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Heil HS, Aigner M, Maier S, Gupta P, Evers LMC, Göb V, Kusch C, Meub M, Nieswandt B, Stegner D, Heinze KG. Mapping densely packed αIIbβ3 receptors in murine blood platelets with expansion microscopy. Platelets 2022; 33:849-858. [PMID: 35109754 DOI: 10.1080/09537104.2021.2023735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Interrogating platelets and their densely packed, highly abundant receptor landscape is key to understand platelet clotting, a process that can save lives when stopping blood loss after an injury, but also kill when causing heart attack, stroke, or pulmonary embolism. The underlying key receptor distributions and interactions, in particular the relevance of integrin clustering, are not fully understood is because of highly abundant and densely distributed αIIbβ3 receptors. This makes receptor distributions difficult to assess even by super-resolution fluorescence microscopy. Here, we combine dual-color expansion and confocal microscopy with colocalization analysis to assess platelet receptor organization without the need of a super-resolution microscope. We show that 4x expansion is highly straight-forward for super-resolution microscopy of platelets, while 10x expansion provides higher precision at the price of increased efforts in sample preparation and imaging. Quantifying various receptor colocalization scenarios we demonstrate that expansion microscopy can pinpoint receptor distributions and interactions in resting and activated platelets being superior to conventional methods that fail in such dense 3D scenarios with highly abundant receptors. We reveal the presence of αIIbβ3 clusters in resting platelets, as well as in activated platelets, indicating that they contribute to the rapid platelet response during platelet clotting.
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Affiliation(s)
- Hannah S Heil
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
| | - Max Aigner
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
| | - Sophia Maier
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
| | - Prateek Gupta
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
| | - Luise M C Evers
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
| | - Vanessa Göb
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany.,Institute of Experimental Biomedicine I, University Hospital Würzburg, Würzburg, Germany
| | - Charly Kusch
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany.,Institute of Experimental Biomedicine I, University Hospital Würzburg, Würzburg, Germany
| | - Mara Meub
- Department of Biotechnology and Biophysics, Biozentrum, University of Würzburg, Würzburg, Germany
| | - Bernhard Nieswandt
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany.,Institute of Experimental Biomedicine I, University Hospital Würzburg, Würzburg, Germany
| | - David Stegner
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany.,Institute of Experimental Biomedicine I, University Hospital Würzburg, Würzburg, Germany
| | - Katrin G Heinze
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
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Brunstein M, Oheim M. Dependence of descriptors of co-localization on microscope spatiotemporal resolution and the choice of regions of interest. Microsc Res Tech 2016; 80:220-230. [DOI: 10.1002/jemt.22790] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 09/27/2016] [Indexed: 11/07/2022]
Affiliation(s)
- Maia Brunstein
- CNRS UMR 8118; Brain Physiology Laboratory; Paris F-75006 France
- Fédération de Recherche en Neurosciences FR 3636, Faculté de Sciences Fondamentales et Biomédicales; Université Paris Descartes; PRES Sorbonne Paris Cité Paris F-75006 France
- Chaire d'excellence, IDEX; Université Sorbonne Paris Cité; Paris F-75006 France
| | - Martin Oheim
- CNRS UMR 8118; Brain Physiology Laboratory; Paris F-75006 France
- Fédération de Recherche en Neurosciences FR 3636, Faculté de Sciences Fondamentales et Biomédicales; Université Paris Descartes; PRES Sorbonne Paris Cité Paris F-75006 France
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Colocalization Estimation Using Graphical Modeling and Variational Bayesian Expectation Maximization: Towards a Parameter-Free Approach. ACTA ACUST UNITED AC 2015. [PMID: 26221663 DOI: 10.1007/978-3-319-19992-4_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
In microscopy imaging, colocalization between two biological entities (e.g., protein-protein or protein-cell) refers to the (stochastic) dependencies between the spatial locations of the two entities in the biological specimen. Measuring colocalization between two entities relies on fluorescence imaging of the specimen using two fluorescent chemicals, each of which indicates the presence/absence of one of the entities at any pixel location. State-of-the-art methods for estimating colocalization rely on post-processing image data using an adhoc sequence of algorithms with many free parameters that are tuned visually. This leads to loss of reproducibility of the results. This paper proposes a brand-new framework for estimating the nature and strength of colocalization directly from corrupted image data by solving a single unified optimization problem that automatically deals with noise, object labeling, and parameter tuning. The proposed framework relies on probabilistic graphical image modeling and a novel inference scheme using variational Bayesian expectation maximization for estimating all model parameters, including colocalization, from data. Results on simulated and real-world data demonstrate improved performance over the state of the art.
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Ferreira SA, Correia A, Madureira P, Vilanova M, Gama FM. Unraveling the Uptake Mechanisms of Mannan Nanogel in Bone-Marrow-Derived Macrophages. Macromol Biosci 2012; 12:1172-80. [DOI: 10.1002/mabi.201200075] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2012] [Revised: 05/02/2012] [Indexed: 12/17/2022]
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Dunn KW, Kamocka MM, McDonald JH. A practical guide to evaluating colocalization in biological microscopy. Am J Physiol Cell Physiol 2011; 300:C723-42. [PMID: 21209361 PMCID: PMC3074624 DOI: 10.1152/ajpcell.00462.2010] [Citation(s) in RCA: 1409] [Impact Index Per Article: 108.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2010] [Accepted: 01/02/2011] [Indexed: 11/22/2022]
Abstract
Fluorescence microscopy is one of the most powerful tools for elucidating the cellular functions of proteins and other molecules. In many cases, the function of a molecule can be inferred from its association with specific intracellular compartments or molecular complexes, which is typically determined by comparing the distribution of a fluorescently labeled version of the molecule with that of a second, complementarily labeled probe. Although arguably the most common application of fluorescence microscopy in biomedical research, studies evaluating the "colocalization" of two probes are seldom quantified, despite a diversity of image analysis tools that have been specifically developed for that purpose. Here we provide a guide to analyzing colocalization in cell biology studies, emphasizing practical application of quantitative tools that are now widely available in commercial and free image analysis software.
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Affiliation(s)
- Kenneth W Dunn
- Dept. of Medicine, Division of Nephrology, Indiana Univ. Medical Center, Indianapolis, IN 46202, USA.
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Adler J, Parmryd I. Quantifying colocalization by correlation: The Pearson correlation coefficient is superior to the Mander's overlap coefficient. Cytometry A 2010; 77:733-42. [DOI: 10.1002/cyto.a.20896] [Citation(s) in RCA: 614] [Impact Index Per Article: 43.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Li H, Shih WY, Shih WH. Highly Photoluminescent and Stable Aqueous ZnS Quantum Dots. Ind Eng Chem Res 2009. [DOI: 10.1021/ie901086d] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Hui Li
- Department of Materials Science and Engineering and School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, Pennsylvania 19104
| | - Wan Y. Shih
- Department of Materials Science and Engineering and School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, Pennsylvania 19104
| | - Wei-Heng Shih
- Department of Materials Science and Engineering and School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, Pennsylvania 19104
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Abstract
Advances in microscopy and fluorescent probes provide new insight into the nanometer-scale biochemistry governing the interactions between eukaryotic cells and pathogens. When combined with mathematical modelling, these new technologies hold the promise of qualitative, quantitative and predictive descriptions of these pathways. Using the light microscope to study the spatial and temporal relationships between pathogens, host cells and their respective biochemical machinery requires an appreciation for how fluorescent probes and imaging devices function. This review summarizes how live cell fluorescence microscopy with common instruments can provide quantitative insight into the cellular and molecular functions of hosts and pathogens.
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Affiliation(s)
- Adam D Hoppe
- Department of Chemistry and Biochemistry, South Dakota State University, Brookings, SD 57007-0896, USA.
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