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Record W4282943453 · doi:10.1016/j.isci.2022.104614

Intronic regulation of SARS-CoV-2 receptor (ACE2) expression mediated by immune signaling and oxidative stress pathways

2022· article· en· W4282943453 on OpenAlexafffund
Daniel Richard, Pushpanathan Muthuirulan, Jennifer A. Aguiar, Andrew C. Doxey, Arinjay Banerjee, Karen Mossman, Jeremy A. Hirota, Terence D. Capellini

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of British ColumbiaUniversity of SaskatchewanMcMaster UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaHarvard UniversityCanada Foundation for InnovationNational Science FoundationMinistry of Agriculture of the People's Republic of ChinaNational Sleep Foundation
KeywordsImmune systemBiologyAngiotensin-converting enzyme 2RegulatorOxidative stressSignal transductionReceptorCell biologyRegulation of gene expressionGeneImmunologyDiseaseGeneticsCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)MedicineBiochemistry

Abstract

fetched live from OpenAlex

The angiotensin-converting enzyme 2 (ACE2) protein is a key catalytic regulator of the renin-angiotensin system (RAS), involved in fluid homeostasis and blood pressure modulation. ACE2 also serves as a cell-surface receptor for some coronaviruses such as SARS-CoV and SARS-CoV-2 . Improved characterization of ACE2 regulation may help us understand the effects of pre-existing conditions on COVID-19 incidence, as well as pathogenic dysregulation following viral infection. Here, we perform bioinformatic analyses to hypothesize on ACE2 gene regulation in two different physiological contexts, identifying putative regulatory elements of ACE2 expression. We perform functional validation of our computational predictions via targeted CRISPR-Cas9 deletions of these elements in vitro , finding them responsive to immune signaling and oxidative-stress pathways. This contributes to our understanding of ACE2 gene regulation at baseline and immune challenge. Our work supports pursuit of these putative mechanisms in our understanding of infection/disease caused by current, and future, SARS-related viruses such as SARS-CoV-2 .

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 score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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

Citations14
Published2022
Admission routes2
Has abstractyes

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