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2017 ; 12
(11
): e0187163
Nephropedia Template TP
gab.com Text
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Low cost and open source multi-fluorescence imaging system for teaching and
research in biology and bioengineering
#MMPMID29140977
Nuñez I
; Matute T
; Herrera R
; Keymer J
; Marzullo T
; Rudge T
; Federici F
PLoS One
2017[]; 12
(11
): e0187163
PMID29140977
show ga
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. In this study, we
describe 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. We 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, we screened a series of long stokes shift
fluorescent proteins that could be combined with cyan/green fluorescent proteins.
We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel
fluorescent imaging. We developed open source Python code 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, we
tested its performance on a diverse range of imaging assays often used in
disciplines such as microbial ecology, microbiology and synthetic biology. We
also assessed its potential use in a high school environment to teach biology,
hardware design, optics, and programming. Together, these 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. All the resources developed
here are available under open source licenses.