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Record W4390051658 · doi:10.1186/s13071-023-06035-1

Identification of Trichinella taxa by ITS-1 amplicon next-generation sequencing with an improved resolution for detecting underrepresented genotypes in mixed natural infections

2023· article· en· W4390051658 on OpenAlexafffundabout
Vladislav A. Lobanov, Kelly Konecsni, W. Brad Scandrett, Emily Jenkins

Bibliographic record

VenueParasites & Vectors · 2023
Typearticle
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsUniversity of SaskatchewanCanadian Food Inspection Agency
FundersCanadian Wildlife Health CooperativeIran Telecommunication Research CenterMinistry of Forests, Lands and Natural Resource OperationsCanadian Food Inspection Agency
KeywordsBiologyAmpliconParasitologyGenotypeTrichinellaIdentification (biology)TaxonGenotypingHigh Resolution MeltAmplicon sequencingComputational biologyGeneticsVeterinary medicineEvolutionary biologyZoologyPolymerase chain reactionGeneHelminthsEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Amplicon-based next-generation sequencing (NGS) has rapidly gained popularity as a powerful method for delineating taxa in complex communities, including helminths. Here, we applied this approach to identify species and genotypes of zoonotic nematodes of the Trichinella genus. A known limitation of the current multiplex PCR (mPCR) assay recommended by the International Commission on Trichinellosis is that it does not differentiate Trichinella nativa from T. chanchalensis. METHODS: The new assay entails deep sequencing of an amplified variable fragment of the ribosomal cistron's (rDNA) internal transcribed spacer 1 using the Illumina platform. The assay was evaluated using first-stage larvae (L1) of select laboratory strains of various Trichinella taxa mixed in known proportions and then validated using archived L1 from 109 wildlife hosts. The species/genotypes of these L1 isolates from wildlife were previously determined using mPCR. RESULTS: NGS data analysis for Trichinella laboratory strains selected as representative of North American fauna revealed a sequence representation bias. Trichinella pseudospiralis, a non-encapsulated species, was the most underrepresented when mixed with T. spiralis, T. murrelli, T. nativa and Trichinella T6 in equal quantities. However, five L1 of T. pseudospiralis were readily revealed by NGS in a mix with 2000 L1 of T. nativa (1:400 ratio). From naturally infected wildlife, all Trichinella taxa revealed by mPCR were also identified by NGS in 103 of 107 (96.3%) samples amplified on both assays. NGS identified additional taxa in 11 (10.3%) samples, whereas additional taxa were revealed by mPCR in only four (3.7%) samples. Most isolates comprised single or mixed infections of T. nativa and Trichinella T6. On NGS, T. chanchalensis (T13) was detected in combination with Trichinella T6 in a wolverine (Gulo gulo) and in combination with T. nativa and Trichinella T6 in a marten (Martes americana) from the Northwest Territories, Canada. CONCLUSIONS: This new NGS assay demonstrates strong potential as a single assay for identifying all recognised Trichinella taxa as well as improved sensitivity for detecting under-represented and novel genotypes in mixed infections. In addition, we report a new host record for T. chanchalensis in American marten.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.351
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes3
Has abstractyes

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