1 Department Ophthalmology, Moran Eye Center, University of Utah, Salt Lake City, Utah, United States of America, 2 Sorenson Media, Salt Lake City, Utah, United States of America, 3 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, United States of America, 4 The Boulder Laboratory For 3-D Electron Microscopy of Cells, University of Colorado, Boulder, Colorado, United States of America, 5 Department Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States of America
Circuitry mapping of metazoan neural systems is difficult because canonical neural regions (regions containing one or more copies of all components) are large, regional borders are uncertain, neuronal diversity is high, and potential network topologies so numerous that only anatomical ground truth can resolve them. Complete mapping of a specific network requires synaptic resolution, canonical region coverage, and robust neuronal classification. Though transmission electron microscopy (TEM) remains the optimal tool for network mapping, the process of building large serial section TEM (ssTEM) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics. Moreover, most molecular neuronal class markers are poorly compatible with optimal TEM imaging. Our objective was to build a complete framework for ultrastructural circuitry mapping. This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking, automated slice-to-slice image registration, and gigabyte-scale image browsing for volume annotation. Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools (SerialEM), mosaicking and registration (ir-tools), and large slice viewers (MosaicBuilder, Viking) can be used to manage terabyte-scale volumes. These methods enable large-scale connectivity analyses of new and legacy data. In well-posed tasks (e.g., complete network mapping in retina), terabyte-scale image volumes that previously would require decades of assembly can now be completed in months. Perhaps more importantly, the fusion of molecular profiling, image acquisition by SerialEM, ir-tools volume assembly, and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics. Finally, this framework provides a mechanism for parallelization of ssTEM imaging, volume assembly, and data analysis across an international user base, enhancing the productivity of a large cohort of electron microscopists.
Funding. National Eye Institute R01 EY02576, R01 EY015128, P01 EY014800 (REM); support from the Cal and JeNeal Hatch Presidential Endowed Chair (REM); an unrestricted grant from Research to Prevent Blindness to the Moran Eye Center; a Research to Prevent Blindness Career Development Award (BWJ); National Institute of Biomedical Imaging and Bioengineering EB005832 (TT). TT would like to acknowledge the support of the Utah Science Technology and Research Initiative (USTAR). DM's work was supported by grant number P41RR00592 to A.H. Hoenger from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). This paper's contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests. Robert E. Marc is a principal of Signature Immunologics. All other authors declare no other competing interests.
Academic Editor: Kristen M. Harris, University of Texas, United States of America
Citation: Anderson JR, Jones BW, Yang JH, Shaw MV, Watt CB, et al. (2009) A Computational Framework for Ultrastructural Mapping of Neural Circuitry. PLoS Biol 7(3): e1000074 doi:10.1371/journal.pbio.1000074
Received: August 21, 2008; Accepted: February 17, 2009; Published: March 31, 2009
Copyright: © 2009 Anderson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abbreviations: AC, amacrine cell; AGB, 1-amino-4-guanidobutane; BC, bipolar cell; CMP, computational molecular phenotyping; CN, complete network; GC, ganglion cell; IgG, immunoglobulin; LM, light microscopy; rgb, red, green, blue image mapping; ssLM, serial section light microscopy; ssTEM, serial section transmission electron microscopy; TEM, transmission electron microscopy
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