Literature DB >> 28926155

iDNA screening: Disease vectors as vertebrate samplers.

Arthur Kocher1,2, Benoit de Thoisy3,4, François Catzeflis5, Sophie Valière6, Anne-Laure Bañuls2, Jérôme Murienne1.   

Abstract

In the current context of global change and human-induced biodiversity decline, there is an urgent need for developing sampling approaches able to accurately describe the state of biodiversity. Traditional surveys of vertebrate fauna involve time-consuming and skill-demanding field methods. Recently, the use of DNA derived from invertebrate parasites (leeches and blowflies) was suggested as a new tool for vertebrate diversity assessment. Bloodmeal analyses of arthropod disease vectors have long been performed to describe their feeding behaviour, for epidemiological purposes. On the other hand, this existing expertise has not yet been applied to investigate vertebrate fauna per se. Here, we evaluate the usefulness of hematophagous dipterans as vertebrate samplers. Blood-fed sand flies and mosquitoes were collected in Amazonian forest sites and analysed using high-throughput sequencing of short mitochondrial markers. Bloodmeal identifications highlighted contrasting ecological features and feeding behaviour among dipteran species, which allowed unveiling arboreal and terrestrial mammals of various body size, as well as birds, lizards and amphibians. Additionally, lower vertebrate diversity was found in sites undergoing higher levels of human-induced perturbation. These results suggest that, in addition to providing precious information on disease vector host use, dipteran bloodmeal analyses may represent a useful tool in the study of vertebrate communities. Although further effort is required to validate the approach and consider its application to large-scale studies, this first work opens up promising perspectives for biodiversity monitoring and eco-epidemiology.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  bloodmeal; dipteran; feeding preference; insect; mosquito; sand fly

Mesh:

Substances:

Year:  2017        PMID: 28926155     DOI: 10.1111/mec.14362

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  10 in total

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3.  Using DNA metabarcoding for simultaneous inference of common vampire bat diet and population structure.

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Journal:  Gigascience       Date:  2019-04-01       Impact factor: 6.524

5.  Ideating iDNA: Lessons and limitations from leeches in legacy collections.

Authors:  Mark E Siddall; Megan Barkdull; Michael Tessler; Mercer R Brugler; Elizabeth Borda; Evon Hekkala
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

6.  Aquatic eDNA for monitoring French Guiana biodiversity.

Authors:  Jérôme Murienne; Isabel Cantera; Axel Cerdan; Kévin Cilleros; Jean-Baptiste Decotte; Tony Dejean; Régis Vigouroux; Sébastien Brosse
Journal:  Biodivers Data J       Date:  2019-09-11

Review 7.  Modernizing the Toolkit for Arthropod Bloodmeal Identification.

Authors:  Erin M Borland; Rebekah C Kading
Journal:  Insects       Date:  2021-01-06       Impact factor: 2.769

8.  Blood Feeding Sources of Nyssomyia antunesi (Diptera: Psychodidae): A Suspected Vector of Leishmania (Kinetoplastida: Trypanosomatidae) in the Brazilian Amazon.

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Journal:  J Med Entomol       Date:  2022-09-14       Impact factor: 2.435

9.  Identification of Mosquito Bloodmeals Collected in Diverse Habitats in Malaysian Borneo Using COI Barcoding.

Authors:  Katherine I Young; Joseph T Medwid; Sasha R Azar; Robert M Huff; Hannah Drumm; Lark L Coffey; R Jason Pitts; Michaela Buenemann; Nikos Vasilakis; David Perera; Kathryn A Hanley
Journal:  Trop Med Infect Dis       Date:  2020-04-01

10.  Measuring protected-area effectiveness using vertebrate distributions from leech iDNA.

Authors:  Yinqiu Ji; Christopher C M Baker; Viorel D Popescu; Jiaxin Wang; Chunying Wu; Zhengyang Wang; Yuanheng Li; Lin Wang; Chaolang Hua; Zhongxing Yang; Chunyan Yang; Charles C Y Xu; Alex Diana; Qingzhong Wen; Naomi E Pierce; Douglas W Yu
Journal:  Nat Commun       Date:  2022-03-23       Impact factor: 17.694

  10 in total

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