Scope of the combinatorial nanoarray cell screening platform – varying parameters can all be contained in the CBC array to match the complexity of natural ECMs and biophysical cues.
Biophysical cues mediated by natural or synthetic extracellular matrices (ECMs) play an essential role in cellular reprogramming. In nature, ECM is structurally complex, spanning a wide range of sizes and hierarchical topographies. However, biomaterials (e.g., hydrogels and nanofibers) used as a synthetic ECM for cellular reprogramming are often designed at a reduced complexity, leading to suboptimal cell-ECM models.
To address the aforementioned issues, Rutgers researchers (https://kblee.rutgers.edu/) have developed a Dynamic Interference Lithography (DIL) and applied the DIL to generate combinatorial ECM libraries with 104-106 unique structural elements for systematically investigating cell-ECM interactions. Further, a quantitative and predictive biophysical cue mapping and assessment approach has been developed to provide insight into ECM-directed cell behaviors such as proliferation, neuronal differentiation, and axonal growth by integrating machine learning-based analytics.
In short, the approach has been implemented and new ECM structures have been discovered for efficient reprogramming of fibroblasts into mature neurons within a short time frame.
- Capable of manufacturing large-scale, comprehensive, and indexable micro/nanoarrays in a highly cost-effective manner
- Highly scalable and reproducible
- A method for manufacturing Combinatorial micro/nano arrays
- Diverse micro/nano arrays for screening unique nano-topographies that control specific cellular phenotypes
- A software for data analysis and nano-topography prediction
- Specific topography for converting skin cells into functional cells such as neurons
Intellectual Property & Development Status: Patent pending. Available for licensing and/or research collaboration.