Culture adaptation of malaria parasites selects for convergent loss-of-function mutants.

Cultured human pathogens may differ significantly from source populations. To investigate the genetic basis of laboratory adaptation in malaria parasites, clinical Plasmodium falciparum isolates were sampled from patients and cultured in vitro for up to three months. Genome sequence analysis was performed on multiple culture time point samples from six monoclonal isolates, and single nucleotide polymorphism (SNP) variants emerging over time were detected. Out of a total of five positively selected SNPs, four represented nonsense mutations resulting in stop codons, three of these in a single ApiAP2 transcription factor gene, and one in SRPK1. To survey further for nonsense mutants associated with culture, genome sequences of eleven long-term laboratory-adapted parasite strains were examined, revealing four independently acquired nonsense mutations in two other ApiAP2 genes, and five in Epac. No mutants of these genes exist in a large database of parasite sequences from uncultured clinical samples. This implicates putative master regulator genes in which multiple independent stop codon mutations have convergently led to culture adaptation, affecting most laboratory lines of P. falciparum. Understanding the adaptive processes should guide development of experimental models, which could include targeted gene disruption to adapt fastidious malaria parasite species to culture.

Microsatellite genotyping and genome-wide single nucleotide polymorphism-based indices of Plasmodium falciparum diversity within clinical infections.

BACKGROUND: In regions where malaria is endemic, individuals are often infected with multiple distinct parasite genotypes, a situation that may impact on evolution of parasite virulence and drug resistance. Most approaches to studying genotypic diversity have involved analysis of a modest number of polymorphic loci, although whole genome sequencing enables a broader characterisation of samples. METHODS: PCR-based microsatellite typing of a panel of ten loci was performed on Plasmodium falciparum in 95 clinical isolates from a highly endemic area in the Republic of Guinea, to characterize within-isolate genetic diversity. Separately, single nucleotide polymorphism (SNP) data from genome-wide short-read sequences of the same samples were used to derive within-isolate fixation indices (F ws), an inverse measure of diversity within each isolate compared to overall local genetic diversity. The latter indices were compared with the microsatellite results, and also with indices derived by randomly sampling modest numbers of SNPs. RESULTS: As expected, the number of microsatellite loci with more than one allele in each isolate was highly significantly inversely correlated with the genome-wide F ws fixation index (r = -0.88, P < 0.001). However, the microsatellite analysis revealed that most isolates contained mixed genotypes, even those that had no detectable genome sequence heterogeneity. Random sampling of different numbers of SNPs showed that an F ws index derived from ten or more SNPs with minor allele frequencies of >10 % had high correlation (r > 0.90) with the index derived using all SNPs. CONCLUSIONS: Different types of data give highly correlated indices of within-infection diversity, although PCR-based analysis detects low-level minority genotypes not apparent in bulk sequence analysis. When whole-genome data are not obtainable, quantitative assay of ten or more SNPs can yield a reasonably accurate estimate of the within-infection fixation index (F ws).

Comparison of genomic signatures of selection on Plasmodium falciparum between different regions of a country with high malaria endemicity.

BACKGROUND: Genome wide sequence analyses of malaria parasites from widely separated areas of the world have identified contrasting population structures and signatures of selection. To compare relatively closely situated but ecologically contrasting regions within an endemic African country, population samples of Plasmodium falciparum clinical isolates were collected in Ghana from Kintampo in the central forest-savannah area, and Navrongo in a drier savannah area ~350 km to the north with more seasonally-restricted transmission. Parasite DNA was sequenced and paired-end reads mapped to the P. falciparum reference genome. RESULTS: High coverage genome wide sequence data for 85 different clinical isolates enabled analysis of 121,712 single nucleotide polymorphisms (SNPs). The local populations had similar proportions of mixed genotype infections, similar SNP allele frequency distributions, and eleven chromosomal regions had elevated integrated haplotype scores (|iHS|) in both. A between-population Rsb metric comparing extended haplotype homozygosity indicated a stronger signal within Kintampo for one of these regions (on chromosome 14) and in Navrongo for two of these regions (on chromosomes 10 and 13). At least one gene in each of these identified regions is a potential target of locally varying selection. The candidates include genes involved in parasite development in mosquitoes, members of variant-expressed multigene families, and a leading vaccine-candidate target of immunity. CONCLUSIONS: Against a background of very similar population structure and selection signatures in the P. falciparum populations of Ghana, three narrow genomic regions showed evidence indicating local differences in historical timing or intensity of selection. Sampling of closely situated populations across heterogeneous environments has potential to refine the mapping of important loci under temporally or spatially varying selection.

Admixture in Humans of Two Divergent Plasmodium knowlesi Populations Associated with Different Macaque Host Species.

Human malaria parasite species were originally acquired from other primate hosts and subsequently became endemic, then spread throughout large parts of the world. A major zoonosis is now occurring with Plasmodium knowlesi from macaques in Southeast Asia, with a recent acceleration in numbers of reported cases particularly in Malaysia. To investigate the parasite population genetics, we developed sensitive and species-specific microsatellite genotyping protocols and applied these to analysis of samples from 10 sites covering a range of >1,600 km within which most cases have occurred. Genotypic analyses of 599 P. knowlesi infections (552 in humans and 47 in wild macaques) at 10 highly polymorphic loci provide radical new insights on the emergence. Parasites from sympatric long-tailed macaques (Macaca fascicularis) and pig-tailed macaques (M. nemestrina) were very highly differentiated (FST = 0.22, and K-means clustering confirmed two host-associated subpopulations). Approximately two thirds of human P. knowlesi infections were of the long-tailed macaque type (Cluster 1), and one third were of the pig-tailed-macaque type (Cluster 2), with relative proportions varying across the different sites. Among the samples from humans, there was significant indication of genetic isolation by geographical distance overall and within Cluster 1 alone. Across the different sites, the level of multi-locus linkage disequilibrium correlated with the degree of local admixture of the two different clusters. The widespread occurrence of both types of P. knowlesi in humans enhances the potential for parasite adaptation in this zoonotic system.

A barcode of organellar genome polymorphisms identifies the geographic origin of Plasmodium falciparum strains.

Malaria is a major public health problem that is actively being addressed in a global eradication campaign. Increased population mobility through international air travel has elevated the risk of re-introducing parasites to elimination areas and dispersing drug-resistant parasites to new regions. A simple genetic marker that quickly and accurately identifies the geographic origin of infections would be a valuable public health tool for locating the source of imported outbreaks. Here we analyse the mitochondrion and apicoplast genomes of 711 Plasmodium falciparum isolates from 14 countries, and find evidence that they are non-recombining and co-inherited. The high degree of linkage produces a panel of relatively few single-nucleotide polymorphisms (SNPs) that is geographically informative. We design a 23-SNP barcode that is highly predictive (~92%) and easily adapted to aid case management in the field and survey parasite migration worldwide.

estMOI: estimating multiplicity of infection using parasite deep sequencing data.

Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein (MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission.

PlasmoView: a web-based resource to visualise global Plasmodium falciparum genomic variation.

Malaria is a global public health challenge, with drug resistance a major barrier to disease control and elimination. To meet the urgent need for better treatments and vaccines, a deeper knowledge of Plasmodium biology and malaria epidemiology is required. An improved understanding of the genomic variation of malaria parasites, especially the most virulent Plasmodium falciparum (Pf) species, has the potential to yield new insights in these areas. High-throughput sequencing and genotyping is generating large amounts of genomic data across multiple parasite populations. The resulting ability to identify informative variants, particularly single-nucleotide polymorphisms (SNPs), will lead to the discovery of intra- and inter-population differences and thus enable the development of genetic barcodes for diagnostic assays and clinical studies. Knowledge of genetic variability underlying drug resistance and other differential phenotypes will also facilitate the identification of novel mutations and contribute to surveillance and stratified medicine applications. The PlasmoView interactive web-browsing tool enables the research community to visualise genomic variation and annotation (eg, biological function) in a geographic setting. The first release contains over 600,000 high-quality SNPs in 631 Pf isolates from laboratory strains and four malaria-endemic regions (West Africa, East Africa, Southeast Asia and Oceania).

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

BACKGROUND: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. RESULTS: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. CONCLUSIONS: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.

Genomic insights into the origin of parasitism in the emerging plant pathogen Bursaphelenchus xylophilus.

Bursaphelenchus xylophilus is the nematode responsible for a devastating epidemic of pine wilt disease in Asia and Europe, and represents a recent, independent origin of plant parasitism in nematodes, ecologically and taxonomically distinct from other nematodes for which genomic data is available. As well as being an important pathogen, the B. xylophilus genome thus provides a unique opportunity to study the evolution and mechanism of plant parasitism. Here, we present a high-quality draft genome sequence from an inbred line of B. xylophilus, and use this to investigate the biological basis of its complex ecology which combines fungal feeding, plant parasitic and insect-associated stages. We focus particularly on putative parasitism genes as well as those linked to other key biological processes and demonstrate that B. xylophilus is well endowed with RNA interference effectors, peptidergic neurotransmitters (including the first description of ins genes in a parasite) stress response and developmental genes and has a contracted set of chemosensory receptors. B. xylophilus has the largest number of digestive proteases known for any nematode and displays expanded families of lysosome pathway genes, ABC transporters and cytochrome P450 pathway genes. This expansion in digestive and detoxification proteins may reflect the unusual diversity in foods it exploits and environments it encounters during its life cycle. In addition, B. xylophilus possesses a unique complement of plant cell wall modifying proteins acquired by horizontal gene transfer, underscoring the impact of this process on the evolution of plant parasitism by nematodes. Together with the lack of proteins homologous to effectors from other plant parasitic nematodes, this confirms the distinctive molecular basis of plant parasitism in the Bursaphelenchus lineage. The genome sequence of B. xylophilus adds to the diversity of genomic data for nematodes, and will be an important resource in understanding the biology of this unusual parasite.

Drug-resistant genotypes and multi-clonality in Plasmodium falciparum analysed by direct genome sequencing from peripheral blood of malaria patients.

Naturally acquired blood-stage infections of the malaria parasite Plasmodium falciparum typically harbour multiple haploid clones. The apparent number of clones observed in any single infection depends on the diversity of the polymorphic markers used for the analysis, and the relative abundance of rare clones, which frequently fail to be detected among PCR products derived from numerically dominant clones. However, minority clones are of clinical interest as they may harbour genes conferring drug resistance, leading to enhanced survival after treatment and the possibility of subsequent therapeutic failure. We deployed new generation sequencing to derive genome data for five non-propagated parasite isolates taken directly from 4 different patients treated for clinical malaria in a UK hospital. Analysis of depth of coverage and length of sequence intervals between paired reads identified both previously described and novel gene deletions and amplifications. Full-length sequence data was extracted for 6 loci considered to be under selection by antimalarial drugs, and both known and previously unknown amino acid substitutions were identified. Full mitochondrial genomes were extracted from the sequencing data for each isolate, and these are compared against a panel of polymorphic sites derived from published or unpublished but publicly available data. Finally, genome-wide analysis of clone multiplicity was performed, and the number of infecting parasite clones estimated for each isolate. Each patient harboured at least 3 clones of P. falciparum by this analysis, consistent with results obtained with conventional PCR analysis of polymorphic merozoite antigen loci. We conclude that genome sequencing of peripheral blood P. falciparum taken directly from malaria patients provides high quality data useful for drug resistance studies, genomic structural analyses and population genetics, and also robustly represents clonal multiplicity.

A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi.

High-density, strand-specific cDNA sequencing (ssRNA-seq) was used to analyze the transcriptome of Salmonella enterica serovar Typhi (S. Typhi). By mapping sequence data to the entire S. Typhi genome, we analyzed the transcriptome in a strand-specific manner and further defined transcribed regions encoded within prophages, pseudogenes, previously un-annotated, and 3'- or 5'-untranslated regions (UTR). An additional 40 novel candidate non-coding RNAs were identified beyond those previously annotated. Proteomic analysis was combined with transcriptome data to confirm and refine the annotation of a number of hpothetical genes. ssRNA-seq was also combined with microarray and proteome analysis to further define the S. Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA-seq provides a novel and powerful approach to the characterization of the bacterial transcriptome.