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Molecular Epidemiology of Community-Associated Methicillin-resistant Staphylococcus aureus in the genomic era: a Cross-Sectional Study

Molecular Epidemiology of Community-Associated Methicillin-resistant Staphylococcus aureus in the... Molecular Epidemiology of Community- Associated Methicillin-resistant SUBJECT AREAS: Staphylococcus aureus in the genomic PHYLOGENETICS EPIDEMIOLOGY BACTERIAL INFECTION era: a Cross-Sectional Study PATHOGENS 1,2 1,2 3 4 1,2 1 Mattia Prosperi , Nazle Veras , Taj Azarian , Mobeen Rathore , David Nolan , Kenneth Rand , 3 1,2 2 1,2 Robert L. Cook , Judy Johnson , J. Glenn Morris Jr. & Marco Salemi Received 23 November 2012 1 2 College of Medicine, Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Emerging Pathogens Accepted 3 Institute, University of Florida, College of Public Health and Health Professions and College of Medicine, Department of 7 May 2013 Epidemiology, University of Florida, Division of Pediatric Infectious Diseases and Immunology, Department of Pediatrics, University of Florida College of Medicine-Jacksonville, Jacksonville, FL. Published 28 May 2013 Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of healthcare-associated infections and significant contributor to healthcare cost. Community-associated-MRSA (CA-MRSA) strains have now invaded healthcare settings. A convenience sample of 97 clinical MRSA isolates was obtained from seven Correspondence and hospitals during a one-week period in 2010. We employed a framework integrating Staphylococcus protein A requests for materials typing and full-genome next-generation sequencing. Single nucleotide polymorphisms were analyzed using should be addressed to phylodynamics. Twenty-six t002, 48 t008, and 23 other strains were identified. Phylodynamic analysis of 30 M.S. (salemi@ t008 strains showed ongoing exponential growth of the effective population size the basic reproductive pathology.ufl.edu) number (R0) ranging from 1.24 to 1.34. No evidence of hospital clusters was identified. The lack of phylogeographic clustering suggests that community introduction is a major contributor to emergence of CA-MRSA strains within hospitals. Phylodynamic analysis provides a powerful framework to investigate MRSA transmission between the community and hospitals, an understanding of which is essential for control. taphylococcus aureus is a causative agent of skin and soft tissue infections (SSTI) and invasive disease with high rates of morbidity and mortality . S. aureus is also the leading cause of hospital-associated infections 2–4 5 S (HAI) , contributing significantly to increased healthcare costs . In 2008, the latest year of available data, CDC estimated that MRSA was responsible for 89,785 cases of invasive disease causing 15,249 deaths in the US . The Center for Medicaid and Medicare Services no longer reimbursing excess hospitals charges attributed to HAIs compounds the financial impact of this issue . Over the past 70 years, since the discovery and widespread utilization of antibiotics, multi-drug resistant strains of S. aureus have emerged. Methicillin-resistant S. aureus (MRSA) originally appeared in hospitals in the 1960s, and then reemerged in the community and hospitals in the 1990s, spreading worldwide and creating reservoirs in both settings . Until the mid-1990s, MRSA infections were mostly reported among individuals with predisposing risk factors and exposure to healthcare facilities (HCF) . However, over the past fifteen years in the United States, we have witnessed a dramatic increase of community-associated (CA) cases in healthy people lacking known risk factors or exposure to the healthcare system . CA-MRSA strains are genetically distinct compared to healthcare-associated MRSA (HA-MRSA) strains. Particularly, CA-MRSA isolates tend to be resistant to fewer non-b-lactam antibiotics, carry a smaller version of the genetic region responsible for methi- 11,12 cillin resistance (SCCmec IV or SCCmec V), and often produce the Panton-Valentine leukocidin (PVL) . In the United States, CA-MRSA strains also seem to spread more efficiently in community settings and are more 13–15 virulent than HA-MRSA strains . It was previously thought that CA-MRSA strains were isolated to populations outside of the healthcare setting and caused relatively mild infections limited to uncomplicated SSTIs . More recently, we have observed a blurring of the definitions which delineate CA- and HA- MRSA both molecularly and epidemiologically. MRSA strains with molecular characteristics of CA-MRSA have invaded healthcare settings and are now recognized as an important cause of HAIs . In 2008, almost 27% of hospital-acquired MRSA infections were SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 1 www.nature.com/scientificreports due to USA300 strains . Within some healthcare institutions, CA- mixing of strains potentially originating from community reservoirs. MRSA strains have replaced HA-MRSA strains . These events dem- In order to the test this hypothesis, we applied an innovative frame- work based on phylodynamic analysis integrating molecular spa onstrate that current infection control measures have failed to pre- vent the emergence of CA-MRSA strains from becoming a major typing and full-genome next-generation sequencing data by Illumina. In particular, we measured the degree of hospital-specific contributor to HAIs. clustering of MRSA strains, as well as the bacterial gene flow (migra- Increasing colonization pressure, or the proportion of patients tion) among different hospitals. Several investigators have used WGS infected or colonized with MRSA upon entry to a HCF, is identified 8,38–40 for the study of emerging pathogens . Although the analysis was as a major driving force for the emergence of CA-MRSA as a cause of 10,17,18 based on a convenience sample and general conclusions should be HAIs . As the proportion of patients admitted to HCFs with interpreted accordingly, it clearly shows how sophisticated molecular MRSA increases, so does the opportunity for nosocomial transmis- 18,19 epidemiology tools, until now mainly used to track outbreaks of fast sion . This nosocomial transmission additionally exposes CA- evolving viruses, can successfully be applied to analyze full genome MRSA strains, previously susceptible to a wider range of antibiotics data of emerging bacterial pathogens. then HA- strains, to greater selective antibiotic pressure. While col- onization pressure contributes to the MRSA burden within HCFs, little is known about the changing dynamics of MRSA in the com- Results munity and how these changes are affecting nosocomial transmis- We analyzed a convenience sample of 97 clinical MRSA isolates from sion. Understanding the dynamics of MRSA at the interface of the six hospitals in northeast Florida. Overall, 48 (50%) were classified as hospital and in the community is critical to evaluating current pre- spa type t008, 26 (27%) as t002, 23 (24%) as other types/unknown vention measures and designing effective interventions . types (Table 1). Out of the 59 isolates from Jacksonville, 42 (71%) Molecular characterization methods are an essential component were t008, 4 (7%) were t002, and 13 (22%) were other/unknown in the study of pathogen epidemiology and allow discrimination types. While information regarding isolate source was not specif- between isolates of epidemiologically important organisms. A variety ically requested, two of the Jacksonville facilities reported that 25 of molecular typing methods can be independently used to classify samples (42.4%) were from inpatients. The remaining 34 isolates MRSA strains, including pulsed-field gel electrophoresis (PFGE), could have originated from inpatients or outpatients. Among the multilocus sequence typing (MLST), or spa-typing by sequencing 38 isolates from Gainesville, 6 were t008 (16%), 22 were t002 the highly polymorphic Staphylococcus protein A (spa) gene . CA- (68%), and were 10 (26%) other types/unknown. Figure 1 sum- MRSA strains in the United States are most commonly in a genetic marizes distribution of spa types across hospitals. Compared to cluster designated as PFGE type USA300, MLST type ST8, or spa- Gainesville, t008 isolates were more prevalent in Jacksonville (p , 21,22 0.0001). Furthermore, among all sampled Jacksonville hospitals, the type t008 . Additionally, Healthcare-Associated strains most com- monly cluster in PFGE type USA100, also recognized as spa-type proportion of t008 isolates within each facility was not significantly different (p 5 0.156) compared to other types. t002. Spa type distribution and frequencies have been used in a number of studies to characterize MRSA epidemics since they pro- After processing the next-generation sequencing data, a final mul- tiple alignment of 40 t008 MRSA isolates (26 from Jacksonville, four vide moderate discrimination and possess high throughput and good 12,23–26 inter-laboratory reproducibility . Spa typing can characterize S. from Gainesville and 10 from GenBank) including 3,249 SNPs was generated (Supplementary file 1). Eleven of the 26 Jacksonville iso- aureus isolates within a defined setting and identify potential epide- lates (42.3%) were confirmed to have come from inpatients. The miological clusters by providing limited discrimination within a clo- remaining 15 isolates may have originated from inpatients or out- nal complex. However, greater discrimination such as provided with patients. A preliminary analysis of phylogenetic signal using a trans- whole-genome sequencing (WGS) and single nucleotide polymorph- ition/transversion vs. divergence graph and the Xia’s test (p , ism (SNP) analysis would be useful, for example to discern outbreak 0.0001) did not show evidence for substitution saturation. This from non-outbreak strains in settings where sporadic strains of a indicated that enough signal for phylogenetic inference existed specific spa-types (i.e. t008) are common. Molecular clock-calibrated phylogenetic trees make it possible to investigate the ancestral population from which a given pathogen originated and the evolutionary as well environmental factors con- Table 1 | Frequencies of spa-types across seven northeast Florida tributing to successful epidemic spread . Such studies have mostly hospitals, collected during 2010 (n 5 97) been limited to fast evolving viruses because they require genomic sequences, sampled over relatively short time intervals, displaying Spa-type Number Percent 28–31 sufficient diversity in order to infer reliable phylogenies . t002 26 26.8% However, the recent application of next generation full-genome t007 1 1.0% sequencing and phylogenetic analysis to the study of bacterial patho- t008 49 50.5% gens has demonstrated the ability to discriminate between extremely t010 1 1.0% 32–34 similar organisms collected within a short timeframe . Addi- t024 1 1.0% tionally, high-resolution phylogenetic and phylogeographic (phylo- t045 4 4.1% t064 1 1.0% dynamic) analyses based on genome-wide SNP data are a powerful t067 1 1.0% tool to infer the origin and test spatiotemporal hypotheses of MRSA 32,33 t078 1 1.0% spread . Such analyses can reveal temporally and spatially related t105 2 2.1% isolates, elucidate the epidemiology of MRSA transmission in the t1062 1 1.0% community, and identify reservoirs when combined with epidemio- t1107 1 1.0% logical data. In addition, this facilitates an understanding of pathogen t121 1 1.0% success in terms of emergence, virulence, and epidemics . Currently, t2229 1 1.0% whole-genome analysis of S. aureus has largely been limited to in t242 1 1.0% 35 36 t539 1 1.0% vitro drug resistance , bacterial population size , and geographic t688 1 1.0% distribution of different strains . t746 1 1.0% This pilot study was designed to investigate whether MRSA cir- Unknown 2 2.1% culation in northeast Florida hospitals is the result of hospital- Total: 97 100% specific epidemics (i.e. endemic transmission) or heterogeneous SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 2 www.nature.com/scientificreports the data set contained enough information for reliable phylogeny inference. The optimal evolutionary model as selected by the Akaike information criterion using MEGA5 was the general time reversible (GTR). Figure 2 depicts the GTR maximum-likelihood (ML) tree, including bacterial sequences from Jacksonville and Gainesville, shows no distinct clustering of hospital-specific clades. All trees esti- mated with other methods and including GenBank reference sequences are available as supplementary material and showed exactly the same pattern. Strict and relaxed molecular clock models, as well as different demographic coalescent models of effective bacterial population size (Ne) over time, interpreted as the number of effective infections (i.e. 30,41 those contributing to onward transmissions) , were tested to infer Figure 1 | Distribution of MRSA spa types across six different hospitals the demographic history of t008 MRSA strains in northeast Florida. in Jacksonville (J) and one in Gainesville (G), both in northeast Florida, We evaluated two parametric (constant effective population size and USA, collected during 2010 (n 5 97). exponential population growth), and one nonparametric estimate (Supplementary Figure S1, and Supplementary Table T1). Likelihood (Bayesian skyline plot) of bacterial population size over time. The mapping analysis reported , 25% of star-like signal (phylogenetic Bayes Factor (BF) strongly favored the relaxed over the strict molecu- noise) and no significant signal for recombination was detected (PHI lar clock model (BF5 42.4), indicating that different bacterial strains test p5 0.82, supplementary figure S2 and S3), indicating overall that evolved at significantly different rates (Table 2). In addition, analysis Figure 2 | ML phylogenetic analyses of MRSA t008 in northeast Florida by HCF. Colored tip branches correspond to healthcare facility from which the isolate was obtained. The numbers along the monophyletic branches correspond to bootstrap values (500 replicates). Branch lengths in nucleotide substitutions per site were scaled according to the bar at the bottom of the tree. SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 3 www.nature.com/scientificreports data to test molecular epidemiology hypotheses of bacterial spread Table 2 | Bayes factor between strict (SC) and relaxed (RC) within a localized healthcare network. These methods can be lever- molecular clock aged to identify emerging epidemics, detect outbreaks, and study a b antibiotic resistance and virulence, as has been recently demon- Clock Marginal likelihood BF 45,46 strated for S. aureus . As rapid sequencing technologies are refined SC 29843.445 and bioinformatic tools are operationalized, we will continue to RC 29822.237 42.416 observe more examples of the utility of WGS and phylogenetic ana- a. The selected molecular clock model (H 5 Null hypothesis, H 5 Alternative hypothesis) is lysis in routine practice. Ultimately, our findings highlight the clear 0 1 highlighted in gray. utility of such methods in seeking to understand, and control, com- b. BF5 Bayes Factor. 6 . BF . 2 indicates positive evidence against the null hypothesis; 10 . BF munity and regional spread of resistant microorganisms. . 6 indicates strong evidence against the null hypothesis, BF . 10 indicates very strong evidence against the null model. We identified a statistically significant difference in the overall distribution of spa-types t008 and t002 among a convenience sample of clinical MRSA isolates from Gainesville and Jacksonville HCFs of the three demographic models showed positive evidence against (Figure 1). MRSA spa type t008 accounted for 71% of isolates the null hypothesis of constant bacterial population size in favor of obtained from Jacksonville compared to 16% of strains from the exponential growth model (BF 5 2.7), which also outperformed Gainesville (Table 1). This is a striking increase from the studies the Bayesian skyline plot model (BF 5 3.9) (Table 3). The temporal conducted in 2003–2004 , where it was found that t008 strains scale of MRSA evolution was inferred using an independent estimate accounted for only 20% of the isolates, while t002 made up the of MRSA genome-wide SNPs evolutionary rate of 7.573 10 , with a majority of isolates. Additionally, a national average of 31.3% of 95% highest posterior density (95% HPD) interval of 5.11 – 10.2 3 25 32 t008/USA300 were reported in invasive infections from participating 10 nucleotide substitution per SNP site per year . The reconstruc- ABC regions reported by the CDC in 2008 . These differences must tion of MRSA t008 demographic history estimated the origin of the be interpreted with care, however, as they may be attributable to the epidemic in mid-1960s, followed by an exponential increase in effec- HCFs’ respective patient populations or our sampling strategy. tive population size, consistent with the known epidemiology of Unexpectedly, phylogeographic analysis of t008 strains demon- MRSA in the United States (Figure 3). By using the estimated growth strated a lack of clustering, i.e. no hospital-specific clades rate of MRSA from the exponential population growth model (0.34, (Figure 2). It was hypothesized that our analysis would identify 95% HPD5 0.14 – 0.57) and estimates of colonization and infection monophyletic branches of isolates clustering within hospitals, sig- duration ranging from 8.5 months to one year, we were able to nifying endemic transmission or distinct community-based determine the potential reproductive number (R0)of S. aureus 42,43 sub-epidemics in populations constituting the facility’s patient popu- within our sample . R0 estimates were not based on traditional lation. The lack of clustering within facilities alludes to other trans- SIR epidemic models; instead, we utilized the estimated Ne and mission dynamics at work. It was also expected that gene flow of t008 growth rate from phylodynamic analysis to determine the R0 for isolates, as measured by the number of observed bacterial migrations infections and colonizations in the population. This method has in the phylogenetic tree, would be observed between specific HCFs, previously been employed by Pybus et al. to estimate the R0 of either in close proximity and/or serving similar populations. Hepatitis C Virus . R0 estimates for MRSA USA300 R0 ranged from However, this was not apparent among our sample, where bacterial 1.24 (95% HPD 1.10 – 1.40) to 1.34 (95% HPD 1.14 – 1.57). strains were randomly distributed among different hospitals without To assess the phylogeographic pattern of MRSA t008 in northeast any restricted or directional flow. It is possible that the complexity of Florida, a discrtete character corresponding to each isolate’s respect- the healthcare network within our study area explains the diversity in ive hospital was assigned to the tip branches of the ML genealogy. hospital distribution among phylogenetic clades and the lack of gene Bacterial gene flow among hospitals was then traced on the basis of flow. For example, the referral system between hospitals and the the maximum parsimony reconstruction of the ancestral characters presence of numerous long-term care, rehabilitation, and long-term (Figure 4a). A randomization test showed that the null hypothesis of acute care facilities is so extensive and geographically dispersed that panmixia, i.e. absence of MRSA t008 population subdivision among sub-epidemics propagated through the intermixing of HCF patient different hospitals, could not be rejected (Figure 4b). In addition, the populations and the community are spatiotemporally isolated and observed bacterial gene flow among the different hospitals was not require a larger sample size to detect. This model would suggest statistically significant (Table 4), indicating a relatively homogenous multiple CA and HA reservoirs intermixing and contributing to epidemic across northeast Florida with no directional gene flow the overall microbial burden on the HCF. The hypothesis is also between specific hospitals. supported by the exponential growth of Ne inferred from the Discussion MRSA phylogeny utilizing the Bayesian coalescent framework This study was designed to provide an initial ‘‘snapshot’’ of MRSA (Figure 3). Ne is a measure of genetic diversity and can be interpreted distribution and phylogeny within a major metropolitan area, and to as the number of bacterial genomes effectively contributing to the permit comparison of these isolates with isolates from a smaller subsequent generation . In regards to MRSA, Ne is expected to neighboring city. What emerges is the power of coupling high-reso- correlate with the number of infected and/or colonized individuals. lution phylogenetics and phylogeography with genome-wide SNP However, it is important to note that since individuals may be Table 3 | Bayes factor between different coalescent models (constant population size, exponential growth, and Bayesian skyline plot) BF Demographic model Marginal likelihood S.E. Constant vs. Exponential Constant vs. BSP Exponential vs. BSP Constant 29822.2 1/2 0.25 2.7 1.2 3.9 Exponential 29820.9 1/2 0.24 BSP 29822.8 1/2 0.24 a. The selected coalescent model is highlighted in gray. b. BF5 Bayes Factor. 6 . BF . 2 indicates positive evidence against the null hypothesis; 10 . BF . 6 indicates strong evidence against the null hypothesis, BF . 10 indicates very strong evidence against the null model. SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 4 www.nature.com/scientificreports Figure 3 | Bayesian skyline plots of MRSA t008 in Jacksonville. Non-parametric curves of MRSA effective population size (Ne) over time were estimated by employing a Bayesian framework. Genetic distances were transformed into a timescale of years by enforcing a relaxed molecular clock model. Solid lines indicate median (blue), and 95% upper and lower high posterior density (HPD) estimates of Ne (black). simultaneously infected and/or colonized with multiple strains or As in any other study based on epidemiological models, it is not transmit the bacteria, such a correlation is not necessarily 1 5 1 . important to highlight some of the potential limitations of our approach. First, results should be interpreted in light of our conveni- By reconstructing the demographic history of bacterial popu- lation, it was also possible to estimate R0 value for MRSA. S. aureus ence sampling strategy, which increased participation from HCFs at the cost of detailed clinical and epidemiological information. A delib- demonstrates several clinical presentations ranging from SSTIs to severe invasive disease. Additionally, attempts to accurately estimate erately planned isolate sampling strategy in future studies will be R0 values are confounded by the existence of colonization states, necessary to strengthen the validity of these initial findings. How- during which individuals can be transiently or persistently colonized ever, the observation that individuals hospitalized and/or utilizing 18,42,48 by the bacteria. R0 estimates have ranged from 0.60 to 1.0 . Our the emergency departments were infected with a heterogeneous estimates are slightly higher, in agreement with previous evidence MRSA population remains valid whether the isolates originated from that the reproductive rate for CA-MRSA strains may be, in fact, inpatient or outpatient populations. Second, although coalescent- higher than that of HA-MRSA strains . based phylodynamic analysis does not require a large sample size, 47,52,53 Overall, our study shows the significant implications of utilizing uniform spatiotemporal sampling is important , and it is pos- sible that our convenience sample did not meet this criterion. Finally, phylodynamic methods for the study of MRSA t008 molecular epi- demiology. While we were limited by lack of clinical and demo- the demographic models based on phylodynamic analysis used here assume no population structure and neutral evolution. The violation graphic data from participating HCFs, our analysis included representative clinical isolates obtained from a similar time point of either assumption can bias the reconstruction of the population demographic history and ultimately our inference of R0. However, and from all acute care facilities serving a population of well over one million persons within a common geographic region. A recent phylogenetic and gene flow analysis did show an overall panmic- tic population (i.e. no population subdivision), suggesting that at point prevalence study of HAIs conducted in Jacksonville, FL in 2009 identified 6.0% of patients with one or more HAIs on the day of the least the first of these assumptions may hold true for the present work. survey . S. aureus was the most common pathogen, causing 15.5% of HAIs. These results were similar to national prevalence estimates In conclusion, our findings suggest complex transmission dyna- obtained 30 years prior from the Study of Efficacy of Nosocomial mics of MRSA between the community and healthcare setting with a Infection Control . Contrastingly, other studies have demonstrated heterogeneous distribution of isolates across healthcare facilities. The that the incidence of S. aureus HAIs in certain geographic areas have overall picture of MRSA emergence and distribution drawn herein been steadily decreasing since 2005 . These variations in MRSA- provides a base for subsequent studies incorporating a structured related HAI incidence may result from varying infection prevention sampling strategy, phylogenetic analysis of genome-wide SNP data, practices, surveillance methods, or strain distribution. Overall, HAI and corresponding clinical and demographic data. Most impor- incidence remains high despite the widespread implementation of tantly, our analysis shows how the application of phylodynamics to comprehensive infection control programs. In this setting, applica- microbial genomics has the potential to track the emergence and tion of this phylodynamic/phylogeographic approach provides a demographic history of MRSA strains, testing molecular epidemi- powerful tool to tease apart the various components of MRSA trans- ology hypotheses at a resolution difficult to obtain with alternative mission within communities, which is essential for the development molecular typing methods. Microbial phylodynamic analysis may of effective interventions. be employed to inform control strategies to prevent nosocomial SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 5 www.nature.com/scientificreports Figure 4 | MRSA t008 phylogeographic patterns in Jacksonville. Phylogeographic analysis using a rooted ML genealogy inferred for 26* sequences from Hospitals J.a, J.c, J.d, J.e, and J.f. A. The most parsimonious reconstruction (MPR) of the state of origin for each internal node (ancestral sequence) in the tree is indicated by the color of the subtending branch according to the legend in the figure. Equivocal branches indicate multiple MPRs. *Note: The four G.a sequences were omitted from the ML genealogy. B. Tree length distribution of 10,000 trees obtained by random joining-splitting. The arrow points to the number of observed migrations in the ML tree. metropolitan area; Gainesville, with a population of 125,000, is in north-central transmission and/or constant reintroduction of CA-MRSA strains Florida, approximately 70 miles to the southwest of Jacksonville. Isolates were from the community into HCFs. completely de-identified, with no available clinical or demographic information. The study protocol was reviewed and approved by the University of Florida Institutional Methods Review Board. Data collection and ethics statement. We obtained a convenience sample of clinical MRSA isolates from invasive and non-invasive infections sent for microbiological Sample processing and spa typing. Cultures of MRSA isolates were processed and culture at six tertiary acute care hospitals in Jacksonville, FL (representing all major an aliquot was frozen at 280uC. Each isolate was grown in liquid subculture hospital systems) and one tertiary acute care hospital in Gainesville, FL during a one overnight at 37uC. Genomic DNA (gDNA) was isolated from pelleted bacteria week period in September of 2010. Jacksonville is located on the northeast coast of using the Roche High Pure PCR kit following the standard protocol for isolation Florida, with a population of approximately 1.3 million in the greater Jacksonville of nucleic acids from bacteria (Roche Applied Science, Indianapolis, IN). The quality of the gDNA extracted was determined through gel electrophoresis and quantity was determined using the Nanodrop 2000 (Fisher ND-2000). Molecular Table 4 | MRSA metapopulation structure test typing of these strains was done by spa typing. PCR was used to amplify the spa repeat region using 1 ml gDNA, 1XGoTaq Green Master Mix and 10pmol of each a b Migration direction Observed gene flow p-value primer, spa-1113f (59- TAA AGA CGA TCC TTC GGT GAG C -39)and spa- 1514r (59- CAG CAG TAG TGC CGT TTG CTT -39). The primers are numbered J.e-J.d 2 0.9474 from the 39 end of the primer on the forward strand of a reference S. aureus J.e-J.c 1 0.9812 sequence (GenBank accession no. J01786; spa-1113f [1092–1113] & spa-1514r J.d-J.f 1 0.8020 [1534–1514]). Thermal cycling conditions consisted of a hot start (5 min at 80 uC) J.f-J.e 1 0.9988 followed by 35 cycles of denaturation (15 s at 94uC), annealing (30 s at 58uC), and J.f-J.a 1 0.9992 extension (60 s at 72uC), with a single final extension of 10 min at 72uC. Gel J.a-J.c 1 0.9972 electrophoresis was used to determine PCR success and all PCR products were Sanger sequenced in both directions. Nucleotide sequences were analyzed by using a. Number of migrations observed in the ML tree. Ridom StaphType software and synchronized with SpaServer b. p . 0.01 indicates that the null hypothesis of panmictic spread (not directional gene flow among (www.spaserver.ridom.de) in order to assign the spa type according to number of different hospitals) cannot be rejected. tandem repeats and length variation in the spa gene . SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 6 www.nature.com/scientificreports Next-generation sequencing and data analysis. To provide better discrimination 5. Hubben, G. et al. Modelling the costs and effects of selective and universal hospital within spa type t008 isolates, we conducted next generation WGS. After confirmation admission screening for methicillin-resistant Staphylococcus aureus. PloS one 6, of quality and determination of quantity, 5 mg of each isolate gDNA was sequenced e14783 (2011). on the Illumina HiSeq 2000 sequencing system. Libraries were constructed for each 6. Centers for Disease Control and Prevention Active Bacterial Core Surveillance isolate using the Covaris E220 and the SPRIworks Fragment Library System (ABCs) Report Emerging Infections Program Network Methicillin-Resistant (Beckman Coulter), and accurate quality control was performed using the Agilent Staphylococcus aureus, 2008. Program (2008) ,http://www.cdc.gov/abcs/reports- Bioanalyzer and qPCR, ensuring library quality before sequencing and ideal cluster findings/survreports/mrsa08.pdf. Accessed: November 2012. density during sequencing. Isolates were uniquely tagged and combined in one of 7. Milstein, A. Ending extra payment for ‘‘never events’’--stronger incentives for eight lanes of the flow cell for a paired-end 75 base pair read. A S. aureus reference patients’ safety. The New England Journal of Medicine 360, 2388–90 (2009). strain was identified by querying available WGS in GenBank and utilizing the species 8. DeLeo, F. R. & Chambers, H. F. Reemergence of antibiotic-resistant tree to select the most appropriate sequence for assembly. After de-multiplexing, Staphylococcus aureus in the genomics era. The Journal of Clinical Investigation single FASTQ output files were mapped to a S. aureus reference strain (GenBank 119, 2464 (2009). accession no. 87125858) with the software BWA version 0.5.8 to obtain SAM files. 9. Klevens, R. M. et al. Invasive methicillin-resistant Staphylococcus aureus SAM files were then processed with the Picard and samtools software into BAM and infections in the United States. JAMA: the Journal of the American Medical pileup files, including consensus sequences, using the default parameters for quality Association 298, 1763–71 (2007). calls. Consensus sequences of each strain were merged in a FASTA file, with an 10. Otter, J. A. & French, G. L. Community-associated methicillin-resistant additional set of 10 t008 S. aureus sequences retrieved from GenBank (accession no. 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MRSA t008 demographic history was inferred as Staphylococcus aureus pathogenesis. Infection and Immunity 79, 1927–35 (2011). previously described by Gray and collaborators . The hypothesis of metapopulation 16. Fridkin, S. K. et al. Methicillin-resistant Staphylococcus aureus disease in three structure, i.e. the existence of different MRSA sub-populations in distinct hospitals, communities. New England Journal of Medicine 352, 1436–1444 (2005). was tested with a modified version of the Slatkin and Maddison test using the ML 17. Gonzalez, B. E. et al. Community-associated strains of methicillin-resistant tree . The bacterial gene flow (migration) among different hospitals was traced using Staphylococccus aureus as the cause of healthcare-associated infection. Infection the state changes and stasis tool (MacClade software), which counts the number of Control and Hospital Epidemiology: the official journal of the Society of Hospital changes in a tree for each pair-wise character state. 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Bootsma, M. C. J., Diekmann, O. & Bonten, M. J. M. Controlling methicillin- Acknowledgements resistant Staphylococcus aureus: Quantifying the effects of interventions. PNAS This work was supported by the University of Florida Emerging Pathogens Institute seed 103, 5620–5625 (2006). grant. M.R. is supported in part by the UF CTSI under a grant by the NIH/NCRR Clinical 43. Scanvic, A. et al. Duration of colonization by methicillin-resistant Staphylococcus and Translational Science Award UL1 RR029890. We would like to acknowledge the aureus after hospital discharge and risk factors for prolonged carriage. Clinical contributions of the North Florida MRSA Collaborative Group and the following Infectious Diseases 32, 1393–8 (2001). individuals to their invaluable contributions to this effort: Diane Halstead, PhD; Yevette 44. Pybus, O. G. et al. The epidemic behavior of the hepatitis C virus. Science (New McCarter, PhD; Timothy Sellen, MS; Ann Ruby; and Jane Hata, PhD. 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Nosocomial infections in U.S. hospitals, 1975-1976: estimated frequency by selected characteristics of patients. The American Journal of Medicine 70, 947–59 (1981). Additional information 51. Kallen, A., Mu, Y. & Bulens, S. Health Care–Associated Invasive MRSA Infections, Supplementary information accompanies this paper at http://www.nature.com/ 2005-2008. JAMA: the Journal of the American Medical Association 304, 641–648 scientificreports (2010). Competing financial interests: MP and MS are partially supported by the NIH/NCRR 52. Pybus, O. G., Rambaut, A. & Harvey, P. H. An integrated framework for the CTSI award to the University of Florida UL1 RR02989, and by the NIH-NINDS grant R01 inference of viral population history from reconstructed genealogies. Genetics NS063897-01A2. MR is supported in part by the UF CTSI under a grant by the NIH/NCRR 155, 1429–37 (2000). Clinical and Translational Science Award UL1 RR029890. This study was also supported by 53. Drummond, A. J., Rambaut, A., Shapiro, B. & Pybus, O. G. Bayesian coalescent seed funding from the University of Florida Emerging Pathogens Institute. The authors inference of past population dynamics from molecular sequences. Molecular report no competing financial interests. Biology and Evolution 22, 1185–92 (2005). License: This work is licensed under a Creative Commons 54. Harmsen, D. et al. Typing of methicillin-resistant Staphylococcus aureus in a Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this university hospital setting by using novel software for spa repeat determination license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ and database management. Journal of Clinical Microbiology 41, 5442–5448 (2003). How to cite this article: Prosperi, M. et al. Molecular Epidemiology of 55. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler Community-Associated Methicillin-resistant Staphylococcus aureus in the genomic era: transform. Bioinformatics (Oxford, England) 25, 1754–60 (2009). a Cross-Sectional Study. Sci. Rep. 3, 1902; DOI:10.1038/srep01902 (2013). SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 8 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Scientific Reports Springer Journals

Molecular Epidemiology of Community-Associated Methicillin-resistant Staphylococcus aureus in the genomic era: a Cross-Sectional Study

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Science, Humanities and Social Sciences, multidisciplinary; Science, Humanities and Social Sciences, multidisciplinary; Science, multidisciplinary
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Abstract

Molecular Epidemiology of Community- Associated Methicillin-resistant SUBJECT AREAS: Staphylococcus aureus in the genomic PHYLOGENETICS EPIDEMIOLOGY BACTERIAL INFECTION era: a Cross-Sectional Study PATHOGENS 1,2 1,2 3 4 1,2 1 Mattia Prosperi , Nazle Veras , Taj Azarian , Mobeen Rathore , David Nolan , Kenneth Rand , 3 1,2 2 1,2 Robert L. Cook , Judy Johnson , J. Glenn Morris Jr. & Marco Salemi Received 23 November 2012 1 2 College of Medicine, Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Emerging Pathogens Accepted 3 Institute, University of Florida, College of Public Health and Health Professions and College of Medicine, Department of 7 May 2013 Epidemiology, University of Florida, Division of Pediatric Infectious Diseases and Immunology, Department of Pediatrics, University of Florida College of Medicine-Jacksonville, Jacksonville, FL. Published 28 May 2013 Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of healthcare-associated infections and significant contributor to healthcare cost. Community-associated-MRSA (CA-MRSA) strains have now invaded healthcare settings. A convenience sample of 97 clinical MRSA isolates was obtained from seven Correspondence and hospitals during a one-week period in 2010. We employed a framework integrating Staphylococcus protein A requests for materials typing and full-genome next-generation sequencing. Single nucleotide polymorphisms were analyzed using should be addressed to phylodynamics. Twenty-six t002, 48 t008, and 23 other strains were identified. Phylodynamic analysis of 30 M.S. (salemi@ t008 strains showed ongoing exponential growth of the effective population size the basic reproductive pathology.ufl.edu) number (R0) ranging from 1.24 to 1.34. No evidence of hospital clusters was identified. The lack of phylogeographic clustering suggests that community introduction is a major contributor to emergence of CA-MRSA strains within hospitals. Phylodynamic analysis provides a powerful framework to investigate MRSA transmission between the community and hospitals, an understanding of which is essential for control. taphylococcus aureus is a causative agent of skin and soft tissue infections (SSTI) and invasive disease with high rates of morbidity and mortality . S. aureus is also the leading cause of hospital-associated infections 2–4 5 S (HAI) , contributing significantly to increased healthcare costs . In 2008, the latest year of available data, CDC estimated that MRSA was responsible for 89,785 cases of invasive disease causing 15,249 deaths in the US . The Center for Medicaid and Medicare Services no longer reimbursing excess hospitals charges attributed to HAIs compounds the financial impact of this issue . Over the past 70 years, since the discovery and widespread utilization of antibiotics, multi-drug resistant strains of S. aureus have emerged. Methicillin-resistant S. aureus (MRSA) originally appeared in hospitals in the 1960s, and then reemerged in the community and hospitals in the 1990s, spreading worldwide and creating reservoirs in both settings . Until the mid-1990s, MRSA infections were mostly reported among individuals with predisposing risk factors and exposure to healthcare facilities (HCF) . However, over the past fifteen years in the United States, we have witnessed a dramatic increase of community-associated (CA) cases in healthy people lacking known risk factors or exposure to the healthcare system . CA-MRSA strains are genetically distinct compared to healthcare-associated MRSA (HA-MRSA) strains. Particularly, CA-MRSA isolates tend to be resistant to fewer non-b-lactam antibiotics, carry a smaller version of the genetic region responsible for methi- 11,12 cillin resistance (SCCmec IV or SCCmec V), and often produce the Panton-Valentine leukocidin (PVL) . In the United States, CA-MRSA strains also seem to spread more efficiently in community settings and are more 13–15 virulent than HA-MRSA strains . It was previously thought that CA-MRSA strains were isolated to populations outside of the healthcare setting and caused relatively mild infections limited to uncomplicated SSTIs . More recently, we have observed a blurring of the definitions which delineate CA- and HA- MRSA both molecularly and epidemiologically. MRSA strains with molecular characteristics of CA-MRSA have invaded healthcare settings and are now recognized as an important cause of HAIs . In 2008, almost 27% of hospital-acquired MRSA infections were SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 1 www.nature.com/scientificreports due to USA300 strains . Within some healthcare institutions, CA- mixing of strains potentially originating from community reservoirs. MRSA strains have replaced HA-MRSA strains . These events dem- In order to the test this hypothesis, we applied an innovative frame- work based on phylodynamic analysis integrating molecular spa onstrate that current infection control measures have failed to pre- vent the emergence of CA-MRSA strains from becoming a major typing and full-genome next-generation sequencing data by Illumina. In particular, we measured the degree of hospital-specific contributor to HAIs. clustering of MRSA strains, as well as the bacterial gene flow (migra- Increasing colonization pressure, or the proportion of patients tion) among different hospitals. Several investigators have used WGS infected or colonized with MRSA upon entry to a HCF, is identified 8,38–40 for the study of emerging pathogens . Although the analysis was as a major driving force for the emergence of CA-MRSA as a cause of 10,17,18 based on a convenience sample and general conclusions should be HAIs . As the proportion of patients admitted to HCFs with interpreted accordingly, it clearly shows how sophisticated molecular MRSA increases, so does the opportunity for nosocomial transmis- 18,19 epidemiology tools, until now mainly used to track outbreaks of fast sion . This nosocomial transmission additionally exposes CA- evolving viruses, can successfully be applied to analyze full genome MRSA strains, previously susceptible to a wider range of antibiotics data of emerging bacterial pathogens. then HA- strains, to greater selective antibiotic pressure. While col- onization pressure contributes to the MRSA burden within HCFs, little is known about the changing dynamics of MRSA in the com- Results munity and how these changes are affecting nosocomial transmis- We analyzed a convenience sample of 97 clinical MRSA isolates from sion. Understanding the dynamics of MRSA at the interface of the six hospitals in northeast Florida. Overall, 48 (50%) were classified as hospital and in the community is critical to evaluating current pre- spa type t008, 26 (27%) as t002, 23 (24%) as other types/unknown vention measures and designing effective interventions . types (Table 1). Out of the 59 isolates from Jacksonville, 42 (71%) Molecular characterization methods are an essential component were t008, 4 (7%) were t002, and 13 (22%) were other/unknown in the study of pathogen epidemiology and allow discrimination types. While information regarding isolate source was not specif- between isolates of epidemiologically important organisms. A variety ically requested, two of the Jacksonville facilities reported that 25 of molecular typing methods can be independently used to classify samples (42.4%) were from inpatients. The remaining 34 isolates MRSA strains, including pulsed-field gel electrophoresis (PFGE), could have originated from inpatients or outpatients. Among the multilocus sequence typing (MLST), or spa-typing by sequencing 38 isolates from Gainesville, 6 were t008 (16%), 22 were t002 the highly polymorphic Staphylococcus protein A (spa) gene . CA- (68%), and were 10 (26%) other types/unknown. Figure 1 sum- MRSA strains in the United States are most commonly in a genetic marizes distribution of spa types across hospitals. Compared to cluster designated as PFGE type USA300, MLST type ST8, or spa- Gainesville, t008 isolates were more prevalent in Jacksonville (p , 21,22 0.0001). Furthermore, among all sampled Jacksonville hospitals, the type t008 . Additionally, Healthcare-Associated strains most com- monly cluster in PFGE type USA100, also recognized as spa-type proportion of t008 isolates within each facility was not significantly different (p 5 0.156) compared to other types. t002. Spa type distribution and frequencies have been used in a number of studies to characterize MRSA epidemics since they pro- After processing the next-generation sequencing data, a final mul- tiple alignment of 40 t008 MRSA isolates (26 from Jacksonville, four vide moderate discrimination and possess high throughput and good 12,23–26 inter-laboratory reproducibility . Spa typing can characterize S. from Gainesville and 10 from GenBank) including 3,249 SNPs was generated (Supplementary file 1). Eleven of the 26 Jacksonville iso- aureus isolates within a defined setting and identify potential epide- lates (42.3%) were confirmed to have come from inpatients. The miological clusters by providing limited discrimination within a clo- remaining 15 isolates may have originated from inpatients or out- nal complex. However, greater discrimination such as provided with patients. A preliminary analysis of phylogenetic signal using a trans- whole-genome sequencing (WGS) and single nucleotide polymorph- ition/transversion vs. divergence graph and the Xia’s test (p , ism (SNP) analysis would be useful, for example to discern outbreak 0.0001) did not show evidence for substitution saturation. This from non-outbreak strains in settings where sporadic strains of a indicated that enough signal for phylogenetic inference existed specific spa-types (i.e. t008) are common. Molecular clock-calibrated phylogenetic trees make it possible to investigate the ancestral population from which a given pathogen originated and the evolutionary as well environmental factors con- Table 1 | Frequencies of spa-types across seven northeast Florida tributing to successful epidemic spread . Such studies have mostly hospitals, collected during 2010 (n 5 97) been limited to fast evolving viruses because they require genomic sequences, sampled over relatively short time intervals, displaying Spa-type Number Percent 28–31 sufficient diversity in order to infer reliable phylogenies . t002 26 26.8% However, the recent application of next generation full-genome t007 1 1.0% sequencing and phylogenetic analysis to the study of bacterial patho- t008 49 50.5% gens has demonstrated the ability to discriminate between extremely t010 1 1.0% 32–34 similar organisms collected within a short timeframe . Addi- t024 1 1.0% tionally, high-resolution phylogenetic and phylogeographic (phylo- t045 4 4.1% t064 1 1.0% dynamic) analyses based on genome-wide SNP data are a powerful t067 1 1.0% tool to infer the origin and test spatiotemporal hypotheses of MRSA 32,33 t078 1 1.0% spread . Such analyses can reveal temporally and spatially related t105 2 2.1% isolates, elucidate the epidemiology of MRSA transmission in the t1062 1 1.0% community, and identify reservoirs when combined with epidemio- t1107 1 1.0% logical data. In addition, this facilitates an understanding of pathogen t121 1 1.0% success in terms of emergence, virulence, and epidemics . Currently, t2229 1 1.0% whole-genome analysis of S. aureus has largely been limited to in t242 1 1.0% 35 36 t539 1 1.0% vitro drug resistance , bacterial population size , and geographic t688 1 1.0% distribution of different strains . t746 1 1.0% This pilot study was designed to investigate whether MRSA cir- Unknown 2 2.1% culation in northeast Florida hospitals is the result of hospital- Total: 97 100% specific epidemics (i.e. endemic transmission) or heterogeneous SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 2 www.nature.com/scientificreports the data set contained enough information for reliable phylogeny inference. The optimal evolutionary model as selected by the Akaike information criterion using MEGA5 was the general time reversible (GTR). Figure 2 depicts the GTR maximum-likelihood (ML) tree, including bacterial sequences from Jacksonville and Gainesville, shows no distinct clustering of hospital-specific clades. All trees esti- mated with other methods and including GenBank reference sequences are available as supplementary material and showed exactly the same pattern. Strict and relaxed molecular clock models, as well as different demographic coalescent models of effective bacterial population size (Ne) over time, interpreted as the number of effective infections (i.e. 30,41 those contributing to onward transmissions) , were tested to infer Figure 1 | Distribution of MRSA spa types across six different hospitals the demographic history of t008 MRSA strains in northeast Florida. in Jacksonville (J) and one in Gainesville (G), both in northeast Florida, We evaluated two parametric (constant effective population size and USA, collected during 2010 (n 5 97). exponential population growth), and one nonparametric estimate (Supplementary Figure S1, and Supplementary Table T1). Likelihood (Bayesian skyline plot) of bacterial population size over time. The mapping analysis reported , 25% of star-like signal (phylogenetic Bayes Factor (BF) strongly favored the relaxed over the strict molecu- noise) and no significant signal for recombination was detected (PHI lar clock model (BF5 42.4), indicating that different bacterial strains test p5 0.82, supplementary figure S2 and S3), indicating overall that evolved at significantly different rates (Table 2). In addition, analysis Figure 2 | ML phylogenetic analyses of MRSA t008 in northeast Florida by HCF. Colored tip branches correspond to healthcare facility from which the isolate was obtained. The numbers along the monophyletic branches correspond to bootstrap values (500 replicates). Branch lengths in nucleotide substitutions per site were scaled according to the bar at the bottom of the tree. SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 3 www.nature.com/scientificreports data to test molecular epidemiology hypotheses of bacterial spread Table 2 | Bayes factor between strict (SC) and relaxed (RC) within a localized healthcare network. These methods can be lever- molecular clock aged to identify emerging epidemics, detect outbreaks, and study a b antibiotic resistance and virulence, as has been recently demon- Clock Marginal likelihood BF 45,46 strated for S. aureus . As rapid sequencing technologies are refined SC 29843.445 and bioinformatic tools are operationalized, we will continue to RC 29822.237 42.416 observe more examples of the utility of WGS and phylogenetic ana- a. The selected molecular clock model (H 5 Null hypothesis, H 5 Alternative hypothesis) is lysis in routine practice. Ultimately, our findings highlight the clear 0 1 highlighted in gray. utility of such methods in seeking to understand, and control, com- b. BF5 Bayes Factor. 6 . BF . 2 indicates positive evidence against the null hypothesis; 10 . BF munity and regional spread of resistant microorganisms. . 6 indicates strong evidence against the null hypothesis, BF . 10 indicates very strong evidence against the null model. We identified a statistically significant difference in the overall distribution of spa-types t008 and t002 among a convenience sample of clinical MRSA isolates from Gainesville and Jacksonville HCFs of the three demographic models showed positive evidence against (Figure 1). MRSA spa type t008 accounted for 71% of isolates the null hypothesis of constant bacterial population size in favor of obtained from Jacksonville compared to 16% of strains from the exponential growth model (BF 5 2.7), which also outperformed Gainesville (Table 1). This is a striking increase from the studies the Bayesian skyline plot model (BF 5 3.9) (Table 3). The temporal conducted in 2003–2004 , where it was found that t008 strains scale of MRSA evolution was inferred using an independent estimate accounted for only 20% of the isolates, while t002 made up the of MRSA genome-wide SNPs evolutionary rate of 7.573 10 , with a majority of isolates. Additionally, a national average of 31.3% of 95% highest posterior density (95% HPD) interval of 5.11 – 10.2 3 25 32 t008/USA300 were reported in invasive infections from participating 10 nucleotide substitution per SNP site per year . The reconstruc- ABC regions reported by the CDC in 2008 . These differences must tion of MRSA t008 demographic history estimated the origin of the be interpreted with care, however, as they may be attributable to the epidemic in mid-1960s, followed by an exponential increase in effec- HCFs’ respective patient populations or our sampling strategy. tive population size, consistent with the known epidemiology of Unexpectedly, phylogeographic analysis of t008 strains demon- MRSA in the United States (Figure 3). By using the estimated growth strated a lack of clustering, i.e. no hospital-specific clades rate of MRSA from the exponential population growth model (0.34, (Figure 2). It was hypothesized that our analysis would identify 95% HPD5 0.14 – 0.57) and estimates of colonization and infection monophyletic branches of isolates clustering within hospitals, sig- duration ranging from 8.5 months to one year, we were able to nifying endemic transmission or distinct community-based determine the potential reproductive number (R0)of S. aureus 42,43 sub-epidemics in populations constituting the facility’s patient popu- within our sample . R0 estimates were not based on traditional lation. The lack of clustering within facilities alludes to other trans- SIR epidemic models; instead, we utilized the estimated Ne and mission dynamics at work. It was also expected that gene flow of t008 growth rate from phylodynamic analysis to determine the R0 for isolates, as measured by the number of observed bacterial migrations infections and colonizations in the population. This method has in the phylogenetic tree, would be observed between specific HCFs, previously been employed by Pybus et al. to estimate the R0 of either in close proximity and/or serving similar populations. Hepatitis C Virus . R0 estimates for MRSA USA300 R0 ranged from However, this was not apparent among our sample, where bacterial 1.24 (95% HPD 1.10 – 1.40) to 1.34 (95% HPD 1.14 – 1.57). strains were randomly distributed among different hospitals without To assess the phylogeographic pattern of MRSA t008 in northeast any restricted or directional flow. It is possible that the complexity of Florida, a discrtete character corresponding to each isolate’s respect- the healthcare network within our study area explains the diversity in ive hospital was assigned to the tip branches of the ML genealogy. hospital distribution among phylogenetic clades and the lack of gene Bacterial gene flow among hospitals was then traced on the basis of flow. For example, the referral system between hospitals and the the maximum parsimony reconstruction of the ancestral characters presence of numerous long-term care, rehabilitation, and long-term (Figure 4a). A randomization test showed that the null hypothesis of acute care facilities is so extensive and geographically dispersed that panmixia, i.e. absence of MRSA t008 population subdivision among sub-epidemics propagated through the intermixing of HCF patient different hospitals, could not be rejected (Figure 4b). In addition, the populations and the community are spatiotemporally isolated and observed bacterial gene flow among the different hospitals was not require a larger sample size to detect. This model would suggest statistically significant (Table 4), indicating a relatively homogenous multiple CA and HA reservoirs intermixing and contributing to epidemic across northeast Florida with no directional gene flow the overall microbial burden on the HCF. The hypothesis is also between specific hospitals. supported by the exponential growth of Ne inferred from the Discussion MRSA phylogeny utilizing the Bayesian coalescent framework This study was designed to provide an initial ‘‘snapshot’’ of MRSA (Figure 3). Ne is a measure of genetic diversity and can be interpreted distribution and phylogeny within a major metropolitan area, and to as the number of bacterial genomes effectively contributing to the permit comparison of these isolates with isolates from a smaller subsequent generation . In regards to MRSA, Ne is expected to neighboring city. What emerges is the power of coupling high-reso- correlate with the number of infected and/or colonized individuals. lution phylogenetics and phylogeography with genome-wide SNP However, it is important to note that since individuals may be Table 3 | Bayes factor between different coalescent models (constant population size, exponential growth, and Bayesian skyline plot) BF Demographic model Marginal likelihood S.E. Constant vs. Exponential Constant vs. BSP Exponential vs. BSP Constant 29822.2 1/2 0.25 2.7 1.2 3.9 Exponential 29820.9 1/2 0.24 BSP 29822.8 1/2 0.24 a. The selected coalescent model is highlighted in gray. b. BF5 Bayes Factor. 6 . BF . 2 indicates positive evidence against the null hypothesis; 10 . BF . 6 indicates strong evidence against the null hypothesis, BF . 10 indicates very strong evidence against the null model. SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 4 www.nature.com/scientificreports Figure 3 | Bayesian skyline plots of MRSA t008 in Jacksonville. Non-parametric curves of MRSA effective population size (Ne) over time were estimated by employing a Bayesian framework. Genetic distances were transformed into a timescale of years by enforcing a relaxed molecular clock model. Solid lines indicate median (blue), and 95% upper and lower high posterior density (HPD) estimates of Ne (black). simultaneously infected and/or colonized with multiple strains or As in any other study based on epidemiological models, it is not transmit the bacteria, such a correlation is not necessarily 1 5 1 . important to highlight some of the potential limitations of our approach. First, results should be interpreted in light of our conveni- By reconstructing the demographic history of bacterial popu- lation, it was also possible to estimate R0 value for MRSA. S. aureus ence sampling strategy, which increased participation from HCFs at the cost of detailed clinical and epidemiological information. A delib- demonstrates several clinical presentations ranging from SSTIs to severe invasive disease. Additionally, attempts to accurately estimate erately planned isolate sampling strategy in future studies will be R0 values are confounded by the existence of colonization states, necessary to strengthen the validity of these initial findings. How- during which individuals can be transiently or persistently colonized ever, the observation that individuals hospitalized and/or utilizing 18,42,48 by the bacteria. R0 estimates have ranged from 0.60 to 1.0 . Our the emergency departments were infected with a heterogeneous estimates are slightly higher, in agreement with previous evidence MRSA population remains valid whether the isolates originated from that the reproductive rate for CA-MRSA strains may be, in fact, inpatient or outpatient populations. Second, although coalescent- higher than that of HA-MRSA strains . based phylodynamic analysis does not require a large sample size, 47,52,53 Overall, our study shows the significant implications of utilizing uniform spatiotemporal sampling is important , and it is pos- sible that our convenience sample did not meet this criterion. Finally, phylodynamic methods for the study of MRSA t008 molecular epi- demiology. While we were limited by lack of clinical and demo- the demographic models based on phylodynamic analysis used here assume no population structure and neutral evolution. The violation graphic data from participating HCFs, our analysis included representative clinical isolates obtained from a similar time point of either assumption can bias the reconstruction of the population demographic history and ultimately our inference of R0. However, and from all acute care facilities serving a population of well over one million persons within a common geographic region. A recent phylogenetic and gene flow analysis did show an overall panmic- tic population (i.e. no population subdivision), suggesting that at point prevalence study of HAIs conducted in Jacksonville, FL in 2009 identified 6.0% of patients with one or more HAIs on the day of the least the first of these assumptions may hold true for the present work. survey . S. aureus was the most common pathogen, causing 15.5% of HAIs. These results were similar to national prevalence estimates In conclusion, our findings suggest complex transmission dyna- obtained 30 years prior from the Study of Efficacy of Nosocomial mics of MRSA between the community and healthcare setting with a Infection Control . Contrastingly, other studies have demonstrated heterogeneous distribution of isolates across healthcare facilities. The that the incidence of S. aureus HAIs in certain geographic areas have overall picture of MRSA emergence and distribution drawn herein been steadily decreasing since 2005 . These variations in MRSA- provides a base for subsequent studies incorporating a structured related HAI incidence may result from varying infection prevention sampling strategy, phylogenetic analysis of genome-wide SNP data, practices, surveillance methods, or strain distribution. Overall, HAI and corresponding clinical and demographic data. Most impor- incidence remains high despite the widespread implementation of tantly, our analysis shows how the application of phylodynamics to comprehensive infection control programs. In this setting, applica- microbial genomics has the potential to track the emergence and tion of this phylodynamic/phylogeographic approach provides a demographic history of MRSA strains, testing molecular epidemi- powerful tool to tease apart the various components of MRSA trans- ology hypotheses at a resolution difficult to obtain with alternative mission within communities, which is essential for the development molecular typing methods. Microbial phylodynamic analysis may of effective interventions. be employed to inform control strategies to prevent nosocomial SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 5 www.nature.com/scientificreports Figure 4 | MRSA t008 phylogeographic patterns in Jacksonville. Phylogeographic analysis using a rooted ML genealogy inferred for 26* sequences from Hospitals J.a, J.c, J.d, J.e, and J.f. A. The most parsimonious reconstruction (MPR) of the state of origin for each internal node (ancestral sequence) in the tree is indicated by the color of the subtending branch according to the legend in the figure. Equivocal branches indicate multiple MPRs. *Note: The four G.a sequences were omitted from the ML genealogy. B. Tree length distribution of 10,000 trees obtained by random joining-splitting. The arrow points to the number of observed migrations in the ML tree. metropolitan area; Gainesville, with a population of 125,000, is in north-central transmission and/or constant reintroduction of CA-MRSA strains Florida, approximately 70 miles to the southwest of Jacksonville. Isolates were from the community into HCFs. completely de-identified, with no available clinical or demographic information. The study protocol was reviewed and approved by the University of Florida Institutional Methods Review Board. Data collection and ethics statement. We obtained a convenience sample of clinical MRSA isolates from invasive and non-invasive infections sent for microbiological Sample processing and spa typing. Cultures of MRSA isolates were processed and culture at six tertiary acute care hospitals in Jacksonville, FL (representing all major an aliquot was frozen at 280uC. Each isolate was grown in liquid subculture hospital systems) and one tertiary acute care hospital in Gainesville, FL during a one overnight at 37uC. Genomic DNA (gDNA) was isolated from pelleted bacteria week period in September of 2010. Jacksonville is located on the northeast coast of using the Roche High Pure PCR kit following the standard protocol for isolation Florida, with a population of approximately 1.3 million in the greater Jacksonville of nucleic acids from bacteria (Roche Applied Science, Indianapolis, IN). The quality of the gDNA extracted was determined through gel electrophoresis and quantity was determined using the Nanodrop 2000 (Fisher ND-2000). Molecular Table 4 | MRSA metapopulation structure test typing of these strains was done by spa typing. PCR was used to amplify the spa repeat region using 1 ml gDNA, 1XGoTaq Green Master Mix and 10pmol of each a b Migration direction Observed gene flow p-value primer, spa-1113f (59- TAA AGA CGA TCC TTC GGT GAG C -39)and spa- 1514r (59- CAG CAG TAG TGC CGT TTG CTT -39). The primers are numbered J.e-J.d 2 0.9474 from the 39 end of the primer on the forward strand of a reference S. aureus J.e-J.c 1 0.9812 sequence (GenBank accession no. J01786; spa-1113f [1092–1113] & spa-1514r J.d-J.f 1 0.8020 [1534–1514]). Thermal cycling conditions consisted of a hot start (5 min at 80 uC) J.f-J.e 1 0.9988 followed by 35 cycles of denaturation (15 s at 94uC), annealing (30 s at 58uC), and J.f-J.a 1 0.9992 extension (60 s at 72uC), with a single final extension of 10 min at 72uC. Gel J.a-J.c 1 0.9972 electrophoresis was used to determine PCR success and all PCR products were Sanger sequenced in both directions. Nucleotide sequences were analyzed by using a. Number of migrations observed in the ML tree. Ridom StaphType software and synchronized with SpaServer b. p . 0.01 indicates that the null hypothesis of panmictic spread (not directional gene flow among (www.spaserver.ridom.de) in order to assign the spa type according to number of different hospitals) cannot be rejected. tandem repeats and length variation in the spa gene . SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 6 www.nature.com/scientificreports Next-generation sequencing and data analysis. To provide better discrimination 5. Hubben, G. et al. Modelling the costs and effects of selective and universal hospital within spa type t008 isolates, we conducted next generation WGS. After confirmation admission screening for methicillin-resistant Staphylococcus aureus. PloS one 6, of quality and determination of quantity, 5 mg of each isolate gDNA was sequenced e14783 (2011). on the Illumina HiSeq 2000 sequencing system. Libraries were constructed for each 6. 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Nosocomial infections in U.S. hospitals, 1975-1976: estimated frequency by selected characteristics of patients. The American Journal of Medicine 70, 947–59 (1981). Additional information 51. Kallen, A., Mu, Y. & Bulens, S. Health Care–Associated Invasive MRSA Infections, Supplementary information accompanies this paper at http://www.nature.com/ 2005-2008. JAMA: the Journal of the American Medical Association 304, 641–648 scientificreports (2010). Competing financial interests: MP and MS are partially supported by the NIH/NCRR 52. Pybus, O. G., Rambaut, A. & Harvey, P. H. An integrated framework for the CTSI award to the University of Florida UL1 RR02989, and by the NIH-NINDS grant R01 inference of viral population history from reconstructed genealogies. Genetics NS063897-01A2. MR is supported in part by the UF CTSI under a grant by the NIH/NCRR 155, 1429–37 (2000). Clinical and Translational Science Award UL1 RR029890. This study was also supported by 53. Drummond, A. J., Rambaut, A., Shapiro, B. & Pybus, O. G. Bayesian coalescent seed funding from the University of Florida Emerging Pathogens Institute. The authors inference of past population dynamics from molecular sequences. Molecular report no competing financial interests. Biology and Evolution 22, 1185–92 (2005). License: This work is licensed under a Creative Commons 54. Harmsen, D. et al. Typing of methicillin-resistant Staphylococcus aureus in a Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this university hospital setting by using novel software for spa repeat determination license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ and database management. Journal of Clinical Microbiology 41, 5442–5448 (2003). How to cite this article: Prosperi, M. et al. Molecular Epidemiology of 55. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler Community-Associated Methicillin-resistant Staphylococcus aureus in the genomic era: transform. Bioinformatics (Oxford, England) 25, 1754–60 (2009). a Cross-Sectional Study. Sci. Rep. 3, 1902; DOI:10.1038/srep01902 (2013). SCIENTIFIC REPORTS | 3 : 1902 | DOI: 10.1038/srep01902 8

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