Background Streptococcus dysgalactiae subspecies equisimilis (SDSE) is an emerging global pathogen that can colonize and infect humans. Although most SDSE isolates possess the Lancefield group G carbohydrate, a significant minority have the group C carbohydrate. Isolates are further sub-typed on the basis of differences within the emm gene. To gain a better understanding of their molecular epidemiology and evolutionary relationships, multilocus sequence typing (MLST) analysis was performed on SDSE isolates collected from Australia, Europe and North America.Methodology/Principal FindingsThe 178 SDSE isolates, representing 37 emm types, segregate into 80 distinct sequence types (STs) that form 17 clonal complexes (CCs). Eight STs recovered from all three continents account for >50% of the isolates. Thus, a small number of STs are highly prevalent and have a wide geographic distribution. Both ST and CC strongly correlate with group carbohydrate. In contrast, eleven STs were associated with >1 emm type, suggestive of recombinational replacements involving the emm gene; furthermore, 35% of the emm types are associated with genetically distant STs. Data also reveal a history of extensive inter- and intra-species recombination involving the housekeeping genes used for MLST. Sequence analysis of single locus variants identified through goeBURST indicates that genetic change mediated by recombination occurred ∼4.4 times more frequently than by point mutation.Conclusions/SignificanceA few genetic lineages with an intercontinental distribution dominate among SDSE causing infections in humans. The distinction between group C and G isolates reflects recent evolution, and no long-term genetic isolation between them was found. Lateral gene transfer and recombination involving housekeeping genes and the emm gene are important mechanisms driving genetic variability in the SDSE population.
Group A Streptococcus (GAS) has a rich evolutionary history of horizontal transfer among its core genes. Yet, despite extensive genetic mixing, GAS strains have discrete ecological phenotypes. To further our understanding of the molecular basis for ecological phenotypes, comparative genomic hybridization of a set of 97 diverse strains to a GAS pangenome microarray was undertaken, and the association of accessory genes with emm genotypes that define tissue tropisms for infection was determined. Of the 22 nonprophage accessory gene regions (AGRs) identified, only 3 account for all statistically significant linkage disequilibrium among strains having the genotypic biomarkers for throat versus skin infection specialists. Networked evolution and population structure analyses of loci representing each of the AGRs reveal that most strains with the skin specialist and generalist biomarkers form discrete clusters, whereas strains with the throat specialist biomarker are highly diverse. To identify coinherited and coselected accessory genes, the strength of genetic associations was determined for all possible pairwise combinations of accessory genes among the 97 GAS strains. Accessory genes showing very strong associations provide the basis for an evolutionary model, which reveals that a major transition between many throat and skin specialist haplotypes correlates with the gain or loss of genes encoding fibronectin-binding proteins. This study employs a novel synthesis of tools to help delineate the major genetic changes associated with key adaptive shifts in an extensively recombined bacterial species.
SummaryIn order to quantitatively distinguish between highly similar RNA sequences, specific primers or probes must be designed. Unfortunately, consistent and reliable results are not always obtained with conventional techniques. This study uses reverse transcription-PCR coupled with direct terminator sequencing to economically and efficiently distinguish between sequence types in pooled samples while providing accurate relative quantification. As an example, the method is applied to measure template concentration of two Barley yellow dwarf virus (BYDV; family Luteoviridae) species in doubly infected wheat plants. A PERL script (polySNP) was developed that uses PHRED to automatically extract relative peak areas and heights from sequencing chromatograms at polymorphic sites. Peak measurements from experimental samples were compared to a standard curve generated by mixing in vitro transcribed RNA from BYDV-PAV and PAS templates in several ratios (ranging from 1:9 to 9:1 PAV:PAS) prior to RT-PCR amplification and sequencing. The relative amount of RNA template added to a sample was regressed onto the proportion of the chromatogram peak height or area corresponding to one virus species. The function of the best fit line was used to calculate template frequency in the experimental samples.
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