Repurposing FDA-approved drugs to target malaria through inhibition of dihydrofolate reductase in the folate biosynthesis pathway: A prospective approach.

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme that regulates the biosynthesis of tetrahydrofolate among various species of Plasmodium parasite. It is a validated target of the antifolate drug pyrimethamine (Pyr) in Plasmodium falciparum (Pf), but its clinical efficacy has been hampered due to the emergence of drug resistance. This has made the attempt to screen Food & Drug Administration-approved drugs against wild- and mutant PfDHFR by employing an in-silico pipeline to identify potent candidates. The current study has followed a virtual screening approach for identifying potential DHFR inhibitors from DrugBank database, based on a structure similarity search of candidates, followed by absorption, distribution, metabolism, and excretion estimation. The screened drugs were subjected to various parameters like docking, molecular mechanics with generalized born and surface area solvation calculations, and molecular simulations. We have thus identified two potential drug candidates, duloxetine and guanethidine, which can be repurposed to be tested for their efficacy against wild type and drug resistant falciparum malaria.

Low prevalence of antimalarial-resistance mutations in India during 2014-15: Impact of combining first-line therapy with primaquine.

BACKGROUND: Antimalarial drug resistance surveillance and containment are crucial for countries aiming to eliminate malaria. Monitoring resistance evolution through studies before and after treatment policy changes is crucial. METHOD: A total of 939 P. falciparum-positive blood samples were collected between 2014 and 2015 across ten sites in India, categorized into four geographic clusters. PCR-amplified products were sequenced to identify point mutations at drug-resistance-conferring genes (Pfdhfr, Pfdhps, Pfmdr1, Pfk13). RESULT: Triple Pfdhfr mutants were found only in northeast India bordering Myanmar, while the wildtype was dominant in central India. Pfdhps wildtypes were prevalent in all areas, and no double mutants were found. Except in Northwest India, Pfmdr1 wildtype was dominant in all clusters. Nonsynonymous double mutations were only found in northwest India. Only synonymous mutations occurred in Pfk13. These were found in Central India at low frequency. The pattern of linkage disequilibrium and principal component analysis reflects low pressure for drug resistance and heterogeneity between the geographic clusters. CONCLUSION: Resistance levels were highest in Northeast India, close to the Myanmar border, where resistance is common. Primaquine has been widely used as a gametocidal and schizonticidal drug, has likely contributed to maintaining low drug resistance levels and preventing strong selection for resistance.

Human NCR3 gene variants rs2736191 and rs11575837 alter longitudinal risk for development of pediatric malaria episodes and severe malarial anemia.

BACKGROUND: Plasmodium falciparum malaria is a leading cause of pediatric morbidity and mortality in holoendemic transmission areas. Severe malarial anemia [SMA, hemoglobin (Hb) < 5.0 g/dL in children] is the most common clinical manifestation of severe malaria in such regions. Although innate immune response genes are known to influence the development of SMA, the role of natural killer (NK) cells in malaria pathogenesis remains largely undefined. As such, we examined the impact of genetic variation in the gene encoding a primary NK cell receptor, natural cytotoxicity-triggering receptor 3 (NCR3), on the occurrence of malaria and SMA episodes over time. METHODS: Susceptibility to malaria, SMA, and all-cause mortality was determined in carriers of NCR3 genetic variants (i.e., rs2736191:C > G and rs11575837:C > T) and their haplotypes. The prospective observational study was conducted over a 36 mos. follow-up period in a cohort of children (n = 1,515, aged 1.9-40 mos.) residing in a holoendemic P. falciparum transmission region, Siaya, Kenya. RESULTS: Poisson regression modeling, controlling for anemia-promoting covariates, revealed a significantly increased risk of malaria in carriers of the homozygous mutant allele genotype (TT) for rs11575837 after multiple test correction [Incidence rate ratio (IRR) = 1.540, 95% CI = 1.114-2.129, P = 0.009]. Increased risk of SMA was observed for rs2736191 in children who inherited the CG genotype (IRR = 1.269, 95% CI = 1.009-1.597, P = 0.041) and in the additive model (presence of 1 or 2 copies) (IRR = 1.198, 95% CI = 1.030-1.393, P = 0.019), but was not significant after multiple test correction. Modeling of the haplotypes revealed that the CC haplotype had a significant additive effect for protection against SMA (i.e., reduced risk for development of SMA) after multiple test correction (IRR = 0.823, 95% CI = 0.711-0.952, P = 0.009). Although increased susceptibility to SMA was present in carriers of the GC haplotype (IRR = 1.276, 95% CI = 1.030-1.581, P = 0.026) with an additive effect (IRR = 1.182, 95% CI = 1.018-1.372, P = 0.029), the results did not remain significant after multiple test correction. None of the NCR3 genotypes or haplotypes were associated with all-cause mortality. CONCLUSIONS: Variation in NCR3 alters susceptibility to malaria and SMA during the acquisition of naturally-acquired malarial immunity. These results highlight the importance of NK cells in the innate immune response to malaria.

An integrated virtual screening and drug repurposing strategy for the discovery of new antimalarial drugs against Plasmodium falciparum phosphatidylinositol 3-kinase.

The emergence and spread of drug resistance in Plasmodium falciparum, the parasite causing the most severe form of human malaria, is a major threat to malaria control and elimination programs around the globe. With P. falciparum having evolved widespread resistance against a number of previously widely used drugs, currently, artemisinin (ART) and its derivatives are the cornerstones of first-line treatments of uncomplicated malaria. However, growing incidences of ART failure reflect the spread of ART-resistant P. falciparum strains. Despite current efforts to understand the primary cause of ART resistance due to mutations in the Kelch 13 gene (PfK13), the mechanism underlying ART resistance is still not completely unclear and no feasible strategies to counteract the causes and thereby restoring the efficiency of ART have been developed. We use a polypharmacology approach to identify potential drugs that can be used for the novel purpose (target). Of note, we have designed a multimodal stratagem to identify approved drugs with a potential antimalarial activity using computational drug reprofiling. Our investigations suggest that oxetacaine, simvastatin, repaglinide, aclidinium, propafenone, and lovastatin could be repurposed for malaria control and prevention.

Changes in the frequencies of Plasmodium falciparum dhps and dhfr drug-resistant mutations in children from Western Kenya from 2005 to 2018: the rise of Pfdhps S436H.

BACKGROUND: Sulfadoxine-pyrimethamine (SP) is the only anti-malarial drug formulation approved for intermittent preventive treatment in pregnancy (IPTp). However, mutations in the Plasmodium falciparum dhfr (Pfdhfr) and dhps (Pfdhps) genes confer resistance to pyrimethamine and sulfadoxine, respectively. Here, the frequencies of SP resistance-associated mutations from 2005 to 2018 were compared in samples from Kenyan children with malaria residing in a holoendemic transmission region. METHODS: Partial sequences of the Pfdhfr and Pfdhps genes were amplified and sequenced from samples collected in 2005 (n = 81), 2010 (n = 95), 2017 (n = 43), and 2018 (n = 55). The frequency of known mutations conferring resistance to pyrimethamine and sulfadoxine were estimated and compared. Since artemisinin-based combination therapy (ACT) is the current first-line treatment for malaria, the presence of mutations in the propeller domain of P. falciparum kelch13 gene (Pfk13) linked to ACT-delayed parasite clearance was studied in the 2017/18 samples. RESULTS: Among other changes, the point mutation of Pfdhps S436H increased in frequency from undetectable in 2005 to 28% in 2017/18. Triple Pfdhfr mutant allele (CIRNI) increased in frequency from 84% in 2005 to 95% in 2017/18, while the frequency of Pfdhfr double mutant alleles declined (allele CICNI from 29% in 2005 to 6% in 2017/18, and CNRNI from 9% in 2005 to undetectable in 2010 and 2017/18). Thus, a multilocus Pfdhfr/Pfdhps genotype with six mutations (HGEAA/CIRNI), including Pfdhps S436H, increased in frequency from 2010 to 2017/18. Although none of the mutations associated with ACT-delayed parasite clearance was observed, the Pfk13 mutation A578S, the most widespread Pfk13 SNP found in Africa, was detected in low frequency (2.04%). CONCLUSIONS: There were changes in SP resistance mutant allele frequencies, including an increase in the Pfdhps S436H. Although these patterns seem consistent with directional selection due to drug pressure, there is a lack of information to determine the actual cause of such changes. These results suggest incorporating molecular surveillance of Pfdhfr/Pfdhps mutations in the context of SP efficacy studies for intermittent preventive treatment in pregnancy (IPTp).

Malaria in Venezuela: changes in the complexity of infection reflects the increment in transmission intensity.

BACKGROUND: Malaria incidence has reached staggering numbers in Venezuela. Commonly, Bolívar State accounted for approximately 70% of the country cases every year. Most cases cluster in the Sifontes municipality, a region characterized by an extractive economy, including gold mining. An increase in migration to Sifontes, driven by gold mining, fueled a malaria spillover to the rest of the country and the region. Here samples collected in 2018 were compared with a previous study of 2003/2004 to describe changes in the parasites population structures and the frequency of point mutations linked to anti-malarial drugs. METHODS: A total of 88 Plasmodium falciparum and 94 Plasmodium vivax isolates were collected in 2018 and compared with samples from 2003/2004 (106 P. falciparum and 104 P. vivax). For P. falciparum, mutations linked to drug resistance (Pfdhfr, Pfdhps, and Pfcrt) and the Pfk13 gene associated with artemisinin delayed parasite clearance, were analysed. To estimate the multiplicity of infection (MOI), and perform P. falciparum and P. vivax population genetic analyses, the parasites were genotyped by using eight standardized microsatellite loci. RESULTS: The P. falciparum parasites are still harbouring drug-resistant mutations in Pfdhfr, Pfdhps, and Pfcrt. However, there was a decrease in the frequency of highly resistant Pfdhps alleles. Mutations associated with artemisinin delayed parasite clearance in the Pfk13 gene were not found. Consistent with the increase in transmission, polyclonal infections raised from 1.9% in 2003/2004 to 39% in 2018 in P. falciparum and from 16.3 to 68% in P. vivax. There is also a decrease in linkage disequilibrium. Bayesian clustering yields two populations linked to the time of sampling, showing that the parasite populations temporarily changed. However, the samples from 2003/2004 and 2018 have several alleles per locus in common without sharing multi-locus genotypes. CONCLUSIONS: The frequency of mutations linked with drug resistance in P. falciparum shows only changes in Pfdhps. Observations presented here are consistent with an increase in transmission from the previously circulating parasites. Following populations longitudinally, using molecular surveillance, provides valuable information in cases such as Venezuela with a fluid malaria situation that is affecting the regional goals toward elimination.

The COVID-19 pandemic preparedness simulation tool: CovidSIM.

BACKGROUND: Efficient control and management in the ongoing COVID-19 pandemic needs to carefully balance economical and realizable interventions. Simulation models can play a cardinal role in forecasting possible scenarios to sustain decision support. METHODS: We present a sophisticated extension of a classical SEIR model. The simulation tool CovidSIM Version 1.0 is an openly accessible web interface to interactively conduct simulations of this model. The simulation tool is used to assess the effects of various interventions, assuming parameters that reflect the situation in Austria as an example. RESULTS: Strict contact reduction including isolation of infected persons in quarantine wards and at home can substantially delay the peak of the epidemic. Home isolation of infected individuals effectively reduces the height of the peak. Contact reduction by social distancing, e.g., by curfews, sanitary behavior, etc. are also effective in delaying the epidemic peak. CONCLUSIONS: Contact-reducing mechanisms are efficient to delay the peak of the epidemic. They might also be effective in decreasing the peak number of infections depending on seasonal fluctuations in the transmissibility of the disease.

Profiles of low complexity regions in Apicomplexa.

BACKGROUND: Low complexity regions (LCRs) are a ubiquitous feature in genomes and yet their evolutionary history and functional roles are unclear. Previous studies have shown contrasting evidence in favor of both neutral and selective mechanisms of evolution for different sets of LCRs suggesting that modes of identification of these regions may play a role in our ability to discern their evolutionary history. To further investigate this issue, we used a multiple threshold approach to identify species-specific profiles of proteome complexity and, by comparing properties of these sets, determine the influence that starting parameters have on evolutionary inferences. RESULTS: We find that, although qualitatively similar, quantitatively each species has a unique LCR profile which represents the frequency of these regions within each genome. Inferences based on these profiles are more accurate in comparative analyses of genome complexity as they allow to determine the relative complexity of multiple genomes as well as the type of repetitiveness that is most common in each. Based on the multiple threshold LCR sets obtained, we identified predominant evolutionary mechanisms at different complexity levels, which show neutral mechanisms acting on highly repetitive LCRs (e.g., homopolymers) and selective forces becoming more important as heterogeneity of the LCRs increases. CONCLUSIONS: Our results show how inferences based on LCRs are influenced by the parameters used to identify these regions. Sets of LCRs are heterogeneous aggregates of regions that include homo- and heteropolymers and, as such, evolve according to different mechanisms. LCR profiles provide a new way to investigate genome complexity across species and to determine the driving mechanism of their evolution.

Estimating multiplicity of infection, allele frequencies, and prevalences accounting for incomplete data.

BACKGROUND: Molecular surveillance of infectious diseases allows the monitoring of pathogens beyond the granularity of traditional epidemiological approaches and is well-established for some of the most relevant infectious diseases such as malaria. The presence of genetically distinct pathogenic variants within an infection, referred to as multiplicity of infection (MOI) or complexity of infection (COI) is common in malaria and similar infectious diseases. It is an important metric that scales with transmission intensities, potentially affects the clinical pathogenesis, and a confounding factor when monitoring the frequency and prevalence of pathogenic variants. Several statistical methods exist to estimate MOI and the frequency distribution of pathogen variants. However, a common problem is the quality of the underlying molecular data. If molecular assays fail not randomly, it is likely to underestimate MOI and the prevalence of pathogen variants. METHODS AND FINDINGS: A statistical model is introduced, which explicitly addresses data quality, by assuming a probability by which a pathogen variant remains undetected in a molecular assay. This is different from the assumption of missing at random, for which a molecular assay either performs perfectly or fails completely. The method is applicable to a single molecular marker and allows to estimate allele-frequency spectra, the distribution of MOI, and the probability of variants to remain undetected (incomplete information). Based on the statistical model, expressions for the prevalence of pathogen variants are derived and differences between frequency and prevalence are discussed. The usual desirable asymptotic properties of the maximum-likelihood estimator (MLE) are established by rewriting the model into an exponential family. The MLE has promising finite sample properties in terms of bias and variance. The covariance matrix of the estimator is close to the Cramér-Rao lower bound (inverse Fisher information). Importantly, the estimator's variance is larger than that of a similar method which disregards incomplete information, but its bias is smaller. CONCLUSIONS: Although the model introduced here has convenient properties, in terms of the mean squared error it does not outperform a simple standard method that neglects missing information. Thus, the new method is recommendable only for data sets in which the molecular assays produced poor-quality results. This will be particularly true if the model is extended to accommodate information from multiple molecular markers at the same time, and incomplete information at one or more markers leads to a strong depletion of sample size.

Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia.

This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, compares the entire expressed whole blood host transcriptome between Kenyan children (3-48 mos.) with non-SMA (Hb ≥ 6.0 g/dL, n = 39) and SMA (n = 18). Differential expression analyses reveal 1403 up-regulated and 279 down-regulated transcripts in SMA, signifying impairments in host inflammasome activation, cell death, and innate immune and cellular stress responses. Immune cell profiling shows decreased memory responses, antigen presentation, and immediate pathogen clearance, suggesting an immature/improperly regulated immune response in SMA. Module repertoire analysis of blood-specific gene signatures identifies up-regulation of erythroid genes, enhanced neutrophil activation, and impaired inflammatory responses in SMA. Enrichment analyses converge on disruptions in cellular homeostasis and regulatory pathways for the ubiquitin-proteasome system, autophagy, and heme metabolism. Pathway analyses highlight activation in response to hypoxic conditions [Hypoxia Inducible Factor (HIF)-1 target and Reactive Oxygen Species (ROS) signaling] as a central theme in SMA. These signaling pathways are also top-ranking in protein abundance measures and a Ugandan SMA cohort with available transcriptomic data. Targeted RNA-Seq validation shows strong concordance with our entire expressed transcriptome data. These findings identify key molecular themes in SMA pathogenesis, offering potential targets for new malaria therapies.

Fitness components and natural selection: why are there different patterns on the emergence of drug resistance in Plasmodium falciparum and Plasmodium vivax?

BACKGROUND: Considering the distinct biological characteristics of Plasmodium species is crucial for control and elimination efforts, in particular when facing the spread of drug resistance. Whereas the evolutionary fitness of all malarial species could be approximated by the probability of being taken by a mosquito and then infecting a new host, the actual steps in the malaria life cycle leading to a successful transmission event show differences among Plasmodium species. These "steps" are called fitness components. Differences in terms of fitness components may affect how selection imposed by interventions, e.g. drug treatments, differentially acts on each Plasmodium species. Thus, a successful malaria control or elimination programme should understand how differences in fitness components among different malaria species could affect adaptive evolution (e.g. the emergence of drug resistance). In this investigation, the interactions between some fitness components and natural selection are explored. METHODS: A population-genetic model is formulated that qualitatively explains how different fitness components (in particular gametocytogenesis and longevity of gametocytes) affect selection acting on merozoites during the erythrocytic cycle. By comparing Plasmodium falciparum and Plasmodium vivax, the interplay of parasitaemia and gametocytaemia dynamics in determining fitness is modelled under circumstances that allow contrasting solely the differences between these two parasites in terms of their fitness components. RESULTS: By simulating fitness components, it is shown that selection acting on merozoites (e.g., on drug resistant mutations or malaria antigens) is more efficient in P. falciparum than in P. vivax. These results could explain, at least in part, why resistance against drugs, such as chloroquine (CQ) is highly prevalent in P. falciparum worldwide, while CQ is still a successful treatment for P. vivax despite its massive use. Furthermore, these analyses are used to explore the importance of understanding the dynamic of gametocytaemia to ascertain the spreading of drug resistance. CONCLUSIONS: The strength of natural selection on mutations that express their advantage at the merozoite stage is different in P. vivax and P. falciparum. Species-specific differences in gametocytogenesis and longevity of gametocytes need to be accounted for when designing effective malaria control and elimination programmes. There is a need for reliable data on gametocytogenesis from field studies.

Disproportionate impact of COVID-19 severity and mortality on hospitalized American Indian/Alaska Native patients.

Epidemiological data across the United States of America illustrate health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. However, limited information is available from prospective observational studies in hospitalized patients, particularly for American Indian or Alaska Native (AI/AN) populations. Here, we present risk factors associated with severe COVID-19 and mortality in patients (4/2020-12/2021, n = 475) at the University of New Mexico Hospital. Data were collected on patient demographics, infection duration, laboratory measures, comorbidities, treatment(s), major clinical events, and in-hospital mortality. Severe disease was defined by COVID-related intensive care unit requirements and/or death. The cohort was stratified by self-reported race/ethnicity: AI/AN (30.7%), Hispanic (47.0%), non-Hispanic White (NHW, 18.5%), and Other (4.0%, not included in statistical comparisons). Despite similar timing of infection and comparable comorbidities, admission characteristics for AI/AN patients included younger age (P = 0.02), higher invasive mechanical ventilation requirements (P = 0.0001), and laboratory values indicative of more severe disease. Throughout hospitalization, the AI/AN group also experienced elevated invasive mechanical ventilation (P < 0.0001), shock (P = 0.01), encephalopathy (P = 0.02), and severe COVID-19 (P = 0.0002), consistent with longer hospitalization (P < 0.0001). Self-reported AI/AN race/ethnicity emerged as the highest risk factor for severe COVID-19 (OR = 3.19; 95% CI = 1.70-6.01; P = 0.0003) and was a predictor of in-hospital mortality (OR = 2.35; 95% CI = 1.12-4.92; P = 0.02). Results from this study highlight the disproportionate impact of COVID-19 on hospitalized AI/AN patients, who experienced more severe illness and associated mortality, compared to Hispanic and NHW patients, even when accounting for symptom onset and comorbid conditions. These findings underscore the need for interventions and resources to address health disparities in the COVID-19 pandemic.

Local population structure of Plasmodium: impact on malaria control and elimination.

BACKGROUND: Regardless of the growing interest in detecting population structures in malarial parasites, there have been limited discussions on how to use this concept in control programmes. In such context, the effects of the parasite population structures will depend on interventions' spatial or temporal scales. This investigation explores the problem of identifying genetic markers, in this case microsatellites, to unveil Plasmodium genetic structures that could affect decisions in the context of elimination. The study was performed in a low-transmission area, which offers a good proxy to better understand problems associated with surveillance at the final stages of malaria elimination. METHODS: Plasmodium vivax samples collected in Tumeremo, Venezuela, between March 2003 and November 2004 were analysed. Since Plasmodium falciparum also circulates in many low endemic areas, P. falciparum samples from the same locality and time period were included for comparison. Plasmodium vivax samples were assayed for an original set of 25 microsatellites and P. falciparum samples were assayed for 12 microsatellites. RESULTS: Not all microsatellite loci assayed offered reliable local data. A complex temporal-cluster dynamics is found in both P. vivax and P. falciparum. Such dynamics affect the numbers and the type of microsatellites required for identifying individual parasites or parasite clusters when performing cross-sectional studies. The minimum number of microsatellites required to differentiate circulating P. vivax clusters differs from the minimum number of hyper-variable microsatellites required to distinguish individuals within these clusters. Regardless the extended number of microsatellites used in P. vivax, it was not possible to separate all individual infections. CONCLUSIONS: Molecular surveillance has great potential; however, it requires preliminary local studies in order to properly interpret the emerging patterns in the context of elimination. Clonal expansions and clusters turnovers need to be taken into account when using molecular markers. Those affect the number and type of microsatellite markers, as well as, the expected genetic patterns in the context of operational investigations. By considering the local dynamics, elimination programmes could cost-effectively use molecular markers. However, population level studies need to consider the local limitations of a given set of loci in terms of providing epidemiologically relevant information.

Differences in selective pressure on dhps and dhfr drug resistant mutations in western Kenya.

BACKGROUND: Understanding the origin and spread of mutations associated with drug resistance, especially in the context of combination therapy, will help guide strategies to halt and prevent the emergence of resistance. Unfortunately, studies have assessed these complex processes when resistance is already highly prevalent. Even further, information on the evolutionary dynamics leading to multidrug-resistant parasites is scattered and limited to areas with low or seasonal malaria transmission. This study describes the dynamics of strong selection for mutations conferring resistance against sulphadoxine-pyrimethamine (SP), a combination therapy, in western Kenya between 1992 and 1999, just before SP became first-line therapy (1999). Importantly, the study is based on longitudinal data, which allows for a comprehensive analysis that contrasts with previous cross-sectional studies carried out in other endemic regions. METHODS: This study used 236 blood samples collected between 1992 and 1999 in the Asembo Bay area of Kenya. Pyrosequencing was used to determine the alleles of dihydrofolate reductase (dhfr) and dihydropterote synthase (dhps) genes. Microsatellite alleles spanning 138 kb around dhfr and dhps, as well as, neutral markers spanning approximately 100 kb on chromosomes 2 and 3 were characterized. RESULTS: By 1992, the South-Asian dhfr triple mutant was already spreading, albeit in low frequency, in this holoendemic Kenyan population, prior to the use of SP as a first-line therapy. Additionally, dhfr triple mutant alleles that originated independently from the predominant Southeast Asian lineage were present in the sample set. Likewise, dhps double mutants were already present as early as 1992. There is evidence for soft selective sweeps of two dhfr mutant alleles and the possible emergence of a selective sweep of double mutant dhps alleles between 1992 and 1997. The longitudinal structure of the dataset allowed estimation of selection pressures on various dhfr and dhps mutants relative to each other based on a theoretical model tailored to P. falciparum. The data indicate that drug selection acted differently on the resistant alleles of dhfr and dhps, as evidenced by fitness differences. Thus a combination drug therapy such as SP, by itself, does not appear to select for "multidrug"-resistant parasites in areas with high recombination rate. CONCLUSIONS: The complexity of these observations emphasizes the importance of population-based studies to evaluate the effects of strong drug selection on Plasmodium falciparum populations.

Investigating the impact of multiple feeding attempts on mosquito dynamics via mathematical models.

A deterministic differential equation model for the dynamics of terrestrial forms of mosquito populations is studied. The model assesses the impact of multiple probing attempts by mosquitoes that quest for blood within human populations by including a waiting class for mosquitoes that failed a blood feeding attempt. The equations are derived based on the idea that the reproductive cycle of the mosquito can be viewed as a set of alternating egg laying and blood feeding outcomes realised on a directed path called the gonotrophic cycle pathway. There exists a threshold parameter, the basic offspring number for mosquitoes, whose nature is affected by the way we interpret the transitions involving the different classes on the gonotrophic cycle path. The trivial steady state for the system, which always exists, can be globally asymptomatically stable whenever the threshold parameter is less than unity. The non-trivial steady state, when it exists, is stable for a range of values of the threshold parameter but can also be driven to instability via a Hopf bifurcation. The model's output reveals that the waiting class mosquitoes do contribute positively to sustain mosquito populations as well as increase their interactions with humans via increased frequency and initial amplitude of oscillations. We conclude that to understand human-mosquito interactions, it is informative to consider multiple probing attempts; known to occur when mosquitoes quest for blood meals within human populations.

Nonsynonymous amino acid changes in the α-chain of complement component 5 influence longitudinal susceptibility to Plasmodium falciparum infections and severe malarial anemia in kenyan children.

Background: Severe malarial anemia (SMA; Hb < 5.0 g/dl) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission regions such as western Kenya. Methods: We investigated the relationship between two novel complement component 5 (C5) missense mutations [rs17216529:C>T, p(Val145Ile) and rs17610:C>T, p(Ser1310Asn)] and longitudinal outcomes of malaria in a cohort of Kenyan children (under 60 mos, n = 1,546). Molecular modeling was used to investigate the impact of the amino acid transitions on the C5 protein structure. Results: Prediction of the wild-type and mutant C5 protein structures did not reveal major changes to the overall structure. However, based on the position of the variants, subtle differences could impact on the stability of C5b. The influence of the C5 genotypes/haplotypes on the number of malaria and SMA episodes over 36 months was determined by Poisson regression modeling. Genotypic analyses revealed that inheritance of the homozygous mutant (TT) for rs17216529:C>T enhanced the risk for both malaria (incidence rate ratio, IRR = 1.144, 95%CI: 1.059-1.236, p = 0.001) and SMA (IRR = 1.627, 95%CI: 1.201-2.204, p = 0.002). In the haplotypic model, carriers of TC had increased risk of malaria (IRR = 1.068, 95%CI: 1.017-1.122, p = 0.009), while carriers of both wild-type alleles (CC) were protected against SMA (IRR = 0.679, 95%CI: 0.542-0.850, p = 0.001). Conclusion: Collectively, these findings show that the selected C5 missense mutations influence the longitudinal risk of malaria and SMA in immune-naïve children exposed to holoendemic P. falciparum transmission through a mechanism that remains to be defined.

Genetic variation in CSF2 (5q31.1) is associated with longitudinal susceptibility to pediatric malaria, severe malarial anemia, and all-cause mortality in a high-burden malaria and HIV region of Kenya.

Plasmodium falciparum infections remain among the leading causes of morbidity and mortality in holoendemic transmission areas. Located within region 5q31.1, the colony-stimulating factor 2 gene (CSF2) encodes granulocyte-macrophage colony-stimulating factor (GM-CSF), a hematopoietic growth factor that mediates host immune responses. Since the effect of CSF2 variation on malaria pathogenesis remains unreported, we investigated the impact of two genetic variants in the 5q31.1 gene region flanking CSF2:g-7032 G > A (rs168681:G > A) and CSF2:g.64544T > C (rs246835:T > C) on the rate and timing of malaria and severe malarial anemia (SMA, Hb < 5.0 g/dL) episodes over 36 months of follow-up. Children (n = 1654, aged 2-70 months) were recruited from a holoendemic P. falciparum transmission area of western Kenya. Decreased incidence rate ratio (IRR) for malaria was conferred by inheritance of the CSF2:g.64544 TC genotype (P = 0.0277) and CSF2 AC/GC diplotype (P = 0.0015). Increased IRR for malaria was observed in carriers of the CSF2 AT/GC diplotype (P = 0.0237), while the inheritance of the CSF2 AT haplotype increased the IRR for SMA (P = 0.0166). A model estimating the longitudinal risk of malaria showed decreased hazard rates among CSF2 AC haplotype carriers (P = 0.0045). Investigation of all-cause mortality revealed that inheritance of the GA genotype at CSF2:g-7032 increased the risk of mortality (P = 0.0315). Higher risk of SMA and all-cause mortality were observed in younger children (P < 0.0001 and P = 0.0015), HIV-1(+) individuals (P < 0.0001 and P < 0.0001), and carriers of HbSS (P = 0.0342 and P = 0.0019). Results from this holoendemic P. falciparum area show that variation in gene region 5q31.1 influences susceptibility to malaria, SMA, and mortality, as does age, HIV-1 status, and inheritance of HbSS.

Complement component 3 mutations alter the longitudinal risk of pediatric malaria and severe malarial anemia.

Severe malarial anemia (SMA) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission regions. To gain enhanced understanding of predisposing factors for SMA, we explored the relationship between complement component 3 (C3) missense mutations [rs2230199 (2307C>G, Arg>Gly102) and rs11569534 (34420G>A, Gly>Asp1224)], malaria, and SMA in a cohort of children (n = 1617 children) over 36 months of follow-up. Variants were selected based on their ability to impart amino acid substitutions that can alter the structure and function of C3. The 2307C>G mutation results in a basic to a polar residue change (Arg to Gly) at position 102 (ß-chain) in the macroglobulin-1 (MG1) domain, while 34420G>A elicits a polar to acidic residue change (Gly to Asp) at position 1224 (α-chain) in the thioester-containing domain. After adjusting for multiple comparisons, longitudinal analyses revealed that inheritance of the homozygous mutant (GG) at 2307 enhanced the risk of SMA (RR = 2.142, 95%CI: 1.229-3.735, P = 0.007). The haplotype containing both wild-type alleles (CG) decreased the incident risk ratio of both malaria (RR = 0.897, 95%CI: 0.828-0.972, P = 0.008) and SMA (RR = 0.617, 95%CI: 0.448-0.848, P = 0.003). Malaria incident risk ratio was also reduced in carriers of the GG (Gly102Gly1224) haplotype (RR = 0.941, 95%CI: 0.888-0.997, P = 0.040). Collectively, inheritance of the missense mutations in MG1 and thioester-containing domain influence the longitudinal risk of malaria and SMA in children exposed to intense Plasmodium falciparum transmission.

Approximations for the hitchhiking effect caused by the evolution of antimalarial-drug resistance.

An analytically feasible, deterministic model for the spread of drug resistance among human malaria parasites, which incorporates all characteristics of the complex malaria-transmission cycle was introduced by Schneider and Kim (Theor. Popul Biol, 2010). The model accounts for the fact that only a fraction of infected hosts receive drug treatment and that hosts can be co-infected by differently many parasites. Furthermore, the model also incorporates host heterogeneity. Antimalarial-drug resistance is assumed to be caused by a single locus with two alleles-a sensitive one and a resistance one. The most important result for this model is that an analytical solution for the frequencies of a linked neutral biallelic locus exists. However, the exact solution does not admit an explicit form, and cannot straightforwardly be interpreted in terms of the model parameters. Here, we establish simple approximations for the equilibrium frequency at the neutral locus. Under the assumption that the resistant allele is initially rare-the biologically most relevant assumption in this context-and that recombination is weak, the approximations become similar to the approximations in the standard hitchhiking model. However, there are crucial differences. In particular, because of the high degree of selfing among malaria parasites in their sexual phase, a genome-wide reduction of relative heterozygosity occurs if selection is sufficiently strong. It turns out that the approximations are accurate even if the recombination rates are not small and the resistant allele is initially not very rare. The main advantage of our approximations is that they are easy to interpret in terms of model parameters. Moreover, they allow to make predictions of the size of the valley of reduced heterozygosity around the selected locus for given model parameters. Reversely, for a given reduction of heterozygosity, it is possible to identify the corresponding parameters. Moreover, we will show that incorporating host heterogeneity leads to an increased hitchhiking effect.

Bias-corrected maximum-likelihood estimation of multiplicity of infection and lineage frequencies.

BACKGROUND: The UN's Sustainable Development Goals are devoted to eradicate a range of infectious diseases to achieve global well-being. These efforts require monitoring disease transmission at a level that differentiates between pathogen variants at the genetic/molecular level. In fact, the advantages of genetic (molecular) measures like multiplicity of infection (MOI) over traditional metrics, e.g., R0, are being increasingly recognized. MOI refers to the presence of multiple pathogen variants within an infection due to multiple infective contacts. Maximum-likelihood (ML) methods have been proposed to derive MOI and pathogen-lineage frequencies from molecular data. However, these methods are biased. METHODS AND FINDINGS: Based on a single molecular marker, we derive a bias-corrected ML estimator for MOI and pathogen-lineage frequencies. We further improve these estimators by heuristical adjustments that compensate shortcomings in the derivation of the bias correction, which implicitly assumes that data lies in the interior of the observational space. The finite sample properties of the different variants of the bias-corrected estimators are investigated by a systematic simulation study. In particular, we investigate the performance of the estimator in terms of bias, variance, and robustness against model violations. The corrections successfully remove bias except for extreme parameters that likely yield uninformative data, which cannot sustain accurate parameter estimation. Heuristic adjustments further improve the bias correction, particularly for small sample sizes. The bias corrections also reduce the estimators' variances, which coincide with the Cramér-Rao lower bound. The estimators are reasonably robust against model violations. CONCLUSIONS: Applying bias corrections can substantially improve the quality of MOI estimates, particularly in areas of low as well as areas of high transmission-in both cases estimates tend to be biased. The bias-corrected estimators are (almost) unbiased and their variance coincides with the Cramér-Rao lower bound, suggesting that no further improvements are possible unless additional information is provided. Additional information can be obtained by combining data from several molecular markers, or by including information that allows stratifying the data into heterogeneous groups.