The Galapagos Chip Platform for High-Throughput Screening of Cell Adhesive Chemical Micropatterns

Urandelger Tuvshindorj, Vanessa Trouillet, Aliaksei Vasilevich, Britta Koch, Steven Vermeulen, Aurélie Carlier, Morgan R Alexander, Stefan Giselbrecht, Roman Truckenmüller, Jan de Boer*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In vivo cells reside in a complex extracellular matrix (ECM) that presents spatially distributed biochemical and -physical cues at the nano- to micrometer scales. Chemical micropatterning is successfully used to generate adhesive islands to control where and how cells attach and restore cues of the ECM in vitro. Although chemical micropatterning has become a powerful tool to study cell-material interactions, only a fraction of the possible micropattern designs was covered so far, leaving many other possible designs still unexplored. Here, a high-throughput screening platform called "Galapagos chip" is developed. It contains a library of 2176 distinct subcellular chemical patterns created using mathematical algorithms and a straightforward UV-induced two-step surface modification. This approach enables the immobilization of ligands in geometrically defined regions onto cell culture substrates. To validate the system, binary RGD/polyethylene glycol patterns are prepared on which human mesenchymal stem cells are cultured, and the authors observe how different patterns affect cell and organelle morphology. As proof of concept, the cells are stained for the mechanosensitive YAP protein, and, using a machine-learning algorithm, it is demonstrated that cell shape and YAP nuclear translocation correlate. It is concluded that the Galapagos chip is a versatile platform to screen geometrical aspects of cell-ECM interaction.

Original languageEnglish
Article number2105704
Number of pages15
JournalSmall
Volume18
Issue number10
Early online date5 Jan 2022
DOIs
Publication statusPublished - Mar 2022

Keywords

  • high-throughput screening
  • machine learning
  • mechanosensing
  • micropatterning
  • silane surface modification
  • thiol-ene click chemistry
  • YAP
  • SELF-ASSEMBLED MONOLAYERS
  • EXTRACELLULAR-MATRIX
  • POLYMER BRUSHES
  • SURFACE MODIFICATION
  • PROTEIN ADSORPTION
  • GEOMETRIC CUES
  • STEM-CELLS
  • BIOMATERIALS
  • INTEGRIN
  • SHAPE

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