Biology subjects

Schaffner, S.

Publications and source records attributed to Schaffner, S..

8 recordsLinked to original sources

bioRxiv2025

Phenotypic assessment and genetic validation of Plasmodium falciparum molecular markers associated with malaria chemoprevention in Senegal

Drug resistance in Plasmodium falciparum threatens to undermine malaria control and elimination efforts. Senegal is a malaria-endemic country that has implemented successive antimalarial and chemopreventive drug-based strategies for two decades. Sulfadoxine-pyrimethamine (SP) is used for chemoprevention in Senegal for intermittent preventive treatment in pregnancy (since 2004) and SP plus amodiaquine (AQ) is used for seasonal malaria chemoprevention (SMC, since 2013). Using whole genome sequence (WGS) data from malaria patient samples from health facilities across Senegal (2006 - 2022), we observed near fixation of Pfdhfr triple mutant and fluctuation in Pfdhps and Pfcrt mutation frequencies over time. It is unclear how these mutations influence drug resistance and fitness phenotypes in natural isolates; therefore, we evaluated natural parasite isolates with different Pfcrt, Pfmdr1, Pfdhps, and Pfdhfr haplotypes. Parasites were culture-adapted and phenotyped for antimalarial drug susceptibility and competitive growth (fitness). Pfcrt CVIET + A220S + Q271E + N326S + R371I and Pfcrt CVIET + A220S + Q271E + I356T + R371I mutants were significantly more resistant to monodesethyl-amodiaquine (md-AQ) compared to Pfcrt wild-type (WT) and Pfcrt CVIET + A220S + Q271E + R371I mutants. Pfdhfr triple mutants were significantly more pyrimethamine (PYR) resistant than Pfdhfr WT and revealed a range of phenotypes, but this was not explained by Pfgch1 copy-number. Pfdhps A437G parasites were significantly more sulfadoxine (SDX) resistant compared to Pfdhps wild-type and Pfdhps S436A mutants, suggesting that A437G is a key mutation for SDX resistance. Competitive growth assays between Pfdhfr-Pfdhps mutants revealed that Pfdhps mutations do not always result in fitness costs. Ongoing phenotypic assessment and genetic validation of these mutations in a Senegalese background is necessary to assess the impact of drug pressure, identify evolving genetic determinants of drug resistance, and provide molecular markers for ongoing surveillance to monitor and guide the use of drug-based interventions. AUTHOR SUMMARYDrug resistance is a major concern for both preventing and treating malaria, especially in Africa where most malaria cases and deaths occur. Since 2013, Senegal has been giving children under 10 years old a combination of sulfadoxine-pyrimethamine plus amodiaquine to prevent malaria during the transmission season, called Seasonal Malaria Chemoprevention (SMC), and plans to continue expanding its use. However, there is evidence from genetic surveillance that drug resistance mutations are present in Senegal which could render this antimalarial drug combination ineffective. Here we use natural P. falciparum isolates obtained from Senegalese patients that represent the extant parasite population to evaluate the consequences of evolving mutations on antimalarial drug resistance and fitness phenotypes. This study is one of the first to use natural parasites to assess the impact of naturally derived mutations on drug resistance and fitness phenotypes. Our results provide evidence that certain combinations of drug resistance mutations impact both parasite drug resistance and fitness, and therefore need to be closely monitored and can inform optimal antimalarial combinations for the prevention or treatment of malaria. This work informs the ongoing evolution of resistance and fitness phenotypes in malaria endemic settings that are introducing new multi first line therapies (MFTs) and SMC interventions that have been used for decades in Senegal. Our approach creates a framework for using genetic surveillance data to form a hypothesis, which can then be phenotypically tested by measuring the resistance and fitness levels of genetically diverse natural parasite isolates.

molecular biology↗

bioRxiv2025

Distinct Co-Methylation Patterns in African and European Populations and Their Genetic Associations

Human populations have substantial genetic diversity, but the extent of epigenetic diversity remains unclear, as population-specific DNA methylation (DNAm) has only been studied for [~]3.0% of CpGs. This study quantifies DNAm using whole-genome bisulfite sequencing (WGBS) and analyzes it alongside whole-genome genotype data to reveal a comprehensive picture of population-specific DNAm. Using a "co-methylated region" (CMR) approach, 36,657 CMRs were identified in 62 lymphoblastoid B cell line (LCL) WGBS samples, with validation in array data sets from 326 LCL samples. Between individuals of European and African ancestry, 101 CMRs exhibited population-specific DNAm patterns (Pop-CMRs), including 91 Pop-CMRs not found in previous investigations, which spanned genes (e.g., CCDC42, GYPE, MAP3K20, and OBI1) related to diseases (e.g., malaria infection and diabetes) with different prevalence and incidence rates between populations. Over half of the Pop-CMRs were asscoated with genetic variants, displaying population-specific allele frequencies and primarily mapping to genes involved in metabolic and infectious processes. Additionally, subsets of Pop-CMRs could be applicable in East Asian populations and peripheral blood-based tissues. This study provides insights into DNAm differences across the genome between populations and explores their associations with genetic variants and biological relevance, advancing our understanding of epigenetic roles in population specificity.

genetics↗

bioRxiv2024

Genetic Basis, Quantitative Nature, and Functional Relevance of Evolutionarily Conserved DNA Methylation

DNA methylation (DNAm) is a key epigenetic mark that modulates regulatory elements and gene expression, playing a crucial role in mammalian development and physiological function. Despite extensive characterization of DNAm profiles across species, little is known about its evolutionary conservation. Here, we conducted a comparative epigenome-wide analysis of great apes to identify and characterize sequence- and methylation-conserved CpGs (MCCs). Using 202 DNAm arrays, alongside 6 matched genotype and 13 matched transcriptomic datasets, we identified 11,500 MCCs for which methylation was evolutionarily related to sequences of CpGs and methylation quantitative trait loci. MCCs were the most stable across healthy human tissues and exhibited weaker genetic associations than other CpGs. Moreover, MCCs showed minimal associations with demographic, environmental factors, and noncancer diseases, yet demonstrated stronger associations with certain cancers than other CpGs, particularly gastrointestinal cancers. Functional enrichment analysis revealed that genes associated with MCC methylation in cancer were enriched for cancer driver genes and canonical cancer pathways, highlighting a significant regulatory role for MCCs in tumorigenesis. Collectively, our findings reveal the extent of DNAm conservation in great ape evolution, its association with genetic conservation, and its relevance to human diseases. These integrative analyses offer evolutionary insights into epigenetic variation and its functional implications in human populations.

genetics↗

bioRxiv2024

MalKinID: A Likelihood-Based Model for Identifying Malaria Parasite Genealogical Relationships Using Identity-by-Descent

Pathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent (IBD) is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, IBD can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for genotype- to-phenotype quantitative-trait-locus experiments. MalKinID (Malaria Kinship Identifier) is a new likelihood-based classification model designed to identify genealogical relationships among malaria parasites based on genome-wide IBD proportions and IBD segment distributions. MalKinID was calibrated to the genomic data from three laboratory-based genetic crosses (yielding 440 parent-child and 9060 full-sibling comparisons). MalKinID identified lab generated F1 progeny with >80% sensitivity and showed that 0.39 (95% CI 0.28, 0.49) of the second- generation progeny of a NF54 and NHP4026 cross were F1s and 0.56 (0.45, 0.67) were backcrosses of an F1 with the parental NF54 strain. In simulated outcrossed importations, MalKinID accurately reconstructs genealogy history with high precision and sensitivity, with F1- scores exceeding 0.84. However, when importation involves inbreeding, such as during serial co-transmission, the precision and sensitivity of MalKinID declined, with F1-scores of 0.76 (0.56, 0.92) and 0.23 (0.0, 0.4) for PC and FS and <0.05 for second-degree and third-degree relatives. Genealogical inference is most powered 1) when outcrossing is the norm or 2) when multi- sample comparisons based on a predefined pedigree are used. MalKinID lays the foundations for using IBD to track parasite transmission history and for separating progeny for quantitative- trait-locus experiments.

genetics↗

bioRxiv2023

BRWD3 promotes KDM5 degradation to maintain H3K4 methylation levels

Histone modifications are critical for regulating chromatin structure and gene expression. Dysregulation of histone modifications likely contributes to disease states and cancer. Depletion of the chromatin-binding protein BRWD3, a known substrate-specificity factor of the Cul4-DDB1 E3 ubiquitin ligase complex, results in increased in H3K4me1 levels. The underlying mechanism linking BRWD3 and H3K4 methylation, however, has yet to be defined. Here, we show that depleting BRWD3 not only causes an increase in H3K4me1 levels, but also causes a decrease in H3K4me3 levels, indicating that BRWD3 influences H3K4 methylation more broadly. Using immunoprecipitation coupled to quantitative mass spectrometry, we identified an interaction between BRWD3 and the H3K4-specific demethylase 5 (KDM5/Lid), an enzyme that removes tri- and di- methyl marks from H3K4. Moreover, analysis of ChIP-seq data revealed that BRWD3 and KDM5 are significantly co- localized throughout the genome and that sites of H3K4me3 are highly enriched at BRWD3 binding sites. We show that BRWD3 promotes K48-linked polyubiquitination and degradation of KDM5 and that KDM5 degradation is dependent on both BRWD3 and Cul4. Critically, depleting KDM5 fully restores altered H3K4me3 levels and partially restores H3K4me1 levels upon BRWD3 depletion. Together, our results demonstrate that BRWD3 regulates KDM5 activity to balance H3K4 methylation levels.

molecular biology↗

bioRxiv2020

An Engrailed1 enhancer underlies human thermoregulatory evolution

Humans rely on sweating to cool off and have the highest eccrine sweat gland density among mammals. We investigated whether altered regulation of the Engrailed 1 (EN1) gene, the levels of which are critical for patterning eccrine glands during development, could underlie the evolution of this defining human trait. First, we identify five EN1 candidate enhancers (ECEs) using comparative genomics and validation of enhancer activity in mouse skin. The human ortholog of one ECE, hECE18, contains multiple derived substitutions that together dramatically increase the activity of this enhancer in keratinocytes. Targeted repression of hECE18 reduces EN1 expression in human keratinocytes, indicating hECE18 upregulates EN1 in this context. Finally, we find that hECE18 increases ectodermal En1 in a humanized knock-in mouse to increase eccrine gland number. Our study uncovers a genetic basis for the evolution of one of the most singular human adaptations and implicates the recurrent mutation of a single enhancer as a novel mechanism for evolutionary change.

evolutionary biology↗

bioRxiv2020

Biomarkers to distinguish bacterial from viral pediatric clinical pneumonia in a malaria endemic setting

BACKGROUNDDifferentiating the etiology of acute febrile respiratory illness in children is a challenge in low-income, malaria-endemic settings because the main pathogens responsible (viruses, bacteria, and malaria parasites) overlap in clinical presentation and frequently occur together as mixed infections. The critical task is to rapidly identify bacterial pneumonia to enable appropriate antibiotic treatment, ideally at point of care. Current diagnostic tests are insufficient and there is a need for the discovery and development of new tools. Here we report the identification of a unique biomarker signature that can be identified in blood samples. METHODSBlood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based high dynamic range assay to quantify [~]1200 proteins. For discovery of new biomarkers, we identified a training set of patient samples in which the underlying etiology of the pneumonia was established as bacterial, viral or malaria. Proteins whose abundances varied significantly between patients with verified etiologies (FDR<0.01) formed the basis for predictive diagnostic models that were created using machine learning techniques (Random Forest, Elastic Net). These models were validated on a dedicated test set of samples. RESULTS219 proteins had significantly different abundances between bacterial and viral infections, and 151 differed between bacterial infections and a mixed pool of viral and malaria infections. Predictive diagnostic models achieved >90% sensitivity and >80% specificity, regardless of whether one or two pathogen classes were present. Bacterial pneumonia was strongly associated with markers of neutrophil activity, in particular neutrophil degranulation. Degranulation markers included HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSIONBlood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia.

genomics↗

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↗