Virtual reality (VR) holds great promise as a tool to study the neural circuitry underlying animal behaviors. Here, we discuss the advantages of VR and the experimental paradigms and technologies that enable closed loop behavioral experiments. We review recent results from VR research in genetic model organisms where the potential combination of rich behaviors, genetic tools and cutting edge neural recording techniques are leading to breakthroughs in our understanding of the neural basis of behavior. We also discuss several key issues to consider when performing VR experiments and provide an outlook for the future of this exciting experimental toolkit.

Transcription is reported to be spatially compartmentalized in nuclear transcription factories with clusters of RNA polymerase II (Pol II). However, little is known about when these foci assemble or their relative stability. We developed a quantitative single-cell approach to characterize protein spatiotemporal organization, with single-molecule sensitivity in live eukaryotic cells. We observed that Pol II clusters form transiently, with an average lifetime of 5.1 (± 0.4) seconds, which refutes the notion that they are statically assembled substructures. Stimuli affecting transcription yielded orders-of-magnitude changes in the dynamics of Pol II clusters, which implies that clustering is regulated and plays a role in the cell’s ability to effect rapid response to external signals. Our results suggest that transient crowding of enzymes may aid in rate-limiting steps of gene regulation.

The presumptive altered dynamics of transient molecular interactions in vivo contributing to neurodegenerative diseases have remained elusive. Here, using single-molecule localization microscopy, we show that disease-inducing Huntingtin (mHtt) protein fragments display three distinct dynamic states in living cells - 1) fast diffusion, 2) dynamic clustering and 3) stable aggregation. Large, stable aggregates of mHtt exclude chromatin and form 'sticky' decoy traps that impede target search processes of key regulators involved in neurological disorders. Functional domain mapping based on super-resolution imaging reveals an unexpected role of aromatic amino acids in promoting protein-mHtt aggregate interactions. Genome-wide expression analysis and numerical simulation experiments suggest mHtt aggregates reduce transcription factor target site sampling frequency and impair critical gene expression programs in striatal neurons. Together, our results provide insights into how mHtt dynamically forms aggregates and disrupts the finely-balanced gene control mechanisms in neuronal cells.

Cellular messenger RNA levels are achieved by the combinatorial complexity of factors controlling transcription, yet the small number of molecules involved in these pathways fluctuates stochastically. It has not yet been experimentally possible to observe the activity of single polymerases on an endogenous gene to elucidate how these events occur in vivo. Here, we describe a method of fluctuation analysis of fluorescently labeled RNA to measure dynamics of nascent RNA–including initiation, elongation, and termination–at an active yeast locus. We find no transcriptional memory between initiation events, and elongation speed can vary by threefold throughout the cell cycle. By measuring the abundance and intranuclear mobility of an upstream transcription factor, we observe that the gene firing rate is directly determined by trans-activating factor search times.

Although mRNA translation is a fundamental biological process, it has never been imaged in real-time with single molecule precision in vivo. To achieve this, we developed Nascent Chain Tracking (NCT), a technique that uses multi-epitope tags and antibody-based fluorescent probes to quantify single mRNA protein synthesis dynamics. NCT reveals an elongation rate of ~10 amino acids per second, with initiation occurring stochastically every ~30 s. Polysomes contain ~1 ribosome every 200-900 nucleotides and are globular rather than elongated in shape. By developing multi-color probes, we show most polysomes act independently; however, a small fraction (~5%) form complexes in which two distinct mRNAs can be translated simultaneously. The sensitivity and versatility of NCT make it a powerful new tool for quantifying mRNA translation kinetics.

Electrical recordings from a large array of electrodes give us access to neural population activity with single-cell, single-spike resolution. These recordings contain extracellular spikes which must be correctly detected and assigned to individual neurons. Despite numerous spike-sorting techniques developed in the past, a lack of high-quality ground-truth datasets hinders the validation of spike-sorting approaches. Furthermore, existing approaches requiring manual corrections are not scalable for hours of recordings exceeding 100 channels. To address these issues, we built a comprehensive spike-sorting pipeline that performs reliably under noise and probe drift by incorporating a channel-covariance feature and a clustering based on fast density-peak finding. We validated performance of our workflow using multiple ground-truth datasets that recently became available. Our software scales linearly and processes a 1000-channel recording in real-time using a single workstation. Accurate, real-time spike sorting from large recording arrays will enable more precise control of closed-loop feedback experiments and brain-computer interfaces.

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55–330 times faster and 2–5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.

Research on early postimplantation mammalian development has been limited by the small size and intrauterine confinement of the developing embryos. Owing to the inability to observe and manipulate living embryos at these stages in utero, the establishment of robust ex utero embryo-culture systems that capture prolonged periods of mouse development has been an important research goal. In the last few years, these methods have been significantly improved by the optimization and enhancement of in vitro culture systems sustaining embryo development during peri-implantation stages for several species, and more recently, proper growth of natural mouse embryos from pregastrulation to late organogenesis stages and of embryonic stem cell (ES)-derived synthetic embryo models until early organogenesis stages. Here, we discuss the most recent ex utero embryo-culture systems established to date for rodents, nonhuman primates, and humans. We emphasize their technical aspects and developmental timeframe and provide insights into the new opportunities that these methods will contribute to the study of natural and synthetic mammalian embryogenesis and the stem-cell field.

The brain of fruit fly Drosophila melanogaster has been used as a model system for functional analysis of neuronal circuits, including connectomics research, due to its modest size (~700 μm) and availability of abundant molecular genetics tools for visualizing neurons. Three-dimensional (3D) reconstruction of high-resolution images of neurons or circuits visualized with appropriate methods is a critical step for obtaining information such as morphology and connectivity patterns of neuronal circuits. In this chapter, we introduce methods for generating 3D reconstructed images with data acquired from confocal laser scanning microscopy (CLSM) or electron microscopy (EM) to analyze neuronal circuits found in the central nervous system (CNS) of the fruit fly. Comparisons of different algorithms and strategies for reconstructing neuronal circuits, using actual studies as references, will be discussed within this chapter.