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Fola AA, He Q, Xie S, Thimmapuram J, Bhide KP, Dorman J, Ciubotariu II, Mwenda MC, Mambwe B, Mulube C, Hawela M, Norris DE, Moss WJ, Bridges DJ, Carpi G. Genomics reveals heterogeneous Plasmodium falciparum transmission and selection signals in Zambia. COMMUNICATIONS MEDICINE 2024; 4:67. [PMID: 38582941 PMCID: PMC10998850 DOI: 10.1038/s43856-024-00498-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 03/28/2024] [Indexed: 04/08/2024] Open
Abstract
BACKGROUND Genomic surveillance is crucial for monitoring malaria transmission and understanding parasite adaptation to interventions. Zambia lacks prior nationwide efforts in malaria genomic surveillance among African countries. METHODS We conducted genomic surveillance of Plasmodium falciparum parasites from the 2018 Malaria Indicator Survey in Zambia, a nationally representative household survey of children under five years of age. We whole-genome sequenced and analyzed 241 P. falciparum genomes from regions with varying levels of malaria transmission across Zambia and estimated genetic metrics that are informative about transmission intensity, genetic relatedness between parasites, and selection. RESULTS We provide genomic evidence of widespread within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in Zambia. Our analysis reveals country-level clustering of parasites from Zambia and neighboring regions, with distinct separation in West Africa. Within Zambia, identity by descent (IBD) relatedness analysis uncovers local spatial clustering and rare cases of long-distance sharing of closely related parasite pairs. Genomic regions with large shared IBD segments and strong positive selection signatures implicate genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Furthermore, differences in selection signatures, including drug resistance loci, are observed between eastern and western Zambian parasite populations, suggesting variable transmission intensity and ongoing drug pressure. CONCLUSIONS Our findings enhance our understanding of nationwide P. falciparum transmission in Zambia, establishing a baseline for analyzing parasite genetic metrics as they vary over time and space. These insights highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.
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Affiliation(s)
- Abebe A Fola
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Qixin He
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Shaojun Xie
- Bioinformatics Core, Purdue University, Purdue University, West Lafayette, IN, USA
| | - Jyothi Thimmapuram
- Bioinformatics Core, Purdue University, Purdue University, West Lafayette, IN, USA
| | - Ketaki P Bhide
- Bioinformatics Core, Purdue University, Purdue University, West Lafayette, IN, USA
| | - Jack Dorman
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Ilinca I Ciubotariu
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Mulenga C Mwenda
- PATH-MACEPA, National Malaria Elimination Centre, Lusaka, Zambia
| | - Brenda Mambwe
- PATH-MACEPA, National Malaria Elimination Centre, Lusaka, Zambia
| | - Conceptor Mulube
- PATH-MACEPA, National Malaria Elimination Centre, Lusaka, Zambia
| | - Moonga Hawela
- PATH-MACEPA, National Malaria Elimination Centre, Lusaka, Zambia
| | - Douglas E Norris
- The Johns Hopkins Malaria Research Institute, W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - William J Moss
- The Johns Hopkins Malaria Research Institute, W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Giovanna Carpi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
- The Johns Hopkins Malaria Research Institute, W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Purdue Institute for Inflammation, Immunology, & Infectious Disease, Purdue University, West Lafayette, IN, USA.
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2
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Targeted Amplicon Deep Sequencing for Monitoring Antimalarial Resistance Markers in Western Kenya. Antimicrob Agents Chemother 2022; 66:e0194521. [PMID: 35266823 PMCID: PMC9017353 DOI: 10.1128/aac.01945-21] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Molecular surveillance of Plasmodium falciparum parasites is important to track emerging and new mutations and trends in established mutations and should serve as an early warning system for antimalarial resistance. Dried blood spots were obtained from a Plasmodium falciparum malaria survey in school children conducted across eight counties in western Kenya in 2019. Real-time PCR identified 500 P. falciparum-positive samples that were amplified at five drug resistance loci for targeted amplicon deep sequencing (TADS). The absence of important kelch 13 mutations was similar to previous findings in Kenya pre-2019, and low-frequency mutations were observed in codons 569 and 578. The chloroquine resistance transporter gene codons 76 and 145 were wild type, indicating that the parasites were chloroquine and piperaquine sensitive, respectively. The multidrug resistance gene 1 haplotypes based on codons 86, 184, and 199 were predominantly present in mixed infections with haplotypes NYT and NFT, driven by the absence of chloroquine pressure and the use of lumefantrine, respectively. The sulfadoxine-pyrimethamine resistance profile was a “superresistant” combination of triple mutations in both Pfdhfr (51I 59R 108N) and Pfdhps (436H 437G 540E), rendering sulfadoxine-pyrimethamine ineffective. TADS highlighted the low-frequency variants, allowing the early identification of new mutations, Pfmdr1 codon 199S and Pfdhfr codon 85I and emerging 164L mutations. The added value of TADS is its accuracy in identifying mixed-genotype infections and for high-throughput monitoring of antimalarial resistance markers.
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Briggs J, Kuchta A, Murphy M, Tessema S, Arinaitwe E, Rek J, Chen A, Nankabirwa JI, Drakeley C, Smith D, Bousema T, Kamya M, Rodriguez-Barraquer I, Staedke S, Dorsey G, Rosenthal PJ, Greenhouse B. Within-household clustering of genetically related Plasmodium falciparum infections in a moderate transmission area of Uganda. Malar J 2021; 20:68. [PMID: 33531029 PMCID: PMC8042884 DOI: 10.1186/s12936-021-03603-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 01/22/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Evaluation of genetic relatedness of malaria parasites is a useful tool for understanding transmission patterns, but patterns are not easily detectable in areas with moderate to high malaria transmission. To evaluate the feasibility of detecting genetic relatedness in a moderate malaria transmission setting, relatedness of Plasmodium falciparum infections was measured in cohort participants from randomly selected households in the Kihihi sub-county of Uganda (annual entomological inoculation rate of 27 infectious bites per person). METHODS All infections detected via microscopy or Plasmodium-specific loop mediated isothermal amplification from passive and active case detection during August 2011-March 2012 were genotyped at 26 microsatellite loci, providing data for 349 samples from 230 participants living in 80 households. Pairwise genetic relatedness was calculated using identity by state (IBS). RESULTS As expected, genetic diversity was high (mean heterozygosity [He] = 0.73), and the majority (76.5 %) of samples were polyclonal. Despite the high genetic diversity, fine-scale population structure was detectable, with significant spatiotemporal clustering of highly related infections. Although the difference in malaria incidence between households at higher (mean 1127 metres) versus lower elevation (mean 1015 metres) was modest (1.4 malaria cases per person-year vs. 1.9 per person-year, respectively), there was a significant difference in multiplicity of infection (2.2 vs. 2.6, p = 0.008) and, more strikingly, a higher proportion of highly related infections within households (6.3 % vs. 0.9 %, p = 0.0005) at higher elevation compared to lower elevation. CONCLUSIONS Genetic data from a relatively small number of diverse, multiallelic loci reflected fine scale patterns of malaria transmission. Given the increasing interest in applying genetic data to augment malaria surveillance, this study provides evidence that genetic data can be used to inform transmission patterns at local spatial scales even in moderate transmission areas.
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Affiliation(s)
- Jessica Briggs
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
| | - Alison Kuchta
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Max Murphy
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Sofonias Tessema
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - John Rek
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | - Anna Chen
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Joaniter I Nankabirwa
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Chris Drakeley
- Department of Immunology and Infection, London School of Hygiene and Tropical Medicine, London, UK
| | - David Smith
- Institute for Health Metrics & Evaluation, University of Washington, Seattle, WA, USA
| | - Teun Bousema
- Department of Medical Microbiology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Moses Kamya
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | | | - Sarah Staedke
- Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK
| | - Grant Dorsey
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Philip J Rosenthal
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Bryan Greenhouse
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
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4
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Watson OJ, Okell LC, Hellewell J, Slater HC, Unwin HJT, Omedo I, Bejon P, Snow RW, Noor AM, Rockett K, Hubbart C, Nankabirwa JI, Greenhouse B, Chang HH, Ghani AC, Verity R. Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling. Mol Biol Evol 2021; 38:274-289. [PMID: 32898225 PMCID: PMC7783189 DOI: 10.1093/molbev/msaa225] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.
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Affiliation(s)
- Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Joel Hellewell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Hannah C Slater
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Irene Omedo
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
| | - Philip Bejon
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya
| | - Robert W Snow
- Population Health Unit, Kenya Medical Research Institute—Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | | | - Kirk Rockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Christina Hubbart
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Joaniter I Nankabirwa
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Makerere University College of Health Sciences, Kampala, Uganda
| | - Bryan Greenhouse
- Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Hsiao-Han Chang
- Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, MA
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
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5
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Taylor AR, Echeverry DF, Anderson TJC, Neafsey DE, Buckee CO. Identity-by-descent with uncertainty characterises connectivity of Plasmodium falciparum populations on the Colombian-Pacific coast. PLoS Genet 2020; 16:e1009101. [PMID: 33196661 PMCID: PMC7704048 DOI: 10.1371/journal.pgen.1009101] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 11/30/2020] [Accepted: 09/08/2020] [Indexed: 01/09/2023] Open
Abstract
Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. Fractions of highly-related sample pairs (whose classification using a threshold accounts for uncertainty) were greater within cities versus between. However, based on both highly-related fractions and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with transmission events involving parasites from five clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this hypothesis. For the first time in malaria epidemiology (and to our knowledge in ecological and epidemiological studies more generally), we account for uncertainty around estimated relatedness (an important consideration for studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use threshold-free methods to compare parasite populations and identify clonal components. Threshold-free methods are especially important in analyses of malaria parasites and other recombining organisms with mixed mating systems where thresholds do not have clear interpretation (e.g. due to clonal propagation) and thus undermine the cross-comparison of studies.
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Affiliation(s)
- Aimee R. Taylor
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Diego F. Echeverry
- Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM), Cali, Colombia
- Universidad Icesi, Calle 18 No. 122-135, Cali, Colombia
- Departamento de Microbiologia, Facultad de Salud, Universidad del Valle, Cali, Colombia
| | - Timothy J. C. Anderson
- Disease Intervention and Prevention Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Daniel E. Neafsey
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Caroline O. Buckee
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
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6
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Fola AA, Kattenberg E, Razook Z, Lautu-Gumal D, Lee S, Mehra S, Bahlo M, Kazura J, Robinson LJ, Laman M, Mueller I, Barry AE. SNP barcodes provide higher resolution than microsatellite markers to measure Plasmodium vivax population genetics. Malar J 2020; 19:375. [PMID: 33081815 PMCID: PMC7576724 DOI: 10.1186/s12936-020-03440-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 10/03/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Genomic surveillance of malaria parasite populations has the potential to inform control strategies and to monitor the impact of interventions. Barcodes comprising large numbers of single nucleotide polymorphism (SNP) markers are accurate and efficient genotyping tools, however may need to be tailored to specific malaria transmission settings, since 'universal' barcodes can lack resolution at the local scale. A SNP barcode was developed that captures the diversity and structure of Plasmodium vivax populations of Papua New Guinea (PNG) for research and surveillance. METHODS Using 20 high-quality P. vivax genome sequences from PNG, a total of 178 evenly spaced neutral SNPs were selected for development of an amplicon sequencing assay combining a series of multiplex PCRs and sequencing on the Illumina MiSeq platform. For initial testing, 20 SNPs were amplified in a small number of mono- and polyclonal P. vivax infections. The full barcode was then validated by genotyping and population genetic analyses of 94 P. vivax isolates collected between 2012 and 2014 from four distinct catchment areas on the highly endemic north coast of PNG. Diversity and population structure determined from the SNP barcode data was then benchmarked against that of ten microsatellite markers used in previous population genetics studies. RESULTS From a total of 28,934,460 reads generated from the MiSeq Illumina run, 87% mapped to the PvSalI reference genome with deep coverage (median = 563, range 56-7586) per locus across genotyped samples. Of 178 SNPs assayed, 146 produced high-quality genotypes (minimum coverage = 56X) in more than 85% of P. vivax isolates. No amplification bias was introduced due to either polyclonal infection or whole genome amplification (WGA) of samples before genotyping. Compared to the microsatellite panels, the SNP barcode revealed greater variability in genetic diversity between populations and geographical population structure. The SNP barcode also enabled assignment of genotypes according to their geographic origins with a significant association between genetic distance and geographic distance at the sub-provincial level. CONCLUSIONS High-throughput SNP barcoding can be used to map variation of malaria transmission dynamics at sub-national resolution. The low cost per sample and genotyping strategy makes the transfer of this technology to field settings highly feasible.
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Affiliation(s)
- Abebe A Fola
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Eline Kattenberg
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Malariology Unit, Institute of Tropical Medicine, Antwerp, Belgium
| | - Zahra Razook
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Dulcie Lautu-Gumal
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Stuart Lee
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - Somya Mehra
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
| | - James Kazura
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- Centre for Global Health and Diseases, Case Western Reserve University, Cleveland, Ohio, USA
| | - Leanne J Robinson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
| | - Moses Laman
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Ivo Mueller
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France
| | - Alyssa E Barry
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia.
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia.
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7
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Malinga J, Mogeni P, Omedo I, Rockett K, Hubbart C, Jeffreys A, Williams TN, Kwiatkowski D, Bejon P, Ross A. Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya. Sci Rep 2019; 9:19018. [PMID: 31836742 PMCID: PMC6911066 DOI: 10.1038/s41598-019-54348-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 11/12/2019] [Indexed: 01/17/2023] Open
Abstract
Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.4 km (95% CI 0.24, 1.20), for a distribution with 58% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.
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Affiliation(s)
- Josephine Malinga
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Polycarp Mogeni
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Irene Omedo
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Kirk Rockett
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Christina Hubbart
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Anne Jeffreys
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Thomas N Williams
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya.,Department of Medicine, South Kensington Campus, Imperial College London, London, UK
| | - Dominic Kwiatkowski
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Philip Bejon
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya.,Centre for Tropical Medicine & Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Amanda Ross
- Swiss Tropical and Public Health Institute, Basel, Switzerland. .,University of Basel, Basel, Switzerland.
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8
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Nelson CS, Sumner KM, Freedman E, Saelens JW, Obala AA, Mangeni JN, Taylor SM, O'Meara WP. High-resolution micro-epidemiology of parasite spatial and temporal dynamics in a high malaria transmission setting in Kenya. Nat Commun 2019; 10:5615. [PMID: 31819062 PMCID: PMC6901486 DOI: 10.1038/s41467-019-13578-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 11/14/2019] [Indexed: 01/03/2023] Open
Abstract
Novel interventions that leverage the heterogeneity of parasite transmission are needed to achieve malaria elimination. To better understand spatial and temporal dynamics of transmission, we applied amplicon next-generation sequencing of two polymorphic gene regions (csp and ama1) to a cohort identified via reactive case detection in a high-transmission setting in western Kenya. From April 2013 to July 2014, we enrolled 442 symptomatic children with malaria, 442 matched controls, and all household members of both groups. Here, we evaluate genetic similarity between infected individuals using three indices: sharing of parasite haplotypes on binary and proportional scales and the L1 norm. Symptomatic children more commonly share haplotypes with their own household members. Furthermore, we observe robust temporal structuring of parasite genetic similarity and identify the unique molecular signature of an outbreak. These findings of both micro- and macro-scale organization of parasite populations might be harnessed to inform next-generation malaria control measures. Here, Nelson et al. use amplicon next-generation sequencing of two P. falciparum polymorphic gene regions to investigate the genetic similarity of parasite populations across time and space in a pediatric cohort in Kenya. They identify both micro- and macro-scale structuring of malaria parasites in this high-transmission setting, which could inform future intervention strategies.
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Affiliation(s)
- Cody S Nelson
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA.
| | - Kelsey M Sumner
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.,Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA
| | - Elizabeth Freedman
- Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA
| | - Joseph W Saelens
- Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA
| | - Andrew A Obala
- School of Medicine, Moi University College of Health Sciences, Eldoret, Kenya
| | - Judith N Mangeni
- School of Nursing, Moi University College of Health Sciences, Eldoret, Kenya
| | - Steve M Taylor
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA.,Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.,Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA
| | - Wendy P O'Meara
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA.,Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA
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Taylor AR, Jacob PE, Neafsey DE, Buckee CO. Estimating Relatedness Between Malaria Parasites. Genetics 2019; 212:1337-1351. [PMID: 31209105 PMCID: PMC6707449 DOI: 10.1534/genetics.119.302120] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 06/03/2019] [Indexed: 11/18/2022] Open
Abstract
Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent. Estimates based on IBS are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on IBD. To generate estimates with errors below an arbitrary threshold of 0.1, we recommend ∼100 polyallelic or 200 biallelic markers. Marker requirements are immediately applicable to haploid malaria parasites and other haploid eukaryotes. C.I.s facilitate comparison when different marker sets are used. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology. We hope it will provide a basis for statistically informed prospective study design and surveillance strategies.
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Affiliation(s)
- Aimee R Taylor
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
| | - Pierre E Jacob
- Department of Statistics, Harvard University, Cambridge, Massachusetts 02138
| | - Daniel E Neafsey
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
| | - Caroline O Buckee
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
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Apinjoh TO, Ouattara A, Titanji VPK, Djimde A, Amambua-Ngwa A. Genetic diversity and drug resistance surveillance of Plasmodium falciparum for malaria elimination: is there an ideal tool for resource-limited sub-Saharan Africa? Malar J 2019; 18:217. [PMID: 31242921 PMCID: PMC6595576 DOI: 10.1186/s12936-019-2844-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 06/18/2019] [Indexed: 12/20/2022] Open
Abstract
The intensification of malaria control interventions has resulted in its global decline, but it remains a significant public health burden especially in sub-Saharan Africa (sSA). Knowledge on the parasite diversity, its transmission dynamics, mechanisms of adaptation to environmental and interventional pressures could help refine or develop new control and elimination strategies. Critical to this is the accurate assessment of the parasite’s genetic diversity and monitoring of genetic markers of anti-malarial resistance across all susceptible populations. Such wide molecular surveillance will require selected tools and approaches from a variety of ever evolving advancements in technology and the changing epidemiology of malaria. The choice of an effective approach for specific endemic settings remains challenging, particularly for countries in sSA with limited access to advanced technologies. This article examines the current strategies and tools for Plasmodium falciparum genetic diversity typing and resistance monitoring and proposes how the different tools could be employed in resource-poor settings. Advanced approaches enabling targeted deep sequencing is valued as a sensitive method for assessing drug resistance and parasite diversity but remains out of the reach of most laboratories in sSA due to the high cost of development and maintenance. It is, however, feasible to equip a limited number of laboratories as Centres of Excellence in Africa (CEA), which will receive and process samples from a network of peripheral laboratories in the continent. Cheaper, sensitive and portable real-time PCR methods can be used in peripheral laboratories to pre-screen and select samples for targeted deep sequence or genome wide analyses at these CEAs.
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Affiliation(s)
- Tobias O Apinjoh
- Department of Biochemistry and Molecular Biology, University of Buea, Buea, Cameroon
| | - Amed Ouattara
- School of Medicine, University of Maryland, College Park, Baltimore, USA
| | - Vincent P K Titanji
- Faculty of Science, Engineering and Technology, Cameroon Christian University, Bali, Cameroon
| | - Abdoulaye Djimde
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
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