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1.
Sci Immunol ; 7(67): eabk3070, 2022 01 21.
Artículo en Inglés | MEDLINE | ID: mdl-34793243

RESUMEN

Effective presentation of antigens by human leukocyte antigen (HLA) class I molecules to CD8+ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multiomic technology to generate a unified ex vivo characterization of the CD8+ T cell response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across four major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCRα/ß sequence diversity, and the utilization of pre-existing SARS-CoV-2-reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations notably influence the CD8+ T cell repertoire shape and utilization of immune recall upon SARS-CoV-2 infection.


Asunto(s)
Alelos , Linfocitos T CD8-positivos/inmunología , COVID-19 , Antígenos de Histocompatibilidad Clase I/inmunología , Células T de Memoria/inmunología , Receptores de Antígenos de Linfocitos T alfa-beta , SARS-CoV-2/inmunología , COVID-19/genética , COVID-19/inmunología , Antígenos de Histocompatibilidad Clase I/genética , Humanos , Receptores de Antígenos de Linfocitos T alfa-beta/genética , Receptores de Antígenos de Linfocitos T alfa-beta/inmunología , SARS-CoV-2/genética
2.
Ecol Evol ; 8(11): 5336-5354, 2018 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-29938057

RESUMEN

Tsetse flies (genus Glossina) are the only vector for the parasitic trypanosomes responsible for sleeping sickness and nagana across sub-Saharan Africa. In Uganda, the tsetse fly Glossina fuscipes fuscipes is responsible for transmission of the parasite in 90% of sleeping sickness cases, and co-occurrence of both forms of human-infective trypanosomes makes vector control a priority. We use population genetic data from 38 samples from northern Uganda in a novel methodological pipeline that integrates genetic data, remotely sensed environmental data, and hundreds of field-survey observations. This methodological pipeline identifies isolated habitat by first identifying environmental parameters correlated with genetic differentiation, second, predicting spatial connectivity using field-survey observations and the most predictive environmental parameter(s), and third, overlaying the connectivity surface onto a habitat suitability map. Results from this pipeline indicated that net photosynthesis was the strongest predictor of genetic differentiation in G. f. fuscipes in northern Uganda. The resulting connectivity surface identified a large area of well-connected habitat in northwestern Uganda, and twenty-four isolated patches on the northeastern margin of the G. f. fuscipes distribution. We tested this novel methodological pipeline by completing an ad hoc sample and genetic screen of G. f. fuscipes samples from a model-predicted isolated patch, and evaluated whether the ad hoc sample was in fact as genetically isolated as predicted. Results indicated that genetic isolation of the ad hoc sample was as genetically isolated as predicted, with differentiation well above estimates made in samples from within well-connected habitat separated by similar geographic distances. This work has important practical implications for the control of tsetse and other disease vectors, because it provides a way to identify isolated populations where it will be safer and easier to implement vector control and that should be prioritized as study sites during the development and improvement of vector control methods.

3.
PLoS Negl Trop Dis ; 11(4): e0005485, 2017 04.
Artículo en Inglés | MEDLINE | ID: mdl-28453513

RESUMEN

Uganda is the only country where the chronic and acute forms of human African Trypanosomiasis (HAT) or sleeping sickness both occur and are separated by < 100 km in areas north of Lake Kyoga. In Uganda, Glossina fuscipes fuscipes is the main vector of the Trypanosoma parasites responsible for these diseases as well for the animal African Trypanosomiasis (AAT), or Nagana. We used highly polymorphic microsatellite loci and a mitochondrial DNA (mtDNA) marker to provide fine scale spatial resolution of genetic structure of G. f. fuscipes from 42 sampling sites from the northern region of Uganda where a merger of the two disease belts is feared. Based on microsatellite analyses, we found that G. f. fuscipes in northern Uganda are structured into three distinct genetic clusters with varying degrees of interconnectivity among them. Based on genetic assignment and spatial location, we grouped the sampling sites into four genetic units corresponding to northwestern Uganda in the Albert Nile drainage, northeastern Uganda in the Lake Kyoga drainage, western Uganda in the Victoria Nile drainage, and a transition zone between the two northern genetic clusters characterized by high level of genetic admixture. An analysis using HYBRIDLAB supported a hybrid swarm model as most consistent with tsetse genotypes in these admixed samples. Results of mtDNA analyses revealed the presence of 30 haplotypes representing three main haplogroups, whose location broadly overlaps with the microsatellite defined clusters. Migration analyses based on microsatellites point to moderate migration among the northern units located in the Albert Nile, Achwa River, Okole River, and Lake Kyoga drainages, but not between the northern units and the Victoria Nile drainage in the west. Effective population size estimates were variable with low to moderate sizes in most populations and with evidence of recent population bottlenecks, especially in the northeast unit of the Lake Kyoga drainage. Our microsatellite and mtDNA based analyses indicate that G. f. fuscipes movement along the Achwa and Okole rivers may facilitate northwest expansion of the Rhodesiense disease belt in Uganda. We identified tsetse migration corridors and recommend a rolling carpet approach from south of Lake Kyoga northward to minimize disease dispersal and prevent vector re-colonization. Additionally, our findings highlight the need for continuing tsetse monitoring efforts during and after control.


Asunto(s)
Variación Genética , Control de Insectos/métodos , Insectos Vectores , Filogeografía , Moscas Tse-Tse/clasificación , Moscas Tse-Tse/genética , Animales , Análisis por Conglomerados , ADN Mitocondrial/química , ADN Mitocondrial/genética , Femenino , Técnicas de Genotipaje , Haplotipos , Masculino , Repeticiones de Microsatélite , Análisis de Secuencia de ADN , Análisis Espacial , Uganda
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