Literature DB >> 30281913

An improved method for utilizing high-throughput amplicon sequencing to determine the diets of insectivorous animals.

Michelle A Jusino1,2, Mark T Banik1, Jonathan M Palmer1, Amy K Wray3, Lei Xiao4, Emma Pelton5,6, Jesse R Barber7, Akito Y Kawahara4, Claudio Gratton5, M Zachariah Peery3, Daniel L Lindner1.   

Abstract

DNA analysis of predator faeces using high-throughput amplicon sequencing (HTS) enhances our understanding of predator-prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (COI). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair "ZBJ" to results using the novel primer pair "ANML." To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single-copy (cloned) COI sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre- and post-PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%), whereas ZBJ amplified 24-40 of 59 taxa (41%-68%). Furthermore, in an HTS comparison of field-collected samples, the ANML primers detected nearly fourfold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  AMPtk; arthropod mock community; bat guano; dietary analysis; insectivore; next-generation sequencing

Mesh:

Substances:

Year:  2019        PMID: 30281913     DOI: 10.1111/1755-0998.12951

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  22 in total

1.  Effects of Field Fumigation and Inoculation With the Pecan Truffle (Tuber lyonii) on the Fungal Community of Pecan (Carya illinoinensis) Seedlings Over 5 Years.

Authors:  Arthur C Grupe; Michelle A Jusino; Alija B Mujic; Brantlee Spakes-Richter; Gregory Bonito; Tim Brenneman; Matthew E Smith
Journal:  Front Microbiol       Date:  2021-05-13       Impact factor: 5.640

2.  In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses.

Authors:  Orianne Tournayre; Maxime Leuchtmann; Ondine Filippi-Codaccioni; Marine Trillat; Sylvain Piry; Dominique Pontier; Nathalie Charbonnel; Maxime Galan
Journal:  Ecol Evol       Date:  2020-05-21       Impact factor: 2.912

3.  Assessment of seasonal variation of diet composition in rodents using DNA barcoding and Real-Time PCR.

Authors:  Filippo Dell'Agnello; Chiara Natali; Sandro Bertolino; Lorenzo Fattorini; Ettore Fedele; Bruno Foggi; Matilde Martini; Caterina Pisani; Francesco Riga; Antonio Sgarlata; Claudio Ciofi; Marco Zaccaroni
Journal:  Sci Rep       Date:  2019-10-01       Impact factor: 4.379

4.  Validation of COI metabarcoding primers for terrestrial arthropods.

Authors:  Vasco Elbrecht; Thomas W A Braukmann; Natalia V Ivanova; Sean W J Prosser; Mehrdad Hajibabaei; Michael Wright; Evgeny V Zakharov; Paul D N Hebert; Dirk Steinke
Journal:  PeerJ       Date:  2019-10-07       Impact factor: 2.984

5.  The menu varies with metabarcoding practices: A case study with the bat Plecotus auritus.

Authors:  Tommy Andriollo; François Gillet; Johan R Michaux; Manuel Ruedi
Journal:  PLoS One       Date:  2019-07-05       Impact factor: 3.240

6.  Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data?

Authors:  Bruce E Deagle; Austen C Thomas; Julie C McInnes; Laurence J Clarke; Eero J Vesterinen; Elizabeth L Clare; Tyler R Kartzinel; J Paige Eveson
Journal:  Mol Ecol       Date:  2018-06-17       Impact factor: 6.185

7.  A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses.

Authors:  Devon R O'Rourke; Nicholas A Bokulich; Michelle A Jusino; Matthew D MacManes; Jeffrey T Foster
Journal:  Ecol Evol       Date:  2020-07-23       Impact factor: 3.167

8.  Comprehensive coverage of human last meal components revealed by a forensic DNA metabarcoding approach.

Authors:  Judith Schneider; Eduard Mas-Carrió; Catherine Jan; Christian Miquel; Pierre Taberlet; Katarzyna Michaud; Luca Fumagalli
Journal:  Sci Rep       Date:  2021-04-23       Impact factor: 4.379

9.  Do the evolutionary interactions between moths and bats promote niche partitioning between bats and birds?

Authors:  Lorinda S Bullington; Mathew T Seidensticker; Nathan Schwab; Philip W Ramsey; Kate Stone
Journal:  Ecol Evol       Date:  2021-11-19       Impact factor: 2.912

10.  A powerful long metabarcoding method for the determination of complex diets from faecal analysis of the European pond turtle (Emys orbicularis, L. 1758).

Authors:  Charlotte Ducotterd; Julien Crovadore; François Lefort; Jean-François Rubin; Sylvain Ursenbacher
Journal:  Mol Ecol Resour       Date:  2020-11-04       Impact factor: 7.090

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