p53-TP53-Induced Glycolysis Regulator Mediated Glycolytic Suppression Attenuates DNA Damage and Genomic Instability in Fanconi Anemia Hematopoietic Stem Cells
Bibliographic record
Abstract
Abstract Emerging evidence has shown that resting quiescent hematopoietic stem cells (HSCs) prefer to utilize anaerobic glycolysis rather than mitochondrial respiration for energy production. Compelling evidence has also revealed that altered metabolic energetics in HSCs underlies the onset of certain blood diseases; however, the mechanisms responsible for energetic reprogramming remain elusive. We recently found that Fanconi anemia (FA) HSCs in their resting state are more dependent on mitochondrial respiration for energy metabolism than on glycolysis. In the present study, we investigated the role of deficient glycolysis in FA HSC maintenance. We observed significantly reduced glucose consumption, lactate production, and ATP production in HSCs but not in the less primitive multipotent progenitors or restricted hematopoietic progenitors of Fanca−/− and Fancc−/− mice compared with that of wild-type mice, which was associated with an overactivated p53 and TP53-induced glycolysis regulator, the TIGAR-mediated metabolic axis. We utilized Fanca−/− HSCs deficient for p53 to show that the p53-TIGAR axis suppressed glycolysis in FA HSCs, leading to enhanced pentose phosphate pathway and cellular antioxidant function and, consequently, reduced DNA damage and attenuated HSC exhaustion. Furthermore, by using Fanca−/− HSCs carrying the separation-of-function mutant p53R172P transgene that selectively impairs the p53 function in apoptosis but not cell-cycle control, we demonstrated that the cell-cycle function of p53 was not required for glycolytic suppression in FA HSCs. Finally, ectopic expression of the glycolytic rate-limiting enzyme PFKFB3 specifically antagonized p53-TIGAR-mediated metabolic reprogramming in FA HSCs. Together, our results suggest that p53-TIGAR metabolic axis-mediated glycolytic suppression may play a compensatory role in attenuating DNA damage and proliferative exhaustion in FA HSCs. Stem Cells 2019;37:937–947
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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 | 0.000 | 0.001 |
| 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".