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      Nanobody immunostaining for correlated light and electron microscopy with preservation of ultrastructure

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          Abstract

          Morphological and molecular characteristics determine the function of biological tissues. Attempts to combine immunofluorescence and electron microscopy invariably compromise the quality of the ultrastructure of tissue sections. We developed NATIVE, a correlated light and electron microscopy approach that preserves ultrastructure while showing the locations of multiple molecular moieties even deep within tissues. This technique allowed the large-scale 3D reconstruction of a volume of mouse hippocampal CA3 tissue at nanometer resolution.

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          Directed evolution of APEX2 for electron microscopy and proteomics

          Stephanie Lam, Jeffrey D. Martell, Kimberli J. Kamer … (2014)
          APEX is an engineered peroxidase that functions both as an electron microscopy tag, and as a promiscuous labeling enzyme for live-cell proteomics. Because the limited sensitivity of APEX precludes applications requiring low APEX expression, we used yeast display evolution to improve its catalytic efficiency. Our evolved APEX2 is far more active in cells, enabling the superior enrichment of endogenous mitochondrial and endoplasmic reticulum membrane proteins and the use of electron microscopy to resolve the sub-mitochondrial localization of calcium uptake regulatory protein MICU1.
          Article 0 comments Cited 525 times – based on 0 reviews     Review now
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            Fixation-resistant photoactivatable fluorescent proteins for correlative light and electron microscopy

            Maria G. Paez Segala, Mei G. Sun, Gleb Shtengel … (2015)
            Fluorescent proteins facilitate a variety of imaging paradigms in live and fixed samples. However, they cease to function following heavy fixation, hindering advanced applications such as correlative light and electron microscopy. Here we report engineered variants of the photoconvertible Eos fluorescent protein that function normally in heavily fixed (0.5–1% OsO4), plastic resin-embedded samples, enabling correlative super-resolution fluorescence imaging and high-quality electron microscopy.
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              The big data challenges of connectomics.

              Jeff W. Lichtman, Hanspeter Pfister, Nir Shavit (2014)
              The structure of the nervous system is extraordinarily complicated because individual neurons are interconnected to hundreds or even thousands of other cells in networks that can extend over large volumes. Mapping such networks at the level of synaptic connections, a field called connectomics, began in the 1970s with a the study of the small nervous system of a worm and has recently garnered general interest thanks to technical and computational advances that automate the collection of electron-microscopy data and offer the possibility of mapping even large mammalian brains. However, modern connectomics produces 'big data', unprecedented quantities of digital information at unprecedented rates, and will require, as with genomics at the time, breakthrough algorithmic and computational solutions. Here we describe some of the key difficulties that may arise and provide suggestions for managing them.
              Article 0 comments Cited 76 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 101215604
                Journal ID (pubmed-jr-id): 32338
                Journal ID (nlm-ta): Nat Methods
                Journal ID (iso-abbrev): Nat. Methods
                Title: Nature methods
                ISSN (Print): 1548-7091
                ISSN (Electronic): 1548-7105
                Publication date Nihms-submitted: 1 October 2018
                Publication date (Electronic): 05 November 2018
                Publication date (Print): December 2018
                Publication date PMC-release: 05 May 2019
                Volume: 15
                Issue: 12
                Pages: 1029-1032
                Affiliations
                [1 ]Program of Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts, USA
                [2 ]Department of Molecular and Cellular Biology and The Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA
                [3 ]Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
                Author notes

                AUTHOR CONTRIBUTIONS

                X.L and T.F. conceived, designed and implemented NATIVE with contributions from all authors. R.S. assisted in collecting serial sections, EM imaging and aligning EM images. D.B. provided the tracing tool and performed EM-LM alignment and 3D rendering. C.G. led segmentation efforts with contributions from X.L., T.F. and J.C. J.L. and H.P. supervised the work. All authors contributed to data analysis. All authors contributed to writing of the manuscript.

                [* ]Correspondence should be addressed to J.L. ( jeff@ 123456mcb.harvard.edu ) or H.P. ( hidde.ploegh@ 123456childrens.harvard.edu )
                Article
                Manuscript ID: NIHMS1507655
                DOI: 10.1038/s41592-018-0177-x
                PMC ID: 6405223
                PubMed ID: 30397326
                SO-VID: 3cc294c0-10ae-4f8d-a428-5816d44eba9e
                License:

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                Categories
                Subject: Article

                ScienceOpen disciplines: Life sciences
                Keywords: clem,nanobody,ultrastructure,immunostaining,connectomics
                Data availability:
                ScienceOpen disciplines: Life sciences
                Keywords: clem, nanobody, ultrastructure, immunostaining, connectomics

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