Trevor J. Wardill

Ultrasensitive fluorescent proteins for imaging neuronal activity

Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultrasensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5–40-µm long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.

Optimization of a GCaMP Calcium Indicator for Neural Activity Imaging

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. GCaMP5 allows more sensitive detection of neural activity in vivo and may find widespread applications for cellular imaging in general.

Genetically encoded calcium indicators for multi-color neural activity imaging and combination with optogenetics

Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Here we describe red, single-wavelength GECIs, “RCaMPs,” engineered from circular permutation of the thermostable red fluorescent protein mRuby. High-resolution crystal structures of mRuby, the red sensor RCaMP, and the recently published red GECI R-GECO1 give insight into the chromophore environments of the Ca2+-bound state of the sensors and the engineered protein domain interfaces of the different indicators. We characterized the biophysical properties and performance of RCaMP sensors in vitro and in vivo in Caenorhabditis elegans, Drosophila larvae, and larval zebrafish. Further, we demonstrate 2-color calcium imaging both within the same cell (registering mitochondrial and somatic [Ca2+]) and between two populations of cells: neurons and astrocytes. Finally, we perform integrated optogenetics experiments, wherein neural activation via channelrhodopsin-2 (ChR2) or a red-shifted variant, and activity imaging via RCaMP or GCaMP, are conducted simultaneously, with the ChR2/RCaMP pair providing independently addressable spectral channels. Using this paradigm, we measure calcium responses of naturalistic and ChR2-evoked muscle contractions in vivo in crawling C. elegans. We systematically compare the RCaMP sensors to R-GECO1, in terms of action potential-evoked fluorescence increases in neurons, photobleaching, and photoswitching. R-GECO1 displays higher Ca2+ affinity and larger dynamic range than RCaMP, but exhibits significant photoactivation with blue and green light, suggesting that integrated channelrhodopsin-based optogenetics using R-GECO1 may be subject to artifact. Finally, we create and test blue, cyan, and yellow variants engineered from GCaMP by rational design. This engineered set of chromatic variants facilitates new experiments in functional imaging and optogenetics.

Compound eyes and retinal information processing in miniature dipteran species match their specific ecological demands

The compound eye of insects imposes a tradeoff between resolution and sensitivity, which should exacerbate with diminishing eye size. Tiny lenses are thought to deliver poor acuity because of diffraction; nevertheless, miniature insects have visual systems that allow a myriad of lifestyles. Here, we investigate whether size constraints result in an archetypal eye design shared between miniature dipterans by comparing the visual performance of the fruit fly Drosophila and the killer fly Coenosia. These closely related species have neural superposition eyes and similar body lengths (3 to 4 mm), but Coenosia is a diurnal aerial predator, whereas slow-flying Drosophila is most active at dawn and dusk. Using in vivo intracellular recordings and EM, we report unique adaptations in the form and function of their photoreceptors that are reflective of their distinct lifestyles. We find that although these species have similar lenses and optical properties, Coenosia photoreceptors have three- to fourfold higher spatial resolution and rate of information transfer than Drosophila. The higher performance in Coenosia mostly results from dramatically diminished light sensors, or rhabdomeres, which reduce pixel size and optical cross-talk between photoreceptors and incorporate accelerated phototransduction reactions. Furthermore, we identify local specializations in the Coenosia eye, consistent with an acute zone and its predatory lifestyle. These results demonstrate how the flexible architecture of miniature compound eyes can evolve to match information processing with ecological demands.

Neural control of tuneable skin iridescence in squid

Fast dynamic control of skin coloration is rare in the animal kingdom, whether it be pigmentary or structural. Iridescent structural coloration results when nanoscale structures disrupt incident light and selectively reflect specific colours. Unlike animals with fixed iridescent coloration (e.g. butterflies), squid iridophores (i.e. aggregations of iridescent cells in the skin) produce dynamically tuneable structural coloration, as exogenous application of acetylcholine (ACh) changes the colour and brightness output. Previous efforts to stimulate iridophores neurally or to identify the source of endogenous ACh were unsuccessful, leaving researchers to question the activation mechanism. We developed a novel neurophysiological preparation in the squid Doryteuthis pealeii and demonstrated that electrical stimulation of neurons in the skin shifts the spectral peak of the reflected light to shorter wavelengths (greater than 145 nm) and increases the peak reflectance (greater than 245%) of innervated iridophores. We show ACh is released within the iridophore layer and that extensive nerve branching is seen within the iridophore. The dynamic colour shift is significantly faster (17 s) than the peak reflectance increase (32 s), revealing two distinct mechanisms. Responses from a structurally altered preparation indicate that the reflectin protein condensation mechanism explains peak reflectance change, while an undiscovered mechanism causes the fast colour shift.

Network Adaptation Improves Temporal Representation of Naturalistic Stimuli in Drosophila Eye: I Dynamics

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1–R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II).

A Neuron-Based Screening Platform for Optimizing Genetically-Encoded Calcium Indicators

Fluorescent protein-based sensors for detecting neuronal activity have been developed largely based on non-neuronal screening systems. However, the dynamics of neuronal state variables (e.g., voltage, calcium, etc.) are typically very rapid compared to those of non-excitable cells. We developed an electrical stimulation and fluorescence imaging platform based on dissociated rat primary neuronal cultures. We describe its use in testing genetically-encoded calcium indicators (GECIs). Efficient neuronal GECI expression was achieved using lentiviruses containing a neuronal-selective gene promoter. Action potentials (APs) and thus neuronal calcium levels were quantitatively controlled by electrical field stimulation, and fluorescence images were recorded. Images were segmented to extract fluorescence signals corresponding to individual GECI-expressing neurons, which improved sensitivity over full-field measurements. We demonstrate the superiority of screening GECIs in neurons compared with solution measurements. Neuronal screening was useful for efficient identification of variants with both improved response kinetics and high signal amplitudes. This platform can be used to screen many types of sensors with cellular resolution under realistic conditions where neuronal state variables are in relevant ranges with respect to timing and amplitude.

The structure–function relationships of a natural nanoscale photonic device in cuttlefish chromatophores

Cuttlefish, Sepia officinalis, possess neurally controlled, pigmented chromatophore organs that allow rapid changes in skin patterning and coloration in response to visual cues. This process of adaptive coloration is enabled by the 500% change in chromatophore surface area during actuation. We report two adaptations that help to explain how colour intensity is maintained in a fully expanded chromatophore when the pigment granules are distributed maximally: (i) pigment layers as thin as three granules that maintain optical effectiveness and (ii) the presence of high-refractive-index proteins—reflectin and crystallin—in granules. The latter discovery, combined with our finding that isolated chromatophore pigment granules fluoresce between 650 and 720 nm, refutes the prevailing hypothesis that cephalopod chromatophores are exclusively pigmentary organs composed solely of ommochromes. Perturbations to granular architecture alter optical properties, illustrating a role for nanostructure in the agile, optical responses of chromatophores. Our results suggest that cephalopod chromatophore pigment granules are more complex than homogeneous clusters of chromogenic pigments. They are luminescent protein nanostructures that facilitate the rapid and sophisticated changes exhibited in dermal pigmentation.

A Novel Interception Strategy in a Miniature Robber Fly with Extreme Visual Acuity

Summary Our visual system allows us to rapidly identify and intercept a moving object. When this object is far away, we base the trajectory on the target’s location relative to an external frame of reference [1]. This process forms the basis for the constant bearing angle (CBA) model, a reactive strategy that ensures interception since the bearing angle, formed between the line joining pursuer and target (called the range vector) and an external reference line, is held constant [2, 3, 4]. The CBA model may be a fundamental and widespread strategy, as it is also known to explain the interception trajectories of bats and fish [5, 6]. Here, we show that the aerial attack of the tiny robber fly Holcocephala fusca is consistent with the CBA model. In addition, Holcocephala fusca displays a novel proactive strategy, termed “lock-on” phase, embedded with the later part of the flight. We found the object detection threshold for this species to be 0.13°, enabled by an extremely specialized, forward pointing fovea (∼5 ommatidia wide, interommatidial angle Δφ = 0.28°, photoreceptor acceptance angle Δρ = 0.27°). This study furthers our understanding of the accurate performance that a miniature brain can achieve in highly demanding sensorimotor tasks and suggests the presence of equivalent mechanisms for target interception across a wide range of taxa. Video Abstract

The killer fly hunger games : target size and speed predict decision to pursuit

Predatory animals have evolved to optimally detect their prey using exquisite sensory systems such as vision, olfaction and hearing. It may not be so surprising that vertebrates, with large central nervous systems, excel at predatory behaviors. More striking is the fact that many tiny insects, with their miniscule brains and scaled down nerve cords, are also ferocious, highly successful predators. For predation, it is important to determine whether a prey is suitable before initiating pursuit. This is paramount since pursuing a prey that is too large to capture, subdue or dispatch will generate a substantial metabolic cost (in the form of muscle output) without any chance of metabolic gain (in the form of food). In addition, during all pursuits, the predator breaks its potential camouflage and thus runs the risk of becoming prey itself. Many insects use their eyes to initially detect and subsequently pursue prey. Dragonflies, which are extremely efficient predators, therefore have huge eyes with relatively high spatial resolution that allow efficient prey size estimation before initiating pursuit. However, much smaller insects, such as killer flies, also visualize and successfully pursue prey. This is an impressive behavior since the small size of the killer fly naturally limits the neural capacity and also the spatial resolution provided by the compound eye. Despite this, we here show that killer flies efficiently pursue natural (Drosophila melanogaster) and artificial (beads) prey. The natural pursuits are initiated at a distance of 7.9 ± 2.9 cm, which we show is too far away to allow for distance estimation using binocular disparities. Moreover, we show that rather than estimating absolute prey size prior to launching the attack, as dragonflies do, killer flies attack with high probability when the ratio of the preys subtended retinal velocity and retinal size is 0.37. We also show that killer flies will respond to a stimulus of an angular size that is smaller than that of the photoreceptor acceptance angle, and that the predatory response is strongly modulated by the metabolic state. Our data thus provide an exciting example of a loosely designed matched filter to Drosophila, but one which will still generate successful pursuits of other suitable prey.