A transcriptional switch underlies commitment to sexual development in malaria parasites.

The life cycles of many parasites involve transitions between disparate host species, requiring these parasites to go through multiple developmental stages adapted to each of these specialized niches. Transmission of malaria parasites (Plasmodium spp.) from humans to the mosquito vector requires differentiation from asexual stages replicating within red blood cells into non-dividing male and female gametocytes. Although gametocytes were first described in 1880, our understanding of the molecular mechanisms involved in commitment to gametocyte formation is extremely limited, and disrupting this critical developmental transition remains a long-standing goal. Here we show that expression levels of the DNA-binding protein PfAP2-G correlate strongly with levels of gametocyte formation. Using independent forward and reverse genetics approaches, we demonstrate that PfAP2-G function is essential for parasite sexual differentiation. By combining genome-wide PfAP2-G cognate motif occurrence with global transcriptional changes resulting from PfAP2-G ablation, we identify early gametocyte genes as probable targets of PfAP2-G and show that their regulation by PfAP2-G is critical for their wild-type level expression. In the asexual blood-stage parasites pfap2-g appears to be among a set of epigenetically silenced loci prone to spontaneous activation. Stochastic activation presents a simple mechanism for a low baseline of gametocyte production. Overall, these findings identify PfAP2-G as a master regulator of sexual-stage development in malaria parasites and mark the first discovery of a transcriptional switch controlling a differentiation decision in protozoan parasites.

Malaria Host Candidate Genes Validated by Association With Current, Recent, and Historical Measures of Transmission Intensity.

Background: Human malaria susceptibility is determined by multiple genetic factors. It is unclear, however, which genetic variants remain important over time. Methods: Genetic associations of 175 high-quality polymorphisms within several malaria candidate genes were examined in a sample of 8096 individuals from northeast Tanzania using altitude, seroconversion rates, and parasite rates as proxies of historical, recent, and current malaria transmission intensity. A principal component analysis was used to derive 2 alternative measures of overall malaria propensity of a location across different time scales. Results: Common red blood cell polymorphisms (ie, hemoglobin S, glucose-6-phosphate dehydrogenase, and α-thalassemia) were the only ones to be associated with all 3 measures of transmission intensity and the first principal component. Moderate associations were found between some immune response genes (ie, IL3 and IL13) and parasite rates, but these could not be reproduced using the alternative measures of malaria propensity. Conclusions: We have demonstrated the potential of using altitude and seroconversion rate as measures of malaria transmission capturing medium- to long-term time scales to detect genetic associations that are likely to persist over time. These measures also have the advantage of minimizing the deleterious effects of random factors affecting parasite rates on the respective association signals.

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.

A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.

MOTIVATION: Quantifying differences in linkage disequilibrium (LD) between sub-groups can highlight genetic regions or sites under selection and/or associated with disease, and may have utility in trans-ethnic mapping studies. RESULTS: We present a novel pseudo Bayes factor (PBF) approach that assess differences in covariance of genotype frequencies from single nucleotide polymorphism (SNP) data from a genome-wide study. The magnitude of the PBF reflects the strength of evidence for a difference, while accounting for the sample size and number of SNPs, without the requirement for permutation testing to establish statistical significance. Application of the PBF to HapMap and Gambian malaria SNP data reveals regional LD differences, some known to be under selection. AVAILABILITY AND IMPLEMENTATION: The PBF approach has been implemented in the BALD (Bayesian analysis of LD differences) C++ software, and is available from http://homepages.lshtm.ac.uk/tgclark/downloads.

The antimalarial efficacy and mechanism of resistance of the novel chemotype DDD01034957.

New antimalarial therapeutics are needed to ensure that malaria cases continue to be driven down, as both emerging parasite resistance to frontline chemotherapies and mosquito resistance to current insecticides threaten control programmes. Plasmodium, the apicomplexan parasite responsible for malaria, causes disease pathology through repeated cycles of invasion and replication within host erythrocytes (the asexual cycle). Antimalarial drugs primarily target this cycle, seeking to reduce parasite burden within the host as fast as possible and to supress recrudescence for as long as possible. Intense phenotypic drug screening efforts have identified a number of promising new antimalarial molecules. Particularly important is the identification of compounds with new modes of action within the parasite to combat existing drug resistance and suitable for formulation of efficacious combination therapies. Here we detail the antimalarial properties of DDD01034957-a novel antimalarial molecule which is fast-acting and potent against drug resistant strains in vitro, shows activity in vivo, and possesses a resistance mechanism linked to the membrane transporter PfABCI3. These data support further medicinal chemistry lead-optimization of DDD01034957 as a novel antimalarial chemical class and provide new insights to further reduce in vivo metabolic clearance.

Candidate human genetic polymorphisms and severe malaria in a Tanzanian population.

Human genetic background strongly influences susceptibility to malaria infection and progression to severe disease and death. Classical genetic studies identified haemoglobinopathies and erythrocyte-associated polymorphisms, as protective against severe disease. High throughput genotyping by mass spectrometry allows multiple single nucleotide polymorphisms (SNPs) to be examined simultaneously. We compared the prevalence of 65 human SNP's, previously associated with altered risk of malaria, between Tanzanian children with and without severe malaria. Five hundred children, aged 1-10 years, with severe malaria were recruited from those admitted to hospital in Muheza, Tanzania and compared with matched controls. Genotyping was performed by Sequenom MassArray, and conventional PCR was used to detect deletions in the alpha-thalassaemia gene. SNPs in two X-linked genes were associated with altered risk of severe malaria in females but not in males: heterozygosity for one or other of two SNPs in the G6PD gene was associated with protection from all forms of severe disease whilst two SNPs in the gene encoding CD40L were associated with respiratory distress. A SNP in the adenyl cyclase 9 (ADCY9) gene was associated with protection from acidosis whilst a polymorphism in the IL-1α gene (IL1A) was associated with an increased risk of acidosis. SNPs in the genes encoding IL-13 and reticulon-3 (RTN3) were associated with increased risk of cerebral malaria. This study confirms previously known genetic associations with protection from severe malaria (HbS, G6PD). It identifies two X-linked genes associated with altered risk of severe malaria in females, identifies mutations in ADCY9, IL1A and CD40L as being associated with altered risk of severe respiratory distress and acidosis, both of which are characterised by high serum lactate levels, and also identifies novel genetic associations with severe malaria (TRIM5) and cerebral malaria(IL-13 and RTN3). Further studies are required to test the generality of these associations and to understand their functional consequences.

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.