Summary Fluorescent imaging in live cells is a cornerstone of life sciences. While natural fluorescent proteins have been engineered to enhance individual features, no existing tag combines ideal properties into a single system: high brightness, reversible binding, compact size, and stability across diverse conditions. Here, we achieve this through de novo design of rhodamine binders (Rhobin). To harness the broad repertoire of rhodamine fluorophores, we developed a generalizable design strategy for a pan-rhodamine binder compatible with diverse wavelengths and applications. Rhobin enables live- and fixed-cell imaging of various subcellular targets in mammalian cells, showing brightness surpassing existing tags. Its reversible fluorophore binding supports super-resolution stimulated emission depletion (STED) and live-cell single-molecule imaging for extended durations compared with HaloTag. Beyond conventional systems, Rhobin enables live imaging of the extremophile Sulfolobus acidocaldarius at 75°C, previously inaccessible with current tags. Together, these results establish Rhobin as a versatile platform for next-generation imaging and biosensor design.

A developmental increase in cerebrospinal fluid (CSF) production during development is essential for neuronal growth and ventricular expansion. A key regulator of CSF production is the specialized sensory multicilia of the choroid plexus (ChP), which mediate non-canonical Sonic hedgehog (Shh) signaling to suppress water channel and ion transporter expression, thereby limiting CSF production. ChP multicilia progressively shortens during development, attenuating Shh signaling and promoting CSF production. Here, we identify miR-34/449 miRNAs as essential regulators of ChP multiciliogenesis. Whereas mutations in canonical ciliogenesis genes elevate CSF production and contribute to hydrocephaly, deletion of miR-34/449 reduces CSF volume and causes microcephaly. Loss of miR-34/449 miRNAs causes excessive basal body amplification, defective basal body docking, and failure of developmental multiciliary shortening. Consequently, miR-34/449-deficient ChP cilia remain abnormally long and fail to attenuate Shh signaling, resulting in sustained repression of water channel and ion transporter expression and reduced CSF production. Mechanistically, miR-34/449 miRNAs directly target Gmnc, a master transcriptional regulator of multiciliogenesis, to restrain basal body amplification and promote basal body docking. Together, our findings identify miR-34/449 miRNAs as critical regulators of ChP multiciliogenesis and establish the developmental remodeling of ChP multicilia as a mechanism to couple Shh signaling dynamics to developmental control of CSF production.

T4 and T5 neurons are the first direction-selective neurons in the visual pathway. They are the most numerous cell types in the fly brain (~6000 within each optic lobe) and, as a population, their compact dendritic arbours span the entire visual field. They are classified into four subtypes (a, b, c, and d). Each subtype encodes one of four orthogonal motion directions (up, down, forwards, backwards). Crucially, the dendrites of these neurons are oriented inversely to the functional direction of motion which they encode. This dendritic orientation is what ultimately determines their functional directional encoding. The development of these neurons is well characterised up to the point of neuropil innervation. However, the full population of these neurons innervate their target neuropil prior to the emergence of directionality within their dendrites. As it stands, development prior to the emergence of dendritic orientations, and the adult oriented dendrite are both well understood, but the key components relating to the emergence of orientation itself are missing. Recent whole-brain electron microscopy (EM) connectomes of Drosophila melanogaster provide an unprecedented level of resolution and completeness when considering the morphology of neurons. Utilising this, we isolate the dendritic arbour of every T4 and T5 neuron within a female adult Drosophila brain, made available through FAFB-FlyWire. In doing so we are able to rigorously quantify the morphology of these dendrites in order to understand their similarities and differences. In doing so we aim to shed light on the origins of dendritic directionality. We reason that either this emerges through a tightly controlled, subtype specific mechanism, or is the result of a subtype agnostic mechanism and external factors. In the former case, we would expect evidence of this in differences between the morphological structure of individual dendrites between T4 and T5, and their subtypes. Our analysis however reveals a high degree of structural similarity between T4 and T5, and within their subtypes. Particularly, the geometry of branching, section orientation, and tree-graph structure of these dendrites show only minor variability, with no consistent separation between T4 and T5, or their subtypes. These results indicate that, despite forming in different neuropils, and serving distinct motion directions, T4 and T5 dendrites follow closely aligned morphological patterns. This suggests a shared mechanism of directed outgrowth, as opposed to symmetry breaking emerging through neuron type or subtype specific mechanisms.

Recent advances in field technology have led to a massive influx of in-the-wild video data for ecological science. The primary bottleneck in leveraging this data is the high cost of expert annotation. While computer vision offers a potential solution, current models frequently fail when deployed in complex marine environments. To characterize these failures, we introduce WildFin, a novel benchmark for fish behavior recognition collected and annotated by ecologists. WildFin spans two critical real-world paradigms: stationary cameras monitoring groups of fish and dynamic divers following individual subjects. The dataset represents a massive curation effort, involving 1,350 hours of fieldwork and 600 hours of expert annotation to produce 9 hours of behavioral data with over 2 million frame-by-frame labels. We benchmark modern vision foundation models and quantify tradeoffs between static and spatiotemporal architectures, revealing the substantial gap that remains between current model capabilities and the demands of real-world underwater behavioral analysis. Project website: this https URL.

A central challenge in systems neuroscience research is to elucidate how distinct neuronal cell types coordinate to produce complex behaviors: an endeavor that requires linking their molecular identity, connectivity and activity patterns in behaving animals. Recent advances in single-cell RNA sequencing and spatial transcriptomics have revealed remarkable molecular diversity among neurons. However, most functional recording techniques, including in vivo two-photon calcium imaging, do not reveal the molecular cell identities of recorded cells. Although manual one-to-one matching between functional imaging and post hoc molecular profiling has been achieved for dozens to a few hundred neurons, these approaches are typically labor-intensive, difficult to scale, and capture only a limited fraction of cell types. Integrating these two modalities at large scale remains challenging, limiting our ability to fully understand the general logic of neural computation. Here we present a cross-modal workflow that integrates in vivo two-photon calcium imaging in behaving mice with Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH), a thick-tissue spatial transcriptomic approach. As a proof of concept, we apply this workflow to the mouse dorsal hippocampus, a brain region with high neuronal density and small cell size where manual cell matching is impractical, making it a stringent test of the method’s accuracy and scalability. Using our approach, we achieved highly accurate alignment between in vivo neural activity and ex vivo molecular cell-type identity across hundreds to thousands of neurons, enabling direct mapping of neural dynamics to molecularly defined neuronal populations. We showed that longitudinal neural recordings followed by molecular mapping reveal distinct neural activity patterns that emerge as animals learn a spatial navigation task. By linking activity patterns to molecularly defined cell types, this method provides a framework for testing whether neural representations are organized through cell-type-specific coding or distributed population activity, offering insight into the computational logic by which neural circuits generate complex behaviors.MOTIVATION The mammalian brain contains an immense diversity of neurons exhibiting substantial morphological, functional, and molecular diversity. Understanding how this molecular heterogeneity supports neural computation and shapes behavior remains a central challenge in systems neuroscience. Yet, most approaches for recording neural activity provide limited access to molecular identity, making it difficult to directly relate functional dynamics to cell-type-specific features across many neurons in the same tissue. Here, we present a cross-modal workflow that recovers, aligns, and matches in vivo neural activity with targeted molecular profiling, enabling functional readouts and RNA profiling to be coupled at the individual cell level. This method provides a powerful platform for uncovering how molecularly defined neurons contribute to complex activity patterns and, ultimately, animal behavior.

RNA design has been hindered by the limited accuracy of three-dimensional (3D) structure prediction. In this study, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an Eterna competition involving 57 pseudoknots, generative artificial intelligence (AI) methods matched experienced human designers in solving most blind challenges, evaluated by single nucleotide-resolution chemical mapping, compensatory mutagenesis, and cryo-electron microscopy. AI-generated molecules with accurate secondary structures formed well-ordered 3D folds stabilized by noncanonical tertiary interactions not modeled during design. Success was guided by an RNet foundation model trained on prior chemical mapping data, suggesting that some difficult RNA design tasks may be tractable without first solving RNA 3D structure prediction.

To select behaviors appropriate to their circumstances and needs, animals integrate information about the external environment with information about the state of their bodies, derived from sensing and processing internal signals (interoception). However, the brain-wide circuit activity underlying interoception and its integration with sensorimotor processing remains unclear, partly because of technical barriers to accessing whole-brain activity at the cellular level during physiological perturbations. We developed an all-optical system for whole-brain neuronal imaging in behaving larval zebrafish during optical uncaging of gut- or bloodstream-targeted nutrients and visuo-motor stimulation. Widespread neural activity throughout the brain encoded nutrient delivery, unfolding on multiple timescales across many peripheral and central regions. Evoked activity depended on delivery location and occurred in response to both amino acids and D-glucose, but not L-glucose. Many gut responsive neurons also responded to swimming and visual stimuli, with brainstem areas primarily integrating gut and motor signals and midbrain regions integrating jointly gut, visual, and motor signals. This platform links body-brain communication studies to brain-wide neural computation in awake, behaving vertebrates.

The lifetime of fluorescent molecules provides an orthogonal readout to fluorescence intensity, opening experimental possibilities of measuring changes in local molecular environments, mechanical tension, and metabolism, among other factors. These changes are best studied live and in vivo; however, limitations of slow imaging speeds, high phototoxicity, and increased data size and complexity have significantly impeded progress on this front. Here, we present a complete and transferable pipeline consisting of a light sheet FLIM microscope and an accompanying machine learning model for data processing that renders long-term and/or high-speed volumetric FLIM (vFLIM) tractable in living systems. We benchmark this pipeline across several biological use cases, model systems, lifetime ranges, and spatiotemporal scales, showcasing a suite of possibilities that our workflow enables. This comprehensive pipeline from imaging to analysis is a crucial step forward towards disseminating the power of live vFLIM to the broader bioimaging community.

The actin cytoskeleton is a fundamental and highly conserved structure that functions in diverse cellular processes, yet its direct contribution to organismal aging remains unclear. Here, we systematically interrogated how genetic and pharmacologic perturbations of actin structure and function influence lifespan and various hallmarks of aging in . Whole-animal and tissue-specific knockdown of actin and key actin-binding proteins (ABPs)- (Arp2/3), (cofilin), and (tropomyosin)-led to premature disruption of filament organization, reduced lifespan, and tissue-specific physiological defects. Actin dysfunction also displayed a more "aged" transcriptome using previously validated transcriptomics clocks, and broadly exacerbated many age-associated phenotypes, including mitochondrial dysfunction, lipid dysregulation, loss of proteostasis, impaired autophagy, and intestinal barrier failure. Pharmacological destabilization with Latrunculin A mirrored genetic knockdowns, while mild stabilization with Jasplakinolide modestly extended lifespan, emphasizing that optimal and finely tuned actin function is critical for healthy aging. Finally, analysis of human genome-wide association data revealed that common polymorphisms correlate with differences in age-related decline in gait speed, suggesting some links between aging and actin across organisms. Taken together, our results provide a comprehensive and publicly accessible resource that maps, for the first time, how changes in actin integrity correlate with diverse aging phenotypes across tissues. This descriptive framework is intended to enable future mechanistic discovery by offering a deep, unbiased dataset that can be integrated with emerging studies to define how actin dynamics can potentially influence aging.

To elicit voluntary movements and integrative reflexes underlying behavior, the brain sends command signals to the spinal cord via specialized long-range descending neurons, known as spinal-projecting neurons (SPNs). The vast and widespread distribution of SPNs, combined with their complex long-distance connectivity, poses a significant challenge for mapping their anatomical organization and associating specific populations with distinct functions. Here we took advantage of the transparency and genetic accessibility of larval zebrafish to uncover the fundamental principles of SPN anatomical organization in a Teleost. Using an optical backfilling method relying on photoactivable GFP, we generate a whole-brain map of all neurons sending axons towards the spinal cord. This approach reveals far more SPNs than previously described through conventional strategies, offering an unparalleled opportunity to revisit distinct spinal-projecting nuclei distributed across hindbrain, midbrain, and diencephalic structures. Combining information on cell location, morphology, and projection patterns, we propose tentative homological designations for zebrafish of SPN nuclei based on established descriptions in mammals and other vertebrates.