Noncovalent hyaluronan crosslinking by TSG-6: Modulation by heparin, heparan sulfate, and PRG4
Bibliographic record
Abstract
The size, conformation, and organization of the glycosaminoglycan hyaluronan (HA) affect its interactions with soluble and cell surface-bound proteins. HA that is induced to form stable networks has unique biological properties relative to unmodified soluble HA. AlphaLISA assay technology offers a facile and general experimental approach to assay protein-mediated networking of HA in solution. Connections formed between two end-biotinylated 50 kDa HA (bHA) chains can be detected by signal arising from streptavidin-coated donor and acceptor beads being brought into close proximity when the bHA chains are bridged by proteins. We observed that incubation of bHA with the protein TSG-6 (tumor necrosis factor alpha stimulated gene/protein 6, TNFAIP/TSG-6) leads to dimerization or higher order multimerization of HA chains in solution. We compared two different heparin (HP) samples and two heparan sulfate (HS) samples for the ability to disrupt HA crosslinking by TSG-6. Both HP samples had approximately three sulfates per disaccharide, and both were effective in inhibiting HA crosslinking by TSG-6. HS with a relatively high degree of sulfation (1.75 per disaccharide) also inhibited TSG-6 mediated HA networking, while HS with a lower degree of sulfation (0.75 per disaccharide) was less effective. We further identified Proteoglycan 4 (PRG4, lubricin) as a TSG-6 ligand, and found it to inhibit TSG-6-mediated HA crosslinking. The effects of HP, HS, and PRG4 on HA crosslinking by TSG-6 were shown to be due to HP/HS/PRG4 inhibition of HA binding to the Link domain of TSG-6. Using the AlphaLISA platform, we also tested other HA-binding proteins for ability to create HA networks. The G1 domain of versican (VG1) effectively networked bHA in solution but required a higher concentration than TSG-6. Cartilage link protein (HAPLN1) and the HA binding protein segment of aggrecan (HABP, G1-IGD-G2) showed only low and variable magnitude HA networking effects. This study unambiguously demonstrates HA crosslinking in solution by TSG-6 and VG1 proteins, and establishes PRG4, HP and highly sulfated HS as modulators of TSG-6 mediated HA crosslinking.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".