Showing 1 - 5 of 5 results
1.
Engineering an E. coli Near-Infrared Light Sensor.
Abstract:
Optogenetics is a technology wherein researchers combine light and genetically engineered photoreceptors to control biological processes with unrivaled precision. Near-infrared (NIR) wavelengths (>700 nm) are desirable optogenetic inputs due to their low phototoxicity and spectral isolation from most photoproteins. The bacteriophytochrome photoreceptor 1 (BphP1), found in several purple photosynthetic bacteria, senses NIR light and activates transcription of photosystem promoters by binding to and inhibiting the transcriptional repressor PpsR2. Here, we examine the response of a library of output promoters to increasing levels of Rhodopseudomonas palustris PpsR2 expression, and we identify that of Bradyrhizobium sp. BTAi1 crtE as the most strongly repressed in Escherichia coli. Next, we optimize Rps. palustris bphP1 and ppsR2 expression in a strain engineered to produce the required chromophore biliverdin IXα in order to demonstrate NIR-activated transcription. Unlike a previously engineered bacterial NIR photoreceptor, our system does not require production of a second messenger, and it exhibits rapid response dynamics. It is also the most red-shifted bacterial optogenetic tool yet reported by approximately 50 nm. Accordingly, our BphP1-PpsR2 system has numerous applications in bacterial optogenetics.
2.
A photoconversion model for full spectral programming and multiplexing of optogenetic systems.
Abstract:
Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength- and intensity-dependent photoconversion, signaling, and output gene expression for our two previously engineered light-sensing Escherichia coli two-component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open-source "Light Plate Apparatus" device. In principle, the parameterized model should predict the gene expression response to any time-varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross-reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision-making pathways integrate multiple input signals.
3.
An open-hardware platform for optogenetics and photobiology.
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Gerhardt, KP
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Olson, EJ
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Castillo-Hair, SM
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Hartsough, LA
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Landry, BP
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Ekness, F
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Yokoo, R
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Gomez, EJ
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Ramakrishnan, P
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Suh, J
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Savage, DF
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Tabor, JJ
Abstract:
In optogenetics, researchers use light and genetically encoded photoreceptors to control biological processes with unmatched precision. However, outside of neuroscience, the impact of optogenetics has been limited by a lack of user-friendly, flexible, accessible hardware. Here, we engineer the Light Plate Apparatus (LPA), a device that can deliver two independent 310 to 1550 nm light signals to each well of a 24-well plate with intensity control over three orders of magnitude and millisecond resolution. Signals are programmed using an intuitive web tool named Iris. All components can be purchased for under $400 and the device can be assembled and calibrated by a non-expert in one day. We use the LPA to precisely control gene expression from blue, green, and red light responsive optogenetic tools in bacteria, yeast, and mammalian cells and simplify the entrainment of cyanobacterial circadian rhythm. The LPA dramatically reduces the entry barrier to optogenetics and photobiology experiments.
4.
Optogenetic characterization methods overcome key challenges in synthetic and systems biology.
Abstract:
Systems biologists aim to understand how organism-level processes, such as differentiation and multicellular development, are encoded in DNA. Conversely, synthetic biologists aim to program systems-level biological processes, such as engineered tissue growth, by writing artificial DNA sequences. To achieve their goals, these groups have adapted a hierarchical electrical engineering framework that can be applied in the forward direction to design complex biological systems or in the reverse direction to analyze evolved networks. Despite much progress, this framework has been limited by an inability to directly and dynamically characterize biological components in the varied contexts of living cells. Recently, two optogenetic methods for programming custom gene expression and protein localization signals have been developed and used to reveal fundamentally new information about biological components that respond to those signals. This basic dynamic characterization approach will be a major enabling technology in synthetic and systems biology.
5.
Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals.
Abstract:
Gene circuits are dynamical systems that regulate cellular behaviors, often using protein signals as inputs and outputs. Here we have developed an optogenetic 'function generator' method for programming tailor-made gene expression signals in live bacterial cells. We designed precomputed light sequences based on experimentally calibrated mathematical models of light-switchable two-component systems and used them to drive intracellular protein levels to match user-defined reference time courses. We used this approach to generate accelerated and linearized dynamics, sinusoidal oscillations with desired amplitudes and periods, and a complex waveform, all with unprecedented accuracy and precision. We also combined the function generator with a dual fluorescent protein reporter system, analogous to a dual-channel oscilloscope, to reveal that a synthetic repressible promoter linearly transforms repressor signals with an approximate 7-min delay. Our approach will enable a new generation of dynamical analyses of synthetic and natural gene circuits, providing an essential step toward the predictive design and rigorous understanding of biological systems.