Biology subjects

Sims, R. R.

Publications and source records attributed to Sims, R. R..

5 recordsLinked to original sources

bioRxiv2026

Ultrasensitive voltage imaging reveals distinct electrical microdomains in neurons

For the brain to compute, electrical signals must propagate over the membranes of individual neurons, connecting synaptic inputs to synaptic outputs1. Complex neuronal morphologies coupled with the spatial organization of synaptic inputs and outputs enable diverse voltage transformations that underlie cell-type specific computations2,3. However, measuring these transformations in vivo has remained challenging, leaving a crucial gap in our mechanistic understanding of single neuron computation. Here, we develop ASAP7y, a genetically encoded voltage indicator with unprecedented subthreshold sensitivity and expanded excitation compatibility in both mice and flies. We leveraged ASAP7y combined with two-photon random-access microscopy to record sensory stimulus-evoked voltage dynamics with millisecond, subcellular, and subthreshold resolution along the neurites of individual neurons in Drosophila. We found remarkable heterogeneity in voltage propagation across cell-types, delineating a fundamental axis of electrical diversity. Leveraging a nanoscale EM reconstruction of the visual system4, we modeled the electrotonic properties of single neurons spanning 717 cell types, revealing how morphology shapes voltage transformations. Finally, we demonstrate that confined voltage propagation creates substrates for local computation, producing subcellular domains with distinct feature selectivity across multiple cell types. These results provide mechanistic insight into how critical single neuron computations arise and reveal parallel processing in single neurons.

neuroscience↗

bioRxiv2024

Two-photon voltage imaging with rhodopsin-based sensors

The recent advances in sophisticated optical techniques, coupled with two-photon sensitive genetic voltage indicators (GEVIs), have enabled in-depth voltage imaging in vivo at single spike and single-cell resolution. To date, these results have been only achieved using ASAP-type sensors, as the complex photocycle of rhodopsin-based voltage indicators posed challenges for their two-photon use, restricting their application to one-photon approaches. In this work, we demonstrate that rhodopsin-based GEVIs (FRET-opsin) can be used under two-photon illumination when their peculiar light intensity dependence of kinetics and sensitivity are considered. We rationally engineer a fully genetically-encoded, rhodopsin-based voltage indicator with the brightest known fluorophore AaFP1, Jarvis, and demonstrate its utility under both one- and two-photon illumination. We also showed two-photon usability of the similar FRET-opsin sensor pAce. Our comparison of 2P scanless with fast 2P scanning illumination revealed that the latter approach is less suitable for this class of indicators and, on the contrary, both sensors responded well when scanless approaches were used. Furthermore, utilising Jarvis, we demonstrated high-fidelity, high-SNR action potential detection at kilohertz-imaging rates both in mouse hippocampal slices and in zebrafish larvae. To the best of our knowledge, this study represents the first report of a fully genetically-encoded rhodopsin-based voltage indicator for high contrast action potential detection under two-photon illumination in vitro and in vivo.

neuroscience↗

bioRxiv2023

High-density volumetric super-resolution microscopy

Volumetric super-resolution microscopy typically encodes the 3D position of single-molecule fluorescence into a 2D image by changing the shape of the point spread function (PSF) as a function of depth. However, the resulting large and complex PSF spatial footprints reduce temporal resolution by requiring lower labelling densities to avoid overlapping fluorescent signals. We quantitatively compare the density dependence of single-molecule light field microscopy (SMLFM) to other 3D PSFs (astigmatism, double helix and tetrapod) showing that SMFLM enables an order-of-magnitude speed improvement compared to the double helix PSF by resolving overlapping emitters through parallax. We then experimentally demonstrate the high accuracy (>99.2 {+/-} 0.1%, 0.1 locs m-2) and sensitivity (>86.6 {+/-} 0.9%, 0.1 locs m-2) of SMLFM at point detection through whole-cell (scan-free) imaging and tracking of single membrane proteins in live primary B cells. We also exemplify high density volumetric imaging (0.15 locs m-2) in dense cytosolic tubulin datasets.

biophysics↗

bioRxiv2020

Single Molecule Light Field Microscopy

We introduce single molecule light field microscopy (SMLFM), a novel 3D single molecule localization technique that is capable of up to 20 nm isotropic precision across a 6 m depth of field. SMLFM can be readily implemented by installing a refractive microlens array into the conjugate back focal plane of any widefield single molecule localization system. We demonstrate that 3D localization can be performed by post-processing 2D localization data generated by common, widely-used, algorithms. In this work we benchmark the performance of SMLFM and finally showcase its capabilities by imaging fluorescently labeled membranes of fixed eukaryotic cells below the diffraction limit.

biophysics↗

bioRxiv2019

Super-resolving light fields in microscopy: depth from disparity

Single molecule localisation microscopy (SMLM) has opened a new window for imaging fluorescently labelled biological specimens. Common 3D SMLM techniques enable data collection across an axial range of 1 - 5m with high precision. Despite the success of 3D single molecule imaging there is a real need to image larger volumes. Here we demonstrate, through simulation and experiment, the potential of Single Molecule Light Field Microscopy (SMLFM) for extended depth-of-field super-resolution imaging, extracting 3D point source position by measuring the disparity between localizations of a point emitter in multiple perspective views.

bioengineering↗