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Record W4387380472 · doi:10.1210/jendso/bvad114.1771

OR33-03 Circadian Analysis Of Nuclear Receptor Protein Expression In Mouse Liver Reveals Peak COUP-TFII, EAR2, LXRa, LXRb And TR4 Expression At The End Of The Mouse Active Cycle ZT0

2023· article· en· W4387380472 on OpenAlexafffundabout
Michael F. Saikali, Jia Xu Li, Carolyn L. Cummins

Bibliographic record

VenueJournal of the Endocrine Society · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNuclear receptorMolecular biologyChemistryCircadian rhythmTranscription factorMass spectrometryBiologyReceptorChromatographyBiochemistryGeneEndocrinology

Abstract

fetched live from OpenAlex

Abstract Disclosure: M.F. Saikali: None. J. Li: None. C.L. Cummins: None. Nuclear Receptors (NRs) are a family of ligand-mediated transcription factors that control the expression of genes involved in a wide range of physiological processes. The ability to study NRs quantitatively at the protein level has been hindered by the poor quality of available antibodies, as well as the lack of available high throughput methods to study more than a few receptors at a time. To address this need, we have developed a mass spectrometry based targeted proteomic assay to quantify the absolute amounts of NR protein in mouse livers over a circadian period. C57Bl6 mice were sacrificed at 12 weeks every 4 hours from zeitgeber time ZT0 to ZT20. Their livers were processed using a transcription factor extraction protocol1. For each sample, 100 µg nuclear protein was processed using the NR assay described previously2. Briefly, the lysate is digested following the Multi-Enzyme Digestion Filter Aided Sample Preparation protocol. The sample is then spiked with 50 fmol of our internal standard mix. This mix is composed of 66 carefully selected peptides that account for 49 NRs, 11 histone peptides, and 6 circadian clock proteins. The resulting digest that contains the internal standards is desalted on C18 tips, followed by separation on an EASY-Spray C18 column (75 um x 50 cm, 3Å), and analyzed on a Thermo QExactive HF mass spectrometer in parallel reaction monitoring mode. We used this assay to quantify the changes in NR protein expression in mouse livers for 9 receptors; RORα, CAR, COUP-TFII, EAR2, GR, LXRα, LXRβ, PPARα, and TR4. RORα showed peak nuclear expression at ZT0, with a peak-to-trough change of 2.2-fold. COUP-TFII, EAR2, LXRα, LXRβ, and TR4 also showed peak expression at ZT0 (the end of the active phase) with changes of 3.3, 2.4, 1.7, 2.0, and 1.6-fold respectively. GR showed peak nuclear expression at ZT12 with a 1.8-fold change. CAR showed 2.3-fold peak expression at ZT16. COUP-TFII, EAR2, and TR4 are considered orphan receptors with no known endogenous ligands. These data will be used to uncover endogenous tissue-specific ligands by analyzing extracts isolated at the zeitgeber time that the receptor is maximally expressed. Sources of Research Support: This project has been supported by the J. P. Bickell Foundation and the Canadian Institutes of Health Research New Frontiers Research Fund and International Development Research Fund. 1.Gillespie, M. A. et al. Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis. Mol Cell (2020) doi:10.1016/j.molcel.2020.03.031.2.Saikali, M. F. & Cummins, C. L. Quantifying the Protein Levels of All Nuclear Hormone Receptors by Mass Spectrometry. J Endocr Soc5, (2021). Presentation: Sunday, June 18, 2023

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 score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.231
Teacher spread0.225 · 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
Published2023
Admission routes3
Has abstractyes

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