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AMi: a GUI-based, open-source system for imaging samples in multi-well plates.

Andrew Bohm1

  • 1Department of Developmental, Molecular, and Chemical Biology, Tufts University, 136 Harrison Avenue, Boston, MA 02111, USA.

Acta Crystallographica. Section F, Structural Biology Communications
|August 10, 2019
PubMed
Summary
This summary is machine-generated.

Researchers developed an affordable automated microscope (AMi) for multi-well plate imaging. This system offers automated control and easy manual inspection for biological sample analysis.

Keywords:
AMiAMiGUIautomated microscopycrystallographymulti-well plates

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Area of Science:

  • Microscopy
  • Automation
  • Bioimaging

Background:

  • High-throughput screening and analysis of biological samples in multi-well plates are crucial in various research fields.
  • Existing automated microscopy solutions can be expensive and complex, limiting accessibility for smaller laboratories.
  • There is a need for cost-effective and user-friendly automated imaging systems for multi-well plate analysis.

Purpose of the Study:

  • To describe the design, construction, and operation of an inexpensive automated microscope (AMi).
  • To provide freely available software (AMiGUI) for controlling the microscope's X, Y, Z translation stage and image acquisition.
  • To enable efficient imaging and analysis of samples within multi-well plates.

Main Methods:

  • The automated microscope utilizes an Arduino-based board running grbl for stage control.
  • A Raspberry Pi microcomputer running Python manages the graphical user interface and image acquisition.
  • The system supports multi-well plates and includes a script for automated z-stack depth-of-field enhancement.

Main Results:

  • The developed automated microscope (AMi) is inexpensive and specifically designed for multi-well plate imaging.
  • Freely available dedicated software (AMiGUI) controls the X, Y, Z translation stage, graphical user interface, and image acquisition.
  • The system allows images to be saved locally or remotely and facilitates manual inspection and capture of individual samples.

Conclusions:

  • The described automated microscope (AMi) provides a cost-effective solution for multi-well plate imaging.
  • The integrated software and hardware components enable both automated and manual sample inspection.
  • This accessible automated microscopy system can benefit researchers requiring efficient bioimaging capabilities for plate-based assays.