Research paperReprint of “Multi-modal image cytometry approach – From dynamic to whole organ imaging”☆
Introduction
In comparison to other techniques such as flow cytometry, mass cytometry, RNA sequencing or enzyme-linked immunosorbent assays, imaging experiments can be comparatively more tedious, have a lower throughput and requires specific technical know-how and trained personnel to carry out. Why then is imaging valuable?
The key advantage of imaging is the capability to visualise cellular components in the context of the entire tissue. Tissue dissociation or lysis is typically required to release cells or genetic material from the tissue for analysis, but in this process, information such as cell–cell interactions, cellular behaviour and localization is lost. Tissue dissociation protocols can also vary between laboratories, and enzymatic digestion using trypsin or Type IV collagenase is also known to cause cleavage of some surface receptors [1]. Imaging is thus a valuable tool for visualising cellular distribution in situ without disrupting the architecture of the tissue, preserving the spatial information.
Imaging modalities for biological discovery are ultimately dependent on technological developments in imaging hardware and software. Antonie van Leeuwenhoek and Robert Hooke, widely regarded as the pioneers of the field of microbiology for their observations of protozoa, were able to make their discoveries by designing the most primitive form of the microscope using glass lenses [2]. Recent technological advances in the field of optical imaging have provided the biologist with a plethora of techniques such as: intra-vital two-photon microscopy to track cellular activity and changes over space and time; light sheet microscopy for whole organ imaging coupled with optical clearing to provide an overview of any changes in the tissue; and confocal microscopy to interrogate specific regions within the tissue at higher resolution. Together, these techniques can be used in combination in an imaging workflow to provide a multi-faceted answer for biological questions (Fig. 1A).
While imaging results are typically assessed visually to provide “yes or no” answers to determine if any differences exist, quantitative analyses of imaging experiments ultimately provide more objective insights into the data acquired. Image cytometry began with this initial purpose, to quantitatively describe cellular phenotypes together with spatial localization and morphology in two-dimensional images in an automated manner [3]. Such analytical methods have been successfully applied for simple nuclear stained cytospin preparations [4], haematoxylin and eosin [5], immunohistochemically stained tissues and fluorescent in situ hybridization (FISH) preparations [6] for the last twenty years. Flow cytometry-style analysis of three-dimensional lymph node static image datasets, termed “histocytometry” [7], dynamic in situ cytometry (DISC) of intra-vital imaging datasets in spleen [8]; as well as correlated dynamic and static images obtained from the same tissue using “intra-vital dynamics-immunosignal correlative (iDISC) microscopy” [9] in recent years have further popularised this form of analysis in a tissue-based context. In this review, we highlight key technical aspects for which to pay attention, for the reader who may be interested to start image cytometry. We also discuss issues linked to sample preparation, image post-processing and analysis for intra-vital imaging and whole organ imaging.
Section snippets
Technical aspects of image cytometry
Prior to starting the experiment, it is crucial to consider the following question “Is imaging even the right tool to answer the biological question?” While imaging is a powerful tool to visually illustrate biological phenomenon, and great imaging data has the capability to blow audiences off their feet, it may not be worthwhile to do imaging solely for the “wow factor” it evokes. In many situations, alternatives such as flow cytometry could be more rapid and reliable for answering the question
Image cytometry for dynamic imaging
Intra-vital imaging provides the scientist with the capability to track cellular behaviour, cell–cell interaction, cell proliferation or cell death within a living mouse over time and space. The generation of reporter mice where specific populations of cell types are labelled with fluorescent proteins was an important step forward for intra-vital imaging, as it made it possible to make observations with minimal perturbation of the biological system [32]. Mice expressing photoconvertible
Image cytometry for whole mount imaging
Immunofluorescence imaging typically focuses on a limited region of interest, with a limited penetration depth. In order to obtain clear and sharp images with minimal signal loss, tissues are typically sectioned into thin 10 µm sections for imaging. However, this makes it difficult to obtain an accurate three-dimensional representation of anatomical structures such as nerves or blood vessels which exist as a three-dimensional network [67]. One strategy to resolve this issue since the 1970s was
Conclusion and future perspectives
Interrogating a piece of tissue using a multi-modal imaging workflow quantitatively allows the biologist to correlate both temporal and spatial information of differing resolutions to provide an objective picture of ongoing biological processes. Recent development of newer techniques for multiplex imaging such as the Opal Vectra system by Perkin Elmer, tissue-based cyclic immunofluorescence (t-CyCIF) [106], co-detection by indexing (CODEX) [107] and imaging mass cytometry [108] make it possible
Acknowledgements
The authors would like to thank Leonard De Li Tan and Keith Weng Kit Leong for providing some of the images for the figure, Dr. Jackson Li Liang Yao who was instrumental in helping to set-up the image cytometry workflow in the Lai Guan Ng lab, as well as members of the lab for providing feedback on the manuscript.
Funding
This work was supported by the National Medical Research Council grant (NMRC/CSA-INV/0023/2017). This article is supported by Singapore Immunology Network (A*STAR) core funding to L.G.N. N.H. is supported by the A*STAR Graduate Scholarship (Singapore).
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A publisher’s error resulted in this article appearing in the wrong issue. The article is reprinted here for the reader’s convenience and for the continuity of the special issue. For citation purposes, please use the original publication details; Cell. Immunol, 344, 103946.**DOI of original item: http://dx.doi.org/10.1016/j.cellimm.2019.103946.