Neural circuit assembly features simultaneous targeting of numerous neuronal processes from constituent neuron types, yet the dynamics is poorly understood. Here, we use the Drosophila olfactory circuit to investigate dynamic cellular processes by which olfactory receptor neurons (ORNs) target axons precisely to specific glomeruli in the ipsi- and contralateral antennal lobes. Time-lapse imaging of individual axons from 30 ORN types revealed a rich diversity in extension speed, innervation timing, and ipsilateral branch locations and identified that ipsilateral targeting occurs via stabilization of transient interstitial branches. Fast imaging using adaptive optics-corrected lattice light-sheet microscopy showed that upon approaching target, many ORN types exhibiting "exploring branches" consisted of parallel microtubule-based terminal branches emanating from an F-actin-rich hub. Antennal nerve ablations uncovered essential roles for bilateral axons in contralateral target selection and for ORN axons to facilitate dendritic refinement of postsynaptic partner neurons. Altogether, these observations provide cellular bases for wiring specificity establishment.

Astrocytes are essential cells of the central nervous system, characterized by dynamic relationships with neurons that range from functional metabolic interactions and regulation of neuronal firing activities, to the release of neurotrophic and neuroprotective factors. In Parkinson’s disease (PD), dopaminergic neurons are progressively lost during the course of the disease, but the effects of PD on astrocytes and astrocyte-to-neuron communication remains largely unknown. This study focuses on the effects of the PD-related mutation LRRK2 G2019S in astrocytes generated from patient-derived induced pluripotent stem cells. We report the alteration of extracellular vesicle (EV) biogenesis in astrocytes, and we identify the abnormal accumulation of key PD-related proteins within multi vesicular bodies (MVBs). We found that dopaminergic neurons internalize astrocyte-secreted EVs and that LRRK2 G2019S EVs are abnormally enriched in neurites and fail to provide full neurotrophic support to dopaminergic neurons. Thus, dysfunctional astrocyte-to-neuron communication via altered EV biological properties may participate in the progression of PD.

Few genetically dominant mutations involved in human disease have been fully explained at the molecular level. In cases where the mutant gene encodes a transcription factor, the dominant-negative mode of action of the mutant protein is particularly poorly understood. Here, we studied the genome-wide mechanism underlying a dominant-negative form of the SOX18 transcription factor (SOX18RaOp) responsible for both the classical mouse mutant Ragged Opossum and the human genetic disorder Hypotrichosis-lymphedema-telangiectasia-renal defect syndrome. Combining three single-molecule imaging assays in living cells together with genomics and proteomics analysis, we found that SOX18RaOp disrupts the system through an accumulation of molecular interferences which impair several functional properties of the wild-type SOX18 protein, including its target gene selection process. The dominant-negative effect is further amplified by poisoning the interactome of its wild-type counterpart, which perturbs regulatory nodes such as SOX7 and MEF2C. Our findings explain in unprecedented detail the multi-layered process that underpins the molecular aetiology of dominant-negative transcription factor function.

Few genetically dominant mutations involved in human disease have been fully explained at the molecular level. In cases where the mutant gene encodes a transcription factor, the dominant-negative mode of action of the mutant protein is particularly poorly understood. Here, we studied the genome-wide mechanism underlying a dominant-negative form of the SOX18 transcription factor (SOX18RaOp) responsible for both the classical mouse mutant Ragged Opossum and the human genetic disorder Hypotrichosis-lymphedema-telangiectasia-renal defect syndrome. Combining three single-molecule imaging assays in living cells together with genomics and proteomics analysis, we found that SOX18RaOp disrupts the system through an accumulation of molecular interferences which impair several functional properties of the wild-type SOX18 protein, including its target gene selection process. The dominant-negative effect is further amplified by poisoning the interactome of its wild-type counterpart, which perturbs regulatory nodes such as SOX7 and MEF2C. Our findings explain in unprecedented detail the multi-layered process that underpins the molecular aetiology of dominant-negative transcription factor function.

Many genomes contain rapidly evolving and highly divergent genes whose homology to genes of known function often cannot be determined from sequence similarity alone. However, coding sequence-independent features of genes, such as intron-exon boundaries, often evolve more slowly than coding sequences and can provide complementary evidence for homology. We found that a linear logistic regression classifier using only structural features of rapidly evolving bicycle aphid effector genes identified many putative bicycle homologs in aphids, phylloxerids, and scale insects, whereas sequence similarity search methods yielded few homologs in most aphids and no homologs in phylloxerids and scale insects. Subsequent examination of sequence features and intron locations supported homology assignments. Differential expression studies of newly-identified bicycle homologs, together with prior proteomic studies, support the hypothesis that BICYCLE proteins act as plant effector proteins in many aphid species and perhaps also in phylloxerids and scale insects.

Activity-driven changes in the neuronal surface glycoproteome are known to occur with synapse formation, plasticity and related diseases, but their mechanistic basis and significance are unclear. Here, we observed that -glycans on surface glycoproteins of dendrites shift from immature to mature forms containing sialic acid in response to increased neuronal activation. In exploring the basis of these -glycosylation alterations, we discovered they result from the growth and proliferation of Golgi satellites scattered throughout the dendrite. Golgi satellites that formed during neuronal excitation were in close association with ER exit sites and early endosomes and contained glycosylation machinery without the Golgi structural protein, GM130. They functioned as distal glycosylation stations in dendrites, terminally modifying sugars either on newly synthesized glycoproteins passing through the secretory pathway, or on surface glycoproteins taken up from the endocytic pathway. These activities led to major changes in the dendritic surface of excited neurons, impacting binding and uptake of lectins, as well as causing functional changes in neurotransmitter receptors such as nicotinic acetylcholine receptors. Neural activity thus boosts the activity of the dendrite's satellite micro-secretory system by redistributing Golgi enzymes involved in glycan modifications into peripheral Golgi satellites. This remodeling of the neuronal surface has potential significance for synaptic plasticity, addiction and disease.

Sensory cues that precede reward acquire predictive (expected value) and incentive (drive reward-seeking action) properties. Mesolimbic dopamine neurons' responses to sensory cues correlate with both expected value and reward-seeking action. This has led to the proposal that phasic dopamine responses may be sufficient to inform value-based decisions, elicit actions, and/or induce motivational states; however, causal tests are incomplete. Here, we show that direct dopamine neuron stimulation, both calibrated to physiological and greater intensities, at the time of reward can be sufficient to induce and maintain reward seeking (reinforcing) although replacement of a cue with stimulation is insufficient to induce reward seeking or act as an informative cue. Stimulation of descending cortical inputs, one synapse upstream, are sufficient for reinforcement and cues to future reward. Thus, physiological activation of mesolimbic dopamine neurons can be sufficient for reinforcing properties of reward without being sufficient for the predictive and incentive properties of cues.

The importance of mechanical force in biology is evident across diverse length scales, ranging from tissue morphogenesis during embryo development to mechanotransduction across single adhesion proteins at the cell surface. Consequently, many force measurement techniques rely on optical microscopy to measure forces being applied by cells on their environment, to visualize specimen deformations due to external forces, or even to directly apply a physical perturbation to the sample via photoablation or optogenetic tools. Recent developments in advanced microscopy offer improved approaches to enhance spatiotemporal resolution, imaging depth, and sample viability. These advances can be coupled with already existing force measurement methods to improve sensitivity, duration and speed, amongst other parameters. However, gaining access to advanced microscopy instrumentation and the expertise necessary to extract meaningful insights from these techniques is an unavoidable hurdle. In this Live Cell Imaging special issue Review, we survey common microscopy-based force measurement techniques and examine how they can be bolstered by emerging microscopy methods. We further explore challenges related to the accompanying data analysis in biomechanical studies and discuss the various resources available to tackle the global issue of technology dissemination, an important avenue for biologists to gain access to pre-commercial instruments that can be leveraged for biomechanical studies.

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but the need for activating only single isolated emitters limits imaging speed and labeling density. Here, we overcome this major limitation using deep learning. We developed DECODE, a computational tool that can localize single emitters at high density in 3D with highest accuracy for a large range of imaging modalities and conditions. In a public software benchmark competition, it outperformed all other fitters on 12 out of 12 data-sets when comparing both detection accuracy and localization error, often by a substantial margin. DECODE allowed us to take live-cell SMLM data with reduced light exposure in just 3 seconds and to image microtubules at ultra-high labeling density. Packaged for simple installation and use, DECODE will enable many labs to reduce imaging times and increase localization density in SMLM.Competing Interest StatementThe authors have declared no competing interest.

Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual's behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.