Limits...
Colocalization coefficients evaluating the distribution of molecular targets in microscopy methods based on pointed patterns

View Article: PubMed Central - PubMed

ABSTRACT

In biomedical studies, the colocalization is commonly understood as the overlap between distinctive labelings in images. This term is usually associated especially with quantitative evaluation of the immunostaining in fluorescence microscopy. On the other hand, the evaluation of the immunolabeling colocalization in the electron microscopy images is still under-investigated and biased by the subjective and non-quantitative interpretation of the image data. We introduce a novel computational technique for quantifying the level of colocalization in pointed patterns. Our approach follows the idea included in the widely used Manders’ colocalization coefficients in fluorescence microscopy and represents its counterpart for electron microscopy. In presented methodology, colocalization is understood as the product of the spatial interactions at the single-particle (single-molecule) level. Our approach extends the current significance testing in the immunoelectron microscopy images and establishes the descriptive colocalization coefficients. To demonstrate the performance of the proposed coefficients, we investigated the level of spatial interactions of phosphatidylinositol 4,5-bisphosphate with fibrillarin in nucleoli. We compared the electron microscopy colocalization coefficients with Manders’ colocalization coefficients for confocal microscopy and super-resolution structured illumination microscopy. The similar tendency of the values obtained using different colocalization approaches suggests the biological validity of the scientific conclusions. The presented methodology represents a good basis for further development of the quantitative analysis of immunoelectron microscopy data and can be used for studying molecular interactions at the ultrastructural level. Moreover, this methodology can be applied also to the other super-resolution microscopy techniques focused on characterization of discrete pointed structures.

No MeSH data available.


Colocalization between fibrillarin and PIP2 quantified using the data from confocal fluorescence microscopy (a, b) and super-resolution structured illumination microscopy (c, d). The graphs represent the results of the calculations by the five scenarios of the intensity level adjustments: non-thresholded image (Threshold: No), Costes thresholding based on the image parts of the nucleolar regions of interest (Threshold: 1 and Threshold: 2) and Costes thresholding based on the whole image (Threshold: 3 and Threshold: 4). a, c Each pair of the bars represents the average relative frequency distribution of the colocalizing pixels (patterned part of the bar) and non-colocalizing pixels (solid part of the bar) of the region of interest in the image (for more illustrative description of the principle of quantification, see Fig. 1). b, d Manders’ overlap coefficients (mean ± standard deviation) calculated from the data in A and C, respectively
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC5037163&req=5

Fig5: Colocalization between fibrillarin and PIP2 quantified using the data from confocal fluorescence microscopy (a, b) and super-resolution structured illumination microscopy (c, d). The graphs represent the results of the calculations by the five scenarios of the intensity level adjustments: non-thresholded image (Threshold: No), Costes thresholding based on the image parts of the nucleolar regions of interest (Threshold: 1 and Threshold: 2) and Costes thresholding based on the whole image (Threshold: 3 and Threshold: 4). a, c Each pair of the bars represents the average relative frequency distribution of the colocalizing pixels (patterned part of the bar) and non-colocalizing pixels (solid part of the bar) of the region of interest in the image (for more illustrative description of the principle of quantification, see Fig. 1). b, d Manders’ overlap coefficients (mean ± standard deviation) calculated from the data in A and C, respectively

Mentions: The fluorescence data in Fig. 5 show the consistent trend in the colocalization ratios as our proposed colocalization coefficients presented in Fig. 4. Figure 5b, d shows higher abundance of non-colocalized fibrillarin and indicates that PIP2 localization is more dependent on fibrillarin than fibrillarin on PIP2. The values in Fig. 5a, c express the higher spatial enrichment of fibrillarin in the nucleoli compared to PIP2. Remarkably, various thresholding approaches reveal the potential weakness of the accuracy of measuring the colocalization in the analyzed FM images. Also, comparing the data in Fig. 5a, b with the data in Fig. 5c, d, we can conclude that the method of imaging causes by itself the potential bias and may lead to different conclusions.Fig. 5


Colocalization coefficients evaluating the distribution of molecular targets in microscopy methods based on pointed patterns
Colocalization between fibrillarin and PIP2 quantified using the data from confocal fluorescence microscopy (a, b) and super-resolution structured illumination microscopy (c, d). The graphs represent the results of the calculations by the five scenarios of the intensity level adjustments: non-thresholded image (Threshold: No), Costes thresholding based on the image parts of the nucleolar regions of interest (Threshold: 1 and Threshold: 2) and Costes thresholding based on the whole image (Threshold: 3 and Threshold: 4). a, c Each pair of the bars represents the average relative frequency distribution of the colocalizing pixels (patterned part of the bar) and non-colocalizing pixels (solid part of the bar) of the region of interest in the image (for more illustrative description of the principle of quantification, see Fig. 1). b, d Manders’ overlap coefficients (mean ± standard deviation) calculated from the data in A and C, respectively
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037163&req=5

Fig5: Colocalization between fibrillarin and PIP2 quantified using the data from confocal fluorescence microscopy (a, b) and super-resolution structured illumination microscopy (c, d). The graphs represent the results of the calculations by the five scenarios of the intensity level adjustments: non-thresholded image (Threshold: No), Costes thresholding based on the image parts of the nucleolar regions of interest (Threshold: 1 and Threshold: 2) and Costes thresholding based on the whole image (Threshold: 3 and Threshold: 4). a, c Each pair of the bars represents the average relative frequency distribution of the colocalizing pixels (patterned part of the bar) and non-colocalizing pixels (solid part of the bar) of the region of interest in the image (for more illustrative description of the principle of quantification, see Fig. 1). b, d Manders’ overlap coefficients (mean ± standard deviation) calculated from the data in A and C, respectively
Mentions: The fluorescence data in Fig. 5 show the consistent trend in the colocalization ratios as our proposed colocalization coefficients presented in Fig. 4. Figure 5b, d shows higher abundance of non-colocalized fibrillarin and indicates that PIP2 localization is more dependent on fibrillarin than fibrillarin on PIP2. The values in Fig. 5a, c express the higher spatial enrichment of fibrillarin in the nucleoli compared to PIP2. Remarkably, various thresholding approaches reveal the potential weakness of the accuracy of measuring the colocalization in the analyzed FM images. Also, comparing the data in Fig. 5a, b with the data in Fig. 5c, d, we can conclude that the method of imaging causes by itself the potential bias and may lead to different conclusions.Fig. 5

View Article: PubMed Central - PubMed

ABSTRACT

In biomedical studies, the colocalization is commonly understood as the overlap between distinctive labelings in images. This term is usually associated especially with quantitative evaluation of the immunostaining in fluorescence microscopy. On the other hand, the evaluation of the immunolabeling colocalization in the electron microscopy images is still under-investigated and biased by the subjective and non-quantitative interpretation of the image data. We introduce a novel computational technique for quantifying the level of colocalization in pointed patterns. Our approach follows the idea included in the widely used Manders’ colocalization coefficients in fluorescence microscopy and represents its counterpart for electron microscopy. In presented methodology, colocalization is understood as the product of the spatial interactions at the single-particle (single-molecule) level. Our approach extends the current significance testing in the immunoelectron microscopy images and establishes the descriptive colocalization coefficients. To demonstrate the performance of the proposed coefficients, we investigated the level of spatial interactions of phosphatidylinositol 4,5-bisphosphate with fibrillarin in nucleoli. We compared the electron microscopy colocalization coefficients with Manders’ colocalization coefficients for confocal microscopy and super-resolution structured illumination microscopy. The similar tendency of the values obtained using different colocalization approaches suggests the biological validity of the scientific conclusions. The presented methodology represents a good basis for further development of the quantitative analysis of immunoelectron microscopy data and can be used for studying molecular interactions at the ultrastructural level. Moreover, this methodology can be applied also to the other super-resolution microscopy techniques focused on characterization of discrete pointed structures.

No MeSH data available.