Development of a GalNAc-Tyrosine-Specific Monoclonal Antibody and Detection of Tyrosine <i>O</i>-GalNAcylation in Numerous Human Tissues and Cell Lines
Bibliographic record
Abstract
Glycosylation is a vital post-translational modification involved in a range of biological processes including protein folding, signaling, and cell–cell interactions. In 2011, a new type of O -linked glycosylation was discovered, wherein the side-chain oxygen of tyrosine is modified with a GalNAc residue (GalNAc-Tyr). At present, very little is known about GalNAc-Tyr prevalence, function, or biosynthesis. Herein, we describe the design and synthesis of a GalNAc-Tyr-derived hapten and its use in generating a GalNAc-Tyr selective monoclonal antibody. The antibody, G10C, has an unusually high affinity (app K D = 100 pM) and excellent selectivity for GalNAc-Tyr. We also obtained a crystal structure of the G10C Fab region in complex with 4-nitrophenyl- N -acetyl-α- d -galactosaminide (a small molecule mimic of GalNAc-Tyr) providing insights into the structural basis for high affinity and selectivity. Using this antibody, we discovered that GalNAc-Tyr is widely expressed in most human tissues, indicating that it is a ubiquitous and underappreciated post-translational modification. Localization to specific cell types and organ substructures within those tissues indicates that GalNAc-Tyr is likely regulated in a cell-specific manner. GalNAc-Tyr was also observed in a variety of cell lines and primary cells but was only present on the external cell surface in certain cancer cell lines, suggesting that GalNAc-Tyr localization may be altered in cancer cells. Collectively, the results shed new light on this under-studied form of glycosylation and provide access to new tools that will enable expanded biochemical and clinical investigations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".