Understanding the biosynthesis of human IgMs through a combinatorial expression of mutant subunits that affect different assembly steps
Bibliographic record
Abstract
Abstract Polymeric IgMs are secreted from plasma cells abundantly despite their structural complexity and intricate multimerization steps. To gain new insights into IgM’s assembly mechanics that underwrite the high-level secretion, we characterized the biosynthetic process of a natural human IgM, SAM-6, using a recombinant HEK293 cell system. By creating a series of mutant subunits that differentially disrupt specific sets of inter-chain disulfide bonds, we assessed their effects on various aspects of IgM biosynthesis in 48 different mutant subunit combinations. The analysis included the visualization of intracellular biosynthetic events such as steady-state subcellular subunit distribution, secretory trafficking bottlenecks, and the ER-associated Russell body formation by fluorescent microscopy. We also characterized various extracellular events including secreted IgM product quality, secretion output, and the release of various assembly intermediates using biochemical and biophysical assays. In this combinatorial mutagenesis approach, we unexpectedly found that the loss of multiple inter-chain disulfide bonds, including the one between μHC and λLC subunits, was tolerated in polymeric IgM formation and secretion. This finding revealed the vital role of underlying non-covalent protein-protein association not only during the orchestration of initial subunit interactions but also in maintaining the polymeric IgM product integrity during ER quality control steps, secretory pathway trafficking, and secretion. We suggest that the IgM assembly process is inherently robust and has a stopgap that permits the secretion of polymeric IgM even when not all the prescribed inter-chain disulfide bonds are formed. This study holistically presents the requirements and exemptions in polymeric IgM biosynthesis by encompassing the characterization of intracellular and extracellular events and the roles of covalent and non-covalent interactions. These findings can guide antibody engineering strategy when designing IgM-based multivalent modalities.
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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) | 0.000 | 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 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".