Genetically modified human type II collagen for N- and C-terminal covalent tagging
Bibliographic record
Abstract
Abstract Collagen is the predominant structural protein in vertebrates, where it contributes to connective tissues and the extracellular matrix; it is also widely used in biomaterials and tissue engineering. Dysfunction of this protein and its processing can lead to a wide variety of developmental disorders and connective tissue diseases. Recombinantly engineering the protein is challenging due to posttranslational modifications generally required for its stability and secretion from cells. Introducing end labels into the protein is problematic, because the N- and C-termini of the physiologically relevant tropocollagen lie internal to the initially flanking N- and C-propeptide sequences. Here, we introduce mutations into human type II procollagen in a manner that address these concerns, and purify the recombinant protein from a stably transfected HT1080 human fibrosarcoma cell line. Our approach introduces chemically addressable groups into the N- and Ctelopeptide termini of tropocollagen. Simultaneous overexpression of formylglycine generating enzyme (FGE) allows the endogenous production of an aldehyde tag in a defined, substituted sequence in the N-terminus of the mutated collagen, while the C-terminus of each chain presents a sulfhydryl group from an introduced cysteine. These modifications are designed to enable specific covalent end-labelling of collagen. We find that the doubly-mutated protein folds and is secreted from cells, while higher-order assembly into well-ordered collagen fibrils is demonstrated through transmission electron microscopy. Chemical tagging of thiols is successful, however background from endogenous aldehydes present in wildtype collagen has thus far obscured the desired specific N-terminal labelling. Strategies to overcome this challenge are proposed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".