Electrophysiology and optical indicators have been used in vertebrate systems to investigate excitable cell firing and calcium transients, but both techniques have been difficult to apply in organisms with powerful reverse genetics. To overcome this limitation, we expressed cameleon proteins, genetically encoded calcium indicators, in the pharyngeal muscle of the nematode worm Caenorhabditis elegans. In intact transgenic animals expressing cameleons, fluorescence ratio changes accompanied muscular contraction, verifying detection of calcium transients. By comparing the magnitude and duration of calcium influx in wild-type and mutant animals, we were able to determine the effects of calcium channel proteins on pharyngeal calcium transients. We also successfully used cameleons to detect electrically evoked calcium transients in individual C. elegans neurons. This technique therefore should have broad applications in analyzing the regulation of excitable cell activity in genetically tractable organisms.

Receptor tyrosine kinases (RTK) are important cell surface receptors that transduce extracellular signals across the plasma membrane. The traditional view of how these receptors function is that ligand binding to the extracellular domains acts as a master-switch that enables receptor monomers to dimerize and subsequently trans-phosphorylate each other on their intracellular domains. However, a growing body of evidence suggests that receptor oligomerization is not merely a consequence of ligand binding, but is instead part of a complex process responsible for regulation of receptor activation. Importantly, the oligomerization dynamics and subsequent activation of these receptors are affected by other cellular components, such as cytoskeletal machineries and cell membrane lipid characteristics. Thus receptor activation is not an isolated molecular event mediated by the ligand-receptor interaction, but instead involves orchestrated interactions between the receptors and other cellular components. Measuring receptor oligomerization dynamics on live cells can yield important insights into the characteristics of these interactions. Therefore, it is imperative to develop techniques that can probe receptor movements on the plasma membrane with optimal temporal and spatial resolutions. Various microscopic techniques have been used for this purpose. Optical techniques including single molecule tracking (SMT) and fluorescence correlation spectroscopy (FCS) measure receptor diffusion on live cells. Receptor-receptor interactions can also be assessed by detecting Förster resonance energy transfer (FRET) between fluorescently-labeled receptors situated in close proximity or by counting the number of receptors within a diffraction limited fluorescence spot (stepwise bleaching). This review will describe recent developments of optical techniques that have been used to study receptor oligomerization on living cells. This article is part of a Special Issue entitled: Interactions between membrane receptors in cellular membranes edited by Kalina Hristova.

With amino acids as model systems, optically active sum frequency generation (OA-SFG) was used to probe the chirality of molecules with a chiral center and an intrinsically achiral chromophore in isotropic solution for the first time. Like that of circular dichroism (CD), the OA-SFG’s near electronic resonance originates from the extrachromophoric chiral perturbation on the carboxyl chromophore. The difference in the relative strengths of OA-SFG and CD among different amino acids can be explained by the difference in the details of perturbations.

Experimental investigations have revealed that synapses possess interesting and, in some cases, unexpected properties. We propose a theoretical framework that accounts for three of these properties: typical central synapses are noisy, the distribution of synaptic weights among central synapses is wide, and synaptic connectivity between neurons is sparse. We also comment on the possibility that synaptic weights may vary in discrete steps. Our approach is based on maximizing information storage capacity of neural tissue under resource constraints. Based on previous experimental and theoretical work, we use volume as a limited resource and utilize the empirical relationship between volume and synaptic weight. Solutions of our constrained optimization problems are not only consistent with existing experimental measurements but also make nontrivial predictions.

The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the "single-particle Wiener filter") to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation.

I consider a topographic projection between two neuronal layers with different densities of neurons. Given the number of output neurons connected to each input neuron (divergence) and the number of input neurons synapsing on each output neuron (convergence), I determine the widths of axonal and dendritic arbors which minimize the total volume of axons and dendrites. Analytical results for one-dimensional and two-dimensional projections can be summarized qualitatively in the following rule: neurons of the sparser layer should have arbors wider than those of the denser layer. This agrees with the anatomic data for retinal, cerebellar, olfactory bulb, and neocortical neurons the morphology and connectivity of which are known. The rule may be used to infer connectivity of neurons from their morphology.

Sighted animals use visual signals to discern directional motion in their environment. Motion is not directly detected by visual neurons, and it must instead be computed from light signals that vary over space and time. This makes visual motion estimation a near universal neural computation, and decades of research have revealed much about the algorithms and mechanisms that generate directional signals. The idea that sensory systems are optimized for performance in natural environments has deeply impacted this research. In this article, we review the many ways that optimization has been used to quantitatively model visual motion estimation and reveal its underlying principles. We emphasize that no single optimization theory has dominated the literature. Instead, researchers have adeptly incorporated different computational demands and biological constraints that are pertinent to the specific brain system and animal model under study. The successes and failures of the resulting optimization models have thereby provided insights into how computational demands and biological constraints together shape neural computation.

Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Recent efforts in protein engineering have significantly increased the performance of GECIs. The state-of-the art single-wavelength GECI, GCaMP3, has been deployed in a number of model organisms and can reliably detect three or more action potentials in short bursts in several systems in vivo . Through protein structure determination, targeted mutagenesis, high-throughput screening, and a battery of in vitro assays, we have increased the dynamic range of GCaMP3 by severalfold, creating a family of “GCaMP5” sensors. We tested GCaMP5s in several systems: cultured neurons and astrocytes, mouse retina, and in vivo in Caenorhabditis chemosensory neurons, Drosophila larval neuromuscular junction and adult antennal lobe, zebrafish retina and tectum, and mouse visual cortex. Signal-to-noise ratio was improved by at least 2- to 3-fold. In the visual cortex, two GCaMP5 variants detected twice as many visual stimulus-responsive cells as GCaMP3. By combining in vivo imaging with electrophysiology we show that GCaMP5 fluorescence provides a more reliable measure of neuronal activity than its predecessor GCaMP3.GCaMP5allows more sensitive detection of neural activity in vivo andmayfind widespread applications for cellular imaging in general.

Correlative light and electron microscopy (CLEM) combines the power of electron microscopy, with its excellent resolution and contrast, with that of fluorescence imaging, which allows the staining of specific molecules, organelles, and cell populations. Fluorescence imaging is also readily compatible with live cells and behaving animals, facilitating real-time visualization of cellular processes, potentially followed by electron microscopic reconstruction. Super-resolution single-molecule localization microscopy is a relatively new modality that harnesses the ability of some fluorophores to photoconvert, through which localization precision better than Abbe’s diffraction limit is achieved through iterative high-resolution localization of single-molecule emitters. Here we describe our lab’s recent progress in the development of reagents and techniques for super-resolution single-molecule localization CLEM and their applications to biological problems.

The use of genetically encoded 'self-labeling tags' with chemical fluorophore ligands enables rapid labeling of specific cells in neural tissue. To improve the chemical tagging of neurons, we synthesized and evaluated new fluorophore ligands based on Cy, Janelia Fluor, Alexa Fluor, and ATTO dyes and tested these with recently improved Drosophila melanogaster transgenes. We found that tissue clearing and mounting in DPX substantially improves signal quality when combined with specific non-cyanine fluorophores. We compared and combined this labeling technique with standard immunohistochemistry in the Drosophila brain.