Development of an Open Source Autonomous Imaging Station for Distribution in High Schools, Universities, and Emerging DIY Scientific Communities

Fernán Federici (University of Cambridge/Universidad Catolica, Chile), Neil Pearson (Earlham Institute), Tim Rudge (Department of Engineering, Universidad Catolica, Chile), Tim Marzullo (Backyard Brains, Inc), Juan Keymer, (Universidad Catolica, Chile)

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. The team developed and published (Nuñez et al., 2017) an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates.

“OpenPlant funds were important because we are generating a real impact in research and teaching through interdisciplinarity. This project not only introduced us to new modes of work based on good practices, documentation and open source licensing but also allowed us to learn from different fields such as open hardware, design, FOSS and advanced DNA fab methods.
— Isaac Nuñez, Pontificia Universidad Catolica, Chile

The team also developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, they screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins for 3-channel fluorescent imaging. Open source Python code was developed to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, the team tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology.

In order to highlight the benefits of employing an open framework, the team formed an industry partnership with the Open Source company Backyard Brains (TM), which has significant experience in creating and distributing open educational and research technology for neuroscience in Latin America and worldwide (, In collaboration, the team assessed the potential use of their imaging statuon in a high school environment, per author Tamara Matute “ ”

We have been able to use these resources in workshops in high schools, community spaces and cultural centres; and implement advanced practicals to teach in vitro synbio, DNA fab and microbiology. The open source and low cost nature of the resources has allowed citizens to better understand the principles behind gene expression analysis and modelling
— Tamara, Matute, Pontificia Universidad Catolica, Chile

Together, their results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for education, scientific research and bioengineering. The paper was selected as Editor's Pick for the PLOS Open Source Toolkit Channel in December 2017.

Nuñez, I., Matute, T., Herrera, R., Keymer, J., Marzullo, T., Rudge, T., & Federici, F. (2017). Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering. PLOS One, 12(11), e0187163.