Small GTPases are generally viewed as organizers of organelle identity, with different families recruited to specific membranes by compartment-selective targeting mechanisms. Here, we identify a membrane state that reverses this relationship. Excessive peptide S-palmitoylation at Golgi generates multilamellar, filipin-poor whorls that recruit ARF, Rab, and Rho family GTPases normally associated with distinct cellular compartments. The whorls simultaneously excluded Golgi transmembrane residents, coat proteins, ER proteins, a GPI-anchored protein, and other palmitoylated proteins, demonstrating that they were selective membrane compartments rather than nonspecific protein aggregates. Preventing myristoylation of ARF6 or geranylgeranylation of Rab11a strongly reduced recruitment, whereas prenylation alone was insufficient, indicating recognition of a composite membrane-targeting code. Lowering cellular cholesterol promoted whorl formation, whereas cholesterol supplementation suppressed it. Chemically distinct lipid perturbations generated GTPase-positive Golgi whorls, suggesting convergence on a shared membrane-remodeling state. As whorls accumulated, endocytic recycling and anterograde trafficking declined, survival signaling decreased, and viability became poorly reversible. These findings show that lipid imbalance can redirect small GTPases across normal organelle boundaries, converting Golgi-derived membranes into selective sinks for trafficking regulators.

Survival during infection depends on both pathogen clearance and the ability to tolerate infection-induced physiological changes. Metabolic adaptations are a central component of this tolerance, but the mechanisms underlying these responses remain incompletely defined. Here, we identify white adipose tissue (WAT) lipolysis as a central regulator of metabolic tolerance to infection. In patients with sepsis, higher circulating non-esterified fatty acid (NEFA) levels were associated with reduced mortality. In mouse models of polymicrobial sepsis, infection induced robust adipose lipolysis and increased circulating NEFAs. Genetic ablation of adipose triglyceride lipase (ATGL) in adipose tissue impaired lipolysis, leading to hypothermia, bradycardia, and increased mortality without altering immune cell populations or pathogen burden, consistent with a defect in tolerance rather than resistance. Mechanistically, lipolysis-derived NEFAs, but not glycerol, were required for protection, as restoring circulating NEFAs rescued autonomic stability and survival in adipose tissue ATGL-deficient mice. Infection-induced lipolysis was redundantly regulated and did not depend on any single upstream signaling pathway. Both pharmacologic activation of lipolysis using a β3-adrenergic agonist and exogenous fatty acid supplementation increased circulating NEFAs, improved survival, and promoted tolerance in mice. Consistent with these findings, analysis of real-world electronic health record data demonstrated that septic patients receiving FDA-approved β3-adrenergic agonists had reduced mortality or hospice discharge in a propensity-matched cohort. Together, these results identify WAT lipolysis and circulating fatty acids as key mediators of tolerance to infection and support a therapeutic strategy based on repurposing clinically available β3-adrenergic agonists to improve outcomes in sepsis.

The measurement of ion concentrations and fluxes inside living cells is key to understanding cellular physiology. Fluorescent indicators that can infiltrate and provide intel on the cellular environment are critical tools for biological research. Developing these molecular informants began with the seminal work of Racker and colleagues ( (1979) 18, 2210), who demonstrated the passive loading of fluorescein in living cells to measure changes in intracellular pH. This work continues, employing a mix of old and new tradecraft to create innovative agents for monitoring ions inside living systems.

The cell cycle is tightly regulated by checkpoint mechanisms that ensure faithful duplication and segregation of the genome. Here, we induced cell-cell fusion between mitotic and interphase cells to study how nuclei from different cell cycle stages behave in a shared cytoplasm. We found that mitosis is a dominant cell cycle state: the mitotic cytoplasm can drive interphase nuclei into mitosis, whereas, in high ratios of interphase versus mitotic nuclei, fusion forced mitotic nuclei to exit mitosis. Both outcomes represent checkpoint override events with impactful consequences. Interphase nuclei forced into mitosis form aberrant mitotic spindles, show partially condensed DNA and ultimately undergo mitotic catastrophe. Conversely, forced mitotic exit resulted in reformation of nuclear envelope membranes around condensed chromosomes, forming nuclei with a defective nuclear import machinery. Altogether, cell-cell fusion revealed the consequences of checkpoint override, forcing nuclei through untimely cell cycle transitions, and highlight how cell-cell fusion experiments can be a powerful system to study how competing cytoplasmic states are integrated in a shared cytoplasm, such as in muscle, placenta formation and in cancer.

Stoichiometric labeling of endogenous synaptic proteins for high-contrast live-cell imaging in brain tissue remains challenging. Here, we describe a conditional mouse genetic strategy termed endogenous labeling via exon duplication (ENABLED), which can be used to fluorescently label endogenous proteins with near ideal properties in all neurons, a sparse subset of neurons, or specific neuronal subtypes. We used this method to label the postsynaptic density protein PSD-95 with mVenus without overexpression side effects. We demonstrated that mVenus-tagged PSD-95 is functionally equivalent to wild-type PSD-95 and that PSD-95 is present in nearly all dendritic spines in CA1 neurons. Within spines, while PSD-95 exhibited low mobility under basal conditions, its levels could be regulated by chronic changes in neuronal activity. Notably, labeled PSD-95 also allowed us to visualize and unambiguously examine otherwise-unidentifiable excitatory shaft synapses in aspiny neurons, such as parvalbumin-positive interneurons and dopaminergic neurons. Our results demonstrate that the ENABLED strategy provides a valuable new approach to study the dynamics of endogenous synaptic proteins in vivo.

In vivo imaging applications typically require carefully balancing conflicting parameters. Often it is necessary to achieve high imaging speed, low photo-bleaching, and photo-toxicity, good three-dimensional resolution, high signal-to-noise ratio, and excellent physical coverage at the same time. Light-sheet microscopy provides good performance in all of these categories, and is thus emerging as a particularly powerful live imaging method for the life sciences. We see an outstanding potential for applying light-sheet microscopy to the study of development and function of the early nervous system in vertebrates and higher invertebrates. Here, we review state-of-the-art approaches to live imaging of early development, and show how the unique capabilities of light-sheet microscopy can further advance our understanding of the development and function of the nervous system. We discuss key considerations in the design of light-sheet microscopy experiments, including sample preparation and fluorescent marker strategies, and provide an outlook for future directions in the field.

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.

At the time of this writing, searching Google Scholar for 'light-sheet microscopy' returns almost 8500 results; over three-quarters of which were published in the last 5 years alone. Searching for other advanced imaging methods in the last 5 years yields similar results: 'super-resolution microscopy' (>16 000), 'single-molecule imaging' (almost 10 000), SPIM (Single Plane Illumination Microscopy, 5000), and 'lattice light-sheet' (1300). The explosion of new imaging methods has also produced a dizzying menagerie of acronyms, with over 100 different species of 'light-sheet' alone, from SPIM to UM (Ultra microscopy) to SiMView (Simultaneous MultiView) to iSPIM (inclined SPIM, not to be confused with iSPIM, inverted SPIM). How then is the average biologist, without an advanced degree in physics, optics, or computer science supposed to make heads or tails of which method is best suited for their needs? Let us also not forget the plight of the optical physicist, who at best might need help with obtaining healthy samples and keeping them that way, or at worst may not realize the impact their newest technique could have for biologists. This review will not attempt to solve all these problems, but instead highlight some of the most recent, successful mergers between biology and advanced imaging technologies, as well as hopefully provide some guidance for anyone interested in journeying into the world of live-cell imaging.

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.