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Plasmodium Cost of Resistance and Life Stage Development within the Mosquito Vector

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Hundreds of thousands of people die annually from malaria; a protozoan of the genus Plasmodium is responsible for this mortality. The Plasmodium parasite undergoes several life stages within the mosquito vector, the transition between which require passage across the lumen

Hundreds of thousands of people die annually from malaria; a protozoan of the genus Plasmodium is responsible for this mortality. The Plasmodium parasite undergoes several life stages within the mosquito vector, the transition between which require passage across the lumen of the mosquito midgut. It has been observed that in about 15% of parasites that develop ookinetes in the mosquito abdomen, sporozoites never develop in the salivary glands, indicating that passage across the midgut lumen is a significant barrier in parasite development (Gamage-Mendis et al., 1993). We aim to investigate a possible correlation between passage through the midgut lumen and drug-resistance trends in Plasmodium falciparum parasites. This study contains a total of 1024 Anopheles mosquitoes: 187 Anopheles gambiae and 837 Anopheles funestus samples collected in high malaria transmission areas of Mozambique between March and June of 2016. Sanger sequencing will be used to determine the prevalence of known resistance alleles for anti-malarial drugs: chloroquine resistance transporter (pfcrt), multidrug resistance (pfmdr1) gene, dihydropteroate synthase (pfdhps) and dihydrofolate reductase (pfdhfr). We compare prevalence of resistance between abdomen and head/thorax in order to determine whether drug resistant parasites are disproportionately hindered during their passage through the midgut lumen. A statistically significant difference between resistance alleles in the two studied body sections supports the efficacy of new anti-malarial gene surveillance strategies in areas of high malaria transmission.

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2021-05

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Aedes aegypti Thermal Choice Experiment

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The non-native mosquito Aedes aegypti has become a common nuisance in Maricopa county. Associated with human settlement, Ae. aegypti is known to reproduce in standing water sources both indoors and outdoors, within vessels such as tires, flowerpots, and neglected swimming

The non-native mosquito Aedes aegypti has become a common nuisance in Maricopa county. Associated with human settlement, Ae. aegypti is known to reproduce in standing water sources both indoors and outdoors, within vessels such as tires, flowerpots, and neglected swimming pools (Jansen & Beebe, 2010). Ae. aegypti and the related Ae. albopictus are the primary vectors of the arboviral diseases chikungunya, Zika, yellow fever and dengue. Ae. aegypti tends to blood feed multiple times per gonotrophic cycle (cycle of feeding and egg laying) which, alongside a preference for human blood and close association with human habitation, contributes to an increased risk of Ae. aegypti borne virus transmission (Scott & Takken, 2012). Between 2010-2017, 153 travel-associated cases of dengue were reported in the whole of Arizona (Rivera et al., 2020); while there have been no documented locally transmitted cases of Aedes borne diseases in Maricopa county, there are no apparent reasons why local transmission can’t occur in the future via local Aedes aegypti mosquitoes infected after feeding from travelling viremic hosts. Incidents of local dengue transmission in New York (Rivera et al., 2020) and Barcelona (European Center for Disease Control [ECDC], 2019) suggest that outbreaks of Aedes borne arbovirus’ can occur in regions more temperate than the current endemic range of Aedes borne diseases. Further, while the fact that Ae. aegypti eggs have a high mortality rate when exposed to cold temperatures limits the ability for Ae aegypti to establish stable breeding populations in temperate climates (Thomas, Obermayr, Fischer, Kreyling, & Beierkuhnlein, 2012), global increases in temperature will expand the possible ranges of Ae aegypti and Aedes borne diseases.

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2020-05

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Quantifying the Evolution of Fluconazole Resistance in S. Cerevisiae Using Molecular Barcodes

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One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it

One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.

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2021-05