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J Clin Microbiol. 2009 October; 47(10): 3246–3254.
Published online 2009 August 5. doi:  10.1128/JCM.00624-09
PMCID: PMC2756899

Molecular Surveillance and Population Structure Analysis of Methicillin-Susceptible and Methicillin-Resistant Staphylococcus aureus in High-Risk Wards[down-pointing small open triangle]

Abstract

In this study we report the results of analysis of 253 isolates of Staphylococcus aureus (132 methicillin [meticillin]-resistant S. aureus [MRSA] isolates and 121 methicillin-susceptible S. aureus [MSSA] isolates) from 209 patients admitted to 18 high-risk wards of six hospitals located in Florence, Italy, over an 8-month period during which a program of epidemiological surveillance of hospital-acquired infections was conducted. The majority (69%) of the 87 reported S. aureus infections were caused by MRSA. No outbreak events have been reported. All the isolates were typed by amplified fragment length polymorphism (AFLP), and AFLP profiles were analyzed in order to define similarity groups. The discriminatory power of AFLP is very high with MSSA (Simpson index of diversity [D], 95.9%), whereas its resolution capability with MRSA (D, 44.7%) is hampered by the well-known high clonality of these populations (the main MRSA group accounted for 74% of the MRSA isolates). Combining AFLP, improved by visual inspection of polymorphisms, with multiplex PCR greatly increases MRSA resolution (D, 85.5%), resolving the MRSA population to a level that is one of the highest reported in the literature. Widespread and sporadic clones of MSSA and MRSA were identified, and their diffusion in the different hospitals and wards over the surveillance period was studied. The understanding of MSSA and MRSA population structures should be the starting point for the design of a more rational surveillance program for S. aureus species, maximizing benefits and reducing the cost of infection control strategies.

Surveillance of hospital-acquired infections (HAIs), as a critical part of any infection control program, is an indispensable instrument for identification of the dimensions of the problem, for early recognition of changes in infection patterns, and for monitoring of infection trends and rates. Furthermore, surveillance programs allow one to evaluate the effectiveness of interventions, reinforcing good practices and influencing key hospital staff and decision makers (3, 16).

Molecular typing techniques greatly improve the quality of epidemiological information obtained by surveillance programs, allowing more-accurate differentiation of strains. Molecular typing techniques are very useful for recognizing sporadic, unrelated strains and endemic, persistent strains (1, 30) and for determining if a single strain or different unrelated strains are the cause of observed increases in the frequency of HAIs by a microbial species.

Staphylococcus aureus is one of the main etiologic agents of HAIs, particularly in high-risk wards such as intensive care units (ICUs), and methicillin (meticillin)-resistant S. aureus (MRSA) strains are more frequently involved than methicillin-susceptible S. aureus (MSSA) strains (12, 35). This situation turns out to be particularly serious due to the diffusion of highly pathogenic and multidrug-resistant strains (6).

The low degree of genetic variability reported for MRSA populations (30) is a major limitation to strain identification, especially when a short time period and a limited area, such as a single hospital, are monitored. Different molecular typing techniques have been used to point out minor but epidemiologically significant genetic differences between MRSA strains (7, 23, 32, 33, 34). No single technique is clearly superior to others in the resolution of MRSA populations, and a combination of two or more methods has been suggested to be the most efficacious approach (23, 34).

Unlike MRSA strains, which have been the subject of several studies of virulence, pathogenesis, development of new antibiotic resistances, strain diffusion worldwide and in hospital settings, and genome analysis (5, 11, 14, 21, 28), MSSA strains, because of their susceptibility to first-line antibiotics, have only occasionally been the subject of molecular epidemiological studies in hospital settings (7, 38). Recent studies performed by multilocus sequence typing have shown a strong genetic relationship between MRSA and MSSA strains, suggesting that MRSA clones arise on multiple occasions from successful hospital MSSA clones by horizontal acquisition of the methicillin resistance (mec) gene (8).

In this work, we report the results obtained from an extended molecular surveillance program for S. aureus carried out for 18 high-risk wards of six hospitals in Florence, Italy, over an 8-month period. Our aim was to study the population structure and the diffusion of the MRSA and MSSA strains that colonize and infect patients admitted to the wards under observation. With this aim, amplified fragment length polymorphism (AFLP) analysis was utilized to type MRSA and MSSA isolates, whereas multiplex PCR was used to subtype MRSA isolates falling into the same AFLP group. The Simpson index was employed to evaluate the discriminatory powers of the two molecular techniques and to analyze the structures of both the MRSA and the MSSA populations.

MATERIALS AND METHODS

Surveillance system, specimen collection, and phenotypic analysis of bacterial isolates.

During a program of surveillance of nosocomial infections, between July 2006 and February 2007, S. aureus isolates were collected from patients admitted to 18 high-risk wards (11 adult ICUs, 5 neonatal ICUs, 1 bone marrow transplantation unit, and 1 hematology ward) of six public hospitals, located in the district of Florence, Italy: a university hospital (H1) (1,700 beds), a university hospital for children (H2) (180 beds), and four nonuniversity hospitals (H3 [161 beds], H4 [246 beds], H5 [104 beds], and H6 [263 beds]). All patients admitted to the hospital wards monitored within the period of the surveillance program who tested positive for S. aureus were included in the study. All S. aureus isolates from positive patients were analyzed, but only those showing different AFLP or AFLP-multiplex PCR molecular profiles (see below) were considered in the results.

S. aureus isolates were identified and tested for antimicrobial susceptibility, according to the recommendations of the Clinical and Laboratory Standards Institute (CLSI), at the Laboratory of Microbiology, Careggi Hospital (Florence, Italy), using the automated Vitek2 system (BioMerieux, Marcy l'Etoile, France). S. aureus ATCC 29213, ATCC 25923, and ATCC 33591 were used as controls.

The surveillance system consists of the Laboratory Information System (Dianoema, Bologna, Italy), which is connected to the real-time epidemiological information system Vigi@ct (Biomerieux, Las Balmas, France) (13). Vigi@ct points out presumed HAIs and outbreak events and prints documents for pathogen detection to be sent, with a clinical questionnaire, to the corresponding hospital ward. Ward clinicians define the event as infection or colonization, and they recognize if an outbreak is occurring or not. Infections, defined on the basis of a positive culture from a presumed infected site, or from body fluid or other sterile sites, were classified as HAIs or community-acquired infections (CAIs) when obtained >48 h or <48 h after hospital admission, respectively; colonization was defined as a positive culture from a specimen in the absence of clinical signs or symptoms of infection. Once compiled, clinical questionnaires were to be returned to the Laboratory of Microbiology at the Careggi Hospital for the updating of the Vigi@ct system.

DNA extraction.

DNA was extracted from bacterial cells, killed in a 50% isopropanol solution, by using the Wizard genomic DNA purification kit (Promega) according to the manufacturer's instructions. Lysostaphin (Sigma) was added at 10 mg/ml at the cell lysis step. DNA was spectrophotometrically quantified (BioPhotometer; Eppendorf).

AFLP analysis.

AFLP was carried out as previously described by Speijer et al. (31) and Vos et al. (39) with slight modifications (10). AFLP-PCR primers EcoRI-A (6-carboxyfluorescein-5′-GACTGCGTACCAATTCA) and MseI-0 (5′-GATGAGTCCTGAGTAA) were chosen via a primer selection procedure aimed at obtaining a suitable number of well-resolved amplified fragments in a defined molecular weight range. Amplified fragments were separated by capillary electrophoresis on an ABI 310 bioanalyzer (10). The sizes of AFLP fragments were determined by using a 50- to 400-bp internal standard (Rox 400HD) and GeneMapper software (version 4.0; Applied Biosystems). Only fragments ranging from 60 to 117 bp and from 127 to 400 bp were analyzed by pairwise comparison with the Dice index. Dendrograms were constructed by the unweighted-pair group method with arithmetic means using NTsys software (Applied Biostatistics, Inc.). With the aim of minimizing automated scoring error (25), manual correction analysis was performed for those peaks whose height was close to 100 relative fluorescence units, the threshold that has been fixed for peak presence/absence attribution.

Because of the intrinsic variability of the AFLP analysis, and in the absence of clarity about intraspecific differentiation criteria in the literature (2, 19, 20, 27), we performed 10 independent replicates of AFLP analysis of the S. aureus DSM 1104 reference strain in order to establish a cutoff value for clonal group definition. Large clonal groups were subtyped based on the presence/absence of polymorphic peaks identified by visual comparison of pherograms on GeneMapper software.

Among the isolates obtained from the same patient, only those with different AFLP profiles were further analyzed.

PCA.

Principal components for the AFLP fingerprint data were derived (9). The principal-component analysis (PCA) computation is displayed as a 3-dimensional scatterplot in which the position along the axes shows the PCA score of the strain profiles. PCA was used to identify subgroups of AFLP profiles of MRSA and MSSA strains that were hidden by 2-dimensional representation of similarity clustering. PCA was performed using SIMCA-P software (version 11.0.0.0; Umetrics AB).

Multiplex PCR.

MRSA isolates were also typed by MRSA-specific multiplex PCR (32). This PCR simultaneously amplifies genomic sequences containing portions of the hypervariable region (HVR; adjacent to the mecA gene), the spa gene (coding for protein A), and the coa gene (coding for the coagulase). PCR was performed on a One-Personal thermocycler (EuroClone, Italy) using 50 ng of DNA with Illustra Hot Start master mix (GE Healthcare) in a final volume of 25 μl. The reaction and cycling conditions have been described previously (32). Eight microliters of each amplicon was electrophoresed in a 2% agarose gel with ethidium bromide (1 μg/ml) and was visualized under UV light. A 100- to 1,500-bp ladder (Roche Applied Sciences) was used as a molecular weight marker. Multiplex PCR profiles were analyzed visually.

S. aureus population analysis.

Population analyses of S. aureus isolates were performed using the Simpson index of diversity (D) (29) and the related confidence interval (CI) (15, 17). These parameters were used to compare the discriminatory powers of the AFLP and multiplex PCR techniques and to analyze the genetic diversity and structures of the MRSA and MSSA populations (1, 15).

RESULTS

S. aureus surveillance.

During an 8-month surveillance program, 253 of 372 S. aureus isolates from 209 patients were considered for the population analysis reported in this work (see Materials and Methods for the selection criteria for patients and bacterial isolates). Antimicrobial susceptibility tests identified 132 MRSA and 121 MSSA isolates. Table Table11 summarizes the data on HAIs, CAIs, and colonizations, the sites of infection/colonization, and the types of infection. Specifically, we found 79 HAIs (31%), 8 CAIs (3%), 129 colonizations (51%), and 37 isolates for which this information was not available (15%). The majority (69%) of the 87 S. aureus infections, mainly pneumonia and bloodstream infections, were caused by MRSA.

TABLE 1.
Numbers of MRSA and MSSA infections and colonizations and origins of specimens

Structure and comparison of MSSA and MRSA populations.

A Dice index cutoff of 0.88 was used to define S. aureus clonal groups. Pairwise analysis of AFLP profiles (Fig. (Fig.1),1), performed separately on MSSA and MRSA isolates, allowed us to identify 54 different MSSA profiles, with 15 clonal groups and 39 unique profiles. Similarly, 22 different profiles of MRSA isolates were identified: 16 unique AFLP profiles and 6 clonal groups (MRSA1 to MRSA6), with the MRSA1 clonal group comprising 98 isolates (74%). When the pairwise analysis was performed on all the MSSA and MRSA isolates with unique profiles and the representatives of each MSSA and MRSA clonal group, high similarities (Dice indices, around 0.80) were observed between the representatives of the MRSA6 and MSSA17 clonal groups, between one MRSA and one MSSA isolate with unique profiles, between the representatives of the MRSA1 clonal group and one MSSA isolate with a unique profile, and between the representatives of the MRSA2 clonal group and one MSSA isolate with a unique profile (Fig. (Fig.11).

FIG. 1.
Pairwise analysis of MSSA (○) and MRSA (•) AFLP profiles. All unique MSSA (39 isolates) and MRSA (16 isolates) profiles, as well as the profiles for representatives of MSSA and MRSA clonal groups, are reported. The number of isolates in ...

Notably, two of the three MRSA isolates involved in CAIs (Table (Table1)1) belong to clonal groups MRSA1 and MRSA3, respectively. Similarly, two of the five MSSA isolates involved in CAIs (Table (Table1)1) belong to the MSSA1 and MSSA15 clonal groups, respectively (data not shown).

PCA results, obtained by analyzing all the unique AFLP profiles and a representative profile for each MSSA and MRSA clonal group, are shown in Fig. Fig.2.2. The first three components explained 20% of the variance and divided the samples into two groups. The major group includes the strains (mainly MSSA) that clustered at a Dice index higher than 0.46 in the pairwise analysis (Fig. (Fig.1),1), whereas the minor group is composed of strains (mainly MRSA) that clustered at a Dice index lower than 0.46. The low point density of the minor group, compared to that of the larger group, attests to the major distance among MRSA profiles as opposed to MSSA profiles.

FIG. 2.
PCA of AFLP data. The distribution of MSSA (○) and MRSA (•) AFLP profiles that are unique (not numbered) or that correspond to clonal groups (numbered) is shown. The prefix MSSA or MRSA before the number of the clonal group is to be deduced ...

Simpson analysis of the AFLP data showed that the MSSA and MRSA populations, homogeneous with regard to the sample size (121 MSSA and 132 MRSA isolates) and the time of collection (the same 8 months), had distinct structures, as demonstrated by D values of 95.9% and 44.7%, respectively, and nonoverlapping CIs calculated for these two populations (Table (Table22).

TABLE 2.
Simpson index of diversity and related CIs of different typing methods

As suggested by van Belkum et al. (36), visual inspection of the profiles generated by molecular typing is an essential complementary procedure for automated analysis. When the AFLP profiles of the large MRSA1 group were subjected to such inspection, three polymorphisms, not detectable by computer-assisted analysis, were found: (i) presence/absence of a 109-bp peak, (ii) simultaneous presence/absence of 184- and 187-bp peaks, and (iii) simultaneous presence/absence of 196- and 200-bp peaks (Fig. (Fig.3).3). Different combinations of these polymorphic markers subdivided the MRSA1 group into six clonal subgroups (MRSA1A to MRSA1F), with MRSA1A comprising 48% of the isolates (Fig. (Fig.3;3; see also Table Table4).4). The reliability of these markers was demonstrated by analyzing seven MRSA isolates from nasal swabs and eight from bronchial aspirates, from a single patient, collected over a 2-month period: all nasal isolates belonged to the MRSA1A subgroup, whereas all bronchial isolates belonged to MRSA1B (data not shown).

FIG. 3.
Results of visual inspection of AFLP profiles. (A) Pherogram from AFLP analysis of a MRSA1 representative. Boxes 1, 2, and 3 identify polymorphic regions. (B) Details of the polymorphic regions at the indicated base pair positions for each of the six ...
TABLE 4.
Definition of MRSA clonal groups by combination of molecular profiles

Multiplex PCR analysis, a technique recently developed for quick, inexpensive, and highly discriminative analysis of MRSA outbreaks (32), was conducted for all 132 MRSA isolates. The amplified fragments ranged from 1,000 to 1,500 bp for the coa gene, from 630 to 1,000 bp for the spa gene, and from 380 to 610 bp for the HVR (Table (Table3).3). Twenty-three different profiles were defined, eight of which (A, B, D, F, L, P, S, and V) were clonal groups comprising more than one isolate; the main multiplex PCR clonal group (group A) comprised 65% of the MRSA isolates.

TABLE 3.
MRSA-specific multiplex profiles and dimensions of amplified fragments

When AFLP and multiplex PCR results were combined, 44 different profiles were defined, 10 of which were clonal groups; the main AFLP-multiplex PCR clonal group, MRSA1A-A, comprises 35% of all the MRSA isolates (Table (Table44).

Comparison of the discriminatory powers of AFLP and multiplex PCR.

Evaluation of the discriminatory powers of the different typing methods for the MRSA strains shows that multiplex PCR has a resolving power comparable to that of AFLP (overlapping CIs) (Table (Table2).2). The fact that the two techniques grouped different sets of MRSA isolates (data not shown) reflects the different analytic natures of the two typing methods. When, with the aim of increasing the resolution within the highly clonal population of the MRSA isolates, AFLP analysis was supported by visual inspection of peak profiles, the discriminatory power was increased from a D of 44.7% to 74.5%, exceeding that of multiplex PCR. A further increase in the resolution of the MRSA population was achieved by combining AFLP and multiplex PCR (D, 85.5%). However, since the CIs were overlapping (67.2 to 81.9% and 80.3 to 90.7%, respectively), the discriminatory powers of AFLP with visual inspection alone and in combination with multiplex PCR were comparable.

Space-time diffusion of S. aureus strains in hospital settings.

Tables Tables55 and and66 (see also the supplemental material) report the space-time diffusion of MSSA and MRSA strains, respectively, in the six hospitals under surveillance. The clonal groups MSSA2, MSSA4, and MSSA10 appear to be widespread (isolated continuously during the 8-month surveillance program from several patients in several wards), whereas the nine MSSA9 strains were all isolated in July to September 2006, five of the six MSSA15 isolates were isolated in July 2006, and the six MSSA1 isolates were isolated in September to December 2006. All the other MSSA clones are represented by sporadic strains (isolates with unique AFLP profiles or isolates of the same clonal group collected from a few patients in a few wards, usually within a short period). Although no outbreak events occurred during the surveillance period, horizontal transmission of strains cannot be excluded. Table Table55 reports the space-time correlation for some MSSA clones; for example, the MSSA10 clone was isolated from four patients (one of whom developed an HAI), admitted in the same period to H4, ward 1 (W1).

TABLE 5.
Diffusion in space and space-time correlation of MSSA clones
TABLE 6.
Diffusion in space and space-time correlation of MRSA clones

With regard to MRSA clonal groups (Table (Table6),6), MRSA1A-A and MRSA1C-A were widespread strains, isolated only in adult ICUs, whereas other clones were more restricted in space (MRSA1A-B, MRSA1A-L, and MRSA1C-F) or time (MRSA2-A, MRSA3-V, and MRSA1B-A [the first three months of the surveillance period]) (see the supplemental material). Space-time correlations were frequently found for different MRSA clones (Table (Table6).6). Also, the three MRSA1A-L isolates, detected from August to October 2006 in three patients in two different wards (H1, W1 and W2), could be viewed as correlated, because the two ICUs share staff and instrumentation, a situation that increases the probability of cross-transmission.

DISCUSSION

This work is part of an extended surveillance program aimed at monitoring different microbial species of nosocomial interest in 18 high-risk wards of six hospitals in Florence, Italy. During an 8-month surveillance period, two S. aureus populations of equal size, the MSSA (121 isolates) and MRSA (132 isolates) populations, were found, with MRSA accounting for the majority of the pneumonia, bloodstream, and other (numerically less important) infections.

We used AFLP, recently reported as one of the best S. aureus typing techniques (24), to resolve MSSA and MRSA populations. AFLP distinguished 15 clonal groups and 39 isolates with unique profiles within the MSSA population, with a resolving power comparable to that of pulsed-field gel electrophoresis (18, 38). The absence of predominant genotypes in the MSSA population is in accordance with the findings of other, similar studies (37, 38). Overall, AFLP seems to be a good approach to MSSA typing in hospital settings for surveillance purposes. Unlike the MSSA population, the MRSA population was not well resolved: 74.2% of MRSA isolates grouped within the MRSA1 clonal group, and only 19 strains (12.1%) had unique AFLP profiles. A similar clonal structure was described previously for MRSA (7, 11, 15, 23, 24). Visual inspection of the profiles for polymorphic peaks enhanced the discriminatory power of AFLP and allowed us to resolve the MRSA1 group into six subgroups; the main subgroup (MRSA1A) comprised 48% of the MRSA isolates.

Recent studies have shown strong genetic relationships between nosocomial MSSA and MRSA strains (7, 18); for example, the majority of the clinical MSSA isolates analyzed in a study in Finland shared highly related pulsed-field gel electrophoresis genotypes with a collection of MRSA strains from the same country (18). In our study, only a few MRSA and MSSA strains showed highly related AFLP profiles. Moreover, the AFLP profiles of the MRSA strains appeared to be more scattered than those of the MSSA strains by cluster analysis (54% versus 90% of profiles clustered at a Dice index value of ≥0.54) (Fig. (Fig.1)1) and PCA analysis (Fig. (Fig.22).

Recent comparative genomic studies have revealed that the S. aureus genome is made up of “core” genes (75% of the genome), conserved by vertical inheritance, and “accessory” genes (25% of the genome), lost and gained by horizontal gene transfer and often associated with virulence and resistance traits (11, 21). This finding reveals a high subtype variability that should be detected in order to resolve highly related isolates that, as in this study, come from a very restricted area over a short period. Our typing approach, combining genomewide analysis by AFLP (improved by visual inspection of the profiles) with a multiplex PCR technique that analyzes highly variable regions related to resistance and pathogenesis (4, 24, 32), demonstrated high discriminatory power and, maximizing the number of detected polymorphisms, resolved the MRSA population to a level that is one of the highest obtained in the literature (26, 38).

Two widespread strains (MRSA1A-A and MRSA1C-A), frequently involved in infections, were identified; in particular, the MRSA1A-A strain, isolated from 47 patients, was the cause of 24 infections (42% of the total MRSA infections). In any case, over the reported period of epidemiological surveillance, no MRSA outbreaks occurred. Space-time correlation was observed several times for MRSA strains, with high numbers of patients (Table (Table6)6) and infections (data not shown) involved; these data are in agreement with clone diffusion mainly by cross-contamination. Unfortunately, the lack of information about the presence and the identity of S. aureus strains in the hospital environment and staff prevented the identification of the sources and routes of presumptive cross-transmission. Our data, showing few probable cases of cross-contamination by MSSA (Table (Table5),5), are in accordance with a study in a Dutch teaching hospital (37) reporting that the majority of MSSA infections could not be explained by cross-infection and probably arose endogenously.

In this study, the occurrence of CAIs with MRSA and MSSA clones, which were also responsible for HAIs, should confirm that, in both cases, the line between HAI and CAI S. aureus strains is blurred, as suggested by other authors (22). Future analysis of MRSA and MSSA strains responsible for CAIs in this district could clarify the relationship between hospital and community infection strains.

Different studies have been carried out in order to evaluate which is the most efficient strategy for the control of pathogenic MRSA strains, even though the resolution of this problem remains controversial. This ongoing debate prompts questions concerning evidence-based interventions and innovative approaches that could improve the control of endemic MRSA strains and reduce their clinical impact (16).

Overall, the results obtained in this study have allowed us to describe the spatial and temporal distribution of the S. aureus strains and to determine the epidemiology of nosocomial infections in the area and time surveyed. The understanding of MSSA and MRSA population structures should be a starting point for the design of a more rational program for the surveillance of S. aureus species, maximizing benefits and reducing the cost of infection control strategies, particularly for MRSA.

Supplementary Material

[Supplemental material]

Acknowledgments

We are grateful to Cristina Indorato for technical assistance.

This study was supported by a grant from Regione Toscana.

Footnotes

[down-pointing small open triangle]Published ahead of print on 5 August 2009.

Supplemental material for this article may be found at http://jcm.asm.org/.

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