Simple and Efficient Production and Purification of Mouse Myelin Oligodendrocyte Glycoprotein for Experimental Autoimmune Encephalomyelitis Studies
Bibliographic record
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS), thought to occur as a result of autoimmune responses targeting myelin. Experimental autoimmune encephalomyelitis (EAE) is the most common animal model of CNS autoimmune disease, and is typically induced via immunization with short peptides representing immunodominant CD4+ T cell epitopes of myelin proteins. However, B cells recognize unprocessed protein directly, and immunization with short peptide does not activate B cells that recognize the native protein. As recent clinical trials of B cell-depleting therapies in MS have suggested a role for B cells in driving disease in humans, there is an urgent need for animal models that incorporate B cell-recognition of autoantigen. To this end, we have generated a new fusion protein containing the extracellular domain of the mouse version of myelin oligodendrocyte glycoprotein (MOG) as well as N-terminal fusions of a His-tag for purification purposes and the thioredoxin protein to improve solubility (MOGtag). A tobacco etch virus (TEV) protease cleavage site was incorporated to allow the removal of all tag sequences, leaving only the pure MOG1-125 extracellular domain. Here, we describe a simple protocol using only standard laboratory equipment to produce large quantities of pure MOGtag or MOG1-125. This protocol consistently generates over 200 mg of MOGtag protein. Immunization with either MOGtag or MOG1-125 generates an autoimmune response that includes pathogenic B cells that recognize the native mouse MOG.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".