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Silvagnoli, A. D.

Publications and source records attributed to Silvagnoli, A. D..

2 recordsLinked to original sources

A Method for Optimizing Imaging Parameters to Record Neuronal and Cellular Activity at Depth with Bioluminescence

Optical imaging of activity has provided valuable insight into brain function and accelerated the field of neuroscience in recent years. Genetically encoded fluorescent activity sensors of calcium, neurotransmitters and voltage have been tools of choice for optical recording of neuronal activity. However, photon scattering and absorbance limits fluorescence imaging to superficial regions for in vivo activity imaging. This limitation prevents recording of population level activity in lower brain regions of experimental animals without implanted hardware. Single and multiphoton methods find maximal use in the cortex and experience loss of signal at greater depths. Successful efforts have been made to increase the depth of fluorescence imaging using fiber photometry and gradient reflective index lenses. However, these methods are highly invasive, requiring an implant within the brain. Bioluminescence imaging offers a promising alternative to achieve activity imaging in deeper brain regions without hardware implanted within the brain. Bioluminescent reporters can be genetically encoded and produce photons without external excitation. The use of enzymatic photon production also enables prolonged imaging sessions without the risk of photobleaching or phototoxicity. These characteristics render bioluminescence suitable to non-invasive imaging of deep neuronal populations. To facilitate the adoption of bioluminescent activity imaging, we sought to develop a low cost, simple in vitro method to optimize imaging parameters for determining optimal exposure times and optical hardware configurations to determine what frame rates can be captured with an individual labs imaging hardware with sufficient signal-to-noise ratios without the use of animals prior to starting an in vivo experiment. To achieve this, we developed an assay for modeling in vivo optical conditions with a brain tissue phantom paired with engineered cells that produce bioluminescence. We then used this assay to limit-test the detection depth vs maximum frame rate for bioluminescence imaging at experimentally relevant tissue depths using off the shelf imaging hardware. With this method, we demonstrate an effective means for increasing the utility of bioluminescent tools and lowering the barrier to adoption of bioluminescence activity imaging with bioluminescent sensors.

neuroscience↗

A Bioluminescent Activity Dependent (BLADe) Platform for Converting Neuronal Activity to Photoreceptor Activation

Genetically encoded sensors and actuators have advanced the ability to observe and manipulate cellular activity, yet few non-invasive strategies enable cells to directly couple their intracellular states to user-defined outputs. We promote a bioluminescent activity-dependent (BLADe) platform that facilitates programmable feedback through genetically encoded light generation. Using calcium (Ca{superscript 2}) flux as a model, we engineered a Ca{superscript 2}-dependent luciferase that functions as an activity-gated light source capable of photoactivating light-sensing actuators. As an initial demonstration of the versatility of this platform we present two separate use cases in neurons. In the first application, the presence of luciferin triggers Ca{superscript 2} dependent local illumination that provides activity dependent gene expression by activating a light-sensitive transcription factor. In the second application, neuronal activity-driven Ca{superscript 2} fluctuations via locally generated bioluminescence control neural dynamics through opsin activation in single cells, populations and intact tissue. BLADe can be expanded to couple any signal that bioluminescent enzymes can be engineered to detect with the wide variety of photosensing actuators. This modular strategy of coupling an activity dependent light emitter to a light sensing actuator offers, in principle, a generalizable framework for state dependent cell-autonomous control across biological systems.

neuroscience↗