Close appositions between the membrane of the endoplasmic reticulum (ER) and other intracellular membranes have important functions in cell physiology. These include lipid homeostasis, regulation of Ca(2+) dynamics, and control of organelle biogenesis and dynamics. Although these membrane contacts have previously been observed in neurons, their distribution and abundance have not been systematically analyzed. Here, we have used focused ion beam-scanning electron microscopy to generate 3D reconstructions of intracellular organelles and their membrane appositions involving the ER (distance ≤30 nm) in different neuronal compartments. ER-plasma membrane (PM) contacts were particularly abundant in cell bodies, with large, flat ER cisternae apposed to the PM, sometimes with a notably narrow lumen (thin ER). Smaller ER-PM contacts occurred throughout dendrites, axons, and in axon terminals. ER contacts with mitochondria were abundant in all compartments, with the ER often forming a network that embraced mitochondria. Small focal contacts were also observed with tubulovesicular structures, likely to be endosomes, and with sparse multivesicular bodies and lysosomes found in our reconstructions. Our study provides an anatomical reference for interpreting information about interorganelle communication in neurons emerging from functional and biochemical studies.

The representation of contextual information peripheral to a salient stimulus is central to an animal's ability to correctly interpret and flexibly respond to that stimulus. While the computations and circuits underlying the context-dependent modulation of stimulus-response pairings have typically been studied in vertebrates, the genetic tractability, numeric simplification, and well-characterized connectivity patterns of the Drosophila melanogaster brain have facilitated circuit-level insights into contextual processing. Recent studies in flies reveal the neuronal mechanisms that create flexible context-dependent behavioral responses to sensory events in conditions of predation threat, feeding regulation, and social interaction.

The N6-methyladenosine (mA) modification is the most prevalent post-transcriptional mRNA modification, regulating mRNA decay and splicing. It plays a major role during normal development, differentiation, and disease progression. The modification is regulated by a set of writer, eraser, and reader proteins. The YTH domain family of proteins consists of three homologous mA-binding proteins, Ythdf1, Ythdf2, and Ythdf3, which were suggested to have different cellular functions. However, their sequence similarity and their tendency to bind the same targets suggest that they may have overlapping roles. We systematically knocked out (KO) the Mettl3 writer, each of the Ythdf readers, and the three readers together (triple-KO). We then estimated the effect in vivo in mouse gametogenesis, postnatal viability, and in vitro in mouse embryonic stem cells (mESCs). In gametogenesis, severity is increased as the deletion occurs earlier in the process, and Ythdf2 has a dominant role that cannot be compensated by Ythdf1 or Ythdf3, due to differences in readers' expression pattern across different cell types, both in quantity and in spatial location. Knocking out the three readers together and systematically testing viable offspring genotypes revealed a redundancy in the readers' role during early development that is gene dosage-dependent. Finally, in mESCs there is compensation between the three Ythdf reader proteins, since the resistance to differentiate and the significant effect on mRNA decay occur only in the triple-KO cells and not in the single KOs. Thus, we suggest a new model for the Ythdf readers function, in which there is profound dosage-dependent redundancy when all three readers are equivalently coexpressed in the same cell types.

The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations.

Continuous attractor networks are used to model the storage and representation of analog quantities, such as position of a visual stimulus. The storage of multiple continuous attractors in the same network has previously been studied in the context of self-position coding. Several uncorrelated maps of environments are stored in the synaptic connections, and a position in a given environment is represented by a localized pattern of neural activity in the corresponding map, driven by a spatially tuned input. Here we analyze networks storing a pair of correlated maps, or a morph sequence between two uncorrelated maps. We find a novel state in which the network activity is simultaneously localized in both maps. In this state, a fixed cue presented to the network does not determine uniquely the location of the bump, i.e. the response is unreliable, with neurons not always responding when their preferred input is present. When the tuned input varies smoothly in time, the neuronal responses become reliable and selective for the environment: the subset of neurons responsive to a moving input in one map changes almost completely in the other map. This form of remapping is a non-trivial transformation between the tuned input to the network and the resulting tuning curves of the neurons. The new state of the network could be related to the formation of direction selectivity in one-dimensional environments and hippocampal remapping. The applicability of the model is not confined to self-position representations; we show an instance of the network solving a simple delayed discrimination task.

The brain is an organ of immense complexity. Next-generation RNA sequencing (RNA-seq) is becoming increasingly popular in the deconstruction of this complexity into distinct classes of 'cell types'. Notably, in addition to revealing the organization of this distinct cell-type landscape, the technology has also begun to illustrate that continuous variation can be found within narrowly defined cell types. Here we summarize the evidence for graded transcriptomic heterogeneity being present, widespread, and functionally relevant in the nervous system. We explain how these graded differences can map onto higher-order organizational features and how they may reframe existing interpretations of higher-order heterogeneity. Ultimately, a multimodal approach incorporating continuously variable cell types will facilitate an accurate reductionist interpretation of the nervous system.

In vivo imaging at high spatiotemporal resolution is key to the understanding of complex biological systems. We integrated an optical phase-locked ultrasound lens into a two-photon fluorescence microscope and achieved microsecond-scale axial scanning, thus enabling volumetric imaging at tens of hertz. We applied this system to multicolor volumetric imaging of processes sensitive to motion artifacts, including calcium dynamics in behaving mouse brain and transient morphology changes and trafficking of immune cells.

Mechano-transduction is an emerging but still poorly understood component of T cell activation. Here we investigated the ligand-dependent contribution made by contractile actomyosin arcs populating the peripheral supramolecular activation cluster (pSMAC) region of the immunological synapse (IS) to T cell receptor (TCR) microcluster transport and proximal signaling in primary mouse T cells. Using super resolution microscopy, OT1-CD8+ mouse T cells, and two ovalbumin (OVA) peptides with different affinities for the TCR, we show that the generation of organized actomyosin arcs depends on ligand potency and the ability of myosin 2 to contract actin filaments. While weak ligands induce disorganized actomyosin arcs, strong ligands result in organized actomyosin arcs that correlate well with tension-sensitive CasL phosphorylation and the accumulation of ligands at the IS center. Blocking myosin 2 contractility greatly reduces the difference in the extent of Src and LAT phosphorylation observed between the strong and the weak ligand, arguing that myosin 2-dependent force generation within actin arcs contributes to ligand discrimination. Together, our data are consistent with the idea that actomyosin arcs in the pSMAC region of the IS promote a mechano-chemical feedback mechanism that amplifies the accumulation of critical signaling molecules at the IS.

Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes.

The Drosophila insulin receptor (dInR) regulates cell growth and proliferation through the dPI3K/dAkt pathway, which is conserved in metazoan organisms. Here we report the identification and functional characterization of the Drosophila forkhead-related transcription factor dFOXO, a key component of the insulin signaling cascade. dFOXO is phosphorylated by dAkt upon insulin treatment, leading to cytoplasmic retention and inhibition of its transcriptional activity. Mutant dFOXO lacking dAkt phosphorylation sites no longer responds to insulin inhibition, remains in the nucleus, and is constitutively active. dFOXO activation in S2 cells induces growth arrest and activates two key players of the dInR/dPI3K/dAkt pathway: the translational regulator d4EBP and the dInR itself. Induction of d4EBP likely leads to growth inhibition by dFOXO, whereas activation of dInR provides a novel transcriptionally induced feedback control mechanism. Targeted expression of dFOXO in fly tissues regulates organ size by specifying cell number with no effect on cell size. Our results establish dFOXO as a key transcriptional regulator of the insulin pathway that modulates growth and proliferation.