Molecular and metabolomic characterization of hiPSC-derived cardiac fibroblasts transitioning to myofibroblasts
Bibliographic record
Abstract
1. Summary Mechanical stress and pathological signaling trigger the activation of fibroblasts to myofibroblasts, which impacts extracellular matrixcomposition, disrupts normal wound healing,andcan generate deleterious fibrosis (Bohl et al., 2008; Sutton and Sharpe, 2000). Myocardial fibrosis independently promotes cardiac arrhythmias, sudden cardiac arrest, and contributes to the severity of heart failure (Frangogiannis, 2021). Fibrosis can also alter cell-to-cell communication and increase myocardial stiffness which eventually may lead to lusitropic and inotropic cardiac dysfunction (PMID: 33135058). Human induced pluripotent stem cell derived cardiac fibroblasts (hiPSC-CFs) have the potential to enhance clinical relevance in precision disease modeling by facilitating the study of patient-specific phenotypes. However, it is unclear whether hiPSC-CFs can be activated to become myofibroblasts akin to primary cells, and the key signaling mechanisms in this process remain unidentified. We hypothesize that the passaging of hiPSC-CFs, like primary cardiac fibroblasts, induces specific genes required for myofibroblast activation and increased mitochondrial metabolism. Passaging of hiPSC-CFs from passage 0 to 3 (P0 to P3) and treatment of P0 with TGFβ1 was associated with a gradual induction of genes to initiate the activation of these cells to myofibroblasts, including collagen, periostin, fibronectin, and collagen fiber processing enzymes with concomitant downregulation of cellular proliferation markers. Most importantly, canonical TGFβ1 and Hippo signaling component genes including TAZ were influenced by passaging hiPSC-CFs. Seahorse assay revealed that passaging and TGFβ1 treatment increased mitochondrial respiration, consistent with fibroblast activation requiring increased energy production, whereas treatment with the glutaminolysis inhibitor BPTES completely attenuated this process. Based on these data, the hiPSC-CF passaging enhanced fibroblast activation, activated fibrotic signaling pathways, and enhanced mitochondrial metabolism approximating what has been reported in primary cardiac fibroblasts. Thus, hiPSC-CFs may provide an accurate in vitro preclinical model for the cardiac fibrotic condition, which may facilitate the identification of putative anti-fibrotic therapies, including patient-specific approaches. Highlights Passaging promotes the activation of fibroblasts to myofibroblasts. TGFβ1 treatment activates the fibroblasts, but their expression profile was uniquely different from myofibroblasts. High energy requiring fibroblast activation is dependent on glutaminase-based mitochondrial metabolism. Passaging induces TGFβ1 and Hippo signaling pathways in activated fibroblasts and myofibroblasts. Graphical Abstract Caption Probing the activation of fibroblasts to myofibroblasts is key in ECM remodeling processes to avoid fibrosis-related adverse complications, and to better understand disease pathology. Here we report that passaging of hiPSC-derived cardiac fibroblasts promotes fibroblast activation along with a gradual shift in gene expression and metabolic changes towards myofibroblasts. TGFβ1 treatment activates non-passaged fibroblasts, but they are dissimilar to myofibroblasts. The energy-intensive fibroblast to myofibroblast activation process is dependent on glutaminase-mediated mitochondrial metabolism and is prevented by treatment with GLS-1 inhibitor BPTES. Our work demonstrates that hiPSC-CFs can offer a preclinical model analogous to primary cardiac fibroblasts that is comparable with passage-mediated myofibroblast activation and increased mitochondrial metabolism. hiPSC-CFs may also facilitate patient-specific novel anti-fibrosis drug screening and disease management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".