From a total of 18,152 MRSA isolates collected between 2008 and 2019, 160 mecA-positive MRSArg strains were identified (0.9%), corresponding to 142 unique patients. This corresponds to a relatively low yearly incidence of 0.0–0.7 per 100,000 population (Figure 1).

The earliest detection of MRSArg isolates occurred in 2008, corresponding to the initial year of the study period. An increasing trend in the prevalence of MRSArg was observed over the course of the study period (Figure 1), rising from only two isolates in 2008 to 35 isolates in 2019. The most frequently detected spa-type across the whole study period was t6675 (n = 80, 50%), and the diversity of spa-types among MRSArg isolates expanded after 2014.

The age of MRSArg cases ranged from 0 to 89 years, with a median age of 33 years (Table 1). The sex distribution was significantly skewed toward female patients (59%) compared to the sex distribution among MRSA in the same period.

The majority of MRSArg detected in this study were related to carriage (76%). This was significantly higher than previously reported for MRSA isolates during the same study period (Table 1). Infections constituted 24%, and no invasive infections were reported. Community-associated cases constituted the majority (64%) of cases, while 36% of MRSAarg cases exhibited an epidemiological connection to the healthcare system at the time of sampling, qualifying them as HA-MRSArg. Notably, 17% of individuals were identified as health care workers (HCWs), which was significantly higher compared to MRSA cases during the same study period. However, only two strains (1.3%) were reported as outbreak associated.

Analysis of acquisition origin revealed that Asia constituted the predominant region, accounting for 43% of cases. Within Asia, the Philippines represented the most significant country-specific source, contributing 36% of total acquisitions. Europe, excluding Norway, comprised 2.5% of cases. Acquisition within Norway was reported for 31% of instances. Overall, the country of acquisition was registered in 80% of cases.

Although the Bruker Daltonics MALDI-TOF database was updated to include S. argenteus in 2018, our results show that MALDI-TOF MS exhibited limited discriminatory power in differentiating S. argenteus from especially the most closely related staphylococci like S. aureus and S. schweitzeri (Table 2). Of the tested representative collection of strains (n = 25), three strains were identified as S. aureus (11.1%), two as S. schweitzeri (7.4%) and one strain did not get any species ID (3.7%). Two additional strains were identified as S. argenteus, but with scores below 2.0 (7.41%). Thus, 29.6% of strains were either not correctly identified or had too low score for species-level identification, while 70.4% of strains were identified correctly to species level.

In silico species identification with Kraken2 in combination with the PlusPF database also exhibited limited accuracy in correctly identifying S. argenteus (Table 3). For only 25.5% of strains, S. argenteus was the top species match, with a median percent identity of only 50.7%. These included ST2793 and ST1223. For 74.5% of strains however, S. aureus was the best match, with a very low median identity of 4.6%, and these strains were ST2250.

For the panel of MRSArg strains representing all spa-types in this study (n = 25), growth was observed on all the chromogenic agar media tested in this study (Supplementary Figure 1). With inoculation of a standardized concentration of MRSArg, chromID MRSA SMART agar yielded the highest growth, or equivalent growth to another chromogenic medium, in 21 out of 25 tested strains (84%). These findings indicate that chromID MRSA SMART agar was thus the most sensitive agar among those assessed for detection of MRSArg.

On all media except chromID MRSA SMART, the colony coloration of MRSArg closely resembled that of MRSA (Figure 2; Supplementary Figure 1). On chromID MRSA SMART agar however, MRSArg colonies exhibited a blueish pigmentation following 48 h of incubation, in contrast to the characteristic pink coloration of MRSA colonies on the same agar. These findings suggest that chromID MRSA SMART agar may serve as a useful supplementary tool for phenotypic differentiation between MRSA and MRSArg.

Results from evaluation of the two enrichment broths for growth of MRSArg showed that growth in PHMB yielded the highest average stationary-phase cell density, reaching 2.67 × 10⁸ CFU/mL (Supplementary Table 1). These results furthermore highlight considerable variation in stationary-phase concentrations across the evaluated broths, with PHMB demonstrating notably higher yield (170%) relative to TSB, while growth in TSBM yielded very low (2%) stationary-phase cell density relative to TSB.

S. argenteus was first identified in 2002 in Northern Australia as S. aureus CC75 (Ng Jacklyn et al., 2009), and subsequently recognized as a distinct species in 2015 (Tong et al., 2015). Although retrospective investigations into misclassified S. argenteus remain relatively scarce, available data demonstrate a global distribution with pronounced regional variation in prevalence. Several studies have suggested geographic “hotspots” for S. argenteus, particularly in Southeast Asia, Northern Australia, and the Amazon basin (Yan et al., 2025). In Japan, prevalence has been reported at 6.4%, with retrospective analyses tracing the earliest detection back to 1986 in food-related samples (Ichikawa et al., 2025). In contrast, European data indicate sporadic occurrence and generally lower prevalence rates (<1%). Reports from Sweden (Tang Hallback et al., 2018), Denmark (Hansen et al., 2017), the Netherlands (Witteveen et al., 2022), Belgium (Argudín et al., 2016) and Germany (Alhussein et al., 2025) describe occasional isolates identified within MRSA and MSSA strain collections, dating from the mid-2000s and later. However, as demonstrated in this study, the prevalence of S. argenteus remains vulnerable to misclassification through routine diagnostic techniques such as MALDI-ToF. Even advanced methods including whole-genome sequencing and taxonomic classification may fail to fully resolve species identity, indicating that current estimates of prevalence are likely conservative and may underestimate the true occurrence of S. argenteus in clinical collections.

During the study period (2008–2019), MRSArg in Norway was predominantly associated with carriage in the community setting. Notably, the percentage of infections was significantly lower than for MRSA (24 and 36% accordingly, p < 0.001), and no invasive infections were reported. These findings may thus suggest that S. argenteus has a lower pathogenic potential than MRSA. However, other factors such as the limited size of the strain collection and the fact that it is primarily young and healthy individuals that are the main source of import into Norway, makes it difficult to make any broad statements regarding pathogenicity.

Despite uncertainty surrounding the inferred site of acquisition, MRSArg displayed significant associations to international acquisition—especially from the Philippines. This is a country with a relatively high number of immigrants to Norway in the study period.¹ Although the Philippines has not been frequently reported as a source previously, it has a high prevalence of MRSA (Masim et al., 2021), which may include misclassified MRSArg. It is also located in Southeast Asia—one of the three geographical hotspots for S. argenteus described by Becker et al. (2019).

A notable proportion of cases identified in our study involved individuals employed in healthcare settings, representing a novel observation not previously documented in the literature. This is likely also the reason for a relatively high proportion of female cases of MRSArg, as women constitute more than 80% of the workforce in the health and social care sector in Norway (Statistisk Sentralbyrå, 2024). However, our broad definition of healthcare-associated MRSArg, necessitated by missing admission-time data, may have misclassified some cases. International criteria distinguish hospital-onset, healthcare-associated community-onset, and community-associated infections by timing ( > 48–72 h) and prior exposure, meaning admission diagnoses often reflect community acquisition (Pantosi and Venditti, 2009). Thus, our approach likely overestimated HA-MRSArg and underestimated CA-MRSArg. We acknowledge this limitation and recommend future studies incorporate admission-time data or sensitivity analyses to align with standard definitions (Pantosi and Venditti, 2009). Notably, the prevalence of MRSArg among HCWs in this cohort significantly exceeded that reported for MRSA within a comparable population, as previously described (Ronning et al., 2024), using the same broad definition of HA. These findings could thus be indicative of MRSArg presenting an increased risk for nosocomial transmission and outbreaks. However, in this study only two strains were registered as outbreak-related, and furthermore, no evidence of cryptic transmission was uncovered based on cgMLST and cgSNP analyses.

The first confirmed case of MRSArg in Norway was from 2008. Nonetheless, earlier cases may have gone undetected, as national MRSA surveillance incorporating spa-typing of isolates was only established that same year. The identification of the initial MRSArg isolate in Norway coincides with its first reported detection in the Netherlands in 2008 (Witteveen et al., 2022), and occurred four years after the earliest known isolate belonging to the “Staphylococcus aureus clonal complex 75” was collected in Australia (McDonald et al., 2006). Temporal trends showed a consistent increase in MRSArg detections over the study period, culminating in a peak of 35 cases in 2019. Correspondingly, the incidence increased from 0.04 cases per 100,000 population in 2008 to 0.7 in 2019. The upward trend may reflect multiple introductions over time, rather than ongoing endemic circulation domestically. This is a substantially lower incidence compared to that of MRSA (from 14.2 in 2008 to 48.6 in 2017) in Norway in a comparable time period (Ronning et al., 2024).

Genotyping revealed limited genomic diversity of MRSArg in Norway, with only three main clusters corresponding to ST2250, ST2793 and ST1223, with t6675/ST2250 as the dominant lineage (50.6%). This is in line with previous studies describing the population structure of S. argenteus (Goswami et al., 2021). We observed an expansion in spa-type diversity after 2014, which may reflect introduction of novel lineages, expansion of community spread or evolutionary adaptation within the local bacterial population.

In this study, we tested two enrichment broths and four chromogenic MRSA media that all supported growth of MRSArg. Endpoint growth assessment was chosen as it provides a robust, reproducible, and clinically relevant measure of medium performance by reflecting maximum biomass yield for reliable detection across diverse MRSArg genotypes. However, endpoint growth assessment has limitations, as it does not capture growth kinetics and may obscure subtle differences in strain performance or medium characteristics. Of the broths tested, PHMB yielded the highest stationary-phase cell concentrations (2.67 × 10⁸ CFU/mL), outperforming both TSB and TSBM, proving to be a highly effective medium for enhancing MRSArg recovery. Of the chromogenic media, only chromID MRSA SMART agar allowed for practical visual differentiation of MRSArg colonies from MRSA colonies based on a distinct blue coloration of MRSArg colonies after 48 h. Moreover, chromID MRSA SMART agar yielded the highest growth across all tested genotypes, indicating superior sensitivity and positioning it as the most effective medium for MRSArg cultivation among those evaluated.

All tested strains across diverse sequence types yielded positive results using the Xpert^® SA Nasal Complete assay, thus allowing for rapid molecular detection of MRSArg, albeit without differentiation from MRSA. While this cross-reactivity poses a risk for misclassification in clinical settings without further species-level identification, is also ensures broad detection of methicillin-resistance within the S. aureus complex, in line with recommended reporting practices from the ESGS position paper (Becker et al., 2019): Routine reporting should not differentiate between S. aureus, S. argenteus, and S. schweitzeri unless clear evidence emerges of divergent pathogenicity or clinical outcomes. Importantly, methicillin-resistant isolates, regardless of species within the S. aureus complex, should be managed according to MRSA protocols to ensure patient safety and appropriate clinical communication. Another important aspect is that this tool can be utilized for the rapid detection or exclusion of MRSArg during outbreak investigations, thereby supporting timely diagnostic clarification and infection control measures.

A notable finding in this study is that reliable identification of S. argenteus still remains a challenge, both with standard diagnostic methods such as MALDI-TOF MS and with bioinformatic methods like Kraken2, leading to difficulties in distinguishing Staphylococcus argenteus from closely related species such as S. aureus and S. schweitzeri. These issues likely stem from low representation of S. argenteus genotypes as well as other S. aureus complex species in the underlying databases (Chen et al., 2018; Eshaghi et al., 2021). A more general issue may be persistent misclassification in databases. This diagnostic ambiguity prompted the development of molecular tools for accurate species-level detection and genotyping within this study.

A species-specific multiplex PCR assay targeting the S. argenteus-specific gene yhfT, the methicillin resistance gene mecA, and the virulence-associated gene lukE was developed and validated. This assay enabled simultaneous detection of species identity, beta-lactam resistance, and virulence marker, offering a rapid and comprehensive molecular diagnostic tool. In concordance with the WGS data, MRSArg was fully distinguished from MRSA. Such assays are critical for overcoming the limitations of conventional phenotypic methods and ensuring accurate identification of MRSArg in both clinical and surveillance contexts. To further enhance diagnostic precision, development and implementation of novel primers tailored to S. argenteus enabled successful Sanger sequencing-based spa-typing across all isolates, achieving 100% type ability. This represents a significant methodological advancement, facilitating robust strain-level resolution and epidemiological tracking of MRSArg.

Whole genome sequencing highlighted the limited genomic diversity of MRSArg strains across the study collection, with only three distinct clades corresponding to ST2250, ST2793, and ST1223. Core genome SNP analysis furthermore revealed low degree of genetic diversity within the major MRSArg STs identified. Although the dataset comprised strains collected from diverse geographic regions and over an extended time period, the overall genetic diversity was thus relatively low compared to, for instance, S. aureus (Liu et al., 2023), likely reflecting the much more recent and limited spread of MRSArg. Following the evolutionary trajectory and potential clonal success of MRSArg may thus provide valuable insights into the emergence and adaptation of a S. aureus-like pathogen.

The antimicrobial resistance profiles of the MRSArg isolates analyzed in this study revealed that antimicrobial resistance to other classes than beta-lactams was notably low, which is in line with previous studies (Witteveen et al., 2022). Consequently, standard treatment regimens commonly applied for MRSA are expected to remain effective, with low risk of treatment failure for MRSArg infections. No adapted or pathogen-specific therapeutic strategies appear necessary for MRSArg based on the phenotypic antibiotic susceptibility testing and antibiotic resistance genes detected in this study. MRSArg strains however, shared many notable virulence factors with S. aureus, many of which are associated with mobile genetic elements like plasmids, phages, pathogenicity islands (Wu et al., 2021), indicating potential horizontal spread.

While the MRSArg strains shared many virulence determinants, we did observe some ST-specific variability, especially in toxin genes. While many MRSA encode PVL, a cytotoxin associated with increased virulence of S. aureus, this was not detected in any MRSArg strain in this study. Instead, S. argenteus possessed analogous genes encoding a distinct leukocidin most closely related to LukED; however, its role in infection remains less well-described. Notably, these genes were misclassified by some tools/databases as lukS/lukF-PVL, which may lead to erroneous conclusions about the prevalence and role of PVL in S. argenteus.

The background population included all strains of MRSA and MRSArg from the Norwegian MRSA reference laboratory strain collection covering the years 2008–2019 (n = 18,152). Inclusion criteria for the S. argenteus study population included all strains with inconclusive spa-typing (“non-typable MRSA”), multilocus sequence types (STs), characteristic repeats, alleles, and clonal complexes that have previously been associated with the species. Strains meeting either of these genetic criteria were presumptively identified as S. argenteus and selected for further investigation.

Epidemiological data on all included cases was collected from the Norwegian Surveillance System for Communicable Diseases (MSIS) and the request forms from the referring laboratory or the treating physician (accessed through the laboratory information system). The Information from MSIS included age, sex, county of residence, country of birth, parent’s country of birth, admission to hospital or nursing home, reason for sampling, place of acquisition, part of a known outbreak (MRSA request forms or Norwegian outbreak rapid alert system Vesuv) and if the person worked within the health care system. The data obtained from the laboratory information system included sample date, sampling site and results of laboratory analyses. All MRSArg cases were categorized as carriage, infection, invasive infection or unknown based on sampling site/type of sample. Age groups were based on categories defined by Diaz et al. (2021). Due to lack of data on admission time for hospitalized patients, we used a broad definition of healthcare-associated MRSArg (HA-MRSArg). A case was classified as HA-MRSArg if diagnosed during admission to a hospital or nursing home and/or if MRSArg was diagnosed in healthcare workers (HCWs), while community-acquired MRSArg (CA-MRSArg) was defined as all other cases.

Bacterial strains were routinely cultured on blood agar at 35°C. Four commercially available chromogenic media designed for the selective identification of MRSA were evaluated using a representative panel of MRSArg strains (n = 25), encompassing all MRSArg spa-types (one strain per spa-type) included in the study (Table 5). The media included chromID MRSA SMART (BioMérieux), Scientific Brilliance Scientific Brilliance MRSA 2 (Thermo Fisher Scientific), BD BBL CHROMagar MRSAII (BD) and CHROMagar MRSA (CHROMagar). Plates were inspected after 24- and 48-h incubation and growth qualitatively assessed as sparse, moderate or abundant.

Two enrichment broths were additionally evaluated in this study; tryptic soy broth (TSB) supplemented with aztreonam (20 mg/L) and cefoxitin (3.5 mg/L) (TSBM), and phenol red mannitol broth supplemented with ceftizoxime (5 mg/L) and aztreonam (75 mg/L) (PHMB). Briefly, MRSArg strains were cultured at 35°C for 24 h in unsupplemented TSB and then diluted (100 μL) in 5 mL enrichment broth. After 24 h incubation at 35°C, serial dilutions were plated on blood agar plates, before semi-quantitative growth assessment after 24- and 48-h incubation.

Antimicrobial susceptibility testing (AST) was performed for all included MRSArg stains (n = 160) at the Norwegian MRSA reference laboratory (2009–2015) or the referring laboratory (2016–2019) using the European Committee on Antimicrobial Susceptibility Testing (EUCAST) disc diffusion method or agar gradient method as previously described (Ronning et al., 2025). Results were interpreted as either susceptible, intermediate or resistant using the clinical breakpoints for S. aureus according to the 2017 EUCAST break point table v.7.1.

Identification of a selection of bacterial strains (n = 25) was performed using matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) (Clark et al., 2013), with a MALDI Biotyper Sirius instrument and the Bruker Daltonics database V12.0.0.0_10833-11897, on single colony obtained from sheep blood agar COLS+ (Oxoid). Log (score) values above 2.0 were accepted as probable species-level identification, while scores between 1.7 and 1.9 were accepted as probable genus-level identification (Sauer et al., 2008).

Rapid detection of MRSArg was performed using the Xpert SA Nasal Complete on a GeneXpert XVI instrument according to the manufacturer’s recommendations. Due to costs and reagent availability, a selection of MRSArg strains (n = 7) from different spa-types, representing all three STs detected in this study, were used for GeneXpert testing.

All 160 MRSArg isolates were subjected to whole genome sequencing. Briefly, colonies were suspended in TE-buffer and treated with proteinase K (2 mg/mL) and lysostaphin (0.1 mg/mL) for 15 min with shaking at 37°C, before heating for 15 min at 65°C. Genomic DNA was then isolated using the EZ1 DNA tissue kit with an EZ1 Advanced XL instrument (Qiagen). Sequencing libraries were prepared using the Nextera XT sample prep kit and sequenced on the MiSeq platform with MiSeq v3 reagents, with 300 bp paired end reads (Illumina). Raw data were quality controlled, trimmed/filtered, classified with Kraken2 (PlusPF database) and de novo assembled, and the assembled genomes annotated, and typed (multi-locus sequence typing, MLST, according to S. aureus pubMLST scheme) with the Nullarbor pipeline version 2.0 (Seemann et al., 2018). Three strains were excluded from further bioinformatic analyses based on quality control. Assemblies are available from GenBank under BioProject PRJNA1306038.

Resistance genes were identified using AMRFinder+ with the NCBI AMRFinder+ database (Feldgarden et al., 2021). Virulence genes were identified using ABRicate (Seemann, 2016) with the Virulence Factor DataBase (VFDB) (Chen et al., 2005). Additionally, SCCmecFinder 1.2 was used for SCCmec typing of all strains (Kaya et al., 2018). The core and accessory genome of the strains was defined and a core genome alignment produced by Roary version 3.13 (Page et al., 2015). Fasttree 2.1.10 (Price et al., 2010) was used to infer a maximum likelihood core genome phylogeny with the GTR model. Distance estimation was performed by Molecular Evolutionary Genetics Analysis (MEGA) software (Tamura et al., 2021), with genetic distances referring to the number of SNPs in the core genome alignment. SeqSphere+ (Ridom) was used for creating a minimum spanning tree (MST) of spa-repeats. Visualizations of phylogenies with metadata were created using iTOL (Letunic and Bork, 2021).

A multiplex real-time PCR for the specific detection of methicillin-resistant S. argenteus was developed in this study (Table 5).

Species-specific candidate genes for PCR assay development were identified using Roary (Page et al., 2015) by performing pan-genome analysis. The dataset comprised reference genomes including S. argenteus (n = 16), S. aureus (n = 21), and other stapylococcal species (n = 53) including Staphylococcus schweitzeri strain NCTC13712, as well as the complete S. argenteus strain collection from this study (Supplementary Table 5). A clustering threshold of 70% identity was used to avoid subclustering of orthologous proteins from different staphyloccoccal species. Potential targets were then selected based on presence in all S. argenteus genomes, absence in all other staphylococcal genomes, presence in single copy and single fragment per genome, and within cluster identity of ≥ 97%. Additionally, for each candidate gene, BLASTn against the non-redundant NCBI database should only yield hits against S. argenteus. From this, a putative acyl–CoA ligase encoding gene, yhfT, was selected as target.

Based on virulence profiles of this MRSArg strain collection, the bicomponent leukotoxin LukED was selected as the secondary target for the species-specific PCR. The sequences of the lukD and lukE genes were extracted from S. argenteus reference genomes (n = 16) and the MRSArg strain collection (n = 160). A multiple alignment was then used to identify conserved regions suitable for primers and probes, after which lukE was selected as the secondary target for the multiplex PCR. Primers and probes for yhfT and lukE were then designed using IDT RealTime qPCR Assay (Table 5).

The PCR primers and probes for yhfT and lukE were tested, in triplex with mecA, against a selection of whole genome sequenced MRSArg (n = 20) and MRSA strains (n = 20) of different genotypes for validation. Validation was performed by assessing diagnostic performance, including concordance WGS, lack of cross-reactivity and comparison of two DNA extraction methods; boiled lysates and EZ1 DNA extraction. The sensitivity (limit of detection) and amplification efficiency of the multiplex PCR was furthermore assayed, using S. argenteus t6675/ST2250 strain SO-SARG8-1.

For validation, two DNA preparation methods were compared. Ten MRSArg and ten MRSA isolates were processed as boiled lysates, prepared by suspending colonies in molecular-grade water, heating at 95°C for 15 min with shaking (300 rpm), centrifuging (14,500 rpm for 2 min), and collecting the supernatant. For another ten MRSArg and ten MRSA isolates, DNA was extracted with the EZ1 Advanced XL instrument from WGS. All samples were tested in duplicate by real-time PCR on the QuantStudio 5 system, using Perfecta Custom Multiplex qPCR SuperMix, an annealing temperature of 62°C, and 35 cycles.

Statistical analyses of discrete variables were performed using Fisher’s exact test. The Benjamini-Hochberg method was used to correct for multiple hypothesis testing, with adjusted p < 0.05 regarded as statistically significant.