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18 Janelia Publications

Showing 1-10 of 18 results
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    09/29/22 | De novo protein identification in mammalian sperm using high-resolution in situ cryo-electron tomography
    Zhen Chen , Momoko Shiozaki , Kelsey M. Haas , Shumei Zhao , Caiying Guo , Benjamin J. Polacco , Zhiheng Yu , Nevan J. Krogan , Robyn M. Kaake , Ronald D. Vale , David A. Agard
    bioRxiv. 2022 Sep 29:. doi: 10.1101/2022.09.28.510016

    Understanding molecular mechanisms of cellular pathways requires knowledge of the identities of participating proteins, their cellular localization and their 3D structures. Contemporary workflows typically require multiple techniques to identify target proteins, track their localization using fluorescence microscopy, followed by in vitro structure determination. To identify mammal-specific sperm proteins and understand their functions, we developed a visual proteomics workflow to directly address these challenges. Our in situ cryo-electron tomography and subtomogram averaging provided 6.0 Å resolution reconstructions of axonemal microtubules and their associated proteins. The well-resolved secondary and tertiary structures allowed us to computationally match, in an unbiased manner, novel densities in our 3D reconstruction maps with 21,615 AlphaFold2-predicted protein models of the mouse proteome. We identified Tektin 5, CCDC105 and SPACA9 as novel microtubule inner proteins that form an extensive network crosslinking the lumen of microtubule and existing proteins. Additional biochemical and mass spectrometry analyses helped validate potential candidates. The novel axonemal sperm structures identified by this approach form an extensive interaction network within the lumen of microtubules, suggesting they have a role in the mechanical and elastic properties of the microtubule filaments required for the vigorous beating motions of flagella.

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    09/27/22 | A scalable implementation of the recursive least-squares algorithm for training spiking neural networks
    Benjamin J. Arthur , Christopher M. Kim , Susu Chen , Stephan Preibisch , Ran Darshan
    bioRxiv. 2022 Sep 27:. doi: 10.1101/2022.09.26.509578

    Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a prominent tool to study computations in the brain. With an increasing size and complexity of neural recordings, there is a need for fast algorithms that can scale to large datasets. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation allows training networks to reproduce neural activity of an order of millions neurons at order of magnitude times faster than the CPU implementation. We demonstrate this by applying our algorithm to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables efficient training of large-scale spiking models, thus allowing for in-silico study of the dynamics and connectivity underlying multi-area computations.

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    09/20/22 | A proliferative to invasive switch is mediated by srGAP1 downregulation through the activation of TGF-β2 signaling.
    Mondal C, Gacha-Garay MJ, Larkin KA, Adikes RC, Di Martino JS, Chien C, Fraser M, Eni-Aganga I, Agullo-Pascual E, Cialowicz K, Ozbek U, Naba A, Gaitas A, Fu T, Upadhyayula S, Betzig E, Matus DQ, Martin BL, Bravo-Cordero JJ
    Cell Reports. 2022 Sep 20;40(12):111358. doi: 10.1016/j.celrep.2022.111358

    Many breast cancer (BC) patients suffer from complications of metastatic disease. To form metastases, cancer cells must become migratory and coordinate both invasive and proliferative programs at distant organs. Here, we identify srGAP1 as a regulator of a proliferative-to-invasive switch in BC cells. High-resolution light-sheet microscopy demonstrates that BC cells can form actin-rich protrusions during extravasation. srGAP1 cells display a motile and invasive phenotype that facilitates their extravasation from blood vessels, as shown in zebrafish and mouse models, while attenuating tumor growth. Interestingly, a population of srGAP1 cells remain as solitary disseminated tumor cells in the lungs of mice bearing BC tumors. Overall, srGAP1 cells have increased Smad2 activation and TGF-β2 secretion, resulting in increased invasion and p27 levels to sustain quiescence. These findings identify srGAP1 as a mediator of a proliferative to invasive phenotypic switch in BC cells in vivo through a TGF-β2-mediated signaling axis.

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    07/29/20 | Dense reconstruction of elongated cell lineages: overcoming suboptimum lineage encoding and sparse cell sampling
    Sugino K, Miyares RL, Espinosa-Medina I, Chen H, Potter CJ, Lee T
    bioRxiv. 07/2020:. doi: 10.1101/2020.07.27.223321

    Acquiring both lineage and cell-type information during brain development could elucidate transcriptional programs underling neuronal diversification. This is now feasible with single-cell RNA-seq combined with CRISPR-based lineage tracing, which generates genetic barcodes with cumulative CRISPR edits. This technique has not yet been optimized to deliver high-resolution lineage reconstruction of protracted lineages. Drosophila neuronal lineages are an ideal model to consider, as multiple lineages have been morphologically mapped at single-cell resolution. Here we find the parameter ranges required to encode a representative neuronal lineage emanating from 100 stem cell divisions. We derive the optimum editing rate to be inversely proportional to lineage depth, enabling encoding to persist across lineage progression. Further, we experimentally determine the editing rates of a Cas9-deaminase in cycling neural stem cells, finding near ideal rates to map elongated Drosophila neuronal lineages. Moreover, we propose and evaluate strategies to separate recurring cell-types for lineage reconstruction. Finally, we present a simple method to combine multiple experiments, which permits dense reconstruction of protracted cell lineages despite suboptimum lineage encoding and sparse cell sampling.Competing Interest StatementThe authors have declared no competing interest.

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    10/28/21 | TEMPO: A system to sequentially label and genetically manipulate vertebrate cell lineages
    Espinosa-Medina I, Feliciano D, Belmonte-Mateos C, Garcia-Marques J, Foster B, Miyares RL, Pujades C, Koyama M, Lee T
    bioRxiv. 10/2021:. doi: 10.1101/2021.10.27.466134

    During development, regulatory factors appear in a precise order to determine cell fates over time. To investigate complex tissue development, one should not just label cell lineages but further visualize and manipulate cells with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labelling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation/inactivation of reporters/effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.One-Sentence Summary Gaining sequential genetic access to vertebrate cell lineages.Competing Interest StatementThe authors have declared no competing interest.

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    04/14/19 | Theoretical modeling on CRISPR-coded cell lineages: efficient encoding and optimal reconstruction
    Sugino K, Garcia-Marques J, Espinosa-Medina I, Lee T
    bioRxiv. 04/2019:. doi: 10.1101/538488

    Delineating cell lineages is a prerequisite for interrogating the genesis of cell types. CRISPR/Cas9 can edit genomic sequence during development which enables to trace cell lineages. Recent studies have demonstrated the feasibility of this idea. However, the optimality of the encoding or reconstruction processes has not been adequately addressed. Here, we surveyed a multitude of reconstruction algorithms and found hierarchical clustering, with a metric based on the number of shared Cas9 edits, delivers the best reconstruction. However, the trackable depth is ultimately limited by the number of available coding units that typically decrease exponentially across cell generations. To overcome this limit, we established two strategies that better sustain the coding capacity. One involves controlling target availability via use of parallel gRNA cascades, whereas the other strategy exploits adjustable Cas9/gRNA editing rates. In summary, we provide a theoretical basis in understanding, designing, and analyzing robust CRISPR barcodes for dense reconstruction of protracted cell lineages.

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    09/19/22 | Structural Diversity within the Endoplasmic Reticulum-From the Microscale to the Nanoscale.
    Obara CJ, Moore AS, Lippincott-Schwartz J
    Cold Spring Harbor Perspectives in Biology. 2022 Sep 19:. doi: 10.1101/cshperspect.a041259

    The endoplasmic reticulum (ER) is a continuous, highly dynamic membrane compartment that is crucial for numerous basic cellular functions. The ER stretches from the nuclear envelope to the outer periphery of all living eukaryotic cells. This ubiquitous organelle shows remarkable structural complexity, adopting a range of shapes, curvatures, and length scales. Canonically, the ER is thought to be composed of two simple membrane elements: sheets and tubules. However, recent advances in superresolution light microscopy and three-dimensional electron microscopy have revealed an astounding diversity of nanoscale ER structures, greatly expanding our view of ER organization. In this review, we describe these diverse ER structures, focusing on what is known of their regulation and associated functions in mammalian cells.

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    09/19/22 | The evolutionary dynamics of extrachromosomal DNA in human cancers.
    Lange JT, Rose JC, Chen CY, Pichugin Y, Xie L, Tang J, Hung KL, Yost KE, Shi Q, Erb ML, Rajkumar U, Wu S, Taschner-Mandl S, Bernkopf M, Swanton C, Liu Z, Huang W, Chang HY, Bafna V, Henssen AG, Werner B, Mischel PS
    Nature Genetics. 2022 Sep 19:. doi: 10.1038/s41588-022-01177-x

    Oncogene amplification on extrachromosomal DNA (ecDNA) is a common event, driving aggressive tumor growth, drug resistance and shorter survival. Currently, the impact of nonchromosomal oncogene inheritance-random identity by descent-is poorly understood. Also unclear is the impact of ecDNA on somatic variation and selection. Here integrating theoretical models of random segregation, unbiased image analysis, CRISPR-based ecDNA tagging with live-cell imaging and CRISPR-C, we demonstrate that random ecDNA inheritance results in extensive intratumoral ecDNA copy number heterogeneity and rapid adaptation to metabolic stress and targeted treatment. Observed ecDNAs benefit host cell survival or growth and can change within a single cell cycle. ecDNA inheritance can predict, a priori, some of the aggressive features of ecDNA-containing cancers. These properties are facilitated by the ability of ecDNA to rapidly adapt genomes in a way that is not possible through chromosomal oncogene amplification. These results show how the nonchromosomal random inheritance pattern of ecDNA contributes to poor outcomes for patients with cancer.

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    09/22/22 | Tracking by Weakly-Supervised Learning and Graph Optimization for Whole-Embryo C. elegans lineages
    Wang L, Dou Q, Fletcher PT, Speidel S, Li S
    International Conference on Medical Image Computing and Computer-Assisted Intervention. 2022 Sep 16:. doi: 10.1007/978-3-031-16440-8

    Tracking all nuclei of an embryo in noisy and dense fluorescence microscopy data is a challenging task. We build upon a recent method for nuclei tracking that combines weakly-supervised learning from a small set of nuclei center point annotations with an integer linear program (ILP) for optimal cell lineage extraction. Our work specifically addresses the following challenging properties of C. elegans embryo recordings: (1) Many cell divisions as compared to benchmark recordings of other organisms, and (2) the presence of polar bodies that are easily mistaken as cell nuclei. To cope with (1), we devise and incorporate a learnt cell division detector. To cope with (2), we employ a learnt polar body detector. We further propose automated ILP weights tuning via a structured SVM, alleviating the need for tedious manual set-up of a respective grid search.

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    07/11/22 | FourierNets enable the design of highly non-local optical encoders for computational imaging
    Deb D, Jiao Z, Sims R, Chen AB, Broxton M, Ahrens MB, Podgorski K, Turaga SC


    Differentiable simulations of optical systems can be combined with deep learning-based reconstruction networks to enable high performance computational imaging via end-to-end (E2E) optimization of both the optical encoder and the deep decoder. This has enabled imaging applications such as 3D localization microscopy, depth estimation, and lensless photography via the optimization of local optical encoders. More challenging computational imaging applications, such as 3D snapshot microscopy which compresses 3D volumes into single 2D images, require a highly non-local optical encoder. We show that existing deep network decoders have a locality bias which prevents the optimization of such highly non-local optical encoders. We address this with a decoder based on a shallow neural network architecture using global kernel Fourier convolutional neural networks (FourierNets). We show that FourierNets surpass existing deep network based decoders at reconstructing photographs captured by the highly non-local DiffuserCam optical encoder. Further, we show that FourierNets enable E2E optimization of highly non-local optical encoders for 3D snapshot microscopy. By combining FourierNets with a large-scale multi-GPU differentiable optical simulation, we are able to optimize non-local optical encoders 170

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