Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance
journal contributionposted on 2021-01-05, 02:28 authored by Alexander PiperAlexander Piper, Jana Batovska, Noel CoganNoel Cogan, John Weiss, John CunninghamJohn Cunningham, Brendan RodoniBrendan Rodoni, Mark Blacket
© The Author(s) 2019.
Trap-based surveillance strategies are widely used for monitoring of invasive insect species, aiming to detect newly arrived exotic taxa as well as track the population levels of established or endemic pests. Where these surveillance traps have low specificity and capture non-target endemic species in excess of the target pests, the need for extensive specimen sorting and identification creates a major diagnostic bottleneck. While the recent development of standardized molecular diagnostics has partly alleviated this requirement, the single specimen per reaction nature of these methods does not readily scale to the sheer number of insects trapped in surveillance programmes. Consequently, target lists are often restricted to a few high-priority pests, allowing unanticipated species to avoid detection and potentially establish populations. DNA metabarcoding has recently emerged as a method for conducting simultaneous, multi-species identification of complex mixed communities and may lend itself ideally to rapid diagnostics of bulk insect trap samples. Moreover, the high-throughput nature of recent sequencing platforms could enable the multiplexing of hundreds of diverse trap samples on a single flow cell, thereby providing the means to dramatically scale up insect surveillance in terms of both the quantity of traps that can be processed concurrently and number of pest species that can be targeted. In this review of the metabarcoding literature, we explore how DNA metabarcoding could be tailored to the detection of invasive insects in a surveillance context and highlight the unique technical and regulatory challenges that must be considered when implementing high-throughput sequencing technologies into sensitive diagnostic applications.
Horticulture Innovation Australia from the Australian Government Department of Agriculture as part of its Rural R&D for Profit program | ST16010
Grains Research and Development Corporation
Plant Biosecurity Cooperative Research Centre(PBCRC) | 2153
Agriculture Victoria's Improved Market Access for Horticulture programme | CMI105584
Australian Government Research Training Program Scholarship
Article NumberARTN giz092
PublisherOxford University Press
Rights StatementThe Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.
Science & TechnologyLife Sciences & BiomedicineBiologyMultidisciplinary SciencesLife Sciences & Biomedicine - Other TopicsScience & Technology - Other Topicsbiosecurityalien speciesbiosurveillanceearly detectionbioinformaticsreference databasequality assurancecontrolsvalidationnon-destructiveENVIRONMENTAL DNAMITOCHONDRIAL PSEUDOGENESOPTIMIZING SURVEILLANCEFALSE POSITIVESPLANTBIODIVERSITYBIOSECURITYSAMPLEIDENTIFICATIONACCURACYAnimalsGenetic MarkersComputational BiologyBiodiversityDatabases, GeneticGenome, InsectDNA Barcoding, TaxonomicHigh-Throughput Nucleotide SequencingInsecta