Published
Principles and Practice of Variable Pressure/Environmental Scanning
Electron Microscopy (VP‐ESEM)
Debbie Stokes
Aberration‐Corrected Analytical Electron Microscopy
Edited by Rik Brydson
Diagnostic Electron Microscopy—A Practical Guide to Interpretation and Technique
Edited by John W. Stirling, Alan Curry & Brian Eyden
Low Voltage Electron Microscopy—Principles and Applications
Edited by David C. Bell & Natasha Erdman
Standard and Super‐Resolution Bioimaging Data Analysis: A Primer
Edited by Ann Wheeler and Ricardo Henriques
Forthcoming
Understanding Practical Light Microscopy
Jeremy Sanderson
Atlas of Images and Spectra for Electron Microscopists
Edited by Ursel Bangert
Focused Ion Beam Instrumentation: Techniques and Applications
Dudley Finch & Alexander Buxbaum
Electron Beam‐Specimen Interactions and Applications in Microscopy
Budhika Mendis
Edited by
Series Editor: Susan Brooks
This edition first published 2018
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Library of Congress Cataloging‐in‐Publication Data
Names: Wheeler, Ann, 1977– editor. | Henriques, Ricardo, 1980– editor.
Title: Standard and Super‐Resolution Bioimaging Data Analysis: A Primer / edited by Dr. Ann Wheeler, Dr. Ricardo Henriques.
Description: First edition. | Hoboken, NJ : John Wiley & Sons, 2018. | Includes index. |
Identifiers: LCCN 2017018827 (print) | LCCN 2017040983 (ebook) | ISBN 9781119096924 (pdf) | ISBN 9781119096931 (epub) | ISBN 9781119096900 (cloth)
Subjects: LCSH: Imaging systems in biology. | Image analysis–Data processing. | Diagnostic imaging–Data processing.
Classification: LCC R857.O6 (ebook) | LCC R857.O6 S73 2017 (print) | DDC 616.07/54–dc23LC record available at https://lccn.loc.gov/2017018827
Cover design by Wiley
Cover image: Courtesy of Ricardo Henriques and Siân Culley at University College London
George Ashdown,
Department of Physics and Randall Division of Cell and Molecular Biophysics, King’s College London, UK
Graeme Ball,
Dundee Imaging Facility, School of Life Sciences, University of Dundee, UK
Sébastien Besson,
Centre for Gene Regulation & Expression and Division of Computational Biology, University of Dundee, UK
Mario De Piano,
Division of Cancer Studies, King’s College London, UK
Ahmed Fetit,
Advanced Imaging Resource, MRC‐IGMM, University of Edinburgh, UK
and
School of Science and Engineering, University of Dundee, UK
Juliette Griffié,
Department of Physics and Randall Division of Cell and Molecular Biophysics, King’s College London, UK
Aliaksandr Halavatyi,
European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
Ricardo Henriques,
MRC Laboratory for Molecular Cell Biology, University College London, UK
Gareth E. Jones,
Randall Division of Cell & Molecular Biophysics, King’s College London, UK
Debora Keller,
Facility for Imaging by Light Microscopy, Imperial College London, UK
Kota Miura,
Nikon Imaging Center, Bioquant, University of Heidelberg, Germany; National Institute of Basic Biology, Okazaki, Japan; Network of European Bioimage Analysts (NEUBIAS)
Nicolas Olivier,
Department of Physics and Astronomy, University of Sheffield, UK
Peter O’Toole,
Technology Facility, Department of Biology, University of York, UK
Dylan Owen,
Department of Physics and Randall Division of Cell and Molecular Biophysics, King’s College London, UK
Thomas Pengo,
University of Minnesota Informatics Institute, University of Minnesota Twin Cities, USA
Michael Shannon,
Department of Physics and Randall Division of Cell and Molecular Biophysics, King’s College London, UK
Stefan Terjung,
European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
Jean‐Yves Tinevez,
Institut Pasteur, Photonic BioImaging (UTechS PBI, Imagopole), Paris, France
Sébastien Tosi,
Advanced Digital Microscopy Core Facility (ADMCF), Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain; Network of European Bioimage Analysts (NEUBIAS)
Claire M. Wells,
School of Cancer and Pharmaceutical Sciences, King’s College London, UK
Ann Wheeler,
Advanced Imaging Resource, MRC‐IGMM, University of Edinburgh, UK
Imaging is now one of the most commonly used techniques in biological research. It is not simply a means of taking a pretty picture; rather advanced microscopy and imaging are now vital biophysical tools underpinning our studies of the most complex biological systems. We have the capability to study cells in real time, with 3D volumes, analysing biophysical interactions, and now moving towards the ability to see and study individual proteins within individual cells within their native environment. Imaging is one of the most useful tools for understanding the fundamental biology of the cell.
This has been made possible through an incredibly rapid period of microscopy development, which has gone hand in hand with the emergence of new fluorescent tags – such as fluorescent proteins – computing power and the latest developments in engineering. Not only has the technology become increasingly versatile and opened up many new possibilities, but leading manufacturers have also made their microscopes increasingly accessible to non‐specialists, resulting in an explosion of data.
All of these developments have left us with a wealth of data, but the images themselves will remain just pretty pictures unless they are analysed appropriately. We are now starting to see an equivalent rapid increase in the development of image analysis, but we are still far from realising its full potential. The basics are vital, and anyone using today’s microscopes should also be looking at the best approaches for analysing their data.
This book is extremely timely and looks at some of the key aspects of data analysis; it will serve as an excellent point of reference. Chapter 1 examines the basics of image data and processing which is common to most users. Chapters 2 and 3 builds on this and looks at how to quantify both routine 2D through to more complex 3D image data sets. However, one of the greatest challenges remains the ability to segment our images. To our own eyes, this can be quite obvious, but it still remains a real computational challenge. Segmenting images and image data e.g. in Chapter 3 will be a continuing area of development that will also help us to correlate data with greater precision in the future.
Beyond the images, the microscope is a powerful biophysical tool. We can see and analyse the co‐localisation of particles such as proteins, but great care is needed in their analyses as outlined by Dylan Owen e.g. in Chapter 6. We can now go beyond this and start to see interactions that occur over a 5 nm range. This enables the studies of particle–particle interactions such as protein–protein heterodimerisation by using FRET, and although the imaging of these phenomena is relative simple the complexity of the quantification is discussed in Chapter 4.
Not only can the microscope study these natural interactions, but we can also use the light, often with lasers, to manipulate cells and trigger critical events that would otherwise occur in a random fashion making their studies very difficult. The interpretation and controls for FRAP and other photo perturbation methods then needs to be carefully considered (Chapter 5).
Many of the above studies can be undertaken using both fixed and live cell imaging. Whole live‐cell imaging and tracking brings its own analytical challenges (Chapter 7) as cells move through three dimensions, pass over one another often changing shape and nature. This needs many of the above elements to come together to help work in such complex sample types.
At the other extreme, from whole cells, the biggest advancement in light microscopy has come from the ability to image below the diffraction limit. Super‐resolution microscopy (SRM) is possible through many different strategies. The analysis and interpretation is an area that is often under‐appreciated and which can result in misinterpretations. For anyone wanting to undertake SRM, it is essential to understand the limitations, controls and best approaches to their analysis (Chapter 8).
Many of the new microscopical techniques now produce very large data sets. This is especially true for 3D live‐cell imaging and SRM. This has developed its own problem, with data analyses now often taking considerably longer than the imaging time itself. The time needed for data analysis has become the most costly element in complex image study. The staff time itself often outweighs the cost of the instrument and consumables and this is why we need to look for automation when handling and analysing the data (Chapter 9), and naturally, once all of this data has been analysed, it is vital to not only present the data in the correct manner, but also to ensure that it is correctly documented and stored (Chapter 10). Only then, can any one image be properly exploited and deliver the required impact.