MétaCan
Menu
← Back to cohort

Ion Channel Activity in a 3‐hydroxyacyl‐coA dehydratase 1 (HACD1) Deficient Muscle Cell Line

2018· article· en· W3175600579 on OpenAlexaboutno aff
Rhiannon Sarah Morgan, Gemma Walmsley, Steven Dyer, Fiona O’Brien, Caroline A. Staunton, Jordan Blondelle, Laurent Tiret, Richard J. Piercy, Richard Barrett‐Jolley

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMyogenesisC2C12MyocyteIon channelBiologyMutationCell biologyPatch clampMyopathyInternal medicineEndocrinologyMolecular biologyGeneticsChemistryMedicineGene

Abstract

fetched live from OpenAlex

Centronuclear myopathy in Labrador retrievers is the most common inherited neuromuscular disorder in dogs: this is caused by a mutation in a fatty acid processing gene, HACD1. The mutation is carried by 15–20% of the breed worldwide (Pele et al., 2005). These dogs present with generalised progressive weakness. A congenital myopathy due to a HACD1 mutation has also been documented in a human family, where infants have hypotonia and delayed motor milestones (Muhammed et al., 2013). The cellular mechanisms by which HACD1 mutation lead to muscle weakness are unknown, but since fatty acids interact with membrane ion channels we hypothesised that dysregulation of membrane function could be involved. To investigate this we have used a muscle cell line (C2C12) with shRNA knock down (KD) of HACD1 in combination with ion channel gene qPCR and patch‐clamp electrophysiology. To quantify changes in C2C12 myogenic differentiation following HACD1 KD, we used a fusion index calculation on day 8 myotubes stained for the differentiation marker MF20 and counted nuclei that were present in MF20 positive myotubes against those that were in undifferentiated, MF20 negative cells. No significant difference in myotube fusion was observed in HACD1‐KD cells compared to control (n=2). Before beginning patch‐clamp studies on C2C12 cells we used qPCR to identify potential ion channel targets in control C2C12 myoblasts. We found expression of (<30ct) of 21 ion channels, including those of particular interest to calcium homeostasis such as the voltage‐gated Ca 2+ channels; Cacna1c, cacna1g, the non‐selective cation (NSC) channels; TRPV4, TRPV2, TRPC1 and a Ca 2+ ‐activated K + channel; Kcnn3. To functionally identify channel gating we used cell‐attached patch‐clamp electrophysiology of control and HACD1‐KD C2C12 myoblasts. K‐means clustering revealed five statistically significant clusters of ion channel activity in these cells ( p <0.05). Assuming an RMP of −15mV (Tanaka et al ., 2017) clusters had centeroids of;(i) conductance 21 ± 0.4pS, Vrev 30 ± 6mV (ii) 28 ± 6pS, −38 ± 4mV (iii) 29 ± 0.7pS, −78 ± 4mV (iv) 40 ± 6pS, 5 ± 3mV (v) 94 ± 13, 16 ± 44mV. In conclusion, the phenotype of the smallest ion channel conductance (28pS) would be consistent with the Ca 2+ ‐activated K + channel KCNN3, and the 94pS consistent with any of the three TRP channels identified by qPCR. These will be further characterised with pharmacological inhibitors and in the future we will examine if the populations change as the control and HACD1‐KD myoblasts differentiate into myotubes. Support or Funding Information Authors would like to thank J Blondelle & L Tiret from the Alfort Veterinary School for the cells used in these experiments. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.013
GPT teacher head0.246
Teacher spread0.234 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicMuscle Physiology and Disorders→French-language works237,207→