Acoustic communication is widespread among vertebrates and central to social behavior. Yet how brain-wide circuits identify conspecific signals and distinguish acoustic elements with different, often sex-specific social valence remains poorly understood. Here we present the first whole-brain analysis of neuronal responses to conspecific vocalisations in vertebrates, using the transparent fish Danionella cerebrum. Combining volumetric calcium imaging with playbacks probing the stimulus space of the natural sound repertoire, we uncover an unexpectedly early and specialized processing hierarchy: hindbrain nuclei already segregate vocalization-like pulse trains from tones, midbrain regions sharpen these representations and extract temporal features that define vocalization type, and the central posterior thalamic nucleus responds selectively to conspecific vocalization rates and thus acts as a gate for social sounds. Male and female brains share this early feature code but diverge in diencephalic and telencephalic regions, where identical acoustic features evoke sex-specific population activity patterns that parallel dimorphic behavior. Together, our results provide the first cellular-resolution, brain-wide account of social sound processing in a vertebrate, from early categorical segregation to thalamic gating and sex-specific population responses in social circuits.

Cfr methylates C8 of adenosine 2503 (A2503) in 23S ribosomal RNA (rRNA) and will also methylate C2 of A2503 after methylating C8. C8methylation confers resistance to more than five classes of clinically used antibiotics, highlighting it as a worrisome mechanism of antibiotic resistance. Here, we report the structure of Cfr, determined by cryogenic electron microscopy (Cryo-EM). Despite its small size (∼36 kDa), we exploit a transient protein–RNA crosslink that forms during catalysis, which requires Cys105 to resolve. Using a Cfr Cys105Ala variant and an 87-nucleotide strand of rRNA, we isolate the crosslinked species and determine its structure to 3.0 Å resolution. Notably, the 87-mer rRNA adopts an L-shaped conformation characteristic of tRNAs, rather than the conformation it assumes in the ribosome.

Connectomics has become essential for the study of brain function, yet for most research groups it remains prohibitively costly in imaging time, data storage, and analysis. Here, we present an imaging, processing, and analysis pipeline for multi-resolution image acquisition and circuit reconstruction. Applied to the central complex of six insect species, we were able to obtain global projectomes at cellular resolution (40-50 nm) with embedded local connectomes describing key computational compartments at synaptic resolution (8-12 nm). We provide standardized protocols for volume EM sample preparation, image acquisition and image alignment, combined with existing methods for µCT block trimming, automatic segmentation, synapse detection, collaborative skeleton tracing with CATMAID, and segmentation proofreading via CAVE. We validated our workflow by reconstructing head direction cells across all six insect species, which revealed deep conservation at the level of cell types, cell numbers and projection patterns, while also revealing circuit level specializations. Overall, our pipeline democratizes comparative connectomics by making this method accessible for small research groups with modest resources.

Monitoring GABAergic inhibition in the nervous system has been enabled by development of an intensiometric molecular sensor that directly detects GABA. However, the first generation iGABASnFR exhibits low signal-to-noise and suboptimal kinetics, making in vivo experiments challenging. To improve sensor performance, we targeted several sites in the protein for near-saturation mutagenesis and evaluated the resulting sensor variants in a high throughput screening system using evoked synaptic release in primary cultured neurons. This identified a sensor variant, iGABASnFR2, with 4.2-fold improved sensitivity and 20% faster kinetics, and binding affinity that remained in a range sensitive to changes in GABA concentration at synapses. We also identified sensors with an inverted response, decreasing fluorescence intensity upon GABA binding. We termed the best such negative-going sensor iGABASnFR2n, which can be used to corroborate observations with the positive-going sensor. These improvements yielded a qualitative enhancement of in vivo performance when compared directly to the original sensor. iGABASnFR2 enabled the first measurements of direction-selective GABA release in the retina. In vivo imaging in somatosensory cortex revealed that iGABASnFR2 can report volume-transmitted GABA release following whisker stimulation. Overall, the improved sensitivity and kinetics of iGABASnFR2 make it a more effective tool for imaging GABAergic transmission in intact neural circuits.

Mitochondria utilize calcium to increase ATP synthesis. However, excessive matrix calcium activates the mitochondrial permeability transition (mPT), a process that permeabilizes the mitochondrial inner membrane and leads to cell death. While initially characterized 50 y ago, the proteins underlying the process are unclear, although integral membrane proteins were expected to be the porous entities during calcium overload. Here, we designed two assays to study the mPT using high-throughput methodologies. By surveying 19,113 proteins in human cells, we identified four proteins that sensitize the human mPT, but only one that was essential for mPT activation, mitochondrial-localized NRLX1. Surprisingly, NLRX1 is not an integral membrane protein, and our work did not identify any essential integral membrane proteins for the human mPT. The mitochondrial permeability transition (mPT) is an evolutionarily conserved destructive process that permeabilizes the inner mitochondrial membrane in response to calcium overload. The molecular mechanism underlying the mPT is not established. To unambiguously identify essential proteins, we designed two phenotypic assays for mitochondrial calcium overload and applied them to FACS-based CRISPR screening in human cells, ultimately evaluating 19,113 genes. The first screen studied mitochondrial membrane potential (MMP) collapse in response to calcium overload. Top-ranked genes were the essential proteins of the mitochondrial calcium uniporter complex, MCU and EMRE, reflecting that the calcium-induced MMP collapse results from mitochondrial calcium entry and not the mPT. The second screen measured the permeability of the inner mitochondrial membrane. Here, the fluorescent interaction of a membrane impermeant 600 Da dye and a mitochondrial-targeted HaloTag protein was studied under mPT activating conditions; calcium overload and the thiol-reactive molecule phenylarsine oxide. With secondary validation, we identified four protein-encoding genes that delayed or prevented the mPT under knockout: NF2, REST, BPTF, and NRLX1. Knockout of the nonmitochondrial proteins BPTF, NF2, or REST increased mitochondrial calcium retention capacity (CRC). However, calcium release or sensitivity to cyclosporin A (CsA) persisted, indicative of mPT sensitizers. Only knockout of the mitochondrial matrix protein, NLRX1, increased CRC, abolished calcium release, and was CsA-insensitive. This top-ranked hit of the mitochondrial permeability screen meets the definition of an essential mPT activator. Integral membrane proteins, including all previously proposed mPT candidates, were not essential activators.

Most existing deep learning-based cell tracking methods rely on supervised learning, requiring large-scale annotated datasets that are often unavailable in real-world scenarios. Moreover, many approaches lack tools and methods for correcting mispredicted links or incorporating corrections through fine-tuning. These limitations contribute to the limited adoption of deep learning-based tracking methods in the life sciences, where manual tracking remains the predominant approach. To reduce the annotation burden and enable model training without extensive labeled data, we introduce a loss function for unsupervised training. Our method leverages the predictable dynamics inherent in many biological processes, providing an initialization that does not require an annotated dataset. We further investigate how minimal user-provided annotations can refine tracking accuracy. To this end, we propose an active learning framework that selectively identifies uncertain decisions within the tracking graph, allowing for efficient annotation of the most informative data points. We evaluate our approach on two microscopy datasets, demonstrating the effectiveness of both our unsupervised training strategy and active learning scheme in improving tracking performance. Our implementation and reproducible experiments are available at github.com/funkelab/attrackt and github.com/funkelab/attrackt_experiments, respectively.

Expansion microscopy (ExM) enables nanoscale imaging on standard microscopes, but combining ExM with single-molecule localization microscopy (SMLM) remains difficult, owing to the incompatibility of expanded hydrogels with photoswitching buffers. Here, we introduce a single-step expansion microscopy method that allows SMLM with spontaneously blinking dyes in 6-14× expanded samples, without re-embedding. We demonstrate nanometer-resolution imaging by resolving the organization of the nuclear pore complex (NPC) and the molecular structure of recombinant homotrimeric proliferating cell nuclear antigen (PCNA).

Calcium imaging with miniature endoscopes has become an essential tool in neuroscience, but conventional miniscopes typically record signals from only a single calcium indicator. Here, we present a dual-color miniature endoscope (miniscope) that enables simultaneous calcium imaging from two neuronal populations using spectrally distinct genetically encoded indicators. In freely moving mice, we used this system to record activity from striatal neurons of the direct (dSPN) and indirect (iSPN) pathways. We showed that dSPNs were activated earlier than iSPNs during contraversive movements, with dSPNs preferentially active during acceleration and iSPNs during deceleration. During ipsiversive turns, however, this temporal relationship was reversed. These findings indicate that dSPNs and iSPNs are not concurrently active, but instead exhibit complementary, direction-dependent dynamics that govern movement velocity. Our dual-color miniscope provides a compact, cost-effective platform for simultaneous two-population imaging, offering new opportunities to dissect coordinated activity across neural circuits in freely behaving animals.

Many fungi utilize high turgor pressure for morphogenesis, requiring tight regulation of ionic gradients. Ion regulation is important for pathogenesis, reproduction, and general homeostasis across the fungal kingdom. In the major human fungal pathogen Candida albicans, potassium (K+) channels fine-tune ionic balance under stressful environmental conditions, contributing to colonization of the human host. Two-pore domain, outwardly rectifying potassium (TOK) channels, uniquely found in fungi, remain insufficiently characterized despite early evidence implicating them in diverse intracellular processes essential for cellular growth and viability, and their potential as antifungal targets. Here, we describe the first atomic resolution structure of a fungal potassium channel—TOK1 from C. albicans (CaTOK)—revealing a membrane topology distinct from all other known K+ channel classes. We propose that CaTOK1 utilizes two unique regions—TOK auxiliary subunit-like channel (TALC) domain and a structured c-terminal bundle—to regulate TOK1 gating. Conformational analysis of TOK1 pore features an inner helical gating mechanism with “up” and “down” conformations similar to mammalian dimeric K+ channels. These findings provide a structural framework for understanding TOK channel activity and lay the groundwork for future studies on fungal ion homeostasis, pathogenicity, and therapeutic development.

To form a blood clot, fibrinogen is converted into fibrin through the action of the enzyme thrombin. Fibrin then polymerizes longitudinally and laterally as it matures into a fiber. Polymerization results in a dense, 3-dimensional branched network. Previous research has shown the relevance of these fibrin gel structures in hemostatic conditions; however, the mechanism by which they form has not been fully resolved. Using light sheet microscopy, 3-dimensional volumes of the fibrin polymerization process were captured. Manual annotation of these microscopy videos revealed that fiber branch points occur through the collision and the binding of diffusing fibers rather than through the splitting of growing fiber termini. However, the density of fibers and amount of data greatly slows manual annotation-based analysis and limits the ability to capture important data, such as growth rates and fiber stiffness. To more quickly process these data, a computational approach was utilized. A custom tracking pipeline, suited to the networks formed by cylindrical fibrin fibers, was developed, beginning with an AI-based classifier. This custom pipeline allowed for the tracking of uniquely labeled fibers over time. Automated merge detection between linking phases further improved accuracy. Additionally, network formation was analyzed through skeletonization techniques to measure the number of branches per junction over time. Combining the skeletonization and tracking methods, single fibers were identified by their lack of branch points and tracked. The addition of branch points to previously tracked objects served as a signal for merge detection. This approach yielded measurements of single fibrin fiber diffusion rates, as well as the first volumetric and length growth rates of fibers throughout polymerization. In addition, the gel point was quantified by analyzing the span of connected objects to characterize the network consolidation over time at the level of single fibers.