Biology subjects

Nkhoma, S. C.

Publications and source records attributed to Nkhoma, S. C..

4 recordsLinked to original sources

bioRxiv2021

Optimizing bulk segregant analysis of drug resistance using Plasmodium falciparum genetic crosses conducted in humanized mice

BackgroundClassical genetic crosses in malaria parasites involve isolation, genotyping, and phenotyping of multiple progeny parasites, which is time consuming and laborious. Bulk segregant analysis (BSA) offers a powerful and efficient alternative to identify loci underlying complex traits in the human malaria parasite, Plasmodium falciparum. MethodsWe have used BSA, which combines genetic crosses using humanized mice with pooled sequencing of progeny populations to measure changes in allele frequency following selection with antimalarial drugs. We used dihydroartemisinin (DHA) drug selection in two genetic crosses (Mal31xKH004 and NF54xNHP1337). We specifically investigated how synchronization, cryopreservation, and the drug selection regimen of progeny pools impacted the success of BSA experiments. FindingsWe detected a strong and repeatable quantitative trait locus (QTL) at chr13 kelch13 locus in both crosses, but did not detect QTLs at ferredoxin (fd), the apicoplast ribosomal protein S10 (arps10), multidrug resistance protein 2 (mdr2). QTLs were detected using synchronized, but not unsynchronized pools, consistent with the stage-specific action of DHA. We also successfully applied BSA to cryopreserved progeny pools. InterpretationOur results provide proof-of-principal of the utility of BSA for rapid, robust genetic mapping of drug resistance loci. Use of cryopreserved progeny pools expands the utility of BSA because we can conduct experiments using archived progeny pools from previous genetic crosses. BSA provides a powerful approach that complements traditional QTL methods for investigating the genetic architecture of resistance to antimalarials, and to reveal new or accessory loci contributing to artemisinin resistance. FundingNational Institutes of Health (NIH); Wellcome trust. O_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSGenetic crosses have been immensely successful for determining the genetic basis of drug resistance in malaria parasites, but require laborious cloning, characterization of drug resistance and genome-wide genotyping of individual progeny. This is a major limitation given that genetic crosses can now be conducted efficiently using humanized mice, rather than chimpanzees. Bulk segregant analysis (BSA) provides an attractive alternative approach because (i) large numbers of uncloned recombinant progeny can be analyzed, increasing statistical power (ii) phenotyping is not required, because we identify QTLs by treatment of progeny bulks, and identifying genome regions that show skews in allele frequency after treatment (iii) genome sequencing of bulk samples provides a rapid, accurate readout of genome-wide allele frequencies. This approach has been effectively leveraged in yeast, rodent malaria and several model organisms. Added value of this studyHere we validate and optimize this approach for P. falciparum genetic crosses, focusing on resistance to dihydroartemisin (DHA) a central component of the first-line antimalarial combination. Mutations in kelch13 are known to confer resistance to DHA, but several additional candidate loci have also been suggested to contribute. Our results confirm involvement of kelch13, but did not identify linkage with other putative candidate loci. We optimized methodology, showing that synchronization is critical, and that BSA can be successfully applied to cryopreserved progeny pools. Implications of all the available evidenceBSA combined with recent advances in rapidly generating genetic crosses provides a powerful approach to investigate the genetic basis of drug resistance in P. falciparum. C_TEXTBOX

genomics↗

bioRxiv2019

Mode and tempo of microsatellite length change in a malaria parasite mutation accumulation experiment

Microsatellite sequences are widely assumed to evolve neutrally, but also play an important role in bacterial pathogenesis, human disease and transcript abundance. The malaria parasite Plasmodium falciparum genome is extraordinarily AT-rich, containing 132,449 microsatellites-stretches of perfect 1-9 bp repeats between 10-1000bp, which comprise 10.74% of the 23 Mb genome. This project was designed to determine the mode and tempo of microsatellite mutations in malaria parasites. We maintained 31 parasite lines derived from a single 3D7 parasite cell for 114-267 days, with frequent bottlenecking to a single cell to minimize effective population size, allowing us to measure mutations accumulated over ~13,207 mitotic divisions. We Illumina sequenced the genomes of both progenitor and end-point mutation accumulation (MA) parasite lines in duplicate to validate stringent calling parameters. Calls were 99.89% (GATK), 99.99% (freeBayes) and 99.96% (HipSTR) concordant in duplicate sequence runs from independent sequence libraries. We observed 98 microsatellite mutations, giving rates of 2.11 x 10-7 - 1.46 x 10-8 /cell division that were strongly influenced by repeat motif and array length. Mutation rate was low relative to other organisms. However, despite this, in a single infection (1011 parasites) there will be 1.46 x 103 - 2.11 x 104 independent mutations at any single microsatellite locus. Given that many microsatellites are found in promotors, introns, within or close to coding sequences, we suggest that they may be important regulators of transcriptional and phenotypic variation in this pathogen. Author summaryMutation is central to evolution: in pathogens, the rate of mutation may determine how rapidly drug resistance evolves or how effectively pathogens can escape immune attack. Malaria parasites have small extremely AT-rich genomes, and genetic variation in natural populations is dominated by repeat number changes in short tandem repeats (microsatellites) rather than point mutations. We therefore focused on quantifying microsatellite mutation. We established 31 parasite cultures in the laboratory all derived from a single parasite cell. These were maintained for 114-267 days with frequent reductions to a single cell, so parasites accumulated mutations during ~13,207 cell divisions. We sequenced the parasite genomes at the end of the experiment to count the mutations. We highlight several conclusions: like other organisms studied, microsatellite mutation rates are associated with both repeat number and repeat motif. However, 41% of changes resulted from loss or gain of more than one repeat: this was particularly true for long repeat arrays. Unlike other eukaryotes, we found no insertions or deletions that were not associated with repeats or homology regions. Overall, we found that microsatellite mutation rates in malaria were amongst the lowest recorded and comparable to those in another AT-rich protozoan (the slime mold Dictyostelium).

evolutionary biology↗

bioRxiv2018

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

Malaria patients can carry one or more clonal lineage of the parasite, Plasmodium falciparum, but the composition of these infections cannot be directly inferred from bulk sequence data. Well-defined, complete haplotypes at single-cell resolution are ideal for describing within-host population structure and unambiguously determining parasite diversity, transmission dynamics and recent ancestry but have not been analyzed on a large scale. We generated 485 near-complete single-cell genome sequences isolated from fifteen P. falciparum patients from Chikhwawa, Malawi, an area of intense malaria transmission. Matched single-cell and bulk genomic analyses revealed patients harbored up to seventeen unique lineages. Estimation of parasite relatedness within patients suggests superinfection by repeated mosquito bites is rarer than co-transmission of parasites from a single mosquito. Our single-cell analysis indicates strong barriers to establishment of new infections in malaria-infected patients and allows high resolution dissection of intra-host variation in malaria parasites.

genetics↗

bioRxiv2017

High-resolution single-cell sequencing of malaria parasites

Single-cell genomics is a powerful tool for determining the genetic structure of complex communities of unicellular organisms. Patients infected with the malaria-causing parasite, Plasmodium falciparum, often carry multiple, genetically distinct parasites. Little is known about the diversity and relatedness of these lineages. We have developed an improved single-cell genomics protocol to reconstruct individual haplotypes from infections, a necessary step in uncovering parasite ecology within the host. This approach captures singly-infected red blood cells (iRBCs) by fluorescence-activated cell sorting (FACS) prior to whole genome amplification (WGA) and whole genome sequencing (WGS). Here, we demonstrate that parasites in late cell cycle stages, which contain increased DNA content, are far superior templates for generating high quality genomic data. Targeting of these cells routinely generates near-complete capture of the 23Mb P. falciparum genome (mean breadth of coverage 90.7%) at high efficiency. We used this approach to analyze the genomes of 48 individual cells from a polyclonal malaria infection sampled in Chikhwawa, Malawi. This comprehensive dataset enabled high-resolution estimation of the clonality and the relatedness of parasite haplotypes within the infection, long-standing problems in malaria biology.

genomics↗