Receptor-regulated cellular signaling often is mediated by formation of transient, heterogeneous protein complexes of undefined structure. We used single and two-color photoactivated localization microscopy to study complexes downstream of the T cell antigen receptor (TCR) in single-molecule detail at the plasma membrane of intact T cells. The kinase ZAP-70 distributed completely with the TCRζ chain and both partially mixed with the adaptor LAT in activated cells, thus showing localized activation of LAT by TCR-coupled ZAP-70. In resting and activated cells, LAT primarily resided in nanoscale clusters as small as dimers whose formation depended on protein-protein and protein-lipid interactions. Surprisingly, the adaptor SLP-76 localized to the periphery of LAT clusters. This nanoscale structure depended on polymerized actin and its disruption affected TCR-dependent cell function. These results extend our understanding of the mechanism of T cell activation and the formation and organization of TCR-mediated signaling complexes, findings also relevant to other receptor systems.

Kv4/K channel-interacting protein (KChIP) potassium channels are a major class of rapidly inactivating K channels in brain and heart. Considering the importance of alternative splicing to the quantitative features of KChIP gating modulation, a previously uncharacterized splice form of KChIP1 was functionally characterized. The KChIP1b splice variant differs from the previously characterized KChIP1a splice form by the inclusion of a novel amino-terminal region that is encoded by an alternative exon that is conserved in mouse, rat, and human genes. The expression of KChIP1b mRNA was high in brain but undetectable in heart or liver by RT-PCR. In cerebellar tissue, KChIP1b and KChIP1a transcripts were expressed at nearly equal levels. Coexpression of KChIP1b or KChIP1a with Kv4.2 channels in oocytes slowed K current decay and destabilized open-inactivated channel gating. Like other KChIP subunits, KChIP1b increased Kv4.2 current amplitude and KChIP1b also shifted Kv4.2 conductance-voltage curves by -10 mV. The development of Kv4.2 channel inactivation accessed from closed gating states was faster with KChIP1b coexpression. Deletion of the novel amino-terminal region in KChIP1b selectively altered the subunit’s modulation of Kv4.2 closed inactivation gating. The role of the KChIP1b NH2-terminal region was further confirmed by direct comparison of the properties of the NH2-terminal deletion mutant and the KChIP1a subunit, which is encoded by a transcript that lacks the novel exon. The features of KChIP1b modulation of Kv4 channels are likely to be conserved in mammals and demonstrate a role for the KChIP1 NH2-terminal region in the regulation of closed inactivation gating.

Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. While many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called "minimal" enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster (1). However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor binding sites that drive patterning.

In teleost fish, the Mauthner (M) cell, a large reticulospinal neuron in the brainstem, triggers escape behavior. Spinal commissural inhibitory interneurons that are electrotonically excited by the M-axon have been identified, but the behavioral roles of these neurons have not yet been addressed. Here, we studied these neurons, named CoLo (commissural local), in larval zebrafish using an enhancer-trap line in which the entire population of CoLos was visualized by green fluorescent protein. CoLos were present at one cell per hemi-segment. Electrophysiological recordings showed that an M-spike evoked a spike in CoLos via electrotonic transmission and that CoLos made monosynaptic inhibitory connections onto contralateral primary motoneurons, consistent with the results in adult goldfish. We further showed that CoLos were active only during escapes. We examined the behavioral roles of CoLos by investigating escape behaviors in CoLo-ablated larvae. The results showed that the escape behaviors evoked by sound/vibration stimuli were often impaired with a reduced initial bend of the body, indicating that CoLos play important roles in initiating escapes. We obtained several lines of evidence that strongly suggested that the impaired escapes occurred during bilateral activation of the M-cells: in normal larvae, CoLo-mediated inhibitory circuits enable animals to perform escapes even in these occasions by silencing the output of the slightly delayed firing of the second M-cell. This study illustrates (1) a clear example of the behavioral role of a specialized class of interneurons and (2) the capacity of the spinal circuits to filter descending commands and thereby produce the appropriate behavior.

Individual neurons in prefrontal cortex – a key brain area involved in cognitive functions – are selective for variables such as space or time, as well as more cognitive aspects of tasks, such as learned categories. Many neurons exhibit mixed selectivity, that is, they show selectivity for multiple variables. A fundamental question is whether neurons are functionally specialized for particular variables and how selectivity for different variables intersects across the population. Here, we analyzed neural correlates of space and time in rats performing a navigational task with two behaviorally important categories – starts and goals. Using simultaneous recordings of many medial prefrontal cortex (mPFC) neurons during behavior, we found that population codes for elapsed time were invariant to different locations within categories, and subsets of neurons had functional preferences for time or space across categories. Thus, mPFC exhibits structured selectivity, which may facilitate complex behaviors by efficiently generating informative representations of multiple variables.

Small cell lung cancer (SCLC) is a highly aggressive type of lung cancer, characterized by rapid proliferation, early metastatic spread, frequent early relapse and a high mortality rate. Recent evidence has suggested that innervation has an important role in the development and progression of several types of cancer. Cancer-to-neuron synapses have been reported in gliomas, but whether peripheral tumours can form such structures is unknown. Here we show that SCLC cells can form functional synapses and receive synaptic transmission. Using in vivo insertional mutagenesis screening in conjunction with cross-species genomic and transcriptomic validation, we identified neuronal, synaptic and glutamatergic signalling gene sets in mouse and human SCLC. Further experiments revealed the ability of SCLC cells to form synaptic structures with neurons in vitro and in vivo. Electrophysiology and optogenetic experiments confirmed that cancer cells can receive NMDA receptor- and GABA receptor-mediated synaptic inputs. Fitting with a potential oncogenic role of neuron-SCLC interactions, we showed that SCLC cells derive a proliferation advantage when co-cultured with vagal sensory or cortical neurons. Moreover, inhibition of glutamate signalling had therapeutic efficacy in an autochthonous mouse model of SCLC. Therefore, following malignant transformation, SCLC cells seem to hijack synaptic signalling to promote tumour growth, thereby exposing a new route for therapeutic intervention.

Small unilamellar vesicles (SUVs) are indispensable model membranes, organelle mimics, and drug and vaccine carriers. However, the lack of robust techniques to functionalize or organize preformed SUVs limits their applications. Here we use DNA nanostructures to coat, cluster, and pattern sub-100-nm liposomes, generating distance-controlled vesicle networks, strings and dimers, among other configurations. The DNA coating also enables attachment of proteins to liposomes, and temporal control of membrane fusion driven by SNARE protein complexes. Such a convenient and versatile method of engineering premade vesicles both structurally and functionally is highly relevant to bottom-up biology and targeted delivery.

Processing bodies (p-bodies) are a prototypical phase-separated RNA-containing granule. Their abundance is highly dynamic and has been linked to translation. Yet, the molecular mechanisms responsible for coordinate control of the two processes are unclear. Here, we uncover key roles for eEF2 kinase (eEF2K) in the control of ribosome availability and p-body abundance. eEF2K acts on a sole known substrate, eEF2, to inhibit translation. We find that the eEF2K agonist nelfinavir abolishes p-bodies in sensory neurons and impairs translation. To probe the latter, we used cryo-electron microscopy. Nelfinavir stabilizes vacant 80S ribosomes. They contain SERBP1 in place of mRNA and eEF2 in the acceptor site. Phosphorylated eEF2 associates with inactive ribosomes that resist splitting in vitro. Collectively, the data suggest that eEF2K defines a population of inactive ribosomes resistant to recycling and protected from degradation. Thus, eEF2K activity is central to both p-body abundance and ribosome availability in sensory neurons.

Human memory appears to be fragile and unpredictable. Free recall of random lists of words is a standard paradigm used to probe episodic memory. We proposed an associative search process that can be reduced to a deterministic walk on random graphs defined by the structure of memory representations. The corresponding graph model can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled (R) out of M items in memory: R=sqrt[3πM/2]. This prediction was verified with a specially designed experimental protocol combining large-scale crowd-sourced free recall and recognition experiments with randomly assembled lists of words or common facts. Our results show that human memory can be described by universal laws derived from first principles.