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Butterworth NJ, Wallman JF, Johnston NP, Dawson BM, Sharp-Heward J, McGaughran A. The blowfly Chrysomya latifrons inhabits fragmented rainforests, but shows no population structure. Oecologia 2023; 201:703-719. [PMID: 36773072 PMCID: PMC10038970 DOI: 10.1007/s00442-023-05333-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 01/27/2023] [Indexed: 02/12/2023]
Abstract
Climate change and deforestation are causing rainforests to become increasingly fragmented, placing them at heightened risk of biodiversity loss. Invertebrates constitute the greatest proportion of this biodiversity, yet we lack basic knowledge of their population structure and ecology. There is a compelling need to develop our understanding of the population dynamics of a wide range of rainforest invertebrates so that we can begin to understand how rainforest fragments are connected, and how they will cope with future habitat fragmentation and climate change. Blowflies are an ideal candidate for such research because they are widespread, abundant, and can be easily collected within rainforests. We genotyped 188 blowflies (Chrysomya latifrons) from 15 isolated rainforests and found high levels of gene flow, a lack of genetic structure between rainforests, and low genetic diversity - suggesting the presence of a single large genetically depauperate population. This highlights that: (1) the blowfly Ch. latifrons inhabits a ~ 1000 km stretch of Australian rainforests, where it plays an important role as a nutrient recycler; (2) strongly dispersing flies can migrate between and connect isolated rainforests, likely carrying pollen, parasites, phoronts, and pathogens along with them; and (3) widely dispersing and abundant insects can nevertheless be genetically depauperate. There is an urgent need to better understand the relationships between habitat fragmentation, genetic diversity, and adaptive potential-especially for poorly dispersing rainforest-restricted insects, as many of these may be particularly fragmented and at highest risk of local extinction.
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Affiliation(s)
- Nathan J Butterworth
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia.
- Faculty of Science, University of Technology Sydney, Ultimo, NSW, 2007, Australia.
| | - James F Wallman
- Faculty of Science, University of Technology Sydney, Ultimo, NSW, 2007, Australia
- Centre for Sustainable Ecosystem Solutions, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Nikolas P Johnston
- Faculty of Science, University of Technology Sydney, Ultimo, NSW, 2007, Australia
- Department of Ecology and Biogeography, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University in Toruń, 87-100, Toruń, Poland
- Centre for Sustainable Ecosystem Solutions, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Blake M Dawson
- Centre for Sustainable Ecosystem Solutions, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Joshua Sharp-Heward
- Centre for Sustainable Ecosystem Solutions, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Angela McGaughran
- Te Aka Mātuatua - School of Science, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand
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Bishop AP, Amatulli G, Hyseni C, Pless E, Bateta R, Okeyo WA, Mireji PO, Okoth S, Malele I, Murilla G, Aksoy S, Caccone A, Saarman NP. A machine learning approach to integrating genetic and ecological data in tsetse flies ( Glossina pallidipes) for spatially explicit vector control planning. Evol Appl 2021; 14:1762-1777. [PMID: 34295362 PMCID: PMC8288027 DOI: 10.1111/eva.13237] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 11/26/2022] Open
Abstract
Vector control is an effective strategy for reducing vector-borne disease transmission, but requires knowledge of vector habitat use and dispersal patterns. Our goal was to improve this knowledge for the tsetse species Glossina pallidipes, a vector of human and animal African trypanosomiasis, which are diseases that pose serious health and socioeconomic burdens across sub-Saharan Africa. We used random forest regression to (i) build and integrate models of G. pallidipes habitat suitability and genetic connectivity across Kenya and northern Tanzania and (ii) provide novel vector control recommendations. Inputs for the models included field survey records from 349 trap locations, genetic data from 11 microsatellite loci from 659 flies and 29 sampling sites, and remotely sensed environmental data. The suitability and connectivity models explained approximately 80% and 67% of the variance in the occurrence and genetic data and exhibited high accuracy based on cross-validation. The bivariate map showed that suitability and connectivity vary independently across the landscape and was used to inform our vector control recommendations. Post hoc analyses show spatial variation in the correlations between the most important environmental predictors from our models and each response variable (e.g., suitability and connectivity) as well as heterogeneity in expected future climatic change of these predictors. The bivariate map suggests that vector control is most likely to be successful in the Lake Victoria Basin and supports the previous recommendation that G. pallidipes from most of eastern Kenya should be managed as a single unit. We further recommend that future monitoring efforts should focus on tracking potential changes in vector presence and dispersal around the Serengeti and the Lake Victoria Basin based on projected local climatic shifts. The strong performance of the spatial models suggests potential for our integrative methodology to be used to understand future impacts of climate change in this and other vector systems.
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Affiliation(s)
- Anusha P. Bishop
- Department of Ecology and Evolutionary BiologyYale UniversityNew HavenCTUSA
- Department of Environmental Science, Policy, & ManagementUniversity of CaliforniaBerkeleyCAUSA
| | | | - Chaz Hyseni
- Department of Ecology and GeneticsUppsala UniversityUppsalaSweden
| | - Evlyn Pless
- Department of Ecology and Evolutionary BiologyYale UniversityNew HavenCTUSA
- Department of AnthropologyUniversity of CaliforniaDavisCAUSA
| | - Rosemary Bateta
- Biotechnology Research InstituteKenya Agricultural and Livestock Research OrganizationKikuyu, NairobiKenya
| | - Winnie A. Okeyo
- Biotechnology Research InstituteKenya Agricultural and Livestock Research OrganizationKikuyu, NairobiKenya
- Department of Biomedical Sciences and TechnologySchool of Public Health and Community DevelopmentMaseno UniversityMaseno, KisumuKenya
| | - Paul O. Mireji
- Biotechnology Research InstituteKenya Agricultural and Livestock Research OrganizationKikuyu, NairobiKenya
- Centre for Geographic Medicine Research CoastKenya Medical Research InstituteKilifiKenya
| | - Sylvance Okoth
- Biotechnology Research InstituteKenya Agricultural and Livestock Research OrganizationKikuyu, NairobiKenya
| | - Imna Malele
- Vector and Vector Borne Diseases Research InstituteTanzania Veterinary Laboratory AgencyTangaTanzania
| | - Grace Murilla
- Biotechnology Research InstituteKenya Agricultural and Livestock Research OrganizationKikuyu, NairobiKenya
| | - Serap Aksoy
- Department of Epidemiology of Microbial DiseasesYale School of Public HealthNew HavenCTUSA
| | - Adalgisa Caccone
- Department of Ecology and Evolutionary BiologyYale UniversityNew HavenCTUSA
| | - Norah P. Saarman
- Department of Ecology and Evolutionary BiologyYale UniversityNew HavenCTUSA
- Department of BiologyUtah State UniversityLoganUTUSA
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Gashururu RS, Githigia SM, Gasana MN, Habimana R, Maingi N, Cecchi G, Paone M, Zhao W, Masiga DK, Gashumba J. An update on the distribution of Glossina (tsetse flies) at the wildlife-human-livestock interface of Akagera National Park, Rwanda. Parasit Vectors 2021; 14:294. [PMID: 34078446 PMCID: PMC8173956 DOI: 10.1186/s13071-021-04786-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 05/11/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Glossina (tsetse flies) biologically transmit trypanosomes that infect both humans and animals. Knowledge of their distribution patterns is a key element to better understand the transmission dynamics of trypanosomosis. Tsetse distribution in Rwanda has not been well enough documented, and little is known on their current distribution. This study determined the current spatial distribution, abundance, diversity, and seasonal variations of tsetse flies in and around the Akagera National Park. METHODS A longitudinal stratified sampling following the seasons was used. Biconical traps were deployed in 55 sites for 6 consecutive days of each study month from May 2018 to June 2019 and emptied every 48 h. Flies were identified using FAO keys, and the number of flies per trap day (FTD) was used to determine the apparent density. Pearson chi-square (χ2) and parametrical tests (t-test and ANOVA) were used to determine the variations between the variables. The significance (p < 0.05) at 95% confidence interval was considered. Logistic regression was used to determine the association between tsetse occurrence and the associated predictors. RESULTS A total of 39,516 tsetse flies were collected, of which 73.4 and 26.6% were from inside Akagera NP and the interface area, respectively. Female flies accounted for 61.3 while 38.7% were males. Two species were identified, i.e. G. pallidipes [n = 29,121, 7.4 flies/trap/day (FTD)] and G. morsitans centralis (n = 10,395; 2.6 FTD). The statistical difference in numbers was significant between the two species (p = 0.000). The flies were more abundant during the wet season (15.8 FTD) than the dry season (4.2 FTD). Large numbers of flies were trapped around the swamp areas (69.1 FTD) inside the park and in Nyagatare District (11.2 FTD) at the interface. Glossina morsitans was 0.218 times less likely to occur outside the park. The chance of co-existing between the two species reduced outside the protected area (0.021 times). CONCLUSIONS The occurrence of Glossina seems to be limited to the protected Akagera NP and a narrow band of its surrounding areas. This finding will be crucial to design appropriate control strategies. Glossina pallidipes was found in higher numbers and therefore is conceivably the most important vector of trypanosomosis. Regional coordinated control and regular monitoring of Glossina distribution are recommended.
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Affiliation(s)
- Richard S Gashururu
- School of Veterinary Medicine, University of Rwanda, P.O. Box 57, Nyagatare, Rwanda. .,Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, Nairobi, Kenya. .,International Centre of Insect Physiology and Ecology (Icipe), P.O. Box 30772-00100, Nairobi, Kenya.
| | - Samuel M Githigia
- Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, Nairobi, Kenya
| | - Methode N Gasana
- Rwanda Agriculture and Animal Resources Board, PO. Box 5016, Kigali, Rwanda
| | - Richard Habimana
- School of Veterinary Medicine, University of Rwanda, P.O. Box 57, Nyagatare, Rwanda
| | - Ndichu Maingi
- Faculty of Veterinary Medicine, University of Nairobi, P.O. Box 29053, Nairobi, Kenya
| | - Giuliano Cecchi
- Food and Agriculture Organization of the United Nations (FAO), Animal Production and Health Division, Rome, Italy
| | - Massimo Paone
- Food and Agriculture Organization of the United Nations (FAO), Animal Production and Health Division, Rome, Italy
| | - Weining Zhao
- Food and Agriculture Organization of the United Nations (FAO), Animal Production and Health Division, Rome, Italy
| | - Daniel K Masiga
- International Centre of Insect Physiology and Ecology (Icipe), P.O. Box 30772-00100, Nairobi, Kenya
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Tsetse blood-meal sources, endosymbionts and trypanosome-associations in the Maasai Mara National Reserve, a wildlife-human-livestock interface. PLoS Negl Trop Dis 2021; 15:e0008267. [PMID: 33406097 PMCID: PMC7822626 DOI: 10.1371/journal.pntd.0008267] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 01/22/2021] [Accepted: 11/22/2020] [Indexed: 01/06/2023] Open
Abstract
African trypanosomiasis (AT) is a neglected disease of both humans and animals caused by Trypanosoma parasites, which are transmitted by obligate hematophagous tsetse flies (Glossina spp.). Knowledge on tsetse fly vertebrate hosts and the influence of tsetse endosymbionts on trypanosome presence, especially in wildlife-human-livestock interfaces, is limited. We identified tsetse species, their blood-meal sources, and correlations between endosymbionts and trypanosome presence in tsetse flies from the trypanosome-endemic Maasai Mara National Reserve (MMNR) in Kenya. Among 1167 tsetse flies (1136 Glossina pallidipes, 31 Glossina swynnertoni) collected from 10 sampling sites, 28 (2.4%) were positive by PCR for trypanosome DNA, most (17/28) being of Trypanosoma vivax species. Blood-meal analyses based on high-resolution melting analysis of vertebrate cytochrome c oxidase 1 and cytochrome b gene PCR products (n = 354) identified humans as the most common vertebrate host (37%), followed by hippopotamus (29.1%), African buffalo (26.3%), elephant (3.39%), and giraffe (0.84%). Flies positive for trypanosome DNA had fed on hippopotamus and buffalo. Tsetse flies were more likely to be positive for trypanosomes if they had the Sodalis glossinidius endosymbiont (P = 0.0002). These findings point to complex interactions of tsetse flies with trypanosomes, endosymbionts, and diverse vertebrate hosts in wildlife ecosystems such as in the MMNR, which should be considered in control programs. These interactions may contribute to the maintenance of tsetse populations and/or persistent circulation of African trypanosomes. Although the African buffalo is a key reservoir of AT, the higher proportion of hippopotamus blood-meals in flies with trypanosome DNA indicates that other wildlife species may be important in AT transmission. No trypanosomes associated with human disease were identified, but the high proportion of human blood-meals identified are indicative of human African trypanosomiasis risk. Our results add to existing data suggesting that Sodalis endosymbionts are associated with increased trypanosome presence in tsetse flies.
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Mayoke A, Ouma JO, Mireji PO, Omondi SF, Muya SM, Itoua A, Okoth SO, Bateta R. Population Structure and Migration Patterns of the Tsetse Fly Glossina fuscipes in Congo-Brazzaville. Am J Trop Med Hyg 2020; 104:917-927. [PMID: 33372648 PMCID: PMC7941806 DOI: 10.4269/ajtmh.20-0774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 11/17/2020] [Indexed: 11/07/2022] Open
Abstract
Tsetse flies of the palpalis group, particularly Glossina fuscipes, are the main vectors of human African trypanosomiasis or sleeping sickness in Congo-Brazzaville. They transmit the deadly human parasite, Trypanosoma brucei gambiense and other trypanosomes that cause animal trypanosomiasis. Knowledge on diversity, population structure, population size, and gene flow is a prerequisite for designing effective tsetse control strategies. There is limited published information on these parameters including migration patterns of G. fuscipes in Congo-Brazzaville. We genotyped 288 samples of G. fuscipes from Bomassa (BMSA), Bouemba (BEMB), and Talangai (TLG) locations at 10 microsatellite loci and determined levels of genetic diversity, differentiation, structuring, and gene flow among populations. We observed high genetic diversity in all three localities. Mean expected heterozygosity was 0.77 ± 0.04, and mean allelic richness was 11.2 ± 1.35. Deficiency of heterozygosity was observed in all populations with positive and significant F IS values (0.077-0.149). Structure analysis revealed three clusters with genetic admixtures, evidence of closely related but potentially different taxa within G. fuscipes. Genetic differentiation indices were low but significant (F ST = 0.049, P < 0.05), indicating ongoing gene flow countered with a stronger force of drift. We recorded significant migration from all the three populations, suggesting exchange of genetic information between and among locations. Ne estimates revealed high and infinite population sizes in BEMB and TLG. These critical factors should be considered when planning area-wide tsetse control interventions in the country to prevent resurgence of tsetse from relict populations and/or reinvasion of cleared habitats.
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Affiliation(s)
- Abraham Mayoke
- Department of Molecular Biology and Biotechnology, Pan African University Institute for Basic Sciences, Technology and Innovation, Nairobi, Kenya
- Kenya Forestry Research Institute, Nairobi, Kenya
- Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, Kikuyu, Kenya
- Marien Ngouabi University, Brazzaville, Congo
| | - Johnson O. Ouma
- African Technical Research Centre, Vector Health International, Arusha, Tanzania
| | - Paul O. Mireji
- Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, Kikuyu, Kenya
| | | | - Shadrack M. Muya
- School of Biological Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | - Andre Itoua
- Laboratoire de Parasitologie, Centre de Recherche Veterinaire et Zootechniques, Brazzaville, Congo
| | - Sylvance O. Okoth
- Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, Kikuyu, Kenya
| | - Rosemary Bateta
- Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization, Kikuyu, Kenya
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