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Automatic Multi-functional Integration Program (AMFIP) towards all-optical mechano-electrophysiology interrogation.

Qin Luo1, Justin Zhang2, Miao Huang3

  • 1Department of Electrical and Computer Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida, United States of America.

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A new open-source software, AMFIP, enables automatic live-cell imaging operations for microscopy systems without extra hardware. This cost-free solution allows cells to sense substrate stiffness before full spreading, impacting mechanosensitive protein expression.

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Area of Science:

  • Biophysics
  • Cell Biology
  • Microscopy

Background:

  • Automatic live-cell imaging is crucial for studying long-term biological phenomena.
  • Existing solutions often require expensive, proprietary hardware and software.
  • There is a need for affordable, programmable, and hardware-independent imaging control systems.

Purpose of the Study:

  • To develop a novel, open-source software for automatic multi-functional and time-lapse live-cell imaging.
  • To enable hardware-independent synchronization of microscopy software platforms.
  • To validate the software's utility in investigating early cellular responses to substrate mechanics.

Main Methods:

  • Developed the Automatic Multi-functional Integration Program (AMFIP), a Java-based, hardware-independent software.
  • Integrated AMFIP with μManager, Nikon NIS-Elements, and other third-party software.
  • Utilized AMFIP for time-lapse imaging of CRISPR/Cas9-engineered Beas2B cells expressing YAP to study substrate mechanosensing.

Main Results:

  • AMFIP successfully synchronized multiple microscopy software platforms for automatic operation without additional hardware.
  • Single Beas2B cells demonstrated substrate-stiffness-dependent YAP expression within 10 hours.
  • Cells exhibited the ability to sense and respond to substrate mechanical cues prior to complete spreading.

Conclusions:

  • AMFIP offers a reliable, open-source, and cost-free solution for automated microscopy operations.
  • The developed software facilitates advanced live-cell imaging studies.
  • This research validates that cells can perceive and react to substrate stiffness early in the spreading process.