Development of a Novel NOD/SCID Transplant System That Provides Enhanced Detection of Rapid-SRC and Insight into Their Self-Renewal and Mobilization.
Bibliographic record
Abstract
Abstract The conventional NOD/SCID xenotransplant model provides a powerful tool to characterize human hematopoietic stem cells. This system relies on IV injection of transplanted cells, with subsequent circulation through the blood prior to homing to appropriate niches. Two major limitations of this model are the presence of residual host factors that resist engraftment (i.e. NK cells and macrophages) and inability to detect stem cells that are incapable of homing or surviving in the circulation. We previously showed that rapid-SRC (R-SRC) were more efficiently detected by direct intrafemoral (IF) injection compared to IV transplantation (Nat Med 2003). Additionally, others showed that depletion of NK cell activity detects a short-term repopulating cell indicating that immune recognition is also important. R-SRC are found in the Lin-CD34+CD38+/lo population and produce a robust human erythromyeloid graft 2 weeks post-transplant. R-SRC are critical for stem cell therapies that require rapid engraftment and their characterization requires an efficient assay. To determine the role of cellular resistance factors we compared human engraftment in NOD/SCID mice, NOD/SCID-B2 microglobulin-null (NOD/SCID-B2m−/−) mice that are depleted of NK cells, or we administered a neutralizing antibody against the IL-2R B-chain (CD122) to NOD/SCID mice. CD122 depletes several populations including NK cells and macrophages. 4–5 x 104 Lin-CD34+CD38lo cells purified from CB were injected IF or IV into these recipients and human engraftment was determined at 2 weeks post-transplant to assay for R-SRC. In addition to determining engraftment levels, we also used the IF assay to gain insight into migration/mobilization function of R-SRC by examining human engraftment in other bones. Human myelolymphoid (CD45+) engraftment in the injected femur (RF) was significantly higher (p<0.05) in IF injected anti-CD122 treated NOD/SCID mice compared to all other groups. Since IF NOD/SCID-B2M−/ − mice had the next highest engraftment levels, these data indicate that R-SRC are very sensitive to NK activity. However the data clearly show that CD122+ cells also play a significant role in resisting stem cell engraftment. Importantly, CD122+ cells markedly affected R-SRC migration/mobilization since there was significantly higher engraftment in non-injected bones from anti-CD122 treated mice even when compared to the NOD/SCID-B2M−/ − mice. Our previous clonal analysis showed that R-SRC that are found in non-injected bones also self-renew in the injected bone before migration. We conclude that in addition to NK cells, CD122+ cells (likely macrophages) prevent the direct engraftment of R-SRC when delivered by IF or IV injection as well as their subsequent in vivo self-renewal and/or migration. Modification to the standard NOD/SCID assay by IF injection in combination with anti-CD122 provides a powerful tool to identify novel populations of stem cells as well as insight into fundamentally important properties of stem cell biology and transplantation. Mouse (n) Injection Tissue CD45+ (%) Erythroid (CD45-CD36+glyA+ (%) Total * RF-injected rt femur;BM-noninjected lt femur, pelvis, two tibiae;glyA-glycophorinA;*-total CD45+plus CD45-erythroid engraftment NOD/SCID anti-CD122 (15) IF RF 13.2 41.4 54.6 BM 4.9 23.3 28.1 NOD/SCID anti-CD122 (18) IV RF 5.3 26.5 31.8 BM 6.6 33.5 40.1 NOD/SCID (13) IF RF 3.6 11.9 15.5 BM 0.9 2.6 3.5 NOD/SCID (15) IV RF 1.4 3.9 5.3 BM 1.3 4.2 5.5 NOD/SCID/B2M−/ − (6) IF RF 7.2 31.9 39.1 BM 1.8 7.0 8.8 NOD/SCID/B2M−/ − (9) IV RF 3.5 4.9 8.3 BM 3.4 9.4 12.8
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".