Difference between revisions of "A Blind Spot in Confocal Reflection Microscopy: The Dependence of Fiber Brightness on Fiber Orientation in Imaging Biopolymer Networks"

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Entry by Leon Furchtgott, APP 225 Fall 2010.
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Fourth entry by Kelly Miller, AP225 Fall 2011
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A Blind Spot in Confocal Reflection Microscopy: The Dependence of Fiber Brightness on Fiber Orientation in Imaging Biopolymer Networks. L.M. Jawerth, S. Munster, D.A. Vader, B. Fabry, and D.A. Weitz. (2010). Biophysical Journal, 98, L01-L03.
 
A Blind Spot in Confocal Reflection Microscopy: The Dependence of Fiber Brightness on Fiber Orientation in Imaging Biopolymer Networks. L.M. Jawerth, S. Munster, D.A. Vader, B. Fabry, and D.A. Weitz. (2010). Biophysical Journal, 98, L01-L03.
  
== Summary ==
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The paper is interested in imaging techniques for biopolymers. In particular, the paper compares the effectiveness in imaging collagen networks of two confocal imaging methods, confocal reflection microscopy (CRM) and confocal fluorescence microscopy (CFM). The authors simultaneously image collagen using the two techniques and find that in CRM, fiber brightness depends strongly on fiber orientation. This explains why when using CRM to image collagen, the network appears to be aligned with the imaging plane, whereas in CFM, the network seems isotropic.  
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== Keywords ==
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[[Collagen networks]], [[Confocal microscopy]], [[Anisotropy]], [[Isotropy]]
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== Overview ==
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Two different confocal imaging techniques were compared in the context of imaging networks of biopolymer fibers. The two techniques compared were: confocal reflection microscopy (CRM) and confocal fluorescence microscopy (CFM). Fluorescently labeled type I collagen networks were imaged using both techniques and the images were compared. The CRM system is not able to detect fibers above more of a 50 degree angle (from the imaging plane). For this imaging system the brightness decreases for more vertically oriented fibers and therefore, the 3D network structure appears in the image, to be aligned with the imaging plane. The other system discussed in this paper, CFM, exhibits little variation of fiber brightness with the angle of the fiber and, as a result, an isotropic collagen network is imaged. Overall, CFM detects approximately twice as many fibers as are visible with CRM, and therefore, yield a more complete structural picture for 3D fiber networks.
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The point of this paper is to provide a simple model to predict the detected fiber brightness as a function of the fiber orientation in CRM.
  
 
== Background ==
 
== Background ==
  
Difference between CRM and CFM: Both CRM and CFM are [http://en.wikipedia.org/wiki/Confocal_microscopy confocal] techniques. CRM uses back-scattered light to form an image. CFM uses laser light to excite fluorophores in an imaging sample and forms an image from the emitted light.  
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Collagen is a ubiquitous protein in mammals that constitutes a primary component of connective tissue in the interstitial space between cells. It appears under the microscope as a branched network of fibers, each of which can be resolved with confocal microscopy. To understand how cell-matrix interaction depends on the local environment of the cell - it is important to image the exact 3-D  fiber environment of the cell. The most commonly used technique for imaging collagen networks is confocal reflection microscopy which uses back-scattered light to form an image. This method has been used to successfully obtain information on the collagen network such as morphology of collagen networks, mesh size, location and the orientation of the fibers.  
  
[http://en.wikipedia.org/wiki/Collagen Collagen ]: Collagen is a protein in mammals that forms the primary component of connective tissues in the interstitial space between cells. Collagen appears to be a branched network of fibers.
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However, sometimes the imaging of these fibers occurs in an anisotropic manner - producing images of the fibers aligned primarily with the imaging plane. This might occur from the intrinsic properties of the sample or the imaging method itself. To try to figure out what is producing the anomalous effects, it is essential to use an alternative imaging modality to examine the collagen structure.  
  
Previous research in collagen network architecture: Collagen 3-D architecture is the subject of a lot of research. To understand collagen's biological role, it is crucial to image the exact 3-D fiber environment in a cell. The most commonly used technique for imaging collage is CRM. CRM studies have shown anisotropy in collagen networks: the fibers tend to orient in the direction of the imaging plane. This might be an intrinsic property of collagen, or it could be caused by the imaging method. To determine the origin of the effect, the authors use CFM and CRM simultaneously on fluorescently labeled collagen type I networks.
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The alternative technique that was used for this purpose was the confocal fluorescence microscope (CFM) which uses laser light to excite fluorophores in the imaging sample and forms an image from the emitted light.
  
 
== Results ==
 
== Results ==
  
Figure 1 shows a comparison of images taken with CRM and with CFM for the same collagen sample, and the differences in imaging are immediately visible. Whereas Figures 1B and 1E (CFM) show a collagen network with no preferential direction, Figures 1A and 1D (CRM) show a network whose fibers are oriented with the imaging plane. Figures 1B and 1E show many fibers that are aligned in the perpendicular direction from the imaging plane that do not show up in the CRM figures. All fibers detected by CRM are also detected by CFM, but a large number are detected only by CFM and not by CRM.
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Data was simultaneously collected using CRM and CFM on fluorescently labelled fibers. The brightness and orientation of individual fibers were analyzed. It was found that fiber brightness decreases in CRM with increasing fiber angle - which means that fibers above an angle of 50 degrees from the imaging plane will be entirely undetected. Consequently, the collagen structure appears aligned with the imaging plane.  
 
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[[Image:jawerth1.jpg|400px|thumb|center|Fig. 1. Simultaneous imaging of a collagen network using CRM and CFM. A. Typical image from CRM. B. Corresponding image using CFM. Red circles highlight fibers that do not appear in the reflection image. C. Overlay of panels A (green) and B (red). D. Projection of 50 x,z slices along the y axis using CRM image data. E. Equivalent projection using CFM. F. Overlay of panels D (green) and E (red). ]]
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To quantify the degree of alignment in the data sets, the authors use a grayscale moments analysis of the data to obtain a histogram of the orientations of the fibers in the sample. This yields values of the azimuthal angle <math>\phi</math> defined within the imaging plane and of the polar angle <math>\theta</math> defined with respect to the perpendicular (z) axis. Since the area of a surface element for a unit sphere is <math>sin \theta d\theta d\phi</math>, an isotropic network should show a sine distribution for <math>\theta</math> and a uniform distribution for <math>\phi</math>. The distributions are shown in Figure 2. The <math>\phi</math> distribution is fairly flat for both imaging methods, revealing that the sample is isotropic within the focal plane. For <math>\theta</math>, CFM data follows a sine distribution whereas CRM data deviates strongly.  
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CFM, on the other hand, detects fibers with similar brightness, independent of their orientation - therefore twice as many fibers are exposed and an isotropic network is displayed.  
  
To test whether the anisotropy in the CRM data is an imaging artifact, the authors rotate the sample by 90 degrees. Whereas the CFM data shows no difference when rotated, the CRM anistropy does not rotate. This suggests that there is some bias within the CRM imaging technique itself.
 
  
[[Image:jawerth2.gif|400px|thumb|center|Fig. 2. Relative frequency of the moment angle <math>\theta</math> for CFM data (triangles) and CRM data (circles) in both rotated (solid) and non-rotated (open) samples. Light-shaded line: sine distribution expected for an isotropic sample. Inset: corresponding <math>\phi</math> distributions.]]
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[[Image:pic_1_polymer.png]]
  
To determine the origin of the anisotropy, the authors calculate the median intensity for each fiber in the CFM and CRM data (Figure 3). In the CFM data, the intensity does not depend on the fiber angle, apart from a small increase in intensity for fibers that are perpendicular to the imaging plane. In contrast, for CRM, the intensity drops quite precipitously for fibers at more than 50 degrees from the imaging plane. As a result, for an isotropic 3-D network, CFM will detect almost twice as many fibers as CRM.
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The authors then provide a description of an experiment that they performed to predict the detected fiber brightness as a function of fiber orientation in the CRM.
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To figure out if the apparent anisotropy seen in CRM is an imaging artifact and not an intrinsic sample property, they rotated the same by 90 degrees. For both types of imaging technique the dat from the rotated case closely match those of the original sample before the reorientation. It was concluded that the apparent anisotropy in the CRM data does not rotate and therefore the apparent anisotropy must arise from a bias in the CRM imaging technique.  
  
[[Image:jawerth3.gif|400px|thumb|center|Fig. 3. Intensity of individual fibers as a function of their <math>\theta</math>-angle for CFM (triangles) and CRM (circles) for both the rotated (open) and nonrotated (solid) cases. Shaded line shows expected values from theory. ]]
 
  
The authors then do some modeling to explain why the intensity drops as a function of fiber angle in CRM. They show using simple geometry that for CFM, light that illuminates a fiber that forms an angle <math>\theta</math> with the z-axis will be reflected at an angle <math>2 \theta</math>. However the aperture of the imaging system has a maximal opening angle, and the amount of light it captures will depend on the angle of the reflected light. This approach predicts the steep dropoff in intensity for fibers with large angles with the imaging plane.
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[[Image:pic_2_polymer.png]]
  
== Discussion ==
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==Conclusion==
  
== Relation to Soft Matter ==
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This paper, aside from its relevance to the subject of soft matter, was incredibly interesting to me because I have just learned all about confocal microscopy, from AP 217. One of the things we addressed in 217 was isotropic resolution which seems to be the issue in this paper. I also found it very interesting because I didn't realize that collagen was a polymer.
  
This paper gives insight into a more experimental area of soft-matter physics than what we covered in our discussions of polymers. In particular it shows the great sensitivity of results about biopolymers to the imaging technique used and the dangers in using the wrong imaging technique for looking at polymers.
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The authors suggest future directions to improving the poor collagen image quality that comes out of CRM and for figuring out exactly why this happens. One thought was to coat the collagen fibers with gold particles before imaging. It has been suggested that labeling the collagen fibers in this way may enhance the reflective properties of the sample, making the CRM a more effective imaging system. Further investigations (from when this paper was written) are needed to confirm whether this is the case.

Latest revision as of 19:17, 30 November 2011

Fourth entry by Kelly Miller, AP225 Fall 2011


A Blind Spot in Confocal Reflection Microscopy: The Dependence of Fiber Brightness on Fiber Orientation in Imaging Biopolymer Networks. L.M. Jawerth, S. Munster, D.A. Vader, B. Fabry, and D.A. Weitz. (2010). Biophysical Journal, 98, L01-L03.


Keywords

Collagen networks, Confocal microscopy, Anisotropy, Isotropy


Overview

Two different confocal imaging techniques were compared in the context of imaging networks of biopolymer fibers. The two techniques compared were: confocal reflection microscopy (CRM) and confocal fluorescence microscopy (CFM). Fluorescently labeled type I collagen networks were imaged using both techniques and the images were compared. The CRM system is not able to detect fibers above more of a 50 degree angle (from the imaging plane). For this imaging system the brightness decreases for more vertically oriented fibers and therefore, the 3D network structure appears in the image, to be aligned with the imaging plane. The other system discussed in this paper, CFM, exhibits little variation of fiber brightness with the angle of the fiber and, as a result, an isotropic collagen network is imaged. Overall, CFM detects approximately twice as many fibers as are visible with CRM, and therefore, yield a more complete structural picture for 3D fiber networks.

The point of this paper is to provide a simple model to predict the detected fiber brightness as a function of the fiber orientation in CRM.

Background

Collagen is a ubiquitous protein in mammals that constitutes a primary component of connective tissue in the interstitial space between cells. It appears under the microscope as a branched network of fibers, each of which can be resolved with confocal microscopy. To understand how cell-matrix interaction depends on the local environment of the cell - it is important to image the exact 3-D fiber environment of the cell. The most commonly used technique for imaging collagen networks is confocal reflection microscopy which uses back-scattered light to form an image. This method has been used to successfully obtain information on the collagen network such as morphology of collagen networks, mesh size, location and the orientation of the fibers.

However, sometimes the imaging of these fibers occurs in an anisotropic manner - producing images of the fibers aligned primarily with the imaging plane. This might occur from the intrinsic properties of the sample or the imaging method itself. To try to figure out what is producing the anomalous effects, it is essential to use an alternative imaging modality to examine the collagen structure.

The alternative technique that was used for this purpose was the confocal fluorescence microscope (CFM) which uses laser light to excite fluorophores in the imaging sample and forms an image from the emitted light.

Results

Data was simultaneously collected using CRM and CFM on fluorescently labelled fibers. The brightness and orientation of individual fibers were analyzed. It was found that fiber brightness decreases in CRM with increasing fiber angle - which means that fibers above an angle of 50 degrees from the imaging plane will be entirely undetected. Consequently, the collagen structure appears aligned with the imaging plane.

CFM, on the other hand, detects fibers with similar brightness, independent of their orientation - therefore twice as many fibers are exposed and an isotropic network is displayed.


Pic 1 polymer.png

The authors then provide a description of an experiment that they performed to predict the detected fiber brightness as a function of fiber orientation in the CRM. To figure out if the apparent anisotropy seen in CRM is an imaging artifact and not an intrinsic sample property, they rotated the same by 90 degrees. For both types of imaging technique the dat from the rotated case closely match those of the original sample before the reorientation. It was concluded that the apparent anisotropy in the CRM data does not rotate and therefore the apparent anisotropy must arise from a bias in the CRM imaging technique.


Pic 2 polymer.png

Conclusion

This paper, aside from its relevance to the subject of soft matter, was incredibly interesting to me because I have just learned all about confocal microscopy, from AP 217. One of the things we addressed in 217 was isotropic resolution which seems to be the issue in this paper. I also found it very interesting because I didn't realize that collagen was a polymer.

The authors suggest future directions to improving the poor collagen image quality that comes out of CRM and for figuring out exactly why this happens. One thought was to coat the collagen fibers with gold particles before imaging. It has been suggested that labeling the collagen fibers in this way may enhance the reflective properties of the sample, making the CRM a more effective imaging system. Further investigations (from when this paper was written) are needed to confirm whether this is the case.