Divergent Levels of CD112 and INKA1 Define a Subset of Human Hematopoietic Stem Cells That Resists Regenerative Stress to Preserve Stemness
Bibliographic record
Abstract
The first insight into the complexity of post-transplant in vivo dynamics of hematopoietic stem cells (HSC) in humans was only recently showcased by examining longitudinal clonal contributions in gene therapy patients. Initial blood reconstitution was achieved by short-term (ST-)HSC, but in the longer-term hematopoiesis originated from long-term (LT-)HSC that only became recruited after a latency phase of 1-2 years (Scala et al 2018). Thus, deciphering the mechanisms governing how LT-HSC might resist transplant mediated activation and/or respond to the varying hematopoietic demands that occur during homeostasis would be an important goal for improving HSC cell therapies. We previously linked INKA1(=C3orf54/FAM212A) mediated PAK4 inhibition and reduced H4K16 acetylation (H4K16ac) to quiescence in human leukemia stem cells (Kaufmann, Blood 2019). Here, we interrogate the role of this signaling axis in normal human hematopoiesis. Immunostaining revealed distinct subsets defined by the dichotomy of INKA1 and H4K16ac within cord blood ST- and LT-HSC, mechanistically supported by BioID, chromatin fiber analysis and PLA data showing INKA1 interacting with the H4K16 deacetylase, SIRT1. Among quiescent LT-HSC, we found that the INKA1high fraction (~10 % of LT-HSC) had the lowest CDK6 levels and represented LT-HSC in an alternative state of quiescence. We then used protein interaction (BioID) data to show that a shared interactor of INKA1 and PAK4, CD112 could be used to sort for the subset of CD112low LT-HSC that was in this alternatively quiescent LT-HSC state (H4K16aclow, CDK6low, CellROXlow). Compared to primary cells, culture attenuates the strict dichotomy of INKA1 and H4K16ac but only in cells in which colocalization of PAK4 with both occurred, suggesting PAK4 interferes with SIRT1-INKA1 interaction thereby permitting H4K16 acetylation. In vitro time course analysis showed that H4K16ac and PAK4 levels preceded the upregulation of the G0-exit marker CDK6 implicating a role in cell cycle priming. Pseudo-time scRNAseq analysis for INKA1high versus PAK4high, CDK6high and CD112high expression in mobilized peripheral blood (modeling in vivo HSC activation) showed enrichment of early or late diffusion indicative of quiescent versus primed cell status, respectively. Strikingly, in xenograft assays CD112low LT-HSC exhibited delayed engraftment kinetics with higher secondary repopulation capacity than faster repopulating CD112high LT-HSC reflecting the subset of LT-HSC that resist early activation. Similarly, INKA1-OE or PAK4 knock-down in vivo resulted in an early restraint in engraftment levels (@4 w), whereas 20 w engraftment reached control levels. When measured in secondary transplant assays the HSC frequency was 4 to 8-fold higher in the groups that showed this early restraint. Thus, resisting early activation (latency) preserves the regenerative potential of such HSC. In vivo 5-Fluorouracil treatment at week 4 accelerated latency exit and further increased HSC frequency of INKA1-OE cells while abolishing serial transplantation potential of controls. Hence, the induction of proliferative stress via creating acute hematopoietic demand is able to lift the INKA1-OE imposed restraint resulting in increased hematopoietic output while also promoting HSC self-renewal. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir. Disclosures Takayanagi: Kirin Holdings Company, Ltd: Current Employment. Dick:Bristol-Myers Squibb/Celgene: Research Funding.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".