Single-cell analysis has revealed that transcription is dynamic and stochastic, but tools are lacking that can determine the mechanism operating at a single gene. Here we utilize single-molecule observations of RNA in fixed and living cells to develop a single-cell model of steroid-receptor mediated gene activation. We determine that steroids drive mRNA synthesis by frequency modulation of transcription. This digital behavior in single cells gives rise to the well-known analog dose response across the population. To test this model, we developed a light-activation technology to turn on a single steroid-responsive gene and follow dynamic synthesis of RNA from the activated locus. DOI:http://dx.doi.org/10.7554/eLife.00750.001.

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

Biological tissue is often composed of cells with similar morphologies replicated throughout large volumes and many biological applications rely on the accurate identification of these cells and their locations from image data. Here we develop a generative model that captures the regularities present in images composed of repeating elements of a few different types. Formally, the model can be described as convolutional sparse block coding. For inference we use a variant of convolutional matching pursuit adapted to block-based representations. We extend the K-SVD learning algorithm to subspaces by retaining several principal vectors from the SVD decomposition instead of just one. Good models with little cross-talk between subspaces can be obtained by learning the blocks incrementally. We perform extensive experiments on simulated images and the inference algorithm consistently recovers a large proportion of the cells with a small number of false positives. We fit the convolutional model to noisy GCaMP6 two-photon images of spiking neurons and to Nissl-stained slices of cortical tissue and show that it recovers cell body locations without supervision. The flexibility of the block-based representation is reflected in the variability of the recovered cell shapes.

Gap junctions (GJs) represent connexin-rich membrane domains that connect interiors of adjoining cells in mammalian tissues. How fast GJs can respond to bacterial pathogens has not been known previously. Using Bessel beam plane illumination and confocal spinning disk microscopy, we found fast (~500 ms) formation of connexin-depleted regions (CDRs) inside GJ plaques between cells exposed to AB5 toxins. CDR formation appears as a fast redistribution of connexin channels within GJ plaques with minor changes in outline or geometry. CDR formation does not depend on membrane trafficking or submembrane cytoskeleton and has no effect on GJ conductance. However, CDR responses depend on membrane lipids, can be modified by cholesterol-clustering agents and extracellular K(+) ion concentration, and influence cAMP signaling. The CDR response of GJ plaques to bacterial toxins is a phenomenon observed for all tested connexin isoforms. Through signaling, the CDR response may enable cells to sense exposure to AB5 toxins. CDR formation may reflect lipid-phase separation events in the biological membrane of the GJ plaque, leading to increased connexin packing and lipid reorganization. Our data demonstrate very fast dynamics (in the millisecond-to-second range) within GJ plaques, which previously were considered to be relatively stable, long-lived structures.

Identifying the neuronal ensembles that respond to specific stimuli and mapping their projection patterns in living animals are fundamental challenges in neuroscience. To this end, we engineered a synthetic promoter, the enhanced synaptic activity-responsive element (E-SARE), that drives neuronal activity-dependent gene expression more potently than other existing immediate-early gene promoters. Expression of a drug-inducible Cre recombinase downstream of E-SARE enabled imaging of neuronal populations that respond to monocular visual stimulation and tracking of their long-distance thalamocortical projections in living mice. Targeted cell-attached recordings and calcium imaging of neurons in sensory cortices revealed that E-SARE reporter expression correlates with sensory-evoked neuronal activity at the single-cell level and is highly specific to the type of stimuli presented to the animals. This activity-dependent promoter can expand the repertoire of genetic approaches for high-resolution anatomical and functional analysis of neural circuits.

Membrane proteins play a tremendously important role in cell physiology and serve as a target for an increasing number of drugs. Structural information is key to understanding their function and for developing new strategies for combating disease. However, the complex physical chemistry associated with membrane proteins has made them more difficult to study than their soluble cousins. Electron crystallography has historically been a successful method for solving membrane protein structures and has the advantage of providing a native lipid environment for these proteins. Specifically, when membrane proteins form two-dimensional arrays within a lipid bilayer, electron microscopy can be used to collect images and diffraction and the corresponding data can be combined to produce a three-dimensional reconstruction, which under favorable conditions can extend to atomic resolution. Like X-ray crystallography, the quality of the structures are very much dependent on the order and size of the crystals. However, unlike X-ray crystallography, high-throughput methods for screening crystallization trials for electron crystallography are not in general use. In this chapter, we describe two alternative methods for high-throughput screening of membrane protein crystallization within the lipid bilayer. The first method relies on the conventional use of dialysis for removing detergent and thus reconstituting the bilayer; an array of dialysis wells in the standard 96-well format allows the use of a liquid-handling robot and greatly increases throughput. The second method relies on titration of cyclodextrin as a chelating agent for detergent; a specialized pipetting robot has been designed not only to add cyclodextrin in a systematic way, but to use light scattering to monitor the reconstitution process. In addition, the use of liquid-handling robots for making negatively stained grids and methods for automatically imaging samples in the electron microscope are described.

During locomotion in vertebrates, reticulospinal neurons in the hindbrain play critical roles in providing descending excitation to the spinal cord locomotor systems. However, despite the fact that many genes that are used to classify the neuronal identities of neurons in the hindbrain have been identified, the molecular identity of the reticulospinal neurons that are critically involved in locomotor drive is not well understood. Chx10-expressing neurons (V2a neurons) are ipsilaterally projecting glutamatergic neurons in the spinal cord and the hindbrain. Many of the V2a neurons in the hindbrain are known to project to the spinal cord in zebrafish, making hindbrain V2a neurons a prime candidate in descending locomotor drive. Results We investigated the roles of hindbrain V2a neurons using optogenetic and electrophysiological approaches. The forced activation of hindbrain V2a neurons using channelrhodopsin efficiently evoked swimming, whereas the forced inactivation of them using Archearhodopsin3 or Halorhodpsin reliably stopped ongoing swimming. Electrophysiological recordings of two populations of hindbrain reticulospinal V2a neurons showed that they were active during swimming. One population of neurons, small V2a neurons in the caudal hindbrain, fired with low rhythmicity, whereas the other population of neurons, large reticulospinal V2a neurons, called MiV1 neurons, fired more rhythmically. Conclusions These results indicated that hindbrain reticulospinal V2a neurons play critical roles in providing excitation to the spinal locomotor circuits during swimming by providing both tonic and phasic inputs to the circuits.

Nonvisual photosensation enables animals to sense light without sight. However, the cellular and molecular mechanisms of nonvisual photobehaviors are poorly understood, especially in vertebrate animals. Here, we describe the photomotor response (PMR), a robust and reproducible series of motor behaviors in zebrafish that is elicited by visual wavelengths of light but does not require the eyes, pineal gland, or other canonical deep-brain photoreceptive organs. Unlike the relatively slow effects of canonical nonvisual pathways, motor circuits are strongly and quickly (seconds) recruited during the PMR behavior. We find that the hindbrain is both necessary and sufficient to drive these behaviors. Using in vivo calcium imaging, we identify a discrete set of neurons within the hindbrain whose responses to light mirror the PMR behavior. Pharmacological inhibition of the visual cycle blocks PMR behaviors, suggesting that opsin-based photoreceptors control this behavior. These data represent the first known light-sensing circuit in the vertebrate hindbrain.

The brain represents sensory information in the coordinated activity of neuronal ensembles. Although the microcircuits underlying olfactory processing are well characterized in Drosophila, no studies to date have examined the encoding of odor identity by populations of neurons and related it to the odor specificity of olfactory behavior. Here we used two-photon Ca(2+) imaging to record odor-evoked responses from >100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity. Using a series of increasingly similar odor blends, we identified conditions in which odor discrimination is difficult behaviorally. We found that MB ensemble responses accounted well for olfactory acuity in this task. Kenyon cell ensembles with as few as 25 cells were sufficient to match behavioral discrimination accuracy. Using a generalization task, we demonstrated that the MB population code could predict the flies' responses to novel odors. The degree to which flies generalized a learned aversive association to unfamiliar test odors depended upon the relative similarity between the odors' evoked MB activity patterns. Discrimination and generalization place different demands on the animal, yet the flies' choices in these tasks were reliably predicted based on the amount of overlap between MB activity patterns. Therefore, these different behaviors can be understood in the context of a single physiological framework.