Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We therefore tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including associations measured from spatiotemporal co-occurrences, to immune phenotypes. We found extensive variation in individual and social behavior among and within mouse strains upon rewilding. In addition, we found that the more associated two individuals were, the more similar their immune phenotypes were. Spatiotemporal association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or shared infection status. These results highlight the importance of shared spatiotemporal activity patterns and/or social networks for immune phenotype and suggest potential immunological correlates of social life.

Focal adhesions (FAs) connect inner workings of the cell to the extracellular matrix to control cell adhesion, migration, and mechanosensing1,2. Previous studies demonstrated that FAs contain three vertical layers, which connect extracellular matrix to the cytoskeleton3,4,5. However, cellular processes rely on precisely-regulated FA turnover, but the molecular machineries that control FA assembly and disassembly have remained elusive. By using super-resolution iPALM microscopy, we identified two unprecedented nanoscale layers within FAs, specified by actin filaments bound to tropomyosin isoforms Tpm1.6 and Tpm3.2. The Tpm1.6-actin filaments beneath the previously identified ‘actin-regulatory layer’ are critical for adhesion maturation and controlled cell motility, whereas the Tpm3.2-actin filament layer towards the bottom of FA facilitates adhesion disassembly. Mechanistically, Tpm3.2 stabilizes KANK-family proteins at adhesions, and hence targets microtubule plus-ends to FAs to catalyse their disassembly. Loss of Tpm3.2 leads to disorganized microtubule network, abnormally stable FAs, and defects in tail retraction during cell migration. Thus, FAs are composed of at least three distinct actin filament layers, each having specific roles in coupling of adhesion to the cytoskeleton, or in controlling adhesion dynamics. In a broader context, these findings demonstrate how distinct actin filament populations can co-exist and perform specific functions within a defined cellular compartment.

There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward 1,2 and reward-predicting cues 1,3,4, but also to other variables such as distance to reward 5, movements 6–11 and behavioral choices 12–15. Based on these findings, a major open question is how the responses to these diverse variables are organized across the population of DA neurons. In other words, do individual DA neurons multiplex multiple variables, or are subsets of neurons specialized in encoding specific behavioral variables? The reason that this fundamental question has been difficult to resolve is that recordings from large populations of individual DA neurons have not been performed in a behavioral task with sufficient complexity to examine these diverse variables simultaneously. To address this gap, we used 2-photon calcium imaging through an implanted lens to record activity of >300 midbrain DA neurons in the VTA during a complex decision-making task. As mice navigated in a virtual reality (VR) environment, DA neurons encoded an array of sensory, motor, and cognitive variables. These responses were functionally clustered, such that subpopulations of neurons transmitted information about a subset of behavioral variables, in addition to encoding reward. These functional clusters were spatially organized, such that neighboring neurons were more likely to be part of the same cluster. Taken together with the topography between DA neurons and their projections, this specialization and anatomical organization may aid downstream circuits in correctly interpreting the wide range of signals transmitted by DA neurons.

Because of their strategic position between the granule cell and pyramidal cell layers, neurons of the hilar region of the hippocampal formation are likely to play an important role in the information processing between the entorhinal cortex and the hippocampus proper. Here we present an electrophysiological characterization of anatomically identified neurons in the fascia dentata as studied using patch-pipette recordings and subsequent biocytin-staining of neurons in slices. The resting potential, input resistance (RN), membrane time constant (taum), "sag" in hyperpolarizing responses, maximum firing rate during a 1-s current pulse, spike width, and fast and slow afterhyperpolarizations (AHPs) were determined for several different types of hilar neurons. Basket cells had a dense axonal plexus almost exclusively within the granule cell layer and were distinguishable by their low RN, short taum, lack of sag, and rapid firing rates. Dentate granule cells also lacked sag and were identifiable by their higher RN, longer taum, and lower firing rates than basket cells. Mossy cells had extensive axon collaterals within the hilus and a few long-range collaterals to the inner molecular layer and CA3c and were characterized physiologically by small fast and slow AHPs. Spiny and aspiny hilar interneurons projected primarily either to the inner or outer segment of the molecular layer and had a dense intrahilar axonal plexus, terminating onto somata within the hilus and CA3c. Physiologically, spiny hilar interneurons generally had higher RN values than mossy cells and a smaller slow AHP than aspiny interneurons. The specialized physiological properties of different classes of hilar neurons are likely to be important determinants of their functional operation within the hippocampal circuitry.

Drosophila Dscam isoforms are derived from two alternative transmembrane/juxtamembrane domains (TMs) in addition to thousands of ectodomain variants. Using a microRNA-based RNA interference technology, we selectively knocked down different subsets of Dscams containing either the exon 17.1- or exon 17.2-encoding TM. Eliminating Dscam[TM1] reduced Dscam expression but minimally affected postembryonic axonal morphogenesis. In contrast, depleting Dscam[TM2] blocked axon arborization. Further removal of Dscam[TM1] enhanced the loss-of-Dscam[TM2] axonal phenotypes. However, Dscam[TM1] primarily regulates dendritic development, as evidenced by the observations that removing Dscam[TM1] alone impeded elaboration of dendrites and that transgenic Dscam[TM1], but not Dscam[TM2], effectively rescued Dscam mutant dendritic phenotypes in mosaic organisms. These distinct Dscam functions can be attributed to the juxtamembrane regions of TMs that govern dendritic versus axonal targeting of Dscam as well. Together, we suggest that specific Drosophila Dscam juxtamembrane variants control dendritic elaboration and axonal arborization.

ZBP1-modulated localization of β-actin mRNA enables a cell to establish polarity and structural asymmetry. Although the mechanism of β-actin mRNA localization has been well established, the underlying mechanism of how a specific molecular motor contributes to the transport of the ZBP1 (also known as IGF2BP1) complex in non-neuronal cells remains elusive. In this study, we report the isolation and identification of KIF11, a microtubule motor, which physically interacts with ZBP1 and is a component of β-actin messenger ribonucleoprotein particles (mRNPs). We show that KIF11 colocalizes with the β-actin mRNA, and the ability of KIF11 to transport β-actin mRNA is dependent on ZBP1. We characterize the corresponding regions of ZBP1 and KIF11 that mediate the interaction of the two proteins in vitro and in vivo. Disruption of the in vivo interaction of KIF11 with ZBP1 delocalizes β-actin mRNA and affects cell migration. Our study reveals a molecular mechanism by which a particular microtubule motor mediates the transport of an mRNP through direct interaction with an mRNA-binding protein.

The most fundamental choice an animal has to make when it detects a threat is whether to freeze, reducing its chances of being noticed, or to flee to safety. Here we show that Drosophila melanogaster exposed to looming stimuli in a confined arena either freeze or flee. The probability of freezing versus fleeing is modulated by the fly's walking speed at the time of threat, demonstrating that freeze/flee decisions depend on behavioral state. We describe a pair of descending neurons crucially implicated in freezing. Genetic silencing of DNp09 descending neurons disrupts freezing yet does not prevent fleeing. Optogenetic activation of both DNp09 neurons induces running and freezing in a state-dependent manner. Our findings establish walking speed as a key factor in defensive response choices and reveal a pair of descending neurons as a critical component in the circuitry mediating selection and execution of freezing or fleeing behaviors.

The basic psychophysical principle of speed-accuracy tradeoff (SAT) has been used to understand key aspects of neuronal information processing in vision and audition, but the principle of SAT is still debated in olfaction. In this study we present the direct observation of SAT in olfaction. We developed a behavioral paradigm for mice in which both the duration of odorant sampling and the difficulty of the odor discrimination task were controlled by the experimenter. We observed that the accuracy of odor discrimination increases with the duration of imposed odorant sampling, and that the rate of this increase is slower for harder tasks. We also present a unifying picture of two previous, seemingly disparate experiments on timing of odorant sampling in odor discrimination tasks. The presence of SAT in olfaction provides strong evidence for temporal integration in olfaction and puts a constraint on models of olfactory processing.

This paper deals with the problem of extracting the activity of individual neurons from multi-electrode recordings. Important aspects of this work are: 1) the sorting is done in two stages - a statistical model of the spikes from different cells is built and only then are occurrences of these spikes in the data detected by scanning through the original data, 2) the spike sorting is done in the frequency domain, 3) strict statistical tests are applied to determine if and how a spike should be classiffed, 4) the statistical model for detecting overlaping spike events is proposed, 5) slow dynamics of spike shapes are tracked during long experiments. Results from the application of these techniques to data collected from the escape response system of the American cockroach, Periplaneta americana, are presented.