Detection of Parathyroid Hormone Receptor 1 (PTH1R): A Novel Approach Using Enzymatic Ligands Applicable to Class B GPCRs
Bibliographic record
Abstract
BACKGROUND Class B GPCRs (receptors of the secretin family) are characterised by long C‐ and N‐terminal domains as well as by their binding of large peptide hormones. One of those, parathyroid hormone (PTH), has been reported to support C‐terminal extension without significant affinity loss for PTH1R. Indeed, the N‐terminal domain of PTH that interacts with the transmembrane domains of PTH1R leading to the activation of this receptor whereas the C‐terminal domain of PTH is involved in affinity interactions. Accordingly, we previously described a fusion protein based on the enhanced green fluorescent protein (EGFP), PTH‐EGFP. This fusion protein supported the detection of recombinant PTH1Rs, but failed to detect endogenous populations of this receptor. The objective of this study is to develop new fusion protein ligands with enzymatic activity which would allow the detection of endogenously expressed PTH1R. METHODS To detect endogenous populations of PTH1R, we generated two new fusion proteins by linking PTH to the N‐terminal of a peroxidase. These peroxidases were either the horseradish peroxidase (HRP; PTH‐HRP) or the genetically modified soybean peroxidase APEX2 (PTH‐APEX2). Reaction of receptor‐bound enzymatic PTH‐fusion protein with widely available substrates allowed a significant signal amplification resulting in the detection of PTH1R. Alternatively, we also used the previously reported ligand PTH‐myc. The myc epitope (EQKLISEEDL) reacts with a number of monoclonal antibodies, some of them conjugated to a peroxidase. The three PTH‐fusion proteins were produced as conditioned medium (CM) following transfection of producer HEK 293a cells with the appropriate vector. RESULTS The stimulation of recipient HEK 293a expressing PTH1R with a trimolecular complex composed of PTH‐myc, a monoclonal mouse anti‐myc antibody and an anti‐mouse HRP‐conjugated antibody led to the specific detection of this receptor either using a colorimetric peroxidase substrate (TrueBlue ™ ) or a luminol‐based luminescent peroxidase substrate. These schemes also supported the detection of endogenously expressed receptors in the osteoblastic cell line HOS. The PTH‐APEX2 CM also supported the detection of recombinant populations of PTH1R using the colorimetric or luminescent approach but failed to detect endogenous populations of PTH1R. However, the PTH‐HRP construction was more sensitive and allowed the detection of endogenously expressed PTH1R in HOS and evidenced recombinant PTH1R as well. The specificity of the PTH1R labeling was confirmed by competing the binding of the PTH fusion proteins by an excess of PTH1R ligand (PTH1‐34 1 μM). CONCLUSIONS Given that anti‐GPCRs antibodies are rarely valid and adapted to detect cell surface receptors, we proposed to detect intact receptors using the high affinity and specificity interaction between the receptor and its ligand. We illustrated this by generating PTH analogs prolonged at their C‐terminal by peroxidases or by an epitope recognized by widely available monoclonal antibodies that support enzymatic detection of PTH1R. Since all class B GPCRs ligands bind their receptor according to the two domain model, it could be possible to generalize the enzymatic ligand strategy to all the class B GPCRs. Support or Funding Information CHU de Québec ‐ Université Laval, Quebec City, QC, Canada G1V 4G2
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".