Hardware design files, code and teaching materials for a low cost and open source fluorescent image registration station.

Overview

FluoPi is composed of a blue-light transilluminator, an amber acrylic filter and a raspberry camera contained in a black acrylic mainframe. All the hardware is controlled with a Raspberry pi small computer. With this equipment you are able to:

• Take images of fluorescent samples ranges from um to cm.
• Perform timelapse assays of up to 3 fluorescent proteins simultaneously
• See electrophoresis gel stained with blue excitable chemicals (such as GelRed or SYBR Safe).

Getting Started

You can see the full project at OSF and a pre-print manuscript at Biorxiv and peer-reviewed article in PLoS

Prerequisites

To assemble this device you need access to a laser cutter and a 3D printer. You also need a mouse, keyboard and a screen with HDMI (or hdmi to VGA adaptor) to connect with the Raspberry pi (you can also manage the equipment through SSH or using programs such as teamviewer)

Installing

All the installation instructions are available on the wiki page

Full documentation and assembly instructions can be found at Docubricks

Running the equipment

The equipment has a manual switch and the camera can be controlled with camera module commands. The project includes some python codes (based on camera python module) to control the hardware:

• timelapse.py --> to perform timelapse experiments
• turnON.py --> to turn ON the transilluminator
• turnOFF.py --> to turn OFF the transilluminator

Running the notebooks

Jupyter notebooks are included (Examples/ and Tutorials/) to demonstrate the analysis principles and the use of the fluopi module to analyse time-lapse image data. Sample image data is included in the relevant folders. You can start from these examples, switching the file paths to your data.

Authors

Universidad Catolica de Chile

• Isaac Nuñez - Prosimio
• Tamara Matute - tfmatute
• Juan Keymner - Keymer Lab
• Tim Rudge - Rudge lab
• Fernan Federici - Federici lab

Backyard Brains Chile

• Roberto Pellizzari - RoHPellizzari
• Tim Marzullo - Backyard Brains

License

This project is licensed under the MIT License - see the LICENSE.txt file for details. Hardware is lincesed under the CERN license.

FAQs and updates

Please follow updates, ask questions and check FAQs in this doc

Acknowledgments

• Toby Wenzel for guidance on Docubricks documentation

• Tom Baden and Andre Chagas for feedback and advice on camera

• Bernardo Pollak for helping out with sequences

• Douglas Densmore for the CIDAR MoClo Parts Kit

• OpenPlant Fund and Fondecyt for providing financial support