Biology subjects

Neafsey, D. E.

Publications and source records attributed to Neafsey, D. E..

27 records · Page 2Linked to original sources

bioRxiv2020

Plasmodium falciparum population genetic complexity influences transcriptional profile and immune recognition of highly related genotypic clusters

As transmission intensity has declined in Senegal, so has the genetic complexity of circulating Plasmodium falciparum parasites, resulting in specific genotypes emerging and persisting over years. We address whether changes in parasite genetic signatures can alter the immune repertoire to variant surface antigens, and whether such responses can influence the expansion or contraction of specific parasite genotypes in the population. We characterize parasites within genotypic clusters, defined as identical by a 24-SNP molecular barcode and a haplotype identifier for other highly polymorphic loci; we measure expression of variant surface antigens (VSA) such as PfEMP-1 by transcript expression typing and expressed var DBL1 sequencing in ex vivo and short-term adapted RNA samples; and we measure IgG responses against VSAs from short-term adapted parasites. We find that parasites within genotypic clusters are genetically identical at other highly polymorphic loci. These parasites express similar Ups var classes and largely the same dominant var DBL1 sequences ex vivo. These parasites are recognized similarly by anti-VSA antibodies after short-term adaptation to culture; however, antibody responses do not correlate with genotype frequencies over time. Both genotype-specific and multiple genotype-reactive surface IgG responses are observed in this population. Parasites with identical genomes are extremely similar in their expression and host antibody recognition of VSAs. Monitoring changes in population-level parasite genomics and transmission dynamics is critical, as fluctuations will influence the breadth of resulting host immune responses to circulating parasite genotypes. These findings suggest shared immune recognition of genetically similar parasites, which has implications for both our understanding of immunity and vaccine development strategies in malaria elimination settings.

microbiology↗

bioRxiv2019

Estimating relatedness between malaria parasites

1.Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites, Plasmodium falciparum and Plasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

genetics↗

bioRxiv2018

Estimating the probable cause of recurrence in Plasmodium vivax malaria: relapse, reinfection or recrudescence?

BackgroundRelapse of Plasmodium vivax infection is the main cause of vivax malaria in many parts of Asia. However at the individual patient level, recurrence of a blood stage infection following treatment within the endemic area can be either a relapse (from dormant liver-stage parasites), a recrudescence (blood-stage treatment failure), or a reinfection (following a new mosquito inoculation). Each requires a different prevention strategy, but previously they could not be distinguished reliably. Time-of-event and genetic data provide complimentary information about the cause of P. vivax recurrence, but the optimum approach to genotyping and analysis remains uncertain.\n\nMethodsIndividual-level data from two large drug trials in acute vivax malaria patients (Vivax History: VHX; Best Primaquine Dose: BPD) conducted on the Thailand-Myanmar border with follow-up of one year were pooled (n=1299). A total of 710 isolates from both acute and recurrent P. vivax episodes were genotyped using 3-9 highly polymorphic microsatellite markers. These pooled data were analyzed using a novel population statistical model incorporating an assessment of genetic relatedness, treatment drug administered, and the time-to-recurrence.\n\nResults99% of genotyped recurrences in individuals who did not receive primaquine (n=365) were estimated to be relapses. In comparison, 14% of genotyped recurrences (n=121) were estimated to be relapses following high-dose supervised primaquine. By comparing episodes across individuals (90194 comparisons), the false-positive rate of relapse identification using genetic data alone was estimated to be 2.2%. We estimated the true failure rate after high-dose primaquine (7mg/kg total dose) to be 2.6% in this epidemiological context, substantially lower the reinfection unadjusted estimate of 12%. Simulation studies show that 9 highly polymorphic microsatellite markers suffice to discriminate between recurrence states. Drug exposures reflected by plasma carboxy-primaquine concentrations were not predictive of treatment failure, but did identify non-adherence.\n\nConclusionUsing this novel statistical model, relapse of P. vivax malaria could be distinguished reliably from reinfection. This showed that in this population supervised high-dose primaquine could avert up to 99% of relapses. In low transmission settings, microsatellite genotyping combined with time-to-event data can accurately discriminate between the different causes of recurrent P. vivax malaria.\n\nAuthor summaryOne hundred years ago, Plasmodium vivax, the most globally diverse cause of human malaria, was present across most of the old-world, throughout tropical and temperate climes. Its main evolutionary advantage over Plasmodium falciparum, responsible for the most deadly type of human malaria, is its ability to stay dormant in the liver, emerging weeks to years later causing recurring illness and continuing transmission. The dormant liver-stage parasites are called hypnozoites. A recurrent infection can either be hypnozoite-derived (a relapse), a blood-stage treatment failure (recrudescence), or from a new mosquito bite (a reinfection). At a population level, each requires a different preventative strategy but no widely applicable methodology existed to discriminate between the three possible states: relapse, recrudescence and reinfection. Parasite genetic data alone cannot resolve the different possibilities. We developed a novel probabilistic framework which uses both epidemiological and genetic data to determine the most likely cause of vivax recurrence at the individual level. We applied this method to the largest available pooled clinical trial data from Southeast Asia incorporating information from highly polymorphic microsatellite markers, drug treatments received and time-to-recurrent illness. This analysis provides a tool for estimating probabilities of relapse, recrudescence and reinfection and, importantly, shows that hypnozoiticidal high-dose primaquine radical cure is much more effective than previously thought.

epidemiology↗

bioRxiv2018

Genomic architecture and introgression shape a butterfly radiation

We here pioneer a low-cost assembly strategy for 20 Heliconiini genomes to characterize the evolutionary history of the rapidly radiating genus Heliconius. A bifurcating tree provides a poor fit to the data, and we therefore explore a reticulate phylogeny for Heliconius. We probe the genomic architecture of gene flow, and develop a new method to distinguish incomplete lineage sorting from introgression. We find that most loci with non-canonical histories arose through introgression, and are strongly underrepresented in regions of low recombination and high gene density. This is expected if introgressed alleles are more likely to be purged in such regions due to tighter linkage with incompatibility loci. Finally, we identify a hitherto unrecognized inversion, and show it is a convergent structural rearrangement that captures a known color pattern switch locus within the genus. Our multi-genome assembly approach enables an improved understanding of adaptive radiation.

evolutionary biology↗

bioRxiv2018

Amplicon deep sequencing of low-density Plasmodium falciparum infections: an evaluation of analysis approaches

BackgroundDeep sequencing of targeted genomic regions is becoming a common tool for understanding the dynamics and complexity of Plasmodium infections, but its lower limit of detection is currently unknown. Here, a new amplicon analysis tool, the Parallel Amplicon Sequencing Error Correction (PASEC) pipeline, is used to evaluate the performance of amplicon sequencing on low-density Plasmodium DNA samples. Illumina-based sequencing of two P. falciparum genomic regions (CSP and SERA2) was performed on two types of samples: in vitro DNA mixtures mimicking low-density infections (1-200 genomes/l) and extracted blood spots from a combination of symptomatic and asymptomatic individuals (44-653,080 parasites/l). Three additional analysis tools--DADA2, HaplotypR, and SeekDeep--were applied to both datasets and the precision and sensitivity of each tool were evaluated. ResultsAmplicon sequencing can contend with low-density samples, showing reasonable detection accuracy down to a concentration of 5 Plasmodium genomes/l. Due to increased stochasticity and background noise, however, all four tools showed reduced sensitivity and precision on samples with very low parasitemia (<5 copies/l) or low read count (<100 reads per amplicon). PASEC could distinguish major from minor haplotypes with an accuracy of 90% in samples with at least 30 Plasmodium genomes/l, but only 61% at low Plasmodium concentrations (<5 genomes/l) and 46% at very low read counts (<25 reads per amplicon). The four tools were additionally used on a panel of extracted parasite-positive blood spots from natural malaria infections. While all four identified concordant patterns of complexity of infection (COI) across four sub-Saharan African countries, the COI values obtained for individual samples differed in some cases. ConclusionsAmplicon deep sequencing can be used to determine the complexity and diversity of low-density Plasmodium infections. Despite differences in their approach, four state-of-the-art tools resolved known haplotype mixtures with similar sensitivity and precision. Researchers can therefore choose from multiple robust approaches for analyzing amplicon data, however, error filtration approaches should not be uniformly applied across samples of varying parasitemia. Samples with very low parasitemia and very low read count have higher false positive rates and call for read count thresholds that are higher than current recommendations.

microbiology↗

bioRxiv2017

De Novo Mutations Resolve Disease Transmission Pathways in Clonal Malaria

Detecting de novo mutations in viral and bacterial pathogens enables researchers to reconstruct detailed networks of disease transmission and is a key technique in genomic epidemiology. However these techniques have not yet been applied to the malaria parasite, Plasmodium falciparum, in which a larger genome, slower generation times, and a complex life cycle make them difficult to implement. Here we demonstrate the viability of de novo mutation studies in P. falciparum for the first time. Using a set of clinical samples and novel methods of sequencing, library preparation, and genotyping, we have genotyped low-complexity regions of the genome with a high degree of accuracy. Despite its slower evolutionary rate compared to bacterial or viral species, de novo mutation can be detected in P. falciparum across timescales of just 1-2 years and evolutionary rates in low-complexity regions of the genome can be up to twice that detected in the rest of the genome. The increased mutation rate allows the identification of separate clade expansions that cannot be found using previous genomic epidemiology approaches and could be a crucial tool for mapping residual transmission patterns in disease elimination campaigns and reintroduction scenarios.

genomics↗

bioRxiv2017

Within-infection diversity of Plasmodium falciparum antigens reflects host-mediated selection

Host immunity exerts strong selection on pathogens, but it does not act in a uniform manner across individual hosts. By providing a direct approach for understanding host-specific selection pressures, patterns of intra-host pathogen diversity complement population genetic analyses performed on broad geographic scales. Here, we perform a combined analysis of inter- and intra-host diversity for the malaria parasite Plasmodium falciparum with haplotype sequences of three antigens sampled from over 4,500 natural infections in sub-Saharan Africa using targeted deep sequencing. We find that multi-strain infections in young children contain non-random combinations of parasite genotypes, and identify individual amino acid positions that may contribute to strain-specific blocking of infections. These results demonstrate for the first time that natural host defenses to Plasmodium detectably impact which infections proceed to the blood stage within a given host. This selection partially explains the extreme amino acid diversity observed at many parasite antigens and suggests that vaccines targeting such proteins should account for the impact of allele-specific immunity.

evolutionary biology↗

bioRxiv2017

hmmIBD: software to infer pairwise identity by descent between haploid genotypes

SummaryWe introduce hmmIBD, software to estimate pairwise identity by decent between haploid genomes, such as those of the malaria parasite, sampled from one or more populations. We verified hmmIBD using simulated data, benchmarked it against a previously published method for detecting IBD within populations, and demonstrated its utility using Plasmodium falciparum data from Cambodia and Ghana.\n\nSupplementary informationSupplementary data include Appendices S1, S2 and S3, and are available online.\n\nAvailability and ImplemetationSource code written in C99/C11-compliant C and requiring no external libraries, is freely available for download at https://github.com/glipsnort/hmmIBD/releases, alongside test datasets.\n\nContactsfs@broadinstitute.org

bioinformatics↗

bioRxiv2016

Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance in western Thailand

BackgroundArtemisinin-based combination therapies are the first line of treatment for Plasmodium falciparum infections worldwide, but artemisinin resistance (ART-R) has risen rapidly in in Southeast Asia over the last decade. Mutations in kelch13 have been associated with artemisinin (ART) resistance in this region. To explore the power of longitudinal genomic surveillance to detect signals in kelch13 and other loci that contribute to ART or partner drug resistance, we retrospectively sequenced the genomes of 194 P. falciparum isolates from five sites in Northwest Thailand, bracketing the era in which there was a rapid increase in ART-R in this region (2001-2014).\n\nResultsWe evaluated statistical metrics for temporal change in the frequency of individual SNPs, assuming that SNPs associated with resistance should increase frequency over this period. After Kelch13-C580Y, the strongest temporal change was seen at a SNP in phosphatidylinositol 4-kinase (PI4K), situated in a pathway recently implicated in the ART-R mechanism. However, other loci exhibit temporal signatures nearly as strong, and warrant further investigation for involvement in ART-R evolution. Through genome-wide association analysis we also identified a variant in a kelch-domain-containing gene on chromosome 10 that may epistatically modulate ART-R.\n\nConclusionsThis analysis demonstrates the potential of a longitudinal genomic surveillance approach to detect resistance-associated loci and improve our mechanistic understanding of how resistance develops. Evidence for additional genomic regions outside of the kelch13 locus associated with ART-R parasites may yield new molecular markers for resistance surveillance and may retard the emergence or spread of ART-R in African parasite populations.

genomics↗