Design and implementation of multiplexed amplicon sequencing panels to serve genomic epidemiology of infectious disease: a malaria case study

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in Plasmodium falciparum

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is being used in Plasmodium population genomics to estimate genetic relatedness, effective population size ( N e ) , population structure, and positive selection. However, a comprehensive evaluation of IBD segment detection tools is lacking for species with high rates of recombination. Here, we employ genetic simulations reflecting P. falciparum's high recombination rate and decreasing N e to benchmark IBD callers, including probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD), using genealogy-based true IBD and downstream inference of population characteristics. Our findings reveal that low marker density per genetic unit, related to high recombination rates relative to mutation rates, significantly affects the quality of detected IBD segments. Most IBD callers suffer from high false negative rates, which can be improved with parameter optimization. Optimized parameters allow for more accurate capture of selection signals and population structure, but hmmIBD is unique in providing less biased estimates of N e . Empirical data subsampled from the MalariaGEN Pf7 database, representing different transmission settings, confirmed these patterns. We conclude that the detection of IBD in high-recombining species requires context-specific evaluation and parameter optimization and recommend that hmmIBD be used for quality-sensitive analysis, such as estimation of N e in these species.

Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing

Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3-4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.

Using a mobile nanopore sequencing lab for end-to-end genomic surveillance of Plasmodium falciparum: A feasibility study

Genomic epidemiology holds promise for malaria control and elimination efforts, for example by informing on Plasmodium falciparum genetic diversity and prevalence of mutations conferring anti-malarial drug resistance. Limited sequencing infrastructure in many malaria-endemic areas prevents the rapid generation of genomic data. To address these issues, we developed and validated assays for P. falciparum nanopore sequencing in endemic sites using a mobile laboratory, targeting key antimalarial drug resistance markers and microhaplotypes. Using two multiplexed PCR reactions, we amplified six highly polymorphic microhaplotypes and ten drug resistance markers. We developed a bioinformatics workflow that allows genotyping of polyclonal malaria infections, including minority clones. We validated the panels on mock dried blood spot (DBS) and rapid diagnostic test (RDT) samples and archived DBS, demonstrating even, high read coverage across amplicons (range: 580x to 3,212x median coverage), high haplotype calling accuracy, and the ability to explore within-sample diversity of polyclonal infections. We field-tested the feasibility of rapid genotyping in Zanzibar in close collaboration with the local malaria elimination program using DBS and routinely collected RDTs as sample inputs. Our assay identified haplotypes known to confer resistance to known antimalarials in the dhfr, dhps and mdr1 genes, but no evidence of artemisinin partial resistance. Most infections (60%) were polyclonal, with high microhaplotype diversity (median HE = 0.94). In conclusion, our assays generated actionable data within a few days, and we identified current challenges for implementing nanopore sequencing in endemic countries to accelerate malaria control and elimination.

Molecular markers for malaria genetic epidemiology: progress and pitfalls

Over recent years, progress in molecular markers for genotyping malaria parasites has enabled informative studies of epidemiology and transmission dynamics. Results have highlighted the value of these tools for surveillance to support malaria control and elimination strategies. There are many different types and panels of markers available for malaria parasite genotyping, and for end users, the nuances of these markers with respect to 'use case', resolution, and accuracy, are not well defined. This review clarifies issues surrounding different molecular markers and their application to malaria control and elimination. We describe available marker panels, use cases, implications for different transmission settings, limitations, access, cost, and data accuracy. The information provided can be used as a guide for molecular epidemiology and surveillance of malaria.

Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana

Malaria results in over 600,000 deaths annually, with the highest burden of deaths in young children living in sub-Saharan Africa. Molecular surveillance can provide important information for malaria control policies, including detection of antimalarial drug resistance. However, genome sequencing capacity in malaria-endemic countries is limited. We designed and implemented an end-to-end workflow to detect Plasmodium falciparum antimalarial resistance markers and diversity in the vaccine target circumsporozoite protein (csp) using nanopore sequencing in Ghana. We analysed 196 clinical samples and showed that our method is rapid, robust, accurate and straightforward to implement. Importantly, our method could be applied to dried blood spot samples, which are readily collected in endemic settings. We report that P. falciparum parasites in Ghana are mostly susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine resistance and no evidence of artemisinin resistance. Multiple single nucleotide polymorphisms were identified in csp, but their significance is uncertain. Our study demonstrates the feasibility of nanopore sequencing for malaria genomic surveillance in endemic countries.

MOIRE: A software package for the estimation of allele frequencies and effective multiplicity of infection from polyallelic data

Malaria parasite genetic data can provide insight into parasite phenotypes, evolution, and transmission. However, estimating key parameters such as allele frequencies, multiplicity of infection (MOI), and within-host relatedness from genetic data has been challenging, particularly in the presence of multiple related coinfecting strains. Existing methods often rely on single nucleotide polymorphism (SNP) data and do not account for within-host relatedness. In this study, we introduce a Bayesian approach called MOIRE (Multiplicity Of Infection and allele frequency REcovery), designed to estimate allele frequencies, MOI, and within-host relatedness from genetic data subject to experimental error. Importantly, MOIRE is flexible in accommodating both polyallelic and SNP data, making it adaptable to diverse genotyping panels. We also introduce a novel metric, the effective MOI ( e M O I ) , which integrates MOI and within-host relatedness, providing a robust and interpretable measure of genetic diversity. Using extensive simulations and real-world data from a malaria study in Namibia, we demonstrate the superior performance of MOIRE over naive estimation methods, accurately estimating MOI up to 7 with moderate sized panels of diverse loci (e.g. microhaplotypes). MOIRE also revealed substantial heterogeneity in population mean MOI and mean relatedness across health districts in Namibia, suggesting detectable differences in transmission dynamics. Notably, e M O I emerges as a portable metric of within-host diversity, facilitating meaningful comparisons across settings, even when allele frequencies or genotyping panels are different. MOIRE represents an important addition to the analysis toolkit for malaria population dynamics. Compared to existing software, MOIRE enhances the accuracy of parameter estimation and enables more comprehensive insights into within-host diversity and population structure. Additionally, MOIRE's adaptability to diverse data sources and potential for future improvements make it a valuable asset for research on malaria and other organisms, such as other eukaryotic pathogens. MOIRE is available as an R package at https://eppicenter.github.io/moire/.

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

Here we introduce a new endpoint "census population size" to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (M O I v a r ), based on the hyper-diversity of the v a r multigene family. We present a Bayesian approach to estimate M O I v a r from sequencing and counting the number of unique DBLα tags (or DBLα types) of v a r genes, and derive from it census population size by summation of M O I v a r in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in v a r diversity, M O I v a r , and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, v a r diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the v a r population genetic characteristics of a high-transmission system (high v a r diversity; low v a r repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Neither the African-Centric S47 Nor P72 Variant of TP53 Is Associated With Reduced Risk of Febrile Malaria in a Malian Cohort Study

BACKGROUND

TP53 has been shown to play a role in inflammatory processes, including malaria. We previously found that p53 attenuates parasite-induced inflammation and predicts clinical protection to Plasmodium falciparum infection in Malian children. Here, we investigated whether p53 codon 47 and 72 polymorphisms are associated with differential risk of P. falciparum infection and uncomplicated malaria in a prospective cohort study of malaria immunity.

METHODS

p53 codon 47 and 72 polymorphisms were determined by sequencing TP53 exon 4 in 631 Malian children and adults enrolled in the Kalifabougou cohort study. The effects of these polymorphisms on the prospective risk of febrile malaria, incident parasitemia, and time to fever after incident parasitemia over 6 months of intense malaria transmission were assessed using Cox proportional hazards models.

RESULTS

Confounders of malaria risk, including age and hemoglobin S or C, were similar between individuals with or without p53 S47 and R72 polymorphisms. Relative to their respective common variants, neither S47 nor R72 was associated with differences in prospective risk of febrile malaria, incident parasitemia, or febrile malaria after parasitemia.

CONCLUSIONS

These findings indicate that p53 codon 47 and 72 polymorphisms are not associated with protection against incident P. falciparum parasitemia or uncomplicated febrile malaria.

Multiplexed ddPCR-amplicon sequencing reveals isolated Plasmodium falciparum populations amenable to local elimination in Zanzibar, Tanzania

Zanzibar has made significant progress toward malaria elimination, but recent stagnation requires novel approaches. We developed a highly multiplexed droplet digital PCR (ddPCR)-based amplicon sequencing method targeting 35 microhaplotypes and drug-resistance loci, and successfully sequenced 290 samples from five districts covering both main islands. Here, we elucidate fine-scale Plasmodium falciparum population structure and infer relatedness and connectivity of infections using an identity-by-descent (IBD) approach. Despite high genetic diversity, we observe pronounced fine-scale spatial and temporal parasite genetic structure. Clusters of near-clonal infections on Pemba indicate persistent local transmission with limited parasite importation, presenting an opportunity for local elimination efforts. Furthermore, we observe an admixed parasite population on Unguja and detect a substantial fraction (2.9%) of significantly related infection pairs between Zanzibar and the mainland, suggesting recent importation. Our study provides a high-resolution view of parasite genetic structure across the Zanzibar archipelago and provides actionable insights for prioritizing malaria elimination efforts.

Carryover Contamination-Controlled Amplicon Sequencing Workflow for Accurate Qualitative and Quantitative Detection of Pathogens: a Case Study on SARS-CoV-2

Carryover contamination during amplicon sequencing workflow (AMP-Seq) put the accuracy of the high-throughput detection for pathogens at risk. The purpose of this study is to develop a carryover contaminations-controlled AMP-Seq (ccAMP-Seq) workflow to enable accurate qualitative and quantitative detection for pathogens. By using the AMP-Seq workflow to detect SARS-CoV-2, Aerosols, reagents and pipettes were identified as potential sources of contaminations and ccAMP-Seq was then developed. ccAMP-Seq used filter tips and physically isolation of experimental steps to avoid cross contamination, synthetic DNA spike-ins to compete with contaminations and quantify SARS-CoV-2, dUTP/uracil DNA glycosylase system to digest the carryover contaminations, and a new data analysis procedure to remove the sequencing reads from contaminations. Compared to AMP-Seq, the contamination level of ccAMP-Seq was at least 22-folds lower and the detection limit was also about an order of magnitude lower-as low as one copy/reaction. By testing the dilution series of SARS-CoV-2 nucleic acid standard, ccAMP-Seq showed 100% sensitivity and specificity. The high sensitivity of ccAMP-Seq was further confirmed by the detection of SARS-CoV-2 from 62 clinical samples. The consistency between qPCR and ccAMP-Seq was 100% for all the 53 qPCR-positive clinical samples. Seven qPCR-negative clinical samples were found to be positive by ccAMP-Seq, which was confirmed by extra qPCR tests on subsequent samples from the same patients. This study presents a carryover contamination-controlled, accurate qualitative and quantitative amplicon sequencing workflow that addresses the critical problem of pathogen detection for infectious diseases. IMPORTANCE Accuracy, a key indicator of pathogen detection technology, is compromised by carryover contamination in the amplicon sequencing workflow. Taking the detection of SARS-CoV-2 as case, this study presents a new carryover contamination-controlled amplicon sequencing workflow. The new workflow significantly reduces the degree of contamination in the workflow, thereby significantly improving the accuracy and sensitivity of the SARS-CoV-2 detection and empowering the ability of quantitative detection. More importantly, the use of the new workflow is simple and economical. Therefore, the results of this study can be easily applied to other microorganism, which has great significance for improving the detection level of microorganism.

Comparison of molecular surveillance methods to assess changes in the population genetics of Plasmodium falciparum in high transmission

A major motivation for developing molecular methods for malaria surveillance is to measure the impact of control interventions on the population genetics of Plasmodium falciparum as a potential marker of progress towards elimination. Here we assess three established methods (i) single nucleotide polymorphism (SNP) barcoding (panel of 24-biallelic loci), (ii) microsatellite genotyping (panel of 12-multiallelic loci), and (iii) varcoding (fingerprinting var gene diversity, akin to microhaplotyping) to identify changes in parasite population genetics in response to a short-term indoor residual spraying (IRS) intervention. Typical of high seasonal transmission in Africa, multiclonal infections were found in 82.3% (median 3; range 1-18) and 57.8% (median 2; range 1-12) of asymptomatic individuals pre- and post-IRS, respectively, in Bongo District, Ghana. Since directly phasing multilocus haplotypes for population genetic analysis is not possible for biallelic SNPs and microsatellites, we chose ~200 low-complexity infections biased to single and double clone infections for analysis. Each genotyping method presented a different pattern of change in diversity and population structure as a consequence of variability in usable data and the relative polymorphism of the molecular markers (i.e., SNPs < microsatellites < var). Varcoding and microsatellite genotyping showed the overall failure of the IRS intervention to significantly change the population structure from pre-IRS characteristics (i.e., many diverse genomes of low genetic similarity). The 24-SNP barcode provided limited information for analysis, largely due to the biallelic nature of SNPs leading to a high proportion of double-allele calls and a view of more isolate relatedness compared to microsatellites and varcoding. Relative performance, suitability, and cost-effectiveness of the methods relevant to sample size and local malaria elimination in high-transmission endemic areas are discussed.

Lineage-informative microhaplotypes for spatio-temporal surveillance of Plasmodium vivax malaria parasites

Challenges in understanding the origin of recurrent Plasmodium vivax infections constrains the surveillance of antimalarial efficacy and transmission of this neglected parasite. Recurrent infections within an individual may arise from activation of dormant liver stages (relapse), blood-stage treatment failure (recrudescence) or new inoculations (reinfection). Molecular inference of familial relatedness (identity-by-descent or IBD) based on whole genome sequence data, together with analysis of the intervals between parasitaemic episodes ("time-to-event" analysis), can help resolve the probable origin of recurrences. Whole genome sequencing of predominantly low-density P. vivax infections is challenging, so an accurate and scalable genotyping method to determine the origins of recurrent parasitaemia would be of significant benefit. We have developed a P. vivax genome-wide informatics pipeline to select specific microhaplotype panels that can capture IBD within small, amplifiable segments of the genome. Using a global set of 615 P. vivax genomes, we derived a panel of 100 microhaplotypes, each comprising 3-10 high frequency SNPs within <200 bp sequence windows. This panel exhibits high diversity in regions of the Asia-Pacific, Latin America and the horn of Africa (median HE = 0.70-0.81) and it captured 89% (273/307) of the polyclonal infections detected with genome-wide datasets. Using data simulations, we demonstrate lower error in estimating pairwise IBD using microhaplotypes, relative to traditional biallelic SNP barcodes. Our panel exhibited high accuracy in predicting the country of origin (median Matthew's correlation coefficient >0.9 in 90% countries tested) and it also captured local infection outbreak and bottlenecking events. The informatics pipeline is available open-source and yields microhaplotypes that can be readily transferred to high-throughput amplicon sequencing assays for surveillance in malaria-endemic regions.

Unravelling var complexity: Relationship between DBLα types and var genes in Plasmodium falciparum

The enormous diversity and complexity of var genes that diversify rapidly by recombination has led to the exclusion of assembly of these genes from major genome initiatives (e.g., Pf6). A scalable solution in epidemiological surveillance of var genes is to use a small ‘tag’ region encoding the immunogenic DBLα domain as a marker to estimate var diversity. As var genes diversify by recombination, it is not clear the extent to which the same tag can appear in multiple var genes. This relationship between marker and gene has not been investigated in natural populations. Analyses of in vitro recombination within and between var genes have suggested that this relationship would not be exclusive. Using a dataset of publicly-available assembled var sequences, we test this hypothesis by studying DBLα-var relationships for four study sites in four countries: Pursat (Cambodia) and Mae Sot (Thailand), representing low malaria transmission, and Navrongo (Ghana) and Chikwawa (Malawi), representing high malaria transmission. In all study sites, DBLα-var relationships were shown to be predominantly 1-to-1, followed by a second largest proportion of 1-to-2 DBLα-var relationships. This finding indicates that DBLα tags can be used to estimate not just DBLα diversity but var gene diversity when applied in a local endemic area. Epidemiological applications of this result are discussed.