{"id":33475,"date":"2020-06-25T11:08:39","date_gmt":"2020-06-25T11:08:39","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=33475"},"modified":"2020-07-06T10:16:17","modified_gmt":"2020-07-06T10:16:17","slug":"molecular-characterization-of-methicillin-resistant-and-methicillin-susceptible-staphylococcus-aureusisolates-obtained-from-human-skin-samples-in-iraq","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol13no2\/molecular-characterization-of-methicillin-resistant-and-methicillin-susceptible-staphylococcus-aureusisolates-obtained-from-human-skin-samples-in-iraq\/","title":{"rendered":"Molecular Characterization of Methicillin-Resistant and Methicillin- Susceptible Staphylococcus aureus Isolates Obtained from Human-Skin Samples in Iraq"},"content":{"rendered":"

Introduction <\/strong><\/p>\n

Staphylococci <\/em>are ubiquitous, including a dozen species occurring as part of the normal flora. The most virulent species is Staphylococcus aureus<\/em>, which colonizes epithelial surfaces and causes infections in humans. Historically, Methicillin has been the treatment of choice for the S. aureus<\/em> infections, but resistance is now widespread. It is believed that this resistance is related to the mec A<\/em>genes, which are carried on mobile genetic elements, and can confer resistance to most beta-lactam antibiotics and other antimicrobial classes [1,2, 3, 4]. All staphylococcal genomes are approximately 2.8 Mbp in size, and are, thus predicted to encode 2500 genes with relatively low G-C content. The comparative analysis has revealed that most regions of the genome are well-conserved; however, several large sequence blocks showed high variability.<\/p>\n

Lindsay and Holden first posited the concept of the \u2018core\u2019; the part of the genome that is present in all strains of S. aureus<\/em>, in contrast to the “accessory genome” which is variable [5,6]. The core contains housekeeping genes and many virulence genes. Its genetic plasticity facilitates the evolution of many virulent and drug-resistant strains, presenting a major clinical challenge (Holden et al.,<\/em> 2004). Most of the dissimilarity among the species of the strains is due to mobile genetic elements, such as bacteriophages or pathogenicity islands [7, 8, 9].<\/p>\n

Gene transfer amongthe S. aureus<\/em> strains is certainly much higher than among different staphylococcal species [10].<\/p>\n

The RAPD technique makesthe study of a large proportion of target genomes possible by generating distinct banding patterns that allow for finer discrimination among the strains [11, 12]. It amplifies segments of target DNA using small arbitrary primers of unknown homology with a target sequence.<\/p>\n

The number and size of the fragments generated during PCR are the basis for typing an isolate [13, 14, 15].\u00a0This work seeks to apply RAPD-PCR extensively to determine the relatedness and genomic variability of a collection of methicillin-susceptible (MSSA) and methicillin-resistant (MRSA) S. aureus<\/em>strains, and thus analyse their diversity.<\/p>\n

Materials and Methods<\/strong><\/p>\n

Isolation of Bacterial Strains and Molecular Detection using the Polymerase Chain Reaction (PCR<\/strong>)<\/p>\n

The study included 100 local isolates of Staphyloccoci spp. <\/em>collected from different clinical skin infections in unrelated patients. All isolates were grown at 37\u00a0\u00b0C on a mannitol salt agar (MSA) medium and were identified at the species level using their morphological characteristics and biochemical tests [16]. For the molecular determination, the MRSA and MSSA genomic DNA was extracted from the staphylococcal cultures via a heat shock\/boiled-cell method that involved boiling and freeze-thawing processes as described elsewhere [17, 18, 19]. The application of the RAPD technique was preceded by the extraction of genomic DNA using the boiling method. The mecA<\/em> gene was amplified to identify the MRSA strains without the need to check for antibiotic susceptibility, as discussed by Tang and Stratton, who suggested that the specificity of MRSA identification is based on the quantitative correlation of the mecA<\/em> gene; this gene encodes the protein PBP2A (penicillin binding protein\u00a02A), which has a low affinity for beta-lactam antibiotics such as\u00a0methicillin). Therefore, this assay allows for a reliable identification within only six hours of sample collection.<\/p>\n

The application of the RAPD technique was preceded by the extraction of genomic DNA using the boiling method. The mecA<\/em> gene was amplified to identify the MRSA strains without the need to check for antibiotic susceptibility, as discussed by Tang and Stratton, who suggested that the specificity of MRSA identification is based on the quantitative correlation of the mecA<\/em> gene; this gene encodes the protein PBP2A (penicillin binding protein\u00a02A), which has a low affinity for beta-lactam antibiotics such as\u00a0methicillin). Therefore, this assay allows for a reliable identification within only six hours of sample collection.<\/p>\n

The purity of the extracted DNA was checked in a NanoDrop (Thermo Scientific) at the wavelengths of A260 and A280. A specificmec<\/em>A -PCR primers with anamplicon size of 533bp was subjected to forward (mec<\/em>A: F 5\u2032- AAAATCGATGGTAAAGGTTGGCAG-3\u2032) and reverse (mec<\/em>A: R 5\u2032- AGTTCTGCAGTACCGGATTTGC-3\u2032) supplied by Integrated DNA Technologies company, Canada . The amplification program was one cycle at 94 \u00b0C for one minute; thirty-five cycles of 94 \u00b0C for one minute, 63 \u00b0C for one minute, 72 \u00b0C for one minute and 72 \u00b0C for ten minutes, using the Mastercycler (Eppendorf). The amplified product was subjected to 2% agarose gel electrophoresis and was visualized under UV (Imagemaster VDS, Pharmacia Biotech, USA) after being stained with Ethidium bromide [20]. Only twenty samples were subjected to the RAPD assay after being molecularly detected as either methicillin-resistant and methicillin-sensitive strains (ten samples were mec<\/em> negative=MSSA and ten were mec<\/em> positive= MRSA) [21].<\/p>\n

Random Amplified Polymorphic DNA: Reaction Mix, Program, and Detection<\/strong><\/p>\n

All isolates from samples in this research were subjected to identification at the species level using their morphological characteristics and biochemical tests; all isolates were confirmed as S. aureus. The processes of DNA amplification were performed using the mecA gene to detect the Methicillin-resistant strains.The RAPD assay was conducted twice under the same conditions to confirm the reproducibility of the method and to eliminate sporadic amplification products from the analysis.\u00a0<\/strong><\/p>\n

The RAPD primers used in the studywere as follows: OPI \u2013 06: (5\u2019<\/sup>– AAGGCGGCAG-3\u2019<\/sup>), OPJ-13: (5\u2019<\/sup>-CCACACTACC-3\u2019<\/sup>), OPE-16: (5\u2019<\/sup>– GGTGACTGTT-3\u2019<\/sup>), OPQ-01: (5\u2019<\/sup>-GGGACGATGG-3\u2019<\/sup>), OPM-20: (5\u2019<\/sup>– AGGTCTTGGG-3\u2019<\/sup>), OPN-07: (5\u2019<\/sup>-CAGCCCAGAG-3\u2019<\/sup>), OPQ-17: (5\u2019<\/sup>– GAAGCCCTTG-3\u2019<\/sup>), OPD-20: (5\u2019<\/sup>-ACCCGGTCAC-3\u2019<\/sup>), OPB-14: (5\u2019<\/sup>– TCCGCTCTGG-3\u2019<\/sup>), and OPA-11: (5\u2019<\/sup>-ACCCGACCTG-3\u2019<\/sup>) (Primer set supplied by OPT (Operon DNA Technologies Company, Canada). The reaction was conducted in a 25 \u03bcl reaction mixture containing 2 \u03bcl of DNA (50 ng), 12.5 \u03bclGoTaq 0T<\/em>\u00ae Green <\/em>Master (Promega, CA), (0.5 \u03bcl) 25 mM MgCl2<\/sub>, 2 \u03bcl of (10 Pmol\\ \u03bcl) of each primer, 2 \u03bcl of deionized and distilled water.The PCR amplifications were performed in a Labnet Thermal Cycler with the following specification: first,a denaturation cycle at 94 \u00baC for five minutes; forty-five cycles (segment denaturation 94 \u00baC for forty-five seconds; annealing 40 \u00baC for one minute; extension 72 \u00baC for forty-five seconds), and then a final extension comprised of one cycle at 72 \u00baC for seven minutes according to Kumar and Gurusubramanian [22, 23, 24].<\/p>\n

The amplified products were analysed by electrophoresis in a 1.5% (w\/v) agarose gel and were visualized under UV (Imagemaster VDS, Pharmacia Biotech, USA) after being stained with ethidium bromide (Kumari and Thakur, 2014). A DNA ladder (250 bp) purchased from BIONEER Co. was used to assess the size of the PCR product, which was, then, photographed using a gel documentation system.<\/p>\n

Statistical Efficiency Discrimination <\/strong><\/p>\n

\u00a0<\/strong>RAPD fragments were scored as (0, 1) where 1 means presence and 0 denotes the absence of a band at a specific position in the gel. The binary patterns obtained were directly compared for their similarities using the NTSYS-pc Numerical Taxonomy and Multivariate Analysis System (version 2.1, Exeter Software) as described by Kosman and Leonard [25, 26]. The data collected were analysed, and only the major bands that were consistently amplified were recorded. The polymorphism of each primer was calculated based on the following equation:<\/p>\n

Polymorphism% = (Np\/Nt) \u00d7100<\/p>\n

Where Nprefers to the number of the polymorphic bands, and Nt reflects the total number of bands of the same primer [27]. The efficiency and discriminatory powers of each primer were calculated. Primer efficiency was calculated as the number of polymorphic bands to the total number of primer bands. The discriminatory power of each primer was calculated as the percentage of the number of polymorphic bands to all of the primers [28, 29].<\/p>\n

Genetic Distance and Relationship Estimation<\/strong><\/p>\n

Phylogenetic analysis and pairwise alignment similarities were calculated via the neighbour-joining method. The genetic distances among all pairs were calculated based on Nei and Li\u2019s similarity indices (Nei and Li, 1979) according to the following formula:<\/p>\n

G.D= 1-{2Nab\/(Na+Nb}<\/p>\n

Where Na is the total number of the fragments observed in individual \u2018a\u2019; Nbisthe total number of fragments \u2018b\u2019 and Nab is the number of fragments shared by both individuals. Genetic relationship tree diagrams were developed to illustrate the relationships among the studied strains. The similarity was calculated based on the following formula [30, 31]\n

Similarity = 1- G.D\u00d7 100%<\/p>\n

Results\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/strong><\/p>\n

The results were analysed using band notes obtained from the PIC of primers,as illustrated in Figure 2,which included the presence or absence of bands, together with their molecular weights that were produced by a primer across the twenty samples starting from the highest to lowest weight, as well as the total number of the amplified bands across all isolates. The bands obtained had a pattern similar to a bar code, allowing for the identification of each individual. In total, 142 bands were generated per the ten primers, of which 141 ranged between 3100 and 100 bp.<\/p>\n\n\n\n
\"Figure<\/td>\nFigure<\/strong> \u00a01: DNA fragments generated by specific PCR amplification\u00a0<\/strong>for the detection of MRSA strains.<\/strong><\/p>\n

Click here to View Figure<\/span><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n\n\n\n
\"Figure<\/td>\nFigure 2: MRSA primer figures, including the ten primers to the left side starting<\/strong><\/p>\n

Click here to View Figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

The average number of bands per primer was 14. Primers OPJ-13 and OPE-16 exhibited the most bands (20) with a 100% polymorphism, and these also had the greatest discriminatory index power (DI, 14.1). Primer OPI-06 produced the smallest number of bands (10) and had the least discriminatory power (DI, 7.09). The differences in the molecular weights of the bands reflected the number of targets for each primer site within the DNA in question. The names and sequences of the commercially-synthesized primers used to generate the PCR products (Operon Technologies, USA) along with a summary of the total number of bands and polymorphic fragments are listed in Table 1.<\/p>\n

Table 1: Fragments Amplified by the Primers in the Twenty S. aureus<\/em> Isolates and the % Efficiency of Amplification and Discriminatory Power<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u00a0<\/strong>Primer Name<\/strong><\/td>\n\u00a0<\/strong>Sequences (5\u2019<\/sup>– 3\u2019<\/sup>)<\/strong><\/td>\nNumber of Bands Amplified in both Strains<\/strong><\/td>\n\u00a0<\/strong><\/p>\n

Polymorphism<\/strong><\/p>\n

(%)<\/strong><\/td>\n

Primer Efficiency<\/strong><\/p>\n

(%)<\/strong><\/td>\n

Primer Discriminatory Power (%)<\/strong><\/td>\n<\/tr>\n
Total <\/strong><\/td>\npolymorphic<\/strong><\/td>\n<\/tr>\n
OPI – 06<\/td>\nAAGGCGGCAG<\/td>\n10<\/td>\n10<\/td>\n100<\/td>\n7.04<\/td>\n7.09<\/td>\n<\/tr>\n
OPJ-13<\/td>\nCCACACTACC<\/td>\n20<\/td>\n20<\/td>\n100<\/td>\n14<\/td>\n14.1<\/td>\n<\/tr>\n
OPE-16<\/td>\nGGTGACTGTT<\/td>\n20<\/td>\n20<\/td>\n100<\/td>\n14<\/td>\n14.1<\/td>\n<\/tr>\n
OPQ-01<\/td>\nGGGACGATGG<\/td>\n16<\/td>\n16<\/td>\n100<\/td>\n11.2<\/td>\n11.3<\/td>\n<\/tr>\n
OPM-20<\/td>\nAGGTCTTGGG<\/td>\n14<\/td>\n14<\/td>\n100<\/td>\n9.8<\/td>\n9.9<\/td>\n<\/tr>\n
OPN-07<\/td>\nCAGCCCAGAG<\/td>\n13<\/td>\n13<\/td>\n100<\/td>\n9.1<\/td>\n9.2<\/td>\n<\/tr>\n
OPQ-17<\/td>\nGAAGCCCTTG<\/td>\n11<\/td>\n11<\/td>\n100<\/td>\n7.7<\/td>\n7.8<\/td>\n<\/tr>\n
OPD-20<\/td>\nACCCGGTCAC<\/td>\n11<\/td>\n10<\/td>\n90.9<\/td>\n7.04<\/td>\n7.09<\/td>\n<\/tr>\n
OPB-14<\/td>\nTCCGCTCTGG<\/td>\n12<\/td>\n12<\/td>\n100<\/td>\n8.4<\/td>\n8.5<\/td>\n<\/tr>\n
OPA-11<\/td>\nACCCGACCTG<\/td>\n15<\/td>\n15<\/td>\n100<\/td>\n10.5<\/td>\n10.6<\/td>\n<\/tr>\n
Total<\/td>\n10<\/td>\n142<\/td>\n141<\/td>\n99.1<\/td>\n–<\/td>\n–<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

In respect to the percentage of polymorphism, a unique band means that the band is present in just one individual and absent in the others (as in the underlined primer OPD-20).The discriminatory index (DI) reflects the likelihood of unrelated isolates being classified as the same type. According to recent guidelines, a typing system should have DI >0.95 for a reliable assessment of the clonal relatedness of the isolates.<\/p>\n

Analysis Of Genetic Distance<\/strong><\/p>\n

The inter-group distance is the average of the paired distances of members from both groups. The similarity measures given took values ranging from zero to unity. For identical genotypes s<\/em>= 1, while for completely distinct measures s <\/em>= 0. Depending onshared bands between MRSA and MSSA,the increase in bands led to a decrease inthe genetic distance, and vice versa. Table\u00a02 illustrates the values of genetic distance. The highest similarity was obtained between strainsnumbers \u201811\u2019 and \u201812\u2019, while the lowest level was obtained between strainsnumbers \u20184\u2019(MRSA) and \u201814\u2019(MSSA).<\/p>\n

Table 2:\u00a0Genetic distance of Both MRSA and MSSA Strains<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 1.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 2.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 3.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 4.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 5.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 6.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 7.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 8.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 9.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 10.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 11.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 12.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 13.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 14.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 15.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 16.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 17.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 18.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 19.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 20.<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
1\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
2.\u00a0 0.32384\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
3.\u00a0 0.56972\u00a0\u00a0 0.28742\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
4.\u00a0 0.52774\u00a0\u00a0 0.56390\u00a0\u00a0 0.42629\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
5.\u00a0 0.56573\u00a0\u00a0 0.55933\u00a0\u00a0 0.66907\u00a0\u00a0 0.41748\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
6.\u00a0 0.72791\u00a0\u00a0 0.58175\u00a0\u00a0 0.45033\u00a0\u00a0 0.48715\u00a0\u00a0 0.49340\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
7. 0.50461\u00a0\u00a0 0.54077\u00a0\u00a0 0.49205\u00a0\u00a0 0.34082\u00a0\u00a0 0.55470\u00a0\u00a0 0.56185\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
8.\u00a0 0.75204\u00a0\u00a0 0.73941\u00a0\u00a0 0.67117\u00a0\u00a0 0.88891\u00a0\u00a0 0.81568\u00a0\u00a0 0.60448\u00a0\u00a0 0.60125\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
9. 0.61871\u00a0\u00a0 0.80902\u00a0\u00a0 0.72639\u00a0\u00a0 0.86500\u00a0\u00a0 0.63106\u00a0\u00a0 0.66304\u00a0\u00a0 0.63931\u00a0\u00a0 0.35483\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
10. 0.72499\u00a0\u00a0 0.67018\u00a0\u00a0 0.49620\u00a0\u00a0 0.60837\u00a0\u00a0 0.56298\u00a0\u00a0 0.53091\u00a0\u00a0 0.51379\u00a0\u00a0 0.46111\u00a0\u00a0 0.44803\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
11. 0.84059\u00a0\u00a0 0.78974\u00a0\u00a0 0.73243\u00a0\u00a0 0.86146\u00a0\u00a0 0.68588\u00a0\u00a0 0.50066\u00a0\u00a0 0.78511\u00a0\u00a0 0.69469\u00a0\u00a0 0.64789\u00a0\u00a0 0.64497\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
12. 0.80057\u00a0\u00a0 0.79228\u00a0\u00a0 0.77245\u00a0\u00a0 0.99901\u00a0\u00a0 0.68508\u00a0\u00a0 0.65301\u00a0\u00a0 0.82513\u00a0\u00a0 0.77245\u00a0\u00a0 0.68791\u00a0\u00a0 0.64004\u00a0\u00a0 0.18312 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
13. 0.72182\u00a0\u00a0 0.75798\u00a0\u00a0 0.82327\u00a0\u00a0 0.82971\u00a0\u00a0 0.65413\u00a0\u00a0 0.57426\u00a0\u00a0 0.75335\u00a0\u00a0 0.86773\u00a0\u00a0 0.69618\u00a0\u00a0 0.68467\u00a0\u00a0 0.31399\u00a0\u00a0 0.21079\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
14. 0.86348\u00a0\u00a0 0.76611\u00a0\u00a0 0.78884\u00a0\u00a0 0.999110.82931\u00a0\u00a0 0.63955\u00a0\u00a0 0.72374\u00a0\u00a0 0.92238\u00a0\u00a0 0.74687\u00a0\u00a0 0.69280\u00a0\u00a0 0.30061\u00a0\u00a0 0.21892\u00a0\u00a0 0.24780\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
15. 0.74262\u00a0\u00a0 0.70182\u00a0\u00a0 0.76229\u00a0\u00a0 0.84480\u00a0\u00a0 0.67800\u00a0\u00a0 0.50583\u00a0\u00a0 0.85419\u00a0\u00a0 0.80151\u00a0\u00a0 0.67775\u00a0\u00a0 0.70992\u00a0\u00a0 0.35410\u00a0\u00a0 0.25220\u00a0\u00a0 0.22125\u00a0\u00a0 0.26860\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
16. 0.75171\u00a0\u00a0 0.67867\u00a0\u00a0 0.73649\u00a0\u00a0 0.76528\u00a0\u00a0 0.72632\u00a0\u00a0 0.48352\u00a0\u00a0 0.65564\u00a0\u00a0 0.81060\u00a0\u00a0 0.89312\u00a0\u00a0 0.62470\u00a0\u00a0 0.40241\u00a0\u00a0 0.30052\u00a0\u00a0 0.23182\u00a0\u00a0 0.25864\u00a0\u00a0 0.20488 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
17. 0.91697\u00a0\u00a0 0.90661\u00a0\u00a0 0.84233\u00a0\u00a0 0.99141\u00a0\u00a0 0.75496\u00a0\u00a0 0.50583\u00a0\u00a0 0.77723\u00a0\u00a0 0.80151\u00a0\u00a0 0.71697\u00a0\u00a0 0.60814\u00a0\u00a0 0.31243\u00a0\u00a0 0.21298\u00a0\u00a0 0.22125\u00a0\u00a0 0.19164\u00a0\u00a0 0.24512\u00a0\u00a0 0.22198\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
18. 0.82496\u00a0\u00a0 0.77411\u00a0\u00a0 0.75602\u00a0\u00a0 0.79932\u00a0\u00a0 0.79286\u00a0\u00a0 0.53633\u00a0\u00a0 0.84953\u00a0\u00a0 0.75602\u00a0\u00a0 0.89463\u00a0\u00a0 0.77777\u00a0\u00a0 0.37457\u00a0\u00a0 0.31208\u00a0\u00a0 0.27686\u00a0\u00a0 0.28499\u00a0\u00a0 0.29680\u00a0\u00a0 0.22960\u00a0\u00a0 0.27660\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
19. 0.80377\u00a0\u00a0 0.71733\u00a0\u00a0 0.74006\u00a0\u00a0 0.73557\u00a0\u00a0 0.69352\u00a0\u00a0 0.55959\u00a0\u00a0 0.83196\u00a0\u00a0 0.77928\u00a0\u00a0 0.69474\u00a0\u00a0 0.72406\u00a0\u00a0 0.37536\u00a0\u00a0 0.27080\u00a0\u00a0 0.21844\u00a0\u00a0 0.28719\u00a0\u00a0 0.24159\u00a0\u00a0 0.30895\u00a0\u00a0 0.29986\u00a0\u00a0 0.21515\u00a0\u00a0 0.00000<\/td>\n<\/td>\n<\/tr>\n
20. 0.68913\u00a0\u00a0 0.72529\u00a0\u00a0 0.78884\u00a0\u00a0 0.88663\u00a0\u00a0 0.70148\u00a0\u00a0 0.58239\u00a0\u00a0 0.88408\u00a0\u00a0 0.70880\u00a0\u00a0 0.62426\u00a0\u00a0 0.69280\u00a0\u00a0 0.23874\u00a0\u00a0 0.19872\u00a0\u00a0 0.24780\u00a0\u00a0 0.29849\u00a0\u00a0 0.24879\u00a0\u00a0 0.33711\u00a0\u00a0 0.28880\u00a0\u00a0 0.26393\u00a0\u00a0 0.22657\u00a0\u00a0 0.00000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n


\nCluster Analysis of RAPD<\/strong><\/p>\n

Cluster analysis was conducted using the unweighted pair-group method, in which the samples were grouped based on similarity to construct a dendrogram. Strikingly, the twenty S. aureus<\/em> isolates formed two distinct groups (Fig. 3). All MRSA strain isolates were mapped to the upper group in the phylogenetic tree. Major Cluster, I included three main groups. The first of these groups contained two sub-clusters; one contained isolate C1 and the other contained isolates C2 and C3. The second group also contained two sub-clusters; one included isolates C4 and C7 and the other included isolates C5 and C6. Likewise, there were two sub-clusters in the third group with the first cluster containing isolates C8 and C9 and the second containing isolate C10.<\/p>\n\n\n\n
\"Figure<\/td>\nFigure 3: Genetic Relationships of MRSA and MSSA Strains Illustrated in a dendrogram.<\/strong><\/span><\/p>\n

Click here to View Figure<\/span><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The second major cluster (Cluster II) represents the MSSA strains and\u00a0 included three main groups. The first group contained two sub-clusters; one contained isolates C11 and C12 and the other contained isolate C20. The second group also included two sub-clusters. The first of these contained only isolate C13, and the second contained isolates C15 and C16. The second sub-cluster, meanwhile, contained isolates C14 and C17. The third group contained only one sub-cluster which included two isolates, C18 and C19.<\/p>\n

Discussion<\/strong><\/p>\n

The taxonomy of a genus is traditionally based on morphological characteristics, but there are significant difficulties in distinguishing the closelyrelated groups such as the populations or strains of the same species. New techniques using molecular markers, however, now allow for much easier identification of such strains [32, 33].<\/p>\n

One of these techniques is RAPD-PCR, which depends on the amplification of DNA fragments with a single arbitrary primer resulting in the generation of amplified products that represent a multiplicity of anonymous sites that are characteristic of the studied genome [34, 35]. This method is widely recognized as a highly discriminatory tool for the molecular typing of a wide range of bacteria, due to its ability to determine polymorphisms in the entire bacterial genome [36].<\/p>\n

The advantage of this technique is that markers are targeted to a much smaller locus within the genome, and the likelihood of identifying false positive markers is small; therefore, the RAPD analysis has been widely used for taxonomic and phylogenetic studies, for species differentiation, and for the study of phylo-geographic patterns of genetic variations [37, 38]. Furthermore, it requires only small amounts of DNA. Compared to other methods, it is simpler, very sensitive, cheaper, faster and less labour-intensive [39, 40, 41]. It can detect rearrangements, additions, or deletions of DNA by visualizing banding shifts, missing bands or the appearance of new bands [42].<\/p>\n

The failure of some primers to amplify DNA may be attributed to their need for special requirements in terms of PCR-reagents or temperature profile since all\u00a0 reaction parameters were identical for all primers. The G+C content of a primer may further interfere with the PCR yield. The RAPD markers developed independently were soon used for linkage mapping and the detection of relatedness among species [43].<\/p>\n

These markers were the simplest (as they do not require prior knowledge of the target sequences for their design), and they are less expensive and fast. In addition, these markers exhibit reasonable efficiency compared with other methods. They can anneal and prime at multiple locations throughout the genome, producing a spectrum of amplification products that are characteristic of the template [44]. Ozbeyet al<\/em>. (2004) stated that using different RAPD primers increases the differentiation power of the process. If RAPD markers are used to detect polymorphisms and genetic relationships, as in the present work, a large number of primers is recommended to make the chance of producing monomorphic bands over the species tested [45].<\/p>\n

In this study the differences in the RAPD profiles obtained with almost all primers revealed the presence of a great genetic heterogeneity between both strains, allowing the researchers to demonstrate the technique\u2019s ability to differentiate strains at the intra-specific level. The strategy for identifying the methicillin-resistant strains among S. aureus<\/em> in this study agreed with that of Ozbeyet al<\/em>.<\/em> (2004),<\/em> who maintained that the RAPD analysis has been applied to identify the strains belonging to the same species.<\/p>\n

Historically, S. aureus<\/em>has been described as a variable bacterium with many pathogenic and antibiotic-resistance variants [9]. Several studies have provided evidence that MRSA strains have evolved in a relatively small number of lineages that are clonally-related, and that some MRSA strains are present in distant lineages. This has led to the prediction that the presence of the mecA<\/em>gene in such widely divergent lineages is the consequence of the horizontal transfer of the mec<\/em>region into related S. aureus<\/em>chromosomal backgrounds, proving that the MRSA strains have evolved several times independently [42]. Our cluster analysis is compatible with Branger\u2019s hypothesis; it demonstrates that MSSA and MRSA genomic groups are distantrelated. In Branger et al<\/em>., the coefficient of relatedness did not exceed 45%, while in this study the coefficient was 40% with degree-interrelatedness (only 15).<\/p>\n

The reasons behind the progressive development of genotypic strategies were the shortcomings in the previous phonotypical methods. Accordingly, RAPD has been proposed as the method of choice for typing S. aureus<\/em>isolates and is considered as one of the most reproducible and discriminatory techniques [46].Using appropriate statistical analysis is very important to make definitive identifications of genetic variation. RAPD subtyping approaches can provide useful epidemiological information regarding antibiotic resistance.<\/p>\n

Conclusion<\/strong><\/p>\n

In this study, the DNA-based assays (both RAPD and conventional PCR) have provided a rapid method for the detection and characterization of methicillin-resistant Staphylococcus aureus<\/em>(MRSA). The RAPD technique allows larger proportions of the genomes to be studied in the generation of the banding pattern, leading to finer discrimination among strains. This analysis has detected the genetic variation revealing that the analyzed S. aureus<\/em>isolates were divided into two distinct groups of the same species, methicillin- susceptible and methicillin-resistant strains.<\/p>\n

References<\/strong><\/p>\n

    \n
  1. Cornelissen C.N., Fisher B. D., and Harvey R. A., Lippincott’s Illustrated Reviews, Microbiology, 3rd Edition, 2013, Lippincott Williams & Wilkins, Tokyo, Japan.<\/li>\n
  2. Nouri, M. A., Al-Halbosiy, M. M. F., Dheeb, B. I. and Hashim, A. J., Cytotoxicity and genotoxicity of gliotoxin on human lymphocytes in vitro, 2015, Journal of K S U \u2013 Science. 27, 193\u2013197.<\/li>\n
  3. Himsworth Ch. G., Miller R. R., Montoya V., Hoang L., Romney M. G., Al-Rawahi G. N., Kerr T., Jardine C. M., Patrick D. M., Tang P., Weese J. S., Carriage of Methicillin-Resistant Staphylococcus aureus<\/em> by Wild Urban Norway Rats (Rattusnorvegicus), of Plos One<\/em>. 2014, 9 (2): 1-9.<\/li>\n
  4. El-Hilali F, El-Hilali H, Dheeb BI, Traore BM, Messouak M, Mazouz H, Moumni M, Belgacem FBM, and El-Mowafy AM., Blood Transfusion Utility During Cardiopulmonary Bypass and Correlation with Key-Biochemical Laboratory Findings: A New Approach to Identify Preventive and Risk Factors (1-Year Practice at University Hospital Hassan-II of Fez), Biochem Anal Biochem 2016, 5:3 DOI: 10.4172\/2161-1009.1000290<\/li>\n
  5. Al-Tekreeti AR, Al-Halbosiy MMF, Dheeb BI, Hashim AJ, Al-Zuhairi AFH., Molecular identification of clinical Candida isolates by simple and randomly amplified polymorphic DNA-PCR, Arab J SciEng, 2017, DOI 10.1007\/s13369-017-2762-1.<\/strong><\/li>\n
  6. Hussain, A. F., Sulaiman, G. M., Dheeb, B. I., Hashim, A. J. and Seddiq, S. H., Improvingconditions for gliotoxin production by local isolates of Aspergillusfumigatus<\/em>, Journal ofbiotechnology research center, 2017, 11(2):14-24.<\/li>\n
  7. Lindsay J A and Holden MT. Staphylococcus aureus: superbug, super genome? Trend Microbiol., 2004: 12 (8): 378- 385.<\/li>\n
  8. Rassin, N. K., Nemat J. A, Dheeb, B. I., Molecular Identification of Aspergillusfumigatus<\/em> Using ISSR and RAPD Markers, Iraqi Journal of Science<\/em>, 2015, 56 (4A), 2788-2797.<\/li>\n
  9. Baba T., Bae T., Schneewind O., Takeuchi F. and Hiramatsu K., Genome Sequence of Staphylococcus aureus<\/em>Strain Newman and Comparative Analysis of Staphylococcal Genomes: Polymorphism and Evolution of Two Major Pathogenicity Islands, of Bacteriol. <\/em>2008, 190(1):300-310.<\/li>\n
  10. Ibrahim, I. M., Iftikhar, M., Ali, I. M., Dheeb, B. I., Abbas, Q. A., Ramizy, A., Eisa, M. H. andAljameel, A. I., Antifungal activity of wide band gap Thioglycolic acid capped ZnS:Mnsemiconductor nanoparticles against some pathogenic fungi, Materials Science and Engineering, 2017, C 73:665\u2013669.<\/li>\n
  11. Chua K.Y.L., Stinear T. P. and Howden B. P., Functional genomics of Staphylococcus aureus<\/em>, of Brif.InFunc. Genomics<\/em>, 2013, 12 (4): 305-315.<\/li>\n
  12. Dheeb BI, Al-Mashhadani II, dheeb BI, Ismail EN, MajeedSM, Majeed DM., A Study of the Expression of Aflatoxin B1 Regulatory Gene in Clinical and Environmental Aspergillusflavus using Real-time PCR, 2014, I J S: B A R, 17 (1), 417-427.<\/li>\n
  13. Dheeb, B. I., Al-Mudallal, N. H., Salman, Z. A. and Ali, M., The Inhibitory Effects ofHuman, Camel and Cow\u2019s Milk against Some Pathogenic Fungi in Iraq, Jordan Journal of Biological Sciences, 2015, 8(2) 89 \u2013 93.<\/li>\n
  14. Xia G., Wolz Ch., Phages of Staphylococcus aureus and their impact on host evolution, of Infection, Genetics and Evolution<\/em>, 2014, 21: 593-601.<\/li>\n
  15. Hussain AF, Sulaiman GM, Dheeb BI , Hashim AJ., Histopathological changes and expression of transforming growth factor beta (TGF-\u03b23) in mice exposed to gliotoxin, Journal of K S U \u2013 Science<\/em>, 2018, 27, 193\u2013197.12.<\/li>\n
  16. Yoke-Kqueen C., Laurence J., Radu S., Characterization of Staphylococcus aureus<\/em> Isolated from The Skin Surface of Athletes and Training Environment by Random Amplified Polymorphic DNA and Antibiotic Resistance profiling, of Biotechnol.<\/em> 2006, 5 (4): 489-494.<\/li>\n
  17. Abdulbaqi NJ, DheebBI ,Irshad R., Expression of Biotransformation and Antioxidant Genes in the Liver of Albino Mice after Exposure to Aflatoxin B1 and an Antioxidant Sourced from Turmeric (Curcuma longa), Jordan Journal of Biological Sciences. 2018, 11(2) 89 \u2013 93.<\/li>\n
  18. Hussein, HS, Dheeb BI, Hamada,TA., Studying the candida <\/em>resistance and sensitivity for some antifungals, Journal of Biotechnology Research Center. 2019, 13 (2)25-34.<\/li>\n
  19. Bander\u00a0 KI, Mohammed SH, ThalijKM, Dheeb BI., Survey Study of the Allergic Fungi in Kirkuk Area and Use Molecular Detection for Identification, 2015, I J S: B A R, 19 (1), 383-397.<\/li>\n
  20. Mehndiratta P.L. and Bhalla P., Typing of Methicillin resistant\u00a0Staphylococcus aureus<\/em>: A technical review, J. of Indian Midic. Microbiol.,<\/em> 2012, 30 (1) : 16-23.<\/li>\n
  21. Dahham, MT, Omar AF, Dheeb BI., Synergistic effect of tea tree oil on fungi causing vaginal thrush in pregnant women,\u00a0 Journal of Biotechnology Research Center, 2019, 13 (2)35-44.<\/li>\n
  22. Shanmugam S., Selvarajan R., Thangiah S., Drug resistance of Staphylococcus aureus in sinusitis patients, Int. J. of Biosci.<\/em> 2011, 1(3):63-71.<\/li>\n
  23. Abdulamir A. S., Yoke T. S., Nordin N. and Abu Bakar F., Detection and quantification of probiotic bacteria using optimized DNA extraction, traditional and real-time PCR methods in complex microbial communities, Afr. J. Biotechnol. 2010, 9 (10): 1481-1492.<\/li>\n
  24. Al-Noaami R. J., Detection the Genotype Estimation of Allele Frequencies for ABO Groups an Rh Factor in Populations of Selah Al-Dine and Kirkuk and Neneva Provinces, Ph.D. thesis, College of Education, Tikrit University, 2014.<\/li>\n
  25. Dheeb BI, Al-Halbosiy MMF, Al lihabi RK, Khashman BM., The effects of Rubusidaeus extract on normal human lymphocytes and cancer cell line. BMC Genomics., 2016, 17(Suppl 6):P19.<\/li>\n
  26. Kumari N. and Thakur S.K., Randomly Amplified Polymorphic DNA- A Brief Review, J. of Americ. Animal and Vet. Scien<\/em>., 2014, 9 (1): 6-13.<\/li>\n
  27. Dheeb B. I., Immunohistochemical study of Tumor Necrosis Factor-alpha(TNF- \u03b1) expression in lung, liver, and spleen during aspergillosis infection, BMC genomics<\/em>., 2013 ,15 (2), 71.<\/li>\n
  28. Kosman E. and Leonard K. J., Similarity coefficients for molecular markers in studies of genetic relationships between individuals for haploid, diploid, and polyploid species, of Molec. Ecol<\/em>. 2005, 14: 415-424.<\/li>\n
  29. AF Hussain, GM Sulaiman, BI Dheeb, AJ Hashim, ESA Alrahman., Histopathological changes and expression of transforming growth factor beta (TGF-\u03b23) in mice exposed to gliotoxin], Journal of K S U \u2013 Science., 2020, 27, 193\u2013197.<\/li>\n
  30. Galal F. H., Comparison of RAPD and PCR-RFLP markers for classification and taxonomic studies of insects, Egypt.Acad. J. of biolog. Sci<\/em>., 2009, 2 (2): 187-195.<\/li>\n
  31. BI Dheeb., Antifungal Activity of Alkaloids and Phenols Compounds extracted from black pepper Piper nigrum against some pathogenic fungi, Jornal of B R., 2015. 9 (2), 46-54.<\/li>\n
  32. AL-Darahi K. F., Mahdi L. K., AL-Naib K. T., Jubreal J., Molecular Charecterization of E. coli <\/em>O157:H7 Strains Using Random Amplified Polymorphic DNA (RAPD), J. of Dohuk Univ<\/em>., 2008, 11 (1): 198-205.<\/li>\n
  33. SY Hammadi, AS Hussein, DM Majeed, BI Dheeb, EN Ismail. RAPD and ISSR analyses of Saccharomyces cerevisiae isolates from different sources Jornal of BRC .2019 .12 (2), 40-50<\/li>\n
  34. AHM Hamoody, JN Abood, BI Dheeb., The synergistic effect of fungus filter Aspergillusterreus and aqueous extract of Fucusvesiculosus on some growth characteristics of the ocimumbasilicum and its content of heocimumbasilicum and itscontentof active substances,\u00a0 Eurasia J Bio sci., 2020. 14, 161-166.<\/li>\n
  35. Larrasa J., Garc\u0131\u00b4a-Sa\u00b4nchez A., Ambrose N. C., Parra A., Alonso J. M., Reyd J. M., Hermoso-de-Mendoza M., And Hermoso-de-Mendoza J., Evaluation of randomly amplified polymorphic DNA and pulsed field gel electrophoresis techniques for molecular typing of Dermatophiluscongolensis, FEMS Microbiology Letters, 2004, 240: 87-97.<\/li>\n
  36. AS Husain, KM Thalij, BI Dheeb., Effects of interaction between Aflatoxins (AFs) and functional materials FM in the hematological, biochemical parameters and enzyme activity in Rats, Egyptian Academic Journal of Biological Sciences, B. Zoology.,\u00a0 2014,\u00a0 6 (2), 17-2.<\/li>\n
  37. Abu-Qatouseh, L. F., Chinni, S. V., Seggewi\u00df, J., Proctor, R. A., Brosius, J., Rozhdestvensky, T. S., … & Becker, K. (2010). Identification of differentially expressed small non-protein-coding RNAs in Staphylococcus aureus displaying both the normal and the small-colony variant phenotype. Journal of Molecular Medicine, 88(6), 565-575.\u200f<\/li>\n
  38. Scarano D. and Rao R., DNA Markers for Food Products Authentication, J. of Diversity<\/em>, 2014, 6: 579-596.<\/li>\n
  39. Ozbey G., Kilic A., Ertas H. B., Muz A., Random amplified polymorphic DNA (RAPD) analysis of Pasteurellamultocida<\/em>andManheimiahaemolytica<\/em>strains isolated from cattle, sheep and goats, J. ofVet. Med. \u2013 Czech, <\/em>2004, 49 (3): 65-69.<\/li>\n
  40. Idil N. and Bilkay I.S., Application of RAPD-PCR for Determining the Clonality of Methicillin Resistant Staphylococcus aureus<\/em>Isolated from Different Hospitals, J. of Braz. Arch. Biol. Technol<\/em>., 2014, 57(4): 548-553.<\/li>\n
  41. Donate-Correa J., Alcoba-Florez J. and M\u00e9ndez-AlvarezS., New Staphylococcus aureus<\/em>genetic cluster associated with infectious osteomyelitis, J.of Int. Microbiol<\/em>. 2011, 14:33-39.<\/li>\n
  42. Datta S., Gangwar S., Kumar S., Gupta S., Rai R., Kaashyap M., Singh P., Chaturvedi S. K., Singh B. B., Nadarajan N., Genetic Diversity in Selected Indian Mungbean [Vignaradiata<\/em>(L.) Wilczek] Cultivars Using RAPD Markers, Ameri.J. of Plant Scien.<\/em> 2012, 3, 1085-1091.<\/li>\n
  43. Al-Zahrani N. H., PCR- based Random Amplified Polymorphic DNA Fingerprinting of Staphylococcus aureus<\/em>strains isolated from patients in Jizan Hospital, Saudi Arabia, J. of Life Sci, <\/em>2013, 10 (12): 316-322.<\/li>\n
  44. Olorunfemi O.B., Onasanya A.A. and Adetuyi F.C., Genetic variation and relationship in Staphylococcus aureus<\/em>isolates from human and food samples using\u00a0 random amplified polymorphic DNAs, African J. of Biotechnol<\/em>., 2005, 4 (7): 611-614.<\/li>\n
  45. Penner G. A., Bush A., Wise R.,\u00a0 Kim W.,\u00a0 Domier L.,\u00a0 Kasha K.,\u00a0 Laroche A., Scoles G., Molnar S. J. and Fedak G., Reproducibility of Random Amplified Polymorphic DNA (RAPD) Analysis among Laboratories, Cold Spring Harbor Laboratory Press ISSN, 1993, 9: 341-345.<\/li>\n
  46. Branger C., Gardye C., Galdbart J-O., Deschamps C., and Lambert N., Genetic Relationship between Methicillin-Sensitive and Methicillin-Resistant Staphylococcus aureus<\/em>Strains from France and from International Sources: Delineation of Genomic Groups, J. of Clin. Microbiol.,<\/em> 2003, 41(7): 2946-295.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Introduction Staphylococci are ubiquitous, including a dozen species occurring as […]<\/p>\n","protected":false},"author":13,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[77],"tags":[],"class_list":["post-33475","post","type-post","status-publish","format-standard","hentry","category-vol13no2"],"_links":{"self":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/33475","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/comments?post=33475"}],"version-history":[{"count":5,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/33475\/revisions"}],"predecessor-version":[{"id":34385,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/33475\/revisions\/34385"}],"wp:attachment":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/media?parent=33475"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/categories?post=33475"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/tags?post=33475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}