Koveal, D. | bioRxiv Science

bioRxiv2026

An optogenetics-compatible red fluorescent calcium indicator with negligible blue light photoactivation

Red genetically encoded calcium indicators (GECIs) are important tools for live cell and in vivo imaging. However, their application in optogenetic experiments has been limited by their complex photophysics, which can yield blue-light-induced artifacts. These photophysical drawbacks arise from the fluorescent protein (FP) used to construct the GECI. To address these limitations, we engineered novel red GECIs based on photostable red FPs, including mScarlet variants. After testing multiple design topologies and screening for calcium responses, we identified a lead variant, named ScaRCaMP-1.0. ScaRCaMP-1.0 exhibits moderate Ca2+ responses ({Delta}F/F0 = -13%) relative to other red GECIs, a tradeoff that appears to have enabled remarkable blue-light photostability at power densities exceeding 200 mW/mm2. We validated the performance of ScaRCaMP-1.0 in an optogenetic regime, and in vivo via fiber photometry. Finally, guided by structural predictions, we investigated the mechanism underlying ScaRCaMP responses. A pair of lysine residues on the surface of the FP appear to be important for controlling Ca2+ responses, and mutation of one residue (K132Y) notably increased the response size ({Delta}F/F0 = -22%) without compromising blue-light photostability. We call the improved variant ScaRCaMP-2.0. Taken together, these results establish ScaRCaMP as an optogenetics-compatible red GECI and demonstrate the potential of mScarlet-based fluorophores as a basis for generating photostable red biosensors.

neuroscience↗

bioRxiv2024

High-resolution in vivo kinematic tracking with injectable fluorescent nanoparticles

Behavioral quantification is a cornerstone of many neuroscience experiments. Recent advances in motion tracking have streamlined the study of behavior in small laboratory animals and enabled precise movement quantification on fast (millisecond) timescales. This includes markerless keypoint trackers, which utilize deep network systems to label positions of interest on the surface of an animal (e.g., paws, snout, tail, etc.). These approaches mark a major technological achievement. However, they have a high error rate relative to motion capture in humans and are yet to be benchmarked against ground truth datasets in mice. Moreover, the extent to which they can be used to track joint or skeletal kinematics remains unclear. As the primary output of the motor system is the activation of muscles that, in turn, exert forces on the skeleton rather than the skin, it is important to establish potential limitations of techniques that rely on surface imaging. This can be accomplished by imaging implanted fiducial markers in freely moving mice. Here, we present a novel tracking method called QD-Pi (Quantum Dot-based Pose estimation in vivo), which employs injectable near-infrared fluorescent nanoparticles (quantum dots, QDs) immobilized on microbeads. We demonstrate that the resulting tags are biocompatible and can be imaged non-invasively using commercially available camera systems when injected into fatty tissue beneath the skin or directly into joints. Using this technique, we accurately capture 3D trajectories of up to ten independent internal positions in freely moving mice over multiple weeks. Finally, we leverage this technique to create a large-scale ground truth dataset for benchmarking and training the next generation of markerless keypoint tracker systems.

neuroscience↗