Rescue of aged muscle stem cell quiescence defects by AKT inhibition revealed with a 3D biomimetic culture assay
Bibliographic record
Abstract
Abstract Adult skeletal muscle harbors a population of muscle stem cells (MuSCs) that are required to repair or reform multinucleated myofibers after tissue injury. In youth, MuSCs return to a reversible state of cell cycle arrest termed ‘quiescence’ after injury resolution. By contrast, a proportion of MuSCs in aged muscle remain in a semi-activated state, causing a premature response to subsequent injury cues that results in incomplete tissue repair and eventual stem cell depletion. Regulation of the balance between MuSC quiescence and activation in youth and in age may hold the key to restoring tissue homeostasis with age, but is incompletely understood. To fill this gap, we developed a simple and tractable in vitro method, with a 96-well footprint, to rapidly inactivate MuSCs freshly isolated from young skeletal muscle tissue, and return them to a quiescent-like state for at least one-week. This was achieved by introducing MuSCs into a three-dimensional (3D) bioartificial niche comprised of a thin sheet of multinucleated myotubes, which we iterate, and analyze temporally, to show that these in vivo niche features provide the minimal cues necessary to inactivate MuSCs and induce quiescence. By seeding the 3D myotube sheets with different starting numbers of MuSCs, the assay revealed cellular heterogeneity and population-level adaptation activities that converged on a common steady-state niche repopulation density; behaviors previously observed only in vivo . Quiescence-associated hallmarks included a Pax7 + CalcR + MyoD - c-FOS - molecular signature, in vivo quiescent-like morphologies including oval-shaped nuclei and long cytoplasmic projections with N-cadherin + tips, as well as the acquisition of polarized niche markers. Leveraging high-content imaging and bespoke CellProfiler TM -based image analysis pipelines, we demonstrate a relationship between morphology and cell fate signatures opening up the possibility of real-time morphology-based screening. Notably, when MuSCs from aged muscle were introduced into the assay, they displayed aberrant proliferative activities, delayed inactivation kinetics, persistence of activation-associated morphologies, and population depletion; quiescence-associated defects that we show are rescued by wortmannin treatment. Thus, the miniaturized assay offers an unprecedented opportunity to systematically investigate long-standing queries in areas such as regulation of adult stem cell pool size and functional heterogeneity within the MuSC population, and to uncover regulators of quiescence in youth and in age.
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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 | 0.000 | 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 | 0.001 |
| 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".