Whole genome single nucleotide polymorphism based phylogeny of Francisella tularensis and its application to the development of a strain typing assay.

BACKGROUND: A low genetic diversity in Francisella tularensis has been documented. Current DNA based genotyping methods for typing F. tularensis offer a limited and varying degree of subspecies, clade and strain level discrimination power. Whole genome sequencing is the most accurate and reliable method to identify, type and determine phylogenetic relationships among strains of a species. However, lower cost typing schemes are necessary in order to enable typing of hundreds or even thousands of isolates. RESULTS: We have generated a high-resolution phylogenetic tree from 40 Francisella isolates, including 13 F. tularensis subspecies holarctica (type B) strains, 26 F. tularensis subsp. tularensis (type A) strains and a single F. novicida strain. The tree was generated from global multi-strain single nucleotide polymorphism (SNP) data collected using a set of six Affymetrix GeneChip resequencing arrays with the non-repetitive portion of LVS (type B) as the reference sequence complemented with unique sequences of SCHU S4 (type A). Global SNP based phylogenetic clustering was able to resolve all non-related strains. The phylogenetic tree was used to guide the selection of informative SNPs specific to major nodes in the tree for development of a genotyping assay for identification of F. tularensis subspecies and clades. We designed and validated an assay that uses these SNPs to accurately genotype 39 additional F. tularensis strains as type A (A1, A2, A1a or A1b) or type B (B1 or B2). CONCLUSION: Whole-genome SNP based clustering was shown to accurately identify SNPs for differentiation of F. tularensis subspecies and clades, emphasizing the potential power and utility of this methodology for selecting SNPs for typing of F. tularensis to the strain level. Additionally, whole genome sequence based SNP information gained from a representative population of strains may be used to perform evolutionary or phylogenetic comparisons of strains, or selection of unique strains for whole-genome sequencing projects.

Gene discovery in Plasmodium vivax through sequencing of ESTs from mixed blood stages.

Despite the significance of Plasmodium vivax as the most widespread human malaria parasite and a major public health problem, gene expression in this parasite is poorly understood. To accelerate gene discovery and facilitate the annotation phase of the P. vivax genome project, we have undertaken a transcriptome approach to study gene expression in the mixed blood stages of a P. vivax field isolate. Using a cDNA library constructed from purified blood stages, we have obtained single-pass sequences for approximately 21,500 expressed sequence tags (ESTs), the largest number of transcript tags obtained so far for this species. Cluster analysis revealed that the library is highly redundant, resulting in 5407 clusters. Clustered ESTs were searched against public protein databases for functional annotation, and more than one-third showed a significant match, the majority of these to Plasmodium falciparum proteins. The most abundant clusters were to genes encoding ribosomal proteins and proteins involved in metabolism, consistent with the predominance of trophozoites in the field isolate sample. In spite of the scarcity of other parasite stages in the field isolate, we could identify genes that are expressed in rings, schizonts and gametocytes. This study should facilitate our understanding of the gene expression in P. vivax asexual stages and provide valuable data for gene prediction and annotation of the P. vivax genome sequence.

Monitoring the long-term molecular epidemiology of the pneumococcus and detection of potential 'vaccine escape' strains.

BACKGROUND: While the pneumococcal protein conjugate vaccines reduce the incidence in invasive pneumococcal disease (IPD), serotype replacement remains a major concern. Thus, serotype-independent protection with vaccines targeting virulence genes, such as PspA, have been pursued. PspA is comprised of diverse clades that arose through recombination. Therefore, multi-locus sequence typing (MLST)-defined clones could conceivably include strains from multiple PspA clades. As a result, a method is needed which can both monitor the long-term epidemiology of the pneumococcus among a large number of isolates, and analyze vaccine-candidate genes, such as pspA, for mutations and recombination events that could result in 'vaccine escape' strains. METHODOLOGY: We developed a resequencing array consisting of five conserved and six variable genes to characterize 72 pneumococcal strains. The phylogenetic analysis of the 11 concatenated genes was performed with the MrBayes program, the single nucleotide polymorphism (SNP) analysis with the DNA Sequence Polymorphism program (DnaSP), and the recombination event analysis with the recombination detection package (RDP). RESULTS: The phylogenetic analysis correlated with MLST, and identified clonal strains with unique PspA clades. The DnaSP analysis correlated with the serotype-specific diversity detected using MLST. Serotypes associated with more than one ST complex had a larger degree of sequence polymorphism than a serotype associated with one ST complex. The RDP analysis confirmed the high frequency of recombination events in the pspA gene. CONCLUSIONS: The phylogenetic tree correlated with MLST, and detected multiple PspA clades among clonal strains. The genetic diversity of the strains and the frequency of recombination events in the mosaic gene, pspA were accurately assessed using the DnaSP and RDP programs, respectively. These data provide proof-of-concept that resequencing arrays could play an important role within research and clinical laboratories in both monitoring the molecular epidemiology of the pneumococcus and detecting 'vaccine escape' strains among vaccine-candidate genes.