Maintaining proper tension is critical for the organization and function of the plasma membrane. To study the mechanisms by which yeast restores normal plasma membrane tension, we used a microfluidics device to expose yeast to hyperosmotic conditions, which reduced cell volume and caused a ∼20% drop in cell surface area. The resulting low tension plasma membrane exhibited large clusters of negatively-charged glycerophospholipids together with nutrient transporters, suggesting phase segregation of the membrane. We found that endocytosis was blocked by the phase segregation and thus was not involved in removing excess membrane. In contrast, rapid recovery of plasma membrane tension was dependent on 1) eisosome morphology changes that were able to absorb most of the excess surface area and 2) lipid transport from the plasma membrane to the endoplasmic reticulum, where lipids were shunted into newly formed lipid droplets.

Systemic lipid homeostasis requires hepatic autophagy, a major cellular program for intracellular fat recycling. Here, we find melanocortin 3 receptor (MC3R) regulates hepatic autophagy in addition to its previously established CNS role in systemic energy partitioning and puberty. Mice with Mc3r deficiency develop obesity with hepatic triglyceride accumulation and disrupted hepatocellular autophagosome turnover. Mice with partially inactive human MC3R due to obesogenic variants demonstrate similar hepatic autophagic dysfunction. In vitro and in vivo activation of hepatic MC3R upregulates autophagy through LC3II activation, TFEB cytoplasmic-to-nuclear translocation, and subsequent downstream gene activation. MC3R-deficient hepatocytes had blunted autophagosome-lysosome docking and lipid droplet clearance. Finally, the liver-specific rescue of Mc3r was sufficient to restore hepatocellular autophagy, improve hepatocyte mitochondrial function and systemic energy expenditures, reduce adipose tissue lipid accumulation, and partially restore body weight in both male and female mice. We thus report a role for MC3R in regulating hepatic autophagy and systemic adiposity.

Inside the cell, proteins essential for signaling, morphogenesis, and migration navigate the complex, ever-changing environment through vesicular trafficking or microtubule-driven mechanisms. However, the mechanisms by which soluble proteins reach their target destinations remain unknown. Here, we show that soluble proteins are directed toward the cell’s advancing edge by advection, diffusion facilitated by fluid flow. The advective transport mechanism operates in a compartment at the front of the cell isolated from the rest of the cytoplasm by a semi-permeable actin-myosin barrier that restricts protein mixing between the compartment and the rest of the cytoplasm. Contraction at the barrier generates a molecularly non-specific fluid flow that propels treadmilling actin monomer, actin-binding, adhesion, and even inert proteins forward. Changes in the dynamic local curvature of the barrier direct the flow, targeting proteins toward the protruding regions of the leading edge, effectively coordinating the distribution of proteins needed for local changes in cellular dynamics. Outside the compartment, diffusion is the primary mode of soluble protein transport. Our findings suggest that cells possess previously unrecognized organizational strategies for managing soluble protein concentration and distributing them efficiently for activities such as protrusion and adhesion.

Motor control in mammals is traditionally viewed as a hierarchy of descending spinal-targeting pathways, with frontal cortex at the top 1–3. Many redundant muscle patterns can solve a given task, and this high dimensionality allows flexibility but poses a problem for efficient learning 4. Although a feasible solution invokes subcortical innate motor patterns, or primitives, to reduce the dimensionality of the control problem, how cortex learns to utilize such primitives remains an open question 5–7. To address this, we studied cortical and subcortical interactions as head-fixed mice learned contextual control of innate hindlimb extension behavior. Naïve mice performed reactive extensions to turn off a cold air stimulus within seconds and, using predictive cues, learned to avoid the stimulus altogether in tens of trials. Optogenetic inhibition of large areas of rostral cortex completely prevented avoidance behavior, but did not impair hindlimb extensions in reaction to the cold air stimulus. Remarkably, mice covertly learned to avoid the cold stimulus even without any prior experience of successful, cortically-mediated avoidance. These findings support a dynamic, heterarchical model in which the dominant locus of control can change, on the order of seconds, between cortical and subcortical brain areas. We propose that cortex can leverage periods when subcortex predominates as demonstrations, to learn parameterized control of innate behavioral primitives.

Symbolic models play a key role in cognitive science, expressing computationally precise hypotheses about how the brain implements a cognitive process. Identifying an appropriate model typically requires a great deal of effort and ingenuity on the part of a human scientist. Here, we adapt FunSearch Romera-Paredes et al. (2024), a recently developed tool that uses Large Language Models (LLMs) in an evolutionary algorithm, to automatically discover symbolic cognitive models that accurately capture human and animal behavior. We consider datasets from three species performing a classic reward-learning task that has been the focus of substantial modeling effort, and find that the discovered programs outperform state-of-the-art cognitive models for each. The discovered programs can readily be interpreted as hypotheses about human and animal cognition, instantiating interpretable symbolic learning and decision-making algorithms. Broadly, these results demonstrate the viability of using LLM-powered program synthesis to propose novel scientific hypotheses regarding mechanisms of human and animal cognition.

The aging process is universal, and it is characterized by a progressive deterioration and decrease in physiological function leading to decline on the organismal level. Nevertheless, a number of genetic and non-genetic interventions have been described, which successfully extend healthspan and lifespan in different species. Furthermore, a number of clinical trials have been evaluating the feasibility of different interventions to promote human health. The goal of the annual Biological Sciences Section of the Gerontological Society of America meeting was to share current knowledge of different topics in aging research and provide a vision of the future of aging research. The meeting gathered international experts in diverse areas of aging research including basic biology, demography, and clinical and translational studies. Specific topics included metabolism, inflammaging, epigenetic clocks, frailty, senescence, neuroscience, stem cells, reproductive aging, inter-organelle crosstalk, comparative transcriptomics of longevity, circadian clock, metabolomics, and biodemography.

Generalist methods for cellular segmentation have good out-of-the-box performance on a variety of image types; however, existing methods struggle for images that are degraded by noise, blurring or undersampling, all of which are common in microscopy. We focused the development of Cellpose3 on addressing these cases and here we demonstrate substantial out-of-the-box gains in segmentation and image quality for noisy, blurry and undersampled images. Unlike previous approaches that train models to restore pixel values, we trained Cellpose3 to output images that are well segmented by a generalist segmentation model, while maintaining perceptual similarity to the target images. Furthermore, we trained the restoration models on a large, varied collection of datasets, thus ensuring good generalization to user images. We provide these tools as 'one-click' buttons inside the graphical interface of Cellpose as well as in the Cellpose API.

All multicellular systems produce and dynamically regulate extracellular matrices (ECMs) that play essential roles in both biochemical and mechanical signaling. Though the spatial arrangement of these extracellular assemblies is critical to their biological functions, visualization of ECM structure is challenging, in part because the biomolecules that compose the ECM are difficult to fluorescently label individually and collectively. Here, we present a cell-impermeable small-molecule fluorophore, termed Rhobo6, that turns on and red shifts upon reversible binding to glycans. Given that most ECM components are densely glycosylated, the dye enables wash-free visualization of ECM, in systems ranging from in vitro substrates to in vivo mouse mammary tumors. Relative to existing techniques, Rhobo6 provides a broad substrate profile, superior tissue penetration, non-perturbative labeling, and negligible photobleaching. This work establishes a straightforward method for imaging the distribution of ECM in live tissues and organisms, lowering barriers for investigation of extracellular biology.

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 1 cm shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

Dendrites on neurons support nonlinear electrical excitations, but the computational significance of these events is not well understood. We developed molecular, optical, and analytical tools to map sub-millisecond voltage dynamics throughout the dendritic trees of CA1 pyramidal neurons under diverse optogenetic and synaptic stimulus patterns, in acute brain slices. We observed history-dependent spike back-propagation in distal dendrites, driven by locally generated Na+ spikes (dSpikes). Dendritic depolarization created a transient window for dSpike propagation, opened by A-type KV channel inactivation, and closed by slow NaV inactivation. Collisions of dSpikes with synaptic inputs triggered calcium channel and N-methyl-D-aspartate receptor (NMDAR)-dependent plateau potentials, with accompanying complex spikes at the soma. This hierarchical ion channel network acts as a spike-rate accelerometer, providing an intuitive picture of how dendritic excitations shape associative plasticity rules.