Adaptation to ex vivo culture reduces human hematopoietic stem cell activity independently of the cell cycle
Bibliographic record
Abstract
ABSTRACT: Loss of long-term hematopoietic stem cell (LT-HSC) function ex vivo hampers the success of clinical protocols that rely on culture. However, the kinetics and mechanisms through which this occurs remain incompletely characterized. In this study, through time-resolved single-cell RNA sequencing, matched in vivo functional analysis, and the use of a reversible in vitro system of early G1 arrest, we defined the sequence of transcriptional and functional events that occur during the first ex vivo division of human LT-HSCs. We demonstrated that the sharpest loss in LT-HSC repopulation capacity happens early on, between 6 and 24 hours of culture, before LT-HSCs commit to cell cycle progression. During this time window, LT-HSCs adapt to the culture environment, limit the global variability in gene expression, and transiently upregulate gene networks involved in signaling and stress responses. From 24 hours, LT-HSC progression past early G1 contributes to the establishment of differentiation programs in culture. However, contrary to the current assumptions, we demonstrated that the loss of HSC function ex vivo is independent of cell cycle progression. Finally, we showed that targeting LT-HSC adaptation to culture by inhibiting the early activation of JAK/STAT signaling improves HSC long-term repopulating function ex vivo. Collectively, our study demonstrated that controlling early LT-HSC adaptation to ex vivo culture, for example, via JAK inhibition, is critically important to improve HSC gene therapy and expansion protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".