Next Article in Journal
Characterisation of Variants of Cyclic di-GMP Turnover Proteins Associated with Semi-Constitutive rdar Morphotype Expression in Commensal and Uropathogenic Escherichia coli Strains
Previous Article in Journal
Genetic Diversity of Hepatitis B and C Viruses Revealed by Continuous Surveillance from 2015 to 2021 in Gabon, Central Africa
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria

1
Laboratory of Molecular Biology, Genomics and Bioinformatics, Department of Biology, Faculty of Nature and Life Sciences, University Hassiba Benbouali of Chlef, Chlef 02000, Algeria
2
School of Medicine, University of St Andrews, St Andrews KY16 9TF, UK
*
Author to whom correspondence should be addressed.
Microorganisms 2023, 11(8), 2047; https://doi.org/10.3390/microorganisms11082047
Submission received: 18 July 2023 / Revised: 2 August 2023 / Accepted: 6 August 2023 / Published: 9 August 2023
(This article belongs to the Section Public Health Microbiology)

Abstract

:
Staphylococcus aureus is an important pathogen responsible for various healthcare- and community-acquired infections. In this study, whole genome sequencing (WGS) was used to genotype S. aureus clinical isolates from two hospitals in Algeria and to characterize their genetic determinants of antimicrobial resistance. Seventeen S. aureus isolates were included in this study. WGS, single-nucleotide polymorphism (SNP)-based phylogenetic analysis, in silico multilocus sequence typing (MLST), spa and staphylococcal cassette chromosome mec (SCCmec) typing and in silico antimicrobial resistance profiling were performed. Phenotypic antibiotic susceptibility testing was performed using the Vitek 2 system and the disk diffusion method. The isolates were separated into sequence types (STs), with ST80 being predominant; five clonal complexes (CCs); four spa types (t044, t127, t368, t386); and two SCCmec types (IVc and IVa). Whole genome analysis revealed the presence of the resistance genes mecA, blaZ, ermC, fusB, fusC, tetK, aph(3′)-IIIa and aad(6) and mutations conferring resistance in the genes parC and fusA. The rate of multidrug resistance (MDR) was 64%. This work provides a high-resolution characterization of methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) isolates and emphasizes the importance of continuous surveillance to monitor the spread of S. aureus in healthcare settings in the country.

1. Introduction

S. aureus is the leading cause of nosocomial infections worldwide [1]. Although it is a normal resident of the skin and mucous membranes of humans and animals, S. aureus can become an opportunistic pathogen by deploying a plethora of virulence factors to cause a variety of infections, ranging from mild skin and soft tissue infections to severe and life-threatening diseases, such as toxic shock syndrome and sepsis [2]. This strong potential of S. aureus to cause diseases is aggravated by its propensity to acquire resistance to multiple antibiotics, limiting the therapeutic options against this pathogen [3].
MRSA is a group of S. aureus strains that have developed resistance to methicillin and to the majority of the β-lactam antibiotics following the acquisition of a mecA gene. This gene which resides on a complex mobile genetic element known as “Staphylococcal Cassette Chromosome” mec element (SCCmec) encodes a 78 kDa penicillin-binding protein (PBP2a) that has a low affinity for β-lactams [3]. MRSA is recognized as one of the leading pathogens responsible for nosocomial and community-associated infections worldwide [4]. Effective MRSA control and prevention strategies in the healthcare system as well as in the community depend on accurate characterization of circulating MRSA clones and identification of their reservoirs and sources of transmission.
Although the prevalence and molecular epidemiology of MRSA in Europe and North America have been extensively documented [5], comparatively, data available from North Africa are limited or scarce. However, from the available data, it appears that the prevalence of MRSA in this region is increasing [6,7].
In Algeria, analyses of S. aureus from diverse geographic locations and clinical origins were mainly based on genotyping methods. These studies showed that the dominant clone was the European ST80 IV PVL+ community-associated (CA)-MRSA [8,9,10,11]; however, WGS-based studies were applied only in a single study on three healthcare-associated (HA)-MRSA isolates [11]. Thus, here we report the characterization of MRSA and MSSA clinical isolates from patients admitted to two tertiary healthcare hospitals in the province of Chlef in Algeria using WGS.

2. Materials and Methods

2.1. Study Setting and Sample Collection

We investigated 17 clinical S. aureus isolates from pus, cerebrospinal fluid (CSF) and blood samples of patients admitted to two hospitals in the Chlef province, Algeria, during the period between November 2018 and July 2019.
All patients gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of the Algerian Thematic Research Agency for Health and Life Sciences (ATRSSV387).

2.2. S. aureus Culture and Identification

Bacteria were enriched in brain heart infusion broth and incubated at 37 °C for 18 h–24 h before being cultured on Mannitol salt agar (Merck, Darmastadt, Germany) for 24 h at 37 °C. Isolates were initially identified by standard microbiological methods using Gram staining, catalase and coagulase tests. Putative staphylococcal isolates were confirmed as S. aureus by PCR targeting the nuc gene as described by Zhang et al. [12]. The PCR reaction was carried out in a total volume of 25 μL, containing 5 μL of chromosomal DNA, 3 μL of each primer (10 μM), 0.5 μL of mixed dNTPs, 2.5 μL of buffer (10×), 0.25 μL of Taq polymerase and 10.75 μL of ultra-pure H2O. The PCR amplification program was as follows: an initial denaturation at 94 °C for 10 min, followed by 35 cycles of 94 °C for 1 min, 58 °C for 30 s and 72 °C for 1 min and a final extension step at 72 °C for 7 min. The PCR products were separated on 2% agarose stained with ethidium bromide and visualized using a UV transilluminator.

2.3. Genomic DNA Extraction and Whole Genome Sequencing

The S. aureus isolates were grown overnight at 37 °C on tryptic soy broth medium under agitation. Whole DNA extraction was performed using MasterPure Gram Positive DNA Purification Kit (Lucigen, Middleton, WI, USA). The quality of the DNA was assessed with a Qubit® fluorometer 3.0 (Invitrogen, Life Technologies, Singapore). Genomic DNA libraries were prepared using the Nextera XT Library Prep Kit (Illumina, San Diego, CA, USA) and were sequenced on the Illumina MiSeq platform (Illumina, San Diego, CA, USA). De novo assembly was performed using the normal mode of Unicycler pipeline v.0.4.7 [13]. The quality of the assembly was assessed by using Quast 4.6, and the assembly was then annotated with the Prokka software version 1.10 [14], using the default parameters.

2.4. MLST Analysis

In silico MLST of the isolates was performed with the Short Read Sequence Typing for bacterial pathogens (SRST2) program [15], which employs bowtie2 to call loci directly from Illumina reads based on the S. aureus MLST database PubMLST (https://pubmlst.org/saureus/, accessed on 15 November 2022).

2.5. SNP-Based Phylogenetic Analysis

The assembled complete genomes were aligned to a reference genome of the S. aureus strain MSSA476 (an MSSA isolate belonging to ST1, with accession number BX571858 retrieved from EMBL/GenBank databases) using snp-sites (https://github.com/sanger-pathogens/snp-sites, accessed on 15 November 2022) [16]. Pangenome analysis was performed using the Roary pipeline (version 3.11.2) [17], and SNPs were identified using Gubbins software v2.3.2 [18]. A maximal likelihood tree was constructed using RAxML version 8.0.26 [19].

2.6. SCCmec and Spa Typing

The SCCmec chromosomal cassettes were identified in the genomes using SCCmecFinder v.1.2 [20], with minimum thresholds set at 60% for sequence coverage and at 90% for sequence identity. Spa typing was performed using spaTyper v.1.0 [21], using the default parameters.

2.7. Analysis of Virulence-Associated Genes

The Panton–Valentine leukocidin (PVL) toxin (lukF-PV and lukS-PV) and the toxic shock syndrome toxin 1 (TSST-1) genes were identified by querying the genome sequences against the database Pathosystems Resource Integration Center (PATRIC version 3.6.12: https://www.patricbrc.org/, accessed on 10 December 2022) with the VFDB and Victors tools [22].

2.8. Genotypic Antimicrobial Resistance Analysis

The presence of antimicrobial resistance genes (ARGs) was assessed by screening the whole genomes against the Comprehensive Antibiotic Resistance Database (CARD) [23].

2.9. In Vitro Antimicrobial Susceptibility Testing

Microdilution susceptibility testing of isolates was performed using either the Vitek® 2 system (bioMérieux®, Marcy L’Etoile, France) or the disk diffusion method. The Vitek® 2 was used with the following antibiotics: erythromycin (ERY), clindamycin (CLI), levofloxacin (LVX), linezolid (LZD), moxifloxacin (MXF), nitrofurantoin (NIT), quinupristin/dalfopristin (QD), tigecycline (TGC), teicoplanin (TEC), tetracycline (TET), trimethroprime + sulfamethoxazol (SXT) and vancomycin (VAN).
The disk diffusion method on Mueller–Hinton agar was performed with the following antibiotic disks: amikacin (AMK; 30 μg), cefoxitin (FOX; 30 μg), ciprofloxacin (CIP; 5 μg), chloramphenicol (CHL; 30 μg), fusidic acid (FUS; 10 μg), gentamycin (GEN; 10 μg), kanamycin (KAN; 30 μg), ofloxacin (OFX; 5 μg) and rifamycin (RIF; 5 μg). Results were interpreted according to the Clinical and Laboratory Standards Institute guidelines [24] and the Committee of the Antibiogram of the French Society of Microbiology [25]. MDR was defined as resistance to three or more classes of antibiotics.

3. Results

3.1. Identification of S. aureus

This study included 17 clinical isolates of S. aureus, isolated from pus (n = 15, 88%), CSF and blood (n = 1, 6%, each). The demographic and clinical data of patients as well as the characteristics of the S. aureus isolates used in this study are presented in Table 1. The majority of the isolates (58.8%, n = 10) were from patients admitted for more than 48 h and were therefore considered as HA-S. aureus, according to the CDC definition [26]. Twelve (70.6%) of the S. aureus isolates were from adults and five were from children (29.4%); of these isolates, eight (47.1%) were from males and nine (52.9%) were from females. Out of the 17 S. aureus isolates, 7 (41.2%) were identified as MRSA by being resistant to cefoxitin and harboring the mecA gene, and 10 (85.8%) were MSSA (Table 1).

3.2. MLST Analysis

In silico MLST analysis of the S. aureus isolates revealed four different STs, ST1, ST22, ST45 and ST80, and a novel single-locus variant of ST15 (slvST15). ST80 was the most prevalent (n = 5, 29.4%), followed by ST1 and ST22 (n = 4, 23.5%, each), slvST15 (n = 3, 17.6%) and ST45 (n = 1, 5.8%) (Figure 1). The MRSA isolates were distributed across three STs, the majority (71.4%, 5/7) in ST80 and one each (14.3%) in ST1 and ST22. The isolates belonged to five known CCs, CC1 (ST1), CC22 (ST22), CC45 (ST45), CC15 (slvST15) and CC80 (ST80) (Figure 1).

3.3. SCCmec, Spa and PVL Typing

A total of four spa types, t044 (n = 5, 29.4%), t127 (n = 3, 17.6%), t368 (n = 2, 11.7%) and t386 (n = 1, 5.9%), were detected among 11 S. aureus isolates; the spa type of the six remaining S. aureus isolates could not be determined (Figure 1). Among the MRSA isolates, two types of SCCmec, type IVc (n = 5, 71.4%) and IVa (n = 2, 28.6%), have been identified (Figure 1). The genes encoding the two components of the PVL toxin (lukF-PV and lukS-PV) were detected in five (1RN, 2RN, 4RN, 15RN and 16RN) out of the seven MRSA isolates, all of which belong to ST80 (71%). Notably, the gene encoding the TSST-1 was detected in one isolate (29RN) belonging to ST22.

3.4. Phylogenetic Analysis

Core genome SNP-based phylogeny revealed that the SNP differences among the 17 S. aureus isolates ranged from 0 to 60210. Phylogenetic reconstruction grouped the isolates into five separate clusters which matched their respective STs (Figure 1).

3.5. Phenotypic Antimicrobial Susceptibility Testing

The 17 isolates were tested for susceptibility against a panel of 21 antibiotics belonging to 13 classes. All S. aureus isolates were susceptible to VAN, QD, SXT, LZD, TEC, TGC and NIT.
The resistance rates observed in this study included 53% to ERY, CLI, AMK and KAN (n = 9, each); 47% to FUS (n = 8); 41.2% to FOX (n = 7); 35% to OFX and TET (n = 6 each); 23.5% to CIP (n = 4); 17.6% to GEN (n = 3); 11.7% to RIF (n = 2); and 5.9% to CHL (n = 1) (Table 2).
Three isolates exhibited co-resistance to two antibiotic classes (β-lactams and aminoglycosides or β-lactams and fusidic acid), whereas three isolates were resistant to β-lactam antibiotics only.
More than half of the S. aureus isolates (64.7%, n = 11) displayed multidrug resistance (MDR), displaying resistance to three or more antibiotic classes. The rate of MDR in the MRSA isolates (71.42%, 5/7) was higher than that in the MSSA isolates (60%, 6/10) (Table 2).

3.6. In Silico Analysis of Antimicrobial Resistance Genes

Analysis of the genomes of the 17 S. aureus isolates revealed the presence and distribution of 10 acquired antibiotic resistance genes conferring resistance to β-lactams (blaZ and mecA), erythromycin (ermC), tetracycline (tet(K)), fosfomycin (fosB), fusidic acid (fusB and fusC), aminoglycosides (aad(6) and aph(3′)-IIIa) and streptothrin (sat-4) (Figure 1) and mutations in four core genes conferring resistance to fusidic acid (fusA), fosfomycin (glpT and murA) and fluoroquinolones (parC).
Seven S. aureus isolates (41%) carried the methicillin resistance gene mecA and were therefore considered as MRSA.
The ermC gene encoding a 23S rRNA adenine-N-6 methyltransferase that confers resistance to the macrolide–lincosamide–streptogramin B (MLSB) class of antibiotics was the most frequent antibiotic resistance genetic determinant identified in our collection of isolates, being present in eight isolates (47%). The blaZ gene encoding a type C β-lactamase was present in seven (41%) S. aureus isolates. The fusC or fusB genes encoding proteins that block the binding of fusidic acid to EF-G responsible for fusidic acid resistance were identified in four isolates (23.5%), whereas fusidic acid resistance conferred by a mutation H457Q in fusA was detected in one isolate (5.8%), 15RN (ST80) (Figure 1).
The fosfomycine resistance gene fosB, encoding a fosfomycin-modifying enzyme, was detected in three isolates (17.6%), and a fourth isolate, 19RN (ST45), had mutations A100V in glpT and E291D and T396N in murA.
Three isolates (17.6%) harbored an S80F mutation in parC, conferring resistance to fluoroquinolones (Figure 1).
Of note, the majority of the above resistance genetic determinants (mecA, blaZ, ermC, fusB, tetK, aad(6), aph(3′)-IIIa) were carried by one HA-MRSA isolate (1RN), which had MDR and carried the PVL toxin genes lukF/lukS-PV.

3.7. Correlation between Phenotypic Antimicrobial Susceptibility Testing and Genotype

The observed correlation between phenotypic resistance and genotype varied widely. It was high for FOX/mecA (100%), ERY/CLI/ermC (94%), TET/tet(K) (94%), MOX/parC (82%) and LVX/parC (76%); moderate for AMK/GEN/KAN/aph(3′)-IIIa/aad(6) (64-70%); and poor for FUS/fusB/fusC and OFX/parC (58%), CIP/parC (52%), QD/ermC and FUS/fusA (47%).

4. Discussion

In this study, WGS was used to determine the phylogeny and molecular characteristics of 10 MSSA and 7 MRSA isolated from clinical samples. The percentage of MRSA among S. aureus isolates in our study (41.1%, 7/17) was in line with that reported in North African countries, 31% in Libya, 45% in Algeria and Tunisia and 52% in Egypt [7]. The prevalence of MRSA in Europe varied from 2% in the Netherlands to 58% in Italy [28,29], and that in Asia varied from 22.6% (India) to 86.5% (Sri Lanka) [28], with an average of 25% in both continents [28,30].
The results presented in this study revealed diversity among our collection of S. aureus isolates with the isolates falling to one of five clonal complexes. The MRSA clone ST80-spa-t044-SCCmec-IVc(2b)-PVL+ which was predominant in this study was also reported as dominant in many parts of the world as a cause of infections in both hospital and community settings [31]. This clone was also previously identified as dominant in different ecological niches in Algeria [32,33].
The second most abundant clone, ST1-t127, was identified in the 1990s as the first CA-MRSA clone [34] and then emerged in diverse healthcare settings [35,36,37], and it was also recovered from companion animals, livestock and livestock products in several countries [38,39,40]. Interestingly, the ST1-t127 clone, which was mainly found as MRSA in many studies [41], was both MRSA and MSSA in this study.
The other second most predominant clone in our study, ST22, was represented by three MSSA and one MRSA (SCCmec type IVa). MRSA belonging to ST22 (EMRSA-15) were reported as the most frequently responsible for nosocomial infections in Europe, are becoming widespread in Asia, Australia, Europe and North America [42,43,44,45], and have also been sporadically isolated in Algeria, Tunisia and South Africa [46]. However, the ST22 MRSA identified in this study does not belong to the EMRSA-15 clone as it contains a type IVa SCCmec element rather than a type IVh and is also ciprofloxacin-sensitive, whereas EMRSA-15 is ciprofloxacin-resistant [42].
Our least frequent clone, ST45, which was commonly reported in North America, Australia and Europe as both MSSA and MRSA in both healthcare and community settings, was also less frequently isolated in South America, Asia and Africa [47].
The SNP-based analysis revealed that the ST1 isolates (10RN and 20RN) were indistinguishable (0 SNP differences). Interestingly, these isolates were recovered from two patients who were admitted 19 days apart to the same hospital and ward (internal medicine), suggesting ward contamination and intra-ward transmission between patients.
Similarly, all the isolates of the ST80 lineage were isolated from the same hospital, two of which (1RN and 16RN) differed by six SNPs only and were from two different patients admitted to the same ward (trauma), but 30 days apart. Isolates 2RN and 15RN, also having a six-SNP difference, were, isolated from patients admitted 45 days apart to separate wards in the same hospital. Isolates 2RN and 4RN, which differed by five SNPs, were isolated from two children admitted 15 days apart to the same ward. The identification of these genomic clusters potentially suggests a persistent contamination of the hospital by the above three clones.
On the other hand, the ST22 isolates (21RN and 25RN) differed by two SNPs; however, they were recovered 51 days apart from two different patients admitted to different hospitals. Considering that (i) the two hospitals are in close proximity (within the same catchment area), (ii) a patient’s choice of being re-admitted to a particular hospital is not restricted, (iii) patients’ health records are decentralized and (iv) inter-hospital patient transfers (for diagnostic procedure or for extra medical care) are frequent, it is therefore possible that any of the above types of patients’ movements and/or referrals between hospitals may have contributed to the dissemination of the S. aureus clones 21RN and 25RN between the two hospitals. Indeed, patient movements between healthcare facilities have been recognized as an important route of pathogen transmission [48].
The three CC15 isolates 13RN, 17RN and 18RN were also closely related, with 7-SNP differences between 13RN and 17RN and 17RN and 18RN and an 11-SNP difference between 13RN and 18RN. These three isolates were recovered from different patients admitted to different wards in the same hospital, suggesting an inter-ward transmission in the same hospital.
Irrespective of the exact mode of intra- or inter-hospital transmissions highlighted above, all the possible scenarios should be considered as breaches in infection control and prevention.
The antibiotic sensitivity testing revealed that all the S. aureus isolates exhibited susceptibility to VAN, QD (a valuable alternative to vancomycin for the treatment of MRSA infections), SXT, LZD, TEC, TGC and NIT. A similar antibiotic susceptibility profile was also reported in a Kenyan study [49].
The prevalence of vancomycin resistance varied globally from 1% in Europe, 3% in South America and 4% in North America to 5% in Asia and 16% in Africa. Similarly, the susceptibility of all our isolates to SXT was interesting, as a high resistance level to this antibiotic was reported among MRSA isolates in Latin America (up to 100%), Taiwan (89%), China (21%) and Africa (from 55% to 72%) [50].
Overall, the rate of MDR in the present study was relatively high (64%), which is consistent with previous reports from Algeria [11,51,52].
The global prevalence of PVL among MRSA strains varied remarkably between geographical regions and populations [53]. The prevalence of PVL among our MRSA isolates (29.4%) falls within the range of other studies [54]. While PVL is generally considered as a potential genetic marker for the differentiation of CA-MRSA and HA-MRSA [55,56], it was, however, equally present in CA-MRSA and HA-MRSA isolates in the present investigation, which was also consistent with a study from Uganda [57].

5. Conclusions

This study suffers from some limitations, mainly the small sample size; despite this, it provides preliminary insights into the genetic diversity and antibiotic resistance of S. aureus strains circulating in hospital settings in Algeria. To the best of our knowledge, this is the first WGS-based study that included a relatively large collection of clinical S. aureus isolates from Algeria, a country where surveillance of S. aureus has been limited thus far. Our findings stress the need for effective MRSA control and prevention strategies in the Algerian healthcare system. In addition, this work highlights the importance of WGS as a useful approach in clinical settings, as it provides high-resolution analyses of pathogens, allowing the determination of the relatedness between epidemic strains and the tracing of their transmission events.

Author Contributions

Conceptualization, M.T.G.H. and M.S.; formal analysis, R.N., A.D. (Abla Djebbar), M.E.A.B., A.D. (Arun Decano), M.T.G.H. and M.S.; funding acquisition, M.T.G.H. and M.S.; investigation, R.N., A.D. (Abla Djebbar), R.M. and M.M.; methodology, M.T.G.H. and M.S.; project administration, M.S.; supervision, M.S.; writing—original draft, R.N.; writing—review and editing, A.D. (Abla Djebbar), M.T.G.H. and M.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Algerian Ministry of Higher Education and Scientific Research (DGRSDT/MESRS) and by grants from the Wellcome Trust (098731/z/11/z to St Andrews University Bioinformatics Unit), the Chief Scientists Office (SIRN10 to M.T.G.H.), and the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care (MR/S004785/1 to M.T.G.H.); this award is also part of the EDCTP2 program supported by the European Union.

Data Availability Statement

Raw reads from Illumina sequencing generated in this study were deposited in the NCBI Sequence Read Archive (SRA) under the BioProject accession number PRJNA930663.

Acknowledgments

We thank the core sequencing and informatics team at the University of St Andrews for sequencing the isolates described in this study.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Solberg, C.O. Spread of Staphylococcus aureus in hospitals: Causes and prevention. Scand. J. Infect. Dis. 2000, 32, 587–595. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Cheung, G.Y.; Bae, J.S.; Otto, M. Pathogenicity and virulence of Staphylococcus aureus. Virulence 2021, 12, 547–569. [Google Scholar] [CrossRef] [PubMed]
  3. Lakhundi, S.; Zhang, K. Methicillin-resistant Staphylococcus aureus: Molecular characterization, evolution, and epidemiology. Clin. Microbiol. Rev. 2018, 31, e00020-18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Chen, C.J.; Huang, Y.C. New epidemiology of Staphylococcus aureus infection in Asia. Clin. Microbiol. Infect. 2014, 20, 605–623. [Google Scholar] [CrossRef] [Green Version]
  5. Köck, R.; Becker, K.; Cookson, B.; van Gemert-Pijnen, J.E.; Harbarth, S.; Kluytmans, J.A.J.W.; Mielke, M.E.; Peters, G.; Skov, R.L.; Struelens, M.J.; et al. Methicillin-resistant Staphylococcus aureus (MRSA): Burden of disease and control challenges in Europe. Eurosurveillance 2010, 15, 19688. [Google Scholar] [CrossRef] [Green Version]
  6. Borg, M.A.; de Kraker, M.; Scicluna, E.; van de Sande-Bruinsma, N.; Tiemersma, E.; Monen, J.; Grundmann, H. Prevalence of methicillin-resistant Staphylococcus aureus (MRSA) in invasive isolates from southern and eastern Mediterranean countries. J. Antimicrob. Chemother. 2007, 60, 1310–1315. [Google Scholar] [CrossRef] [Green Version]
  7. Falagas, M.E.; Karageorgopoulos, D.E.; Leptidis, J.; Korbila, I.P. MRSA in Africa: Filling the global map of antimicrobial resistance. PLoS ONE 2013, 8, e68024. [Google Scholar] [CrossRef] [Green Version]
  8. Djoudi, F.; Bonura, C.; Benallaoua, S.; Touati, A.; Touati, D.; Aleo, A.; Calà, C.; Fasciana, T.; Mammina, C. Panton-Valentine leukocidin positive sequence type 80 methicillin-resistant Staphylococcus aureus carrying a staphylococcal cassette chromosome mec type IVc is dominant in neonates and children in an Algiers hospital. New Microbiol. 2013, 36, 49–55. [Google Scholar]
  9. Antri, K.; Rouzic, N.; Dauwalder, O.; Boubekri, I.; Bes, M.; Lina, G.; Vandenesch, F.; Tazir, M.; Ramdani-Bouguessa, N.; Etienne, J. High prevalence of methicillin-resistant Staphylococcus aureus clone ST80-IV in hospital and community settings in Algiers. Clin. Microbiol. Infect. 2011, 17, 526–532. [Google Scholar] [CrossRef] [Green Version]
  10. Ramdani-Bouguessa, N.; Bes, M.; Meugnier, H.; Forey, F.; Reverdy, M.E.; Lina, G.; Vandenesch, F.; Tazir, M.; Etienne, J. Detection of methicillin-resistant Staphylococcus aureus strains resistant to multiple antibiotics and carrying the Panton-Valentine leukocidin genes in an Algiers hospital. Antimicrob. Agents Chemother. 2006, 50, 1083–1085. [Google Scholar] [CrossRef] [Green Version]
  11. Aouati, H.; Hadjadj, L.; Aouati, F.; Agabou, A.; Ben Khedher, M.; Bousseboua, H.; Bentchouala, C.; Rolain, J.M.; Diene, S.M. Emergence of methicillin-resistant Staphylococcus aureus ST239/241 SCCmec-III mercury in Eastern Algeria. Pathogens 2021, 10, 1503. [Google Scholar] [CrossRef]
  12. Zhang, K.; Sparling, J.; Chow, B.L.; Elsayed, S.; Hussain, Z.; Church, D.L.; Gregson, D.; Louie, T.J.; Conly, J.M. New quadriplex PCR assay for detection of methicillin and mupirocin resistance and simultaneous discrimination of Staphylococcus aureus from coagulase-negative staphylococci. J. Clin. Microbiol. 2004, 42, 4947–4955. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Wick, R.R.; Judd, L.M.; Gorrie, C.L.; Holt, K.E. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput. Biol. 2017, 13, e1005595. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Inouye, M.; Dashnow, H.; Raven, L.A.; Schultz, M.B.; Pope, B.J.; Tomita, T.; Zobel, J.; Holt, K.E. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med. 2014, 6, 90. [Google Scholar] [CrossRef] [Green Version]
  16. Holden, M.T.; Titball, R.W.; Peacock, S.J.; Cerdeño-Tárraga, A.M.; Atkins, T.; Crossman, L.C.; Pitt, T.; Churcher, C.M.; Mungall, K.L.; Bentley, S.D.; et al. Genomic plasticity of the causative agent of melioidosis, Burkholderia pseudomallei. Proc. Natl. Acad. Sci. USA 2004, 101, 14240–14245. [Google Scholar] [CrossRef]
  17. Page, A.J.; Cummins, C.A.; Hunt, M.; Wong, V.K.; Reuter, S.; Holden, M.T.; Fookes, M.; Falush, D.; Keane, J.A.; Parkhill, J. Roary: Rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015, 31, 3691–3693. [Google Scholar] [CrossRef] [Green Version]
  18. Croucher, N.J.; Page, A.J.; Connor, T.R.; Delaney, A.J.; Keane, J.A.; Bentley, S.D.; Parkhill, J.; Harris, S.R. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 2015, 43, e15. [Google Scholar] [CrossRef] [Green Version]
  19. Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014, 30, 1312–1313. [Google Scholar] [CrossRef] [Green Version]
  20. Kaya, H.; Hasman, H.; Larsen, J.; Stegger, M.; Johannesen, T.B.; Allesøe, R.L.; Lemvigh, C.K.; Aarestrup, F.M.; Lund, O.; Larsen, A.R. SCC mec Finder, a web-based tool for typing of staphylococcal cassette chromosome mec in Staphylococcus aureus using whole-genome sequence data. Msphere 2018, 3, e00612-17. [Google Scholar] [CrossRef] [Green Version]
  21. Bartels, M.D.; Petersen, A.; Worning, P.; Nielsen, J.B.; Larner-Svensson, H.; Johansen, H.K.; Andersen, L.P.; Jarløv, J.O.; Boye, K.; Larsen, A.R.; et al. Comparing whole-genome sequencing with Sanger sequencing for spa typing of methicillin-resistant Staphylococcus aureus. J. Clin. Microbiol. 2014, 52, 4305–4308. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Wattam, A.R.; Abraham, D.; Dalay, O.; Disz, T.L.; Driscoll, T.; Gabbard, J.L.; Gillespie, J.J.; Gough, R.; Hix, D.; Kenyon, R.; et al. PATRIC, the bacterial bioinformatics database and analysis resource. Nucleic Acids Res. 2014, 42, D581–D591. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Alcock, B.P.; Raphenya, A.R.; Lau, T.T.; Tsang, K.K.; Bouchard, M.; Edalatmand, A.; Huynh, W.; Nguyen, A.V.; Cheng, A.A.; Liu, S.; et al. CARD 2020: Antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 2020, 48, D517–D525. [Google Scholar] [CrossRef]
  24. CLSI M100; Performance Standards for Antimicrobial Susceptibility Testing, 32th ed.; CLSI supplement M100. Clinical and Laboratory Standards Institutes: Malvern, PA, USA, 2022.
  25. Comité de l’Antibiogramme de la Société Française de Microbiologie. Antibiogram Committee of the French Society of Microbiology Guidelines. Available online: https://www.sfm-microbiologie.org/wp-content/uploads/2022/06/CASFM2022_V1.0.pdf (accessed on 12 July 2022).
  26. Garner, J.S.; Jarvis, W.R.; Emori, T.G.; Horan, T.C.; Hughes, J.M. CDC definitions for nosocomial infections, 1988. Am. J. Infect. Control 1988, 16, 128–140. [Google Scholar] [CrossRef] [PubMed]
  27. Hadfield, J.; Croucher, N.J.; Goater, R.J.; Abudahab, K.; Aanensen, D.M.; Harris, S.R. Phandango: An interactive viewer for bacterial population genomics. Bioinformatics 2018, 34, 292–293. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Fluit, A.C.; Wielders, C.L.C.; Verhoef, J.; Schmitz, F.J. Epidemiology and susceptibility of 3,051 Staphylococcus aureus isolates from 25 university hospitals participating in the European SENTRY study. J. Clin. Microbiol. 2001, 39, 3727–3732. [Google Scholar] [CrossRef] [Green Version]
  29. Dulon, M.; Haamann, F.; Peters, C.; Schablon, A.; Nienhaus, A. MRSA prevalence in European healthcare settings: A review. BMC Infect. Dis. 2011, 11, 138. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Song, J.H.; Hsueh, P.R.; Chung, D.R.; Ko, K.S.; Kang, C.I.; Peck, K.R.; Yeom, J.; Kim, S.W.; Chang, H.; Kim, Y.; et al. Spread of methicillin-resistant Staphylococcus aureus between the community and the hospitals in Asian countries: An ANSORP study. J. Antimicrob. Chemother. 2011, 66, 1061–1069. [Google Scholar] [CrossRef] [Green Version]
  31. Goering, R.V.; Larsen, A.R.; Skov, R.; Tenover, F.C.; Anderson, K.L.; Dunman, P.M. Comparative genomic analysis of European and Middle Eastern community-associated methicillin-resistant Staphylococcus aureus (CC80: ST80-IV) isolates by high-density microarray. Clin. Microbiol. Infect. 2009, 15, 748–755. [Google Scholar] [CrossRef] [Green Version]
  32. Achek, R.; El-Adawy, H.; Hotzel, H.; Hendam, A.; Tomaso, H.; Ehricht, R.; Neubauer, H.K.; Nabi, I.; Hamdi, T.M.; Monecke, S. Molecular Characterization of Staphylococcus aureus Isolated from Human and Food Samples in Northern Algeria. Pathogens 2021, 10, 1276. [Google Scholar] [CrossRef]
  33. Mairi, A.; Touati, A.; Pantel, A.; Zenati, K.; Martinez, A.Y.; Dunyach-Remy, C.; Sotto, A.; Lavigne, J. Distribution of toxinogenic methicillin-resistant and methicillin-susceptible Staphylococcus aureus from different ecological niches in Algeria. Toxins 2019, 11, 500. [Google Scholar] [CrossRef] [Green Version]
  34. Herold, B.C.; Immergluck, L.C.; Maranan, M.C.; Lauderdale, D.S.; Gaskin, R.E.; Boyle-Vavra, S.; Leitch, C.; Daum, R.S. Community-acquired methicillin-resistant Staphylococcus aureus in children with no identified predisposing risk. JAMA 1998, 279, 593–598. [Google Scholar] [CrossRef] [Green Version]
  35. Otter, J.A.; French, G.L. Community-associated meticillin-resistant Staphylococcus aureus strains as a cause of healthcare-associated infection. J. Hosp. Infect. 2011, 79, 189–193. [Google Scholar] [CrossRef]
  36. Caboclo RM, F.; Cavalcante, F.S.; Iorio, N.L.P.; Schuenck, R.P.; Olendzki, A.N.; Felix, M.J.; Chamon, R.C.; dos Santos, K.R.N. Methicillin-resistant Staphylococcus aureus in Rio de Janeiro hospitals: Dissemination of the USA400/ST1 and USA800/ST5 SCCmec type IV and USA100/ST5 SCCmec type II lineages in a public institution and polyclonal presence in a private one. Am. J. Infect. Control 2013, 41, e21–e26. [Google Scholar] [CrossRef]
  37. Zhang, J.; Gu, F.F.; Zhao, S.Y.; Xiao, S.Z.; Wang, Y.C.; Guo, X.K.; Ni, Y.; Han, L.Z. Prevalence and molecular epidemiology of Staphylococcus aureus among residents of seven nursing homes in Shanghai. PLoS ONE 2015, 10, e0137593. [Google Scholar] [CrossRef] [PubMed]
  38. Kaiser-Thom, S.; Gerber, V.; Collaud, A.; Hurni, J.; Perreten, V. Prevalence and WGS-based characteristics of Staphylococcus aureus in the nasal mucosa and pastern of horses with equine pastern dermatitis. BMC Vet. Res. 2022, 18, 79. [Google Scholar] [CrossRef]
  39. Parisi, A.; Caruso, M.; Normanno, G.; Latorre, L.; Sottili, R.; Miccolupo, A.; Fraccalvieri, R.; Santagada, G. Prevalence, antimicrobial susceptibility and molecular typing of methicillin-resistant Staphylococcus aureus (MRSA) in bulk tank milk from southern Italy. Food Microbiol. 2016, 58, 36–42. [Google Scholar] [CrossRef]
  40. Carfora, V.; Giacinti, G.; Sagrafoli, D.; Marri, N.; Giangolini, G.; Alba, P.; Feltrin, F.; Sorbara, L.; Amoruso, R.; Caprioli, A.; et al. Methicillin-resistant and methicillin-susceptible Staphylococcus aureus in dairy sheep and in-contact humans: An intra-farm study. J. Dairy Sci. 2016, 99, 4251–4258. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Earls, M.R.; Kinnevey, P.M.; Brennan, G.I.; Lazaris, A.; Skally, M.; O’Connell, B.; Humphreys, H.; Shore, A.C.; Coleman, D.C. The recent emergence in hospitals of multidrug-resistant community-associated sequence type 1 and spa type t127 methicillin-resistant Staphylococcus aureus investigated by whole-genome sequencing: Implications for screening. PLoS ONE 2017, 12, e0175542. [Google Scholar] [CrossRef] [PubMed]
  42. Holden, M.T.; Hsu, L.Y.; Kurt, K.; Weinert, L.A.; Mather, A.E.; Harris, S.R.; Strommenger, B.; Layer, F.; Witte, W.; de Lencastre, H.; et al. A genomic portrait of the emergence, evolution, and global spread of a methicillin-resistant Staphylococcus aureus pandemic. Genome Res. 2013, 23, 653–664. [Google Scholar] [CrossRef] [Green Version]
  43. Hsu, L.Y.; Harris, S.R.; Chlebowicz, M.A.; Lindsay, J.A.; Koh, T.H.; Krishnan, P.; Tan, T.Y.; Hon, P.Y.; Grubb, W.; Bentley, S.D.; et al. Evolutionary dynamics of methicillin-resistant Staphylococcus aureus within a healthcare system. Genome Biol. 2015, 16, 81. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Kinnevey, P.M.; Shore, A.C.; Mac Aogáin, M.; Creamer, E.; Brennan, G.I.; Humphreys, H.; Rogers, T.R.; O’Connell, B.; Coleman, D.C. Enhanced tracking of nosocomial transmission of endemic sequence type 22 methicillin-resistant Staphylococcus aureus type IV isolates among patients and environmental sites by use of whole-genome sequencing. J. Clin. Microbiol. 2016, 54, 445–448. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Pokhrel, R.H.; Aung, M.S.; Thapa, B.; Chaudhary, R.; Mishra, S.K.; Kawaguchiya, M.; Urushibara, N.; Kobayashi, N. Detection of ST772 Panton-Valentine leukocidin-positive methicillin-resistant Staphylococcus aureus (Bengal Bay clone) and ST22 S. aureus isolates with a genetic variant of elastin binding protein in Nepal. New Microbes New Infect. 2016, 11, 20–27. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Schaumburg, F.; Alabi, A.S.; Peters, G.; Becker, K. New epidemiology of Staphylococcus aureus infection in Africa. Clin. Microbiol. Infect. 2014, 20, 589–596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Effelsberg, N.; Stegger, M.; Peitzmann, L.; Altinok, O.; Coombs, G.W.; Pichon, B.; Kearns, A.M.; Randad, P.R.; Heaney, C.D.; Bletz, S.; et al. Global epidemiology and evolutionary history of Staphylococcus aureus ST45. J. Clin. Microbiol. 2020, 59, 10–1128. [Google Scholar] [CrossRef]
  48. Donker, J.M.; van der Laan, L.; Hendriks, Y.J.; Kluytmans, J.A. Evaluation of Staphylococcus aureus nasal carriage screening before vascular surgery. PLoS ONE 2012, 7, e38127. [Google Scholar] [CrossRef]
  49. Omuse, G.; Kabera, B.; Revathi, G. Low prevalence of methicillin resistant Staphylococcus aureus as determined by an automated identification system in two private hospitals in Nairobi, Kenya: A cross sectional study. BMC Infect. Dis. 2014, 14, 669. [Google Scholar] [CrossRef] [Green Version]
  50. Coelho, C.; de Lencastre, H.; Aires-de-Sousa, M. Frequent occurrence of trimethoprim-sulfamethoxazole hetero-resistant Staphylococcus aureus isolates in different African countries. Eur. J. Clin. Microbiol. Infect. Dis. 2017, 36, 1243–1252. [Google Scholar] [CrossRef]
  51. Rebiahi, S.A.; Abdelouahid, D.E.; Rahmoun, M.; Abdelali, S.; Azzaoui, H. Emergence of vancomycin-resistant Staphylococcus aureus identified in the Tlemcen university hospital (North-West Algeria). Médecine Mal. Infect. 2011, 41, 646–651. [Google Scholar] [CrossRef]
  52. Alioua, M.A.; Labid, A.; Amoura, K.; Bertine, M.; Gacemi-Kirane, D.; Dekhil, M. Emergence of the European ST80 clone of community-associated methicillin-resistant Staphylococcus aureus as a cause of healthcare-associated infections in Eastern Algeria. Médecine Mal. Infect. 2014, 44, 180–183. [Google Scholar] [CrossRef]
  53. Bhatta, D.R.; Cavaco, L.M.; Nath, G.; Kumar, K.; Gaur, A.; Gokhale, S.; Bhatta, D.R. Association of Panton Valentine Leukocidin (PVL) genes with methicillin resistant Staphylococcus aureus (MRSA) in Western Nepal: A matter of concern for community infections (a hospital based prospective study). BMC Infect. Dis. 2016, 16, 199. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Abdulgader, S.M.; Shittu, A.O.; Nicol, M.P.; Kaba, M. Molecular epidemiology of Methicillin-resistant Staphylococcus aureus in Africa: A systematic review. Front. Microbiol. 2015, 6, 348. [Google Scholar] [CrossRef] [PubMed]
  55. Vandenesch, F.; Naimi, T.; Enright, M.C.; Lina, G.; Nimmo, G.R.; Heffernan, H.; Liassine, N.; Bes, M.; Greenland, T.; Reverdy, M.E.; et al. Community-acquired methicillin-resistant Staphylococcus aureus carrying Panton-Valentine leukocidin genes: Worldwide emergence. Emerg. Infect. Dis. 2003, 9, 978. [Google Scholar] [CrossRef] [PubMed]
  56. Boyle-Vavra, S.; Daum, R.S. Community-acquired methicillin-resistant Staphylococcus aureus: The role of Panton–Valentine leukocidin. Lab. Investig. 2007, 87, 3–9. [Google Scholar] [CrossRef] [Green Version]
  57. Kateete, D.P.; Bwanga, F.; Seni, J.; Mayanja, R.; Kigozi, E.; Mujuni, B.; Ashaba, F.K.; Baluku, H.; Najjuka, C.F.; Källander, K.; et al. CA-MRSA and HA-MRSA coexist in community and hospital settings in Uganda. Antimicrob. Resist. Infect. Control 2019, 8, 94. [Google Scholar] [CrossRef]
Figure 1. Core genome maximum likelihood phylogenetic tree of the 17 S. aureus isolates and the reference genome of the S. aureus strain MSSA476, visualized using Phandango [27]. The phylogeny tree on the left is linked to the metadata in the middle: STs, CCs, SCCmec types, Spa types (represented by various colors as indicated in the legend on the right); presence (dark blue) and absence (grey) of PVL, TSST and antibiotic resistance gene/mutation.
Figure 1. Core genome maximum likelihood phylogenetic tree of the 17 S. aureus isolates and the reference genome of the S. aureus strain MSSA476, visualized using Phandango [27]. The phylogeny tree on the left is linked to the metadata in the middle: STs, CCs, SCCmec types, Spa types (represented by various colors as indicated in the legend on the right); presence (dark blue) and absence (grey) of PVL, TSST and antibiotic resistance gene/mutation.
Microorganisms 11 02047 g001
Table 1. Patient and S. aureus isolate characteristics.
Table 1. Patient and S. aureus isolate characteristics.
IsolateMSSA/MRSAHA/CAAgeSexAdmission DateCollection DateHospitalWardSpecimen
1RNMRSAHAADF20.12.201824.12.2018ATraumaPus
2RNMRSAHACHF15.01.201920.01.2019APediatricPus
4RNMRSACACHM30.12.201831.12.2018APediatricPus
7RNMRSAHAADF17.01.201920.01.2019AEmergencyPus
9RNMSSACACHM26.02.201927.02.2019APediatricBlood
10RNMSSACAADM21.04.201922.04.2019AIMPus
13RNMSSAHAADF18.04.201921.04.2019AIMCSF
14RNMRSACACHM22.01.201923.01.2019APediatricPus
15RNMRSACAADF28.11.201829.11.2018AEmergencyPus
16RNMRSACAADM21.01.201922.01.2019ATraumaPus
17RNMSSAHACHF11.02.201924.02.2019APediatricPus
18RNMSSAHAADF14.02.201925.02.2019AEmergencyPus
19RNMSSACAADM13.03.201914.03.2019BENTPus
20RNMSSAHAADM09.05.201913.05.2019AIMPus
21RNMSSAHAADF09.05.201913.05.2019AIMPus
25RNMSSAHAADF21.03.201924.03.2019BIMPus
29RNMSSAHAADM23.04.201929.04.2019AIMPus
MRSA: Methicillin-Resistant S. aureus; MSSA: Methicillin-Susceptible S. aureus; CA: Community-Associated; HA: Healthcare-Associated; AD: Adult; CH: Child; F: Female; M: Male; IM: Internal Medicine; ENT: Ear, Nose and Throat; CSF: Cerebrospinal Fluid.
Table 2. Phenotypic antimicrobial resistance profiles of the S. aureus isolates.
Table 2. Phenotypic antimicrobial resistance profiles of the S. aureus isolates.
IsolateMIC (μg/mL)Inhibition Zone Diameters (mm)
LVXMXFERYCLINQDLZDTECVANTETTGCNITSXTCHLGENAMKKANFOXCIPOFXFUSRIFMDR
1RNSSRRSSSSRSSSSSRRRIRRSY
2RNSSSSSSSSSSSSSSRRRRSRSY
4RNSSRRSSSSSSSSSRRRRIRSRY
7RNSSRRSSSSRSSSSSSRRSSSSY
9RNSSRRSSSSSSSSSSSSSSSRSY
10RNSSSSSSSSSSSSSSSSSISSIN
13RNSSRRSSSSRSSSSRRRSRSSIY
14RNSSSSSSSSSSSSSSIIRSSSSN
15RNSSSSSSSSSSSSSSRRRSSSSN
16RNSSRRSSSSRSSSSRRIRIRRSY
17RNSSRRSSSSRSSSSSRRSRRSSY
18RNSSRRSSSSRSSSRSRRSISRSY
19RNSSRRSSSSSSISSSSSSIRSRY
20RNSSSSSSSSSSSSSSRRSRRRSY
21RNSSSSSSSSSSSSSSSSSSSSSN
25RNSSSSSSSSSSSSSSSSSSSRSN
29RNISSSSSSSSSSSSSSSSSSRSN
Total
n00990000600013997468211
(%)(0%)(0%)(53%)(53%)(0%)(0%)(0%)(0%)(35%)(0%)(0%)(0%)(5.9%)(17.6%)(53%)(53%)(41.2%)(23.5%)(35%)(47%)(11.7%)(64.7%)
MIC: Minimum Inhibitory Concentration (μg/mL); n: Number; R: Resistant; I: Intermediate; S: Susceptible; MDR: Multidrug Resistance; Y: Yes; N: No; AMK: Amikacin; CHL: Chloramphenicol; CIP: Ciprofloxacin; CLIN: Clindamycin; ERY: Erythromycin; FOX: Cefoxitin; FUS: Fusidic Acid; GEN: Gentamycin; KAN: Kanamycin; LVX: Levofloxacin; LZD: Linezolid; MXF: Moxifloxacin; NIT: Nitrofrurantoin; OFX: Ofloxacin; QD: Quinupristin/Dalfopristin; RIF: Rifamycin; SXT: Trimethroprim/Sulfamethoxazole; TEC: Teicoplanin; TET: Tetracycline; TGC: Tigecyclin; VAN: Vancomycin.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Namoune, R.; Djebbar, A.; Mekler, R.; McHugh, M.; Bekara, M.E.A.; Decano, A.; Holden, M.T.G.; Sebaihia, M. Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria. Microorganisms 2023, 11, 2047. https://doi.org/10.3390/microorganisms11082047

AMA Style

Namoune R, Djebbar A, Mekler R, McHugh M, Bekara MEA, Decano A, Holden MTG, Sebaihia M. Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria. Microorganisms. 2023; 11(8):2047. https://doi.org/10.3390/microorganisms11082047

Chicago/Turabian Style

Namoune, Rachida, Abla Djebbar, Rebecca Mekler, Martin McHugh, Mohammed El Amine Bekara, Arun Decano, Matthew T. G. Holden, and Mohammed Sebaihia. 2023. "Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria" Microorganisms 11, no. 8: 2047. https://doi.org/10.3390/microorganisms11082047

APA Style

Namoune, R., Djebbar, A., Mekler, R., McHugh, M., Bekara, M. E. A., Decano, A., Holden, M. T. G., & Sebaihia, M. (2023). Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria. Microorganisms, 11(8), 2047. https://doi.org/10.3390/microorganisms11082047

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop