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The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage.

Oeck S, Malewicz NM, Hurst S, Rudner J, Jendrossek V - Radiat Oncol (2015)

Bottom Line: It significantly reduced the analysis time of radiation-induced DNA-damage foci.The macro allows improved foci evaluation regarding accuracy, reproducibility and analysis speed compared to manual analysis.As innovative option, the macro offers a combination of multichannel evaluation including colocalization analysis and the possibility to run all analyses in a batch mode.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. sebastian.oeck@uk-essen.de.

ABSTRACT

Background: The quantitative analysis of foci plays an important role in many cell biological methods such as counting of colonies or cells, organelles or vesicles, or the number of protein complexes. In radiation biology and molecular radiation oncology, DNA damage and DNA repair kinetics upon ionizing radiation (IR) are evaluated by counting protein clusters or accumulations of phosphorylated proteins recruited to DNA damage sites. Consistency in counting and interpretation of foci remains challenging. Many current software solutions describe instructions for time-consuming and error-prone manual analysis, provide incomplete algorithms for analysis or are expensive. Therefore, we aimed to develop a tool for costless, automated, quantitative and qualitative analysis of foci.

Methods: For this purpose we integrated a user-friendly interface into ImageJ and selected parameters to allow automated selection of regions of interest (ROIs) depending on their size and circularity. We added different export options and a batch analysis. The use of the Focinator was tested by analyzing γ-H2.AX foci in murine prostate adenocarcinoma cells (TRAMP-C1) at different time points after IR with 0.5 to 3 Gray (Gy). Additionally, measurements were performed by users with different backgrounds and experience.

Results: The Focinator turned out to be an easily adjustable tool for automation of foci counting. It significantly reduced the analysis time of radiation-induced DNA-damage foci. Furthermore, different user groups were able to achieve a similar counting velocity. Importantly, there was no difference in nuclei detection between the Focinator and ImageJ alone.

Conclusions: The Focinator is a costless, user-friendly tool for fast high-throughput evaluation of DNA repair foci. The macro allows improved foci evaluation regarding accuracy, reproducibility and analysis speed compared to manual analysis. As innovative option, the macro offers a combination of multichannel evaluation including colocalization analysis and the possibility to run all analyses in a batch mode.

No MeSH data available.


Related in: MedlinePlus

The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu (2), buttons (1) and Focinator Options (3 and 4). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 (on top after opening the image). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings (3): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch (4) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance
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Fig1: The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu (2), buttons (1) and Focinator Options (3 and 4). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 (on top after opening the image). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings (3): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch (4) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance

Mentions: To develop the Focinator as a tool for automated quantitative and qualitative analysis of foci with ImageJ, we first integrated a user-friendly interface. The interface (Fig. 1) includes eight buttons, a menu as well as nine shortcuts for the following commands < F1 > Automated Mode, <F2 > Options, <F3 > Thresholding, <F4 > Separation, <F5 > Selecting ROIs, <F6 > Thresholding and Selecting ROIs, <F7 > Analyzing - Foci Count, <F8 > Open Next Image in the folder. The menu also includes further information under About The Focinator and an instruction manual under Help. The second step for the development was an automated selection of the regions of interest (ROIs), such as cells or nuclei, depending on their appearance (Fig. 2). Moreover, automated detection of foci and the analysis of ROIs and foci were included (Fig. 3).Fig. 1


The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage.

Oeck S, Malewicz NM, Hurst S, Rudner J, Jendrossek V - Radiat Oncol (2015)

The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu (2), buttons (1) and Focinator Options (3 and 4). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 (on top after opening the image). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings (3): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch (4) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4554354&req=5

Fig1: The ImageJ-based interface of the Focinator offers options to adapt the evaluation parameters to distinct image characteristics. Figure 1 shows ImageJ with the Focinator macro installed as start-up macro after opening a multi-channel image. This microscope image with the file format ZVI 16-bit includes three fluorescence channels. The main window of the Focinator is implemented into the ImageJ window. It consists of a menu (2), buttons (1) and Focinator Options (3 and 4). The Focinator Options windows offer several preferences for the user to adapt the macro’s behavior to individual requirements. Picture Settings: First step is to tell the macro, the input folder and if there is a multi-channel image or more single pictures will be opened. In the second step you choose in which channel the foci have to be counted and where the ROIs should be selected. In our example, the γ-H2.AX foci are in channel number 2 (on top after opening the image). The macro will use the setting “1st foci channel = front channel” for all pictures automatically. If no second foci channel is used the setting should be changed to “inactive”. ROI Settings (3): Depending on image quality, size and magnification, it is recommended to set the threshold and the size filters for ROIs. Alternatively, the choice of automated thresholding is possible. It is possible to exclude objects that are partially outside of the image. If there are objects to exclude because they are not circular enough or too small, it is possible to exclude them via circularity filters or size filters. “Use fill holes” should be activated, if the ROI selection left holes in the cells. Overlapping ROIs (cells, nuclei) might be separated by choosing “watershed”. Regarding the batch mode “check selection” offers the possibility of stopping during the selection process. “Invert images” should be checked when working with images with light background. For the automated batch (4) mode, output directories need to be chosen to save the results. An important step of evaluation is to choose the right noise level. Noise level values can be set independently in multi-channel analysis to exclude background artifacts. By defining the cut off, foci with intensities below a certain value are deleted, which excludes background noise. The value for area correction is dependent on the mean size of the analyzed nuclei. The factor corrects the foci number divided by the individual area of each nucleus. The usage of the percentile option enables the user to delete the outliers, such as cells with false γ-H2.AX foci induced by replication. Colocalization analyses are also possible. This option compares the localization of two foci in two different channels with a selectable tolerance
Mentions: To develop the Focinator as a tool for automated quantitative and qualitative analysis of foci with ImageJ, we first integrated a user-friendly interface. The interface (Fig. 1) includes eight buttons, a menu as well as nine shortcuts for the following commands < F1 > Automated Mode, <F2 > Options, <F3 > Thresholding, <F4 > Separation, <F5 > Selecting ROIs, <F6 > Thresholding and Selecting ROIs, <F7 > Analyzing - Foci Count, <F8 > Open Next Image in the folder. The menu also includes further information under About The Focinator and an instruction manual under Help. The second step for the development was an automated selection of the regions of interest (ROIs), such as cells or nuclei, depending on their appearance (Fig. 2). Moreover, automated detection of foci and the analysis of ROIs and foci were included (Fig. 3).Fig. 1

Bottom Line: It significantly reduced the analysis time of radiation-induced DNA-damage foci.The macro allows improved foci evaluation regarding accuracy, reproducibility and analysis speed compared to manual analysis.As innovative option, the macro offers a combination of multichannel evaluation including colocalization analysis and the possibility to run all analyses in a batch mode.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. sebastian.oeck@uk-essen.de.

ABSTRACT

Background: The quantitative analysis of foci plays an important role in many cell biological methods such as counting of colonies or cells, organelles or vesicles, or the number of protein complexes. In radiation biology and molecular radiation oncology, DNA damage and DNA repair kinetics upon ionizing radiation (IR) are evaluated by counting protein clusters or accumulations of phosphorylated proteins recruited to DNA damage sites. Consistency in counting and interpretation of foci remains challenging. Many current software solutions describe instructions for time-consuming and error-prone manual analysis, provide incomplete algorithms for analysis or are expensive. Therefore, we aimed to develop a tool for costless, automated, quantitative and qualitative analysis of foci.

Methods: For this purpose we integrated a user-friendly interface into ImageJ and selected parameters to allow automated selection of regions of interest (ROIs) depending on their size and circularity. We added different export options and a batch analysis. The use of the Focinator was tested by analyzing γ-H2.AX foci in murine prostate adenocarcinoma cells (TRAMP-C1) at different time points after IR with 0.5 to 3 Gray (Gy). Additionally, measurements were performed by users with different backgrounds and experience.

Results: The Focinator turned out to be an easily adjustable tool for automation of foci counting. It significantly reduced the analysis time of radiation-induced DNA-damage foci. Furthermore, different user groups were able to achieve a similar counting velocity. Importantly, there was no difference in nuclei detection between the Focinator and ImageJ alone.

Conclusions: The Focinator is a costless, user-friendly tool for fast high-throughput evaluation of DNA repair foci. The macro allows improved foci evaluation regarding accuracy, reproducibility and analysis speed compared to manual analysis. As innovative option, the macro offers a combination of multichannel evaluation including colocalization analysis and the possibility to run all analyses in a batch mode.

No MeSH data available.


Related in: MedlinePlus