Although the endoplasmic reticulum (ER) extends throughout axons and axonal ER dysfunction is implicated in numerous neurological diseases, its role at nerve terminals is poorly understood. We developed novel genetically encoded ER-targeted low-affinity Ca(2+) indicators optimized for examining axonal ER Ca(2+). Our experiments revealed that presynaptic function is tightly controlled by ER Ca(2+) content. We found that neuronal activity drives net Ca(2+) uptake into presynaptic ER although this activity does not contribute significantly to shaping cytosolic Ca(2+) except during prolonged repetitive firing. In contrast, we found that axonal ER acts as an actuator of plasma membrane (PM) function: [Ca(2+)]ER controls STIM1 activation in presynaptic terminals, which results in the local modulation of presynaptic function, impacting activity-driven Ca(2+) entry and release probability. These experiments reveal a critical role of presynaptic ER in the control of neurotransmitter release and will help frame future investigations into the molecular basis of ER-driven neuronal disease states.

Glia play crucial roles in the development and homeostasis of the nervous system. While the GLIA in the Drosophila embryo have been well characterized, their study in the adult nervous system has been limited. Here, we present a detailed description of the glia in the adult nervous system, based on the analysis of some 500 glial drivers we identified within a collection of synthetic GAL4 lines. We find that glia make up ∼10% of the cells in the nervous system and envelop all compartments of neurons (soma, dendrites, axons) as well as the nervous system as a whole. Our morphological analysis suggests a set of simple rules governing the morphogenesis of glia and their interactions with other cells. All glial subtypes minimize contact with their glial neighbors but maximize their contact with neurons and adapt their macromorphology and micromorphology to the neuronal entities they envelop. Finally, glial cells show no obvious spatial organization or registration with neuronal entities. Our detailed description of all glial subtypes and their regional specializations, together with the powerful genetic toolkit we provide, will facilitate the functional analysis of glia in the mature nervous system. GLIA 2017.

The cellular mechanisms governing non-muscle myosin II (NM2) filament assembly are largely unknown. Using EGFP-NM2A knock-in fibroblasts and multiple super-resolution imaging modalities, we characterized and quantified the sequential amplification of NM2 filaments within lamellae, wherein filaments emanating from single nucleation events continuously partition, forming filament clusters that populate large-scale actomyosin structures deeper in the cell. Individual partitioning events coincide spatially and temporally with the movements of diverging actin fibres, suppression of which inhibits partitioning. These and other data indicate that NM2A filaments are partitioned by the dynamic movements of actin fibres to which they are bound. Finally, we showed that partition frequency and filament growth rate in the lamella depend on MLCK, and that MLCK is competing with centrally active ROCK for a limiting pool of monomer with which to drive lamellar filament assembly. Together, our results provide new insights into the mechanism and spatio-temporal regulation of NM2 filament assembly in cells.

Place cells in the CA1 region of the hippocampus express location-specific firing despite receiving a steady barrage of heterogeneously tuned excitatory inputs that should compromise output dynamic range and timing. We examined the role of synaptic inhibition in countering the deleterious effects of off-target excitation. Intracellular recordings in behaving mice demonstrate that bimodal excitation drives place cells, while unimodal excitation drives weaker or no spatial tuning in interneurons. Optogenetic hyperpolarization of interneurons had spatially uniform effects on place cell membrane potential dynamics, substantially reducing spatial selectivity. These data and a computational model suggest that spatially uniform inhibitory conductance enhances rate coding in place cells by suppressing out-of-field excitation and by limiting dendritic amplification. Similarly, we observed that inhibitory suppression of phasic noise generated by out-of-field excitation enhances temporal coding by expanding the range of theta phase precession. Thus, spatially uniform inhibition allows proficient and flexible coding in hippocampal CA1 by suppressing heterogeneously tuned excitation.

Although myosin II filaments are known to exist in non-muscle cells, their dynamics and organization are incompletely understood. Here, we combined structured illumination microscopy with pharmacological and genetic perturbations, to study the process of actomyosin cytoskeleton self-organization into arcs and stress fibres. A striking feature of the myosin II filament organization was their 'registered' alignment into stacks, spanning up to several micrometres in the direction orthogonal to the parallel actin bundles. While turnover of individual myosin II filaments was fast (characteristic half-life time 60 s) and independent of actin filament turnover, the process of stack formation lasted a longer time (in the range of several minutes) and required myosin II contractility, as well as actin filament assembly/disassembly and crosslinking (dependent on formin Fmnl3, cofilin1 and α-actinin-4). Furthermore, myosin filament stack formation involved long-range movements of individual myosin filaments towards each other suggesting the existence of attractive forces between myosin II filaments. These forces, possibly transmitted via mechanical deformations of the intervening actin filament network, may in turn remodel the actomyosin cytoskeleton and drive its self-organization.

A complex brain consists of multiple intricate neural networks assembled from distinct sets of input and output neurons as well as region-specific local interneurons. Within a given anatomical set, there exist diverse neuronal types that can vary in morphology, neural physiology, and modes of neurotransmission. The genetic programs that guide specification of neuronal types during neurogenesis preconfigure the brain. This is best demonstrated in the Drosophila central brain, which is composed of ∼100 pairs of individually tailored neuronal lineages. Each neuronal lineage (the neurons/glia produced from a single stem cell) can contain multiple morphological classes of neurons that can consist of many analogous neuronal types. The detailed patterns of neuronal diversification are lineage-specific and can differ drastically even among neighboring neuronal lineages. Furthermore, the interrelationships between neuronal lineages and neural networks are complex. These phenomena underscore the importance of tracking all neuronal lineages in understanding brain development and evolution.

Extracellular expression of heat shock protein 90 (eHsp90) by tumor cells is correlated with malignancy. Development of small molecule probes that can detect eHsp90 in vivo may therefore have utility in the early detection of malignancy. We synthesized a cell impermeable far-red fluorophore-tagged Hsp90 inhibitor to target eHsp90 in vivo. High resolution confocal and lattice light sheet microscopy show that probe-bound eHsp90 accumulates in punctate structures on the plasma membrane of breast tumor cells and is actively internalized. The extent of internalization correlates with tumor cell aggressiveness, and this process can be induced in benign cells by over-expressing p110HER2. Whole body cryoslicing, imaging and histology of flank and spontaneous tumor-bearing mice strongly suggests that eHsp90 expression and internalization is a phenomenon unique to tumor cells in vivo and may provide an 'Achilles heel' for the early diagnosis of metastatic disease and targeted drug delivery.

Fluorescent proteins (FPs) that can be optically highlighted enable PALM super-resolution microscopy and pulse-chase experiments of cellular molecules. Most FPs evolved in cytoplasmic environments either in the original source organism or in the cytoplasm of bacteria during the course of optimization for research applications. Consequently, many FPs may fold incorrectly in the chemically distinct environments in subcellular organelles. Here, we describe the first monomeric photoswitchable (from green to bright red) FP adapted for oxidizing environments.

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.

In this paper, we present a novel error measure to compare a computer-generated segmentation of images or volumes against ground truth. This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations that we usually encounter in biomedical image processing: (1) Some errors, like small boundary shifts, are tolerable in practice. Which errors are tolerable is application dependent and should be explicitly expressible in the measure. (2) Non-tolerable errors have to be corrected manually. The effort needed to do so should be reflected by the error measure. Our measure is the minimal weighted sum of split and merge operations to apply to one segmentation such that it resembles another segmentation within specified tolerance bounds. This is in contrast to other commonly used measures like Rand index or variation of information, which integrate small, but tolerable, differences. Additionally, the TED provides intuitive numbers and allows the localization and classification of errors in images or volumes. We demonstrate the applicability of the TED on 3D segmentations of neurons in electron microscopy images where topological correctness is arguable more important than exact boundary locations. Furthermore, we show that the TED is not just limited to evaluation tasks. We use it as the loss function in a max-margin learning framework to find parameters of an automatic neuron segmentation algorithm. We show that training to minimize the TED, i.e., to minimize crucial errors, leads to higher segmentation accuracy compared to other learning methods.