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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 data quantified using EM immunolabeling of fibrillarin and PIP2. a The pair cross-correlation function compares the empirical frequencies of the pairs of particles on the chosen distance with the theoretical frequency distribution of these pairs. The values higher than value one indicate higher density than theoretically expected for random process. b Each pair of the bars represents the relative frequency distribution of the colocalizing and non-colocalizing particles of given label on the given distance range (for detailed visual description of the principle, see Fig. 1). Each shaded or filled area represents the proportion of the particles in the average image. The dark gray bar shows the values of the proposed coefficients  (patterned part of the bar) and  (solid part of the bar). The white bars show the values of the coefficients  (patterned part of the bar) and  (solid part of the bar); A is fibrillarin and B is PIP2. c Tendency of the levels of the colocalization coefficients  and  for various distance intervals (mean ± standard deviation). d Tendency of the average ratios of colocalizing particles of one type A round single particle of another type, represented by the coefficients  and
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Fig4: Colocalization data quantified using EM immunolabeling of fibrillarin and PIP2. a The pair cross-correlation function compares the empirical frequencies of the pairs of particles on the chosen distance with the theoretical frequency distribution of these pairs. The values higher than value one indicate higher density than theoretically expected for random process. b Each pair of the bars represents the relative frequency distribution of the colocalizing and non-colocalizing particles of given label on the given distance range (for detailed visual description of the principle, see Fig. 1). Each shaded or filled area represents the proportion of the particles in the average image. The dark gray bar shows the values of the proposed coefficients (patterned part of the bar) and (solid part of the bar). The white bars show the values of the coefficients (patterned part of the bar) and (solid part of the bar); A is fibrillarin and B is PIP2. c Tendency of the levels of the colocalization coefficients and for various distance intervals (mean ± standard deviation). d Tendency of the average ratios of colocalizing particles of one type A round single particle of another type, represented by the coefficients and

Mentions: The representative images obtained by CM, SIM, and EM are shown in Fig. 3. The EM image data were used to calculate the pair cross-correlation function (PCCF) shown as a graph in Fig. 4a. The levels of PCCF describe, how many times the measured frequency of particles exceeds the theoretical frequency, and they reveal the higher occurrence of the pairs of particles on the distance intervals less than 225 nm.Fig. 3


Colocalization coefficients evaluating the distribution of molecular targets in microscopy methods based on pointed patterns
Colocalization data quantified using EM immunolabeling of fibrillarin and PIP2. a The pair cross-correlation function compares the empirical frequencies of the pairs of particles on the chosen distance with the theoretical frequency distribution of these pairs. The values higher than value one indicate higher density than theoretically expected for random process. b Each pair of the bars represents the relative frequency distribution of the colocalizing and non-colocalizing particles of given label on the given distance range (for detailed visual description of the principle, see Fig. 1). Each shaded or filled area represents the proportion of the particles in the average image. The dark gray bar shows the values of the proposed coefficients  (patterned part of the bar) and  (solid part of the bar). The white bars show the values of the coefficients  (patterned part of the bar) and  (solid part of the bar); A is fibrillarin and B is PIP2. c Tendency of the levels of the colocalization coefficients  and  for various distance intervals (mean ± standard deviation). d Tendency of the average ratios of colocalizing particles of one type A round single particle of another type, represented by the coefficients  and
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5037163&req=5

Fig4: Colocalization data quantified using EM immunolabeling of fibrillarin and PIP2. a The pair cross-correlation function compares the empirical frequencies of the pairs of particles on the chosen distance with the theoretical frequency distribution of these pairs. The values higher than value one indicate higher density than theoretically expected for random process. b Each pair of the bars represents the relative frequency distribution of the colocalizing and non-colocalizing particles of given label on the given distance range (for detailed visual description of the principle, see Fig. 1). Each shaded or filled area represents the proportion of the particles in the average image. The dark gray bar shows the values of the proposed coefficients (patterned part of the bar) and (solid part of the bar). The white bars show the values of the coefficients (patterned part of the bar) and (solid part of the bar); A is fibrillarin and B is PIP2. c Tendency of the levels of the colocalization coefficients and for various distance intervals (mean ± standard deviation). d Tendency of the average ratios of colocalizing particles of one type A round single particle of another type, represented by the coefficients and
Mentions: The representative images obtained by CM, SIM, and EM are shown in Fig. 3. The EM image data were used to calculate the pair cross-correlation function (PCCF) shown as a graph in Fig. 4a. The levels of PCCF describe, how many times the measured frequency of particles exceeds the theoretical frequency, and they reveal the higher occurrence of the pairs of particles on the distance intervals less than 225 nm.Fig. 3

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.