
{"id":179,"date":"2017-12-01T09:03:06","date_gmt":"2017-12-01T14:03:06","guid":{"rendered":"http:\/\/pages.charlotte.edu\/elo\/?page_id=179"},"modified":"2019-02-21T19:40:45","modified_gmt":"2019-02-22T00:40:45","slug":"research","status":"publish","type":"page","link":"https:\/\/pages.charlotte.edu\/elo\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<h2><strong><span style=\"text-decoration: underline\">Study Sites<\/span><\/strong><\/h2>\n<h2><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2019\/02\/AfricaSites-1.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-501 aligncenter\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2019\/02\/AfricaSites-1-244x300.jpg\" alt=\"\" width=\"342\" height=\"421\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2019\/02\/AfricaSites-1-244x300.jpg 244w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2019\/02\/AfricaSites-1-768x944.jpg 768w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2019\/02\/AfricaSites-1-833x1024.jpg 833w\" sizes=\"auto, (max-width: 342px) 100vw, 342px\" \/><\/a><\/h2>\n<h2><strong>I. Transmission dynamics of malaria parasites<\/strong><\/h2>\n<p>+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<p>Human movements and dispersal of vector mosquitoes allow spread of malaria and impact genetic structure of the parasite populations. Understanding the relatedness among\u00a0<em>Plasmodium<\/em>\u00a0populations and how such influenced by geographical and environmental features is vital. The combined approach of population genomics and landscape genetics allows us to examine the role of spatial variation and local adaptation in disease transmission. Knowledge of the source\/sink of infections and the magnitude of disease spread are keys to make decision and implement control measures effectively in the most malarious areas.<\/p>\n<div>\n<p style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/landscape-plot-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-144\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/landscape-plot-2-300x222.jpg\" alt=\"\" width=\"392\" height=\"290\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/landscape-plot-2-300x222.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/landscape-plot-2.jpg 536w\" sizes=\"auto, (max-width: 392px) 100vw, 392px\" \/><\/a><\/p>\n<p style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Landscape genetic plot showing the level of gene flow among\u00a0<em>P. vivax<\/em>\u00a0populations in the Myanmar-China border area.<\/strong><\/span><\/p>\n<\/div>\n<div id=\"attachment_146\" class=\"wp-caption aligncenter\" style=\"width: 508px\">\n<h5 style=\"text-align: center\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-146\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/barplot-2-300x114.jpg\" alt=\"\" width=\"508\" height=\"193\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/barplot-2-300x114.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/barplot-2.jpg 713w\" sizes=\"auto, (max-width: 508px) 100vw, 508px\" \/><\/h5>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Bayesian inferences of genetic\u00a0clusters by STRUCTURE among\u00a0<em>P. vivax<\/em>\u00a0samples in Myanmar.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_142\" class=\"wp-caption aligncenter\" style=\"width: 563px\">\n<p style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/migration-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-142\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/migration-2-300x121.jpg\" alt=\"\" width=\"563\" height=\"227\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/migration-2-300x121.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/migration-2-768x310.jpg 768w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/migration-2.jpg 922w\" sizes=\"auto, (max-width: 563px) 100vw, 563px\" \/><\/a><\/p>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Migratory pathways and rates of\u00a0<em>Plasmodium falciparum<\/em>\u00a0and\u00a0<em>P. vivax<\/em>\u00a0in Ethiopia based on Migrate-N and BayesAss.<\/strong><\/span><\/h5>\n<\/div>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<div id=\"attachment_142\" class=\"wp-caption aligncenter\">\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<p><strong style=\"font-size: 1.4em\">II. Molecular epidemiology of malaria<\/strong><\/p>\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<\/div>\n<p>Emergence of antimalarial drug resistance and persistence of submicroscopic parasite reservoirs are apparent hurdles to malaria reduction and elimination in many African countries. These issues require close monitoring and effective resolution. One aspect of my research is to examine demographic factors of malaria prevalence, transmission intensity, disease severity, as well as bio-markers related to antimalarial drug resistance.\u00a0This information will contribute to assessing and monitoring the disease burden in places where people are still battling or at high risk of malaria.<\/p>\n<div id=\"attachment_150\" class=\"wp-caption aligncenter\" style=\"width: 435px\">\n<p><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Resistance-plot.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-150 aligncenter\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Resistance-plot-300x226.jpg\" alt=\"\" width=\"435\" height=\"328\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Resistance-plot-300x226.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Resistance-plot-768x579.jpg 768w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Resistance-plot.jpg 914w\" sizes=\"auto, (max-width: 435px) 100vw, 435px\" \/><\/a><\/p>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Antimalarial treatment policy in Ethiopia and mutation prevalence of antimalarial resistance genes in\u00a0<em>Plasmodium falciparum<\/em>.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_152\" class=\"wp-caption aligncenter\" style=\"text-align: center;width: 514px\">\n<p><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Prevalence-plot-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-152\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Prevalence-plot-2-300x178.jpg\" alt=\"\" width=\"514\" height=\"305\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Prevalence-plot-2-300x178.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Prevalence-plot-2.jpg 743w\" sizes=\"auto, (max-width: 514px) 100vw, 514px\" \/><\/a><\/p>\n<h5><span style=\"color: #ffffff\"><strong><em>Plasmodium malariae<\/em>\u00a0prevalence and circumsporozoite protein gene diversity in Kenya, 2014 and 2015.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_154\" class=\"wp-caption aligncenter\" style=\"width: 359px\">\n<p style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/age-plot-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-154\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/age-plot-2-300x182.jpg\" alt=\"\" width=\"359\" height=\"218\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/age-plot-2-300x182.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/age-plot-2.jpg 766w\" sizes=\"auto, (max-width: 359px) 100vw, 359px\" \/><\/a><\/p>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Histogram showing the mean malaria prevalence rate of the three age groups (under 5, aged 5\u201314, and over 14) in the lowlands and highlands of Western Kenya.<\/strong><\/span><\/h5>\n<\/div>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<h2>III. Evolution of parasite-host interactions<\/h2>\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<p>Malaria is caused by the invasion of\u00a0<em>Plasmodium<\/em>\u00a0into human red blood cell and subsequently disrupts its normal function. RBC invasion involves multiple interactions between parasite ligand and host receptor proteins. Although a number of invasion ligands have been recently documented, in very few cases have their functional significance and red blood cell receptors been identified, especially in\u00a0<em>P. vivax<\/em>. It is always possible that parasites evolve novel RBC invasion pathways. This could influence the efficacy of existing preventive vaccines and elevate malaria burden at a global level. My research explores molecular mechanisms of parasite invasion with the goal to identify key RBC binding proteins.<\/p>\n<div id=\"attachment_158\" class=\"wp-caption aligncenter\" style=\"width: 370px\">\n<h5><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-158 aligncenter\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/duffy-vivax-1-270x300.jpg\" alt=\"\" width=\"370\" height=\"411\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/duffy-vivax-1-270x300.jpg 270w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/duffy-vivax-1.jpg 564w\" sizes=\"auto, (max-width: 370px) 100vw, 370px\" \/> <span style=\"color: #ffffff\"><strong>Detection of\u00a0<em>P. vivax<\/em>\u00a0infection in Duffy-negative Ethiopians by microscopy and PCR method.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_160\" class=\"wp-caption alignnone\" style=\"text-align: center;width: 763px\">\n<p style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/qPCR-plot-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-160\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/qPCR-plot-2-300x104.jpg\" alt=\"\" width=\"763\" height=\"265\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/qPCR-plot-2-300x104.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/qPCR-plot-2.jpg 935w\" sizes=\"auto, (max-width: 763px) 100vw, 763px\" \/><\/a><\/p>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>High copy number of PvDBP observed in\u00a0<em>Plasmodium vivax<\/em>\u00a0from Duffy negative patients in Ethiopia based on quantitative real-time PCR.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_156\" class=\"wp-caption aligncenter\" style=\"width: 365px\">\n<p style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-4.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-156\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-4-300x291.jpg\" alt=\"\" width=\"365\" height=\"354\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-4-300x291.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-4.jpg 588w\" sizes=\"auto, (max-width: 365px) 100vw, 365px\" \/><\/a><\/p>\n<h5 style=\"text-align: center\"><span style=\"color: #ffffff\"><strong>Maximum likelihood tree of\u00a0<em>Plasmodium vivax<\/em>\u00a0isolates that have different PvDBP copy number.<\/strong><\/span><\/h5>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p class=\"wp-caption-text\" style=\"text-align: center\">\n<\/div>\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<h2>IV. Phylogeny of malaria parasites and vectors<\/h2>\n<p>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++<\/p>\n<p>Genetic relationships among biological organisms take into account the mutational changes occurred over time as well as migration rates. My research examines mutational and genotypic variation within parasite species and explores genetic relatedness at the spatial and temporal scales to elucidate ancestral origins and character changes. This involves the use of geo-reference tools to model geological changes with respect to species movement and distribution over time. This information sheds light on the role and impact of long-distance migration and adaptive radiation on species diversity and population structure.<\/p>\n<div id=\"attachment_172\" class=\"wp-caption aligncenter\" style=\"width: 391px\">\n<h5><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-172 aligncenter\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-1-1-300x229.jpg\" alt=\"\" width=\"391\" height=\"298\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-1-1-300x229.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-1-1.jpg 692w\" sizes=\"auto, (max-width: 391px) 100vw, 391px\" \/><span style=\"color: #ffffff\"><strong>Maximum-likelihood analyses of circumsporozoite protein gene (<em>csp<\/em>) sequences of\u00a0<em>Plasmodium malariae<\/em>\u00a0and global dist<\/strong><strong>ribution of t<\/strong><strong>he samples.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_170\" class=\"wp-caption aligncenter\" style=\"text-align: center;width: 390px\">\n<p><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-170\" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-2-300x231.jpg\" alt=\"\" width=\"390\" height=\"301\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-2-300x231.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-2-768x591.jpg 768w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/Phylogeny-2.jpg 771w\" sizes=\"auto, (max-width: 390px) 100vw, 390px\" \/><\/a><\/p>\n<h5><span style=\"color: #ffffff\"><strong>Neighbor-joining trees showing the genetic relatedness among\u00a0<em>Plasmodium falciparum<\/em>\u00a0and\u00a0<em>P. vivax<\/em>\u00a0samples in Ethiopia.<\/strong><\/span><\/h5>\n<\/div>\n<div id=\"attachment_169\" class=\"wp-caption aligncenter\" style=\"width: 377px\">\n<h5 style=\"text-align: center\"><a href=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/haplotype-network-2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-169 \" src=\"http:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/haplotype-network-2-300x246.jpg\" alt=\"\" width=\"377\" height=\"309\" srcset=\"https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/haplotype-network-2-300x246.jpg 300w, https:\/\/pages.charlotte.edu\/elo\/wp-content\/uploads\/sites\/1210\/2012\/10\/haplotype-network-2.jpg 599w\" sizes=\"auto, (max-width: 377px) 100vw, 377px\" \/><\/a><span style=\"color: #ffffff\"><strong>Phylogenetic network of mitochondrial haplotypes of CO1 gene in\u00a0<em>Aedes albopictus<\/em>\u00a0around the world.<\/strong><\/span><\/h5>\n<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Study Sites I. Transmission dynamics of malaria parasites +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Human movements and dispersal of vector mosquitoes allow spread of malaria and impact genetic structure of the parasite populations. Understanding the relatedness among\u00a0Plasmodium\u00a0populations and how such influenced by geographical and environmental features is vital. The combined approach of population genomics and landscape genetics allows us to [&hellip;]<\/p>\n","protected":false},"author":1132,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-179","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/pages\/179","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/users\/1132"}],"replies":[{"embeddable":true,"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/comments?post=179"}],"version-history":[{"count":53,"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/pages\/179\/revisions"}],"predecessor-version":[{"id":504,"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/pages\/179\/revisions\/504"}],"wp:attachment":[{"href":"https:\/\/pages.charlotte.edu\/elo\/wp-json\/wp\/v2\/media?parent=179"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}