The budding yeast centromere contains Cse4, a specialized histone H3 variant. Fluorescence pulse-chase analysis of an internally tagged Cse4 reveals that it is replaced with newly synthesized molecules in S phase, remaining stably associated with centromeres thereafter. In contrast, C-terminally-tagged Cse4 is functionally impaired, showing slow cell growth, cell lethality at elevated temperatures, and extra-centromeric nuclear accumulation. Recent studies using such strains gave conflicting findings regarding the centromeric abundance and cell cycle dynamics of Cse4. Our findings indicate that internally tagged Cse4 is a better reporter of the biology of this histone variant. Furthermore, the size of centromeric Cse4 clusters was precisely mapped with a new 3D-PALM method, revealing substantial compaction during anaphase. Cse4-specific chaperone Scm3 displays steady-state, stoichiometric co-localization with Cse4 at centromeres throughout the cell cycle, while undergoing exchange with a nuclear pool. These findings suggest that a stable Cse4 nucleosome is maintained by dynamic chaperone-in-residence Scm3.DOI: http://dx.doi.org/10.7554/eLife.02203.001.

To investigate the fundamental question of how nervous systems encode, organize, and sequence behaviors, Kato et al. imaged neural activity with cellular resolution across the brain of the worm Caenorhabditis elegans. Locomotion behavior seems to be continuously represented by cyclical patterns of distributed neural activity that are present even in immobilized animals.

The molecular mechanism responsible for capturing, sorting and retrieving vesicle membrane proteins following triggered exocytosis is not understood. Here we image the post-fusion release and then capture of a vesicle membrane protein, the vesicular acetylcholine transporter, from single vesicles in living neuroendocrine cells. We combine these measurements with super-resolution interferometric photo-activation localization microscopy and electron microscopy, and modelling to map the nanometer-scale topography and architecture of the structures responsible for the transporter’s capture following exocytosis. We show that after exocytosis, the transporter rapidly diffuses into the plasma membrane, but most travels only a short distance before it is locally captured over a dense network of membrane-resident clathrin-coated structures. We propose that the extreme density of these structures acts as a short-range diffusion trap. They quickly sequester diffusing vesicle material and limit its spread across the membrane. This system could provide a means for clathrin-mediated endocytosis to quickly recycle vesicle proteins in highly excitable cells.

Transcription, the first step of gene expression, is exquisitely regulated in higher eukaryotes to ensure correct development and homeostasis. Traditional biochemical, genetic, and genomic approaches have proved successful at identifying factors, regulatory sequences, and potential pathways that modulate transcription. However, they typically only provide snapshots or population averages of the highly dynamic, stochastic biochemical processes involved in transcriptional regulation. Single-molecule live-cell imaging has, therefore, emerged as a complementary approach capable of circumventing these limitations. By observing sequences of molecular events in real time as they occur in their native context, imaging has the power to derive cause-and-effect relationships and quantitative kinetics to build predictive models of transcription. Ongoing progress in fluorescence imaging technology has brought new microscopes and labeling technologies that now make it possible to visualize and quantify the transcription process with single-molecule resolution in living cells and animals. Here we provide an overview of the evolution and current state of transcription imaging technologies. We discuss some of the important concepts they uncovered and present possible future developments that might solve long-standing questions in transcriptional regulation.

The optical microscope has revolutionized biology since at least the 17 Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.

The packaging and budding of Gag polyprotein and viral RNA is a critical step in the HIV-1 life cycle. High-resolution structures of the Gag polyprotein have revealed that the capsid (CA) and spacer peptide 1 (SP1) domains contain important interfaces for Gag self-assembly. However, the molecular details of the multimerization process, especially in the presence of RNA and the cell membrane, have remained unclear. In this work, we investigate the mechanisms that work in concert between the polyproteins, RNA, and membrane to promote immature lattice growth. We develop a coarse-grained (CG) computational model that is derived from subnanometer resolution structural data. Our simulations recapitulate contiguous and hexameric lattice assembly driven only by weak anisotropic attractions at the helical CA-SP1 junction. Importantly, analysis from CG and single-particle tracking photoactivated localization (spt-PALM) trajectories indicates that viral RNA and the membrane are critical constituents that actively promote Gag multimerization through scaffolding, while overexpression of short competitor RNA can suppress assembly. We also find that the CA amino-terminal domain imparts intrinsic curvature to the Gag lattice. As a consequence, immature lattice growth appears to be coupled to the dynamics of spontaneous membrane deformation. Our findings elucidate a simple network of interactions that regulate the early stages of HIV-1 assembly and budding.

The termination of the proliferation of Drosophila neural stem cells, also known as neuroblasts (NBs), requires a "decommissioning" phase that is controlled in a lineage-specific manner. Most NBs, with the exception of those of the Mushroom body (MB), are decommissioned by the ecdysone receptor and mediator complex causing them to shrink during metamorphosis, followed by nuclear accumulation of Prospero and cell cycle exit. Here, we demonstrate that the levels of Imp and Syp RNA-binding proteins regulate NB decommissioning. Descending Imp and ascending Syp expression have been shown to regulate neuronal temporal fate. We show that Imp levels decline slower in the MB than other central brain NBs. MB NBs continue to express Imp into pupation, and the presence of Imp prevents decommissioning partly by inhibiting the mediator complex. Late-larval induction of transgenic Imp prevents many non-MB NBs from decommissioning in early pupae. Moreover, the presence of abundant Syp in aged NBs permits Prospero accumulation that, in turn, promotes cell cycle exit. Together our results reveal that progeny temporal fate and progenitor decommissioning are co-regulated in protracted neuronal lineages.

Continuous monitoring of blood pressure in laboratory animals is necessary to understand the effect of treatments for cardiovascular related conditions, such as hypertension. Current methods to measure laboratory rat blood pressure require the animal to be constrained. Our proposed method is a small implantable device which fits around the carotid artery of the rat. Initial data from a mock rat artery setup, with equivalent artery pressure as found in the rat, show that the cuff design effectively detects the pressure change inside the mock artery.

The Importance Weighted Auto Encoder (IWAE) objective has been shown to improve the training of generative models over the standard Variational Auto Encoder (VAE) objective. Here, we derive importance weighted extensions to Adversarial Variational Bayes (AVB) and Adversarial Autoencoder (AAE). These latent variable models use implicitly defined inference networks whose approximate posterior density qφ(z|x) cannot be directly evaluated, an essential ingredient for importance weighting. We show improved training and inference in latent variable models with our adversarially trained importance weighting method, and derive new theoretical connections between adversarial generative model training criteria and marginal likelihood based methods. We apply these methods to the important problem of inferring spiking neural activity from calcium imaging data, a challenging posterior inference problem in neuroscience, and show that posterior samples from the adversarial methods outperform factorized posteriors used in VAEs.