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, blurred or undersampled, 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 or undersampled images. Unlike previous approaches, which 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.

Synchronous neuronal ensembles play a pivotal role in the consolidation of long-term memory in the hippocampus. However, their organization during the acquisition of spatial memory remains less clear. In this study, we used neuronal population voltage imaging to investigate the synchronization patterns of CA1 pyramidal neuronal ensembles during the exploration of a new environment, a critical phase for spatial memory acquisition. We found synchronous ensembles comprising approximately 40% of CA1 pyramidal neurons, firing simultaneously in brief windows (∼25ms) during immobility and locomotion in novel exploration. Notably, these synchronous ensembles were not associated with ripple oscillations but were instead phase-locked to local field potential theta waves. Specifically, the subthreshold membrane potentials of neurons exhibited coherent theta oscillations with a depolarizing peak at the moment of synchrony. Among newly formed place cells, pairs with more robust synchronization during locomotion displayed more distinct place-specific activities. These findings underscore the role of synchronous ensembles in coordinating place cells of different place fields.

Most mammalian cells prevent viral infection and proliferation by expressing various restriction factors and sensors that activate the immune system. While anti-human immunodeficiency virus type 1 (HIV-1) host restriction factors have been identified, most of them are antagonized by viral proteins. This has severely hindered their development in anti-HIV-1 therapy. Here, we describe CCHC-type zinc-finger-containing protein 3 (ZCCHC3) as a novel anti-HIV-1 factor that is not antagonized by viral proteins. ZCCHC3 suppresses production of HIV-1 and other retroviruses. We show that ZCCHC3 acts by binding to Gag nucleocapsid protein via zinc-finger motifs. This prevents interaction between the Gag nucleocapsid protein and viral genome and results in production of genome-deficient virions. ZCCHC3 also binds to the long terminal repeat on the viral genome via the middle-folded domain, sequestering the viral genome to P-bodies, which leads to decreased viral replication and production. Such a dual antiviral mechanism is distinct from that of any other known host restriction factors. Therefore, ZCCHC3 is a novel potential target in anti-HIV-1 therapy.

Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.

Light sheet microscopes enable rapid, high-resolution imaging of biological specimens; however, biological processes span a variety of spatiotemporal scales. Moreover, long-term phenotypes are often instigated by rare or fleeting biological events that are difficult to capture with a single imaging modality and constant imaging parameters. To overcome this limitation, we present smartLLSM, a microscope that incorporates AI-based instrument control to autonomously switch between epifluorescent inverted imaging and lattice light sheet microscopy. We apply this technology to two major scenarios. First, we demonstrate that the instrument provides population-level statistics of cell cycle states across thousands of cells on a coverslip. Second, we show that by using real-time image feedback to switch between imaging modes, the instrument autonomously captures multicolor 3D datasets or 4D time-lapse movies of dividing cells at rates that dramatically exceed human capabilities. Quantitative image analysis on high-content + high-throughput datasets reveal kinetochore and chromosome dynamics in dividing cells and determine the effects of drug perturbation on cells in specific mitotic stages. This new methodology enables efficient detection of rare events within a heterogeneous cell population and records these processes with high spatiotemporal 4D imaging over statistically significant replicates.

The density and distribution of regulatory information in non-coding DNA of eukaryotic genomes is largely unknown. Evolutionary analyses have estimated that ∼60% of nucleotides in intergenic regions of the D. melanogaster genome is functionally relevant. This estimate is difficult to reconcile with the commonly accepted idea that enhancers are compact regulatory elements that generally encompass less than 1 kilobase of DNA. Here, we approached this issue through a functional dissection of the regulatory region of the gene shavenbaby (svb). Most of the ∼90 kilobases of this large regulatory region is highly conserved in the genus Drosophila, though characterized enhancers occupy a small fraction of this region. By analyzing the regulation of svb in different contexts of Drosophila development, we found that the regulatory architecture that drives svb expression in the abdominal pupal epidermis is organized in a dramatically different way than the information that drives svb expression in the embryonic epidermis. While in the embryonic epidermis svb is activated by compact and dispersed enhancers, svb expression in the pupal epidermis is driven by large regions with enhancer activity, which occupy a great portion of the svb cis-regulatory DNA. We observed that other developmental genes also display a dense distribution of putative regulatory elements in their regulatory regions. Furthermore, we found that a large percentage of conserved non-coding DNA of the Drosophila genome is contained within putative regulatory DNA. These results suggest that part of the evolutionary constraint on non-coding DNA of Drosophila is explained by the density of regulatory information.

The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.

How memories of past events influence behavior is a key question in neuroscience. The major associative learning center in Drosophila, the Mushroom Body (MB), communicates to the rest of the brain through Mushroom Body Output Neurons (MBONs). While 21 MBON cell types have their dendrites confined to small compartments of the MB lobes, analysis of EM connectomes revealed the presence of an additional 14 MBON cell types that are atypical in having dendritic input both within the MB lobes and in adjacent brain regions. Genetic reagents for manipulating atypical MBONs and experimental data on their functions has been lacking. In this report we describe new cell-type-specific GAL4 drivers for many MBONs, including the majority of atypical MBONs. Using these genetic reagents, we conducted optogenetic activation screening to examine their ability to drive behaviors and learning. These reagents provide important new tools for the study of complex behaviors in Drosophila.

Neurons express various combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here, we use epitope-tagged endogenous NR subunits, expansion light-sheet microscopy, and electron microscopy (EM) connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion-sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type-specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determine patterns of synaptic inputs. In support of this model, we identify a transmembrane protein selectively associated with a subset of spatially restricted synapses and demonstrate its requirement for synapse formation through genetic analysis. We propose that mechanisms that regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.

Cells rely on a diverse array of engulfment processes to sense, exploit, and adapt to their environments. Among these, macropinocytosis enables indiscriminate and rapid uptake of large volumes of fluid and membrane, rendering it a highly versatile engulfment strategy. Much of the molecular machinery required for macropinocytosis has been well established, yet how this process is regulated in the context of organs and organisms remains poorly understood. Here, we report the discovery of extensive macropinocytosis in the outer epithelium of the cnidarian . Exploiting 's relatively simple body plan, we developed approaches to visualize macropinocytosis over extended periods of time, revealing constitutive engulfment across the entire body axis. We show that the direct application of planar stretch leads to calcium influx and the inhibition of macropinocytosis. Finally, we establish a role for stretch-activated channels in inhibiting this process. Together, our approaches provide a platform for the mechanistic dissection of constitutive macropinocytosis in physiological contexts and highlight a potential role for macropinocytosis in responding to cell surface tension. [Media: see text] [Media: see text] [Media: see text] [Media: see text].