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Record W2765662126 · doi:10.3389/fcimb.2017.00452

Increased Expression of a MicroRNA Correlates with Anthelmintic Resistance in Parasitic Nematodes

2017· article· en· W2765662126 on OpenAlexaff
Victoria Gillan, Kirsty Maitland, Roz Laing, Henry Y. Gu, Neil D. Marks, Alan D. Winter, David J. Bartley, Alison Morrison, Philip Skuce, Andrew Rezansoff, John S. Gilleard, Axel Martinelli, Collette Britton, Eileen Devaney

Bibliographic record

VenueFrontiers in Cellular and Infection Microbiology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Calgary
FundersUniversity of GlasgowZoetisScottish GovernmentRural and Environment Science and Analytical Services DivisionAgricultural and Horticultural Development BoardWellcome TrustWellcome
KeywordsBiologyHaemonchus contortusmicroRNATeladorsagia circumcinctaGeneTranscriptomeGeneticsDrug resistanceGene expressionGene expression profilingIvermectinRegulation of gene expressionNematode

Abstract

fetched live from OpenAlex

Resistance to anthelmintic drugs is a major problem in the global fight against parasitic nematodes infecting humans and animals. While previous studies have identified mutations in drug target genes in resistant parasites, changes in the expression levels of both targets and transporters have also been reported. The mechanisms underlying these changes in gene expression are unresolved. Here we take a novel approach to this problem by investigating the role of small regulatory RNAs in drug resistant strains of the important parasite Haemonchus contortus. microRNAs (miRNAs) are small (22 nt) non-coding RNAs that regulate gene expression by binding predominantly to the 3’UTR of mRNAs. Changes in miRNA expression have been implicated in drug resistance in a variety of tumour cells. In this study, we focused on two geographically distinct ivermectin resistant strains of H. contortus and two lines generated by multiple rounds of backcrossing between susceptible and resistant parents, with ivermectin selection. All four resistant strains showed significantly increased expression of a single miRNA, hco-miR-9551, compared to the susceptible strain. This same miRNA is also upregulated in a multi-drug-resistant strain of the related nematode Teladorsagia circumcincta. hco-miR-9551 is enriched in female worms, is likely to be located on the X chromosome and is restricted to clade V parasitic nematodes. Genes containing predicted binding sites for hco-miR-9551 were identified computationally and refined based on differential expression in a transcriptomic dataset prepared from the same drug resistant and susceptible strains. This analysis identified three putative target mRNAs, one, of which, a CHAC domain containing protein, is located in a region of the H. contortus genome introgressed from the resistant parent. hco-miR-9551 was shown to interact with the 3’UTR of this gene by dual luciferase assay. This study is the first to suggest a role for miRNAs and the genes they regulate in drug resistant parasitic nematodes. miR-9551 also has potential as a biomarker of resistance in different nematode species.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.248
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2017
Admission routes1
Has abstractyes

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