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

<p>Abstract</p> <p>Background</p> <p>A low genetic diversity in <it>Francisella tularensis </it>has been documented. Current DNA based genotyping methods for typing <it>F. tularensis </it>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.</p> <p>Results</p> <p>We have generated a high-resolution phylogenetic tree from 40 <it>Francisella </it>isolates, including 13 <it>F. tularensis </it>subspecies <it>holarctica </it>(type B) strains, 26 <it>F. tularensis </it>subsp. <it>tularensis </it>(type A) strains and a single <it>F. novicida </it>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 <it>F. tularensis </it>subspecies and clades. We designed and validated an assay that uses these SNPs to accurately genotype 39 additional <it>F. tularensis </it>strains as type A (A1, A2, A1a or A1b) or type B (B1 or B2).</p> <p>Conclusion</p> <p>Whole-genome SNP based clustering was shown to accurately identify SNPs for differentiation of <it>F. tularensis </it>subspecies and clades, emphasizing the potential power and utility of this methodology for selecting SNPs for typing of <it>F. tularensis </it>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.</p

Local Admixture of Amplified and Diversified Secreted Pathogenesis Determinants Shapes Mosaic \u3cem\u3eToxoplasma gondii\u3c/em\u3e Genomes

Toxoplasma gondii is among the most prevalent parasites worldwide, infecting many wild and domestic animals and causing zoonotic infections in humans. T. gondii differs substantially in its broad distribution from closely related parasites that typically have narrow, specialized host ranges. To elucidate the genetic basis for these differences, we compared the genomes of 62 globally distributed T. gondii isolates to several closely related coccidian parasites. Our findings reveal that tandem amplification and diversification of secretory pathogenesis determinants is the primary feature that distinguishes the closely related genomes of these biologically diverse parasites. We further show that the unusual population structure of T. gondii is characterized by clade-specific inheritance of large conserved haploblocks that are significantly enriched in tandemly clustered secretory pathogenesis determinants. The shared inheritance of these conserved haploblocks, which show a different ancestry than the genome as a whole, may thus influence transmission, host range and pathogenicity

Monitoring the Long-Term Molecular Epidemiology of the Pneumococcus and Detection of Potential ‘Vaccine Escape’ Strains

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.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).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.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

Antimicrobial Peptides, Polymorphic Toxins, and Self-Nonself Recognition Systems in Archaea: an Untapped Armory for Intermicrobial Conflicts

Diverse and highly variable systems involved in biological conflicts and self-versus-nonself discrimination are ubiquitous in bacteria but much less studied in archaea. We performed comprehensive comparative genomic analyses of the archaeal systems that share components with analogous bacterial systems and propose an approach to identify new systems that could be involved in these functions. We predict polymorphic toxin systems in 141 archaeal genomes and identify new, archaea-specific toxin and immunity protein families. These systems are widely represented in archaea and are predicted to play major roles in interactions between species and in intermicrobial conflicts. This work is expected to stimulate experimental research to advance the understanding of poorly characterized major aspects of archaeal biology.Numerous, diverse, highly variable defense and offense genetic systems are encoded in most bacterial genomes and are involved in various forms of conflict among competing microbes or their eukaryotic hosts. Here we focus on the offense and self-versus-nonself discrimination systems encoded by archaeal genomes that so far have remained largely uncharacterized and unannotated. Specifically, we analyze archaeal genomic loci encoding polymorphic and related toxin systems and ribosomally synthesized antimicrobial peptides. Using sensitive methods for sequence comparison and the “guilt by association” approach, we identified such systems in 141 archaeal genomes. These toxins can be classified into four major groups based on the structure of the components involved in the toxin delivery. The toxin domains are often shared between and within each system. We revisit halocin families and substantially expand the halocin C8 family, which was identified in diverse archaeal genomes and also certain bacteria. Finally, we employ features of protein sequences and genomic locus organization characteristic of archaeocins and polymorphic toxins to identify candidates for analogous but not necessarily homologous systems among uncharacterized protein families. This work confidently predicts that more than 1,600 archaeal proteins, currently annotated as “hypothetical” in public databases, are components of conflict and self-versus-nonself discrimination systems

Computational analysis of genes with lethal knockout phenotype and prediction of essential genes in archaea

ABSTRACTThe identification of microbial genes essential for survival as those with lethal knockout phenotype (LKP) is a common strategy for functional interrogation of genomes. However, interpretation of the LKP is complicated because a substantial fraction of the genes with this phenotype remains poorly functionally characterized. Furthermore, many genes can exhibit LKP not because their products perform essential cellular functions but because their knockout activates the toxicity of other genes (conditionally essential genes). We analyzed the sets of LKP genes for two archaea, Methanococcus maripaludis and Sulfolobus islandicus, using a variety of computational approaches aiming to differentiate between essential and conditionally essential genes and to predict at least a general function for as many of the proteins encoded by these genes as possible. This analysis allowed us to predict the functions of several LKP genes including previously uncharacterized subunit of the GINS protein complex with an essential function in genome replication and of the KEOPS complex that is responsible for an essential tRNA modification as well as GRP protease implicated in protein quality control. Additionally, several novel antitoxins (conditionally essential genes) were predicted, and this prediction was experimentally validated by showing that the deletion of these genes together with the adjacent genes apparently encoding the cognate toxins caused no growth defect. We applied principal component analysis based on sequence and comparative genomic features showing that this approach can separate essential genes from conditionally essential ones and used it to predict essential genes in other archaeal genomes.IMPORTANCEOnly a relatively small fraction of the genes in any bacterium or archaeon is essential for survival as demonstrated by the lethal effect of their disruption. The identification of essential genes and their functions is crucial for understanding fundamental cell biology. However, many of the genes with a lethal knockout phenotype remain poorly functionally characterized, and furthermore, many genes can exhibit this phenotype not because their products perform essential cellular functions but because their knockout activates the toxicity of other genes. We applied state-of-the-art computational methods to predict the functions of a number of uncharacterized genes with the lethal knockout phenotype in two archaeal species and developed a computational approach to predict genes involved in essential functions. These findings advance the current understanding of key functionalities of archaeal cells

Additional file 7 of Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions

Additional file 7: Fig. S5. Linear Discriminant Analysis of gene essentiality in S. islandicus

Additional file 6 of Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions

Additional file 6: Table S2. Selected examples of potential subfunctionalization of paralogs (proteins which belong to the same COG). Selected by the following criteria: (1) present in most genomes in the respective lineage; (2) have small number of paralogs (3) have low and high variability estimates