Disease-Causing Mitochondrial Heteroplasmy Segregated Within Induced Pluripotent Stem Cell Clones Derived from a Patient with MELAS
Bibliographic record
Abstract
Mitochondrial diseases display pathological phenotypes according to the mixture of mutant versus wild-type mitochondrial DNA (mtDNA), known as heteroplasmy. We herein examined the impact of nuclear reprogramming and clonal isolation of induced pluripotent stem cells (iPSC) on mitochondrial heteroplasmy. Patient-derived dermal fibroblasts with a prototypical mitochondrial deficiency diagnosed as mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) demonstrated mitochondrial dysfunction with reduced oxidative reserve due to heteroplasmy at position G13513A in the ND5 subunit of complex I. Bioengineered iPSC clones acquired pluripotency with multilineage differentiation capacity and demonstrated reduction in mitochondrial density and oxygen consumption distinguishing them from the somatic source. Consistent with the cellular mosaicism of the original patient-derived fibroblasts, the MELAS-iPSC clones contained a similar range of mtDNA heteroplasmy of the disease-causing mutation with identical profiles in the remaining mtDNA. High-heteroplasmy iPSC clones were used to demonstrate that extended stem cell passaging was sufficient to purge mutant mtDNA, resulting in isogenic iPSC subclones with various degrees of disease-causing genotypes. On comparative differentiation of iPSC clones, improved cardiogenic yield was associated with iPSC clones containing lower heteroplasmy compared with isogenic clones with high heteroplasmy. Thus, mtDNA heteroplasmic segregation within patient-derived stem cell lines enables direct comparison of genotype/phenotype relationships in progenitor cells and lineage-restricted progeny, and indicates that cell fate decisions are regulated as a function of mtDNA mutation load. The novel nuclear reprogramming-based model system introduces a disease-in-a-dish tool to examine the impact of mutant genotypes for MELAS patients in bioengineered tissues and a cellular probe for molecular features of individual mitochondrial diseases.
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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) | 0.001 | 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".