Archaeal histone-based chromatin complexes are the evolutionary precursor of the eukaryotic nucleosomal landscape. Histones are encoded by most Archaea and are present in sufficient quantities in many heat-loving species to plausibly completely wrap and condense the genome(s). Establishing whether the in vivo archaeal histone-based chromatin structure(s) align to the repeating extended polymeric structures revealed with purified components in vitro remains an important goal to link the biological roles of archaeal and eukaryotic histone-based chromatin structures. Deploying advanced imaging and cryo-electron tomography techniques with the hyperthermophilic, histone-encoding archaeon Thermococcus kodakarensis, we reveal that the in vivo histone-based chromatin architecture changes dramatically during the growth cycle. While the cytoplasm contains a relatively uniform nucleoid in exponential growth, tightly packed, helical filaments that conform to archaeal histone-based chromatin observed in vitro emerge during the transition to stationary phase. The in vitro extended chromatin conformation of histone-based genome architecture observed in vivo establishes that archaeal information processing machinery can function on tightly packed and regularly organized histone-based chromatin structures. We also observe large, nucleic-acid rich, globular condensates directly alongside the helical filamentous chromatin conformation that may represent an additional conformation of archaeal chromatin. Our results suggest that alternative forms of archaeal chromatin may be achieved without obvious chromatin remodeling complexes or biologically significant levels of post-translational modifications to histone proteins, providing a plausible evolutionary driver for the emergence of more complex mechanisms that protect and regulate expression of eukaryotic genomes.

High-spatial-resolution in situ mapping of biomolecules within tissue reveals critical insights into the complex molecular landscape and spatial organization of biological systems. Mass spectrometry imaging (MSI) is a powerful tool for spatially resolved molecular analysis of biological samples, with ongoing demand for improved spatial resolution. Tissue expansion combined with MSI (TEMI) is a recently developed approach that enables multiomics molecular mapping across various biological tissues with significantly improved spatial resolution. Unlike conventional methods that depend on instrument-based enhancements in spatial resolution, TEMI physically enlarges tissue samples via harsh-condition-free hydrogel expansion, achieving more than 3.5-fold increase in effective imaging resolution using standard MSI instrumentation. TEMI delivers single-cell spatial resolution in tissue samples and enables detection of biomolecular heterogeneity that remains uncharacterizable in unexpanded tissue using conventional MSI. Notably, TEMI supports high-spatial-resolution mapping of multiple biomolecular classes-including lipids, metabolites, N-glycans, peptides and proteins-within a single tissue sample. Here, we provide a detailed, step-by-step guide for TEMI, including hydrogel-based tissue expansion under mild conditions, cryosectioning of the expanded tissue-hydrogel sample, a comprehensive experimental workflow for multiomics TEMI on a single tissue section, data acquisition and visualization pipelines, as well as troubleshooting tips. Overall, we demonstrate that TEMI overcomes the long-standing spatial limitations of MSI without requiring hardware modifications, ensuring compatibility with existing MSI instruments and promoting broad accessibility and adoption within the research community.

The gold standard datasets for mapping connectomes are electron microscopy volumes of densely labeled neural tissue at nanometer resolution. Yet reconstructing and proofreading neuronal arbors and annotating all synapses requires pipelining multiple software tools that are often fragmented, inconsistently maintained, or proprietary, hindering reproducibility and automation. Here, we introduce Catena, an open-source, comprehensive, developer-centric software suite for connectomics that integrates modules for 3D neuron and organelle segmentation, synapse detection, microtubule tracking, and neurotransmitter inference. Catena organizes its modules in composable, chunk-wise processing pipelines in a completely documented, extensible, and adaptable design. We further reduce compute and ground-truth data requirements with pretrained machine learning models, facilitating fine-tuning. Catena ships fully containerized modules that encapsulate evolving dependencies for consistent execution across workstations and clusters. By consolidating open components, shareable models, and containerized runtimes, Catena delivers a reproducible and scalable approach to mapping cellular connectomes from electron microscopy volumes. Code and documentation: this https URL

Cell-state diversity drives tissue adaptability, repair, and disease resilience, but capturing this complexity is a challenge. Current approaches rely on transcriptional profiling and overlook organelle structure, a key indicator of metabolism and stress. We developed spatial Organellomics (sOrganellomics), an imaging workflow that integrates automated segmentation with machine learning to classify and spatially map cell states from multi-organelle signatures. In liver and pancreas, these signatures distinguished broad cellular classes. In liver, sOrganellomics revealed that zonal position did not fully explain organelle-defined hepatocyte categories. Instead, hepatocytes formed intermixed communities within canonical zones, supporting a refined subzonal diversity model. Nutritional stress reshaped this organization. Intravital imaging linked fasting-induced organelle remodeling with altered mitochondrial membrane potential in vivo, supporting multi-organelle architecture as a structural readout of tissue adaptation.

Fluorescence microscopy applications often require specialized instruments that are optimized for different experimental goals. Here, we present a reconfigurable microscopy module that integrates highly inclined swept tile (HIST) illumination for high-sensitivity single-molecule imaging and line-scanning confocal microscopy for rapid and optically sectioned volumetric acquisition. The system shares major hardware components, including lasers, scanning optics, and detection hardware, while employing unique beam shaping pathways to enable rapid switching between modalities without realignment. We characterize the module performance by measuring the excitation beam profiles, the point spread functions (PSF), and the optical transfer functions (OTF) across 40x, 60x, and 100x magnifications and demonstrate imaging applications including diffraction-limited fixed and live-cell volumetric imaging, fluorescence recovery after photobleaching, and super-resolution DNA-PAINT and single particle tracking (SPT). We also demonstrate the capability to execute multimodal imaging workflows by performing confocal imaging for chromatin density classification correlated with SPT data of nuclear proteins with diverse functions. Together, these results demonstrate a versatile imaging platform capable of supporting complementary fluorescence imaging modalities within a single instrument.

Nervous systems form wiring patterns that are reproducible across individuals. This reproducibility is thought to emerge from molecular encoding and developmental events, but their relative contributions remain unclear. We address this question in the C. elegans neuropil, where embryonic developmental dynamics and adult anatomy are resolved at single-cell resolution. We find that transient morphogenetic structures — rosettes, corridor cells, pioneer axon scaffold — restrict which axons make contact, shaping the neuropil into overlapping neighborhoods. This demonstrates how early events constrain wiring choices, but not whether they explain the resulting reproducibility. To explain, we use an agent-based model of stochastic innervation that recapitulates macro- and micro-level reproducibility, revealing a trade-off between physical constraint and molecular specificity that limits neighborhood size. Counterintuitively, less selective axons produce more reproducible wiring when constrained within neighborhoods. This trade-off lets nervous systems maximize reproducibility without having to molecularly encode every axon-contact, a strategy for robust yet flexible wiring.

Biological memory systems store single experiences while continuing to learn, but how one-shot plasticity limits interference with existing memories is unclear. Behavioral timescale synaptic plasticity (BTSP) rapidly modifies synapses active within seconds of a dendritic plateau. We isolate its plateau-triggered component in a model where plastic weights and a stable instructive pathway jointly determine whether a plateau occurs, closing a feedback loop between the synaptic state and the plastic event that modifies it. For unstructured inputs, instantiated by independent uniform signed patterns, the dynamics reduce exactly to pathway alignment, which determines the fidelity of the instructed representation, the synaptic-turnover rate and the mean rewrite interval. For structured inputs, instantiated by correlated bimodal Curie–Weiss patterns, the instructive pathway biases which component of input structure enters the plastic synaptic state. In a BTSP-inspired continual-recognition network, combined instructive and plastic drives determined the selected memory unit for each one-shot write, whereas a Hebbian control used the same plastic weights for credit assignment and memory storage. The BTSP-inspired network remained accurate at longer repeat lags than Hebbian controls, an advantage that grew with network size, with both architectures optimized independently at every repeat lag. A reduced theory predicted held-out accuracy, lag capacity and dynamics of memory-trace strength directly from optimized parameters. It showed why intermediate proximal and distal coupling was optimal: proximal plastic drive guided plateau generation toward selected memory units, slowing synaptic turnover but limiting new encoding, whereas distal instructive drive enhanced familiar responses but could also make novel inputs appear familiar. The memory-trace strength in the rate-and-depth-matched Hebbian control still decayed faster and showed less effective credit assignment than in the BTSP-inspired network. These results connect dendritic plateau physiology to continual memory and support partial separation of allocation from storage as a mechanism for limiting interference during continual learning.

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.

An animal's ability to survive and thrive-whether fleeing from danger, eating a meal, or fighting an infection-arises from the collective moment-to-moment activity of many interacting cell types throughout the body. Physiology seeks to elucidate these cellular interactions that span organs, cell types and timescales, but has been limited by the inability to record this time-varying cellular activity simultaneously throughout the entire body. Here we develop WHOLISTIC (WHole-Organism Live-Imaging System for recording Tissue and IntraCellular activity), a method to image second-timescale activity of cells across the entire vertebrate body at cellular resolution. WHOLISTIC advances and integrates volumetric fluorescence microscopy, machine learning, and pancellular transgenic expression of calcium sensors1, demonstrated in larval zebrafish, with proof of concept in adult Danionella cerebrum. To access information about the molecular and ultrastructural substrates for the measured dynamics, we advanced whole-body expansion microscopy2. At the cellular scale, body-wide screening revealed unexpected responses, including chondrocyte reactions to cold and meningeal responses to ketamine. At the organ scale, WHOLISTIC identified rhythmic travelling waves along the renal nephron. At the multi-organ scale, it revealed unknown muscle synergies and muscle-organ interactions. At the whole-organism scale, the method captured brainstem-controlled redistribution of body-wide blood flow. Combining optogenetics with WHOLISTIC enabled all-optical causal dissection of brain-body interactions. These advances establish a paradigm for systems biology that bridges cellular and organismal physiology, enabling comprehensive discovery across scales-from fundamental mechanisms to therapeutic targets.

Robust homeostatic plasticity is essential for survival, enabling neuronal circuits to withstand destabilizing forces and restore function during critical challenges such as predator evasion or toxin exposure. Semaphorin/Plexin signaling is central to presynaptic homeostatic potentiation at central synapses and at neuromuscular junctions across species. However, our understanding of this pathway has remained incomplete, as secreted Semaphorins bind weakly to their Plexin receptors and require additional coreceptors for efficient signaling. Here, we identify Neuropilin and Tolloid-like protein (Neto-α), an auxiliary subunit for ionotropic glutamate receptors (iGluRs), and the tyrosine kinase Abelson (Abl) as essential components of the Sema2b/PlexB signaling pathway that drives rapid homeostatic potentiation and stabilizes synaptic strength at the neuromuscular junction. Neto-α functions as a Neuropilin-like coreceptor that cooperates with Sema2b to relieve PlexB autoinhibition and initiate signaling. In parallel, Neto-α recruits Abl, which functions as a cytosolic amplifier to enhance pathway output. We demonstrate that both pathway activation and amplification are required for a rapid and effective homeostatic response. By integrating these two functions within a single molecular assembly, Neto-α ensures fast and efficient compensatory responses to perturbations. This evolutionarily conserved signaling module, Neto (or Neuropilin)/Sema/Plex/Abl, likely operates in cellular contexts beyond neural function, including in tumorigenesis.