Anterograde Neuronal Circuit Tracers Derived from Herpes Simplex Virus 1: Development, Application, and Perspectives
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Automated Sorting of Neuronal Trees in Fluorescent Images of Neuronal
www.nature.com/scientificreports OPEN Automated sorting of neuronal trees in fuorescent images of neuronal networks using Received: 29 August 2017 Accepted: 10 April 2018 NeuroTreeTracer Published: xx xx xxxx Cihan Kayasandik1, Pooran Negi1, Fernanda Laezza2, Manos Papadakis1 & Demetrio Labate 1 Fluorescence confocal microscopy has become increasingly more important in neuroscience due to its applications in image-based screening and profling of neurons. Multispectral confocal imaging is useful to simultaneously probe for distribution of multiple analytes over networks of neurons. However, current automated image analysis algorithms are not designed to extract single-neuron arbors in images where neurons are not separated, hampering the ability map fuorescence signals at the single cell level. To overcome this limitation, we introduce NeuroTreeTracer – a novel image processing framework aimed at automatically extracting and sorting single-neuron traces in fuorescent images of multicellular neuronal networks. This method applies directional multiscale flters for automated segmentation of neurons and soma detection, and includes a novel tracing routine that sorts neuronal trees in the image by resolving network connectivity even when neurites appear to intersect. By extracting each neuronal tree, NeuroTreetracer enables to automatically quantify the spatial distribution of analytes of interest in the subcellular compartments of individual neurons. This software is released open-source and freely available with the goal to facilitate applications in neuron screening and profling. Neuronal reconstruction is critical in a variety of neurobiological studies. During the last two decades, a large number of algorithms and sofware toolkits were developed aiming at providing digital reconstruction of neurons from images acquired using bright feld or fuorescent microscopy1. -
Nadder: a Scale-Space Approach for the 3D Analysis of Neuronal Traces
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.01.127035; this version posted December 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. nAdder: A scale-space approach for the 3D analysis of neuronal traces Minh Son Phan1, Katherine Matho2, Emmanuel Beaurepaire1, Jean Livet2, and Anatole Chessel1 1Laboratory for Optics and Biosciences, CNRS, INSERM, Ecole Polytechnique, IP Paris, Palaiseau, France 2Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012 Paris, France December 4, 2020 1 ABSTRACT 2 Tridimensional microscopy and algorithms for automated segmentation and tracing are revolutionizing 3 neuroscience through the generation of growing libraries of neuron reconstructions. Innovative 4 computational methods are needed to analyze these neural traces. In particular, means to analyse the 5 geometric properties of traced neurites along their trajectory have been lacking. Here, we propose 6 a local tridimensional (3D) scale metric derived from differential geometry, which is the distance 7 in micrometers along which a curve is fully 3D as opposed to being embedded in a 2D plane or 1D 8 line. We apply this metric to various neuronal traces ranging from single neurons to whole brain data. 9 By providing a local readout of the geometric complexity, it offers a new mean of describing and 10 comparing axonal and dendritic arbors from individual neurons or the behavior of axonal projections 11 in different brain regions. -
Automated Sorting of Neuronal Trees in Fluorescent Images of Neuronal
Automated sorting of neuronal trees in fluorescent images of neuronal networks using NeuroTreeTracer Cihan Kayasandik1,+, Pooran Negi1,+, Fernanda Laezza2, Manos Papadakis1, and Demetrio Labate1,* 1University of Houston, Department of Mathematics, Houston, Texas, United States of America 2University of Texas Medical Branch, Department of Pharmacology and Toxicology, Galveston, Texas, United States of America *corresponding author: [email protected] +these authors contributed equally to this work ABSTRACT Fluorescence confocal microscopy has become increasingly more important in neuroscience due to its applications in image- based screening and profiling of neurons. Multispectral confocal imaging is useful to simultaneously probe for distribution of multiple analytes over networks of neurons. However, current automated image analysis algorithms are not designed to extract single-neuron arbors in images where neurons are not separated, hampering the ability map fluorescence signals at the single cell level. To overcome this limitation, we introduce NeuroTreeTracer – a novel image processing framework aimed at automatically extracting and sorting single-neuron traces in fluorescent images of multicellular neuronal networks. This method applies directional multiscale filters for automated segmentation of neurons and soma detection, and includes a novel tracing routine that sorts neuronal trees in the image by resolving network connectivity even when neurites appear to intersect. By extracting each neuronal tree, NeuroTreetracer enables to automatically -
Raav-Based Retrograde Trans-Synaptic Labeling, Expression and Perturbation
bioRxiv preprint doi: https://doi.org/10.1101/537928; this version posted February 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. rAAV-based retrograde trans-synaptic tracing retroLEAP: rAAV-based retrograde trans-synaptic labeling, expression and perturbation Janine K Reinert1,#,* & Ivo Sonntag1,#,*, Hannah Sonntag2, Rolf Sprengel2, Patric Pelzer1, 1 1 1 Sascha Lessle , Michaela Kaiser , Thomas Kuner 1 Department Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany 2 Max Planck Research Group at the Institute for Anatomy and Cell Biology, at Heidelberg University, Heidelberg, Germany #These authors contributed equally to this work * Correspondence: Janine K Reinert: [email protected] Ivo Sonntag: [email protected] 1 out of 11 bioRxiv preprint doi: https://doi.org/10.1101/537928; this version posted February 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. rAAV-based retrograde trans-synaptic tracing Abstract Identifying and manipulating synaptically connected neurons across brain regions remains a core challenge in understanding complex nervous systems. RetroLEAP is a novel approach for retrograde trans-synaptic Labelling, Expression And Perturbation. GFP-dependent recombinase (Flp-DOG) detects trans-synaptic transfer of GFP-tetanus toxin heavy chain fusion protein (GFP-TTC) and activates expression of any gene of interest in synaptically connected cells. RetroLEAP overcomes existing limitations, is non-toxic, highly flexible, efficient, sensitive and easy to implement. Keywords: trans-synaptic, tracing, TTC, Cre-dependent, GFP-dependent flippase. -
Methods to Investigate the Structure and Connectivity of the Nervous System
University of Massachusetts Medical School eScholarship@UMMS GSBS Student Publications Graduate School of Biomedical Sciences 2017-02-16 Methods to investigate the structure and connectivity of the nervous system Donghyung Lee California Institute of Technology Et al. Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/gsbs_sp Part of the Neuroscience and Neurobiology Commons Repository Citation Lee D, Huang T, De La Cruz A, Callejas A, Lois C. (2017). Methods to investigate the structure and connectivity of the nervous system. GSBS Student Publications. https://doi.org/10.1080/ 19336934.2017.1295189. Retrieved from https://escholarship.umassmed.edu/gsbs_sp/2000 Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in GSBS Student Publications by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. Fly ISSN: 1933-6934 (Print) 1933-6942 (Online) Journal homepage: http://www.tandfonline.com/loi/kfly20 Methods to investigate the structure and connectivity of the nervous system Donghyung Lee, Ting-Hao Huang, Aubrie De La Cruz, Antuca Callejas & Carlos Lois To cite this article: Donghyung Lee, Ting-Hao Huang, Aubrie De La Cruz, Antuca Callejas & Carlos Lois (2017): Methods to investigate the structure and connectivity of the nervous system, Fly, DOI: 10.1080/19336934.2017.1295189 To link to this article: http://dx.doi.org/10.1080/19336934.2017.1295189 © 2017 The Author(s). Published with license by Taylor & Francis© Donghyung Lee, Ting-Hao Huang, Aubrie De La Cruz, Antuca Callejas, and Carlos Lois Accepted author version posted online: 16 Feb 2017. -
Slow Axonal Transport and Presynaptic Targeting of Clathrin Packets
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.20.958140; this version posted February 20, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Slow Axonal Transport and Presynaptic Targeting of Clathrin Packets Archan Ganguly 1,2, Florian Wernert3, Sébastien Phan 2,4, Daniela Boassa 2,4, Utpal Das 1,2, Rohan Sharma 1,2, Ghislaine Caillol 3, Xuemei Han 5, John R. Yates III 5, Mark H. Ellisman 2,4, Christophe Leterrier 3, and Subhojit Roy 1,2 * 1 Department of Pathology, University of California, San Diego, La Jolla, CA 2 Department of Neurosciences, University of California, San Diego, La Jolla, CA 3 Aix Marseille Université, CNRS, INP UMR7051, NeuroCyto, Marseille, France 4 National Center for Microscopy and Imaging Research, University of California, San Diego, La Jolla, CA 5 Department of Cell Biology, The Scripps Research Institute, La Jolla, CA * Correspondence: [email protected] SUMMARY Clathrin has established roles in endocytosis, with clathrin-cages enclosing membrane infoldings, followed by rapid disassembly and reuse of clathrin-monomers. In neurons, clathrin synthesized in cell- bodies is conveyed via slow axonal transport – enriching at presynapses – however, mechanisms underlying transport/targeting are unknown, and its role at synapses is debated. Combining live- imaging, mass-spectrometry (MS), Apex-labeled EM-tomography and super-resolution, we found that unlike dendrites where clathrin assembles and disassembles as expected, axons contain stable ‘clathrin transport-packets’ that move intermittently with an anterograde bias, conveying endocytosis-related proteins. -
Extraction of Protein Profiles from Primary Neurons Using Active
Journal of Neuroscience Methods 225 (2014) 1–12 Contents lists available at ScienceDirect Journal of Neuroscience Methods jo urnal homepage: www.elsevier.com/locate/jneumeth Extraction of protein profiles from primary neurons using active ଝ contour models and wavelets a,∗ b a a Danny Misiak , Stefan Posch , Marcell Lederer , Claudia Reinke , a b Stefan Hüttelmaier , Birgit Möller a Institute of Molecular Medicine, Martin Luther University Halle-Wittenberg, Heinrich-Damerow-Str. 1, 06120 Halle, Germany b Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06099 Halle, Germany h i g h l i g h t s • Extraction of neuron areas using active contours with a new distance based energy. • Location of structural neuron parts by a wavelet based approach. • Automatic extraction of spatial and quantitative data about distributions of proteins. • Extraction of various morphological parameters, in a fully automated manner. • Extraction of a distinctive profile for the Zipcode binding protein (ZBP1/IGF2BP1). a r t i c l e i n f o a b s t r a c t Article history: The function of complex networks in the nervous system relies on the proper formation of neuronal Received 26 October 2013 contacts and their remodeling. To decipher the molecular mechanisms underlying these processes, it is Received in revised form essential to establish unbiased automated tools allowing the correlation of neurite morphology and the 18 December 2013 subcellular distribution of molecules by quantitative means. Accepted 19 December 2013 We developed NeuronAnalyzer2D, a plugin for ImageJ, which allows the extraction of neuronal cell morphologies from two dimensional high resolution images, and in particular their correlation with Keywords: protein profiles determined by indirect immunostaining of primary neurons. -
Cortical Organization: Neuroanatomical Approaches
Changes in characteristics Cortical organization: seen through phylogeny neuroanatomical Increase in the absolute and particularly approaches relative mass of the brain compared to body size Comparatively larger increase in telencephalic Study of neuronal circuitry structures particularly the cerebral cortex and microstructure Helen Barbas Expansion in number of radial units [email protected] http://www.bu.edu/neural/ Neuroinformatics Aug., 2009 From: Rakic 1 Evolution of the Nervous System Neoteny: prolongation of fetal growth How does a larger or reorganized brain come about? rate into postnatal times results in increase in the size of the human brain Environmental factors Internal factors – change in posture freedom of the hands movement of eyes from a lateral to central position EMERGENCE OF BINOCULAR VISION Crossing at the optic chiasm is complete in animals with small degree of binocular vision FREEDOM OF THE HANDS Direct projection to the pyramidal tract in animals with fine use of the hands 2 Distinct modes of radial migration: How did these changes come about in evolution? Inside-out: characterizes pattern in mammalian cortex By what mechanism? Outside-in: characterizes reptilian cortex Consequences of differential migration: differences in cortical thickness, synaptic interactions Factors contributing to the inside-out pattern reelin (glycoprotein) Addition of new cells to the mice deficient in reelin have inverted primate CNS cortical lamination cdk5 (cyclin-dependent protein kinase) mice lacking cdk5 or its activator p35 Example -
Axonal Transport and the Eye
Br J Ophthalmol: first published as 10.1136/bjo.60.8.547 on 1 August 1976. Downloaded from Brit. 7. Ophthal. (1976) 60, 547 Editorial: Axonal transport and the eye Since the earliest days of histology, it has been and proteins, and are predominantly found in the known that the neurons have a large amount of particulate fraction of nerve homogenates. The basophilic material in the cell body. More recently slower transported material is mainly soluble this has been shown to be due to masses of rough protein (McEwen and Grafstein, I968; Kidwai and endoplasmic reticulum which are responsible for a Ochs, I969; Sj6strand, 1970). Much of the former high rate of protein synthesis of neurons. Since the and more than 6o per cent of the latter is probably earliest days of the microscopy of living cells in neurotubular protein (tubulin), and the neurotubules vitro, particulate movement within these cells has are thought to play a major part in axonal transport been recognized, particularly in neurons (Nakai, (Schmitt and Samson, I968). The neurotubules I964). The last 30 years have seen the gradual have a similar structure to actin, and are linked to accumulation of the knowledge required to explain high-energy phosphate compounds. Myosin-like these two observations. In the last io years in proteins are also found in axoplasm. It is suggested particular, the development of radioactive tracer that moving material might in part roll along the techniques has revealed much information on the neurotubules, or that the neurotubules themselves movement of protein and other substances within might move by a mechanism involving myosin- axons, a process termed axonal transport (Barondes, guanosine triphosphate-neurotubule cross bonds I967). -
High-Resolution Data-Driven Model of the Mouse Connectome
RESEARCH High-resolution data-driven model of the mouse connectome Joseph E. Knox1,2, Kameron Decker Harris 2,3, Nile Graddis1, Jennifer D. Whitesell 1, Hongkui Zeng 1, Julie A. Harris1, Eric Shea-Brown 1,2, and Stefan Mihalas 1,2 1Allen Institute for Brain Science, Seattle, Washington, USA 2Applied Mathematics, University of Washington, Seattle, Washington, USA 3Computer Science and Engineering, University of Washington, Seattle, Washington, USA Keywords: Connectome, Whole-brain, Mouse an open access journal ABSTRACT Knowledge of mesoscopic brain connectivity is important for understanding inter- and intraregion information processing. Models of structural connectivity are typically constructed and analyzed with the assumption that regions are homogeneous. We instead use the Allen Mouse Brain Connectivity Atlas to construct a model of whole-brain connectivity at the scale of 100 µm voxels. The data consist of 428 anterograde tracing experiments in wild type C57BL/6J mice, mapping fluorescently labeled neuronal projections brain-wide. Inferring spatial connectivity with this dataset is underdetermined, since the approximately 2 × 105 source voxels outnumber the number of experiments. Citation: Knox, J. E., Harris, K. D., To address this issue, we assume that connection patterns and strengths vary smoothly Graddis, N., Whitesell, J. D., Zeng, H., Harris, J. A., Shea-Brown, E., & across major brain divisions. We model the connectivity at each voxel as a radial basis Mihalas, S. (2019). High-resolution data-driven model of the mouse kernel-weighted average of the projection patterns of nearby injections. The voxel model connectome. Network Neuroscience, outperforms a previous regional model in predicting held-out experiments and compared 3(1), 217–236. -
Hypothesis-Driven Structural Connectivity Analysis Supports Network Over Hierarchical Model of Brain Architecture
Hypothesis-driven structural connectivity analysis supports network over hierarchical model of brain architecture Richard H. Thompson and Larry W. Swanson1 Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089 Contributed by Larry W. Swanson, June 30, 2010 (sent for review May 14, 2010) The brain is usually described as hierarchically organized, although (9) and a massive input from the SUBv (10). Only two major an alternative network model has been proposed. To help distin- brainstem inputs were identified: the dorsal raphé (DR), the guish between these two fundamentally different structure-function presumptive source of ACBdmt serotonin (11), and the inter- hypotheses, we developed an experimental circuit-tracing strategy fascicular nucleus (IF), the presumptive source of ACBdmt do- that can be applied to any starting point in the nervous system and pamine (12) that is medial to the expected ventral tegmental area then systematically expanded, and applied it to a previously obscure (VTA) itself (13). Thus, the ACBdmt receives direct inputs from dorsomedial corner of the nucleus accumbens identified functionally three massively interconnected cerebral regions implicated in as a “hedonic hot spot.” A highly topographically organized set of stress and depression, as well as restricted brainstem sites pro- connections involving expected and unexpected gray matter regions viding dopaminergic and serotonergic terminals. was identified that prominently features regions associated with Only one ACBdmt axonal output was labeled with PHAL (Fig. appetite, stress, and clinical depression. These connections are 1A; the filled purple area is a representative injection site): a arranged as a longitudinal series of circuits (closed loops). Thus, the descending pathway through the medial forebrain bundle with two results do not support a rigidly hierarchical model of nervous system clear terminal fields. -
A Scale-Space Approach for 3D Neuronal Traces Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.01.127035; this version posted June 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A SCALE-SPACE APPROACH FOR 3D NEURONAL TRACES ANALYSIS Minh Son Phan1, Katherine Matho2, Jean Livet2, Emmanuel Beaurepaire1, and Anatole Chessel1 1Laboratory for Optics and Biosciences, CNRS, INSERM, Ecole Polytechnique, IP Paris, Palaiseau, France 2Sorbonne Université, Institut de la Vison, INSERM, CNRS, Paris, France June 1, 2020 ABSTRACT 1 The advent of large-scale microscopy along with advances in automated image analysis algorithms 2 is currently revolutionizing neuroscience. These approaches result in rapidly increasing libraries 3 of neuron reconstructions requiring innovative computational methods to draw biological insight 4 from. Here, we propose a framework from differential geometry based on scale-space representation 5 to extract a quantitative structural readout of neurite traces seen as tridimensional (3D) curves 6 within the anatomical space. We define and propose algorithms to compute a multiscale hierarchical 7 decomposition of traced neurites according to their intrinsic dimensionality, from which we deduce 8 a local 3D scale, i.e. the scale in microns at which the curve is fully 3D as opposed to being 9 embedded in a 2D plane or a 1D line. We applied our scale-space analysis to recently published 10 data including zebrafish whole brain traces to demonstrate the importance of the computed local 3D 11 scale for description and comparison at the single arbor levels and as a local spatialized information 12 characterizing axons populations at the whole brain level.