New Candidate Regulators of Hematopoietic Stem Cells Identified from Transcriptional Comparisons of Highly Purified Populations of Longterm Repopulating Cells with Markedly Different in Vivo Self-Renewal Activities
Bibliographic record
Abstract
Abstract Significant advances have been made in the development of methods for purifying murine hematopoietic cells with longterm (>4 months) in vivo reconstituting ability although these longterm repopulating cells (LTRCs) remain heterogeneous with regard to the self-renewal (SR) activity they display when transplanted into irradiated hosts. Furthermore our group has also identified cell culture conditions that differentially alter LTRC activity without immediate effects on their proliferation or survival. Here, we show that highly purified LTRCs with high and low SR properties can be prospectively isolated from normal adult mouse bone marrow (ABM) as 2 separate populations according to their expression of CD150 within the EPCR++CD48−CD45mid fraction of cells: 56% total LTRCs and 43% of the high SR type in the CD150+ subset vs. 39% total LTRCs and 32% of the low SR type in the CD150− subset (as determined from 62 and 28 single cell transplants, respectively). As a first test of whether these populations would likely be useful to search for new molecular differences associated with their different SR properties, we compared the level of expression in these 2 populations of a small set of genes previously reported to regulate LTRC SR activity: c-Kit, Bmi1, Gata3, Rae28, Ezh2 and Lnk by quantitative real-time PCR (Q-RT-PCR). This exercise revealed transcript levels of the first 4 of these genes to be significantly higher in the CD150+ subset that is selectively enriched in high SR LTRCs, thus validating the concept that they have a distinct molecular signature. Previous evidence shows that high SR LTRCs are present in both FL LTRCs and ABM LTRCs but they differ in some properties (i.e.: cell cycle status, regeneration kinetics). We therefore began a search for ontogeny-independent components of the SR machinery by comparing tags present in 2 LongSAGE libraries produced from CD45midlin−Rho−SP ABM cells and from lin−Sca1+CD43+Mac1+ embryonic day 14.5 fetal liver (FL) cells (each 20–30% total LTRCs and 12–20% of the high SR type, as determined by 132 (FL) and 352 (ABM) single cell transplants, respectively). From these comparisons and additional data in other publicly available datasets for primitive murine hematopoietic cells, we identified 28 genes not previously shown to have a functional role in LTRC SR control. We then compared the level of expression of these 28 genes between the CD150+ subsets of EPCR++CD48−CD45mid ABM cells and FL cells (24% total LTRCs and 12% high SR LTRCs in the FL subset) and their respective downstream lin− progeny. This comparison revealed 10 of these genes to be down-regulated in the lin− populations of both ABM and FL. Further comparison of the expression of these 10 genes between the high vs. low SR LTRCs (found in the CD150+ and CD150− subsets of EPCR++CD48−CD45mid) ABM cells showed the expression of 5 (Vwf, Rhob, Pld3, Prnp and Smarcc2) to be downregulated in the CD150− (low SR LTRC) subset. Interestingly, the first 4 of these genes, as well as 2 of the preliminary set of SR regulators (Bmi1 and Gata3), were also selectively down-regulated in EPCR++CD150+CD48−CD45mid ABM cells that had been incubated for 16 hours in 1 or 10 ng/ml Steel factor + 20 ng/ml IL-11 (conditions that decrease LTRC activity in vivo 4–5-fold before any of these divide or die). Taken together, these results point to the existence of more, although a rather small number of additional genes, including Vwf, Rhob, Pld3, and Prnp, whose products may be involved in controlling the SR potential of normal mouse LTRCs.
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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) | 0.002 | 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".