Simultaneously Measuring Image Features and Resolution in Live-Cell STED Images
Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a nonbiological proxy for a point-like object, such as a fluorescent bead. Although appropriate for...
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Published in | Biophysical journal Vol. 115; no. 6; pp. 951 - 956 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Elsevier Inc
18.09.2018
The Biophysical Society |
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Abstract | Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a nonbiological proxy for a point-like object, such as a fluorescent bead. Although appropriate for confocal microscopy, bead-based measurements are problematic for stimulated emission depletion microscopy and similar techniques where the resolution depends critically on the choice of fluorophore and acquisition parameters. In this article, we demonstrate that for a known geometry (e.g., tubules), the resolution can be measured in situ by fitting a model that accounts for both the point spread function (PSF) and the fluorophore distribution. To address the problem of coupling between tubule diameter and PSF width, we developed a technique called nested-loop ensemble PSF fitting. This approach enables extraction of the size of cellular features and the PSF width in fixed-cell and live-cell images without relying on beads or precalibration. Nested-loop ensemble PSF fitting accurately recapitulates microtubule diameter from stimulated emission depletion images and can measure the diameter of endoplasmic reticulum tubules in live COS-7 cells. Our algorithm has been implemented as a plugin for the PYthon Microscopy Environment, a freely available and open-source software. |
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AbstractList | Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a nonbiological proxy for a point-like object, such as a fluorescent bead. Although appropriate for confocal microscopy, bead-based measurements are problematic for stimulated emission depletion microscopy and similar techniques where the resolution depends critically on the choice of fluorophore and acquisition parameters. In this article, we demonstrate that for a known geometry (e.g., tubules), the resolution can be measured in situ by fitting a model that accounts for both the point spread function (PSF) and the fluorophore distribution. To address the problem of coupling between tubule diameter and PSF width, we developed a technique called nested-loop ensemble PSF fitting. This approach enables extraction of the size of cellular features and the PSF width in fixed-cell and live-cell images without relying on beads or precalibration. Nested-loop ensemble PSF fitting accurately recapitulates microtubule diameter from stimulated emission depletion images and can measure the diameter of endoplasmic reticulum tubules in live COS-7 cells. Our algorithm has been implemented as a plugin for the PYthon Microscopy Environment, a freely available and open-source software.Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a nonbiological proxy for a point-like object, such as a fluorescent bead. Although appropriate for confocal microscopy, bead-based measurements are problematic for stimulated emission depletion microscopy and similar techniques where the resolution depends critically on the choice of fluorophore and acquisition parameters. In this article, we demonstrate that for a known geometry (e.g., tubules), the resolution can be measured in situ by fitting a model that accounts for both the point spread function (PSF) and the fluorophore distribution. To address the problem of coupling between tubule diameter and PSF width, we developed a technique called nested-loop ensemble PSF fitting. This approach enables extraction of the size of cellular features and the PSF width in fixed-cell and live-cell images without relying on beads or precalibration. Nested-loop ensemble PSF fitting accurately recapitulates microtubule diameter from stimulated emission depletion images and can measure the diameter of endoplasmic reticulum tubules in live COS-7 cells. Our algorithm has been implemented as a plugin for the PYthon Microscopy Environment, a freely available and open-source software. Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a nonbiological proxy for a point-like object, such as a fluorescent bead. Although appropriate for confocal microscopy, bead-based measurements are problematic for stimulated emission depletion microscopy and similar techniques where the resolution depends critically on the choice of fluorophore and acquisition parameters. In this article, we demonstrate that for a known geometry (e.g., tubules), the resolution can be measured in situ by fitting a model that accounts for both the point spread function (PSF) and the fluorophore distribution. To address the problem of coupling between tubule diameter and PSF width, we developed a technique called nested-loop ensemble PSF fitting. This approach enables extraction of the size of cellular features and the PSF width in fixed-cell and live-cell images without relying on beads or precalibration. Nested-loop ensemble PSF fitting accurately recapitulates microtubule diameter from stimulated emission depletion images and can measure the diameter of endoplasmic reticulum tubules in live COS-7 cells. Our algorithm has been implemented as a plugin for the PYthon Microscopy Environment, a freely available and open-source software. |
Author | Bewersdorf, Joerg Schroeder, Lena K. Barentine, Andrew E.S. Graff, Michael Baddeley, David |
AuthorAffiliation | 2 Department of Biomedical Engineering, Yale University, New Haven, Connecticut 1 Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 3 Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand |
AuthorAffiliation_xml | – name: 1 Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut – name: 3 Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand – name: 2 Department of Biomedical Engineering, Yale University, New Haven, Connecticut |
Author_xml | – sequence: 1 givenname: Andrew E.S. surname: Barentine fullname: Barentine, Andrew E.S. organization: Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut – sequence: 2 givenname: Lena K. surname: Schroeder fullname: Schroeder, Lena K. organization: Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut – sequence: 3 givenname: Michael surname: Graff fullname: Graff, Michael organization: Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut – sequence: 4 givenname: David surname: Baddeley fullname: Baddeley, David email: d.baddeley@auckland.ac.nz organization: Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut – sequence: 5 givenname: Joerg surname: Bewersdorf fullname: Bewersdorf, Joerg email: joerg.bewersdorf@yale.edu organization: Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut |
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Cites_doi | 10.1002/smll.200800055 10.1038/nbt765 10.1007/s12575-009-9008-x 10.1002/anie.201100371 10.1016/j.cell.2016.06.016 10.1111/j.1365-2818.2009.03304.x 10.1364/OPTICA.5.000032 10.1038/nmeth.2448 10.1126/science.1137395 10.1073/pnas.75.4.1820 10.1371/journal.pone.0054421 10.1038/ncomms10778 10.1364/OE.16.004154 10.1016/j.jsb.2013.05.004 |
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