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41 Janelia Publications

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    03/20/24 | Interactive simulation and visualization of point spread functions in single molecule imaging.
    Magdalena C. Schneider , Fabian Hinterer , Alexander Jesacher , Gerhard J. Schütz
    Optics Communications. 2024 Mar 20:. doi: 10.1016/j.optcom.2024.130463

    The point spread function (PSF) is fundamental to any type of microscopy, most importantly so for single-molecule localization techniques, where the exact PSF shape is crucial for precise molecule localization at the nanoscale. Optical aberrations and fixed fluorophore dipoles often result in non-isotropic and distorted PSFs, impairing and biasing conventional fitting approaches. Further, PSF shapes are deliberately modified in PSF engineering approaches for providing improved sensitivity, e.g., for 3D localization or determination of dipole orientation. As this can lead to highly complex PSF shapes, a tool for visualizing expected PSFs would facilitate the interpretation of obtained data and the design of experimental approaches. To this end, we introduce a comprehensive and accessible computer application that allows for the simulation of realistic PSFs based on the full vectorial PSF model. Our tool incorporates a wide range of microscope and fluorophore parameters, including orientationally constrained fluorophores, as well as custom aberrations, transmission and phase masks, thus enabling an accurate representation of various imaging conditions. An additional feature is the simulation of crowded molecular environments with overlapping PSFs. Further, our app directly provides the Cramér–Rao bound for assessing the best achievable localization precision under given conditions. Finally, our software allows for the fitting of custom aberrations directly from experimental data, as well as the generation of a large dataset with randomized simulation parameters, effectively bridging the gap between simulated and experimental scenarios, and enhancing experimental design and result validation.

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    01/04/24 | Petascale pipeline for precise alignment of images from serial section electron microscopy.
    Popovych S, Macrina T, Kemnitz N, Castro M, Nehoran B, Jia Z, Bae JA, Mitchell E, Mu S, Trautman ET, Saalfeld S, Li K, Seung HS
    Nature Communications. 2024 Jan 04;15(1):289. doi: 10.1038/s41467-023-44354-0

    The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

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    09/01/23 | OME-Zarr: a cloud-optimized bioimaging file format with international community support.
    Josh Moore , Daniela Basurto-Lozada , Sébastien Besson , John Bogovic , Eva M. Brown , Jean-Marie Burel , Gustavo de Medeiros , Erin E. Diel , David Gault , Satrajit S. Ghosh , Ilan Gold , Yaroslav O. Halchenko , Matthew Hartley , Dave Horsfall , Mark S. Keller , Mark Kittisopikul , Gabor Kovacs , Aybüke Küpcü Yoldaş , Albane le Tournoulx de la Villegeorges , Tong Li , Prisca Liberali , Melissa Linkert , Dominik Lindner , Joel Lüthi , Jeremy Maitin-Shepard , Trevor Manz , Matthew McCormick , Khaled Mohamed , William Moore , Bugra Özdemir , Constantin Pape , Lucas Pelkmans , Martin Prete , Tobias Pietzsch , Stephan Preibisch , Norman Rzepka , David R. Stirling , Jonathan Striebel , Christian Tischer , Daniel Toloudis , Petr Walczysko , Alan M. Watson , Frances Wong , Kevin A. Yamauchi , Omer Bayraktar , Muzlifah Haniffa , Stephan Saalfeld , Jason R. Swedlow
    Histochemistry and Cell Biology. 2023 Feb 25;160(3):223-251. doi: 10.1007/s00418-023-02209-1

    A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the format itself – OME-Zarr – along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain — the file format that underlies so many personal, institutional, and global data management and analysis tasks.

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    07/22/23 | Towards Generalizable Organelle Segmentation in Volume Electron Microscopy.
    Heinrich L, Patton W, Bennett D, Ackerman D, Park G, Bogovic JA, Eckstein N, Petruncio A, Clements J, Pang S, Shan Xu C, Funke J, Korff W, Hess H, Lippincott-Schwartz J, Saalfeld S, Weigel A, CellMap Project Team
    Microscopy and Microanalysis. 2023 Jul 22;29(Supplement_1):975. doi: 10.1093/micmic/ozad067.487
    06/16/23 | Architecture and dynamics of a desmosome-endoplasmic reticulum complex.
    Bharathan NK, Giang W, Hoffman CL, Aaron JS, Khuon S, Chew T, Preibisch S, Trautman ET, Heinrich L, Bogovic J, Bennett D, Ackerman D, Park W, Petruncio A, Weigel AV, Saalfeld S, COSEM Project Team , Wayne Vogl A, Stahley SN, Kowalczyk AP
    Nature Cell Biology. 2023 Jun 16;25(6):823-835. doi: 10.1038/s41556-023-01154-4

    The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometre proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.

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    06/06/23 | A Connectome of the Male Drosophila Ventral Nerve Cord
    Shin-ya Takemura , Kenneth J Hayworth , Gary B Huang , Michal Januszewski , Zhiyuan Lu , Elizabeth C Marin , Stephan Preibisch , C Shan Xu , John Bogovic , Andrew S Champion , Han S J Cheong , Marta Costa , Katharina Eichler , William Katz , Christopher Knecht , Feng Li , Billy J Morris , Christopher Ordish , Patricia K Rivlin , Philipp Schlegel , Kazunori Shinomiya , Tomke Sturner , Ting Zhao , Griffin Badalamente , Dennis Bailey , Paul Brooks , Brandon S Canino , Jody Clements , Michael Cook , Octave Duclos , Christopher R Dunne , Kelli Fairbanks , Siqi Fang , Samantha Finley-May , Audrey Francis , Reed George , Marina Gkantia , Kyle Harrington , Gary Patrick Hopkins , Joseph Hsu , Philip M Hubbard , Alexandre Javier , Dagmar Kainmueller , Wyatt Korff , Julie Kovalyak , Dominik Krzeminski , Shirley A Lauchie , Alanna Lohff , Charli Maldonado , Emily A Manley , Caroline Mooney , Erika Neace , Matthew Nichols , Omotara Ogundeyi , Nneoma Okeoma , Tyler Paterson , Elliott Phillips , Emily M Phillips , Caitlin Ribeiro , Sean M Ryan , Jon Thomson Rymer , Anne K Scott , Ashley L Scott , David Shepherd , Aya Shinomiya , Claire Smith , Alia Suleiman , Satoko Takemura , Iris Talebi , Imaan F M Tamimi , Eric T Trautman , Lowell Umayam , John J Walsh , Tansy Yang , Gerald M Rubin , Louis K Scheffer , Jan Funke , Stephan Saalfeld , Harald F Hess , Stephen M Plaza , Gwyneth M Card , Gregory S X E Jefferis , Stuart Berg
    bioRxiv. 2023 Jun 06:. doi: 10.1101/2023.06.05.543757

    Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.

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    05/31/23 | Comparative connectomics and escape behavior in larvae of closely related Drosophila species.
    Zhu J, Boivin J, Pang S, Xu CS, Lu Z, Saalfeld S, Hess HF, Ohyama T
    Current Biology. 2023 May 31:. doi: 10.1016/j.cub.2023.05.043

    Evolution has generated an enormous variety of morphological, physiological, and behavioral traits in animals. How do behaviors evolve in different directions in species equipped with similar neurons and molecular components? Here we adopted a comparative approach to investigate the similarities and differences of escape behaviors in response to noxious stimuli and their underlying neural circuits between closely related drosophilid species. Drosophilids show a wide range of escape behaviors in response to noxious cues, including escape crawling, stopping, head casting, and rolling. Here we find that D. santomea, compared with its close relative D. melanogaster, shows a higher probability of rolling in response to noxious stimulation. To assess whether this behavioral difference could be attributed to differences in neural circuitry, we generated focused ion beam-scanning electron microscope volumes of the ventral nerve cord of D. santomea to reconstruct the downstream partners of mdIV, a nociceptive sensory neuron in D. melanogaster. Along with partner interneurons of mdVI (including Basin-2, a multisensory integration neuron necessary for rolling) previously identified in D. melanogaster, we identified two additional partners of mdVI in D. santomea. Finally, we showed that joint activation of one of the partners (Basin-1) and a common partner (Basin-2) in D. melanogaster increased rolling probability, suggesting that the high rolling probability in D. santomea is mediated by the additional activation of Basin-1 by mdIV. These results provide a plausible mechanistic explanation for how closely related species exhibit quantitative differences in the likelihood of expressing the same behavior.

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    02/01/23 | Local shape descriptors for neuron segmentation.
    Sheridan A, Nguyen TM, Deb D, Lee WA, Saalfeld S, Turaga SC, Manor U, Funke J
    Nature Methods. 2023 Feb 01;20(2):295-303. doi: 10.1038/s41592-022-01711-z

    We present an auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of local shape descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a study comparing several existing methods across various specimen, imaging techniques, and resolutions, auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinity-based segmentation methods to be on par with the current state of the art for neuron segmentation (flood-filling networks), while being two orders of magnitudes more efficient-a critical requirement for the processing of future petabyte-sized datasets.

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    10/26/22 | Rapid reconstruction of neural circuits using tissue expansion and lattice light sheet microscopy
    Joshua L. Lillvis , Hideo Otsuna , Xiaoyu Ding , Igor Pisarev , Takashi Kawase , Jennifer Colonell , Konrad Rokicki , Cristian Goina , Ruixuan Gao , Amy Hu , Kaiyu Wang , John Bogovic , Daniel E. Milkie , Edward S. Boyden , Stephan Saalfeld , Paul W. Tillberg , Barry J. Dickson
    eLife. 2022 Oct 26:. doi: 10.7554/eLife.81248

    Electron microscopy (EM) allows for the reconstruction of dense neuronal connectomes but suffers from low throughput, limiting its application to small numbers of reference specimens. We developed a protocol and analysis pipeline using tissue expansion and lattice light-sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many samples with single synapse resolution and molecular contrast. We validate this approach in Drosophila, demonstrating that it yields synaptic counts similar to those obtained by EM, can be used to compare counts across sex and experience, and to correlate structural connectivity with functional connectivity. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

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    08/23/22 | Transverse endoplasmic reticulum expansion in hereditary spastic paraplegia corticospinal axons.
    Zhu P, Hung H, Batchenkova N, Nixon-Abell J, Henderson J, Zheng P, Renvoisé B, Pang S, Xu CS, Saalfeld S, Funke J, Xie Y, Svara F, Hess HF, Blackstone C
    Human Molecular Genetics. 2022 Aug 23;31(16):2779-2795. doi: 10.1093/hmg/ddac072

    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.

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