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      Microsatellite based molecular epidemiology of Leishmania infantum from re-emerging foci of visceral leishmaniasis in Armenia and pilot risk assessment by ecological niche modeling

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          Abstract

          Background

          Visceral leishmaniasis (VL) is re-emerging in Armenia since 1999 with 167 cases recorded until 2019. The objectives of this study were (i) to determine for the first time the genetic diversity and population structure of the causative agent of VL in Armenia; (ii) to compare these genotypes with those from most endemic regions worldwide; (iii) to monitor the diversity of vectors in Armenia; (iv) to predict the distribution of the vectors and VL in time and space by ecological niche modeling.

          Methodology/Principal findings

          Human samples from different parts of Armenia previously identified by ITS-1-RFLP as L. infantum were studied by Multilocus Microsatellite Typing (MLMT). These data were combined with previously typed L. infantum strains from the main global endemic regions for population structure analysis. Within the 23 Armenian L. infantum strains 22 different genotypes were identified. The combined analysis revealed that all strains belong to the worldwide predominating MON1-population, however most closely related to a subpopulation from Southeastern Europe, Maghreb, Middle East and Central Asia. The three observed Armenian clusters grouped within this subpopulation with strains from Greece/Turkey, and from Central Asia, respectively. Ecological niche modeling based on VL cases and collected proven vectors ( P. balcanicus, P. kandelakii) identified Yerevan and districts Lori, Tavush, Syunik, Armavir, Ararat bordering Georgia, Turkey, Iran and Azerbaijan as most suitable for the vectors and with the highest risk for VL transmission. Due to climate change the suitable habitat for VL transmission will expand in future all over Armenia.

          Conclusions

          Genetic diversity and population structure of the causative agent of VL in Armenia were addressed for the first time. Further genotyping studies should be performed with samples from infected humans, animals and sand flies from all active foci including the neighboring countries to understand transmission cycles, re-emergence, spread, and epidemiology of VL in Armenia and the entire Transcaucasus enabling epidemiological monitoring.

          Author summary

          Leishmaniasis is a vector-borne disease caused by protozoan parasites of the genus Leishmania. In Armenia visceral leishmaniasis (VL) is re-emerging since 1999 after a long break of 30 years, with 167 cases recorded until 2019. Molecular diagnosis of VL was implemented only in 2016, and the causative agent was identified as L. infantum. In the present study we expanded the investigation of the causative agent to a characterization at strain level and the identification of its phylogenetic position among the L. infantum genotypes circulating worldwide. This is the first study addressing genetic diversity and population structure of L. infantum in Armenia and in Transcaucasia. Armenia is an extremely interesting region due to its bio-geographic specificities e.g. the high number of different climates in this small mountainous country and the observed high diversity of sand fly species, part of which occurring in very high altitudes. Ecological niche modeling based on registered VL cases and sand fly vectors collected in active VL foci revealed that the risk of further spread of VL is very high due to climate change. Studies of this region should be expanded to enable targeted control measures.

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          Most cited references93

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          Detecting the number of clusters of individuals using the software structure: a simulation study

          The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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            A working guide to boosted regression trees.

            1. Ecologists use statistical models for both explanation and prediction, and need techniques that are flexible enough to express typical features of their data, such as nonlinearities and interactions. 2. This study provides a working guide to boosted regression trees (BRT), an ensemble method for fitting statistical models that differs fundamentally from conventional techniques that aim to fit a single parsimonious model. Boosted regression trees combine the strengths of two algorithms: regression trees (models that relate a response to their predictors by recursive binary splits) and boosting (an adaptive method for combining many simple models to give improved predictive performance). The final BRT model can be understood as an additive regression model in which individual terms are simple trees, fitted in a forward, stagewise fashion. 3. Boosted regression trees incorporate important advantages of tree-based methods, handling different types of predictor variables and accommodating missing data. They have no need for prior data transformation or elimination of outliers, can fit complex nonlinear relationships, and automatically handle interaction effects between predictors. Fitting multiple trees in BRT overcomes the biggest drawback of single tree models: their relatively poor predictive performance. Although BRT models are complex, they can be summarized in ways that give powerful ecological insight, and their predictive performance is superior to most traditional modelling methods. 4. The unique features of BRT raise a number of practical issues in model fitting. We demonstrate the practicalities and advantages of using BRT through a distributional analysis of the short-finned eel (Anguilla australis Richardson), a native freshwater fish of New Zealand. We use a data set of over 13 000 sites to illustrate effects of several settings, and then fit and interpret a model using a subset of the data. We provide code and a tutorial to enable the wider use of BRT by ecologists.
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              ESTIMATING F-STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: SoftwareRole: Visualization
                Role: Funding acquisitionRole: Investigation
                Role: InvestigationRole: MethodologyRole: Resources
                Role: Funding acquisitionRole: Project administrationRole: ResourcesRole: Supervision
                Role: Investigation
                Role: Data curationRole: InvestigationRole: Resources
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Project administrationRole: ResourcesRole: Supervision
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: 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
                19 April 2021
                April 2021
                : 15
                : 4
                : e0009288
                Affiliations
                [1 ] Division of Molecular Biotechnology and Functional Genomics, Technical University of Applied Sciences Wildau, Wildau, Germany
                [2 ] Research Platform Data Analysis & Simulation, Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
                [3 ] Research Institute of Epidemiology, Virology and Medical Parasitology after A.B. Alexanyan, Ministry of Health, Yerevan, Armenia
                [4 ] Eurasia International University, Yerevan, Armenia
                [5 ] National Center of Disease Control and Prevention, Ministry of Health,Yerevan, Armenia
                [6 ] Yerevan State Medical University after Mkitar Herats, Yerevan, Armenia
                [7 ] Martsinovsky Institute of Medical Parasitology, Tropical and Vector-borne Diseases, Sechenov First Moscow State Medical University, Moscow, Russia
                [8 ] Department of Biogeography, University of Bayreuth, Bayreuth, Germany
                [9 ] Global Health & Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
                Universiteit Antwerpen, BELGIUM
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-4168-8684
                https://orcid.org/0000-0001-8482-1372
                https://orcid.org/0000-0001-5705-9327
                https://orcid.org/0000-0001-8361-0960
                https://orcid.org/0000-0002-2278-610X
                https://orcid.org/0000-0001-9063-2682
                https://orcid.org/0000-0001-5850-6950
                Article
                PNTD-D-20-01088
                10.1371/journal.pntd.0009288
                8055006
                33872307
                20f0a8ff-e83a-43b0-ad6b-edcd0ede71fd
                © 2021 Kuhls et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 June 2020
                : 3 March 2021
                Page count
                Figures: 7, Tables: 5, Pages: 31
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: FKZ01DK14021
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 16PGF0170
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001655, Deutscher Akademischer Austauschdienst;
                Award ID: 1618841
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001871, Fundação para a Ciência e a Tecnologia;
                Award ID: IF/0773/2015
                Award Recipient :
                This work was supported by grants from the Federal Ministry of Education and Research of Germany (Bundesministerium für Bildung und Forschung – 01DK14021 and 16PGF0170) awarded to KK. Additional support from the German Academic Exchange Service (Deutscher Akademischer Austauschdienst – DAAD – Research grant 1618841 awarded to AS) and the Foundation for Science and Technology (FCT) Portugal (Fundação para a Ciência e a Tecnologia – IF/0773/2015 awarded to SC) is gratefully acknowledged. 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
                Asia
                Armenia
                People and Places
                Geographical Locations
                Europe
                Armenia
                Medicine and Health Sciences
                Medical Conditions
                Tropical Diseases
                Neglected Tropical Diseases
                Leishmaniasis
                Medicine and Health Sciences
                Medical Conditions
                Parasitic Diseases
                Protozoan Infections
                Leishmaniasis
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Zoonoses
                Leishmaniasis
                Biology and Life Sciences
                Organisms
                Eukaryota
                Protozoans
                Parasitic Protozoans
                Leishmania
                Leishmania Infantum
                People and Places
                Population Groupings
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                Geographical Locations
                Asia
                Turkey (Country)
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                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Disease Vectors
                Insect Vectors
                Sand Flies
                Biology and Life Sciences
                Species Interactions
                Disease Vectors
                Insect Vectors
                Sand Flies
                People and Places
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                Asia
                Azerbaijan
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                Europe
                Azerbaijan
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                European Union
                Greece
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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