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      Population genetic analysis of Chadian Guinea worms reveals that human and non-human hosts share common parasite populations

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          Abstract

          Following almost 10 years of no reported cases, Guinea worm disease (GWD or dracunculiasis) reemerged in Chad in 2010 with peculiar epidemiological patterns and unprecedented prevalence of infection among non-human hosts, particularly domestic dogs. Since 2014, animal infections with Guinea worms have also been observed in the other three countries with endemic transmission (Ethiopia, Mali, and South Sudan), causing concern and generating interest in the parasites’ true taxonomic identity and population genetics. We present the first extensive population genetic data for Guinea worm, investigating mitochondrial and microsatellite variation in adult female worms from both human and non-human hosts in the four endemic countries to elucidate the origins of Chad’s current outbreak and possible host-specific differences between parasites. Genetic diversity of Chadian Guinea worms was considerably higher than that of the other three countries, even after controlling for sample size through rarefaction, and demographic analyses are consistent with a large, stable parasite population. Genealogical analyses eliminate the other three countries as possible sources of parasite reintroduction into Chad, and sequence divergence and distribution of genetic variation provide no evidence that parasites in human and non-human hosts are separate species or maintain isolated transmission cycles. Both among and within countries, geographic origin appears to have more influence on parasite population structure than host species. Guinea worm infection in non-human hosts has been occasionally reported throughout the history of the disease, particularly when elimination programs appear to be reaching their end goals. However, no previous reports have evaluated molecular support of the parasite species identity. Our data confirm that Guinea worms collected from non-human hosts in the remaining endemic countries of Africa are Dracunculus medinensis and that the same population of worms infects both humans and dogs in Chad. Our genetic data and the epidemiological evidence suggest that transmission in the Chadian context is currently being maintained by canine hosts.

          Author summary

          Since the mid-1980’s, when Guinea worm ( Dracunculus medinensis) was formally targeted for eradication, the associated national and international efforts to control and eliminate the parasite have been remarkably successful. As of 2017, 16 of the 21 countries with endemic transmission have been certified free of the disease by World Health Organization, and one country (Sudan) is in the pre-certification stage. However, recent and unprecedented prevalence of apparent Guinea worm infection in Chadian dogs has caused concern. That this seemingly sudden emergence in non-human hosts also coincided with an apparent reemergence of infection among humans in Chad after almost 10 years without reported cases raised questions about the population history of Guinea worm in Chad and whether worms from human and non-human hosts were, in fact, the same species. To address these questions, we characterized the genetic variation in Guinea worms collected from various host species and locations in Chad and in the other three endemic countries. Genetic variation was measured in adult female worms using sequence variation of mitochondrial DNA genes and repeat number polymorphism at 23 nuclear microsatellite loci. We found that, regardless of host species, all worms sampled from the remaining endemic countries in Africa are D. medinensis and show no evidence of isolated transmission on the basis of host species.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              Inference of Population Structure Using Multilocus Genotype Data

              We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: InvestigationRole: ResourcesRole: Writing – review & editing
                Role: InvestigationRole: Resources
                Role: Investigation
                Role: Investigation
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                4 October 2018
                October 2018
                : 12
                : 10
                : e0006747
                Affiliations
                [1 ] Biology Department, Vassar College, Poughkeepsie, New York, United States of America
                [2 ] Parasitic Diseases Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
                [3 ] Parasite Genomics Group, Wellcome Sanger Institute, Hinxton, United Kingdom
                [4 ] The Carter Center, Atlanta, GA, United States of America
                James Cook University, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-9235-2019
                Article
                PNTD-D-18-00418
                10.1371/journal.pntd.0006747
                6191157
                30286084
                61629b11-10ed-4246-9c25-1653206112a6

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 19 March 2018
                : 11 August 2018
                Page count
                Figures: 7, Tables: 5, Pages: 24
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 098051
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 098051
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 206194
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 206194
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100005527, Carter Center;
                Award Recipient :
                This work was supported by The Carter Center, whose work to eradicate Guinea worm disease has been made possible by financial and in-kind contributions from many donors. A full listing of supporters can be found at The Carter Center website ( http://www.cartercenter.org/donate/corporate-government-foundation-partners/index.html). JAC and CD were also supported by the Wellcome Trust ( https://wellcome.ac.uk/), via their core support of the Sanger Institute (grants 098051 and 206194). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and Places
                Geographical Locations
                Africa
                Chad
                Biology and Life Sciences
                Biochemistry
                Bioenergetics
                Energy-Producing Organelles
                Mitochondria
                Biology and Life Sciences
                Cell Biology
                Cellular Structures and Organelles
                Energy-Producing Organelles
                Mitochondria
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Nematoda
                Dracunculus
                Dracunculus Medinensis
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Helminths
                Dracunculus Medinensis
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Haplotypes
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Dogs
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Medicine and Health Sciences
                Parasitic Diseases
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Custom metadata
                vor-update-to-uncorrected-proof
                2018-10-16
                Mitochondrial sequences can be found in their untrimmed, non-concatenated state at NCBI ( https://www.ncbi.nlm.nih.gov/) under the accession numbers MH048098‒MH048448. Microsatellite data, both raw allele calls (including peak height/area) and derived maternal genotypes, are deposited in the DRYAD repository ( https://doi.org/10.5061/dryad.89qb406).

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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