Population Genetics of<i>Staphylococcus</i>

Smyth, Davida S.; Robinson, D. Ashley

doi:10.1002/9780470600122.ch16

Cited by 5 publications

(7 citation statements)

References 150 publications

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“…S. aureus exhibits two near-clades. This near-clading pattern uncovered by modern markers (Feil et al, 2003;Smyth and Robinson, 2010) parallels the one revealed by MLEE 25 years ago (Musser et al, 1990).…”

Section: Bacteriasupporting

confidence: 48%

“…b Llewellyn et al (2009aLlewellyn et al ( d , 2009bLlewellyn et al ( , 2011 b ) Sarkar and Guttman (2004) b,e Lymbery and Thompson (2012) c Sheppard et al (2010) b Minning et al (2011) a,b Smyth and Robinson (2010) b,e Miotto et al (2013) …”

Section: The Model Of Predominant Clonal Evolution and Its Last Develmentioning

confidence: 99%

“…Staphylococcus aureus shows strong LD (Smyth and Robinson, 2010). This species' MLEE MLGs often have intercontinental distributions (Musser et al, 1990).…”

Section: Bacteriamentioning

confidence: 99%

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Is Predominant Clonal Evolution a Common Evolutionary Adaptation to Parasitism in Pathogenic Parasitic Protozoa, Fungi, Bacteria, and Viruses?

Tibayrenc

Ayala

2017

Advances in Parasitology

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Section: Bacteriasupporting

confidence: 48%

Section: The Model Of Predominant Clonal Evolution and Its Last Develmentioning

confidence: 99%

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Is Predominant Clonal Evolution a Common Evolutionary Adaptation to Parasitism in Pathogenic Parasitic Protozoa, Fungi, Bacteria, and Viruses?

Tibayrenc

Ayala

2017

Advances in Parasitology

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“…CC30 is rarely observed at frequencies higher than approximately 30% in carriage samples, and Ruimy et al suggested that 30% appears to be the approximate maximum frequency for any single CC within carriage samples, reflecting competition between lineages (26), which is also in line with our findings. If it is true that essentially any S. aureus strain is able to colonize the human host, the observed geographical divergence in CCs could be due to ethnic or sociodemographic differences in host susceptibility or the geographic distribution of S. aureus genotypes (30).…”

Section: Discussionmentioning

confidence: 99%

Age- and Gender-Associated Staphylococcus aureus spa Types Found among Nasal Carriers in a General Population: the Tromsø Staph and Skin Study

Sangvik

Olsen

et al. 2011

J Clin Microbiol

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Staphylococcus aureus nasal carriers risk autoinfection; however, knowledge about the factors that make specific strains successful colonizers is limited. This study was undertaken to identify the most successful S. aureus clones in nasal carriers and compare their distribution among host groups. The population structure of S. aureus isolates from healthy adults was investigated by spa typing 1,981 isolates from persistent and intermittent nasal carriers participating in a health survey. In the baseline screening (1,113 isolates), the most common spa types were t012 (8.4%), t084 (7.6%), and t065 (4.9%). Three large spa clonal complexes (spa CC012, spa CC065, and spa CC084) comprised 62.4% of the isolates. In multivariate models adjusted for age and smoking status, male sex was associated with higher risk for spa type t084 (odds ratio [OR], 1.72; 95% confidence interval [CI], 1.06 to 2.77), and lower risk of spa type t012 (OR, 0.60; 95% CI, 0.39 to 0.92) colonization. The prevalence of spa type t012 decreased significantly with increasing age (P ‫؍‬ 0.03), with a prevalence almost twice as high in the youngest group (age 30 to 44 years, prevalence ‫؍‬ 11.1%) as in the oldest group (age, 60 to 87 years; prevalence ‫؍‬ 5.6%). Among baseline isolates, spa type t084 had a twofold-higher prevalence among intermittent carriers than among persistent carriers (10.6% versus 5.5%; P ‫؍‬ 0.04). In summary, the two most prevalent spa types found in this study were significantly associated with age and/or gender. This may provide valuable clues to the multifactorial mechanisms, among them bacterial factors, involved in nasal colonization with S. aureus.

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“…Multilocus sequence typing (MLST) has identified clones such as sequence type 2 (ST2) that are common in hospitals (15,(17)(18)(19)(20)(21)(22)(23)(24). However, a robust classification of S. epidermidis STs into larger groups of related STs has been lacking (25). Recently, we used Bayesian clustering of the MLST data in the international database to identify a species-wide population structure of six genetic clusters (GCs) that may relate to bacterial lifestyle (26).…”

mentioning

confidence: 99%

Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

et al. 2016

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Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital.

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Population Genetics ofStaphylococcus

Cited by 5 publications

References 150 publications

Is Predominant Clonal Evolution a Common Evolutionary Adaptation to Parasitism in Pathogenic Parasitic Protozoa, Fungi, Bacteria, and Viruses?

Is Predominant Clonal Evolution a Common Evolutionary Adaptation to Parasitism in Pathogenic Parasitic Protozoa, Fungi, Bacteria, and Viruses?

Age- and Gender-Associated Staphylococcus aureus spa Types Found among Nasal Carriers in a General Population: the Tromsø Staph and Skin Study

Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

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