Multimodal Imaging\nUnveils the Impact of Nanotopography\non Cellular Metabolic Activities
Nanoscale surface topography is an\neffective approach in modulating\ncell-material interactions, significantly impacting cellular and nuclear\nmorphologies, as well as their functionality. However, the adaptive\nchanges in cellular metabolism induced by the mechanical and geometrical\nmicroenvironment of the nanotopography remain poorly understood. In\nthis study, we investigated the metabolic activities in cells cultured\non engineered nanopillar substrates by using a label-free multimodal\noptical imaging platform. This multimodal imaging platform, integrating\ntwo photon fluorescence (TPF) and stimulated Raman scattering (SRS)\nmicroscopy, allowed us to directly visualize and quantify metabolic\nactivities of cells in 3D at the subcellular scale. We discovered\nthat the nanopillar structure significantly reduced the cell spreading\narea and circularity compared to flat surfaces. Nanopillar-induced\nmechanical cues significantly modulate cellular metabolic activities\nwith variations in nanopillar geometry further influencing these metabolic\nprocesses. Cells cultured on nanopillars exhibited reduced oxidative\nstress, decreased protein and lipid synthesis, and lower lipid unsaturation\nin comparison to those on flat substrates. Hierarchical clustering\nalso revealed that pitch differences in the nanopillar had a more\nsignificant impact on cell metabolic activity than diameter variations.\nThese insights improve our understanding of how engineered nanotopographies\ncan be used to control cellular metabolism, offering possibilities\nfor designing advanced cell culture platforms which can modulate cell\nbehaviors and mimic natural cellular environment and optimize cell-based\napplications. By leveraging the unique metabolic effects of nanopillar\narrays, one can develop more effective strategies for directing the\nfate of cells, enhancing the performance of cell-based therapies,\nand creating regenerative medicine applications.
Publication Details
- Journal
- Figshare
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1021/cbmi.4c00051.s001
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00