Neurons integrate synaptic inputs within their dendrites and produce spiking outputs, which then propagate down the axon and back into the dendrites where they contribute to plasticity. Mapping the voltage dynamics in dendritic arbors of live animals is crucial for understanding neuronal computation and plasticity rules. Here we combine patterned channelrhodopsin activation with dual-plane structured illumination voltage imaging, for simultaneous perturbation and monitoring of dendritic and somatic voltage in Layer 2/3 pyramidal neurons in anesthetized and awake mice. We examined the integration of synaptic inputs and compared the dynamics of optogenetically evoked, spontaneous, and sensory-evoked back-propagating action potentials (bAPs). Our measurements revealed a broadly shared membrane voltage throughout the dendritic arbor, and few signatures of electrical compartmentalization among synaptic inputs. However, we observed spike rate acceleration-dependent propagation of bAPs into distal dendrites. We propose that this dendritic filtering of bAPs may play a critical role in activity-dependent plasticity.

Forces controlling tissue morphogenesis are attributed to cellular-driven activities, and any role for extracellular matrix (ECM) is assumed to be passive. However, all polymer networks, including ECM, can develop autonomous stresses during their assembly. Here, we examine the morphogenetic function of an ECM before reaching homeostatic equilibrium by analyzing de novo ECM assembly during Drosophila ventral nerve cord (VNC) condensation. Asymmetric VNC shortening and a rapid decrease in surface area correlate with the exponential assembly of collagen IV (Col4) surrounding the tissue. Concomitantly, a transient developmentally induced Col4 gradient leads to coherent long-range flow of ECM, which equilibrates the Col4 network. Finite element analysis and perturbation of Col4 network formation through the generation of dominant Col4 mutations that affect assembly reveal that VNC morphodynamics is partially driven by a sudden increase in ECM-driven surface tension. These data suggest that ECM assembly stress and associated network instabilities can actively participate in tissue morphogenesis.

NDP52 is an autophagy receptor involved in the recognition and degradation of invading pathogens and damaged organelles. Although NDP52 was first identified in the nucleus and is expressed throughout the cell, to date, there is no clear nuclear functions for NDP52. Here, we use a multidisciplinary approach to characterise the biochemical properties and nuclear roles of NDP52. We find that NDP52 clusters with RNA Polymerase II (RNAPII) at transcription initiation sites and that its overexpression promotes the formation of additional transcriptional clusters. We also show that depletion of NDP52 impacts overall gene expression levels in two model mammalian cells, and that transcription inhibition affects the spatial organisation and molecular dynamics of NDP52 in the nucleus. This directly links NDP52 to a role in RNAPII-dependent transcription. Furthermore, we also show that NDP52 binds specifically and with high affinity to double-stranded DNA (dsDNA) and that this interaction leads to changes in DNA structure in vitro. This, together with our proteomics data indicating enrichment for interactions with nucleosome remodelling proteins and DNA structure regulators, suggests a possible function for NDP52 in chromatin regulation. Overall, here we uncover nuclear roles for NDP52 in gene expression and DNA structure regulation.

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

Retinal Müller glia function as injury-induced stem-like cells in zebrafish but not mammals. However, insights gleaned from zebrafish have been applied to stimulate nascent regenerative responses in the mammalian retina. For instance, microglia/macrophages regulate Müller glia stem cell activity in the chick, zebrafish, and mouse. We previously showed that post-injury immunosuppression by the glucocorticoid dexamethasone accelerated retinal regeneration kinetics in zebrafish. Similarly, microglia ablation enhances regenerative outcomes in the mouse retina. Targeted immunomodulation of microglia reactivity may therefore enhance the regenerative potential of Müller glia for therapeutic purposes. Here, we investigated potential mechanisms by which post-injury dexamethasone accelerates retinal regeneration kinetics, and the effects of dendrimer-based targeting of dexamethasone to reactive microglia. Intravital time-lapse imaging revealed that post-injury dexamethasone inhibited microglia reactivity. The dendrimer-conjugated formulation: (1) decreased dexamethasone-associated systemic toxicity, (2) targeted dexamethasone to reactive microglia, and (3) improved the regeneration enhancing effects of immunosuppression by increasing stem/progenitor proliferation rates. Lastly, we show that the gene rnf2 is required for the enhanced regeneration effect of D-Dex. These data support the use of dendrimer-based targeting of reactive immune cells to reduce toxicity and enhance the regeneration promoting effects of immunosuppressants in the retina.

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

Mfsd2a is the transporter for docosahexaenoic acid (DHA), an omega-3 fatty acid, across the blood brain barrier (BBB). Defects in Mfsd2a are linked to ailments from behavioral and motor dysfunctions to microcephaly. Mfsd2a transports long-chain unsaturated fatty-acids, including DHA and α-linolenic acid (ALA), that are attached to the zwitterionic lysophosphatidylcholine (LPC) headgroup. Even with the recently determined structures of Mfsd2a, the molecular details of how this transporter performs the energetically unfavorable task of translocating and flipping lysolipids across the lipid bilayer remains unclear. Here, we report five single-particle cryo-EM structures of Danio rerio Mfsd2a (drMfsd2a): in the inward-open conformation in the ligand-free state and displaying lipid-like densities modeled as ALA-LPC at four distinct positions. These Mfsd2a snapshots detail the flipping mechanism for lipid-LPC from outer to inner membrane leaflet and release for membrane integration on the cytoplasmic side. These results also map Mfsd2a mutants that disrupt lipid-LPC transport and are associated with disease.

The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.

Animals can learn general task structures and use them to solve new problems with novel sensory specifics. This capacity of ‘learning to learn’, or meta-learning, is difficult to achieve in artificial systems, and the mechanisms by which it is achieved in animals are unknown. As a step toward enabling mechanistic studies, we developed a behavioral paradigm that demonstrates meta-learning in head-fixed mice. We trained mice to perform a two-alternative forced-choice task in virtual reality (VR), and successively changed the visual cues that signaled reward location. Mice showed increased learning speed in both cue generalization and serial reversal tasks. During reversal learning, behavior exhibited sharp transitions, with the transition occurring earlier in each successive reversal. Analysis of motor patterns revealed that animals utilized similar motor programs to execute the same actions in response to different cues but modified the motor programs during reversal learning. Our study demonstrates that mice can perform meta-learning tasks in VR, thus opening up opportunities for future mechanistic studies.

Primary aldosteronism (PA) is the most frequent form of secondary hypertension. Over the past two decades, major advances have been made in our understanding of the disease with the identification of germline or somatic mutations in ion channels and pumps. These mutations enhance calcium signaling, the main trigger of aldosterone biosynthesis.