community, highlighting the growing public health concern of methicillin-resistant S. aureus (MRSA) in both settings(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Among causative pathogens, Staphylococcus aureus is the predominant agent in both community-acquired (CA) and healthcare-associated (HA) SSTIs, although virtually any bacterial species, including Streptococcus spp. and Gram-negative bacteria, can induce inflammation in soft tissues(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Mild to moderate SSTIs are typically managed with oral antibiotics, while severe or complicated infections often require parenteral therapy, surgical drainage, and supportive care(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Appropriate antimicrobial selection is increasingly critical due to the high prevalence of multidrug-resistant S. aureus strains(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The host immune response to SSTIs is initiated by innate immune cells, primarily keratinocytes and neutrophils, which provide rapid containment of infection, followed by adaptive immune components, including dendritic cells and T-lymphocytes, that contribute to pathogen clearance and immune memory(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).. Treatment strategies depend on infection severity.Its pathogenicity is attributed to a wide array of virulence factors, including surface proteins that promote adhesion, toxins that damage host tissues, and enzymes that facilitate immune evasion(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).The spa gene is widely used as a molecular marker for strain typing and epidemiological studies due to its high variability in the X-region, which consists of short tandem repeats (STRs)(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The number and sequence of these repeats vary among strains, providing a reliable method to differentiate clonal lineages(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Spa typing allows researchers and clinicians to track outbreaks, monitor the spread of methicillin-resistant S. aureus (MRSA), and study genetic diversity within populations. Modern techniques, such as high-resolution melting (HRM) analysis, have enhanced the ability to rapidly genotype S. aureus strains based on spa gene variability(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStaphylococcus aureus is a Gram-positive, facultative anaerobic bacterium that is a major cause of skin and soft tissue infections (SSTIs), bloodstream infections, pneumonia, and device-associated infections(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Among these, protein A, encoded by the spa gene, plays a crucial role in immune modulation by binding to the Fc region of immunoglobulin G (IgG), thereby interfering with opsonisation and phagocytosis. HRM detects subtle differences in melting temperature (Tm) and amplicon size, enabling discrimination between spa types without the need for sequencing(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).In addition to its epidemiological significance, variations in the spa gene may correlate with virulence and resistance profiles, providing insights into the behaviour of different S. aureus strains. This approach has been particularly valuable for identifying endemic lineages, clonal complexes, and potential sources of infection in both community and healthcare settings(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe combination of spa typing with antimicrobial susceptibility testing and CRISPR-Cas profiling offers a comprehensive view of the genetic landscape and potential pathogenicity of clinical isolates(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Overall, the spa gene serves as both a virulence element and a molecular epidemiology tool, making it central to understanding the transmission, evolution, and clinical impact of S. aureus infections(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1.Design of the study \u0026amp; Ethical Considerations\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted on 100 specimens taken overall between July and October 2025. Approved for this study in line with ethical norms by the Al-Hilla Teaching Hospital. Hospital ethics committee under document number [ IRB: 5\u0026ndash;26, 7/8/2023]. Apart from that, every person involved in the research was briefed regarding the study before the sample gathering, and their permission was obtained concerning the test administration as well as the publishing of the results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2.Isolation, \u0026amp; The Identification of Isolates\u003c/h2\u003e \u003cp\u003eUnder sterile conditions, a total of 100 clinical specimens, including abscesses, boils, and wound infections, were collected from patients who were infected with the pathogen. Prior to swabbing, the swab was soaked in a sterile saline solution in order to increase its moisture content for patients who had dry wounds. After the samples were obtained, they were moved to the research unit of Microbiology and Antimicrobial Substances, which is located inside the Department of Microbiology at the Al-Hilla teaching hospital. It was determined that the \u003cem\u003eStaph aureus\u003c/em\u003e isolate was identified through the utilisation of conventional microbiological and biochemical techniques, which included inoculation on a medium consisting of mannitol salt agar. \u003cem\u003eStaph aureus\u003c/em\u003e isolates were characterised by the colony morphology as well as the bacterium's capacity to make oxidase, catalase, citrate, and urease tests. Each of these characteristics was taken into consideration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3.Antibiotic Susceptibility Test by Vitek-2 system\u003c/h2\u003e \u003cp\u003eThe Viteck-2 system is an automated system used for the identification of bacterial species and the determination of their antibiotic susceptibility profiles. The stages involved in the identification process were as follows: bacterial isolates were inoculated on MacConkey agar plates and then incubated at temperatures ranging from 48 to 72 degrees Celsius for a period of 24 hours. In a sterile tube, a single colony that was completely pure was suspended in 3 mm of normal saline. With the help of VITEK Densichek (bioM\u0026eacute;rieux ), the turbidity of the bacterial suspension was adjusted so that it was in accordance with the McFarland standard, which was between 0.5 and 0.7, in 0.45% sodium chloride. It was necessary to manually load the suspension tubes and the VITEK 2 ID(Gram Negative) card into the machine. A computer that is connected to the VITEK-2 system receives rustle as data for each sample after approximately six to eight hours have passed since the instrument was first used. According to the VITEK2 Compact System, the identification of \u003cem\u003eStaph aureus\u003c/em\u003e is dependent on the biochemical reactions that take place between the bacterial isolates that are suspended in their solutions and the medium that is included within the VITEK-2 Identification cards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4.DNA isolation and amplification :\u003c/h2\u003e \u003cp\u003eGenomic DNA of Isolated bacteria was extracted using the classical protocol by Presto Mini gDNA Bacteria Kit (Geneaid, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5.Primers:\u003c/h2\u003e \u003cp\u003eThe primers utilized in this study were produced by Macrogen Company, located in Korea. To prepare the working solution, the primers were diluted from stock using TE buffer to achieve a concentration of 10 picomoles per microliter, after which they were stored at -20\u0026deg;C. The oligonucleotide primers for all genes investigated in this research were sourced from prior studies and are detailed in Table\u0026nbsp;(1). This table includes the primer sequences for each studied gene, along with their corresponding amplicon size in base pairs (bp) and the respective reference. These PCR primers were employed for detecting subtypes of the system in clinical isolates of \u003cem\u003eStaph aureus.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;(1): \u003cb\u003eThe primers, their sequences, annealing temperatures, and the amplicons used in this study.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrimer-Names\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSequences (\u003c/em\u003e5` \u0026minus;\u0026thinsp;3`)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAnnealing-Tem.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAmplicon\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCas1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTAGAAAAYCATTACTTTGTTACYG\u003c/p\u003e \u003cp\u003eCRAATCCATGWAWAGCTARYTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e370\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCas4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTAAAYTWGAACGTMRRRTBGC\u003c/p\u003e \u003cp\u003eGYTTWGGTTCTTTKYKSACARC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e255\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCas6\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTTTAGGAAGTRTTTTACATGGYGTG\u003c/p\u003e \u003cp\u003eCCWGAAAATTCRCCAAACTTYA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e630\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCas9\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGGKAAAATTATMTATCGRAGTRRYG\u003c/p\u003e \u003cp\u003eCWGTRTAYAAAAGATTTGCTCGTGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e883\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGACGATCCTTCGGTGAGC\u003c/p\u003e \u003cp\u003eGCTTTTGCAATGTCATTTACTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e56\u0026deg;C for 20 s,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6.Molecular detection of CRISPR/Cas systems :\u003c/h2\u003e \u003cp\u003eMolecular identification of subtypes of system (Cas1, Cas4, Cas6, Cas9) was conducted using conventional PCR, following the protocol outlined by Soliman \u003cem\u003eet al\u003c/em\u003e. (2022). PCR amplification of DNA was carried out in a final mixture volume of 25 \u0026micro;l using GoTaq\u0026reg; G2 Green Master Mix from Promega, USA. The PCR mixtures and conditions are detailed in Table\u0026nbsp;2 of the study. After PCR amplification, the products were subjected to agarose gel electrophoresis using 1.5% gels containing green star stain, running at 100V for 35 minutes. Visualisation of the PCR products was performed using a gel documentation system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7.CRISPR Analysis\u003c/h2\u003e \u003cp\u003eThe final gel images were analyzed by BioNumerics (version 7) software (Applied-Maths, Saint-Martens-Latem, Belgium) to identify the size PCR products and to build a phylogenetic tree using UPGMA (unweighted pair group method with arithmetic mean) method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.8Statistical analysis\u003c/b\u003e :\u003c/h2\u003e \u003cp\u003eFrequency data analysis was conducted using Pearson's chi-squared test and Fisher's exact test. The data were processed and analyzed using the Statistical Package for the Social Sciences (SPSS) version 22. Results were presented as percentages.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1.Distribution of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eStaph aureus\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cstrong\u003eamong different specimens\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring this study conducted between \u003cstrong\u003eJuly and October 2025\u003c/strong\u003ein Al-Hilla teaching Hospital,, a total of 100 clinical specimens were collected from patients with various infections, including abscesses, boils, and wound infections. These specimens underwent aerobic culturing on different media. Out of 100 clinical samples, 20% were positive for Staphylococcus aureus, 55% yielded other bacterial species, and 25% showed no bacterial growth, as in Fig(1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.Biochemical tests for identification\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, all these results confirm that the isolates are \u003cstrong\u003eS. aureus\u003c/strong\u003e, because they are Gram-positive cocci that are catalase-positive, coagulase-positive, ferment mannitol, produce hemolysin, and are oxidase-negative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.Distribution of Cases by Sex and Age Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study,6 females (30%) and 14 males (70%) were studied, and males predominate in all groups except G1. \u0026nbsp;P-values (0.383, 0.865, 0.439) \u0026gt; 0.05 ( no significant difference )between sexes across age groups. Sex differences are not statistically significant. As in table2.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.Antibiotic Susceptibility Test Systems \u0026nbsp;by the Vitek-2 system\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the Table3, showed \u0026nbsp;All isolates are methicillin-resistant (\u003cem\u003eMRSA\u003c/em\u003e). Traditional \u0026beta;-lactams (penicillin, oxacillin) show very high resistance. Glycopeptides (vancomycin, teicoplanin) and linezolid remain largely effective. Tigecycline and trimethoprim/sulfamethoxazole are the most effective antibiotics against these isolates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (3): Percentage of Antibiotics Sensitive and Resistance by \u003cem\u003eS. aureus\u003c/em\u003e clinical isolates. Against 13 types of Antibiotics by Vitek2 Compact According to CLSI (2025)(n=20).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"113%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsolate N.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenzyl pencillin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOxacillin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGentamicin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCiprofloxacin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Erythromycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Clindamycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLinezolid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeicoplanin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVancomycin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeteacycline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTigecycline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRifampicin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrimethoprim / sulfamethoxazole\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eR%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e53.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e73.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eS%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e86.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e73.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e86.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eI%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;represents a significant difference at p\u0026lt;0.05. R, resistant; S, sensitive; I, intermediate.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.Genetic detection of CRISPR/Cas systems by PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, the detection of Cas-1 by PCR in 20 isolates showed that about 5(25%) carried this gene, as in Fig(2).WhileCas-4in 13(65%)isolates carried this gene in Fig(3).Detection about 6(30%) out of 20 isolates carried Cas-6 \u0026nbsp;in Fig(4)and Cas-9 in8( 40%)as in Fig(4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Correlation between antimicrobial susceptibility of \u003cem\u003eS. aureus\u0026nbsp;\u003c/em\u003eclinical isolates and the presence of CRISPR/Cas types\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn the present study, Table 4 shows the antimicrobial susceptibility patterns of\u0026nbsp;\u003cem\u003eStaphylococcus aureus\u003c/em\u003e clinical isolates were analysed in relation to the presence of different\u0026nbsp;\u003cstrong\u003eCRISPR-Cas subtypes\u003c/strong\u003e (Cas1, Cas4, Cas6, and Cas90). CRISPR-Cas systems are adaptive immune mechanisms in bacteria that protect against foreign genetic elements, such as plasmids and phages, and have been implicated in influencing horizontal gene transfer, including the acquisition of antibiotic resistance genes. Among the 20\u0026nbsp;\u003cem\u003eS. aureus\u003c/em\u003e isolates, the distribution of CRISPR-Cas subtypes was as follows:\u0026nbsp;\u003cstrong\u003eCas1\u003c/strong\u003e (5 isolates),\u0026nbsp;\u003cstrong\u003eCas4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(13 isolates),\u0026nbsp;\u003cstrong\u003eCas6\u003c/strong\u003e (6 isolates), and\u0026nbsp;\u003cstrong\u003eCas9\u003c/strong\u003e (8 isolates). The antibiotic resistance patterns varied across these subtypes, indicating a possible, though selective, association between CRISPR-Cas presence and antimicrobial resistance.\u003cstrong\u003eCas1-positive isolates\u003c/strong\u003e exhibited high resistance to \u0026beta;-lactams (benzyl penicillin and oxacillin), tetracycline, and gentamicin, while remaining mostly sensitive to vancomycin, linezolid, teicoplanin, tigecycline, and trimethoprim/sulfamethoxazole.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis pattern suggests that Cas1 may coexist with resistance factors for certain antibiotics but does not broadly confer multidrug resistance\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003eCas4-positive isolates\u003c/strong\u003e, the most prevalent subtype, demonstrated extensive resistance to \u0026beta;-lactams, ciprofloxacin, and tetracycline, alongside partial resistance to macrolides and aminoglycosides. Statistical analysis exposed a significant association between Cas4 presence and \u003cstrong\u003egentamicin resistance (p = 0.032)\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e suggesting that Cas4 may contribute to or co-occur with mechanisms that mediate aminoglycoside resistance.\u003cstrong\u003eCas6-positive isolates\u003c/strong\u003e mirrored the resistance pattern of Cas1, with notable resistance to \u0026beta;-lactams and some macrolides but high susceptibility to glycopeptides, linezolid, tigecycline, and trimethoprim/sulfamethoxazole. No statistically significant correlations were observed between Cas6 and any specific antibiotic resistance (p \u0026gt; 0.05), indicating a limited influence of this subtype on the antimicrobial phenotype.\u003cstrong\u003eCas90-positive isolates\u003c/strong\u003e displayed moderate resistance to tetracycline, erythromycin, and gentamicin, while maintaining sensitivity to vancomycin, linezolid, teicoplanin, and tigecycline. Importantly, Cas90 presence was significantly associated with \u003cstrong\u003etetracycline resistance (p = 0.003)\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e highlighting a potential role in modulating resistance to this antibiotic class.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOverall, while \u0026beta;-lactam resistance (penicillin, oxacillin) remained universally high across all CRISPR-Cas subtypes, glycopeptides (vancomycin, teicoplanin), linezolid, tigecycline, and trimethoprim/sulfamethoxazole retained high effectiveness regardless of Cas type. These findings indicate that CRISPR-Cas systems do not universally confer resistance but may be \u003cstrong\u003elinked selectively to resistance against certain antibiotics\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e particularly aminoglycosides and tetracyclines in Cas4 and Cas9 isolates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (4): Correlation between antimicrobial susceptibility of \u003cem\u003eS.\u003c/em\u003e \u003cem\u003eaureus\u003c/em\u003e isolates and the presence of CRISPR/Cas Types.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003cimg 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\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (5):\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDistribution of Cas Genes\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eamong pathogenic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;isolates\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCas-\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003egenes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCR Product\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive (N, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative (N, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eCas1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e370bp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e5 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e15 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eCas4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e255 bp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e13 (65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCas6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e630 bp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e6 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e14 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eCas9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e883 bp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e8 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e12 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e5.High \u0026ndash; Resolution melting of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eS. aureus\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eIsolates (\u0026ndash;dRn/dT ):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, the figure presents derivative high-resolution melting (HRM) curves (\u0026ndash;dRn/dT) of the amplified PCR products, where each peak represents the melting temperature\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(Tm) of an individual sample. The melting peaks are closely clustered but not identical, with Tm values distributed approximately between 84 and 86 \u0026deg;C. These small yet reproducible shifts in Tm indicate the presence of sequence variations among the tested samples, such as single-nucleotide polymorphisms (SNPs) or minor differences in GC content. Each sample exhibits a single, sharp, and symmetrical peak, suggesting. High specificity of PCR amplification. Absence of non-specific products or primer-dimer formation. The comparable peak heights further indicate similar amplicon concentrations across samples. The distinct positions of the melting peaks allow the samples to be classified into different melting profiles, demonstrating genetic heterogeneity within the amplified region. This confirms the ability of HRM analysis to differentiate closely related variants without the need for sequencing. These results highlight HRM as a rapid, sensitive, and cost-effective molecular tool for genotyping, strain discrimination, and detection of minor genetic variations in molecular epidemiological studies.\u003c/p\u003e\n\u003cp\u003eIn this figure( \u0026nbsp; \u0026nbsp;7 \u0026nbsp;),\u0026ndash;dRn/dT difference plot showing melting profile variations of Staphylococcus aureus isolates relative to reference Isolate 1. Distinct curve patterns indicate genetic diversity among the analysed isolates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (6) : (\u0026ndash;dRn/dT)spa typing results of 20 \u003cem\u003eStaphylococcus aureus\u0026nbsp;\u003c/em\u003eclinical isolates.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsolate N.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHRM Tm (\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProduct size pb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpa type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepeat of spa types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-10-21-17-34-24-34-22-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e04-21-12-41-20-17-12-12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e85.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e15-12-16-02-25-17-24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-10-21-17-34-24-34-22-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-10-21-17-34-24-34-22-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e83.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003et491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e26-23-12-34-34-12-12-23-02-12-23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-10-21-17-34-24-34-22-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e04-21-12-41-20-17-12-12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e83.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et14870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-10-13-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e83.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e26-23-12-34-34-12-12-23-02-12-23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e84.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-19-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e83.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003et491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e26-23-12-34-34-12-12-23-02-12-23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e04-21-12-41-20-17-12-12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e84.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-19-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e86.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e15-12-16-02-24-24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e84.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-19-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e83.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e26-23-12-34-34-12-12-23-02-12-23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e82.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e04-21-12-41-20-17-12-12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A19\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e84.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e11-19-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eS.A20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eCC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e86.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003et030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e15-12-16-02-24-24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 633px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC= clonal complex\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study,\u003cstrong\u003e20 (20%) were positive for\u0026nbsp;\u003c/strong\u003e\u003cem\u003eS. aureus out of 100 different clinical specimens (40 boils,35wound,25 abscesses )\u003c/em\u003e\u003cem\u003eagree with the study by\u0026nbsp;\u003c/em\u003e[18], who found common\u0026nbsp;\u003cem\u003eS. aureus in skin and soft tissue, while the study by\u0026nbsp;\u003c/em\u003e[19] found that\u0026nbsp;A total of 79 S. aureus isolates were recovered from 54(57.4%) patients out of the 94 involved in the study. Forty isolates were from wound swabs and 39 from abscesses. In this study population (n = 20), there were 6 females (30%) and 14 males (70%). Males predominated across all age groups except the youngest (G1). Statistical analysis showed that sex differences across age groups were not significant, as indicated by P-values \u0026gt; 0.05 (0.383, 0.865, 0.439), suggesting that neither sex was disproportionately affected by the condition under investigation. These findings align with several community-based studies where\u0026nbsp;\u003cem\u003eS. aureus\u003c/em\u003e infection rates did not significantly differ by sex [19],Some studies report mild male predominance in specific age ranges, but without statistical significance when confounding variables such as exposure risk and health-seeking behaviours are controlled (19).\u003c/p\u003e\n\u003cp\u003eThe age distribution in the present study revealed more male cases in older age groups (G4: 16\u0026ndash;20 years). Age-related patterns of\u0026nbsp;\u003cem\u003eS. aureus\u003c/em\u003e colonisation and infection have been reported in the literature, with complex interactions between immunity, exposure, and comorbidities influencing prevalence(20),A large multicenter analysis documented a slight male predominance in invasive disease, but differences often did not reach statistical significance (21), Similarly, age-specific trends are dependent, with community settings showing more pediatric cases and hospital-based studies showing older adult preponderance (22),In the present study, CRISPR/Cas-associated genes were investigated among 20 clinical\u0026nbsp;\u003cem\u003eStaphylococcus aureus\u003c/em\u003e isolates using PCR. The results demonstrated a variable distribution of Cas genes. Cas1 was detected in 5 isolates (25%), Cas4 in 13 isolates (65%), Cas6 in 6 isolates (30%), and Cas9 in 8 isolates (40%). These findings indicate that CRISPR/Cas elements are present in a proportion of pathogenic\u0026nbsp;\u003cem\u003eS. aureus\u003c/em\u003e strains, although not universally distributed. The relatively low prevalence of Cas1 and Cas6 compared with Cas4 suggests heterogeneity in CRISPR/Cas system carriage among clinical isolates. Similar variability has been reported in recent studies, where CRISPR-Cas systems were found inconsistently across\u0026nbsp;\u003cem\u003eS. aureus\u003c/em\u003e populations, reflecting differences in strain lineage, geographic distribution, and exposure to mobile genetic elements (MGEs) such as plasmids and bacteriophages. Cas4 was the most frequent gene detected (65%) and showed a statistically significant association (p = 0.005). Cas4 is often linked with spacer acquisition and adaptation phases of CRISPR immunity, which may explain its higher detection rate in strains exposed to foreign genetic material. Previous genomic surveys have similarly reported Cas4 enrichment in certain bacterial pathogens as part of active CRISPR defence modules.\u003c/p\u003e\n\u003cp\u003eThe present study also evaluated the relationship between CRISPR/Cas subtype carriage and antimicrobial susceptibility patterns. CRISPR/Cas systems function as adaptive immune mechanisms that protect bacteria against invasion by MGEs, which frequently carry antibiotic resistance determinants (23), Therefore, CRISPR presence may influence horizontal gene transfer and indirectly affect resistance acquisition.Cas1-positive isolates exhibited high resistance to \u0026beta;-lactam antibiotics (benzyl penicillin and oxacillin), tetracycline, and gentamicin, while remaining largely susceptible to vancomycin, linezolid, teicoplanin, tigecycline, and trimethoprim/sulfamethoxazole. This pattern suggests coexistence of Cas1 with certain resistance determinants but does not indicate broad multidrug resistance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study showed that the Cas4 subtype was common among isolates and was linked to high levels of resistance to \u0026beta;-lactam antibiotics, ciprofloxacin, and tetracycline, with a statistically significant correlation between Cas4 and gentamicin resistance (p = 0.032). Isolates positive for Cas6 exhibited resistance patterns similar to those observed in Cas1 isolates, showing high resistance to \u0026beta;-lactam antibiotics while remaining susceptible to glycopeptides and linezolid, with no statistically significant correlations with any of the tested antibiotics (p \u0026gt; 0.05). These results indicate cas is inactive or incomplete in clinical isolates.Cas9- isolates exhibited moderate resistance to tetracycline, erythromycin, and gentamicin, with a statistically significant correlation between Cas9 presence and tetracycline resistance (p = 0.003). Cas9 is a key component of type II CRISPR systems, which may influence bacterial genomes and play a role in resistance acquisition. However, CRISPR-Cas systems may coexist with resistance genes rather than completely suppress them.\u003c/p\u003e\n\u003cp\u003eThe differential melting curves (-dRn/dT) of the PCR reaction products showed single, sharp, and symmetrical peaks in all isolates, indicating high specificity of the amplification process and the absence of nonspecific products or primer dipoles. The similarity in peak height also suggests homogeneity in the concentrations of the amplification products among the samples, further enhancing the reliability of the assay. Melting temperatures ranged from 82 to 86\u0026deg;C with slight and reproducible variations, reflecting subtle genetic differences such as single nucleotide polymorphisms (SNPs) or minor variations in base content within the amplified region of the spa gene\u0026mdash;differences sufficient to produce distinct melting patterns.Spa-HRM analysis classified the isolates into seven clonal complexes (CC1\u0026ndash;CC7). The spa gene is an important molecular marker in epidemiological studies due to the polymorphism of its X region, which is rich in repeats. HRM analysis allowed for the differentiation of several spa subtypes, including t304, t078, t037, t491, t059, t030, and t14870, demonstrating significant genetic diversity among the clinical isolates studied.\u003c/p\u003e\n\u003cp\u003eThe t304 (CC7) subtype was the most frequent, appearing in multiple isolates, suggesting potential clonal expansion or local spread of this strain. The t078 (CC6) subtype was also frequently observed, consistent with previous reports linking these subtypes to hospital- and community-acquired infections and their role in ongoing transmission.\u003c/p\u003e\n\u003cp\u003eThe HRM variation plot further confirmed genetic diversity by showing distinct fusion patterns compared to the reference isolate, highlighting the effectiveness of this technique in differentiating isolates with subtle genetic differences and supporting its use in epidemiological outbreak surveillance. Statistical analysis also revealed a significant correlation between higher melting temperature and belonging to the high Tm clonal complexes. Melting temperature remained a statistically significant independent predictor even after adjusting for the size of the spa output, while fragment size showed no significant effect. The high Nagelkerke R\u0026sup2; value supports the model\u0026apos;s efficiency, confirming the reliability of HRM-Tm as a molecular marker for lineage differentiation.\u003c/p\u003e"},{"header":" Conclusion","content":"\u003cp\u003eThe present findings confirm that (–dRn/dT )spa typing is an effective method for identifying genetic heterogeneity among \u003cem\u003eS. aureus\u003c/em\u003e clinical isolates. The observed variation in melting temperatures and spa types reflects the presence of multiple clonal lineages circulating in the study population. (–dRn/dT) represents a rapid, sensitive, and cost-effective approach for genotyping, strain discrimination, and detection of minor genetic variations, supporting its value in molecular epidemiological investigations of \u003cem\u003eS. aureus\u003c/em\u003e infections.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received to assist with the preparation of this Research\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe hospital staff who deserve our sincere gratitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial support and sponsorship\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e.Nil\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAsadollahi, P., Farahani, N.N., Mirzaii, M., Khoramrooz, S.S., van Belkum, A., Asadollahi, K. and Dadashi, M. (2018) \u0026lsquo;Distribution of the most prevalent \u003cem\u003espa\u003c/em\u003e types among clinical isolates of methicillin-resistant and -susceptible \u003cem\u003eStaphylococcus aureus\u003c/em\u003e around the world: a review\u0026rsquo;, \u003cstrong\u003eFrontiers in Microbiology\u003c/strong\u003e, 9, Article 163.\u003c/li\u003e\n \u003cli\u003eBalasubramanian, D., Harper, L., Shopsin, B. and Torres, V.J. (2017) \u0026lsquo;\u003cem\u003eStaphylococcus aureus\u003c/em\u003e pathogenesis in diverse host environments\u0026rsquo;, \u003cstrong\u003ePathogens and Disease\u003c/strong\u003e, 75(1), ftx005.\u003c/li\u003e\n \u003cli\u003eChow, A., Htun, H.L., Hon, P.Y., Ang, B., Kanagasabai, K., Koh, J. and Hsu, L.Y. (2021) \u0026lsquo;Comparative epidemiology and factors associated with major healthcare-associated methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e clones among interconnected healthcare facilities in Singapore\u0026rsquo;, \u003cstrong\u003eClinical Microbiology and Infection\u003c/strong\u003e, 27(5), pp. 785.e1\u0026ndash;785.e9.\u003c/li\u003e\n \u003cli\u003eCris\u0026oacute;stomo, M.I., Westh, H., Tomasz, A., Chung, M., Oliveira, D.C. and de Lencastre, H. (2001) \u0026lsquo;The evolution of methicillin resistance in \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u0026rsquo;, \u003cstrong\u003eProceedings of the National Academy of Sciences\u003c/strong\u003e, 98(17), pp. 9865\u0026ndash;9870.\u003c/li\u003e\n \u003cli\u003eDavid, M.Z. and Daum, R.S. (2017) \u0026lsquo;Community-associated methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e: epidemiology and clinical consequences of an emerging epidemic\u0026rsquo;, \u003cstrong\u003eClinical Microbiology Reviews\u003c/strong\u003e, 30(1), pp. 3\u0026ndash;56.\u003c/li\u003e\n \u003cli\u003ede Lencastre, H., Chung, M. and Westh, H. (2000) \u0026lsquo;Archaic strains of methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e: molecular and microbiological properties of isolates from the 1960s in Denmark\u0026rsquo;, \u003cstrong\u003eMicrobial Drug Resistance\u003c/strong\u003e, 6(1), pp. 1\u0026ndash;10.\u003c/li\u003e\n \u003cli\u003eEriksen, K.R. and Erichsen, I. (1964) \u0026lsquo;Resistance to methicillin, isoxazolyl penicillins, and cephalothin in \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u0026rsquo;, \u003cstrong\u003eActa Pathologica et Microbiologica Scandinavica\u003c/strong\u003e, 62, pp. 255\u0026ndash;275.\u003c/li\u003e\n \u003cli\u003eHille, F., Richter, H., Wong, S.P., Bratovic, M., Ressel, S. and Charpentier, E. (2018) \u0026lsquo;The biology of CRISPR\u0026ndash;Cas: backward and forward\u0026rsquo;, \u003cstrong\u003eCell\u003c/strong\u003e, 172(6), pp. 1239\u0026ndash;1259.\u003c/li\u003e\n \u003cli\u003eHong, F., Salmon, S., Ong, X.Y., Liew, K., Koh, Y., Young, A. and Fisher, D. (2021) \u0026lsquo;Routine antiseptic baths and MRSA decolonisation: diverse approaches across Singapore\u0026rsquo;s acute-care hospitals\u0026rsquo;, \u003cstrong\u003eJournal of Hospital Infection\u003c/strong\u003e, 112, pp. 87\u0026ndash;91.\u003c/li\u003e\n \u003cli\u003eKlein, E.Y., Mojica, N., Jiang, W., Cosgrove, S.E. and Septimus, E. (2022) \u0026lsquo;Trends in invasive \u003cem\u003eStaphylococcus aureus\u003c/em\u003e infections by age and sex\u0026rsquo;, \u003cstrong\u003eThe Lancet Infectious Diseases\u003c/strong\u003e, 22(4), pp. 567\u0026ndash;576.\u003c/li\u003e\n \u003cli\u003eKlein, S., Morath, B., Weitz, D., Schweizer, P.A., S\u0026auml;hr, A., Heeg, K. and Nurjadi, D. (2022) \u0026lsquo;Comparative genomics reveals clonal heterogeneity in persistent \u003cem\u003eStaphylococcus aureus\u003c/em\u003e infection\u0026rsquo;, \u003cstrong\u003eFrontiers in Cellular and Infection Microbiology\u003c/strong\u003e, 12, 817841.\u003c/li\u003e\n \u003cli\u003eKluytmans-VandenBergh, M.F.Q. and Kluytmans, J.A.J.W. (2006) \u0026lsquo;Community-acquired methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e: current perspectives\u0026rsquo;, \u003cstrong\u003eClinical Microbiology and Infection\u003c/strong\u003e, 12(Suppl. 1), pp. 9\u0026ndash;15.\u003c/li\u003e\n \u003cli\u003eKluytmans-Vandenbergh, M.F.Q. and Kluytmans, J.A.J.W. (2006) \u0026lsquo;Community-acquired \u003cem\u003eStaphylococcus aureus\u003c/em\u003e carriage: determinants and implications\u0026rsquo;, \u003cstrong\u003eClinical Microbiology Reviews\u003c/strong\u003e, 19(3), pp. 469\u0026ndash;493.\u003c/li\u003e\n \u003cli\u003eKoonin, E.V. and Makarova, K.S. (2023) \u0026lsquo;Evolutionary and functional classification of CRISPR\u0026ndash;Cas systems\u0026rsquo;, \u003cstrong\u003eAnnual Review of Microbiology\u003c/strong\u003e, 77, pp. 1\u0026ndash;25.\u003c/li\u003e\n \u003cli\u003eMakarova, K.S., Wolf, Y.I., Iranzo, J., Shmakov, S.A. and Koonin, E.V. (2020) \u0026lsquo;Evolutionary classification of CRISPR\u0026ndash;Cas systems: a burst of class 2 and derived variants\u0026rsquo;, \u003cstrong\u003eNature Reviews Microbiology\u003c/strong\u003e, 18(2), pp. 67\u0026ndash;83.\u003c/li\u003e\n \u003cli\u003eMakarova, K.S., Wolf, Y.I. and Koonin, E.V. (2023) \u0026lsquo;In silico approaches for prediction of anti-CRISPR proteins\u0026rsquo;, \u003cstrong\u003eJournal of Molecular Biology\u003c/strong\u003e, 435(7), 168036.\u003c/li\u003e\n \u003cli\u003eMontoya-Urrego, D., Vanegas, J.M., Jim\u0026eacute;nez, J.N. and Gonz\u0026aacute;lez-G\u0026oacute;mez, D. (2025) \u0026lsquo;Analysis of the dynamics of transition from non-colonization to colonization and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e bacteremia in hemodialysis patients using Markov models\u0026rsquo;, \u003cstrong\u003eF1000Research\u003c/strong\u003e, 13, 837.\u003c/li\u003e\n \u003cli\u003eNyman, J.A., Lees, C.H., Bockstedt, L.A., Filice, G.A., Lexau, C., Lesher, L.J. and Lynfield, R. (2011) \u0026lsquo;Cost of screening intensive care unit patients for methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u0026rsquo;, \u003cstrong\u003eAmerican Journal of Infection Control\u003c/strong\u003e, 39(1), pp. 27\u0026ndash;34.\u003c/li\u003e\n \u003cli\u003ePinilla-Redondo, R., Russel, J., Mayo-Mu\u0026ntilde;oz, D., Shah, S.A., Garrett, R.A. and S\u0026oslash;rensen, S.J. 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(2015) \u0026lsquo;\u003cem\u003eStaphylococcus aureus\u003c/em\u003e infections: epidemiology, pathophysiology, clinical manifestations, and management\u0026rsquo;, \u003cstrong\u003eClinical Microbiology Reviews\u003c/strong\u003e, 28(3), pp. 603\u0026ndash;661.\u003c/li\u003e\n \u003cli\u003eTurner, N.A., Sharma-Kuinkel, B.K., Maskarinec, S.A., Eichenberger, E.M., Shah, P.P., Carugati, M., Holland, T.L. and Fowler, V.G. (2019) \u0026lsquo;Methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e: an overview of basic and clinical research\u0026rsquo;, \u003cstrong\u003eNature Reviews Microbiology\u003c/strong\u003e, 17(4), pp. 203\u0026ndash;218.\u003c/li\u003e\n \u003cli\u003eWatson, D.W., Iglesias, S.L., Vasarhelyi, E.M. and Heinrichs, D.E. (2021) \u0026lsquo;GraXRS-dependent resistance of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e to human osteoarthritic synovial fluid\u0026rsquo;, \u003cstrong\u003emSphere\u003c/strong\u003e, 6(2), e01128-20.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"MRSA, Skin and Soft Tissue Infections, SSTIs, Vitek2 Compact ","lastPublishedDoi":"10.21203/rs.3.rs-9076229/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9076229/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eIntroduction :\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMRSA is a global health concern due to its antibiotic resistance and its role in severe, often fatal skin and soft tissue infections in healthcare and community settings.\u003c/p\u003e\n\u003cp\u003eObjective:\u003c/p\u003e\n\u003cp\u003eThe study focuses on detecting MRSA and assessing virulence-associated Cas genes in clinical isolates from skin and soft tissue infections.\u003c/p\u003e\n\u003cp\u003eMethod\u003c/p\u003e\n\u003cp\u003eAmong 100 SSTI patients studied, 20% had \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, 55% had other bacteria, and 25% showed no growth based on standard laboratory identification methods. Antimicrobial susceptibility testing by Viteck-2 system was done, and Molecular analysis by PCR showed diverse CRISPR-Cas subtypes. HRM spa genotyping recognised.\u003c/p\u003e\n\u003cp\u003eResults and Discussion:\u003c/p\u003e\n\u003cp\u003eAmong the 20 cases, males were more frequently affected than females, with the highest infection rates observed in the 16–20 and 6–10 year age groups, although no significant association with sex or age was found. Antimicrobial susceptibility testing revealed high resistance to oxacillin, confirming the prevalence of MRSA, along with resistance to multiple other antibiotics, indicating widespread multidrug resistance. Molecular analysis showed diverse CRISPR-Cas subtypes, with significant associations between Cas subtypes and resistance to gentamicin and tetracycline. HRM spa typing demonstrated marked genetic diversity, identifying seven clonal complexes with predominant local lineages, highlighting endemic circulation and potential for increased virulence and antimicrobial resistance.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusion:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe isolates showed high MRSA occurrence (100% oxacillin resistance) and resistance to some antibiotics. CRISPR-Cas analysis discovered genetic heterogeneity, with Cas4 most common, and specific links between Cas subtypes and resistance (gentamicin–Cas4, tetracycline–Cas10).HRM spa genotyping recognized seven clonal complexes, representing both local endemic motion and significant genetic variety, which may influence virulence and resistance patterns. The findings highlight the high MRSA burden, the diverse genetic landscape of S. aureus, and the probable role of CRISPR-Cas in resistance, the necessity for incessant surveillance and informed antimicrobial therapy.\u003c/p\u003e","manuscriptTitle":"Molecular detection of Incidence MRSA isolates from Skin and Soft Tissue Infections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-11 06:29:13","doi":"10.21203/rs.3.rs-9076229/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c7fe8b9-f0ef-4f96-a2e0-0399a585799c","owner":[],"postedDate":"March 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64204370,"name":"Bacteriology"}],"tags":[],"updatedAt":"2026-03-11T06:29:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-11 06:29:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9076229","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9076229","identity":"rs-9076229","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}