Rational Generation of Monoclonal Antibodies and Intrabodies Selective for Pathogenic TDP-43
Bibliographic record
Abstract
ABSTRACT TAR DNA-binding protein 43 (TDP-43), encoded by the TARDBP gene, is a ribonucleoprotein associated with the pathogenesis of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer’s disease (AD). Under physiological conditions, TDP-43 is predominantly localized in the nucleus, where it participates in a variety of cellular functions related to RNA splicing, transport, and stability, as well as miRNA biogenesis. In disease, it is disproportionately mislocalized to the cytoplasm where it forms aggregates, which contribute to neurotoxicity and prion-like cell-to-cell propagation of pathogenic TDP-43. Targeting of misfolded aggregates of TDP-43 represents an attractive therapeutic strategy. However, development of effective immunotherapeutic agents remains a challenge, as they require stringent selectivity for misfolded TDP-43 in order to maintain the essential functions of physiologically native TDP-43. To address this issue, monoclonal antibodies (mAbs) and intrabodies were generated against an epitope in the N-terminal domain of TDP-43 that is only exposed when the protein is misfolded, but not in its properly folded form. We show that mouse and rabbit mAbs against this epitope displayed high binding affinities by surface plasmon resonance analysis and selectively reacted with pathological TDP-43 in post-mortem tissues from ALS, FTD, and AD patients. In a cell line system, human embryonic kidney (HEK) 293T cells, mAbs and corresponding intrabodies specifically reacted with cytoplasmic aggregates of transfected misfolded TDP-43 lacking the nuclear localization signal, TDP-43 ΔNLS . Functionally, mAbs inhibited cell-to-cell transmission of misfolded TDP-43 and the seeding activity of misfolded TDP-43 from FTLD brain homogenates by a novel RT-QuIC assay. Intrabodies promoted the degradation of intracellular aggregates of TDP-43 in HEK293T cells and in induced pluripotent stem cell-derived motor neurons (iPSC-MNs) from ALS patients. The results provide proof-of-concept evidence that supports selective targeting of misfolded toxic aggregates of TDP-43 as a potentially safe and effective avenue to treat neurodegenerative diseases associated with TDP-43 proteinopathy.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".