DNA i-motif levels are overwhelmingly depleted in living human cells: insights from in-cell NMR
Bibliographic record
Abstract
Abstract I-Motifs (iM) are non-canonical DNA structures potentially forming in accessible, single-stranded, cytosine-rich genomic regions, with regulatory roles. Chromatin, protein interactions, and intracellular properties seem to govern iM formation at sites with i-motif formation propensity (iMFPS) in human cells, yet their specific contributions remain unclear. Using in-cell NMR with oligonucleotide iMFPS models, we monitored iM-associated structural equilibria in asynchronous and cell cycle-synchronized HeLa cells at 37°C. Our findings show that iMFPS displaying pH T <7 under reference in vitro conditions occur predominantly in unfolded states in cells, while those with pH T >7 occur as a mix of folded and unfolded states depending on the cell cycle phase. Comparing these results with previous data obtained using an iM-specific antibody (iMab) revealed that cell cycle-dependent iM formation has a dual origin and iM formation concerns only a small fraction (possibly 1%) of genomic sites with iM formation propensity. We propose a comprehensive model aligning observations from iMab and in-cell NMR and enabling the identification of iMFPS capable of adopting iM structures under physiological conditions in living human cells. Our results suggest that many iMFPS may have biological roles linked to their unfolded states.
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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 | 0.000 |
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".