Toolbox for Exploring Modular Gene Regulation in Synthetic Biology Training

Magaraci, Michael S.; Bermudez, Jessica G.; Yogish, Deeksha; Pak, Daniel; Mollov, Viktor; Tycko, Josh; Issadore, David; Mannickarottu, Sevile G.; Chow, Brian Y.

doi:10.1021/acssynbio.6b00057

Cited by 16 publications

(22 citation statements)

References 19 publications

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“…In general, the programmable LED matrix, and related devices for automated illumination, stand to facilitate the analysis and application of optogenetic circuits and other light‐responsive systems. These lighting setups directly pertain to the optogenetic regulation of gene expression in prokaryotes and eukaryotes, and readily extend to additional optogenetic experiments . More generally, setups for programmable, parallelized illumination may also benefit the analysis of other light‐sensitive biological and chemical processes, for example, the cultivation of photoautotrophic organisms, such as cyanobacteria …”

Section: Discussionmentioning

confidence: 99%

Optogenetic Control by Pulsed Illumination

et al. 2018

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Sensory photoreceptors evoke numerous adaptive responses in nature and serve as light-gated actuators in optogenetics to enable the spatiotemporally precise, reversible, and noninvasive control of cellular events. The output of optogenetic circuits can often be dialed in by varying illumination quality, quantity, and duration. A programmable matrix of light-emitting diodes has been devised to efficiently probe the response of optogenetic systems to intermittently applied light of varying intensity and pulse frequency. Circuits for light-regulated gene expression markedly differed in their responses to pulsed illumination of a single color which sufficed for their sequential triggering. In addition to quantity and quality, the pulse frequency of intermittent light hence provides a further input variable for output control in optogenetics and photobiology. Pulsed illumination schemes allow the reduction of overall light dose and facilitate the multiplexing of several lightdependent actuators and reporters.

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Section: Discussionmentioning

confidence: 99%

Optogenetic Control by Pulsed Illumination

et al. 2018

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“…[ 27 – 31 ]), wireless connectivity [ 32 ], and cost as little as US$1 [ 33 ]. Open source devices for in vivo fluorescence imaging of whole organisms and cell populations are of special interest for spatio-temporal studies [ 26 , 34 , 35 ]. Fluorescence imaging has traditionally relied on broad-spectrum illumination systems, such as mercury lamps, that require channel separation for multicolor imaging.…”

Section: Introductionmentioning

confidence: 99%

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

Núñez

Matute

Herrera³

et al. 2017

PLoS ONE

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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.

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“…Open source devices for in vivo fluorescence imaging of whole organisms and cell populations are of special interest for spatio-temporal studies [26,34,35]. Fluorescence imaging has traditionally relied on broad-spectrum illumination systems, such as mercury lamps, that require channel separation for multicolor imaging.…”

Section: Introductionmentioning

confidence: 99%

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

Núñez

Matute

Herrera

et al. 2017

Preprint

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(FF) ¶ These authors contributed equally to this work. AbstractThe 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 for STEM teaching in a high school environment, using it 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 STEM education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

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Toolbox for Exploring Modular Gene Regulation in Synthetic Biology Training

Cited by 16 publications

References 19 publications

Optogenetic Control by Pulsed Illumination

Optogenetic Control by Pulsed Illumination

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

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