Resolving within-host malaria parasite diversity using single-cell sequencing

Nkhoma, Standwell C.; Trevino, Simon G.; Gorena, Karla M.; Nair, Shalini; Khoswe, Stanley; Jett, Catherine; Garcia, Roy; Daniel, Benjamin J.; Dia, Aliou; Terlouw, Dianne J.; Ward, Stephen A.; Anderson, Timothy J.; Cheeseman, Ian H.

doi:10.1101/391268

Cited by 17 publications

(15 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relatedness inference for polyploids (e.g. [59,13]) is comparable to that for polyclonal malaria samples, which arise due co-transmission and superinfection [60]. However, relatedness inference across polyclonal malaria samples is more challenging, since the equivalence of ploidy is unknown and variable.…”

Section: Discussionmentioning

confidence: 99%

Estimating relatedness between malaria parasites

Taylor

Jacob

Neafsey

et al. 2019

Preprint

View full text Add to dashboard Cite

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-bystate 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.

show abstract

Section: Discussionmentioning

confidence: 99%

Estimating relatedness between malaria parasites

Taylor

Jacob

Neafsey

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The estimated occurrence rate of mixed infections ranges from 18% to 63% in African and Southeast Asia countries (Anderson et al 2000; Zhu et al 2018). Although there was likely more intense competition in this experimental cross, with millions of sporozoites infecting a single mouse, single cell sequencing has revealed seventeen unique clones in a single human infection (Nkhoma et al 2018), which suggests that similar competitive interactions will also occur in patients. We note that while the intensity of competition may be similar in humanized mice, in vitro parasite cultures or infected humans, the nature of selection may differ.…”

Section: Discussionmentioning

confidence: 99%

Genetic mapping of fitness determinants across the malaria parasitePlasmodium falciparumlife cycle

Kumar

McDew-White

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

28Malaria is transmitted through female Anopheline mosquitoes where gamete fusion and meiosis 29 occurs, and humans where parasites proliferate asexually. We describe a powerful approach to 30 identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-31 cycle stages in human malaria parasite Plasmodium falciparum using bulk segregant analysis 32 (BSA). We combined experimental genetic crosses using humanized mice, with selective whole 33 genome amplification and BSA at multiple developmental stages in both mosquito and vertebrate 34 host to examine parasite competition and identify genomic regions under selection. We generated 35 crosses between artemisinin resistant (ART-R, kelch13-C580Y) and ART-sensitive (ART-S, 36 kelch13-WT) parasite clones recently isolated from Southeast Asian patients. We then quantified 37 genome-wide changes in allele frequency in the parasite progeny population from infected midgut 38 and salivary glands of Anopheles stephensi mosquitoes, infected livers, emerging merozoites and 39 aliquots of in vitro cultured progeny parasites at intervals over 30 days. Three striking results 40 emerge: we observed (i) a strong skew (>80%) towards alleles from the ART-R parent in the 41 mosquito stage, that dropped to ~50% in the blood stage as selfed ART-R parasites were selected 42 against; (ii) highly repeatable skews in allele frequencies across the genome in blood stage 43 parasites; (iii) particularly strong selection (selection coefficient (s) ≤ 0.18/asexual cycle) against 44 alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 45 containing ARPS10. This approach robustly identifies selected loci and has strong potential for 46 identifying parasite genes that interact with the mosquito vector or compensatory loci involved in 47 drug resistance. 48 49 3 50 Parasitic organisms frequently use multiple hosts and have several morphologically and 51 transcriptionally distinctive life cycle stages. Within each host, parasites must circumvent immune 52 defenses and navigate to new tissues. There are frequently extreme bottlenecks in parasite numbers 53 during transmission (Hopp et al. 2015), with rapid proliferative growth within hosts, and intense 54 competition between co-infecting parasite genotypes. For example, the life cycle of malaria 55 parasites involves successive infection of two hosts: female Anopheles mosquitoes, where gamete 56 fusion, meiosis and recombination occurs, and humans in which parasites travel from the skin, 57 develop in the liver and then proliferate asexually in the blood stream. Ideally, we would like to 58 understand how natural selection operates across the complete life cycle and document the genes 59 subject to selection pressures at each life cycle stage: during erythrocytic growth, gametocyte 60 production, oocyst development in the mosquito midgut, migration of sporozoites to the salivary 61 glands, transmission from the salivary glands, sporozoite survival in the skin, and est...

show abstract

“…The probability of selfing depends on the number of parasite clones in the human source infection: certain if monoclonal vs. uncertain if polyclonal. Polyclonal infections result from either a single mosquito inoculation, in which case most parasite clones are likely interrelated, or multiple inoculations, in which case parasite clones are likely unrelated (Wong et al 2017, 2018; Nkhoma et al 2018). The prevalence of polyclonal infections depends on many epidemiological factors, e.g.…”

mentioning

confidence: 99%

Estimating Relatedness Between Malaria Parasites

et al. 2019

View full text Add to dashboard Cite

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. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent. Estimates based on IBS are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on IBD. To generate estimates with errors below an arbitrary threshold of 0.1, we recommend 100 polyallelic or 200 biallelic markers. Marker requirements are immediately applicable to haploid malaria parasites and other haploid eukaryotes. C.I.s facilitate comparison when different marker sets are used. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology. We hope it will provide a basis for statistically informed prospective study design and surveillance strategies.

show abstract

Resolving within-host malaria parasite diversity using single-cell sequencing

Cited by 17 publications

References 40 publications

Estimating relatedness between malaria parasites

Estimating relatedness between malaria parasites

Genetic mapping of fitness determinants across the malaria parasitePlasmodium falciparumlife cycle

Estimating Relatedness Between Malaria Parasites

Contact Info

Product

Resources

About