Genomic profile of Brazilian methicillin-resistant Staphylococcus aureus resembles clones dispersed worldwide

Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework. Moreover, phylogenetic inference provides sound statistical tools to exhibit the main features of molecular evolution from the analysis of actual sequences. This chapter focuses on phylogenetic tree estimation under the maximum likelihood (ML) principle. Phylogenies inferred under this probabilistic criterion are usually reliable and important biological hypotheses can be tested through the comparison of different models. Estimating ML phylogenies is computationally demanding, and careful examination of the results is warranted. This chapter focuses on PhyML, a software that implements recent ML phylogenetic methods and algorithms. We illustrate the strengths and pitfalls of this program through the analysis of a real data set. PhyML v3.0 is available from (http://atgc_montpellier.fr/phyml/).

Bacterial genome sequencing has become so easy and accessible that the genomes of multiple strains of more and more individual species have been and will be generated. These data sets provide for in depth analysis of intra-species diversity from various aspects. The pan-genome analysis, whereby the size of the gene repertoire accessible to any given species is characterized together with an estimate of the number of whole genome sequences required for proper analysis, is being increasingly applied. Different models exist for the analysis and their accuracy and applicability depend on the case at hand. Here we discuss current models and suggest a new model of broad applicability, including examples of its implementation.

Emerging and re-emerging infectious diseases, especially those caused by drug-resistant bacteria, are a major problem worldwide. Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) appeared rapidly and unexpectedly in the United States, resulting in an epidemic caused primarily by isolates classified as USA300. The evolutionary and molecular underpinnings of this epidemic are poorly understood. Specifically, it is unclear whether there has been clonal emergence of USA300 isolates or evolutionary convergence toward a hypervirulent phenotype resulting in the independent appearance of similar organisms. To definitively resolve this issue and understand the phylogeny of USA300 isolates, we used comparative whole-genome sequencing to analyze 10 USA300 patient isolates from eight states in diverse geographic regions of the United States and multiple types of human infection. Eight of 10 isolates analyzed had very few single nucleotide polymorphisms (SNPs) and thus were closely related, indicating recent diversification rather than convergence. Unexpectedly, 2 of the clonal isolates had significantly reduced mortality in a mouse sepsis model compared with the reference isolate (P = 0.0002), providing strong support to the idea that minimal genetic change in the bacterial genome can have profound effects on virulence. Taken together, our results demonstrate that there has been recent clonal expansion and diversification of a subset of isolates classified as USA300. The findings add an evolutionary dimension to the epidemiology and emergence of USA300 and suggest a similar mechanism for the pandemic occurrence and spread of penicillin-resistant S. aureus (known as phage-type 80/81 S. aureus) in the 1950s.