Quantifying the Protein Levels of All Nuclear Hormone Receptors by Mass Spectrometry
Bibliographic record
Abstract
Abstract Nuclear Receptors (NRs) are a family of ligand-activated transcription factors that control the expression of genes involved in a wide range of physiological processes. An atlas detailing the expression of all NRs at the mRNA level was completed in 2006 using quantitative PCR [Bookout et al. Cell 2006]. The comparative measurement of NRs at the protein level, however, has been hindered by the poor quality of commercially available antibodies, as well as the absence of a high throughput method for quantitation. To address this need, we are developing a mass spectrometry-based targeted proteomic assay to quantify the absolute amounts of NR protein in a panel of mouse tissues. NRs were overexpressed in HEK293 cells by transient transfection and protein was isolated. The cell lysates were digested with a combination of trypsin and Lys-C following the Multi-Enzyme Digestion Filter Aided Sample Preparation protocol. The peptides were desalted using an in-house made C18 tip, separated on an EASY-Spray C18 column (75 um x 50 cm, 3Å), and analyzed on a Thermo QExactive HF in Top20 data-dependent acquisition mode. Protein identifications were made using MaxQuant software, and the identifications were mined for members of the NR family. The NR peptides detected were searched against an in silico generated list of optimal NR peptides (filtered for uniqueness, length, absence of post translational modifications, and conservation between human and mouse). The matching peptides were validated by parallel reaction monitoring (PRM) and purchased as synthetic isotopes with a heavy terminal arginine or lysine. Peptide linearity, and lower limits of detection (LLOD) were estimated by spiking digests from a C57Bl/6 mouse liver lysate with increasing amounts of the labeled peptides and analyzing by PRM. Peptides that displayed non-linear behavior were excluded for quantitation. The LLOD were between 100 amol and 1.5 fmol on column. A test panel of tissues (cerebrum, hippocampus, cerebellum, liver, spleen, brown/white adipose, and kidney) showed that we could detect endogenous expression of NRs. To date, we have purchased and validated peptides for 44 of the 49 receptors. We used this assay to quantify the changes in NR protein expression in mouse livers in response to 16 hours of fasting. We found significant changes in the nuclear expression of CAR (3.1-fold increase), RXRβ (1.8-fold increase), SHP (3.9-fold decrease) and RARβ (2.0-fold decrease) in the fasted vs. fed state. Increased CAR activity with fasting was further supported by label-free quantitative proteomics on the same lysates which revealed 210 differentially expressed proteins (2-fold change, p<0.05), with 61 (29%) identified as known CAR target genes. Once complete, this assay will provide researchers with a robust quantitative tool to investigate changes in NR protein expression that will be widely applicable to endocrine research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".