Iterative multi-photon adaptive compensation technique (IMPACT) has been developed for wavefront measurement and compensation in highly scattering tissues. Our previous report was largely based on the measurements of fixed tissue. Here we demonstrate the advantages of IMPACT for in vivo imaging and report the latest results. In particular, we show that IMPACT can be used for functional imaging of awake mice, and greatly improve the in vivo neuron imaging in mouse cortex at large depth (~660 microns). Moreover, IMPACT enables neuron imaging through the intact skull of adult mice, which promises noninvasive optical measurements in mouse brain.

Glucose is arguably the most important molecule in metabolism, and its mismanagement underlies diseases of vast societal import, most notably diabetes. Although glucose-related metabolism has been the subject of intense study for over a century, tools to track glucose in living organisms with high spatio-temporal resolution are lacking. We describe the engineering of a family of genetically encoded glucose sensors with high signal-to-noise ratio, fast kinetics and affinities varying over four orders of magnitude (1 µM to 10 mM). The sensors allow rigorous mechanistic characterization of glucose transporters expressed in cultured cells with high spatial and temporal resolution. Imaging of neuron/glia co-cultures revealed ∼3-fold higher glucose changes in astrocytes versus neurons. In larval Drosophila central nervous system explants, imaging of intracellular neuronal glucose suggested a novel rostro-caudal transport pathway in the ventral nerve cord neuropil, with paradoxically slower uptake into the peripheral cell bodies and brain lobes. In living zebrafish, expected glucose-related physiological sequelae of insulin and epinephrine treatments were directly visualized in real time. Additionally, spontaneous muscle twitches induced glucose uptake in muscle, and sensory- and pharmacological perturbations gave rise to large but enigmatic changes in the brain. These sensors will enable myriad experiments, most notably rapid, high-resolution imaging of glucose influx, efflux, and metabolism in behaving animals.

The zebrafish Danio rerio has emerged as a powerful vertebrate model system that lends itself particularly well to quantitative investigations with live imaging approaches, owing to its exceptionally high optical clarity in embryonic and larval stages. Recent advances in light microscopy technology enable comprehensive analyses of cellular dynamics during zebrafish embryonic development, systematic mapping of gene expression dynamics, quantitative reconstruction of mutant phenotypes and the system-level biophysical study of morphogenesis. Despite these technical breakthroughs, it remains challenging to design and implement experiments for in vivo long-term imaging at high spatio-temporal resolution. This article discusses the fundamental challenges in zebrafish long-term live imaging, provides experimental protocols and highlights key properties and capabilities of advanced fluorescence microscopes. The article focuses in particular on experimental assays based on light sheet-based fluorescence microscopy, an emerging imaging technology that achieves exceptionally high imaging speeds and excellent signal-to-noise ratios, while minimizing light-induced damage to the specimen. This unique combination of capabilities makes light sheet microscopy an indispensable tool for the in vivo long-term imaging of large developing organisms.

In vivo calcium imaging from axons provides direct interrogation of afferent neural activity, informing the neural representations that a local circuit receives. Unlike in somata and dendrites, axonal recording of neural activity-both electrically and optically-has been difficult to achieve, thus preventing comprehensive understanding of neuronal circuit function. Here we developed an active transportation strategy to enrich GCaMP6, a genetically encoded calcium indicator, uniformly in axons with sufficient brightness, signal-to-noise ratio, and photostability to allow robust, structure-specific imaging of presynaptic activity in awake mice. Axon-targeted GCaMP6 enables frame-to-frame correlation for motion correction in axons and permits subcellular-resolution recording of axonal activity in previously inaccessible deep-brain areas. We used axon-targeted GCaMP6 to record layer-specific local afferents without contamination from somata or from intermingled dendrites in the cortex. We expect that axon-targeted GCaMP6 will facilitate new applications in investigating afferent signals relayed by genetically defined neuronal populations within and across specific brain regions.

Neurochemical signals like dopamine (DA) play a crucial role in a variety of brain functions through intricate interactions with other neuromodulators and intracellular signaling pathways. However, studying these complex networks has been hindered by the challenge of detecting multiple neurochemicals in vivo simultaneously. To overcome this limitation, we developed a single-protein chemigenetic DA sensor, HaloDA1.0, which combines a cpHaloTag-chemical dye approach with the G protein-coupled receptor activation-based (GRAB) strategy, providing high sensitivity for DA, sub-second response kinetics, and an extensive spectral range from far-red to near-infrared. When used together with existing green and red fluorescent neuromodulator sensors, Ca2+ indicators, cAMP sensors, and optogenetic tools, HaloDA1.0 provides high versatility for multiplex imaging in cultured neurons, brain slices, and behaving animals, facilitating in-depth studies of dynamic neurochemical networks.

For in vivo deep tissue imaging, high order wavefront measurement and correction is needed for handling the severe wavefront distortion. Towards such a goal, we have developed the iterative multi-photon adaptive compensation technique (IMPACT). In this work, we explore using IMPACT to perform calcium imaging of neocortex through the intact skull of adult mice, and to image through the highly scattering white matter on the hippocampus surface.

Optogenetic reagents allow for depolarization and hyperpolarization of cells with light. This provides unprecedented spatial and temporal resolution to the control of neuronal activity both in vitro and in vivo. In the intact animal this requires strategies to deliver light deep into the highly scattering tissue of the brain. A general approach that we describe here is to implant optical fibers just above brain regions targeted for light delivery. In part due to the fact that expression of optogenetic proteins is accomplished by techniques with inherent variability (e.g., viral expression levels), it also requires strategies to measure and calibrate the effect of stimulation. Here we describe general procedures that allow one to simultaneously stimulate neurons and use photometry with genetically encoded activity indicators to precisely calibrate stimulation.

Whole-cell recording has been used to measure and manipulate a neuron's spiking and subthreshold membrane potential, allowing assessment of the cell's inputs and outputs as well as its intrinsic membrane properties. This technique has also been combined with pharmacology and optogenetics as well as morphological reconstruction to address critical questions concerning neuronal integration, plasticity, and connectivity. This protocol describes a technique for obtaining whole-cell recordings in awake head-fixed animals, allowing such questions to be investigated within the context of an intact network and natural behavioral states. First, animals are habituated to sit quietly with their heads fixed in place. Then, a whole-cell recording is obtained using an efficient, blind patching protocol. We have successfully applied this technique to rats and mice.

Nitrate (NO3-) uptake and distribution are critical to plant life. Although the upstream regulation of nitrate uptake and downstream responses to nitrate in a variety of cells have been well-studied, it is still not possible to directly visualize the spatial and temporal distribution of nitrate with high resolution at the cellular level. Here, we report a nuclear-localized, genetically encoded biosensor, nlsNitraMeter3.0, for the quantitative visualization of nitrate distribution in Arabidopsis thaliana. The biosensor tracked the spatiotemporal distribution of nitrate along the primary root axis and disruptions by genetic mutation of transport (low nitrate uptake) and assimilation (high nitrate accumulation). The developed biosensor effectively monitors nitrate concentrations at cellular level in real time and spatiotemporal changes during the plant life cycle.

Although most proteins conform to the classical one-structure/one-function paradigm, an increasing number of proteins with dual structures and functions have been discovered. In response to cellular stimuli, such proteins undergo structural changes sufficiently dramatic to remodel even their secondary structures and domain organization. This "fold-switching" capability fosters protein multi-functionality, enabling cells to establish tight control over various biochemical processes. Accurate predictions of fold-switching proteins could both suggest underlying mechanisms for uncharacterized biological processes and reveal potential drug targets. Recently, we developed a prediction method for fold-switching proteins using structure-based thermodynamic calculations and discrepancies between predicted and experimentally determined protein secondary structure. Here we seek to leverage the negative information found in these secondary structure prediction discrepancies. To do this, we quantified secondary structure prediction accuracies of 192 known fold-switching regions (FSRs) within solved protein structures found in the Protein Data Bank (PDB). We find that the secondary structure prediction accuracies for these FSRs vary widely. Inaccurate secondary structure predictions are strongly associated with fold-switching proteins compared to equally long segments of non-fold-switching proteins selected at random. These inaccurate predictions are enriched in helix-to-strand and strand-to-coil discrepancies. Finally, we find that most proteins with inaccurate secondary structure predictions are underrepresented in the PDB compared with their alternatively folded cognates, suggesting that unequal representation of fold-switching conformers within the PDB could be an important cause of inaccurate secondary structure predictions. These results demonstrate that inconsistent secondary structure predictions can serve as a useful preliminary marker of fold switching. This article is protected by copyright. All rights reserved.