The Development of Xeno-free Culture Substrates for Long-term Culture of Human Pluripotent Stem Cells
Bibliographic record
Abstract
Human pluripotent stem cells (hPSCs) are subject to a highly dynamic microenvironment in the developing embryo, replete with a wide range of biochemical and biophysical cues. Given the transitory and complex nature of pluripotency, efforts to fully understand the factors that maintain hPSCs in vitro can be leveraged for tissue engineering and regenerative medicine applications. In vitro culture methods for hPSCs have largely relied on xenogenic and non-chemically defined culture substrates, namely basement membrane extracts (eg., Matrigel and Geltrex) and supportive feeder layers, while xeno-free culture substrates that support high levels of proliferation and pluripotent marker expression are currently lacking. In this thesis, the role of substrate stiffness and extracellular matrix (ECM) composition in maintaining hPSC pluripotency and proliferation was explored. We first developed a high throughput matrix microarray screening platform capable of tightly controlling substrate stiffness and ECM protein composition. Proof-of-concept screening with this platform identified several non-intuitive matrix and substrate stiffness combinations capable of supporting hPSC pluripotency in long term culture. Subsequently, we employed a bioinformatics and mass spectrometry screening approach to identify novel ECM factors that support hPSC pluripotency. These factors were screened using a design of experiments (DOE) screening strategy on our matrix microarray where we identified a novel matrix condition that outperformed Geltrex in long term culture. Cells grown on this substrate in chemically defined conditions exhibited improved cell survival, increased proliferation, and greater expression of pluripotency factors compared to Geltrex. Through RNA-Seq and phosphoproteome arrays, we determined that an increase in AKT signalling ostensibly drove the observed increase in pluripotency and proliferation on our novel substrate. In summary, the integration of a combinatorial microarray screening platform and statistical modeling facilitated the study of the effect of substrate stiffness and ECM composition on hPSC pluripotency. The optimal hPSC culture substrate developed in this work could be used to permit massive expansion of hPSCs in chemically defined conditions for tissue engineering and regenerative medicine applications. This screening approach can also be applied to other cells to optimally guide cell phenotype.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".