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Record W4406883594 · doi:10.1002/jcsm.13705

Characterization of SARS‐CoV‐2 Entry Genes in Skeletal Muscle and Impacts of In Vitro Versus In Vivo Infection

2025· article· en· W4406883594 on OpenAlexafffund
Salyan Bhattarai, Eva Kaufmann, Feng‐Xia Liang, Yumin Zheng, Ekaterina Gusev, Qutayba Hamid, Jun Ding, Maziar Divangahi, Basil J. Petrof

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsQueen's UniversityMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsSkeletal muscleMyogenesisAtrophyMuscle atrophyIn vivoBiologyPathologyIn silicoFurinMedicineProteasesCell biologyVirologyGeneAnatomyEnzymeGeneticsBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: COVID-19 has been associated with both respiratory (diaphragm) and non-respiratory (limb) muscle atrophy. It is unclear if SARS-CoV-2 infection of skeletal muscle plays a role in these changes. This study sought to: 1) determine if cells comprising skeletal muscle tissue, particularly myofibres, express the molecular components required for SARS-CoV-2 infection; 2) assess the capacity for direct SARS-CoV-2 infection and its impact on atrophy pathway genes in myogenic cells; and 3) in an animal model of COVID-19, examine the relationship between viral infection of skeletal muscle and myofibre atrophy within the diaphragm and limb muscles. METHODS: We used in silico bioinformatics analysis of published human single cell RNA-seq datasets, as well as direct qPCR examination of human myotubes and diaphragm biopsies, to assess expression of key genes involved in SARS-CoV-2 cellular entry. In Vitro, we determined the ability of SARS-CoV-2 to directly infect myogenic cells and employed qPCR to assess the impact on muscle atrophy pathway genes (ubiquitin-proteasome, autophagy). In vivo, the diaphragm and quadriceps of Roborovski hamsters with SARS-CoV-2 respiratory infection were examined at day 3 post-inoculation to evaluate the relationship between atrophy pathway and SARS-CoV-2 transcripts by qPCR, as well as histological measurements of myofibre morphology. RESULTS: Angiotensin converting enzyme 2 (ACE2), the primary receptor for SARS-CoV-2, as well as cooperating proteases (furin, cathepsins B and L), are expressed by myofibres. ACE2 expression was increased 5-fold (p = 0.01) in the diaphragms of mechanically ventilated human subjects compared to controls. In Vitro, a time-dependent increase of SARS-CoV-2 transcript levels was observed in myotubes directly exposed to the virus (p = 0.002). This was associated with downregulation of the ubiquitin ligase MuRF1 (by 64%, p = 0.002) and the autophagy gene LC3B (by 31%, p = 0.009). In contrast, in vivo infection led to upregulation of MuRF1 in quadriceps (23-fold, p = 0.0007) and autophagy genes in both quadriceps (5.2-fold for Gabarapl1, p = 0.03; 7-fold for p62, p = 0.0002) and diaphragm (2.2-fold for Gabarapl1, p = 0.03; 2.3-fold for p62, p = 0.057). In infected hamsters the diaphragm lacked viral transcripts but exhibited atrophy (48% decrease in myofibre area; p = 0.02), whereas the quadriceps lacked myofibre atrophy despite elevated viral transcripts in the muscle. CONCLUSIONS: Although myogenic cells express the genes required for SARS-CoV-2 entry and can be directly infected, there was no evident relationship between viral transcript levels and manifestations of atrophy, either in vitro or in vivo. Our results do not support direct myofibre infection by SARS-CoV-2 as a likely cause of atrophy in COVID-19.

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)0.000
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 score0.474
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.268
Teacher spread0.260 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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