Filter
Associated Lab
- 43418 (1) Apply 43418 filter
- 43430 (3) Apply 43430 filter
- Ahrens Lab (5) Apply Ahrens Lab filter
- Aso Lab (2) Apply Aso Lab filter
- Betzig Lab (4) Apply Betzig Lab filter
- Beyene Lab (1) Apply Beyene Lab filter
- Card Lab (3) Apply Card Lab filter
- Clapham Lab (2) Apply Clapham Lab filter
- Darshan Lab (4) Apply Darshan Lab filter
- Dickson Lab (3) Apply Dickson Lab filter
- Dudman Lab (3) Apply Dudman Lab filter
- Espinosa Medina Lab (7) Apply Espinosa Medina Lab filter
- Feliciano Lab (1) Apply Feliciano Lab filter
- Fitzgerald Lab (4) Apply Fitzgerald Lab filter
- Funke Lab (6) Apply Funke Lab filter
- Harris Lab (1) Apply Harris Lab filter
- Hermundstad Lab (6) Apply Hermundstad Lab filter
- Hess Lab (7) Apply Hess Lab filter
- Jayaraman Lab (3) Apply Jayaraman Lab filter
- Karpova Lab (1) Apply Karpova Lab filter
- Keleman Lab (1) Apply Keleman Lab filter
- Keller Lab (1) Apply Keller Lab filter
- Lavis Lab (13) Apply Lavis Lab filter
- Lee (Albert) Lab (1) Apply Lee (Albert) Lab filter
- Leonardo Lab (1) Apply Leonardo Lab filter
- Li Lab (5) Apply Li Lab filter
- Lippincott-Schwartz Lab (8) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (5) Apply Liu (Zhe) Lab filter
- Looger Lab (10) Apply Looger Lab filter
- O'Shea Lab (1) Apply O'Shea Lab filter
- Pachitariu Lab (5) Apply Pachitariu Lab filter
- Pedram Lab (1) Apply Pedram Lab filter
- Podgorski Lab (2) Apply Podgorski Lab filter
- Reiser Lab (4) Apply Reiser Lab filter
- Romani Lab (3) Apply Romani Lab filter
- Rubin Lab (1) Apply Rubin Lab filter
- Saalfeld Lab (7) Apply Saalfeld Lab filter
- Scheffer Lab (1) Apply Scheffer Lab filter
- Schreiter Lab (1) Apply Schreiter Lab filter
- Sgro Lab (3) Apply Sgro Lab filter
- Singer Lab (1) Apply Singer Lab filter
- Spruston Lab (2) Apply Spruston Lab filter
- Stern Lab (8) Apply Stern Lab filter
- Sternson Lab (3) Apply Sternson Lab filter
- Stringer Lab (6) Apply Stringer Lab filter
- Svoboda Lab (6) Apply Svoboda Lab filter
- Tebo Lab (1) Apply Tebo Lab filter
- Tillberg Lab (4) Apply Tillberg Lab filter
- Truman Lab (1) Apply Truman Lab filter
- Turaga Lab (3) Apply Turaga Lab filter
- Turner Lab (3) Apply Turner Lab filter
- Vale Lab (2) Apply Vale Lab filter
- Wang (Shaohe) Lab (1) Apply Wang (Shaohe) Lab filter
Associated Project Team
Publication Date
- December 2022 (16) Apply December 2022 filter
- November 2022 (19) Apply November 2022 filter
- October 2022 (13) Apply October 2022 filter
- September 2022 (28) Apply September 2022 filter
- August 2022 (14) Apply August 2022 filter
- July 2022 (20) Apply July 2022 filter
- June 2022 (12) Apply June 2022 filter
- May 2022 (23) Apply May 2022 filter
- April 2022 (9) Apply April 2022 filter
- March 2022 (16) Apply March 2022 filter
- February 2022 (20) Apply February 2022 filter
- January 2022 (12) Apply January 2022 filter
- Remove 2022 filter 2022
Type of Publication
202 Publications
Showing 71-80 of 202 resultsWe present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8% of cell lineages spanning 1 h, as compared to 31.8% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.
To coordinate cellular physiology, eukaryotic cells rely on the inter-organelle transfer of molecules at specialized organelle-organelle contact sites1,2. Endoplasmic reticulum-mitochondria contact sites (ERMCSs) are particularly vital communication hubs, playing key roles in the exchange of signaling molecules, lipids, and metabolites3. ERMCSs are maintained by interactions between complementary tethering molecules on the surface of each organelle4,5. However, due to the extreme sensitivity of these membrane interfaces to experimental perturbation6,7, a clear understanding of their nanoscale structure and regulation is still lacking. Here, we combine 3D electron microscopy with high-speed molecular tracking of a model organelle tether, VAPB, to map the structure and diffusion landscape of ERMCSs. From EM reconstructions, we identified subdomains within the contact site where ER membranes dramatically deform to match local mitochondrial curvature. In parallel live cell experiments, we observed that the VAPB tethers that mediate this interface were not immobile, but rather highly dynamic, entering and leaving the site in seconds. These subdomains enlarged during nutrient stress, indicating ERMCSs can readily remodel under different physiological conditions. An ALS-associated mutation in VAPB altered the normal fluidity of contact sites, likely perturbing effective communication across the contact site and preventing remodeling. These results establish high speed single molecule imaging as a new tool for mapping the structure of contact site interfaces and suggest that the diffusion landscape of VAPB is a crucial component of ERMCS homeostasis.
The severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) and SARS-CoV-1 accessory protein Orf3a colocalizes with markers of the plasma membrane, endocytic pathway, and Golgi apparatus. Some reports have led to annotation of both Orf3a proteins as a viroporin. Here we show that neither SARS-CoV-2 nor SARS-CoV-1 form functional ion conducting pores and that the conductances measured are common contaminants in overexpression and with high levels of protein in reconstitution studies. Cryo-EM structures of both SARS-CoV-2 and SARS-CoV-1 Orf3a display a narrow constriction and the presence of a basic aqueous vestibule, which would not favor cation permeation. We observe enrichment of the late endosomal marker Rab7 upon SARS-CoV-2 Orf3a overexpression, and co-immunoprecipitation with VPS39. Interestingly, SARS-CoV-1 Orf3a does not cause the same cellular phenotype as SARS-CoV-2 Orf3a and does not interact with VPS39. To explain this difference, we find that a divergent, unstructured loop of SARS-CoV-2 Orf3a facilitates its binding with VPS39, a HOPS complex tethering protein involved in late endosome and autophagosome fusion with lysosomes. We suggest that the added loop enhances SARS-CoV-2 Orf3a ability to co-opt host cellular trafficking mechanisms for viral exit or host immune evasion.
Cell lineage defines the mitotic connection between cells that make up an organism. Mapping these connections in relation to cell identity offers an extraordinary insight into the mechanisms underlying normal and pathological development. The analysis of molecular determinants involved in the acquisition of cell identity requires gaining experimental access to precise parts of cell lineages. Recently, we have developed CaSSA and CLADES, a new technology based on CRISPR that allows targeting and labeling specific lineage branches. Here we discuss how to better exploit this technology for lineage studies in Drosophila, with an emphasis on neuronal specification.
Interplay between models and experimental data advances discovery and understanding in biology, particularly when models generate predictions that allow well-designed experiments to distinguish between alternative mechanisms. To illustrate how this feedback between models and experiments can lead to key insights into biological mechanisms, we explore three examples from cellular slime mold chemotaxis. These examples include studies that identified chemotaxis as the primary mechanism behind slime mold aggregation, discovered that cells likely measure chemoattractant gradients by sensing concentration differences across cell length, and tested the role of cell-associated chemoattractant degradation in shaping chemotactic fields. Although each study used a different model class appropriate to their hypotheses - qualitative, mathematical, or simulation-based - these examples all highlight the utility of modeling to formalize assumptions and generate testable predictions. A central element of this framework is the iterative use of models and experiments, specifically: matching experimental designs to the models, revising models based on mismatches with experimental data, and validating critical model assumptions and predictions with experiments. We advocate for continued use of this interplay between models and experiments to advance biological discovery.
Chemical synapses between axons and dendrites mediate much of the brain’s intercellular communication. Here we describe a new kind of synapse – the axo-ciliary synapse - between axons and primary cilia. By employing enhanced focused ion beam – scanning electron microscopy on samples with optimally preserved ultrastructure, we discovered synapses between the serotonergic axons arising from the brainstem, and the primary cilia of hippocampal CA1 pyramidal neurons. Functionally, these cilia are enriched in a ciliary-restricted serotonin receptor, 5-hydroxytryptamine receptor 6 (HTR6), whose mutation is associated with learning and memory defects. Using a newly developed cilia-targeted serotonin sensor, we show that optogenetic stimulation of serotonergic axons results in serotonin release onto cilia. Ciliary HTR6 stimulation activates a non-canonical Gαq/11-RhoA pathway. Ablation of this pathway results in nuclear actin and chromatin accessibility changes in CA1 pyramidal neurons. Axo-ciliary synapses serve as a distinct mechanism for neuromodulators to program neuron transcription through privileged access to the nuclear compartment.
Electron cryo-microscopy (cryo-EM) can generate high-resolution views of cells with faithful preservation of molecular structure. In situ cryo-EM, therefore, has enormous potential to reveal the atomic details of biological processes in their native context. However, in practice, the utility of in situ cryo-EM is limited by the difficulty of reliably locating and confidently identifying molecular targets (particles) and their conformational states in the crowded cellular environment. We recently showed that 2DTM, a fine-grained template-based search applied to cryo-EM micrographs, can localize particles in two-dimensional views of cells with high precision. Here we demonstrate that the signal-to-noise ratio (SNR) observed with 2DTM can be used to differentiate related complexes in focused ion beam (FIB)-milled cell sections. We apply this method in two contexts to locate and classify related intermediate states of 60S ribosome biogenesis in the Saccharomyces cerevisiae cell nucleus. In the first, we separate the nuclear pre-60S population from the cytoplasmic mature 60S population, using the subcellular localization to validate assignment. In the second, we show that relative 2DTM SNRs can be used to separate mixed populations of nuclear pre-60S that are not visually separable. We use a maximum likelihood approach to define the probability of each particle belonging to each class, thereby establishing a statistic to describe the confidence of our classification. Without the need to generate 3D reconstructions, 2DTM can be applied even when only a few target particles exist in a cell.
Molecular profiles of neurons influence neural development and function but bridging the gap between genes, circuits, and behavior has been very difficult. Here we used single cell RNAseq to generate a complete gene expression atlas of the Drosophila larval central nervous system composed of 131,077 single cells across three developmental stages (1 h, 24 h and 48 h after hatching). We identify 67 distinct cell clusters based on the patterns of gene expression. These include 31 functional mature larval neuron clusters, 1 ring gland cluster, 8 glial clusters, 6 neural precursor clusters, and 13 developing immature adult neuron clusters. Some clusters are present across all stages of larval development, while others are stage specific (such as developing adult neurons). We identify genes that are differentially expressed in each cluster, as well as genes that are differentially expressed at distinct stages of larval life. These differentially expressed genes provide promising candidates for regulating the function of specific neuronal and glial types in the larval nervous system, or the specification and differentiation of adult neurons. The cell transcriptome Atlas of the Drosophila larval nervous system is a valuable resource for developmental biology and systems neuroscience and provides a basis for elucidating how genes regulate neural development and function.
Hereditary spastic paraplegias (HSPs) comprise a large group of inherited neurologic disorders affecting the longest corticospinal axons (SPG1-86 plus others), with shared manifestations of lower extremity spasticity and gait impairment. Common autosomal dominant HSPs are caused by mutations in genes encoding the microtubule-severing ATPase spastin (SPAST; SPG4), the membrane-bound GTPase atlastin-1 (ATL1; SPG3A) and the reticulon-like, microtubule-binding protein REEP1 (REEP1; SPG31). These proteins bind one another and function in shaping the tubular endoplasmic reticulum (ER) network. Typically, mouse models of HSPs have mild, later onset phenotypes, possibly reflecting far shorter lengths of their corticospinal axons relative to humans. Here, we have generated a robust, double mutant mouse model of HSP in which atlastin-1 is genetically modified with a K80A knock-in (KI) missense change that abolishes its GTPase activity, whereas its binding partner Reep1 is knocked out. Atl1KI/KI/Reep1-/- mice exhibit early onset and rapidly progressive declines in several motor function tests. Also, ER in mutant corticospinal axons dramatically expands transversely and periodically in a mutation dosage-dependent manner to create a ladder-like appearance, on the basis of reconstructions of focused ion beam-scanning electron microscopy datasets using machine learning-based auto-segmentation. In lockstep with changes in ER morphology, axonal mitochondria are fragmented and proportions of hypophosphorylated neurofilament H and M subunits are dramatically increased in Atl1KI/KI/Reep1-/- spinal cord. Co-occurrence of these findings links ER morphology changes to alterations in mitochondrial morphology and cytoskeletal organization. Atl1KI/KI/Reep1-/- mice represent an early onset rodent HSP model with robust behavioral and cellular readouts for testing novel therapies.
The detection of visual motion enables sophisticated animal navigation, and studies on flies have provided profound insights into the cellular and circuit bases of this neural computation. The fly's directionally selective T4 and T5 neurons encode ON and OFF motion, respectively. Their axons terminate in one of the four retinotopic layers in the lobula plate, where each layer encodes one of the four directions of motion. Although the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here, we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to the known cell types. Our reconstruction explains how the ON- and OFF-motion pathways converge. T4 and T5 cells that project to the same layer connect to common synaptic partners and comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.