Drosophila has been developed recently as a model system to investigate the molecular and neural mechanisms underlying responses to drugs of abuse. Genetic screens for mutants with altered drug-induced behaviors thus provide an unbiased approach to define novel molecules involved in the process. We identified mutations in the Drosophila LIM-only (LMO) gene, encoding a regulator of LIM-homeodomain proteins, in a genetic screen for mutants with altered cocaine sensitivity. Reduced Lmo function increases behavioral responses to cocaine, while Lmo overexpression causes the opposite effect, reduced cocaine responsiveness. Expression of Lmo in the principal Drosophila circadian pacemaker cells, the PDF-expressing ventral lateral neurons (LN(v)s), is sufficient to confer normal cocaine sensitivity. Consistent with a role for Lmo in LN(v)function,Lmomutants also show defects in circadian rhythms of behavior. However, the role for LN(v)s in modulating cocaine responses is separable from their role as pacemaker neurons: ablation or functional silencing of the LN(v)s reduces cocaine sensitivity, while loss of the principal circadian neurotransmitter PDF has no effect. Together, these results reveal a novel role for Lmo in modulating acute cocaine sensitivity and circadian locomotor rhythmicity, and add to growing evidence that these behaviors are regulated by shared molecular mechanisms. The finding that the degree of cocaine responsiveness is controlled by the Drosophila pacemaker neurons provides a neuroanatomical basis for this overlap. We propose that Lmo controls the responsiveness of LN(v)s to cocaine, which in turn regulate the flies’ behavioral sensitivity to the drug.

Pavlovian fear conditioning is an associative learning paradigm in which mice learn to associate a neutral conditioned stimulus with an aversive unconditioned stimulus. In this study, we demonstrate a novel role for the transcriptional regulator Lmo4 in fear learning. LMO4 is predominantly expressed in pyramidal projection neurons of the basolateral complex of the amygdala (BLC). Mice heterozygous for a genetrap insertion in the Lmo4 locus (Lmo4gt/+), which express 50% less Lmo4 than their wild type (WT) counterparts display enhanced freezing to both the context and the cue in which they received the aversive stimulus. Small-hairpin RNA-mediated knockdown of Lmo4 in the BLC, but not the dentate gyrus region of the hippocampus recapitulated this enhanced conditioning phenotype, suggesting an adult- and brain region-specific role for Lmo4 in fear learning. Immunohistochemical analyses revealed an increase in the number of c-Fos positive puncta in the BLC of Lmo4gt/+ mice in comparison to their WT counterparts after fear conditioning. Lastly, we measured anxiety-like behavior in Lmo4gt/+ mice and in mice with BLC-specific downregulation of Lmo4 using the elevated plus maze, open field, and light/dark box tests. Global or BLC-specific knockdown of Lmo4 did not significantly affect anxiety-like behavior. These results suggest a selective role for LMO4 in the BLC in modulating learned but not unlearned fear.

An estimated 2 million Americans use cocaine, resulting in large personal and societal costs. Discovery of the genetic factors that contribute to cocaine abuse is important for understanding this complex disease. Previously, mutations in the Drosophila LIM-only (dLmo) gene were identified because of their increased behavioral sensitivity to cocaine. Here we show that the mammalian homolog Lmo4, which is highly expressed in brain regions implicated in drug addiction, plays a similar role in cocaine-induced behaviors. Mice with a global reduction in Lmo4 levels show increased sensitivity to the locomotor stimulatory effects of cocaine upon chronic cocaine administration. This effect is reproduced with downregulation of Lmo4 in the nucleus accumbens by RNA interference. Thus, Lmo genes play conserved roles in regulating the behavioral effects of cocaine in invertebrate and mammalian models of drug addiction.

The second messenger cyclic AMP (cAMP) operates in discrete subcellular regions within which proteins that synthesize, break down or respond to the second messenger are precisely organized. A burgeoning knowledge of compartmentalized cAMP signaling is revealing how the local control of signaling enzyme activity impacts upon disease. The aim of this Cell Science at a Glance article and the accompanying poster is to highlight how misregulation of local cyclic AMP signaling can have pathophysiological consequences. We first introduce the core molecular machinery for cAMP signaling, which includes the cAMP-dependent protein kinase (PKA), and then consider the role of A-kinase anchoring proteins (AKAPs) in coordinating different cAMP-responsive proteins. The latter sections illustrate the emerging role of local cAMP signaling in four disease areas: cataracts, cancer, diabetes and cardiovascular diseases.

Pruning is important for sculpting neural circuits, as it removes excessive or inaccurate projections. Here we show that the removal of sensory neuron dendrites during pruning in Drosophila melanogaster is directed by local caspase activity. Suppressing caspase activity prevented dendrite removal, whereas a global activation of caspases within a neuron caused cell death. A new genetically encoded caspase probe revealed that caspase activity is confined to the degenerating dendrites of pruning neurons.

Time invariant description of synaptic connectivity in cortical circuits may be precluded by the ongoing growth and retraction of dendritic spines accompanied by the formation and elimination of synapses. On the other hand, the spatial arrangement of axonal and dendritic branches appears stable. This suggests that an invariant description of connectivity can be cast in terms of potential synapses, which are locations in the neuropil where an axon branch of one neuron is proximal to a dendritic branch of another neuron. In this paper, we attempt to reconstruct the potential connectivity in local cortical circuits of the cat primary visual cortex (V1). Based on multiple single-neuron reconstructions of axonal and dendritic arbors in 3 dimensions, we evaluate the expected number of potential synapses and the probability of potential connectivity among excitatory (pyramidal and spiny stellate) neurons and inhibitory basket cells. The results provide a quantitative description of structural organization of local cortical circuits. For excitatory neurons from different cortical layers, we compute local domains, which contain their potentially pre- and postsynaptic excitatory partners. These domains have columnar shapes with laminar specific radii and are roughly of the size of the ocular dominance column. Therefore, connections between most excitatory neurons in the ocular dominance column can be implemented by local synaptogenesis. Structural connectivity involving inhibitory basket cells is generally weaker than excitatory connectivity. Here, only nearby neurons are capable of establishing more than one potential synapse, implying that within the ocular dominance column these connections have more limited potential for circuit remodeling.

Accuracy of automated structural RNA alignment is improved by using models that consider not only primary sequence but also secondary structure information. However, current RNA structural alignment approaches tend to perform poorly on incomplete sequence fragments, such as single reads from metagenomic environmental surveys, because nucleotides that are expected to be base paired are missing.

We present a simple, yet effective, auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of Local Shape Descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors are designed to capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a large study comparing several existing methods across various specimen, imaging techniques, and resolutions, we find that auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinitybased segmentation methods to be on par with the current state of the art for neuron segmentation (Flood-Filling Networks, FFN), while being two orders of magnitudes more efficient—a critical requirement for the processing of future petabyte-sized datasets. Implementations of the new auxiliary learning task, network architectures, training, prediction, and evaluation code, as well as the datasets used in this study are publicly available as a benchmark for future method contributions.Competing Interest StatementThe authors have declared no competing interest.

We present an auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of local shape descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a study comparing several existing methods across various specimen, imaging techniques, and resolutions, auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinity-based segmentation methods to be on par with the current state of the art for neuron segmentation (flood-filling networks), while being two orders of magnitudes more efficient-a critical requirement for the processing of future petabyte-sized datasets.

Serotonin plays different roles across networks within the same sensory modality. Previously, we used whole-cell electrophysiology in Drosophila to show that serotonergic neurons innervating the first olfactory relay are inhibited by odorants (Zhang and Gaudry, 2016). Here we show that network-spanning serotonergic neurons segregate information about stimulus features, odor intensity and identity, by using opposing coding schemes in different olfactory neuropil. A pair of serotonergic neurons (the CSDns) innervate the antennal lobe and lateral horn, which are first and second order neuropils. CSDn processes in the antennal lobe are inhibited by odors in an identity independent manner. In the lateral horn, CSDn processes are excited in an odor identity dependent manner. Using functional imaging, modeling, and EM reconstruction, we demonstrate that antennal lobe derived inhibition arises from local GABAergic inputs and acts as a means of gain control on branch specific inputs that the CSDns receive within the lateral horn.