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Characterization of Community-Acquired Methicillin-Resistant Staphylococcus aureus by Pulsed-Field Gel Electrophoresis, Multilocus Sequence Typing, and Staphylococcal Protein A Sequencing: Establishing a Strain Typing Database by Jill Carolyne Roberts A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Global Health College of Public Health University of South Florida Co-Major Professor: Andrew Cannons, Ph.D. Co-Major Professor: Boo Kwa, Ph.D. Philip Amuso, Ph.D. Azliyati Azizan, Ph.D. Burt Anderson, Ph.D. Date of Approval: March 20, 2006 Keywords: S. aureus, PFGE, MLST, spa typing, genotyping Copyright 2006, Jill Carolyne Roberts
Dedication I would like to dedicate this dissertation to my mother Carolyne Roberts. Without your support I would never have realized and greatly exceeding my educational goals. Your faith in my ability to accomplish any goal, encouragement to strive for independence, strength of character, and resilience have contributed immensely to my success. A daughter cannot wish for a better role model and for that you will always have my deepest respect and love.
Acknowledgements I would like to thank Dr. Andrew Cannons for his guidance and support throughout this project. In particular I am grateful for his encouraging attendance and presentation of my research at several local and national meetings. I would also like to thank Dr. Boo Kwa for his continued support not only in this research but in my Masters degree research. A special thanks to Dr. Philip Amuso and Dr. Azliyati Azizan for serving on both my supervisory and dissertation committees and to Dr. Burt Anderson for serving as outside committee member for my defense. To all the members of the Center for Biological Defense laboratory for continued support and friendship and especially Dr. Vicki Luna for acquiring nearly all the organisms used in this study. A special thanks is also owed to Dr. Aparna Tatavarthy for allowing me to shadow her to learn many techniques, for countless words of advice on this research, for reviewing this manuscript, and for her friendship. Finally, I owe a huge debt of gratitude to Ms. Kealy Peak for her superb microbiological skills, for endless conversations on strain typing and other microbiology topics, and most importantly for her support and friendship.
i Table of Contents List of Tables iv List of Figures v Abstract vi Introduction 1 Impact of Staphylococcus aureus 1 Staphylococcus aureus Pathogenesis 3 Role of S. aureus in Bioterrorism 6 Community-acquired Methicillin-resistant S. aureus (CA-MRSA) 8 Techniques for Subtyping S. aureus 10 Pulsed-field Gel Electrophoresis for Subtyping Methicillin-resistant S. aureus 12 Multilocus Sequence Typing of S. aureus 15 Staphylococcal Protein A Gene Sequencing ( spa Typing) 18 Objectives 22 Materials and Methods 23 S. aureus Isolates 23 Pulsed-field Gel Electrophoresis 24 Virtual Digest to Identify Secondary Enzymes for S. aureus PFGE 26
ii DNA Isolation for MLST and spa Typing 26 PCR for Multilocus Sequence Typing 27 PCR for spa Typing 28 Wizard PCR Clean-up Kit for MLST and spa Typing 29 Preparation of DNA Sequencing Reactions for MLST and spa Typing 30 Results 32 Staphylococcus aureus BioNumerics Database 32 Analysis of S. aureus Epidemic Clone USA 300 in S. aureus PFGE Database 38 Analysis of S. aureus Epidemic Clone USA 100 in S. aureus PFGE Database 39 Use of Restriction Digestion of the MW2 Genome to Identify Secondary Enzymes for S. aureus PFGE 40 Analysis of the PFGE Patterns of 12 USA 300 Epidemic Clone Isolates Using SmaI, EagI, and Sac II 45 Analysis of the PFGE Patterns of Seven Pairs of Identical Isolates Using Sma I, EagI, and Sac II 49 Selection of CA-MRSA Isolates for Multilocus Sequence Typing 53 PCR Amplification of Housekeeping Genes for MLST 53 DNA Sequencing, Alignment, and Assigning of Alleles and Sequence Types for CA-MRSA MLST 56 Comparison of PFGE Data and MLST Data for 30 CA-MRSA Isolates 59 PCR Amplification of spa Region of CA-MRSA 62 DNA Sequencing, Alignment, and Assigning of Repeats and spa Types for CA-MRSA spa Typing 65
iii Comparison of PFGE, MLST, and spa Typing Data for 30 CA-MRSA Isolates 68 Discussion 71 References 88 Appendices 108 Appendix A 109 About the Author End Page
iv List of Tables Table 1. Summary of S. aureus toxin genes 6 Table 2. Advantages and disadvantages of pul sed-field gel electrophoresis 14 Table 3. Control strains 24 Table 4. MLST and spa typing primers 29 Table 5. Summary of results for all isolates tested 39 Table 6. Summary of results for all isolates tested 40 Table 7. Virtual digestion of S. aureus MW2 genome 42 Table 8. Multilocus sequence typing alleles and sequence types for 30 S. aureus isolates 58 Table 9. Comparison of S. aureus MLST alleles 59 Table 10. MLST Sequence Type Information 60 Table 11. Summary of spa repeats and spa types 67 Table 12. Summary of spa Type Information 68
v List of Figures Figure 1. Pulsed-field gel electrophoresis of Staphylococcus aureus 33 Figure 2. Dendrograms of sporadic isolates and epidemic controls 34 Figure 3. USA 300 isolates demonstrating 100% identity by Sma I PFGE 46 Figure 4. USA 300 isolates demonstrating 100% identity by EagI PFGE 47 Figure 5. USA 300 isolates demonstrating 100% identity by Sac II PFGE 48 Figure 6. Seven pairs of identical isolates by Sma I PFGE 50 Figure 7. Seven pairs of isolates further distinguished by EagI PFGE 51 Figure 8. Seven pairs of isolates further distinguished by Sac II PFGE 52 Figure 9. BioNumerics Analysis 54 Figure 10. PCR amplification of the internal fragment of the gmk gene for MLST 55 Figure 11. Clustal W (1.82) multiple sequence alignment for arc housekeeping gene fragment 57 Figure 12. BioNumerics analysis and MLST data 61 Figure 13. Amplification of spa region 63 Figure 14. Amplification of spa region 64 Figure 15. Clustal W multiple sequence alignment for spa typing 66 Figure 16. BioNumerics analysis including PFGE, MLST, and spa data 69 Figure 17. Summary of PFGE pulsotypes, spa types, and sequence types for 30 CA-MRSA isolates 70
vi Characterization of Community-Acquired Methicillin-Resistant Staphylococcus aureus by Pulsed-Field Gel Electrophoresis, Multilocus Sequence Typing, and Staphylococcal Protein A Sequencing: Establishing a Strain Typing Database Jill Carolyne Roberts Abstract Staphylococcus aureus has long been recognized as a leading cause of nosocomial infection. However, several recent publications have demonstrated this pathogen as the cause of community-acquired severe wound infections and necrotizing pneumonia in otherwise healthy individuals. These highly virulent endemic clones have been reported in several locations in the United States and Canada. The rapid spread of the organism, the ability of certain clones to cause serious infection, and the antibiotic resistance of the endemic clones, illustrates the importance of infection control measures. In this study we examined three S. aureus typing techniques; pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and Staphylococcal protein A (spa) sequencing for subspeciation of community-acquired methicillin-resistant S. aureus (CA-MRSA). It is hypothesized that PFGE will result in a higher level of discrimination among the strains, while MLST and spa typing will result in highly portable data that lacks the discriminatory power of PFGE. Thirty CA-MRSA isolates that were obtained from Florida and Washington State were characterized by molecular typing methods. Whole genome restriction analysis was performed by PFGE using the Sma I enzyme. Sequence-
vii based typing analyses, MLST and spa typing, were performed by polymerase chain reaction (PCR) followed by sequencing. PFGE data was analyzed using the BioNumerics software package and sequence-based data was analyzed using DNAstar MLST Alleles were assigned using the online MLST database (www.mlst.net) and spa types were assigned using the Ridom SpaServer (www.ridom.de/spaserver). Molecular characterization of the 30 isolates resulted in 21 pulsotypes, four MLST sequence types (STs), and six spa types. Combining data from both MLST and spa typing resulted in only seven strain categories, many of which grouped isolates that are not epidemiologically linked. These data demonstrate that techniques such as MLST and spa typing are not well suited for tracking isolates with limited evolutionary diversity such as the CA-MRSA epidemic clones.
1 Introduction Impact of Staphylococcus aureus Staphylococcus aureus is a Gram positive, nonmotile cocci that is one of the leading causes of nosocomial infection. Approximately 2% of all patients admitted to the hospital will develop S. aureus infection (66), which is a major public health concern due to the associated morbidity, mortality, and cost of care. Infection with S. aureus results in twice the length of stay, deaths, and medical costs as compared to patients without infection who are receiving the same treatment (94). The average cost of hospital stay in a study of patients in New York City hospitals was $13,263 without complications versus $32,100 for patients with hospital-acquired S. aureus infection (94). Furthermore, the economic impact is increasing due to the spread of antibiotic resistance, particularly methicillin resistance, among S. aureus isolates. A 2004 report from the National Nosocomial Infections Surveillance (NNIS) System, a network of healthcare agencies which report nosocomial infection surveillance data, demonstrated that nearly 60% of all S. aureus isolates in US hospitals are methicillin resistant (11). The cost of treating infections caused by methicillin-resistant S. aureus (MRSA) is approximately $2,500 more than treating susceptible S. aureus due to the increased length of stay and more expensive antibiotic treatment (94). Among the many types of disease caused by S. aureus are localized skin infections including carbuncles, furuncles, impetigo, and sties, and one disseminated skin
2 condition known as scalded skin syndrome. More serious conditions caused by S. aureus include septicemia, wound infection, post-surgical infection, pneumonia, osteomyelitis, toxic shock syndrome, and endocarditis (96). NNIS surveillance data from 1990 to 1996 demonstrated that S. aureus was the most common cause of nosocomial pneumonia and surgical site infection, and the second leading cause of nosocomial bloodstream infections (10). Furthermore, S. aureus is one of the leading causes of food-borne illness (63). Most cases of food-borne illness result from the toxin produced by the organism and therefore there is little surveillance data to elucidate the true contribution of S. aureus to the estimated 76 million cases of food-borne illness that occur annually in the United States (63). However, in at least one documented case, MRSA organism was spread from a food handler to restaurant patrons via the gastrointestinal route (52). S. aureus is found in the anterior nares of both adults and children with approximately one-third of the population co lonized during any given time (19, 67, 85). Among the carriers, between three and 10% of individuals will be colonized with MRSA (19, 46, 67, 85). The rates of MRSA carriage are highest among individuals with human immunodeficiency virus (HIV), intravenous drug users, patients with open abscesses, and those persons who were recently hospitalized (85). However, the number of children colonized with MRSA, who have no potentia l risk factors for MRSA carriage, has increased significantly in the past four years (19, 46). The emergence of these community-acquired MRSA (CA-MRSA) strain s is of particular concern because colonization typically precedes infection, with greater than 80% of infecting isolates originating from the nose (18, 19). Asymptomatic carriers of S. aureus can be a source of
3 spread of the organism in both the community and hospital setting. However, not all S. aureus strains are equal in their ability to cause serious disease. Staphylococcus aureus Pathogenesis Complete genome sequencing has been performed on seven S. aureus strains, including four MRSA isolates. Comparison of these genomes indicates that S. aureus has a stable core of vertically transmitted genes, present in all seven genomes, but also frequently acquires genes by horizontal transfer (66). Approximately 25% of the S. aureus genome consists of genes that are horizontally transferred by mobile elements including bacteriophages, chromosomal cassettes, plasmids, and transposons (66). Many of these genes encode virulence and resistance determinants (44, 66). Further information on these determinants has been elucidated by comparison of the seven S. aureus genomes to a related but less pathogenic species, Staphylococcus epidermidis (66). These studies suggest that the pathogenesis of S. aureus is largely due to the presence of MSCRAMMS (microbial surface components recognizing adhesive matrix molecules), capsule production, antibiotic resistance genes, and toxins (66, 96). MSCRAMMS are bacterial proteins present in a number of pathogenic organisms that aid in binding to human tissues and artificial surfaces. MSCRAMMS have been identified in S. aureus that bind to fibronectin, fibrinogen, and collagen components of the host cell wall (35). Most strains produce two fibronectin binding proteins, FnBPA and FnBPB which are involved in host cell attachment and binding to plasma clots and to artificial surfaces (35). Fibrinogen binding is mediated by two proteins, ClfA and ClfB, that are not only involved in the same att achment processes as the fibronectin-binding proteins, but also seem to have a role in endocarditis (35). Collagen binding, mediated by
4 the Cna protein, is not a characteristic of most isolates. However, Cna is necessary for binding to collagen and therefore has an important role in septic arthritis caused by S. aureus (35). The classical experiments by Griffith illustrating the genetic transformation principle using Streptococcus pneumoniae also demonstrated the role of the bacterial capsule in pathogenesis. These experiments demonstrated that unencapsulated nonvirulent S. pneumoniae isolates could acquire the ability to form capsule if mixed with encapsulated strains and these strains could th en cause pneumonia in a mouse model (68). Although considered a seminal contribution to the field of genetics, this experiment also highlighted the role of the capsule in S. pneumoniae virulence. Although often overlooked as a virulence factor, it is of particular note that all of the organisms responsible for septic meningitis, Neisseria meningitidis S. pneumoniae and Haemophilus influenzae produce polysaccharide capsules (96). The S. aureus capsule has several roles in pathogenesis including host cell binding via MSCRAMMS as described above, biofilm formation, and immune system avoidance. Although the MSCRAMMS likely play a role in biofilm formation, a number of capsular genes are also involved (35, 96). The type of capsule present on a particular strain, determining the serotype of that isolate, has been related to virulence (118). Finally, the staphylococcal protein A component of the S. aureus capsule has been shown to bind to antibodies without leading to lysis of the cell (96). This antibody coat may allow the organism to escape the immune response (96). One of the most well studied areas of S. aureus pathogenesis is its array of antibiotic resistance genes. The organism has acquired resistance by mutation of genes
5 on the chromosome as well as transfer of resistance determinants from other organisms by conjugation, transformation, and transduction (44, 51, 62). Although resistance to many antibiotics is common in S. aureus methicillin resistance is of particular concern due to its public health impact in terms of mortality, morbidity, and cost. MRSA was reported in European hospitals in the early 1960s immediately following the introduction of methicillin to clinical practice (13). Resistance occurs in these isolates due to the production of a penicillin-binding protein, PBP 2a, that has a low affinity for binding lactam antibiotics (13). The PBP 2a protein thus performs the cell growth functions of the high-affinity proteins while simultaneously providing the cell resistance to an entire class of antibiotics (13). Phylogenetic studies have demonstrated that genetic exchange has resulted in S. aureus acquiring methicillin resistance at least five times since the first isolates were described in 1960, (20, 27, 28, 31, 32) and MRSA isolates have since spread worldwide (1, 5, 15, 25, 37, 56, 58, 87, 102, 110, 122). S. aureus isolates differ in their ability to cause disease due in part to the expression of toxin genes present in their genome. Certain toxins such as PantonValentine Leukocidin (PVL) are known to cause necrotizing pneumonia and wound infections (36, 39, 50, 65, 117), while others su ch as Staphylococcal enterotoxin A and B are related to food poisoning (55, 57, 63, 69, 96, 99, 104). Many of the S. aureus toxin genes reside in four Staphylococcal pathogenicity islands (SaP1 SaP4) along with other virulence factors while some of the genes are phage or plasmid encoded (66). A summary of staphylococcal toxin genes and their function is shown in Table 1.
TABLE 1. Summary of S. aureus toxin genes Gene Location and Function Reference sea Phage encoded superantigen food poisoning Klotz et al. (2003) seb SaP1 superantigen food poisoning Klotz et al. (2003) sec 1,2,3 SaP2 3 related superantigens food poisoning Klotz et al. (2003) sed Plasmid encoded superantigen food poisoning Klotz et al. (2003) see Phage encoded superantigen food poisoning Klotz et al. (2003) seg Phage encoded superantigen gastrointestinal syndrome Klotz et al. (2003) seh Superantigen gastrointestinal syndrome Klotz et al. (2003) sei SaP3 superantigen gastrointestinal syndrome Klotz et al. (2003) sej Plasmid encoded superantigen unknown function Sumby et al. (2003) sek Phage encoded superantigen unknown function Seergev et al. (2004) sel SaP2 superantigen food poisoning Seergev et al. (2004) sem SaP3 superantigen unknown function Klotz et al. (2003) sen SaP3 superantigen unknown function Klotz et al. (2003) seo SaP3 superantigen unknown function Klotz et al. (2003) sep Phage encoded superantigen food poisoning Kuroda et al. (2001) seq SaP1 superantigen unknown function Seergev at al. (2004) seu Superantigen unknown function Klotz et al. (2004) TSST SaP1 toxic shock syndrome toxin Salyers et al. (2002) eta Phage encoded exfoliative toxin, scalded skin syndrome Salyers et al. (2002) etb Phage encoded exfoliative toxin, scalded skin syndrome Salyers et al. (2002) hla Gamma hemolysin component red blood cell lysis Kuroda et al. (2001) hlb Gamma hemolysin component red blood cell lysis Kuroda et al. (2001) hld Alpha hemolysin red blood cell lysis and tissue necrosis Kuroda et al. (2001) lukS Phage encoded PVL pneumonia, etc. Gillet et al. (2002) lukF Phage encoded PVL pneumonia, etc. Gillet et al. (2002) Role of S. aureus in Bioterrorism The deliberate contamination of food products with microbial agents including organisms and/or their toxins is a distinct possibility due to the complexity of the food service industry (63). Food is particularly vulnerable during the processing, preparation, and delivery stages (63). Staphylococcal entero toxin B (SEB), considered a select agent, can be used to contaminate food or low-volume water supplies, or alternatively it can be administered as an aerosol (63, 93). Contamination of food supplies with SEB is a lowtech means of incapacitating a large number of people by simultaneously inducing an 6
7 outbreak of vomiting and diarrhea. In addition to these symptoms, typical S. aureus food-borne intoxication includes fever, chills, headache, non-productive cough, and shortness of breath (93). In most cases, the gastrointestinal symptoms clear quickly and full recovery is likely, but the cough is long-lasting and persons are usually incapacitated for up to two weeks (93). S. aureus food poisoning could therefore be a useful tactic to a terrorist who wishes to do economic damage to a particular company or to induce panic in a particular population. A more deadly scenario occurs when SEB is aerosolized. Studies have shown that SEB acts as a superantigen that activates T-cells leading to the release of massive amounts of cytokines within the respiratory mucosa which can lead to death by severe pulmonary edema (69). Although this route of exposure is unlikely due to the technical issues involved in mass production and aeroso lizing SEB, just a few hundred cases would overwhelm the capacities of most local medical institutions to provide ventilation support (69, 93). Although most research has focused on the detection of SEB in food products both for bioterrorism detection (55) and food-borne illness detection (99), the other S. aureus toxins should also be considered as possible bioweapons. The majority of foodborne illness outbreaks are due to staphylococcal enterotoxin A (SEA) and newly described enterotoxins elicit a gastrointestinal syndrome in mouse models (57). Furthermore, S. aureus isolates capable of causing serious disease contain various combinations of toxin genes, and many isolates do not contain seb genes. Therefore detection methods for S. aureus intoxication should include a wide variety of toxins (99).
8 Community-acquired Methicillin-Resistant S. aureus (CA-MRSA) MRSA has been circulating in hospitals since the early 1960s but reports of infection in the community were relatively rare. However, in the early 1990s strains of highly virulent CA-MRSA were reported in We stern Australia (112). In recent years the incidence of CA-MRSA has been increasing with outbreaks occurring in the United States (5, 7, 12, 14, 37, 54, 70, 71, 79, 81, 112), Canada (77), and overseas (2, 25, 36, 39, 110). CA-MRSA strains differ from hospital-acquired MRSA (HA-MRSA) in their antibiotic resistance profiles, their virulence determinants, and their ability to cause disease in patients without traditional risk factors (24, 43, 119). Methicillin resistance in S. aureus is encoded by the mecA gene located in the staphylococcal cassette chromosome mec (SCC mec ) region. This region also contains the regulatory and recombinase genes. Several different SCC mec complexes have been described that contain insertions and deletions in the regulatory and recombinase genes (3, 64). CA-MRSA strains frequently carry variants of the SCC mec IV element, the smallest of the known SCC mec elements (2, 3, 64, 116). This finding has lead to a number of hypotheses concerning the spread of the CA-MRSA isolates. While one group believes that CA-MRSA isolates evolved from HA-MRSA (2), another introduces the differences in SCC mec complexes as evidence that CA-MRSA and HA-MRSA are in fact not related (116). Interestingly, the same studies report different results when comparing growth rates of CA-MRSA and HA-MRSA stra ins. In two studies CA-MRSA isolates displayed a faster doubling time than the HA-MRSA isolates (116, 123) and the authors postulate that this occurs due to the small size of the SCC mec complex. However, another study found no difference in growth rates between the two types of isolates (2).
9 Regardless of the evolutionary background of the isolates, it seems clear that MRSA is replacing methicillin-sensitive S. aureus (MSSA) in the community. Many CA-MRSA strains carry the genes for encoding PVL, a toxin involved in tissue necrosis (117). Binding of PVL to ne utrophils induces an immune cascade that includes secretion of degradative enzymes and generation of superoxide ions which promotes necrosis of tissue (123). Several studies have demonstrated a link between PVL-producing S. aureus isolates and primary skin infections and necrotizing pneumonia (7, 12, 14, 25, 36, 37, 39, 50, 54, 61, 65, 71, 77), although other virulence factors many also play a role (95). Pneumonia caused by PVL-positive CA-MRSA isolates has a high mortality rate as shown in a study of 23 patients in which 14 patients (61%) died from the disease (65). Wound infections caused by similar isolates are not usually fatal but are often accompanied by serious complications such as the need for reconstructive surgery to reverse tissue damage and prolonged stays in the intensive care unit (71). Pulsed-field gel electrophoresis (PFGE) of 957 MRSA isolates resulted in the identification of eight major lineages of S. aureus strains known as USA 100 USA 800 (70). While most were hospital-associated strains, USA 300 and USA 400 were associated with community-acquired infections (70). Recent studies have indicated that these two clones are spreading rapidly and they are now referred to as epidemic clones. USA 300 epidemic clone has been reported as a cause of serious wound infections in football players in Missouri and Connecticut among otherwise healthy, young individuals (5, 54). USA 300 is also responsible for the sharp increase in necrotizing wound infections reported in California (71) and may be responsible for another outbreak in California reported in the same time frame with similar epidemiology (75). Alarmingly,
10 studies in Texas have also demonstrated the emergence of an epidemic clone among pediatric isolates in Houston and Dallas (14, 72, 81). Although these studies did not provide conclusive evidence that the responsible clone is USA 300 in the form of pulsedfield patterns, the antibiotic resistance data, epidemiological data, and the multilocus sequence type (MLST) 8, are all consistent with USA 300 and not USA 400 (14, 72, 81). The USA 400 epidemic CA-MRSA clone, which has a distinct PFGE pattern and multilocus sequence type, has been reported as the cause of wound infections in New York and Canada (7, 77). Finally, a retrospective study of patient charts identified CAMRSA isolates in Georgia, Minnesota, and Maryland (37). However, this study provided only antibiotic resistance data and the epidemic clones can not be differentiated without genomic subspeciation. Techniques for subtyping S. aureus Bacterial subtyping is useful for a number of epidemiological and infection control practices including tracking the spread of strains of interest, determining isolates involved in outbreaks, monitoring trends in endemic isolates, and source tracking. Earlier techniques for subtyping S. aureus were phenotypic and biochemical in nature but many of these have been replaced with genomic techniques that offer higher discriminatory power. The Gold Standard for typing S. aureus isolates is PFGE. It has been shown to be more discriminatory than phenotypic techniques such as bacteriophage typing (4, 70), that is based on the susceptibility of certain strains for bacteriophage lysis detected by plaque assay, and antibiogram typing, based on antibiotic susceptibility patterns (48, 74). Phage typing was used by the Centers for Disease
11 Control and Prevention (CDC) for many years to type S. aureus isolates as it had higher discriminatory power than other techniques available at the time, despite the fact that nearly 20% of isolates were non-typeable by this method (4). The CDC has since replaced phage typing with pulsed-field typing for a number of organisms including S. aureus (4). Likewise, PFGE has replaced many biochemical typing methods such as biotyping, which uses a panel of biochemical reactions to identify strains, capsular typing, based on serotyping using monoclona l antibodies, and zymotyping, based on the electrophoretic mobility patterns of esterases (97). Early molecular techniques used for S. aureus genotyping include plasmid profile analysis, whole genome restriction enzyme analysis (REA), and ribotyping. Plasmid profile analysis is limited both by the number of isolates that lacked plasmids, and that plasmids are mobile and can therefore be lost (48). REA is limited by the large number of fragments generated in the digest that results in overlapping fragments not separated by agarose gel electrophoresis (111). Ribotyping, based on the use of probes to detect the ribosomal rRNA genes, has had mixed results in its use for typing S. aureus While the technique has been shown to be useful in a hospital outbreak of MSSA (82), it lacks the discriminatory power to differentiate MR SA strains (21, 82, 89, 111). Many PCR-based techniques have also been used for S. aureus typing (103). Multiplex PCR allows the rapid identification of MRSA versus MSSA isolates, but cannot identify strains (84). Hypervariable region PCR (HVR-PCR) can cl assify MSSA but cannot discriminate epidemic and sporadic MRSA (47, 98) and arbitrarily primed PCR (RAPD), has been useful in typing isolates from cattle (86, 111), but lacks the discriminatory power of PFGE for MRSA strains. Some techniques that have excellent discriminatory power
12 include GeneChips and whole genome sequencing, but their use is restricted due to high cost, lengthy analysis, and required technical expertise (26, 51, 62, 66). Methicillin resistance in S. aureus is believed to have been acquired at least 5 times since the 1960s and has spread throughout hospitals worldwide (27). In contrast, community-acquired MRSA have only appeared in the last decade, a relative short time period on an evolutionary scale. As such, CA-MRSA lacks the genetic diversity that is often seen in HA-MRSA (34). Due to the fact that MRSA strains, and particularly CAMRSA strains were derived from relatively fe w clones, a typing technique must be used that has sufficient discriminatory power to differentiate the strains into epidemiologically related and non-related groups (107, 111). Pulsed-field Gel Electrophoresis for Subtyping Methicillin-Resistant S. aureus The first step in PFGE involves embedding the microorganisms of interest in an agarose block to prevent shearing of th e DNA during electrophoresis. Immobilization allows the organisms to be lysed in situ followed by macrorestriction of the DNA using the restriction enzyme of choice. The Sma I enzyme is used for S. aureus PFGE as it results in 10-20 fragments, depending on the isolate, which range in size from 10 to 700 kb which can be easily separated on a PFGE gel (42). The agarose plugs containing the restricted DNA are then loaded on the gel and an electrical current is applied. The direction of the current (switch) is alternated during the electrophoresis to allow large fragments of DNA to align themselves with the current (108, 111). The run time, voltage, and switch times are experimentally determined based on the size of the fragments generated by macrorestriction. The resulting fingerprint patterns can be
13 visualized using ethidium bromide and analy zed either by sight and application of the Tenover criteria for strain typing (108), or by computer using BioNumerics GelCompar or other software packages. To date no S. aureus isolate has ever been reported that is non-typeable by PFGE and epidemiological data suggests that unique DNA fingerprint patterns are consistent with strain designations. PFGE has been used for a wide variety of applications in healthcare institutions, research laboratories, public health laboratories, and other government laboratories. The SENTRY program uses both PFGE and ribotyping to track multidrug-resistant bacteria in healthcare organizations (23). PFGE can be used to track highly virulent, epidemic clones such as USA 300 and USA 400 (12, 70, 119). DNA fingerprint patterns can be used to determine if particular strains are related to disease outcome (12, 70, 114, 119). In particular, the patterns may predict if strains are PVL positive and which SCC mec cassette they are carrying (121). PFGE may al so be used to compare methicillin-sensitive to methicillin-resistant strains (8). One of the largest programs utilizing this technique is the PulseNet program at the CDC and worldwide. PulseNet is a network of public health la boratories that submit isolates involved in suspected food-borne illness outbreaks for molecular typing and comparison to other isolates in the database (105). This technique has been used successfully to identify outbreaks, to determine the number of isolates involved, and to track the source of the outbreak (38, 90, 105). PulseNet participants must use a standardized protocol and pass rigorous quality control training before they may submit samples to the database. Currently there exists no PulseNet database for S. aureus and no standardized protocol has been developed for S. aureus PFGE. A recent publication suggests that CDC is
14 developing a database of S. aureus PFGE fingerprints aimed at tracking the CA-MRSA epidemic clones (70), however it is unclear if this database will be a part of PulseNet and therefore available for worldwide sample submission. MRSA fingerprint databases do exist in Europe, Canada, and Australia and efforts to standardize protocols have been successful. A protocol developed in Canada has shortened the S. aureus PFGE procedure from five days to 48 hours and laboratories using the procedure reported excellent reproducibility and interlaboratory comparison (76). Similarly, a harmonized European protocol was tested by 10 laboratories in ei ght countries and demonstrated sufficient interlaboratory reproducibility to track epidemic MRSA strains in Europe (78). Although PFGE has been used for a number of applications, there are as many disadvantages as advantages to using the technique (Table 2) and other molecular techniques are under investigation. TABLE 2. Advantages and disadvantages of pulsed-field gel electrophoresis Advantages Disadvantages Highly discriminatory May be too discriminatory Reproducible Time-consuming All strains can be typed Expensive Patterns are stable over time Technically demanding BioNumerics software allows comparison between laboratories Interlaboratory comparison may be difficult as software is subjective Demonstrated use in epidemiological studies Need to store marker isolate Not necessary to standardize DNA plug preparation procedure, type of agarose used, or plug digestion. Must standardize cell concentrations, lysis conditions, PFGE equipment, electrophoresis conditions, run times, and analytical methods Genomic Information not needed. Need control strain on every gel
15 Multilocus Sequence Typing of S. aureus Genome-based sequencing techniques have been explored as an alternative to gelbased techniques such as PFGE to circumvent problems associated with cost, time, technical expertise required, and interlaboratory comparison of resulting data. One of the more recent techniques used for molecular typing of S. aureus is multilocus sequence typing (MLST). MLST was designed based on the principles of multilocus enzyme electrophoresis (MLEE) in which the electrophoretic mobilities of housekeeping enzymes of isolates of interest are compared (29). In MLST, the gel analysis is bypassed by comparing nucleotides from housekeeping genes, chosen because they likely represent the stable core genome as opposed to virulence genes (31). The number of housekeeping genes that must be sequenced depends on the organism typed and the genes used for the analysis. Organisms such as Enterococcus faecalis can be typed using just two genes while typing of S. aureus requires seven housekeeping genes (29, 80). A standardized protocol has been established for S. aureus MLST which requires amplification of the genes of interest, followed by sequencing of approximately 450 base pair fragments (http://saureus.mlst.net). This fragment size was selected because the entire length of the fragment can easily be sequenced in either direction with just one reaction (113). Each gene sequence is assigned an allele and the sequences of all seven genes make up an allelic pattern. One of the major advantages of using MLST is that the gene sequences once resolved can be entered into the database and alleles assigned by comparison with sequences already entered. The same principle allows allelic patterns to be assigned as sequence types (STs) if a match of all seven alleles exists in the database. Therefore any
16 isolate that is typed can easily be compared to all previously typed isolates, allowing worldwide tracking of STs of interest (28). MLST was primarily designed for global epidemiology and the online database includes a phylogenic program, eBURST, that s ubdivides isolates that share high genetic similarity into clonal clusters (CCs) using allelic profile data (33). Isolates within each clonal cluster share 100% genetic identity at six of seven loci with at least one other member of the group (32). The founding genotype is identified parsimoniously as the genotype that differs from the highest number of other genotypes in the CC at only one locus and usually corresponds to a strain that is present in the population in high numbers due to increased fitness or random genetic drift (32, 33). The eBURST program generates radial diagrams that can be used to address basic questions about the evolutionary and population biology of bacterial species (28). S. aureus CCs are usually simple with a single founder surrounded by isolates with allelic profiles that differ from that of the founder in only one housekeeping ge ne, known as single locus variants (SLVs) (32). This is especially true of MRSA because MLST assesses variations that accumulate slowly in the population and MRSA isolates have not had much time to accumulate variations in their housekeeping genes to distinguish them from their MSSA ancestors (28, 31). The evolution of S. aureus and the acquisition of methicillin-resistance have been examined by a large number of MLST studies. Comparison of isolates from carriers were identical to those with invasive disease suggesting that S. aureus disease-causing isolates do not differ genetically from carrier strains, in contrast to other studies that suggest disease is caused by hypervirulent clones (31, 120). However, MLST
17 demonstrated that some STs are commonly found in high-risk patients, such as intravenous drug users, and these STs correlated with the disease presentation (73). In depth analysis of the nature of mutations within alleles between members of a clonal group, demonstrated that S. aureus clonal diversification occurs 15-fold more frequently by point mutation than by recombination (31). Similar fine-scale analyses indicate that methicillin-resistance in S. aureus may have been horizontally acquired at least 20 times and that these strains exist in five major lineages of S. aureus (17, 27, 113). MLST demonstrated that the early MRSA isolates were highly related to MSSA isolates (28). Furthermore, modern MRSA lineages are unrelated by eBURST analysis to the early MRSA isolates further demonstrating that mec A has been acquired by horizontal transfer (92). The horizontal acquisition of mec A into MSSA isolates has been corroborated by two separate studies that demonstrated that the first MRSA evolved from an epidemic MSSA isolate in Europe (20, 92). A number of recent studies have attempted to use MLST to demonstrate the relationship between sporadic isolates, those occurring in one or a few patients, HA-MRSA, and CA-MRSA ( 2, 16). As previously mentioned, these studies contradicted one another concerning the evolution of these epidemic clones from hospital-acquired strains (2, 16). Three recent studies highlight the use of MLST in global epidemiology to track epidemic isolat es; the identification of two major genotypes of MRSA in Asia with distinct geographic di stributions (58), the introduction of epidemic ST239 in Saudi Arabia and Romania (15), and the first detection of an epidemic MRSA clone in Spain (87). MLST using housekeeping genes has demonstrated use in defining clonal complexes (40) and in global epidemiological applications but it is time consuming and
18 is not well suited for monitoring localized outbreaks. The adaptation of the MLST protocol for use on the Light Cycler platform eliminates the need for electrophoresis and may diminish the processing time (6). Similarly, the use of DNA array technology allows scanning of all genes of interest simultaneously which although time saving is at this time cost prohibitive (115). Another variation of the technique is multilocus restriction fragment typing (MLRFT) in which housekeeping genes are amplified, digested, and visualized on an agarose gel. This technique avoids the costs involved in sequencing but does not result in the genomic data necessary for the use of MLST in global studies. While financial and technical factors may result in limited use of MLST for public health applications, further studies are needed to examine the possible use of virulence genes, in addition to housekeeping genes, to increase the discriminatory power for monitoring local outbreaks (17). Staphylococcal Protein A Gene Sequencing ( spa Typing) MLST has shown promise in studies of global epidemiology but the technique is time consuming due to the amplification and sequencing of seven genes for each isolate tested. Therefore recent efforts have aimed at the use of single markers such as clumping factor B ( clfB ) typing, coagulase ( coa ) typing, and staphylococcal protein A ( spa) gene typing for S. aureus subtyping (59, 60, 101). The three tec hniques are similar in that each requires amplification and sequencing of repeat regions. These studies have demonstrated that spa typing has the highest discriminatory power of the three genes, but it may also be used in combination with the other techniques for even higher resolution (59, 60, 101).
19 The spa gene contains a polymorphic 24-base pair variable-number tandem repeat (VNTR) region, with unknown biological func tion, immediately upstream of the region coding the C-terminal cell wall attachment sequence (100). The diversity of the repeat regions within spa is likely a result of deletion and duplication of the repetitive units and by point mutation (100). Amplification and sequencing of spa is simplified by the existence of well-conserved regions flanking the repeats (83). Repeats are easily located within a spa sequence by identifying the conserved regions. The 24-base pair repeats can then be compared with known repeats using the online database (www.ridom.de/spaserver). The number of repeats and their order can then be used to determine the spa type using the spaserver. Although the online server is currently free, an advanced database program, RidomStaphType is available that simplifies the technique by reading chromatograms directly from the sequencer and assigning spa types (41). There is some disagreement on the acceptable length of spa repeats with one repeat reported as 21 base pairs long (53), but the database currently contains 96 reported repeats, most of which are 24 base pairs long. Similarly, one study reported three of 41 isolates were non-typeable by spa sequencing (1) while another successfully typed thousands of isolates (59). Repeat combin ations ranging from 1 repeat per isolate to 23 repeats in one isolate are represented in the online database resulting in the designation of 1165 spa types from 21 countries to date (www.ridom.de/spaserver). The assignment of simple numeric codes, use of just one gene for amplification and sequencing, standardization of the protocols among laboratories, and the ease of data storage illustrates some of the advantages of using simple PCR-based approaches such as spa typing (100, 106). However, studies using this technique have found that while strains
20 with different spa types can generally be considered not related, strains with the same spa type are not necessarily epidemiologically related (106). Several recent studies have correlated spa type 44 with CA-MRSA isolates that are PVL positive recovered from infections in Denmark (30), Belgium (22), and Germany, France, and Switzerland (121). In a German hospital, spa typing was successfully used to track epidemic isolates and to disprove that person-to-person transmission of MRSA was occurring within the facility which allowed better use of infection control resources (41). A comparison of HA-MRSA with HA-MSSA and CAMSSA in Portugal using spa typing found that the three major MRSA clones were not related to any of the MSSA isolates tested (1). This data suggests that MRSA in Portugal did not result from acquisition of SCC mec by MSSA isolates in Portugal but likely was imported from abroad (1). A study of isolates in Hungary demonstrated that MRSA isolates recently introduced into the hospital environment varied little in spa types but MRSA clones circulating for longer periods of time and spread among several hospitals showed a higher degree of variability (83). This study further suggests that the spa gene may play a role in attachment and pathogenesis as an explanation for why certain epidemic clones, with stable spa types, are highly successful and have been circulating for decades (83). The comparison of CA-MRSA isolates to HA-MRSA isolates suggested once again that CA-MRSA is the result of recent acquisition of SCC mec into a MSSA background because all CA-MRSA isolates were related by spa typing but none were related to the HA-MRSA isolates (34). Some studies suggest that spa is relatively stable and can therefore be used to characterize both macroand microevolution in the primarily clonal population structure of S. aureus (59, 100). However, a recent study of
21 S. aureus isolates recovered from persistently infected cystic fibrosis patients found that one genetic change occurs in spa every 70 months (53). While some of the problems encountered with the use of spa gene typing, including low discriminatory power, may be overcome by combining the techniques such as coa typing and hypervariable region typing (74, 103), the expense of sequencing will continue to restrict the use of PCR/sequence based typing methods.
22 Objectives Recent studies have demonstrated the emergence of highly virulent communityacquired isolates of S. aureus that are capable of causing serious disease in otherwise healthy populations. These infections are of concern due to increased morbidity, mortality, and cost of care. Surveillance programs should be implemented by public health, hospital, and research laboratories to determine the extent of CA-MRSA dissemination, to better understand the epidemiology behind the spread of the organism, to propose infection control measures, and to provide adequate treatment. Currently there is no ongoing surveillance of S. aureus infections in the United States and the objective of this project was to determine what typing methods would be suitable for monitoring S. aureus The suspected outcome is that no one typing method will be suitable for each S. aureus typing study and that the method should be selected based on the desired outcome. The following specific aims were designed to test this hypothesis: 1. To establish a database of S. aureus isolates and categorize the isolates by PFGE. 2. To type a subset of the S. aureus isolates using MLST. 3. To type the same subset of S. aureus isolates using spa Typing. 4. To compare and contrast the usefulness of the 3 typing methods for public health applications.
23 Materials and Methods S. aureus Isolates A total of 403 isolates were used in this study, including communityassociated methicillin-resistant S. aureus (CA-MRSA) organisms isolated from wound, nose, sputum, blood, and other sources. CA-M RSA isolates were requested from two hospitals in Washington, 1 hospital in Florida, and Quest Diagnostics, a regional testing laboratory in Florida. All clinical isolates were collected from patients treated on an outpatient basis, within 48 hours of consultation. Control strains USA 100 USA 800 were obtained from the Network on Antimicrobial Resistance in S. aureus (NARSA) (Table 3). The PFGE standardization c ontrol strain, NCTC 8324 (NRS77) was also obtained from NARSA. Several additional st rains were obtained from the American Type Tissue Collection (ATCC) (Manassas, VA) (Table 3). The identification of all isolates as methicillin-resistant S. aureus was based on Gram stain reaction and cell morphology, catalase reaction, Microdase disk oxidase test (REMEL Inc., Lenexa, KS), slide and tube coagulase testing in rabbit plasma with EDTA (REMEL Inc.) and the API STAPH identification system (bioMerieux, Inc., Hazelwood, MO) supplemented with lysostaphin testing (REMEL Inc.). Profiles were analyzed using the API STAPH Codebook, Reference # 20590, 14 th Edition. Methicillin-resistance was determined on Mueller Hinton agar by the direct colony method of standardized disk diffusion susceptibility testing against 1 g oxacillin and 30 g cefoxitin disks incubated at 35 C
24 and 30 C, respectively (REMEL Inc., Technical Insert No. 33000) (49). Zones of inhibition < 10mm around the oxacillin disk and < 19 mm at cefoxitin are indicative of oxacillin and methicillin resistance (9). The presence of the mec A gene product was confirmed using the Penicillin Binding Protein (PBP2) Latex Agglutination Test (Oxoid Limited, Hampshire, England). A list of all strains used in the study appears in Appendix A. TABLE 3. Control strains CBD Designation Identifier CBD0007 ATCC 14458A CBD0019 ATCC 51740 CBD0034 ATCC 29213 CBD0036 ATCC 14458B CBD 0044 ATCC 25923 CBD0544 ATCC 6538 CBD0545 ATCC 12600 CBD0623 NRS77 (NCTC 8325) CBD0653 ATCC 33593 CBD0654 NRS 100 (COL) CBD0655 NRS 271A CBD0656 NRS 271B CBD0797 NRS 70 (N315) CBD0798 NRS 123 CBD0835 ATCC 49775A CBD0836 ATCC 49775B CBD1064 NRS382 (USA 100) CBD1065 NRS383 (USA 200) CBD1066 NRS384 (USA 300) CBD1067 NRS123 (USA 400) CBD1068 NRS385 (USA 500) CBD1069 NRS22 (USA 600) CBD1070 NRS386 (USA 700) CBD1071 NRS387 (USA 800) Pulsed-field Gel Electrophoresis A single isolated colony of S. aureus was aseptically transferred from a BBL TM Trypicase Soy Agar Plate (Becton Dickinson, Sparks, MD) to 5 ml BBL TM Trypticase TM Soy Broth (Becton Dickinson, Sparks, MD). The broth culture was incubated 16 hours in
25 a 37 C water bath with gentle agitation. Cells were pelleted for 10 min at 4 C, 5200 g and resuspended in 1.5 ml of PIV solution (10 mM Tris-HCl, 1 M NaCl). Plugs were prepared by adding 300 l of cells to 300 l of InCert agarose (Cambrex Bioscience, Rockland, ME), pipeting the mixture into reusable plug molds (Bio-Rad, Hercules, CA), and allowing them to cool for 10 min at 4 C. The plugs were then incubated for 5 hr at 37 C in 7 ml of EC-Lysis solution (6 mM Tris-HCl (pH 7.6), 1 M NaCl, 100 mM EDTA (pH 7.5), 0.5% Brij-58, 0.2% Deoxycholate, 0.5% sarkosyl, 20 g/ml RNase, 1 mg/ml lysozyme). Lysostaphin (no. L7386, Sigma, St. Louis, MO) was added to the EC-Lysis buffer at a concentration of 3 U/ml. EC-lysis solution was replaced with ESP solution (0.5 M EDTA (pH 9.0), 1% sarkosyl, 50 g/ml proteinase K) and the plugs were incubated overnight at 50 C. Plugs were then washed three times (45 min each wash) with TE (10 mM Tris-HCl (pH 7.5)), 1 mM EDTA (pH 7.5) and stored at 4 C until needed. Plugs were digested in Sma I overnight at room temperature (or overnight at 37 C for EagI and Sac II digestions). Plugs were then melted at 69 C for 10 min, and loaded into the wells of a 1.6 Seakem Gold (Cambrex BioScience, Rockland, ME) gel prepared by adding 3.2 g of agarose to 200 ml of 0.5X TBE (Tris Boric Acid EDTA). Sma I digested NCTC 8325 was used as a marker for all gels. PFGE was performed using a DR-II CHEF Mapper (Bio-Rad, Hercules, CA) using the following parameters: 200V, 14 C, 5.3 s initial switch, 34.9 s final switch, 0.5X TBE running buffer, and 20 to 22 hrs run time. The run time varied based on which of two available DR-II CHEF Mapper gel boxes was utilized. Following electrophoresis, gels were stained for 20 min in 200 ml of water containing 1 g/ml ethidium bromide and destained for 20 min in water (repeat
26 2x). Gels were then visualized using the Bio-Rad Gel Doc System utilizing the Quantity One version 4.6 software (Bio-Rad, Hercules, CA). Data was analyzed using BioNumerics (Applied Math, Sint-Martens, Belgium) Version 3.0. Dendrograms were derived from the unweighted pair group method using arithmetic averages (UPGMA) and based on Dice coefficients. Band position tolerance and optimization were set at 1.00%. Virtual Digestion to Identify Secondary Enzymes for S. aureus PFGE A list of 262 commercially available enzymes was compiled using catalog lists from New England Biolabs (Beverly, MA), Fisher Scientific (Pittsburgh, PA) Roche Applied Science (Indianapolis, IN), and Invitrogen (Carlsbad, CA). A list of all enzymes tested appears in Table 7. Restriction digestion of the S. aureus MW2 genome was performed for all 262 enzymes online at The Institute for Genomic Research (TIGR) website using the Restriction Digest Tool (www.tigr.org/tigrscripts/CMR2/restrict_display.pl). Using a subset of the enzymes, the genomes of other available S. aureus genomes including, Staphylococcus aureus Michigan VRSA and Staphylococcus aureus MU50 were digested. This resulted in the same size fragments for the S. aureus MW2 genome thus it was determined that virtual digestion of the MW2 genome was sufficient. Only those enzymes that resulted in 10 to 50 fragments were further considered for S. aureus PFGE. DNA Isolation for MLST and spa Typing Genomic DNA was isolated from all S. aureus strains using the MagNA Pure LC DNA Isolation Kit III (Bacteria, Fungi) (Roche Di agnostics, Indianapolis, IN) protocol as
27 follows. Cells were grown for 16 hours at 37 C in 4 ml BBL TM Trypticase TM Soy Broth (Becton Dickinson, Sparks, MD). Pellets were obtained by centrifugation of 1 ml of the overnight cell culture at 8,000 g for 10 min. After discarding the supernatant, the samples were lysed by adding 130 l of Bacterial Lysis Buffer, followed by mixing, then adding 20 l of Proteinase K provided in the kit and incubation for 10 min at 65 C. Organisms were then inactivated by boiling samples at 95 C for 10 min. Magnetic glass particles, which bind to the DNA, were added to the samples immediately before loaded onto the MagNA Pure LC Instrument (Roche Diagnostics, Indianapolis, IN). Samples were loading following onscreen instructions and the instrument performed a series of washes that removed unbound substances. The DNA was then eluted and it was experimentally determined through a series of dilutions that 1:20 dilutions of MagNA Pure genomic DNA sample was sufficient as template for both MLST and spa typing polymerase chain reactions. PCR for Multilocus Sequence Typing MLST of 30 S. aureus isolates was performed as per the standardized protocol (http://saureus.mlst.net/misc/info.asp). Internal fragments of the following seven housekeeping genes; arc (carbamate kinase), aro (shikimate dehydrogenase), glp (glycerol kinase), gmk (guanylate kinase), pta (phosphate acetyltransferase), tpi (triosephosphate isomerase), yqi (acetyl coenzyme A acetyltransferase) were amplified by PCR. PCR master mixes were prepared for each amplification using reagents from the Takara PCR Amplification Kit (Fisher Scientific, Pittsburg, PA) including 6l MgCl 2 5 l 10x PCR buffer, and 4 l dNTPs. Each reaction included 1 l each forward and reverse primers (1
28 g/l), 0.25 l (1.2U) Takara Taq polymerase (Fisher Scientific, Pittsburg, PA), and 30 l water for each reaction. Approximately 3l of 1:20 MagNA Pure isolated genomic DNA was added as template. The PCR protocol included an initial 5 min denaturation at 95C, followed by 30 cycles of denaturation at 95C for 1 min, annealing at 55 C for 1 min, extension at 72C for 1 min, and a final extension step of 72C for 5 min. The annealing temperature was raised to 65C for PCR amplification of the gmk, pta, and/or yqi gene for some isolates to obtain a single band. A list of all primers used for MLST PCR appears in Table 4. PCR for spa Typing Amplification of the spa gene was performed for 30 S. aureus isolates using the same master mix, DNA concentration, and primer concentration as reported above for MLST. The primers used for spa are listed in Table 4. Isolates CBD0614 and CBD0633 required the use of spaF2 (spa Forward 2) primer, all other isolates were amplified with spaF1. The PCR protocol included an initial 10 min denaturation at 95C, followed by 30 cycles of 30 seconds denaturation at 95C, annealing at 60C for 30 sec, extension at 72C for 45 sec, and a final extension step of 72C for 10 min (83).
29 TABLE 4. MLST and spa typing primers primer sequences obtained from www.mlst.net and www.ridom.de/spaserver/. Primer Designation Sequence (5 to 3) arc Forward TTG ATT CAC CAG CGC GTA TTG TC arc Reverse AGG TAT CTG CTT CAA TCA GCG aro Forward ATC GGA AAT CCT ATT TCA CAT TC aro Reverse GGT GTT GTA TTA ATA ACG ATA TC glp Forward CTA GGA ACT GCA ATC TTA ATC C glp Reverse TGG TAA AAT CGC ATG TCC AAT TC gmk Forward ATC GTT TTA TCG GGA CCA TC gmk Reverse TCA TTA ACT ACA ACG TAA TCG TA pta Forward GTT AAA ATC GTA TTA CCT GAA GG pta Reverse GAC CCT TTT GTT GAA AAG CTT AA tpi Forward TCG TTC ATT CTG AAC GTC GTG AA tpi Reverse TTT GCA CCT TCT AAC AAT TGT AC yqi Forward CAG CAT ACA GGA CAC CTA TTG GC yqi Reverse CGT TGA GGA ATC GAT ACT GGA AC spaF1 (Forward 1) GAC GAT CCT TCG GTG AGC spaF2 (Forward 2) CAG CAG TAG TGC CGT TTG C spa Reverse GAA CAA CGT AAC GGC TTC ATC C Wizard PCR Clean-up Kit for MLST and spa Typing PCR products were purified (removal of amplification primers and primer dimers) for sequencing using the Wizard PCR Preps DNA Purification System (Promega, Madison, WI) as follows. 100l of Direct PCR Purification Buffer was added to the PCR product followed by mixing. The DNA was then added to 1 ml of resin and vortexed briefly 3 times over a 1 min interval to bind the DNA to the resin. The DNA/resin mixture was then transferred to a 3 ml syringe with a Wizard Minicolumn attached. The syringe was then used to push the resin/DNA slurry into the minicolumn. A wash step was performed by adding 2 ml 80% isopropanol to the syringe and pushing it through the minicolumn. The minicolumn was then transferred to a 1.5 ml microcentrifuge tube followed by centrifugation at 10,000 g for 2 min. The minicolumn was then transferred to a second 1.5 ml microcentrifuge tube. To elute the DNA, 30 l of 65C water was
30 added to the column and allowed to stand 1 min. Centrifugation for 1 min eluted the DNA which was then stored at -20C until needed. Preparation of DNA Sequencing Reactions for MLST and spa Typing All sequencing reactions were performed on a CEQ 8000 Sequencer (Beckman Coulter, Fullerton, CA) using the CEQ Dye Terminator Cycle Sequencing with Quick Start Kit (Beckman Coulter, Fullerton, CA) as follows. Sequencing reactions were performed in 0.2 ml tubes containing 8.0 L DTCS Quick Start Master Mix, 2.0 L primer (25 pmol/ L), 2 L template, and 8.0 L of water. The recommended thermal cycling program was 30 cycles of 96 C for 20 sec, 50 C for 20 sec, and 60 C for 4 min. Ethanol precipitation of all templates was then performed as follows. The templates were added to sterile 0.5 ml microfuge tubes and 4 L of stop solution (equal volumes of 1.5 M NaOAc (pH 5.2) and 50 mM EDTA (pH 8.0) and 1 L of glycogen (20 mg/ml) was added. Following a brief mix, 60 L of cold 95% ethanol was added to each template and mixed. The samples were then centrifuged at the maximum speed for 15 min at 4 C. The supernatants were then removed without di sturbing the pellets. The pellets were then washed with 200 L of cold 70% ethanol and centrifuged at maximum speed for 10 min at 4 C. The wash step was then repeated and the pellets were dried in a concentrator for 20 min. Dried pellets were resuspended in 40 L of sample loading solution and transferred to a 96-well sequencing plate (Beckman-Coulter, Fullerton, CA). A drop of mineral oil was added to each sample before loading onto the CEQ 8000 and running the LFR (Long Fragment Run) sequencing program. All sequences were aligned using the
31 SeqMan II component of the Lasergene Expert Sequence Analysis Software package (DNASTAR, Madison, WI). MLST alleles and sequence types were assigned using online MLST database (http://saureus.mlst.net). All spa typing alleles and spa types were assigned using the online database (http://spa.ridom.de/spatypes.shtml).
32 Results Staphylococcus aureus BioNumerics Database PulseNet has demonstrated that PFGE is useful for tracking trends in the spread of microorganisms of interest. A large collection of S. aureus isolates including clinical isolates from Florida and Washington was used to develop a database of DNA fingerprint patterns that could be used to investigate the trends of S. aureus infection in these two states. Macrorestriction followed by pulsedfield gel electrophoresis was performed for every S. aureus isolate in the Center for Biological Defense (CBD) collection. The S. aureus PFGE size standard, Sma I digested NRS77 (NCTC 8325), was used for normalization. This standard is required by the software to allow comparison across the length of the agarose gels and to allow gel to gel comparison. The standard was run in lanes 1, 6, 11 and 15 on gels prepared with a small comb (15 wells), and in lanes 1, 5, and 10 on gels prepared with a larger comb (10 wells) (Figure 1). PFGE was performed on a total of 403 isolates and all isolates were typeable by this technique. Images from a total of 44 gels were imported into the BioNumerics database and a UPGMA dendrogram based on Dice coefficients was generated. A total of 88 isolates matched the USA 100 pulsotype and 136 isolates matched the USA 300 pulsotype. The remaining 161 isolates (does not include non-epidemic control strains) demonstrated pulsotypes consistent with sporadic strains as the patterns were either unique to that strain or were present in a low number of isolates. A
dendrogram was generated using BioNumerics to represent all of the strains included in the study (Figure 2). In this figure, USA 100 and USA 300 epidemic clone control strains represent 88 and 136 isolates respectively (Figure 2). Data for each individual strain is included in Appendix A. 33 Figure 1. Pulsed-field gel electrophoresis of Staphylococcus aureus S. aureus isolates were run on 1.0% agarose gels following macrorestriction with Sma I enzyme. The standard marker (NCTC 8325) was run in lanes 1, 5, and 10 to allow normalization across the gel as well as gel to gel comparison. Images were uploaded to the BioNumerics software package for dendrogram creation.
Figure 2. Dendrogram of sporadic isolates and epidemic controls. Data was analyzed using BioNumerics (Applied Math, Sint-Martens, Belgium) Version 3.0. Dendrograms were derived from the unweighted pair group method using arithmetic averages (UPGMA) and based on Dice coefficients. Band position tolerance and optimization were set at 1.00%. 34
35 . . . . . . . . . . . . . . . . . . . . . . . . . CBD0898 CBD0954 CBD0695 CBD0665 CBD0950 CBD0929 CBD0892 CBD0896 CBD0662 CBD0864 CBD0802 CBD0909 CBD1055 CBD0859 CBD1039 CBD0844 CBD0948 CBD0931 CBD1013 CBD1023 CBD0677 CBD0535 CBD1038 CBD0007 CBD0479 CBD0474 CBD0064 CBD0545 CBD0860 CBD0653 CBD0904 CBD1071 CBD0536 CBD0537 CBD0979 CBD0528 CBD0529 CBD0722 CBD1027 CBD0721 CBD1016 CBD0874 CBD0682 CBD0688 CBD0730 CBD0801 CBD0915 CBD0616 CBD0617 CBD0538 CBD0723 CB D 0 7 3 6 Wound Wound Nose Nose Wound Nose Wound Wound Sputum Wound Unknown Wound Wound Wound Wound Wound Wound Wound Wound Wound Nose Sputum Wound Feces Wound Wound Unknown Sputum Wound Blood Wound NARSA Sputum Sputum Nose Wound Wound Nose Wound Nose Wound Wound Nose Nose Nose Unknown Wound Blood Wound Blood Nose No s e FL FL FL FL FL FL FL FL FL FL Unknown FL WA FL WA FL FL FL FL FL FL WA WA A TC C WA WA A TC C A TC C FL A TC C FL USA800 WA WA FL WA WA FL FL FL FL FL FL FL FL Unknown FL FL FL WA FL FL Figure 2. (Continued) Dendrogram of sporadic isolates and epidemic controls.
36 . . . . . . . . . . . . . . . . . . . . . . . . . . CB D 0 5 3 8 CBD0723 CBD0736 CBD0718 CBD0974 CBD0486 CBD0708 CBD0709 CBD0705 CBD0729 CBD0918 CBD0725 CBD0902 CBD0680 CBD0664 CBD1048 CBD0875 CBD0719 CBD0633 CBD0672 CBD0890 CBD0928 CBD0649 CBD0684 CBD0903 CBD0850 CBD0878 CBD0852 CBD1035 CBD1070 CBD0035 CBD0531 CBD0504 CBD0505 CBD0926 CBD1066 CBD0036 CBD0483 CBD0679 CBD0655 CBD0720 CBD1067 CBD0475 CBD1069 CBD0526 CBD0533 CBD0019 CBD0530 CBD0470 CBD0944 CBD0543 CBD0473 Bl o o d Nose Nose Sputum Wound Wound Nose Nose Nose Nose Wound Nose Urine Sputum Nose Wound Wound Sputum Nose Nose Urine Nose Blood Nose Wound Wound Eye Wound Wound NARSA Food Wound Unknown Unknown Wound NARSA Feces Sputum Sputum NRS271A Nose NARSA Wound NARSA Wound Sputum Food Body Fluid Sputum Wound Unknown Mouth WA FL FL FL FL WA FL FL FL FL FL FL FL FL FL WA FL FL FL FL FL FL FL FL FL FL FL FL FL USA700 FL DOH WA FL FL FL USA300 A TCC WA FL NARSA FL USA400 WA USA600 WA WA Dupont WA WA FL Unknown WA Figure 2. (Continued) Dendrogram of sporadic isolates and epidemic controls.
. . . . . . . . . CBD0543 CBD0473 CBD0855 CBD0544 CBD0527 CBD0534 CBD0675 CBD0477 CBD0836 CBD0044 CBD1046 CBD0835 CBD0691 CBD1065 CBD0481 CBD0656 CBD0532 CBD0645 Unknown Mouth Wound Wound Wound Sputum Nose Wound Wound Unknown Wound Wound Nose NARSA Blood NRS271B Wound Nose Unknown WA FL A TCC WA WA FL WA A TCC A TCC WA A TCC FL USA200 WA NARSA WA FL Figure 2. (Continued) Dendrogram of sporadic isolates and epidemic controls. 37
38 Analysis of S. aureus Epidemic Clone USA 300 in S. aureus PFGE Database. A number of studies have demonstrated the epidemiology of this strain and its link to wound infections and necrotizing pneumonia (12, 37, 71). The dendrogram generated by BioNumerics analysis indicated that a large number of isolates possessed pulsotypes consistent with the USA 300 epidemic clone control strain. This analysis demonstrated the first documented USA 300 isolates in both Florida and Washington State. Excluding those isolates from unknown sources, non-clinical sources, unknown clinical background, and/or non-MRSA, the da tabase contains 332 CA-MRSA clinical isolates. A total of 136 CA-MRSA isolates were found to possess pulsotypes consistent with the USA 300 clone including 119 isolates from Florida and 17 isolates from Washington. Although the clinical background of these isolates was limited, they were grouped according to their source, i.e. wound, sputum, blood, nose, and other. Isolates that were reported as abscess, wound, furunculosis, and cellulitis were grouped as wound infections, while those listed as nasal, nose, and nares were grouped as nose infections. Clinical sources listed as other included urine, unspecified body fluid, eye, feces, and cervix. The clinical source for each individual isolate is listed in Appendix 1. Wound infections accounted for the majority of the 332 clinical isolates in the database, 194 (58%) of the isolates. A total of 121 of these wound isolates (63%) demonstrated the USA 300 pulsotype (Table 5). These data demonstrated both that the majority of isolates in the database are from wounds and that the majority of the wound isolates are USA 300 pulsotype. Although USA 300 was present in isolates from the other clinical sources, it constituted a minority of the isolates (Table 5).
TABLE 5. Summary of results for all isolates tested No. (%) of isolates: USA 300 positive USA 300 negative Source of Isolates FL WA FL WA Total no. of isolates from source (% of total) Wound 106 (55) 15 (8) 63 (32) 10 (5) 194 (58) Sputum 1 (6) 0 8 (50) 7 (44) 16 (5) Blood 1 (5) 1 (5) 15 (71) 4 (19) 21 (6) Nose 10 (11) 1 (1) 76 (87) 0 87 (26) Other 1 (7) 0 12 (86) 1 (7) 14 (4) Total 119 (36) 17 (5) 174 (52) 22 (7) 332 (100) Analysis of S. aureus Epidemic Clone USA 100 in S. aureus PFGE Database. There is a paucity of data concerning the epidemiology of the USA 100 epidemic clone but it is believed to be primary an HA-MRSA (70). Analysis of the S. aureus BioNumerics database demonstrated that 88 of the isolates have pulsotypes consistent with USA 100 (no more than 1 band difference). Using the same exclusion criteria as the USA 300 analysis, the database containi ng CA-MRSA isolates includes 82 USA 100 isolates from Florida and 6 USA 100 isolates from Washington State. USA 100 isolates constituted the majority of the nose (47%) and blood (58%) isolates and was rarely present in wound, sputum, and isolates from other clinical sources (Table 6). The clinical source for each individual isolate is listed in Appendix 1. Few blood isolates were present in the database (21 total), limiting the conclusions that can be made concerning the etiology of blood-borne infections caused by this clone. However, S. aureus was 39
40 identified in 87 nose isolates confirming the nose as the second most common isolation site behind wound isolates (Table 6). Due to the limited clinical information provided for the isolates in this study, it is unclear whether these nose isolates were a cause of infection or if they are present as colonizing strains. TABLE 6. Summary of results for all isolates tested No. (%) of isolates: USA 100 positive USA 100 negative Source of Isolates FL WA FL WA Total no. of isolates from source (% of total) Wound 25 (13) 1 (1) 144 (74) 24 (12) 194 (58) Sputum 0 3 (19) 9 (56) 4 (25) 16 (5) Blood 10 (48) 2 (10) 6 (29) 3 (14) 21 (6) Nose 41 (47) 0 45(52) 1 (1) 87 (26) Other 6 (43) 0 7 (50) 1 (7) 14 (4) Total 82 (25) 6 (2) 211 (64) 33 (10) 332 (100) Use of Restriction Digestion of the MW2 Genome to Identify Secondary Enzymes for S. aureus PFGE. Studies with organisms other than S. aureus have demonstrated that differences in strains are often not detected by the use of just one restriction enzyme for PFGE (88). Virtual digestion of the S. aureus enzyme was performed in an attempt to find a secondary enzyme for S. aureus PFGE. A total of 262 commercially available restriction enzymes were tested for their ability to virtually digest the MW2 S. aureus genome into 10 to 50 fragments. Restriction digestion was performed using the TIGR Restriction Digest Tool (www.tigr.org/tigr-scripts/CMR2/restrict_display.pl) and the S. aureus
41 MW2, Michigan VRSA, and MU50 genomes. After testing 25 enzymes it was determined that the same number of restriction fragments resulted regardless of the S. aureus genome selected and further digestions used only the S. aureus MW2 genome. The majority of the enzymes, 242, resulted in >50 fragments which cannot be resolved on a conventional pulsed-field gel. Eleven enzymes either failed to cut or had recognition sites in the S. aureus MW2 genome that would result in too few bands for epidemiological studies. Two enzymes were excluded based on expense as their use would exceed $1,000 per gel. Two additional enzymes were excluded because the resulting digestion pattern would contain bands that are too close together to be resolved by PFGE. This technique also identified Xma I and Xma CI, both of which are isoschizomers of Sma I. Because their use would result in the same pattern as Sma I and since Sma I is less expensive and in common use, these two enzymes were also excluded. Results for each enzyme tested are shown in Ta ble 7. Virtual digestion and application of the criteria mentioned above resulted in the id entification of two enzymes, in addition to Sma I, EagI and Sac II, which could potentially be used for S. aureus PFGE.
42 Enzyme Fragments Enzyme Fragments Enzyme Fragments 1 Aat II 82 37 Ban II 0 73 BsmB I 168 2 Acc I 1250 38 BbrP I 412 74 BsmF I 479 3 Acc III 122 39 Bbs I 491 75 BsoB I 163 4 Acc B7 I 441 40 Bbv I 1561 76 Bsp 12861 1178 5 Acc 65 I 166 41 BbvC I 36 77 BspD I 1047 6 Aci I 2144 42 Bcc I 2239 78 BspE I 122 7 Acl I 1227 43 Bcg I 249 79 BspH I 1073 8 Acs I 8109 44 BciV I 319 80 BspM I 535 9 Acy I 541 45 Bcl I 1007 81 BspLU 11 I 864 10 Afe I 259 46 Bfa I 4374 82 Bsr I 1499 11 Afl II 356 47 Bfr I 356 83 BsrB I 64 12 Afl III 2059 48 BfrB I 1367 84 BsrD I 904 13 Age I 169 49 Bgl II 162 85 BsrF I 482 14 Ahd I 167 50 Blp I 216 86 BsrG I 758 15 Alu I 8998 51 Bmr I 178 87 BsrS I 1499 16 Alw 26 I 824 53 Bmy I 1178 88 BssH II 74 17 Alw 44 I 355 53 Bpm I 183 89 BssK I 1792 18 Alw I 966 54 BpuA I 491 90 BssS I 179 19 AlwN I 546 55 Bpu 10 I 184 91 Bst1 107 I 547 20 Apa I 115 56 Bsa I 106 92 BstAP I 897 21 ApaL I 355 57 BsaA I 1897 93 BstB I 807 22 Apo I 8109 58 BsaB I 1113 94 BstE II 213 23 Asc I 5 59 BsaH I 541 95 BstF 5 I 1429 24 Ase I 4484 60 BsaJ I 1371 96 BstN I 1471 25 Asp 700 1060 61 BsaM I 502 97 BstO I 1471 26 Asp 718 166 62 BsaW I 561 98 BstU I 1796 27 AspE I 167 63 BsaX I 199 99 BstX I 298 28 AspH I 766 64 BseR I 155 100 BstY I 799 29 Asp I 231 65 Bsg I 425 101 BstZ 17 I 547 30 Ava I 163 66 BsiE I 295 102 Bst98 I 356 31 Ava II 1242 67 BsiHKA I 766 103 Bsu 36 I 110 32 Avr II 95 68 BsiW I 180 104 Btg I 436 33 Bae I 283 69 BsiY I 200 105 Bts I 261 34 Bal I 269 70 Bsl I 30 106 Cac 8 I 2633 35 Bam HI 115 71 Bsm I 502 107 Cel II 216 36 Ban I 642 72 BsmA I 824 108 Cfo I 3175 Table 7. Virtual digestion of S. aureus MW2 genome. A total of 262 enzymes were used to virtually digest the S. aureus genome. The resulting fragment numbers are listed in the table. Isolates with digestion results of 10 to 50 fragments (bold) were considered for further analysis.
43 Enzyme Fragments Enzyme Fragments Enzyme Fragments 109 Cfr 10 I 482 145 HinF I 7098 181 Mvn I 1796 110 Cla I 1047 146 Hpa I 755 182 Mwo I 1250 111 Csp I 12 147 Hpa II 1331 183 Nae I 59 112 Csp 45 I 807 148 Hph I 2163 184 Nar I 77 113 CviA II 9004 149 Hpy 99 I 1423 185 Nci I 320 114 Dde I 4962 150 Hpy 188 I 6130 186 Nco I 238 115 Dpn I 5167 151 HpyCH 4 III 7180 187 Nde I 1173 116 Dpn II 5167 152 HpyCH 4 IV 8749 188 Nde II 5167 117 Dra I 5616 153 HpyCH 4 V 13916 189 NgoM IV 59 118 Dra II 466 154 Hsp 92 I 541 190 Nhe I 201 119 Dra III 358 155 Hsp 92 II 9004 191 Nla III 161 120 Drd I 229 156 Ita I 3972 192 Nla IV 1685 121 Eae I 477 157 Kas I 77 193 Not I 0 122 Eag I 27 158 Kpn I 166 194 Nru I 165 123 Ear I 420 159 Ksp I 28 195 Nsi I 1367 124 Eci I 145 160 Ksp632 I 420 196 Nsp I 2181 125 Ecl HK I 167 161 Mae I 4374 197 Pac I 429 126 EclX I 27 162 Mae II 8749 198 PaeR7 I 75 127 Eco 47 III 256 163 Mae III 7993 199 Pci I 864 128 Eco 52 I 27 164 Mam I 1113 200 PfiF I 231 129 EcoN I 243 186 Mbo I 5167 201 PflM I 441 130 EcoO 109 I 466 166 Mbo II 4292 202 PinA I 165 131 EcoR I 625 167 Mfe I 2044 203 Ple I 760 132 EcoR II 1471 168 Mlu I 220 204 Pme I 76 133 EcoR V 917 169 MluN I 269 205 Pml I 412 134 Fau I 303 170 Mly I 760 206 PpuM I 225 135 Fnu 4H I 3972 171 Mme I 769 207 PshA I 151 136 Fok I 1429 172 Mnl I 3100 208 Psi I 2673 137 Fse I 0 173 Mro I 122 209 Psp1406 I 1227 138 Fsp I 364 174 Msc I 269 210 PspG I 1471 139 Hae II 829 175 Mse I 36832 211 PspOM I 115 140 Hae III 1362 176 Msl I 2441 212 Pst I 453 141 Hga I 768 177 Msp I 1331 213 Pvu I 90 142 Hha I 3175 178 MspA1 I 815 214 Pvu II 598 143 Hinc II 1846 179 Mun I 2044 215 Rca I 1073 144 Hind III 1069 180 Mva I 1471 216 Rsa I 7280 Table 7 (Continued). Virtual digestion of S. aureus MW2 genome. A total of 262 enzymes were used to virtually digest the S. aureus genome. The resulting fragment numbers are listed in the table. Isolates with digestion results of 10 to 50 fragments (bold) were considered for further analysis.
44 Enzyme Fragments Enzyme Fragments Enzyme Fragments 217 Rsr II 12 233 SgF I 4 249 Tse I 3171 218 Sac I 62 234 SgrA I 13 250 Tsp45 I 2783 219 Sac II 28 235 Sma I 27 251 Tsp509 I 37578 220 Sal I 149 236 Sml I 1276 251 TspR I 2461 221 Sap I 85 237 SnaB I 625 253 Tth111 I 231 222 Sau3A I 5167 238 Spe I 385 254 Van91 I 441 223 Sau96 I 1801 239 Sph I 280 255 Vsp I 4484 224 Sbf I 11 240 Ssp I 4198 256 Xba I 400 225 Sca I 534 241 SspB I 758 257 Xcm I 5000 226 ScrF I 1792 242 Stu I 82 258 Xho I 75 227 SexA I 358 243 Sty I 745 259 Xho II 799 228 SfaN I 2554 244 Swa I 584 260 Xma I 27 229 Sfc I 1925 245 Taq I 6741 261 XmaC I 27 230 Sfi I 0 246 Tfi I 5494 262 Xmn I 1060 231 Sfo I 77 247 Tli I 75 232 Sfu I 807 248 Tru9 I 36832 Table 7 (Continued). Virtual digestion of S. aureus MW2 genome. A total of 262 enzymes were used to virtually digest the S. aureus genome. The resulting fragment numbers are listed in the table. Isolates with digestion results of 10 to 50 fragments (bold) were considered for further analysis.
45 Analysis of the PFGE Patterns of 12 USA 300 Epidemic Clone Isolates Using Sma I, Eag I, and Sac II. Twelve CA-MRSA isolates that have identical Sma I pulsotypes consistent with the USA 300 epidemic clone were used to test the ability of the two additional enzymes to discriminate identical isolates (Figure 3). Restriction digestion of these isolates with EagI resulted in approximately the same number of fragments as digestion with Sma I, although the pulsotype generated was distinct from that of Sma I (Figure 4). Phylogenetic analysis of the EagI PFGE using the BioNumerics software package determined that the 12 isolates were identical. Likewise, digestion with Sac II resulted in a unique pulsotype, but with approximately the same number of bands as the other two enzymes (Figure 5). As shown in Figure 5, digestion with Sac II also confirmed that the 12 CAMRSA USA 300 isolates are identical. Thus, S. aureus PFGE was successfully performed with the three enzymes predicted by virtual digestion and BioNumerics analysis of the three pulsed-field gels was in agreement that the 12 isolates are 100% identical.
Dice (Opt:1.00%) (Tol 2.0%-2.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGE 100 PFGE . . . . . . CBD0540 CBD0541 CBD0611 CBD0685 CBD0700 CBD0869 CBD0912 CBD0949 CBD0964 CBD1010 CBD1042 CBD1045 A bscess Wound A bscess Leg Nose Right Axilla Unknown Back Lesion Right Thigh Scalp Chest Abscess A rm Abscess WA WA FL FL FL Quest Quest Quest Quest Quest WA WA Figure 3. USA 300 isolates demonstrating 100% identity by Sma I PFGE. Isolates possessing pulsotypes identical to the USA 300 epidemic clone were used to demonstrate the use of Sma I for digestion for PFGE. The original clinical source information is present in the figure. Quest represents isolates obtained from Quest Diagnostics in Tampa, Florida. 46
Dice (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGEEag1 100 PFGEEag1 . . . . . . CBD0540 CBD0541 CBD0611 CBD0685 CBD0700 CBD0869 CBD0912 CBD0949 CBD0964 CBD1010 CBD1042 CBD1045 A bscess Wound A bscess Leg Nose Right Axilla Unknown Back Lesion Right Thigh Scalp Chest Abscess A rm Abscess WA WA FL FL TGH Quest Quest Quest Quest Quest WA WA Figure 4. USA 300 isolates demonstrating 100% identity by Eag I PFGE. The same isolates present in Figure 3 were used to demonstrate the use of EagI for digestion of S. aureus for PFGE. The original clinical source information is present in the figure. Quest represents isolates obtained from Quest Diagnostics and TGH isolates obtained from Tampa General Hospital both in Tampa, Florida. 47
Dice (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGESacII 100 PFGESacII CBD0540 CBD0541 CBD0611 CBD0685 CBD0700 CBD0869 CBD0912 CBD0949 CBD0964 CBD1010 CBD1042 CBD1045 A bscess Wound A bscess Leg Nose Right Axilla Unknown Back Lesion Right Thigh Scalp Chest Abscess A rm Abscess WA WA FL FL TGH Quest Quest Quest Quest Quest WA WA Figure 5. USA 300 isolates demonstrating 100% identity by Sac II PFGE. The same isolates present in Figure 3 were used to demonstrate the use of Sac II for digestion of S. aureus for PFGE. The original clinical source information is present in the figure. Quest represents isolates obtained from Quest Diagnostics and TGH isolates obtained from Tampa General Hospital both in Tampa, Florida. 48
49 Analysis of the PFGE Patterns of Seven Pairs of Identical Isolates using Sma I, Eag I, and Sac II. Seven pairs of CA-MRSA isolates that were 100% identical by Sma I PFGE (Figure 6) were chosen to test the ability of EagI and Sac II to further discriminate the pairs. Digestion with both enzymes again resulted in approximately the same number of resolvable fragments as Sma I as predicted by virtual digestion. However, digestion with EagI and subsequent BioNumerics analysis demonstrated one to two band differences between isolates within three of the seven pairs (Figures 7). Similarly, digestion with Sac II followed by BioNumerics analysis also detected one to two band differences between isolates in the same three pairs as identified using EagI (Figure 7 and 8). Thus, EagI and Sac II were able to discriminate between isolates that were identical by Sma I (Figures 6-8).
Dice (Opt:1.00%) (Tol 2.0%-2.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGE 100 95 90 85 80 75 70 PFGE . . . . . . . CBD0723 CBD0736 CBD0654 CBD0799 CBD0000 CBD0979 CBD0735 CBD0743 CBD0676 CBD0690 CBD0643 CBD0644 CBD0713 CBD0714 Nose Nose NRS100 Unknown Nose Nose Nose Blood Nasopharynx Nose Nasal Nose Nose Nose FL FL NARSA Unknown FL FL FL FL FL FL FL FL FL FL Figure 6. Seven pairs of identical isolates by Sma I PFGE. Sma I digestion was used to demonstrate seven pairs of identical isolates. The original source of the isolates is shown. The NRS100 control strain, obtained from NARSA, is included in this set of isolates. 50
Dice (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGEEag1 100 90 80 70 60 50 40 PFGEEag1 . . . . . . . CBD0654 CBD0799 CBD0000 CBD0979 CBD0676 CBD0690 CBD0735 CBD0743 CBD0723 CBD0736 CBD0713 CBD0714 CBD0643 CBD0644 NRS100 Unknown Nose Nose Nasopharynx Nose Nose Blood Nose Nose Nose Nose Nose Nasal NARSA Unknown FL FL FL FL FL FL FL FL FL FL FL FL Figure 7. Seven pairs of isolates further distinguished by Eag I PFGE. EagI digestion was used to demonstrate that the isolates digested by Sma I, shown in Figure 6, could be further distinguished by EagI digestion. The original source of the isolates is shown. The NRS100 control strain, obtained from NARSA, is included in this set of isolates. 51
Dice (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGESacII 100 90 80 70 60 50 PFGESacII . . . . . . . CBD0735 CBD0743 CBD0723 CBD0736 CBD0654 CBD0799 CBD0676 CBD0690 CBD0000 CBD0979 CBD0713 CBD0714 CBD0643 CBD0644 Nose Blood Nose Nose NRS100 Unknown Nasopharynx Nose Nose Nose Nose Nose Nose Nose FL FL FL FL NARSA Unknown FL FL FL FL FL FL FL FL Figure 8. Seven pairs of isolates further distinguished by Sac II PFGE. Sac II digestion was used to demonstrate that the isolates digested by Sma I, shown in Figure 6, could be further distinguished by Sac II digestion. The original source of the isolates is shown. The NRS100 control strain, obtained from NARSA, is included in this set of isolates. 52
53 Selection of CA-MRSA Isolates for Multilocus Sequence Typing. In order to explore the use of genomic typing methods for CA-MRSA subspeciation, 30 isolates that were previ ously typed by PFGE were chosen for MLST. The isolates were selected to represent bot h Florida and Washington State (Figure 9). CA-MRSA isolated from a variety of clinical sources including wounds, urine, blood, sputum, and nose were included to represent the variety of disease caused by S. aureus (Figure 9). Furthermore, isolates possessing several pulsotypes as determined using the PFGE database were included (Figure 9). Isol ates with identical pulsotypes were also included among the 30 CA-MRSA as controls as shown in Figure 9. PCR Amplification of Housekeeping Genes for MLST Following isolation of genomic DNA, internal fragments of the following seven housekeeping genes; arc aro, glp gmk pta tpi and yqi were amplified by PCR using the primers listed in Table 4. PCR was performed according to the standardized protocol for S. aureus (saureus.mlst.net) for most isolates. However, adjustment of the annealing temperature, increasing from 60C to 65C, was necessary for PCR amplification of the gmk, pta, and/or yqi genes for some isolates to obtain a single band for sequencing. The PCR primers, primer dimers, and enzymes were removed from the amplification reactions prior to sequencing using the Wizard PCR Preps kit and 1 l of the resulting product was run on a gel to confirm a single band was present (Figure 10).
Figure 9. BioNumerics Analysis. A UPGMA derived dendrogram illustrates the pulsotypes of the 30 CA-MRSA isolates used for MLST. 54
Figure 10. PCR amplification of the internal fragment of the gmk gene for MLST PCR reactions were purified using the Wizard PCR Preps kit to remove primer dimers and amplification primers. The result was a single band of 429 base pairs corresponding to the internal fragment of the gmk gene. The marker used for all agarose gels was Promega Benchtop 1 Kb Ladder. 55
56 DNA Sequencing, Alignment, and Assigning of Alleles and Sequence Types for CAMRSA MLST. A minimum of four forward and reverse sequencing reactions were performed for each PCR product analyzed, comprising 28 sequencing reactions for each of the 30 isolates examined. The resulting DNA sequences were uploaded to the SeqMan program for alignment. Each gene was analyzed separately for each isolate using both forward and reverse sequencing reactions to remove ambiguity in base calling. The consensus sequence data from the alignments was then entered into the MLST database for comparison to known housekeeping gene sequences (alleles). The online allele tool allowed consensus sequences to be cut and paste into the database and compared to known sequences. Alleles were then assigned for the seven gene sequences from all isolates used in this study as each sequence matched a known allele present in the database (Table 8). The resulting allelic pattern could then be entered into the database to assign a sequence type. For example, the following pattern, arcC allele 3, aroE allele 3, glpF allele 1, gmK allele 1, pta allele 4, tpi allele 4, and yqi allele 3 corresponds to ST 8. All isolates used in this study possess known STs as indicated in Table 8. As illustrated by Table 8 and Figure 11, there is little variation of the alleles present among the CA-MRSA isolates used for this study. Although a large number of alleles have been described for each of the seven housekeeping genes (Table 9), our isolates failed to show much variation. Consequently, despite the presence of 734 known STs in the S. aureus database, our isolates were comprised of only four sequence types (Table 8).
57 468arcF TTATTAATCCAACAAGCTAAAT CGAACAGTGACACAACGCCGGCAATGCCATTGGATACT 60 704arcF TTATTAATCCAACAAGCTAAAT CGAACAGTGACACAACGCCGGCAATGCCATTGGATACT 60 692arcF TTATTAATCCAACAAGCTAAAT CGAACAGTGACACAACGCCGGCAATGCCATTGGATACT 60 ************************************************************ 468arcF TGTGGTGCAATGTCACA GGGTATGATAGGCTATTGGTTGGAAACTGAAATCAATCGCATT 120 704arcF TGTGGTGCAATGTCACA GGGTATGATAGGCTATTGGTTGGAAACTGAAATCAATCGCATT 120 692arcF TGTGGTGCAATGTCACA GGGTATGATAGGCTATTGGTTGGAAACTGAAATCAATCGCATT 120 ************************************************************ 468arcF TTAAC TGAAATGAATAGTGAT AGAACTGTAGGCACAATCGTTACA CGTGTGGAAGTAGAT 180 704arcF TTAAC TGAAATGAATAGTGAT AGAACTGTAGGCACAATCGTTACA CGTGTGGAAGTAGAT 180 692arcF TTAAC TGAAATGAATAGTGAT AGAACTGTAGGCACAATCGTTACA CGTGTGGAAGTAGAT 180 ************************************************************ 468arcF AAAGATGATCCACGA TTTGATAACCCAACTAAACCAATTGGTCCTTTTTATACGAAAGAA 240 704arcF AAAGATGATCCACGA TTTGATAACCCAACTAAACCAATTGGTCCTTTTTATACGAAAGAA 240 692arcF AAAGATGATCCACGA TTTGATAACCCAACTAAACCAATTGGTCCTTTTTATACGAAAGAA 240 ************************************************************ 468arcF GAAG TTGAAGAATTACAAAAAGAACAGCCAGACTCA GTCTTTAAAGAAGATGCAGGACGT 300 704arcF GAAG TTGAAGAATTACAAAAAGAACAGCCAGACTCA GTCTTTAAAGAAGATGCAGGACGT 300 692arcF GAAG TTGAAGAATTACAAAAAGAACAGCCAGACTCA GTCTTTAAAGAAGATGCAGGACGT 300 ************************************************************ 468arcF GGTTATA GAAAAGTAGTTGCGTCACCACTACCTCAAT CTATACTAGAACACCAGTTAATT 360 704arcF GGTTATA GAAAAGTAGTTGCGTCACCACTACCTCAAT CTATACTAGAACACCAGTTAATT 360 692arcF GGTTATA GAAAAGTAGTTGCGTCACCACTACCTCAAT CTATACTAGAACACCAGTTAATT 360 ************************************************************ 468arcF CGAACTTTAGCAGACGGTAAAAAT ATTGTCATTGCATGCGGTGGTGGCGGTATTCCAGTT 420 704arcF CGAACTTTAGCAGACGGTAAAAAT ATTGTCATTGCATGCGGTGGTGGCGGTATTCCAGTT 420 692arcF CGAACTTTAGCAGACGGTAAAAAT ATTGTCATTGCATGCGGTGGTGGCGGTATTCCAGTT 420 ************************************************************ 468arcF ATAAAAAAAG AAAATACCTATGAAGGTGTTGAAGCG 456 704arcF ATAAAAAAAG AAAATACCTATGAAGGTGTTGAAGCG 456 692arcF ATAAAAAAAG AAAATACCTATGAAGGTGTTGAAGCG 456 ************************************ Figure 11. Clustal W (1.82) multiple sequence alignment of arc housekeeping gene fragment. Alignment of the sequences of the arc genes from three S. aureus isolates demonstrates 100% identity resulting in the assignment of the same allele at this loci for these isolates.
58 Strain Source State arcC aroE glpF gmk pta tpi yqi ST CBD0467 blood WA 1 4 1 4 12 1 10 5 CBD0468 wound WA 3 3 1 1 4 4 3 8 CBD0471 urine WA 1 4 1 4 12 1 10 5 CBD0472 blood WA 1 4 1 4 12 1 10 5 CBD0479 wound WA 3 3 1 1 4 4 3 8 CBD0482 wound WA 1 4 1 4 12 1 10 5 CBD0541 wound WA 3 3 1 1 4 4 3 8 CBD0542 blood WA 1 4 1 4 12 1 28 105 CBD0611 wound FL 3 3 1 1 4 4 3 8 CBD0613 nose FL 1 4 1 4 12 1 10 5 CBD0614 wound FL 1 4 1 4 12 1 10 5 CBD0618 nose FL 1 4 1 4 12 1 10 5 CBD0633 nose FL 1 4 1 4 12 1 28 105 CBD0637 nose FL 1 4 1 4 12 1 10 5 CBD0644 nose FL 1 4 1 4 12 1 10 5 CBD0652 nose FL 1 4 1 4 12 1 10 5 CBD0665 nose FL 3 3 1 1 4 4 3 8 CBD0674 nose FL 3 3 1 1 4 4 3 8 CBD0677 nose FL 3 3 1 1 4 4 3 8 CBD0685 wound FL 3 3 1 1 4 4 3 8 CBD0691 nose FL 10 14 8 6 10 3 2 45 CBD0692 nose FL 3 3 1 1 4 4 3 8 CBD0704 sputum FL 3 3 1 1 4 4 3 8 CBD0717 nose FL 1 4 1 4 12 1 10 5 CBD0727 blood FL 1 4 1 4 12 1 10 5 CBD0728 blood FL 1 4 1 4 12 1 10 5 CBD0734 nose FL 1 4 1 4 12 1 10 5 CBD0736 nose FL 1 4 1 4 12 1 10 5 CBD0737 wound FL 3 3 1 1 4 4 3 8 CBD0885 urine FL 3 3 1 1 4 4 3 8 Table 8. Multilocus sequence typing alleles and sequence types for 30 S. aureus isolates Thirty S. aureus isolates were chosen for MLST which represent strains from both Florida and Washington State and clini cal sources including nose, sputum, urine, blood, and wound isolates. The alleles and ST types were assigned using the online S. aureus database and sequences obtained from the housekeeping genes of the 30 isolates.
59 TABLE 9. Comparison of S. aureus MLST alleles Gene Total Alleles in Database Total Alleles in Present Study arcC 87 3 aroE 129 3 glpF 100 2 gmk 71 3 pta 98 3 tpi 101 3 yqiL 95 4 Comparison of PFGE Data and MLST Data for 30 CA-MRSA Isolates. A dendrogram was prepared for the 30 S. aureus isolates typed by MLST using the S. aureus PFGE database. The isolates were grouped into 21 pulsotypes by PFGE, as compared to four STs, as shown in Figure 12. Isolates did not cluster based on either the state in which they were isolated or on their disease manifestations. Isolates with the same pulsotype always had the same MLST sequence type, however isolates with the same sequence type were frequently furthe r differentiated by PFGE (Figure 12). For example, CBD 0665 and CBD 0677 were both assigned to ST 8 by MLST, but the PFGE patterns differ by >7 bands. The largest cluster of isolates was a match to the USA 300 epidemic clone (control not shown), which is also ST 8 by MLST (Figure 12). Database searches for the four resulting STs determined that they are found worldwide (Table 10).
60 TABLE 10. MLST Sequence Type Information ST Geographical Location (s) of ST Additional Information 5 UK, Thailand, US (MI,NY,PA,NJ,MD), Scotland, France, Belgium, Canada, Finland, Portugal, Japan, Netherlands, Poland, Columbia, Switzerland, Slovenia EMRSA 3 European endemic strain, isolated from blood, pus, etc in hospital. Also frequently isolated from carriers in numerous countries. 8 UK, Canada, Netherlands, Scotland, Ireland, Australia, US (NY,MD) France, Germany, Denmark, Sweden, Greece, Switzerland, Belgium EMRSA 2,6,7,12,13,14 European endemic strains, isolated from blood, pus, etc in hospital. Also frequently isolated from carriers in numerous countries 45 Canada, Belgium, Germany, Sweden, Finland, Netherlands, UK, US (NY), Australia, Switzerland European endemic strains, isolated from blood, pus, etc in hospital. Also frequently isolated from carriers in numerous countries 105 US (FL), Switzerland Only 3 strains added to date, 1 isolated from urine, two from unknown clinical source. All isolates from hospital
Dice (Opt:1.00%) (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0%-100.0%]PFGE 100 90 80 70 60 50 PFGE . . . . . . . . . . . . . . . CBD0468 CBD0541 CBD0611 CBD0674 CBD0685 CBD0737 CBD0665 CBD0677 CBD0479 CBD0692 CBD0704 CBD0734 CBD0471 CBD0613 CBD0542 CBD0717 CBD0727 CBD0728 CBD0637 CBD0467 CBD0618 CBD0644 CBD0652 CBD0472 CBD0482 CBD0736 CBD0885 CBD0633 CBD0614 CBD0691 Wound Wound Wound Nose Wound Wound Nose Nose Wound Nose Sputum Nose Urine Nose Blood Nose Blood Blood Nose Blood Nose Nose Nose Blood Wound Nose Urine Nose Wound Nose WA WA FL FL FL FL FL FL WA FL FL FL WA FL WA FL FL FL FL WA FL FL FL WA WA FL FL FL FL FL 8 8 8 8 8 8 8 8 8 8 8 5 5 5 105 5 5 5 5 5 5 5 5 5 5 5 8 105 5 45 Figure 12. BioNumerics analysis and MLST data. Dendrograms were derived from the unweighted pair group method using arithmetic averages and based on Dice coefficients. Band position tolerance and optimization were set at 1.0%. The sequence types for MLST as assigned using the online database (saureus.mlst.net) appear in the final column. 61
62 PCR Amplification of spa Region of CA-MRSA The 30 CA-MRSA isolates that were characterized by PFGE and MLST were further characterized by spa typing. PCR was performed for the CA-MRSA using the genomic template isolated for MLST and the primers listed in Table 4. Amplification for spa typing required the use of two different forward primers, spaF1 or spaF2 (Table 4). PCR amplification of all isolates was initially performed using the spaF1 primer. These initial results indicated that CBD0614 produced a product that was much smaller in size than the rest of the isolates tested. This isolate was amplified again using the spaF2 primer which resulted in the same small sized fragment suggesting that this isolate possesses a low number of spa repeats (Figure 13). The initial amplification of CBD0633 using the spaF1 primer failed but was successful using the spaF2 primer as shown in Figure 13. Amplification of the spa region resulted in the same size fragments for all isolates except CBD0614 (Figure 13), CBD0633 (Figure 13), CBD0691 (Figure 14), and CBD0885 (Figure 14). The PCR primers, primer dimers, and enzymes were removed from the amplification reactions prior to sequencing using the Wizard PCR Preps kit and 1 l of the resulting product was run on a gel to confirm a single band was present (not shown).
Marker MarkerCBD0644 CBD0468 CBD0467 CBD0637 CBD0633 CBD0618 CBD0614 CBD0613 CBD0611 CBD0542 CBD0541 CBD0482 CBD0479 CBD0472 Control CBD0471 Figure 13. Amplification of spa region. Polymerase chain reaction was performed on 30 S. aureus isolates to amplify the spa region for molecular typing. In the 15 isolates pictured, the amplified region ranged in size due to the number of 24 base pair spa repeats in each isolate. CBD0614 possesses only two spa repeats, and CBD0633 possesses only nine spa repeats, accounting for the small size of the products pictured, while the remaining isolates all contain 10 spa repeats. The marker used on this gel was Promega Benchtop Ladder. The last lane pictured was the no DNA control. 63
MarkerCBD0885 CBD0665 CBD0652 CBD0737 CBD0736 CBD0734 CBD0728 CBD0727 CBD0717 CBD0704 CBD0692 CBD0691 CBD0685 CBD0677MarkerCBD0674 Figure 14. Amplification of spa region. Polymerase chain reaction was performed on 30 S. aureus isolates to amplify the spa region for molecular typing. In the 15 isolates pictured, the amplified region ranged in size due to the number of 24 base pair spa repeats in each isolate. CBD0691 possesses only seven, and CBD0885 only six spa repeats, accounting for the small size of the products pictured. The remaining isolates all contain 10 spa repeats. The marker used on this gel was Promega Benchtop Ladder. 64
65 DNA Sequencing, Alignment, and Assigning of Repeats and spa Types for CAMRSA spa Typing. A minimum of four forward and four reverse sequencing reactions were performed for each PCR product analyzed, comprising 8 sequencing reactions for each of the 30 isolates examined. The resulting DNA sequences were uploaded to the SeqMan program for alignment. The use of eight sequences for each isolate removed ambiguity in base calling. The repeat regions were easily identified in the aligned sequences by visual examination of the consensus sequence (Figure 15). The majority of the isolates in the study were found to contain 10 repeats (Table 11). Exceptions included CBD0614 (2 repeats), CBD0633 (9 repeats), CBD0691 (7 repeats) and CBD0855 (6 repeats) as shown in Table 11. Each repeat region was then entered into the spa database for comparison to known spa repeats worldwide. The online repeat finder allowed individual repeats to be cut and paste into the database and repeats assigned. All isolates used in this study contained repeats of 24 base pairs that had previously been identified and were therefore able to be assigned numbers using the online tool (Table 11). The pattern of the repeats was then entered into the database for comparison against known spa types and spa types were assigned when possible. For example, CBD0479 contained 10 repeats with the following pattern: R11-19-12-21-17-34-24-34-22-25, a pattern previously identified, and assigned to spa type 8 (Table 11). A total of six spa types were identified in the study, including spa type 2, spa type 8, spa type 586, and three isolates with unknown spa types that were not identical to one another. Information from the worldwide database on the known spa types is presented in Table 12.
66 479 AAAAGAGGAAGACAATAACAAGCCTGGCAAAGAAGACAAT AACAAGCCTGGCAAAGAAGA 60 685 AAAAGAGGAAGACAATAACAAGCCTGGCAAAGAAGACAAT AACAAGCCTGGCAAAGAAGA 60 674 AAAAGAGGAAGACAATAACAAGCCTGGCAAAGAAGACAAT AACAAGCCTGGCAAAGAAGA 60 ************************************************************ 479 CAACAACAAGCCT GGTAAAGAAGACAACAACAAGCCTGGC AAAGAAGACGGCAACAAGCC 120 685 CAACAACAAGCCT GGTAAAGAAGACAACAACAAGCCTGGC AAAGAAGACGGCAACAAGCC 120 674 CAACAACAAGCCT GGTAAAGAAGACAACAACAAGCCTGGC AAAGAAGACGGCAACAAGCC 120 ************************************************************ 479 TGGTAAAGAAG ACAACAAAAAACCTGGTAAAGAAGATGGC AACAAGCCTGGTAAAGAAGA 180 685 TGGTAAAGAAG ACAACAAAAAACCTGGTAAAGAAGATGGC AACAAGCCTGGTAAAGAAGA 180 674 TGGTAAAGAAG ACAACAAAAAACCTGGTAAAGAAGATGGC AACAAGCCTGGTAAAGAAGA 180 ************************************************************ 479 CAACAAAAAACCT GGTAAAGAAGACGGCAACAAGCCTGGC AAAGAAGATGGCAACAAACC 240 685 CAACAAAAAACCT GGTAAAGAAGACGGCAACAAGCCTGGC AAAGAAGATGGCAACAAACC 240 674 CAACAAAAAACCT GGTAAAGAAGACGGCAACAAGCCTGGC AAAGAAGATGGCAACAAACC 240 ************************************************************ 479 TGGT 244 685 TGGT 244 674 TGGT 244 **** Figure 15. Clustal W (1.82) multiple sequence alignment for spa typing. Alignment of the sequences of the spa genes from three S. aureus isolates demonstrates 100% identity resulting in the assignment of the same repeats and the same spa type for these three isolates.
67 TABLE 11. Summary of spa repeats and spa type Strain Source State Repeat Pattern spa Type CBD0467 Blood WA R26-2317-34-17-20-17-12-17-16 2 CBD0468 Wound WA R11-1912-21-17-34-24-34-22-25 8 CBD0471 Urine WA R26-23-17-34-17-20-17-12-17-16 2 CBD0472 Blood WA R26-2317-34-17-20-17-12-17-16 2 CBD0479 Wound WA R11-1912-21-17-34-24-34-22-25 8 CBD0482 Wound WA R26-2317-34-17-20-17-12-17-16 2 CBD0541 Wound WA R11-1912-21-17-34-24-34-22-25 8 CBD0542 Blood WA R26-2317-34-17-20-17-12-17-16 2 CBD0611 Wound FL R11-19-12-21-17-34-24-34-22-25 8 CBD0613 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0614 Wound FL R26-16 586 CBD0618 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0633 Nose FL R26-23-17-34-17-12-17-17-16 Unknown CBD0637 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0644 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0652 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0665 Nose FL R11-19-12-21-17-34-24-34-22-25 8 CBD0674 Nose FL R11-19-12-21-17-34-24-34-22-25 8 CBD0677 Nose FL R11-19-12-21-17-34-24-34-22-25 8 CBD0685 Wound FL R11-19-12-21-17-34-24-34-22-25 8 CBD0691 Nose FL R8-16-2-43-34-17-34 Unknown CBD0692 Nose FL R11-19-12-21-17-34-24-34-22-25 8 CBD0704 Sputum FL R11-19-12-21-17-34-24-34-22-25 8 CBD0717 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0727 Blood FL R26-23-17-34-17-20-17-12-17-16 2 CBD0728 Blood FL R26-23-17-34-17-20-17-12-17-16 2 CBD0734 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0736 Nose FL R26-23-17-34-17-20-17-12-17-16 2 CBD0737 Wound FL R11-19-12-21-17-34-24-34-22-25 8 CBD0885 Urine FL R11-34-24-34-22-25 Unknown
68 TABLE 12. Summary of spa Type Information ST Geographical Location (s) of ST Additional Information 2 France, Germany, Norway, Sweden, Denmark, Hungary, Austria, Italy, Belgium EMRSA-3, New York clone, Japan clone, Pediatric, Match to isolates with USA100 and USA800 pulsotypes. Matches isolates with MLST types 5, 231, 113 8 Germany, France, Sweden, Norwary, Denmark, Netherlands, Austria, Italy, Belgium Northern German MRSA (subclone), Matched isolates with USA 300 pulsotype, Archaic/Iberian. Matches isolates with MLST type 8. 586 Germany Only 2 isolates in Germany, no further information available. Comparison of PFGE, MLST, and spa Typing Data for 30 CA-MRSA Isolates. Sequence types and spa types were added to the dendrogram prepared for the 30 S. aureus isolates using the S. aureus PFGE database (Figure 16). The isolates were grouped into four sequence types by MLST and six spa types (Figure 16). As previously noted in the worldwide database (Table 12) isolates with patterns consistent with USA 300 controls were spa type 8, and isolates consistent with USA 100 controls were spa type 2 (control data not shown). The 30 CA-MRSA isolates were assigned to four sequence types by MLST and six spa types by staphylococcal protein A typing. However, these subtypes were further differentiated into 21 pulsotypes by PFGE as demonstrated in Figure 17.
Dice (Opt:1.00%) (Tol 1.0%-1.0%) (H>0.0% S>0.0%) [0.0% -100.0%]PFGE 100 90 80 70 60 50 PFGE . . . . . . . . . . . . . . . CBD0468 CBD0541 CBD0611 CBD0674 CBD0685 CBD0737 CBD0665 CBD0677 CBD0479 CBD0692 CBD0704 CBD0613 CBD0734 CBD0717 CBD0542 CBD0471 CBD0727 CBD0728 CBD0637 CBD0644 CBD0652 CBD0467 CBD0618 CBD0614 CBD0472 CBD0482 CBD0736 CBD0633 CBD0885 CBD0691 Wound Wound Wound Nose Wound Wound Nose Nose Wound Nose Sputum Nose Nose Nose Blood Urine Blood Blood Nose Nose Nose Blood Nose Wound Blood Wound Nose Nose Urine Nose WA WA FL FL FL FL FL FL WA FL FL FL FL FL WA WA FL FL FL FL FL WA FL FL WA WA FL FL FL FL 8 8 8 8 8 8 8 8 8 8 8 5 5 5 105 5 5 5 5 5 5 5 5 5 5 5 5 105 8 45 8 8 8 8 8 8 8 8 8 8 8 2 2 2 2 2 2 2 2 2 2 2 2 586 2 2 2 UNK UNK UNK Figure 16. BioNumerics analysis including PFGE, MLST, and spa data. Dendrograms were derived from the unweighted pair group method using arithmetic averages and based on Dice coefficients. Band position tolerance and optimization were set at 1.0%. The sequence types for MLST appear in the second to last column and the spa types appear in the final column. 69
70 ST45 Unk spa type CBD0691 CBD0633 CBD0542 CBD0613 CBD0734 CBD0717 CBD0637 CBD0644 CBD0652 CBD0467 CBD0618 471/727/728* 472/482/736** CBD0704 USA300*** CBD0885 CBD0614 CBD0665 CBD0677 CBD0479 CBD0962 ST105 ST5 ST8 Unk spa type spa type 2 spa type 8 spa type 586 Unk spa type CBD0471, CBD0727, CBD0728 have identical pulsotypes ** CBD0472, CBD0482, CBD0736 have identical pulsotypes *** CBD0468, CBD0541, CBD0611, CBD0674, CBD 0685, CBD0727 are USA300 pulsotype Figure 17. Summary of PFGE pulsotypes, spa types, and Sequence types for 30 CAMRSA isolates. Typing the 30 CA-MRSA resulted in 21 PFGE pulsotypes, 6 spa types, and 4 MLST sequence types as illustrated.
71 Discussion Staphylococcus aureus causes a wide variety of diseases both within the hospital environment and in the community. S. aureus is one of the most commonly diagnosed bacterial infections which causes diseases ranging from self-limiting food poisoning to life-threatening septicemia and pneumonia. Control and treatment options for this organism are complicated by its remarkable ability to adapt to its environment especially through the acquisition of antibiotic resistance determinants. The most alarming trend in recent years was the acquisition of methicillin resistance that rendered the use of all lactam antibiotics useless for S. aureus infections. More recently, MRSA strains have been identified in persons in the community who lack the traditional risk factors for S. aureus infection. The CA-MRSA infections are of particular public health concern because they result in serious diseases including necrotizing fasciitis and necrotizing pneumonia. The high morbidity, mortality, and cost of care for strains such as these highlights the need for public health, hospital, and other laboratories to accurately identify these microorganisms. These factors illustrate the need for a proactive approach to surveillance, identification of hypervirulent strains, and infection control measures to prevent spread of the organism and to provide the most effective treatment options to patients. In this project S. aureus isolates that were collected from Florida and Washington states and from a variety of clinical diseases were used to establish a large database of
72 DNA fingerprint patterns. Only community-acquired, methicillin-resistant isolates were included in this study. The definition of community-acquired S. aureus includes isolates collected within 72 hours of hospitalization, nonmulti-drug resistant isolates, and isolates collected from persons with no prior history of hospitalization (64). The present study used slightly more stringent characteristics in that CA-MRSA is defined as isolates collected in an outpatient setting, or isolates collected no more than 48 hours after hospitalization, and only one isolate per patient was used in the analyses. The DNA fingerprint patterns resulting from PFGE were analyzed using the BioNumerics software package to create dendrograms used for phylogenetic comparison of the isolates. A total of 403 isolates were analyzed and compared to a number of control strains (Appendix 1). Although a large number of the isolates included in the study demonstrated sporadic pulsotypes (Figure 2), the dendrogram contained two pulsotypes consistent with the control strains USA 300 and USA 100. Identifying these repeat pulsotypes among the isolates was the first step in surveillance for hypervirulent clones and it established the presence of the epidemic CA-MRSA isolate USA 300 in both Florida and Washington states, geographic regions in which neither strain had previously been identified (91). A total of 136 of the CA-MRSA isolates analyzed possessed patterns consistent with USA 300 a strain that is known to carry the PVL toxin genes and to cause serious wound infection. Consistent with other repor ts, the majority of these organisms were isolated from wound cultures, and most of the wound cultures included in this study contained the USA 300 strain. This finding has important implications for public health measures to control the spread of this isolate. First, this strain accounts for the greatest
73 majority of all of the isolates included in this study, a fact that is probably related to its epidemic potential as described in numerous other studies (12, 24, 70, 72, 110). Second, the strain is known to carry the PVL toxin genes which likely contribute it its ability to cause serious diseases including necrotizing fasciitis and pneumonia in an otherwise healthy person with none of the usual risk factors related to S. aureus infection (12, 37, 71). Finally, this strain, while resistant to methicillin and therefore all of the -lactam antibiotics, is not generally resistant to antimicrobials such as trimethoprimsulfamethoxazole (Bactrim ), and therefore the usual recommended treatment for MRSA, vancomycin, can be avoided. The use of vancomycin for the treatment of MRSA should be discouraged as it is believed to contribute to the evolution of VRSA (vancomycin-resistant S. aureus ) (45). However, vancomycin is commonly used to treat MRSA as most cases are believed to be multi-drug resistant and therefore untreatable by any other antimicrobial therapy. The knowledge that this strain is circulating within a community can be used along with other clinical factors to guide the treatment plan for patients. The presence of the USA 100 strain among the CA-MRSA, accounting for 88 of the isolates included in this study, was unexpected as this isolate was previously reported as a hospital-acquired strain (70). This strain was identified primarily in isolates from the nose and blood (Table 6). It is interesting to note that USA 100 strain does not carry the PVL genes and has not been associated with any particular disease etiology in contrast to USA 300. Therefore, it is possible that USA 100 is present in a large number of isolates collected from the nose because it is primarily involved in colonization rather than infection. The presence of USA 100 in blood isolates is not easily interpreted due to
74 the low number of blood isolates included in this study. There are two major public health implications of the presence of this strain in the community. First, it appears that a classically hospital-acquired isolate has moved into the community (70). Traditionally CA-MRSA included only those isolates harboring the SCC mec IV element. In contrast, USA 100 carries the SCC mec type II resistance element. Second, studies have shown that MRSA carriers are most likely to develop staphylococcal disease caused by the same isolate that they harbor (18, 19, 46). The spread of isolates within the community, and from the hospital to the community, are both scenarios of public health concern. One possible mechanism for the spread of epidemic clones from the hospital environment to the community may be transmission by asymptomatic carriers. A study of CA-MRSA epidemiology suggested that surveillance for S. aureus isolates should include periodic nasal colonization studies, a method which could also be used to track the USA 100 isolates (119). Monitoring the rates of MRSA nasal carriage among otherwise healthy individuals followed by appropriate treatment to eliminate strains, even in persons who do not display symptoms of disease, may be warranted to stop the spread of epidemic strains. The identification of the two epidemic strains has illustrated the usefulness of PFGE in surveillance studies and it is to data considered the Gold Standard for typing of S. aureus isolates. However, an unanswered concern regarding S. aureus PFGE is that the use of just one restriction enzyme does not explore the potential discriminatory power of the technique. Studies using organisms such as Salmonella have demonstrated that the use of multiple enzymes often unmasked relationships that were not seen using single digest macrorestriction (88). The present study demonstrated through the use of virtual
75 digestion that secondary enzymes could be identified for S. aureus PFGE (Table 7) but that the discriminatory power was unchanged by the use of more than one enzyme (Figures 3-8). Therefore Sma I digestion is sufficient for S. aureus PFGE but unfortunately results in data that at present cannot easily be shared between laboratories. Compilation of data on the spread of CA-MRSA in the United States currently requires a review of the pertinent lite rature as no nationwide database for S. aureus exists. The CDC currently compiles DNA fingerprint data on a number of organisms to track food-borne outbreaks in a program referred to as PulseNet. In a 2003 publication the CDC reported in house efforts at establishing a national database for MRSA (70). However, since that publication there has been no standardization of the S. aureus PFGE protocol, no guidelines for certifying laboratories to submit isolates, and conflicting information concerning the pulsotypes which are considered epidemic clones (70, 109). A standardized protocol will be required for S. aureus researchers to compare data and control strains will be necessary for each group to determine if epidemic isolates are circulating in their communities. Furthermore, the criteria for certifying laboratories to submit data to PulseNet is extensive and the data flow is unidirectional. One of the major concerns of PulseNet participants, as presented at the 2005 PulseNet Update Meeting in Atlanta, was that data is sent to CDC and no analysis is returned to the submitting group. Without a detailed report on the isolates present in the community the chain from identification to treatment is broken and the user gets very little out of participating in PulseNet. As a result of requesting CA-MRSA isolates from various clinical entities this study essentially monitored those communities for the presence of S. aureus isolates of
76 interest during the period the isolates were collected. Using the database created from PFGE data two epidemic S. aureus isolates were identified that could potentially have considerable public health impact. Ideally this data could now be shared with clinicians working in the effected area. However, the study was limited to distinct geographical areas, primarily Central Florida, and Washington State, and little is known how these isolates compare to those present in the rest of the United States or worldwide. Such information would be of great value as data comparison would result in better understanding of how the isolates are spread which in turn can direct public health efforts to prevent their spread. While the United States has not yet established a network for tracking S. aureus isolates, other countries such as Canada, Australia, and several European countries routinely track S. aureus isolates using PCR-based techniques (2, 25, 77, 87). The use of gel-based techniques for molecular typing has a considerable number of advantages and disadvantages as listed in Table 2. PFGE is considered the Gold Standard for S. aureus typing due in large part to the following advantages listed in the table; high discriminatory power, all isolates are typeable, and results are highly reproducible. Regardless of these advantages, the disadvantage of low portability of data and the time-consuming nature of performing PFGE makes the technique less than desirable for some public health applications. As a consequence, efforts are underway to identify a technique that is fast, has high discriminatory power, and results in highly portable data. Any technique that results in numerical or sequence data is going to be highly portable while those involving analysis of gels are no more applicable than PFGE. Therefore the many available techniques that involve restriction digest to generate
77 fingerprints such as REA, riboprinting, and MLEE were not considered for this study. The PCR and sequence-based techniques such as multilocus sequence typing that directly compares sequence data for the presence of single nucleotide changes, and spa typing in which tandem repeats in a particular genomic region are analyzed and compared, were considered the best options for this study. These two typing techniques have been extensively used in characterizing S. aureus isolates overseas but neither has been applied to the study of CA-MRSA isolates in the United States. Thirty isolates from the PFGE database which represent both Florida and Washington, a number of disease etiologies, and a variety of pulsotypes as determined by PFGE, were analyzed by both MLST and spa typing (Figure 9). The goal of this analysis was to determine if these PCR-based techniques would be useful in identifying the hypervirulent clones among the CA-MRSA isolates thereby providing an alternative to PFGE typing. Multilocus sequence typing was performed on the 30 isolates according to the well-established protocol and resulted in allele assignment and sequence types for all isolates tested (Table 8). The genes used for the MLST were housekeeping genes that are present in all isolates with has two advantages for the technique. First, these genes must be present in all S. aureus isolates so therefore all isolates should be typeable by MLST. Second, variation in the housekeeping genes is slow and genetic relationships between clones can therefore be detected. Unfortunately, there is little variation in the housekeeping genes among CA-MRSA isolates as demonstrated in Table 8. Sequence results from one of the regions, internal fragment of the glp gene, demonstrated the same result for all isolates, except one (CBD0691), indicated that nearly all of the isolates have the same allele at this locus. Alleles with no variation such as this are of no value to the
78 technique and omission of this gene would have resulted in the same overall result. The lack of variation among the isolates resulted in only 4 STs identified among the 30 CAMRSA isolates. Furthermore, isolates with significantly different PFGE patterns, as well as different phenotypes (data not shown), such as CBD0885 and CBD0467, possessed the same allelic pattern and were therefore assigned to the same sequence type. The MLST approach was designed to measure the evolutionary differences between S. aureus isolates. Variations in housekeeping genes accumulate very slowly and MLST is therefore suitable to measure changes among specific clones. MLST has been used successfully to create models for the evolution of MRSA from MSSA ancestors and these studies have concluded that MRSA has arisen from at least 5 different lineages (27-29, 31-33). The significance of this is that isolates identified in any location can be compared using the eBURST algorithm to determine how MRSA was introduced into a specific geographic location. Studies such as these using MLST have demonstrated that MRSA evolved from MSSA strains already present within a country in some cases such as Denmark, Germany, and France. Understanding the long-term epidemiology of the spread of MRSA isolates worldwide will likely contribute to efforts to control the spread of other S. aureus strains of interest. For example, other studies have demonstrated the spread of antibiotic resistance genes, other than mec A, and virulence determinants, such as toxin genes, within particular clonal complexes as defined by MLST (113). Each of these studies involved the evolution of a set of genetically related isolates, often described as a clone. However, highly related isolates such as the 30 CA-MRSA isolates used in this study may belong to the same clonal complex and the same clone, but these clones may contain isolates with considerably
79 different pathogenic potential. Isolates belonging to the same clone as defined by MLST in this study were associated with different disease etiologies, possessed different virulence factors, and varied in their resistance patterns (data not shown), all of which contribute to the public health measures necessary for their control and the available treatment options. Therefore it is often necessary to identify S. aureus at the strain level rather than the level of a particular clone, especially when treatment options are considered. The relatively stable core genome of the S. aureus isolates renders the MLST housekeeping gene protocol of little use for typing highly related strains such as MRSA and particularly CA-MRSA which has only been identified in the United States in the last 6 years. Modification of the existing MLST protocol to eliminate genes of little use such as glp and replacing them with hypervariable genes such as surface antigen genes may increase the discriminatory power of the technique. A mix of both conserved and hypervariable genes may be required for adequate discriminatory power that represents the true relationship at the level of the strain and still corresponds to clinical significance. Conversely, it is entirely possible that the use of too many genes may result in closely related stains appearing different due to the increased discriminatory power. Experimentation with different combinations of conserved and hypervariable genes will be required to create a more discriminatory MLST protocol for S. aureus However, regardless of the genes used another major disadvantage of the MLST approach is that it is comparable to PFGE in the amount of time required for the analysis. The required PCR amplification and sequencing of seven genomic regions was not only timeconsuming but significant ambiguity existed in the assignment of alleles for each region.
80 Although multiple sequence reactions were prepared in both the forward and reverse directions, the sequence-calling software often gave numerous results for the same nucleotide leading to repeat sequencing. Furthermore, the large number of sequences required for the assignment of an ST type for a single isolate is costly when compared to PFGE. The major advantage of the technique was that multilocus sequence typing resulted in data that was highly portable and was easily compared to MLST results obtained for strains worldwide using the online database. The four STs identified among the 30 CA-MRSA isolates were present in the database indicating that they had been identified in other studies. For each of the four STs, the database contained information concerning the geographic locations in which isolates with the same ST have been identified. Significantly, the database also contains information on the background of the isolates deposited including such information as clinical site of infection, carrier status, matches to known epidemic clones, and PFGE patterns (Table 10). However, the database is limited to mostly European countries as MLST typing in the rest of the world is rarely performed. A more comprehensive database would be desirable for continued use of this technique, but a similar typing tec hnique that is not as time-consuming or as costly, but results in higher discriminatory power would be more applicable. Several recent studies have demonstrated the applicability of spa typing for typing S. aureus isolates of interest (1, 41, 59, 83, 103, 106). This technique is attractive in that in requires PCR amplification of only the variable region of the spa gene followed by sequencing as opposed to the PCR amplification of seven regions required for MLST. Consequently, the amount of time required and costs involved in spa typing are
81 considerably less than MLST. The 30 CA-MRSA isolates that were typed by MLST were characterized by spa typing in the hopes that this technique would be highly discriminatory, rapid, and inexpensive. The spa typing technique proved to be more rapid than either MLST or PFGE in that results could be obtained in 48 hours as opposed to five days required for the other two techniques. Sequencing of the relatively short spa repeat regions resulted in sequence data that was unambiguous and much more quickly analyzed in comparison to MLST data. However, as with MLST, the discriminatory power of spa typing for the CA-MRSA isolates was considerably less than that of PFGE with only 6 distinct spa types present among the isolates as compared to 21 distinct pulsotypes (Table 11). Furthermore, although all of the repeats identified in this study were present in the spa database, the pattern of three of the isolates was unknown and these could therefore not be assigned to spa types. As demonstrated with the MLST data, spa typing data could be used to search the worldwide database for information regarding the spread of particular spa types, once again including geographical location, clinical data, MLST typing data, and pulsotypes (Table 12). Technically, because spa typing was able to further differentiate subtypes within sequence types defined by MLST, it is the more discriminatory of the two techniques but insomuch as analysis of CA-MRSA isolates is concerned, it does not approach the discriminatory power of PFGE. The variability of the spa gene between MSSA and MRSA isolates appears to be considerably higher than that among CA-MRSA isolates and spa typing has been used successfully to differentiate epidemic and sporadic isolates during nosocomial outbreaks (103). At least two European hospitals have reportedly replaced PFGE with spa typing for analyzing S. aureus isolates present in their facilities (1, 2, 41). Similar to MLST
82 studies, spa typing was used to determine that MRSA strains present in Portugal are not descended from long-established MSSA strains present within the country but were likely imported from abroad (1). Another study of nosocomial outbreaks determined that in each case where spa types were different between isolates, other typing techniques confirmed that the isolates were in fact not related (106). The same study also suggested, and has been demonstrated in the present study, that isolates with the same spa type are not necessarily epidemiologically related (106). The use of spa typing for tracking S. aureus isolates for some applications such as nosocomial spread of isolates and its considerable advantages in terms of time and portability of data would be useful as an initial screen to rule out the necessity of more discriminatory technique such as PFGE. The presence of S. aureus isolates with increased virulence, antibiotic resistance determinants, and high transmissibility is a major public health concern. Active surveillance and application of the appropriate infection control measures will be required to control the spread of these strains. In the present study molecular methods for typing S. aureus isolates, the first step in surveillance, were compared for their ability to type a set of closely related CA-MRSA isolates. No one particular method excelled at typing these isolates in terms of discriminatory power, length of analysis, cost, and portability of data. These data suggest that the technique used for typing should be selected based on the purpose of the typing study. Cost and availability of the required equipment will of course also determine what typing methods can be used to type S. aureus All of the techniques discussed herein require highly specialized and costly equipment including PFGE gel boxes, thermocyclers, and nucleic acid sequencers. Many laboratories may not have access to any of this equipment and may be required to send
83 samples to other laboratories for testing. However, an ever-increasing number of hospital and public health laboratories do have access to this equipment and an application of each of the techniques to particular studies follows. Infection control in a hospital environment is critical to prevent acquisition of nosocomial infection. Outbreaks of nosocomial infection caused by S. aureus in the hospital environment are common and can be caused by either MSSA or MRSA. Infection control measures must be implemented to control the spread as quickly as possible but what measures are used depends on the extent of the spread. For example, if the surgical and ICU wards are both reporting S. aureus outbreaks, it is imperative that the infection control practitioners know if the same strain is responsible for the outbreaks in both locations. A quick way to determine if the strains are different is to use spa typing. Strains with different spa types are epidemiologically unrelated and therefore infection control measures unique to each ward should be initiated. Conversely, those strains with identical spa types may be related, and this could then be confirmed using PFGE. In this case, the outbreak is likely from a common source and efforts should be directed at identifying infected personnel working in both wards or shared equipment. Following this same scenario, spa typing could then be used to rule out infection from healthcare workers who may be colonized with S. aureus In the event of a matching spa type, PFGE could then be used to confirm the outbreak strain originated with the healthcare worker. Infection control measures can then be aimed at treating the healthcare worker as well as providing infection control prevention education. Another use of spa typing is to rule out recurrent infection in carriers as opposed to successive infection with a different strain. An initial screening by spa typing can aid in determining
84 if post-surgical infections are most likely to occur due to the patients own flora or nosocomially-acquired infection as hospital-acquired strains are significantly different in spa types from community-acquired S. aureus. Finally, in an outbreak situation where PFGE confirmed that USA 300 is present in the community, strains from a patient with a wound infection who is otherwise healthy can be analyzed by spa typing to determine if the strain belongs to ST 8 consistent with all USA 300 isolates. This patient could then be considered part of the outbreak and treated with the appropriate antibiotics. Although most of the studies that are listed above as examples of spa typing applications could also be performed using MLST, spa typing for these applications has considerable advantages in terms of time and cost. Large-scale epidemiological studies are often more concerned with the origins of the strains present in a geographic location during a particular time frame. MLST studies have been used to track the origins of MRSA in many countries, and have in particular demonstrated that MRSA originated when MSSA strains previously identified in the country developed methicillin-resistance by acquisition of one of the SCC mec mobile elements. These studies have provided a considerable amount of data concerning the worldwide spread of antibiotic-resistant strains. Further applications of this technique will be to track the worldwide spread of the Panton-Valentine Leukocidin toxin genes, other newly described toxin genes, and other virulence factors. MLST analysis of strains that are present in a particular community over a long time period will demonstrate which clonal complexes are most successful in that community. Analysis of the strains present within that clonal complex can then be used to determine what factors likely determine the evolutionary advantage that allows those strains to be successful. Although spa
85 typing can be used for similar studies, the lack of an algorithm to define the precise evolutionary relationships between spa types, as is present for sequence types in the eBURST analysis program, limits the use of spa typing for long-term evolutionary studies. As demonstrated with the CA-MRSA isolates, often it is only the most discriminatory of the techniques that is required for a particular study. Only PFGE was able to identify the presence of the USA 300 isolates in Florida and Washington State. The presence of this highly virulent, highly transmissible pathogen in the community has significant public health consequences. The treatment of these patients can be guided by the knowledge that this strain carries the methicillin-resistance SCC mec IV element and is known to be susceptible to other antibiotics, negating the need to perform antibiotic susceptibility testing, and hopefully preventing the use of vancomycin to treat the infection. It is well known that this isolate is easily spread among athletes, prisoners, and others sharing common facilities which can guide infection control measures within these facilities. Often hospitals are contaminated with particular isolates for long periods of time and the source of the isolates are never discovered. Detailed information regarding the susceptibilities of these nosocomial inhabitants is often well known and nosocomial infections within that facility are treated accordingly. PFGE testing of hospital strains can determine what isolates are present and therefore more likely to cause nosocomial infection and have in the past detected changes from one dominant strain to another, leading to changes in the appropriate therapy. Periodic nasal colonization studies in the community can be used to determine what strains are present among carriers. These strains are important as most S. aureus infections are caused by the persons normal flora.
86 As demonstrated in the present study, PFGE identified the USA 100 epidemic clone among community-acquired S. aureus isolates. The public health significance of this finding is that a traditionally hospital-acquired MRSA is present in large numbers in the community. This data can be used to create a model for the spread of this isolate and to guide public health efforts to prevent further spread. As mentioned above, the use of spa typing can rule out infections with identical strains in many cases, but PFGE must be used to confirm that the strains are in fact identical. Although PFGE provides considerable advantages in terms of discriminatory power, global studies involving the technique will have to wait for the establishment of PFGE fingerprinting databases and standardized protocols. Surveillance programs for the spread of S. aureus isolates should be implemented by laboratories at the local, state, federal, and worldwide levels to guide infection control practices, to determine effective treatment therapies, to describe the epidemiology of the spread of S. aureus and to study the evolution of the strains. No one typing method is available to address all of these areas. Those typing methods such as PFGE that detect rapid variation are well-suited to outbreak investigations, while the typing methods that categorize isolates by relatively stable genetic loci such as MLST and spa typing are more suited to long-term epidemiological and evolutionary studies. Future studies should include improvements to each of the techniques. A worldwide database of DNA fingerprint pa tterns obtained using a standardized PFGE protocol is necessary to address the issue of portability of data. Furthermore, newer PFGE protocols for S. aureus are under development to shorten the time period required for analysis. Modification of the MLST pr otocol to include both variable and highly-
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109 Appendix A. List of all Staphylococcus aureus isolates in BioNumerics database Number CBD Number Origin Source Antibiotype Pulsotype 1 CBD0007 Feces ATCC Unknown Sporadic 2 CBD0019 Food DuPont Unknown Sporadic 3 CBD0034 Wound Fisher Scientific MSSA Sporadic 4 CBD0035 Food Dept. of Health Unknown Sporadic 5 CBD0036 Feces ATCC Unknown Sporadic 6 CBD0044 Unknown ATCC MSSA Sporadic 7 CBD0064 Unknown ATCC Unknown Sporadic 8 CBD0467 Sputum WA MRSA Sporadic 9 CBD0468 Wound WA MRSA USA 300 10 CBD0469 Blood WA MRSA USA 300 11 CBD0470 Sputum WA MRSA Sporadic 12 CBD0471 Urine WA MRSA Sporadic 13 CBD0472 Blood WA MRSA Sporadic 14 CBD0473 Sputum WA MSSA Sporadic 15 CBD0474 Wound WA MSSA Sporadic 16 CBD0475 Wound WA MSSA Sporadic 17 CBD0476 Urine WA MSSA USA 400 18 CBD0477 Wound WA MSSA Sporadic 19 CBD0478 Wound WA MRSA Sporadic 20 CBD0479 Wound WA MRSA Sporadic 21 CBD0480 Sputum WA MRSA Sporadic 22 CBD0481 Blood WA MRSA Sporadic 23 CBD0482 Wound WA MRSA Sporadic 24 CBD0483 Sputum WA MRSA Sporadic 25 CBD0484 Blood WA MRSA USA 100 26 CBD0485 Sputum WA MRSA USA 100 27 CBD0486 Wound WA MRSA Sporadic 28 CBD0504 Unknown FL MSSA Sporadic 29 CBD0505 Unknown LifeLink MSSA Sporadic 30 CBD0526 Wound WA MSSA Sporadic 31 CBD0527 Wound WA MSSA Sporadic 32 CBD0528 Wound WA MSSA Sporadic 33 CBD0529 Wound WA MSSA Sporadic 34 CBD0530 Body Fluid WA MSSA Sporadic 35 CBD0531 Wound WA MSSA Sporadic 36 CBD0532 Wound WA MSSA Sporadic 37 CBD0533 Sputum WA MSSA Sporadic 38 CBD0534 Sputum WA MSSA Sporadic 39 CBD0535 Sputum WA MSSA Sporadic 40 CBD0536 Sputum WA MSSA Sporadic 41 CBD0537 Sputum WA MSSA Sporadic 42 CBD0538 Sputum WA MSSA Sporadic 43 CBD0539 Wound WA MRSA USA 300 44 CBD0540 Wound WA MRSA USA 300 45 CBD0541 Wound WA MRSA USA 300 46 CBD0542 Blood WA MRSA USA 100 47 CBD0543 Unknown Unknown MRSA Sporadic
110 Number CBD Number Origin Source Antibiotype Pulsotype 48 CBD0544 Wound ATCC MSSA Sporadic 49 CBD0545 Sputum ATCC MSSA Sporadic 50 CBD0546 Marine Sponge FL MSSA Sporadic 51 CBD0611 Wound FL MRSA USA 300 52 CBD0612 Wound FL MRSA USA 300 53 CBD0613 Nose FL MRSA USA 100 54 CBD0614 Wound FL MRSA USA 100 55 CBD0615 Blood FL MRSA USA 100 56 CBD0616 Blood FL MRSA Sporadic 57 CBD0617 Wound FL MRSA Sporadic 58 CBD0618 Nose FL MRSA USA 100 59 CBD0619 Nose FL MRSA USA 100 60 CBD0620 Urine FL MRSA USA 100 61 CBD0621 Nose FL MRSA USA 100 62 CBD0622 Urine FL MRSA USA 100 63 CBD0623 NRS 77 NARSA Unknown PFGE Standard 64 CBD0624 Nose FL MRSA USA 100 65 CBD0625 Nose FL MRSA USA 100 66 CBD0626 Nose FL MRSA USA 100 67 CBD0627 Cervix FL MRSA Sporadic 68 CBD0628 Feces FL MRSA Sporadic 69 CBD0629 Blood FL MRSA Sporadic 70 CBD0630 Nose FL MRSA USA 100 71 CBD0631 Blood FL MRSA USA 100 72 CBD0632 Sputum FL MRSA Sporadic 73 CBD0633 Nose FL MRSA Sporadic 74 CBD0634 Blood FL MRSA USA 100 75 CBD0635 Blood FL MRSA USA 100 76 CBD0636 Nose FL MRSA USA 100 77 CBD0637 Nose FL MRSA USA 100 78 CBD0638 Nose FL MRSA USA 100 79 CBD0639 Nose FL MRSA USA 100 80 CBD0640 Wound FL MRSA USA 300 81 CBD0641 Nose FL MRSA USA 100 82 CBD0642 Nose FL MRSA USA 100 83 CBD0643 Nose FL MRSA Sporadic 84 CBD0644 Nose FL MRSA Sporadic 85 CBD0645 Nose FL MRSA Sporadic 86 CBD0646 Wound FL MRSA USA 100 87 CBD0647 Wound FL MRSA USA 100 88 CBD0648 Blood FL MRSA USA 100 89 CBD0649 Blood FL MRSA Sporadic 90 CBD0650 Sputum FL MRSA Sporadic 91 CBD0651 Nose FL MRSA USA 100 92 CBD0652 Nose FL MRSA Sporadic 93 CBD0653 Blood ATCC MRSA Sporadic 94 CBD0654 NRS100 NARSA MRSA Sporadic 95 CBD0655 NRS271A NARSA MRSA Sporadic 96 CBD0656 NRS271B NARSA MRSA Sporadic 97 CBD0662 Sputum FL MRSA Sporadic 98 CBD0663 Nose FL MRSA USA 100
111 Number CBD Number Origin Source Antibiotype Pulsotype 99 CBD0664 Nose FL MRSA Sporadic 100 CBD0665 Nose FL MRSA Sporadic 101 CBD0666 Blood FL MRSA USA 100 102 CBD0667 Blood FL MRSA Sporadic 103 CBD0668 Blood FL MRSA Sporadic 104 CBD0669 Nose FL MRSA USA 300 105 CBD0670 Nose FL MRSA USA 100 106 CBD0671 Nose FL MRSA USA 100 107 CBD0672 Nose FL MRSA Sporadic 108 CBD0673 Nose FL MRSA USA 100 109 CBD0674 Nose FL MRSA USA 300 110 CBD0675 Nose FL MRSA Sporadic 111 CBD0676 Nose FL MRSA USA 100 112 CBD0677 Nose FL MRSA Sporadic 113 CBD0678 Nose FL MRSA USA 100 114 CBD0679 Sputum FL MRSA Sporadic 115 CBD0680 Sputum FL MRSA Sporadic 116 CBD0681 Nose FL MRSA USA 100 117 CBD0682 Nose FL MRSA Sporadic 118 CBD0683 Nose FL MRSA USA 100 119 CBD0684 Nose FL MRSA Sporadic 120 CBD0685 Wound FL MRSA USA 300 121 CBD0686 Nose FL MRSA USA 100 122 CBD0687 Nose FL MRSA USA 100 123 CBD0688 Nose FL MRSA Sporadic 124 CBD0689 Blood FL MRSA USA 300 125 CBD0690 Nose FL MSSA USA 100 126 CBD0691 Nose FL MRSA Sporadic 127 CBD0692 Nose FL MRSA Sporadic 128 CBD0693 Nose FL MRSA USA 100 129 CBD0694 Nose FL MRSA Sporadic 130 CBD0695 Nose FL MRSA Sporadic 131 CBD0696 Blood FL MRSA USA 100 132 CBD0697 Nose FL MRSA USA 300 133 CBD0698 Nose FL MRSA USA 100 134 CBD0699 Nose FL MRSA USA 100 135 CBD0700 Nose FL MRSA USA 300 136 CBD0701 Nose FL MRSA Sporadic 137 CBD0702 Nose FL MRSA USA 300 138 CBD0703 Nose FL MRSA USA 100 139 CBD0704 Sputum FL MRSA Sporadic 140 CBD0705 Nose FL MRSA Sporadic 141 CBD0706 Nose FL MRSA USA 100 142 CBD0707 Nose FL MRSA USA 100 143 CBD0708 Nose FL MRSA Sporadic 144 CBD0709 Nose FL MRSA Sporadic 145 CBD0710 Nose FL MRSA USA 100 146 CBD0711 Nose FL MRSA USA 100 147 CBD0712 Nose FL MRSA USA 300 148 CBD0713 Nose FL MRSA Sporadic 149 CBD0714 Nose FL MRSA Sporadic
112 Number CBD Number Origin Source Antibiotype Pulsotype 150 CBD0715 Feces FL MRSA USA 100 151 CBD0716 Nose FL MRSA USA 100 152 CBD0717 Nose FL MRSA USA 100 153 CBD0718 Sputum FL MRSA Sporadic 154 CBD0719 Sputum FL MRSA Sporadic 155 CBD0720 Nose FL MRSA Sporadic 156 CBD0721 Nose FL MRSA Sporadic 157 CBD0722 Nose FL MRSA Sporadic 158 CBD0723 Nose FL MRSA Sporadic 159 CBD0724 Nose FL MRSA USA 600 160 CBD0725 Nose FL MRSA Sporadic 161 CBD0726 Nose FL MRSA USA 300 162 CBD0727 Blood FL MRSA USA 100 163 CBD0728 Blood FL MRSA USA 100 164 CBD0729 Nose FL MRSA Sporadic 165 CBD0730 Nose FL MRSA Sporadic 166 CBD0731 Nose FL MRSA USA 100 167 CBD0732 Nose FL MRSA USA 100 168 CBD0733 Nose FL MRSA USA 100 169 CBD0734 Nose FL MRSA USA 100 170 CBD0736 Nose FL MRSA Sporadic 171 CBD0737 Wound FL MRSA USA 300 172 CBD0738 Wound FL MRSA USA 300 173 CBD0739 Sputum FL MRSA USA 300 174 CBD0740 Wound FL MRSA USA 300 175 CBD0741 Nose FL MRSA USA 300 176 CBD0742 Nose FL MRSA Sporadic 177 CBD0743 Blood FL MRSA USA 100 178 CBD0744 Nose FL MRSA USA 100 179 CBD0745 Nose FL MRSA USA 100 180 CBD0786 Unknown FL MRSA USA 300 181 CBD0787 Wound FL MRSA USA 300 182 CBD0788 Wound FL MRSA USA 300 183 CBD0789 Wound FL MRSA USA 300 184 CBD0790 Wound FL MRSA Sporadic 185 CBD0791 Unknown FL MRSA USA 300 186 CBD0792 Unknown FL MRSA USA 300 187 CBD0793 Unknown FL MRSA USA 300 188 CBD0794 Unknown FL MRSA USA 300 189 CBD0795 Unknown FL MRSA USA 300 190 CBD0796 Unknown FL MSSA USA 300 191 CBD0797 N315 NARSA MRSA Sporadic 192 CBD0798 N123 NARSA MRSA USA 400 193 CBD0799 Unknown Unknown MRSA Sporadic 194 CBD0800 Unknown Unknown MRSA Sporadic 195 CBD0801 Unknown Unknown MRSA Sporadic 196 CBD0802 Unknown Unknown MRSA Sporadic 197 CBD0803 Unknown Unknown MRSA Sporadic 198 CBD0804 Unknown Unknown MRSA Sporadic 199 CBD0834 Wound FL MRSA USA 300 200 CBD0835 Wound ATCC MSSA Sporadic
113 Number CBD Number Origin Source Antibiotype Pulsotype 201 CBD0836 Wound ATCC MSSA Sporadic 202 CBD0842 Wound FL MRSA USA 300 203 CBD0843 Wound FL MRSA USA 300 204 CBD0844 Wound FL MRSA Sporadic 205 CBD0845 Rectum FL MRSA USA 100 206 CBD0846 Wound FL MRSA USA 100 207 CBD0847 Wound FL MRSA USA 100 208 CBD0848 Wound FL MRSA Sporadic 209 CBD0849 Wound FL MRSA USA 300 210 CBD0850 Wound FL MRSA Sporadic 211 CBD0851 Wound FL MRSA USA 300 212 CBD0852 Wound FL MRSA Sporadic 213 CBD0853 Eye FL MRSA USA 300 214 CBD0854 Wound FL MRSA USA 300 215 CBD0855 Wound FL MRSA Sporadic 216 CBD0856 Wound FL MRSA USA 300 217 CBD0857 Wound FL MRSA USA 100 218 CBD0858 Wound FL MRSA USA 300 219 CBD0859 Wound FL MRSA Sporadic 220 CBD0860 Wound FL MSSA Sporadic 221 CBD0861 Nose FL MRSA USA 300 222 CBD0863 Wound FL MRSA USA 300 223 CBD0864 Wound FL MRSA Sporadic 224 CBD0865 Wound FL MRSA USA 300 225 CBD0866 Wound FL MRSA USA 300 226 CBD0867 Wound FL MRSA USA 300 227 CBD0868 Wound FL MRSA USA 300 228 CBD0869 Wound FL MRSA USA 300 229 CBD0870 Wound FL MRSA USA 300 230 CBD0871 Wound FL MRSA USA 300 231 CBD0872 Wound FL MRSA USA 300 232 CBD0873 Wound FL MRSA Sporadic 233 CBD0874 Wound FL MRSA Sporadic 234 CBD0875 Wound FL MRSA Sporadic 235 CBD0876 Wound FL MRSA USA 300 236 CBD0877 Wound FL MRSA USA 300 237 CBD0878 Eye FL MRSA Sporadic 238 CBD0879 Wound FL MRSA USA 300 239 CBD0880 Eye FL MRSA USA 100 240 CBD0881 Wound FL MRSA USA 300 241 CBD0882 Wound FL MRSA USA 300 242 CBD0883 Wound FL MRSA USA 300 243 CBD0884 Unknown FL MRSA USA 100 244 CBD0885 Urine FL MRSA Sporadic 245 CBD0886 Unknown FL MRSA Sporadic 246 CBD0887 Wound FL MRSA USA 300 247 CBD0888 Urine FL MRSA USA 100 248 CBD0889 Wound FL MRSA USA 300 249 CBD0890 Urine FL MRSA Sporadic 250 CBD0891 Wound FL MRSA USA 300 251 CBD0892 Wound FL MRSA Sporadic
114 Number CBD Number Origin Source Antibiotype Pulsotype 252 CBD0893 Wound FL MRSA USA 300 253 CBD0894 Wound FL MRSA USA 300 254 CBD0895 Wound FL MRSA USA 300 255 CBD0896 Wound FL MRSA Sporadic 256 CBD0897 Unknown FL MRSA USA 100 257 CBD0898 Wound FL MRSA Sporadic 258 CBD0899 Wound FL MRSA USA 300 259 CBD0900 Wound FL MRSA USA 100 260 CBD0901 Wound FL MRSA USA 300 261 CBD0902 Urine FL MRSA Sporadic 262 CBD0903 Wound FL MRSA Sporadic 263 CBD0904 Unknown FL MRSA Sporadic 264 CBD0905 Wound FL MRSA USA 100 265 CBD0906 Wound FL MRSA USA 300 266 CBD0907 Wound FL MRSA USA 300 267 CBD0908 Wound FL MRSA USA 300 268 CBD0909 Wound FL MRSA Sporadic 269 CBD0910 Wound FL MRSA USA 300 270 CBD0911 Wound FL MRSA USA 100 271 CBD0912 Unknown FL MRSA USA 300 272 CBD0913 Wound FL MRSA USA 300 273 CBD0914 Wound FL MRSA USA 300 274 CBD0915 Wound FL MRSA Sporadic 275 CBD0916 Wound FL MRSA USA 100 276 CBD0917 Wound FL MRSA USA 100 277 CBD0918 Wound FL MRSA Sporadic 278 CBD0919 Wound FL MRSA Sporadic 279 CBD0920 Wound FL MRSA USA 300 280 CBD0921 Wound FL MRSA USA 100 281 CBD0922 Wound FL MRSA USA 100 282 CBD0923 Wound FL MRSA USA 300 283 CBD0924 Wound FL MRSA USA 100 284 CBD0925 Wound FL MRSA USA 100 285 CBD0926 Wound FL MRSA Sporadic 286 CBD0927 Nose FL MRSA USA 300 287 CBD0928 Nose FL MRSA Sporadic 288 CBD0929 Wound FL MRSA Sporadic 289 CBD0930 Wound FL MRSA USA 300 290 CBD0931 Wound FL MRSA Sporadic 291 CBD0932 Wound FL MRSA USA 300 292 CBD0933 Wound FL MRSA USA 300 293 CBD0934 Wound FL MRSA USA 100 294 CBD0935 Wound FL MRSA USA 300 295 CBD0936 Wound FL MRSA USA 100 296 CBD0937 Wound FL MRSA USA 300 297 CBD0938 Wound FL MRSA USA 300 298 CBD0939 Wound FL MRSA Sporadic 299 CBD0940 Wound FL MRSA USA 300 300 CBD0941 Wound FL MRSA USA 300 301 CBD0942 Wound FL MRSA USA 300 302 CBD0943 Wound FL MRSA Sporadic
115 Number CBD Number Origin Source Antibiotype Pulsotype 303 CBD0944 Wound FL MRSA Sporadic 304 CBD0945 Wound FL MRSA USA 300 305 CBD0946 Wound FL MRSA USA 300 306 CBD0947 Wound FL MRSA USA 300 307 CBD0948 Wound FL MRSA Sporadic 308 CBD0949 Wound FL MRSA USA 300 309 CBD0950 Wound FL MRSA Sporadic 310 CBD0951 Wound FL MRSA USA 300 311 CBD0952 Wound FL MRSA Sporadic 312 CBD0953 Wound FL MRSA USA 300 313 CBD0954 Wound FL MRSA Sporadic 314 CBD0955 Wound FL MRSA USA 300 315 CBD0956 Wound FL MRSA USA 300 316 CBD0957 Wound FL MRSA USA 300 317 CBD0958 Wound FL MRSA USA 300 318 CBD0959 Wound FL MRSA USA 300 319 CBD0960 Wound FL MRSA USA 100 320 CBD0961 Wound FL MRSA USA 300 321 CBD0963 Wound FL MRSA USA 300 322 CBD0964 Wound FL MRSA USA 300 323 CBD0965 Wound FL MRSA USA 300 324 CBD0966 Wound FL MRSA USA 300 325 CBD0967 Wound FL MRSA USA 300 326 CBD0968 Wound FL MRSA USA 100 327 CBD0969 Wound FL MRSA USA 100 328 CBD0970 Wound FL MRSA Sporadic 329 CBD0971 Wound FL MRSA USA 300 330 CBD0972 Wound FL MRSA USA 300 331 CBD0973 Unknown FL MRSA USA 300 332 CBD0974 Wound FL MRSA Sporadic 333 CBD0975 Wound FL MRSA USA 300 334 CBD0976 Wound FL MRSA USA 300 335 CBD0977 Wound FL MRSA USA 300 336 CBD0978 Wound FL MRSA USA 100 337 CBD0979 Nose FL MSSA Sporadic 338 CBD0997 Wound FL MRSA USA 300 339 CBD0998 Wound FL MRSA Sporadic 340 CBD0999 Wound FL MRSA USA 300 341 CBD1000 Wound FL MRSA USA 300 342 CBD1001 Wound FL MRSA USA 300 343 CBD1002 Wound FL MRSA USA 300 344 CBD1003 Wound FL MRSA USA 100 345 CBD1004 Wound FL MRSA USA 300 346 CBD1006 Wound FL MRSA USA 300 347 CBD1007 Wound FL MRSA USA 300 348 CBD1008 Wound FL MRSA USA 300 349 CBD1009 Wound FL MRSA USA 300 350 CBD1010 Wound FL MRSA USA 300 351 CBD1011 Wound FL MRSA USA 300 352 CBD1012 Wound FL MRSA USA 300 353 CBD1013 Wound FL MRSA Sporadic
116 Number CBD Number Origin Source Antibiotype Pulsotype 354 CBD1014 Wound FL MRSA USA 300 355 CBD1015 Wound FL MRSA USA 300 356 CBD1016 Wound FL MRSA Sporadic 357 CBD1017 Wound FL MRSA USA 300 358 CBD1018 Wound FL MRSA USA 300 359 CBD1019 Wound FL MRSA USA 300 360 CBD1020 Wound FL MRSA USA 100 361 CBD1021 Wound FL MRSA USA 300 362 CBD1022 Wound FL MRSA USA 300 363 CBD1023 Wound FL MRSA Sporadic 364 CBD1024 Wound FL MRSA USA 300 365 CBD1025 Wound FL MRSA USA 100 366 CBD1026 Wound FL MRSA USA 300 367 CBD1027 Wound FL MRSA Sporadic 368 CBD1028 Wound FL MRSA USA 300 369 CBD1029 Wound FL Intermediate USA 400 370 CBD1030 Wound FL MRSA USA 300 371 CBD1031 Wound FL MRSA USA 100 372 CBD1032 Unknown FL MRSA USA 300 373 CBD1033 Wound FL MRSA USA 300 374 CBD1034 Wound FL MRSA USA 300 375 CBD1035 Wound WA Borderline Sporadic 376 CBD1036 Wound WA MRSA USA 300 377 CBD1037 Wound WA MRSA USA 300 378 CBD1038 Wound WA MRSA Sporadic 379 CBD1039 Wound WA MRSA Sporadic 380 CBD1040 Wound WA MRSA USA 300 381 CBD1041 Wound WA MRSA USA 300 382 CBD1042 Wound WA MRSA USA 300 383 CBD1043 Sputum WA MRSA USA 100 384 CBD1044 Wound WA MRSA USA 300 385 CBD1045 Wound WA MRSA USA 300 386 CBD1046 Wound WA MRSA Sporadic 387 CBD1047 Wound WA MRSA USA 300 388 CBD1048 Wound WA MRSA Sporadic 389 CBD1049 Wound WA MRSA USA 100 390 CBD1050 Wound WA MRSA USA 300 391 CBD1051 Nose WA MRSA USA 300 392 CBD1052 Wound WA MRSA USA 300 393 CBD1053 Wound WA MRSA USA 300 394 CBD1054 Sputum WA MRSA USA 100 395 CBD1055 Wound WA MRSA Sporadic 396 CBD1064 USA 100 NARSA MRSA USA 100 397 CBD1065 USA 200 NARSA MRSA USA 200 398 CBD1066 USA 300 NARSA MRSA USA 300 399 CBD1067 USA 400 NARSA MRSA USA 400 400 CBD1068 USA 500 NARSA MRSA USA 500 401 CBD1069 USA 600 NARSA MRSA USA 600 402 CBD1070 USA 700 NARSA MRSA USA 700 403 CBD1071 USA 800 NARSA MRSA USA 800
117 About the Author Jill Roberts received a Bachelor of Science degree in Microbiology from Indiana University in 1996. She received a Master of Public Health degree in Tropical Infectious Diseases from the University of South Florida in 1998. She received a Master of Science degree from the University of Texas in Microbiology and Molecular Genetics in 2003. She entered the Ph.D. program in Global Communicable Diseases at the University of South Florida, College of Public Health in August of 2003.
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Roberts, Jill Carolyne.
Characterization of Community-acquired Methicillin-resistant Staphylococcus aureus by Pulsed-field Gel Electrophoresis, Multilocus Sequence Typing, and Staphylococcal Protein A Sequencing: Establishing a Strain Typing Database
h [electronic resource] /
by Jill Carolyne Roberts.
[Tampa, Fla] :
b University of South Florida,
ABSTRACT: Staphylococcus aureus has long been recognized as a leading cause of nosocomial infection. However, several recent publications have demonstrated this pathogen as the cause of community-acquired severe wound infections and necrotizing pneumonia in otherwise healthy individuals. These highly virulent endemic clones have been reported in several locations in the United States and Canada. The rapid spread of the organism, the ability of certain clones to cause serious infection, and the antibiotic resistance of the endemic clones, illustrates the importance of infection control measures. In this study we examined three S. aureus typing techniques; pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and Staphylococcal protein A (spa) sequencing for subspeciation of community-acquired methicillin-resistant S. aureus (CA-MRSA). It is hypothesized that PFGE will result in a higher level of discrimination among the strains, while MLST and spa typing will result in highly portable data that lacks the discriminatory power of PFGE.Thirty CA-MRSA isolates that were obtained from Florida and Washington State were characterized by molecular typing methods. Whole genome restriction analysis was performed by PFGE using the SmaI enzyme. Sequence-based typing analyses, MLST and spa typing, were performed by polymerase chain reaction (PCR) followed by sequencing. PFGE data was analyzed using the BioNumerics software package and sequence-based data was analyzed using DNAstar. MLST Alleles were assigned using the online MLST database (www.mlst.net) and spa types were assigned using the Ridom SpaServer (www.ridom.de/spaserver). Molecular characterization of the 30 isolates resulted in 21 pulsotypes, four MLST sequence types (STs), and six spa types. Combining data from both MLST and spa typing resulted in only seven strain categories, many of which grouped isolates that are not epidemiologically linked.These data demonstrate that techniques such as MLST and spa typing are not well suited for tracking isolates with limited evolutionary diversity such as the CA-MRSA epidemic clones.
Dissertation (Ph.D.)--University of South Florida, 2006.
Includes bibliographical references.
Text (Electronic dissertation) in PDF format.
System requirements: World Wide Web browser and PDF reader.
Mode of access: World Wide Web.
Title from PDF of title page.
Document formatted into pages; contains 117 pages.
Adviser: Andrew Cannons, Ph.D.
Methicillin-Resistant Staphylococcus aureus.
Electrophoresis, Gel, Pulsed-Field.
Bacterial Typing Techniques.
Staphylococcal Protein A.
x Public Health
t USF Electronic Theses and Dissertations.