Cellular and Molecular Insights into the Divergence of Neural Stem Cells on Matrigel and Poly-l-lysine Interfaces.
Cuiping WuSuru LiuLei ZhouZhengnong ChenQuanjun YangYaqi CuiMing ChenLinpeng LiBingbing KeChunyan LiShan-Kai YinPublished in: ACS applied materials & interfaces (2024)
Poly-l-lysine (PLL) and Matrigel, both classical coating materials for culture substrates in neural stem cell (NSC) research, present distinct interfaces whose effect on NSC behavior at cellular and molecular levels remains ambiguous. Our investigation reveals intriguing disparities: although both PLL and Matrigel interfaces are hydrophilic and feature amine functional groups, Matrigel stands out with lower stiffness and higher roughness. Based on this diversity, Matrigel surpasses PLL, driving NSC adhesion, migration, and proliferation. Intriguingly, PLL promotes NSC differentiation into astrocytes, whereas Matrigel favors neural differentiation and the physiological maturation of neurons. At the molecular level, Matrigel showcases a wider upregulation of genes linked to NSC behavior. Specifically, it enhances ECM-receptor interaction, activates the YAP transcription factor, and heightens glycerophospholipid metabolism, steering NSC proliferation and neural differentiation. Conversely, PLL upregulates genes associated with glial cell differentiation and amino acid metabolism and elevates various amino acid levels, potentially linked to its support for astrocyte differentiation. These distinct transcriptional and metabolic activities jointly shape the divergent NSC behavior on these substrates. This study significantly advances our understanding of substrate regulation on NSC behavior, offering novel insights into optimizing and targeting the application of these surface coating materials in NSC research.
Keyphrases
- amino acid
- transcription factor
- stem cells
- signaling pathway
- neural stem cells
- gene expression
- healthcare
- staphylococcus aureus
- spinal cord
- genome wide
- spinal cord injury
- cell proliferation
- poor prognosis
- deep learning
- dna methylation
- oxidative stress
- mass spectrometry
- extracellular matrix
- neural network
- mesenchymal stem cells
- heat shock protein