In general, neurons in insects and many other invertebrate groups are individually recognizable, enabling us to assign an index number to specific neurons in a manner which is rarely possible in a vertebrate brain. This endows many studies on insect nervous systems with the opportunity to document neurons with great precision, so that in favourable cases we can return to the same neuron or neuron type repeatedly so as to recognize many separate morphological classes. The visual system of the fly's compound eye particularly provides clear examples of the accuracy of neuron wiring, allowing numerical comparisons between representatives of the same cell type, and estimates of the accuracy of their wiring.

Ventral tegmental area (VTA) glutamate neurons are important components of reward circuitry, but whether they are subject to cholinergic modulation is unknown. To study this, we used molecular, physiological, and photostimulation techniques to examine nicotinic acetylcholine receptors (nAChRs) in VTA glutamate neurons. Cells in the medial VTA, where glutamate neurons are enriched, are responsive to acetylcholine (ACh) released from cholinergic axons. VTA VGLUT2 neurons express mRNA and protein subunits known to comprise heteromeric nAChRs. Electrophysiology, coupled with two-photon microscopy and laser flash photolysis of photoactivatable nicotine, was used to demonstrate nAChR functional activity in the somatodendritic subcellular compartment of VTA VGLUT2 neurons. Finally, optogenetic isolation of intrinsic VTA glutamatergic microcircuits along with gene-editing techniques demonstrated that nicotine potently modulates excitatory transmission within the VTA via heteromeric nAChRs. These results indicate that VTA glutamate neurons are modulated by cholinergic mechanisms and participate in the cascade of physiological responses to nicotine exposure.

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

A central tenet of biology is that globular proteins have a unique 3D structure under physiological conditions. Recent work has challenged this notion by demonstrating that some proteins switch folds, a process that involves remodeling of secondary structure in response to a few mutations (evolved fold switchers) or cellular stimuli (extant fold switchers). To date, extant fold switchers have been viewed as rare byproducts of evolution, but their frequency has been neither quantified nor estimated. By systematically and exhaustively searching the Protein Data Bank (PDB), we found ∼100 extant fold-switching proteins. Furthermore, we gathered multiple lines of evidence suggesting that these proteins are widespread in nature. Based on these lines of evidence, we hypothesized that the frequency of extant fold-switching proteins may be underrepresented by the structures in the PDB. Thus, we sought to identify other putative extant fold switchers with only one solved conformation. To do this, we identified two characteristic features of our ∼100 extant fold-switching proteins, incorrect secondary structure predictions and likely independent folding cooperativity, and searched the PDB for other proteins with similar features. Reassuringly, this method identified dozens of other proteins in the literature with indication of a structural change but only one solved conformation in the PDB. Thus, we used it to estimate that 0.5-4% of PDB proteins switch folds. These results demonstrate that extant fold-switching proteins are likely more common than the PDB reflects, which has implications for cell biology, genomics, and human health.

RNA is the fundamental information transfer system in the cell. The ability to follow single messenger RNAs (mRNAs) from transcription to degradation with fluorescent probes gives quantitative information about how the information is transferred from DNA to proteins. This review focuses on the latest technological developments in the field of single-mRNA detection and their usage to study gene expression in both fixed and live cells. By describing the application of these imaging tools, we follow the journey of mRNA from transcription to decay in single cells, with single-molecule resolution. We review current theoretical models for describing transcription and translation that were generated by single-molecule and single-cell studies. These methods provide a basis to study how single-molecule interactions generate phenotypes, fundamentally changing our understating of gene expression regulation.

The brain is a network of neurons and its biological output is behaviour. This is an exciting age, with a growing acknowledgement that the comprehensive compilation of synaptic circuits densely reconstructed in the brains of model species is now both technologically feasible and a scientifically enabling possibility in neurobiology, much as 30 years ago genomics was in molecular biology and genetics. Implemented by huge advances in electron microscope technology, especially focused ion beam-scanning electron microscope (FIB-SEM) milling (see Glossary), image capture and alignment, and computer-aided reconstruction of neuron morphologies, enormous progress has been made in the last decade in the detailed knowledge of the actual synaptic circuits formed by real neurons, in various brain regions of the fly It is useful to distinguish synaptic pathways that are major, with 100 or more presynaptic contacts, from those that are minor, with fewer than about 10; most neurites are both presynaptic and postsynaptic, and all synaptic sites have multiple postsynaptic dendrites. Work on has spearheaded these advances because cell numbers are manageable, and neuron classes are morphologically discrete and genetically identifiable, many confirmed by reporters. Recent advances are destined within the next few years to reveal the complete connectome in an adult fly, paralleling advances in the larval brain that offer the same prospect possibly within an even shorter time frame. The final amendment and validation of segmented bodies by human proof-readers remains the most time-consuming step, however. The value of a complete connectome in is that, by targeting to specific neurons transgenes that either silence or activate morphologically identified circuits, and then identifying the resulting behavioural outcome, we can determine the causal mechanism for behaviour from its loss or gain. More importantly, the connectome reveals hitherto unsuspected pathways, leading us to seek novel behaviours for these. Circuit information will eventually be required to understand how differences between brains underlie differences in behaviour, and especially to herald yet more advanced connectomic strategies for the vertebrate brain, with an eventual prospect of understanding cognitive disorders having a connectomic basis. Connectomes also help us to identify common synaptic circuits in different species and thus to reveal an evolutionary progression in candidate pathways.

Macroglial cells in the central nervous system exhibit regional specialization and carry out region-specific functions. Diverse glial cells arise from specific progenitors in specific spatiotemporal patterns. This raises an interesting possibility that there exist glial precursors with distinct developmental fates, which govern region-specific gliogenesis. Here we mapped the glial progeny produced by the type II neuroblasts, which, like vertebrate radial glia cells, yield both neurons and glia via intermediate neural progenitors (INPs). Distinct type II neuroblasts produce different characteristic sets of glia. A single INP can make both astrocyte-like and ensheathing glia, which co-occupy a relatively restrictive subdomain. Blocking apoptosis uncovers further lineage distinctions in the specification, proliferation, and survival of glial precursors. Both the switch from neurogenesis to gliogenesis and the subsequent glial expansion depend on Notch signaling. Taken together, lineage origins preconfigure the development of individual glial precursors with involvement of serial Notch actions in promoting gliogenesis.

Painful events establish opponent memories: cues that precede pain are remembered negatively, whereas cues that follow pain, thus coinciding with relief are recalled positively. How do individual reinforcement-signaling neurons contribute to this "timing-dependent valence-reversal?" We addressed this question using an optogenetic approach in the fruit fly. Two types of fly dopaminergic neuron, each comprising just one paired cell, indeed established learned avoidance of odors that preceded their photostimulation during training, and learned approach to odors that followed the photostimulation. This is in striking parallel to punishment versus relief memories reinforced by a real noxious event. For only one of these neuron types, both effects were strong enough for further analyses. Notably, interfering with dopamine biosynthesis in these neurons partially impaired the punishing effect, but not the relieving after-effect of their photostimulation. We discuss how this finding constraints existing computational models of punishment versus relief memories and introduce a new model, which also incorporates findings from mammals. Furthermore, whether using dopaminergic neuron photostimulation or a real noxious event, more prolonged punishment led to stronger relief. This parametric feature of relief may also apply to other animals and may explain particular aspects of related behavioral dysfunction in humans.

Human immunodeficiency virus type 1 (HIV-1) assembly occurs on the inner leaflet of the host cell plasma membrane, incorporating the essential viral envelope glycoprotein (Env) within a budding lattice of HIV-1 Gag structural proteins. The mechanism by which Env incorporates into viral particles remains poorly understood. To determine the mechanism of recruitment of Env to assembly sites, we interrogate the subviral angular distribution of Env on cell-associated virus using multicolor, three-dimensional (3D) superresolution microscopy. We demonstrate that, in a manner dependent on cell type and on the long cytoplasmic tail of Env, the distribution of Env is biased toward the necks of cell-associated particles. We postulate that this neck-biased distribution is regulated by vesicular retention and steric complementarity of Env during independent Gag lattice formation.

The GAL4-UAS system has proven its versatility in studying the function and expression patterns of neurons the Drosophila central nervous system. Although the GAL4 system has been used for 25 years, recent genetic intersectional tools have enabled genetic targeting of very small numbers of neurons aiding in the understanding of their function. This split-GAL4 system is extremely powerful for studying neuronal morphology and the neural basis of animal behavior. However, choosing lines to intersect that have overlapping patterns restricted to one to a few neurons has been cumbersome. This challenge is now growing as the collections of GAL4 driver lines has increased. Here we present a new method and software plug-in for Fiji to dramatically improve the speed of querying large databases of potential lines to intersect and aid in the split-GAL4 creation. We also provide pre-computed datasets for the Janelia GAL4 (5,738 lines) and VT GAL4 (7,429 lines) of the Drosophila central nervous system (CNS). The tool reduced our split-GAL4 creation effort dramatically.