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      Parasites of an Arctic scavenger; the wolverine ( Gulo gulo)

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          Abstract

          Parasites are fundamental components within all ecosystems, shaping interaction webs, host population dynamics and behaviour. Despite this, baseline data is lacking to understand the parasite ecology of many Arctic species, including the wolverine ( Gulo gulo), a top Arctic predator and scavenger. Here, we combined traditional count methods (i.e. adult helminth recovery, where taxonomy was confirmed by molecular identification) with 18S rRNA high-throughput sequencing to document the wolverine parasite community. Further, we investigated whether the abundance of parasites detected using traditional methods were associated with host metadata, latitude, and longitude (ranging from the northern limit of the boreal forest to the low Arctic and Arctic tundra in Nunavut, Canada). Adult parasites in intestinal contents were identified as Baylisascaris devosi in 72% (n = 39) of wolverines and Taenia spp. in 22% (n = 12), of which specimens from 2 wolverines were identified as T. twitchelli based on COX1 sequence. 18S rRNA high-throughput sequencing on DNA extracted from faeces detected additional parasites, including a pseudophyllid cestode ( Diplogonoporus spp. or Diphyllobothrium spp.), two metastrongyloid lungworms ( Angiostrongylus spp. or Aelurostrongylus spp., and Crenosoma spp.), an ascarid nematode ( Ascaris spp. or Toxocara spp.), a Trichinella spp. nematode, and the protozoan Sarcocystis spp., though each at a prevalence less than 13% (n = 7). The abundance of B. devosi significantly decreased with latitude (slope = -0.68; R 2 = 0.17; P = 0.004), suggesting a northerly limit in distribution. We describe B. devosi and T. twitchelli in Canadian wolverines for the first time since 1978, and extend the recorded geographic distribution of these parasites ca 2000 km to the East and into the tundra ecosystem. Our findings illustrate the value of molecular methods in support of traditional methods, encouraging additional work to improve the advancement of molecular screening for parasites.

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          Highlights

          • Combining traditional and molecular methods better captures parasite diversity.

          • B. devosi and Taenia spp. distribution extends ca 2000 km East and into the tundra.

          • The abundance of B. devosi in wolverines significantly decreases with latitude.

          • B. devosi and Taenia spp. abundance is not associated with wolverine host metadata.

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          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                Journal
                Int J Parasitol Parasites Wildl
                Int J Parasitol Parasites Wildl
                International Journal for Parasitology: Parasites and Wildlife
                Elsevier
                2213-2244
                16 October 2020
                December 2020
                16 October 2020
                : 13
                : 178-185
                Affiliations
                [a ]School of Biosciences, The Sir Martin Evans Building, Museum Avenue, Cardiff University, Cardiff, Wales, UK
                [b ]Université de Moncton, Campus de Moncton, Pavillon Léopold-Taillon, 18, Avenue Antonine-Maillet, Moncton, New Brunswick, Canada
                [c ]Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
                [d ]Department of Environment, Government of Nunavut, PO Box 209, Igloolik, Nunavut, Canada
                [e ]ArctiConnexion, Québec, Canada
                Author notes
                []Corresponding author. watsons2@ 123456cardiff.ac.uk
                Article
                S2213-2244(20)30094-8
                10.1016/j.ijppaw.2020.10.004
                7591336
                33134077
                59dceb01-09ad-496d-a8fa-43209e840760
                © 2020 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 September 2020
                : 14 October 2020
                : 14 October 2020
                Categories
                Article

                wolverine,helminths,arctic,parasite community,18s sequencing,parasite surveillance

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