Organelle Cooperation in Stem Cell Fate: Lysosomes as Emerging Regulators of Cell Identity
Bibliographic record
Abstract
Regulation of stem cell fate is best understood at the level of gene and protein regulatory networks, though it is now clear that multiple cellular organelles also have critical impacts. A growing appreciation for the functional interconnectedness of organelles suggests that an orchestration of integrated biological networks functions to drive stem cell fate decisions and regulate metabolism. Metabolic signaling itself has emerged as an integral regulator of cell fate including the determination of identity, activation state, survival, and differentiation potential of many developmental, adult, disease, and cancer-associated stem cell populations and their progeny. As the primary adenosine triphosphate-generating organelles, mitochondria are well-known regulators of stem cell fate decisions, yet it is now becoming apparent that additional organelles such as the lysosome are important players in mediating these dynamic decisions. In this review, we will focus on the emerging role of organelles, in particular lysosomes, in the reprogramming of both metabolic networks and stem cell fate decisions, especially those that impact the determination of cell identity. We will discuss the inter-organelle interactions, cell signaling pathways, and transcriptional regulatory mechanisms with which lysosomes engage and how these activities impact metabolic signaling. We will further review recent data that position lysosomes as critical regulators of cell identity determination programs and discuss the known or putative biological mechanisms. Finally, we will briefly highlight the potential impact of elucidating mechanisms by which lysosomes regulate stem cell identity on our understanding of disease pathogenesis, as well as the development of refined regenerative medicine, biomarker, and therapeutic strategies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".