Tracking the flow of malaria parasites and drug resistance within the DRC and across its borders

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ABSTRACT Malaria​ ​remains​ ​endemic​ ​in​ ​sub-Saharan​ ​Africa​ ​in​ ​large​ ​part​ ​due​ ​to​ ​continued​ ​evolution​ ​and​ ​spread​ ​of​ ​drug resistance​ ​which​ ​undermines​ ​ongoing​ ​large-scale​ ​control​ ​and​ ​elimination​ ​efforts.​ ​We​ ​will​ ​leverage high-throughput​ ​genotyping​ ​of​ ​parasites​ ​using​ ​a​ ​state-of-the-art​ ​panel​ ​of​ ​molecular​ ​inversion​ ​probes​ ​(MIPs)​ ​for targeted​ ​sequencing​ ​of​ ​thousands​ ​of​ ​resistance​ ​and​ ​neutral​ ​loci​ ​across​ ​thousands​ ​of​ ​infections​ ​covering​ ​the entire​ ​Democratic​ ​Republic​ ​of​ ​Congo​ ​(DRC)​ ​and​ ​select​ ​areas​ ​in​ ​bordering​ ​countries.​ ​This​ ​will​ ​provide​ ​us​ ​a​ ​map with​ ​an​ ​unprecedented​ ​scale​ ​and​ ​resolution​ ​to​ ​define​ ​the​ ​evolution​ ​and​ ​spread​ ​of​ ​antimalarial​ ​resistance mutations.​ ​In​ ​this​ ​project,​ ​we​ ​will​ ​first​ ​develop​ ​our​ ​genotyping​ ​panel​ ​which​ ​should​ ​provide​ ​a​ ​high-resolution​ ​tool for​ ​studying​ ​all​ ​known​ ​drug​ ​resistance​ ​loci​ ​and​ ​general​ ​parasite​ ​population​ ​structure​ ​in​ ​this​ ​and​ ​other​ ​settings. Applying​ ​this​ ​to​ ​well​ ​annotated​ ​samples​ ​from​ ​across​ ​the​ ​DRC​ ​and​ ​bordering​ ​countries,​ ​we​ ​will​ ​define​ ​the prevalence​ ​of​ ​drug​ ​resistance​ ​mutations​ ​and​ ​define​ ​them​ ​based​ ​on​ ​their​ ​genetic​ ​haplotypes​ ​which​ ​act​ ​as​ ​a unique​ ​fingerprints.​ ​We​ ​will​ ​then​ ​map​ ​these​ ​drug​ ​resistance​ ​haplotypes​ ​and​ ​study​ ​their​ ​spread​ ​and​ ​spatial associations​ ​and​ ​further​ ​examine​ ​their​ ​epidemiologic​ ​associations​ ​and​ ​interactions.​ ​Onto​ ​this​ ​detailed​ ​spatial map,​ ​we​ ​will​ ​​ ​examine​ ​specific​ ​locales​ ​of​ ​interest​ ​for​ ​temporal​ ​changes.​ ​​ ​These​ ​focal​ ​regions​ ​in​ ​the​ ​DRC represent​ ​diverse​ ​ecologic​ ​and​ ​demographic​ ​features​ ​that​ ​likely​ ​impact​ ​resistance​ ​spread​ ​and​ ​evolution including​ ​areas​ ​with​ ​minimal​ ​health​ ​care​ ​infrastructure​ ​and​ ​ongoing​ ​regions​ ​of​ ​conflict.​ ​Our​ ​final​ ​work​ ​will​ ​be​ ​to apply​ ​more​ ​sophisticated​ ​models​ ​to​ ​the​ ​rich​ ​sequence​ ​data​ ​in​ ​order​ ​to​ ​estimate​ ​the​ ​flow​ ​of​ ​parasites​ ​and resistance​ ​mutations​ ​within​ ​and​ ​between​ ​the​ ​DRC.​ ​This​ ​includes​ ​the​ ​development​ ​of​ ​new​ ​​ ​population​ ​structure models​ ​(MALECOT)​ ​incorporating​ ​parasite​ ​infections​ ​that​ ​have​ ​multiple​ ​strains​ ​allowing​ ​for​ ​a​ ​better understanding​ ​of​ ​the​ ​full​ ​dataset​ ​as​ ​in​ ​polyclonal​ ​infections​ ​are​ ​often​ ​the​ ​majority​ ​in​ ​endemic​ ​African​ ​countries. This​ ​model​ ​should​ ​be​ ​broadly​ ​applicable​ ​to​ ​other​ ​studies​ ​of​ ​malaria​ ​or​ ​infections​ ​with​ ​mixed​ ​strains.​ ​We​ ​will also​ ​leverage​ ​​ ​spatially​ ​explicit​ ​models​ ​to​ ​define​ ​general​ ​parasite​ ​flow​ ​in​ ​both​ ​relative​ ​and​ ​absolute​ ​terms comparing​ ​and​ ​contrasting​ ​to​ ​the​ ​flow​ ​of​ ​resistant​ ​parasites.​ ​This​ ​work​ ​will​ ​provide​ ​the​ ​patterns​ ​of​ ​general​ ​gene flow​ ​and​ ​barriers​ ​on​ ​the​ ​spread​ ​of​ ​specific​ ​drug​ ​resistance​ ​alleles​ ​and​ ​haplotypes.​ ​In​ ​summary,​ ​not​ ​only​ ​will this​ ​project​ ​enhance​ ​our​ ​understanding​ ​of​ ​malaria​ ​landscape​ ​genetics​ ​and​ ​the​ ​evolution​ ​and​ ​spread​ ​of antimalarial​ ​resistance,​ ​it​ ​will​ ​provide​ ​tools​ ​and​ ​analysis​ ​framework​ ​for​ ​improving​ ​public​ ​health​ ​interventions that​ ​will​ ​directly​ ​inform​ ​the​ ​DRC​ ​National​ ​Malaria​ ​Control​ ​Program.