Rapid, Field-Deployable Method for Genotyping and Discovery of Single-Nucleotide Polymorphisms Associated with Drug Resistance in Plasmodium falciparum

Despite efforts to reduce malaria morbidity and mortality, drug-resistant parasites continue to evade control strategies. Recently, emphasis has shifted away from control and toward regional elimination and global eradication of malaria. Such a campaign requires tools to monitor genetic changes in the parasite that could compromise the effectiveness of antimalarial drugs and undermine eradication programs. These tools must be fast, sensitive, unambiguous, and cost-effective to offer real-time reports of parasite drug susceptibility status across the globe. We have developed and validated a set of genotyping assays using high-resolution melting (HRM) analysis to detect molecular biomarkers associated with drug resistance across six genes in Plasmodium falciparum. We improved on existing technical approaches by developing refinements and extensions of HRM, including the use of blocked probes (LunaProbes) and the mutant allele amplification bias (MAAB) technique. To validate the sensitivity and accuracy of our assays, we compared our findings to sequencing results in both culture-adapted lines and clinical isolates from Senegal. We demonstrate that our assays (i) identify both known and novel polymorphisms, (ii) detect multiple genotypes indicative of mixed infections, and (iii) distinguish between variants when multiple copies of a locus are present. These rapid and inexpensive assays can track drug resistance and detect emerging mutations in targeted genetic loci in P. falciparum. They pro- vide tools for monitoring molecular changes associated with changes in drug response across populations and for determining whether parasites present after drug treatment are the result of recrudescence or reinfection in clinical settings.Organismic and Evolutionary Biolog

Quantum cascade laser-based reflectance spectroscopy: a robust approach for the classification of plastic type

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Michel, A. P. M., Morrison, A. E., Colson, B. C., Pardis, W. A., Moya, X. A., Harb, C. C., & White, H. K. Quantum cascade laser-based reflectance spectroscopy: a robust approach for the classification of plastic type. Optics Express, 28(12), (2020): 17741-17756, doi:10.1364/OE.393231.The identification of plastic type is important for environmental applications ranging from recycling to understanding the fate of plastics in marine, atmospheric, and terrestrial environments. Infrared reflectance spectroscopy is a powerful approach for plastics identification, requiring only optical access to a sample. The use of visible and near-infrared wavelengths for plastics identification are limiting as dark colored plastics absorb at these wavelengths, producing no reflectance spectra. The use of mid-infrared wavelengths instead enables dark plastics to be identified. Here we demonstrate the capability to utilize a pulsed, widely-tunable (5.59 - 7.41 µm) mid-infrared quantum cascade laser, as the source for reflectance spectroscopy, for the rapid and robust identification of plastics. Through the application of linear discriminant analysis to the resulting spectral data set, we demonstrate that we can correctly classify five plastic types: polyethylene terephthalate (PET), high density polyethylene (HDPE), low density polyethylene (LDPE), polypropylene (PP), and polystyrene (PS), with a 97% accuracy rate.Richard Saltonstall Charitable Foundation; National Academies Keck Futures Initiative (NAKFI DBS13)

Mining data from 1000 genomes to identify the causal variant in regions under positive selection

The human genome contains hundreds of regions in which the patterns of genetic variation indicate recent positive natural selection, yet for most of these the underlying gene and the advantageous mutation remain unknown. We recently reported the development of a method, Composite of Multiple Signals (CMS), that combines tests for multiple signals of natural selection and increases resolution by up to 100-fold

Malaria Life Cycle Intensifies Both Natural Selection and Random Genetic Drift

Analysis of genome sequences of 159 isolates of Plasmodium falciparum from Senegal yields an extraordinarily high proportion (26.85%) of protein-coding genes with the ratio of nonsynonymous to synonymous polymorphism greater than one. This proportion is much greater than observed in other organisms. Also unusual is that the site-frequency spectra of synonymous and nonsynonymous polymorphisms are virtually indistinguishable. We hypothesized that the complicated life cycle of malaria parasites might lead to qualitatively different population genetics from that predicted from the classical Wright-Fisher (WF) model, which assumes a single random-mating population with a finite and constant population size in an organism with nonoverlapping generations. This paper summarizes simulation studies of random genetic drift and selection in malaria parasites that take into account their unusual life history. Our results show that random genetic drift in the malaria life cycle is more pronounced than under the WF model. Paradoxically, the efficiency of purifying selection in the malaria life cycle is also greater than under WF, and the relative efficiency of positive selection varies according to conditions. Additionally, the site-frequency spectrum under neutrality is also more skewed toward low-frequency alleles than expected with WF. These results highlight the importance of considering the malaria life cycle when applying existing population genetic tools based on the WF model. The same caveat applies to other species with similarly complex life cycles.Organismic and Evolutionary Biolog

Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay

Although studies have identified hundreds of loci associated with human traits and diseases, pinpointing causal alleles remains difficult, particularly for non-coding variants. To address this challenge, we adapted the massively parallel reporter assay (MPRA) to identify variants that directly modulate gene expression. We applied it to 32,373 variants from 3,642 cis-expression quantitative trait loci and control regions. Detection by MPRA was strongly correlated with measures of regulatory function. We demonstrate MPRA’s capabilities for pinpointing causal alleles, using it to identify 842 variants showing differential expression between alleles, including 53 well-annotated variants associated with diseases and traits. We investigated one in detail, a risk allele for ankylosing spondylitis, and provide direct evidence of a non-coding variant that alters expression of the prostaglandin EP4 receptor. These results create a resource of concrete leads and illustrate the promise of this approach for comprehensively interrogating how non-coding polymorphism shapes human biology.National Institutes of Health (U.S.) (grant DP2OD006514)National Institutes of Health (U.S.) (grant K99HG0081)National Institutes of Health (U.S.) (grant R01HG006785

COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data.

International audienceComplex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI

Sequence-Based Association and Selection Scans Identify Drug Resistance Loci in the Plasmodium Falciparum Malaria Parasite

Through rapid genetic adaptation and natural selection, the Plasmodium falciparum parasite—the deadliest of those that cause malaria—is able to develop resistance to antimalarial drugs, thwarting present efforts to control it. Genome-wide association studies (GWAS) provide a critical hypothesis-generating tool for understanding how this occurs. However, in P. falciparum, the limited amount of linkage disequilibrium hinders the power of traditional array-based GWAS. Here, we demonstrate the feasibility and power improvements gained by using whole-genome sequencing for association studies. We analyzed data from 45 Senegalese parasites and identified genetic changes associated with the parasites’ in vitro response to 12 different antimalarials. To further increase statistical power, we adapted a common test for natural selection, XP-EHH (cross-population extended haplotype homozygosity), and used it to identify genomic regions associated with resistance to drugs. Using this sequence-based approach and the combination of association and selection-based tests, we detected several loci associated with drug resistance. These loci included the previously known signals at pfcrt, dhfr, and pfmdr1, as well as many genes not previously implicated in drug-resistance roles, including genes in the ubiquitination pathway. Based on the success of the analysis presented in this study, and on the demonstrated shortcomings of array-based approaches, we argue for a complete transition to sequence-based GWAS for small, low linkage-disequilibrium genomes like that of P. falciparum.Molecular and Cellular BiologyOrganismic and Evolutionary Biolog

Identification and Functional Validation of the Novel Antimalarial Resistance Locus PF10_0355 in Plasmodium falciparum

The Plasmodium falciparum parasite's ability to adapt to environmental pressures, such as the human immune system and antimalarial drugs, makes malaria an enduring burden to public health. Understanding the genetic basis of these adaptations is critical to intervening successfully against malaria. To that end, we created a high-density genotyping array that assays over 17,000 single nucleotide polymorphisms (~1 SNP/kb), and applied it to 57 culture-adapted parasites from three continents. We characterized genome-wide genetic diversity within and between populations and identified numerous loci with signals of natural selection, suggesting their role in recent adaptation. In addition, we performed a genome-wide association study (GWAS), searching for loci correlated with resistance to thirteen antimalarials; we detected both known and novel resistance loci, including a new halofantrine resistance locus, PF10_0355. Through functional testing we demonstrated that PF10_0355 overexpression decreases sensitivity to halofantrine, mefloquine, and lumefantrine, but not to structurally unrelated antimalarials, and that increased gene copy number mediates resistance. Our GWAS and follow-on functional validation demonstrate the potential of genome-wide studies to elucidate functionally important loci in the malaria parasite genome.Bill & Melinda Gates FoundationEllison Medical FoundationExxon Mobil FoundationFogarty International CenterNational Institute of Allergy and Infectious Diseases (U.S.)Burroughs Wellcome FundDavid & Lucile Packard FoundationNational Science Foundation (U.S.). Graduate Research Fellowship Progra