AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED ...

FULL FULL ARTICLE ARTICLE

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING

Proper evaluation of the health risks of low-dose ionizing radiation exposure heavily relies on the ability to

Dmitry Klokova* and Roopa Suppiahb

accurately measure very low levels of DNA damage in cells. One of the most sensitive methods for measuring DNA damage levels is the quantification of DNA repair

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

foci that consist of macromolecular aggregates of DNA repair proteins, such as γH2AX and 53BP1, forming around individual DNA double-strand breaks. They can be quantified using immunofluorescence microscopy and are widely used as markers of DNA double-strand breaks. However this quantification, if performed manually, may be very tedious and prone to inter-individual bias. Low-

a Radiological Protection Research and Instrumentation, Canadian Nuclear Laboratory, 1 Plant Rd, Chalk River, ON K0J1P0, Canada b Department of Biomedical and Molecular Sciences, Queen’s University, 99 University Ave, Kingston, ON K7L 3N6, Canada

Article Info Keywords: DNA damage; DNA repair foci; low-dose radiation; mammalian cell culture; image analysis; quantification; automation Article History: Received 16 February 2015, Accepted 13 April 2015, Available online 3 June 2015. DOI: http://dx.doi.org/10.12943/ANR.2015.00042 *Corresponding author: [email protected]

dose radiation studies are especially sensitive to this potential bias due to a very low magnitude of the effects anticipated. Therefore, we designed and validated an

Introduction

algorithm for the semi-automated processing of

Accurate evaluation of health risks associated with exposure to low doses (≤100 mGy) of ionizing radiation represents a major challenge.

microscopic images and quantification of DNA repair foci. The algorithm uses ImageJ, a freely available image analysis software that is customizable to individual cellular properties or experimental conditions. We validated the algorithm using immunolabeled 53BP1 and γH2AX in normal human fibroblast AG01522 cells under both normal and irradiated conditions. This method is easy to learn, can be used by nontrained personnel, and can help avoiding discrepancies in inter-laboratory comparison studies examining the effects of low-dose radiation.

Because measuring cancer rates in animal models is associated with a high cost and requires lengthy studies, most often DNA damage endpoints are used as biological indicators in low-dose radiation studies. Exposure to ionizing radiation can induce a wide variety of DNA lesions such as DNA base modifications, DNA inner- and inter-strand cross-links, DNA−histone cross-links, and DNA single-strand and double-strand breaks [1]. It is widely accepted that a DNA double-strand break (DSB) is the most deleterious type of DNA damage. If not repaired, even a single DSB can lead to cell death [2, 3]. Also, improper repair of a DNA DSB may lead to various types of chromosomal aberrations that are characteristic of many types of tumor cells [4]. Therefore, for evaluating biological consequences of low-dose radiation related to cancer, being able to accurately measure DNA DSB in various experimental models is useful. Since the 1998 discovery of γH2AX [5], a phosphorylated histone H2AX that is produced in response to DNA DSB formation, research in the area of DNA damage and repair has exploded [6]. Not only this has led to many discoveries resulting in the current comprehensive knowledge of early molecular events, their sequence, and participating proteins following the formation of DNA breaks after irradiation, but this has also provided researchers with a very powerful tool to study dose–response relationships of many genotoxic substances. It has become possible because each DNA DSB could be visualized by fluorescence microscopy using immuno-labeled γH2AX, which forms large aggregates around each individual DSB. Those aggregates are seen on microscopic images as nuclear foci, also referred to in literature as ionizing radiation-induced foci [7]. In addition to γH2AX, other proteins have been shown to form foci that co-localize with DNA DSB. These include Rad51 [8], 53BP1 [9], NBS complex [10], and others [11]. All of them have specific roles in DNA DSB sensing, signalling, chromatin modification, and repair [7]. However, the most widely used markers of DNA DSB are γH2AX and 53BP1 foci [12, 13]. AECL NUCLEAR REVIEW

75

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

76

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

Quantification of foci allows detection of effects induced by a radiation dose as low as 1 mGy [14]. However, because quantification of foci is most often done by manual counting (by eye), it is associated with a number of disadvantages. The most important among them are very long analysis times (due to the tedious nature of this work), the requirement of highly trained personnel, and individual-related bias. Additionally, other information such as foci size and intensity that can be helpful for understanding mechanisms of DNA repair is missing from manual scoring. This has led to efforts to automate foci quantification using computerized approaches. Various solutions have been proposed, varying from the standalone FociCounter [15] to specialized high throughput processing platforms [16]. These provided certain benefits, such as time savings, the lack of operator subjectivity, and others; however, many limitations still exist. FociCounter requires substantial operator time and focused work and lacks a batch regime [15], the RABiT (Rapid Automated Biodosimetry Tool for Radiological Triage) system is an expensive platform that is custom built and is not yet available commercially [17]. Other approaches require images that are generated by expensive confocal microscopy [18], adapted for specific types of cells [19], or not freely available [20]. The purpose of this study was to develop an algorithm for a freely available image analysis software that would allow computerized counting of foci and would be capable of using images produced by a regular fluorescent microscope. This algorithm should yield results comparable with conventional manual foci counting and be adjustable to particular properties of cells used or foci types scored. Materials and Methods Reagents Dulbecco’s modified Eagle’s medium (DMEM) medium was purchased from HyClone (Fisher Scientific, Toronto, Ontario). Methanol was purchased from Commercial Alcohols, Inc (Brampton, Ontario). Vectashield mounting medium was obtained from Vector Labs (Burlington, Ontario). Paraformaldehyde, L-glutamine, penicillin, and streptomycin were purchased from Sigma-Aldrich Canada. DAPI (4′,6-diamidino −2-phenylindole dihydrochloride hydrate) was purchased from Invitrogen (Burlington, Ontario). Bovine serum albumin (BSA) was obtained from VWR Canada and fetal bovine serum (FBS) was purchased from Gibco (Invitrogen, Burlington, Ontario). Mouse antibody (2F3) against H2AX (phospho S139) was from Abcam (Cambridge, Massachusetts) and rabbit antibody against 53BP1 (sc-22760) was from Santa Cruz Biotechnology, Inc (Santa Cruz, California). Secondary goat anti-mouse Alexa-488 IgG conjugate antibody and secondary goat anti-rabbit Alexa−594 IgG conjugate antibody were purchased from Invitrogen (Burlington, Ontario).

Cell culture and irradiation Normal human fibroblast AG01522 cells were obtained from a local liquid nitrogen cell culture stock maintained at the Canadian Nuclear Laboratories. The cells had a recorded passage 11 indicating that they were far from the senescence state, which was confirmed by their ability to normally grow and double every 2 days. AG01522 cells were maintained by weekly sub-culturing in DMEM, supplemented with 10% FBS, at 37 °C in a 5% CO2–95% air atmosphere. Sub-confluent, exponentially growing cells were used in the experiments. Exponentially growing cells were seeded onto 30 mm petri dishes containing 22 mm × 22 mm sterile glass coverslips and were allowed to attach overnight. The next day, AG01522 cells were exposed to 2 Gy of gamma-radiation at room temperature using a GammaCell-220 irradiator (Atomic Energy Canada Limited, Ontario) equipped with 60 Co γ-ray source at a dose rate of 6.6 Gy/min. Immediately after irradiation the cell cultures were returned to the CO2 incubator and incubated for either 1 h or 24 h at which point the cells were sampled for immunofluorescence microscopy. Immunofluorescence microscopy After either 1 h or 24 h of incubation, irradiated cells were fixed in 2% paraformaldehyde in Tris buffered saline (TBS) for 30 min at room temperature. At the time of fixation, cell cultures were 40%–60% confluent. Cells were then rinsed in TBS and −20 °C methanol was added to cells for 1 min, followed by blocking cells in TBS-Tween (TTN) buffer (1% BSA, 0.2% Tween-20 in TBS) for 30 min at room temperature. Coverslips with cells were incubated in anti-γH2AX mouse antibody diluted 1:600 in TTN or anti-53BP1 antibody diluted 1:500 in TTN for 2 h at room temperature. After rinsing with TBS and blocking with TTN for 20 min, cells were stained for 1 h at room temperature with secondary goat antimouse Alexa-488 antibody (for γH2AX) at 1:600 dilution in TTN or with secondary goat antirabbit Alexa-594 antibody (for 53BP1) at 1:600 dilution in TTN. The coverslips were rinsed, immersed in 0.05 µg/mL DAPI in TBS, mounted on microscope slides using Vectashield mounting medium, and then sealed with nail polish. Slides were analyzed using a Zeiss Axioplan-2 fluorescent microscope equipped with a Neofluor 100× oil immersion objective. Five optical Z-sections (0.5 µm/section) per nucleus were captured using the Northern Eclipse software. Exposure times for untreated and irradiated samples were kept identical. Fifty cells per sample were imaged. Image analysis Freely available ImageJ software was used for all image manipulation and analyses (available from http://imagej. nih.gov/ij/). For manual quantification of 53BP1 foci, images were generated by projection of a maximum intensity algorithm from 5 optical Z-sections per cell followed by deconvolution. Foci were then scored manually from a computer screen. For automatic quantification, an ImageJ macro script was generated that included the initial steps as above (maximum intensity projection and deconvolution) followed by

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

thresholding, creating a binary mask, and counting the foci (Figure 1).

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

Results and Discussion Gamma-radiation produces around 20 DNA DSB per 1 Gy per mammalian genome [21]. It is expected that each DSB results in one DNA repair focus [22]. It follows then that it is expected that around 20 foci need to be resolved by immunofluorescence microscopy to accurately quantify DNA damage. Because of the cell nucleus depth, one needs to capture a number of images at various Z-planes spanning the entire nucleus depth to collect sharp images of all foci. The depth and the number of Z-planes would vary depending on cell type, with adherent cells characterized by flat morphology requiring fewer Z-planes compared with suspension cells such as lymphocytes. The best image quality can be achieved by using a scanning laser confocal microscope, because its design specifically cuts off optical signal that originates outside of a specific Z-plane, i.e., out-of-focus signal, resulting in very sharp images. However, confocal microscopes are very expensive and are not available to many laboratories. Instead, a regular fluorescence microscope can be used to generate the required number of Z-planes. If a focus lies outside of a specific Z-plane its signal can still be present on a corresponding image as a blurry spot if it is

not too far from the Z-plane (Figure 2). However, a focus will not be present on an image at all, if it lies too far from the Z-plane. When 1 image is generated from a stack of captured Z-planes using maximum intensity projection, it needs an additional step of deconvolution to remove the blurriness from out-of-focus signal and to enhance the sharpness of all the DNA repair foci (Figure 2). The quality of the generated final image, although still lower compared with the quality of an image produced by confocal microscopy, is sufficient for reliable foci quantification. Figure 3 shows representative images of nonirradiated or irradiated with 2 Gy γ-rays AG01522 cells immuno-labelled with γH2AX (green signal) or 53BP1 (red signal). It can be seen that nonirradiated control cells are characterized by a homogenous pan-staining within the cell nuclei. In contrast, a foci-like pattern was observed in irradiated cells for both γH2AX and 53BP1. All images in Figure 3 were made using conventional fluorescence microscopy (5 Z-planes per nucleus at 0.5 µm increments) followed by stacking the Z-planes, calculating the resulting image using the maximum intensity projection, and deconvolving the projection image. For image manipulations, the ImageJ software was used. It is a very powerful, yet freely distributed software that was developed by scientists for scientists [23]. It allows the user to build custom-made macros, a set of commands that

FIGURE 1. Diagram of a process of foci quantification. First block represents microscopic imaging, with 5 Z-planes captured that will cover an entire nucleus of the most mammalian adherent cell types. Then collected Z-planes can be processed manually using ImageJ software as described in Figure 2, followed by a manual by eye count of foci. Alternatively, a macro for ImageJ was proposed and generated that enables automated processing of the images using same algorithms as in manual processing supplemented with additional algorithms steps, including foci count. AECL NUCLEAR REVIEW

77

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

FIGURE 2. Diagram of a cell with foci and an imaging principle. Nuclear depth necessitates capturing several Z-planes using a microscope and an attached camera to cover all or most of the fcoi per nucleus. Z-planes will have various quality foci signal, from in-focus to out-of-focus or absent. Image processing software creates a Z-stack using all the Z-planes and creates a composite maximum intensity projection image which is then deconvolved to enhance foci image quality. The resulting image can be used for foci counting, either manually or using computer software.

can be executed automatically, for specific purposes. It is this ability that was used in this study to automate DNA repair foci counting in irradiated cultured cells. First, to automate initial image manipulations (Z-stack generation and deconvolution), the following commands were incorporated into the macro: 1. // comments go here; start processing folder 01 2. open(“C:\\...\\53BP1-cell-01\\1.tif”); 3. open(“C:\\...\\53BP1-cell-01\\2.tif”); 4. open(“C:\\...\\53BP1-cell-01\\3.tif”); 5. open(“C:\\...\\53BP1-cell-01\\4.tif”); 6. open(“C:\\...\\53BP1-cell-01\\5.tif”); 7. run(“Images to Stack”); 8. run(“Z Project...”, “start=1 stop=5 projection=[Max Intensity]”); 9. run(“16-bit”); 10. run(“Iterative Deconvolution”, “operation=Deconvolve image=MAX_Stack point=MAX_Stack number=5 lp=1 monotonic”); where “C:\\ANR-2015-paper\\53BP1-cell-01\\” is an example of the location of the original 5 Z-planes (note that

78

FIGURE 3. Representative microphotographs of human cells with foci. AG01522 cells, nonirradiated (control) or 1 h after 2 Gy gamma-irradiation were immuno-stained with antiγH2AX or anti-53BP1 antibody.

here and in subsequent descriptions of macro commands, line numbers are given for convenience of discussion and should not be used in the actual macro). In our study we used 50 cells per sample, meaning that 50 separate folders named “53BP1-cell−01” to “53BP1-cell−50” with raw images were created. Therefore, 50 corresponding blocks with the commands 2–10 should be included in the macro, which is a simple task using copy, paste, and replace commands in any text editor. Then, the final deconvolved image is saved as a 16-bit format image (required for subsequent image manipulations) and as a pseudo-colored image for presentation purposes (examples are shown in Figure 3). This is done using the following strings: 11. run(“16-bit”); 12. saveAs(“tif”, “C:\\...\\01_tif_ for_thresholding.tif”); 13. run(“Red”); 14. run(“RGB Color”); 15. saveAs(“tif”, “C:\\...\\01_53BP1_ processed.tif”); 16. close(); 17. close(); 18. close(); Then, the following commands perform final image manipulations and foci counting: 19. open(“C:\\...\\01_tif_for_ thresholding.tif”);

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

setAutoThreshold(“Yen dark”); setOption(“BlackBackground”, false); run(“Convert to Mask”); run(“Watershed”); run(“Analyze Particles...”, “size=20-Infinity circularity=0.00–1.00 show=Nothing display clear summarize”); 25. close();

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

20. 21. 22. 23. 24.

The command in line 20 uses a threshold algorithm called “Yen dark” that is included in the default set of ImageJ threshold algorithms and is best suited to discriminate signal-positive from signal-negative areas of the DNA repair foci image. Using this algorithm, as opposed to a simple linear thresholding, allows accurate inclusion of foci with very different absolute intensity levels. The line 21 command ensures that it is foci, not the background, that are taken as

positive areas to be included in a mask in the next step. Then the image is converted to a binary mask image (with only 2 possible pixel values) that separates all the pixels to either belonging to a focus or not. The function “Watershed” (line 23) separates overlapping foci. And finally, the function “Analyze particles”, also included in the default ImageJ package, counts the number of foci. Proper adjustment of the parameter “size” within this function is essential and should be changed depending on a specific foci type that is being analyzed. For example, 53BP1 is known to form larger size foci compared with γH2AX (compare the 2 foci types on Figure 3), thus the size will need an adjustment when switching from γH2AX to 53BP1. Once this parameter is optimized and verified by comparing result of the computer counts with the manual (by eye) results on 1 or 2 deconvolved images, it can be used for the entire set of images within a study or experiment. A window with foci counting results is

FIGURE 4. ImageJ macro developed and tested in this study. The text in black represents comments that are useful for description of particular commands or block of commands and the text in blue is the macro itself. The first 23 lines represent the main building block of the entire macro. It is repeated 50 times for each of the 50 cells with the unique location of raw Z-planes. Changes to be made in each of the 50 blocks include folder names where the Z-planes are stored and the file name for processed and thresholding images; these are highlighted in green. The parameter value that should be optimized depending on the type of foci to be analyzed, e.g., 53BP1 foci vs. γH2AX foci, and that should be validated empirically for every experiment is in red. The last 2 lanes save results to an excel file and the destination folder and the file name may be changed. AECL NUCLEAR REVIEW

79

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

displayed at the end. The results can also be automatically saved by incorporating the following commands at the end of the entire macro (after the 50 blocks of image processing and foci counting, Figure 4):

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

26. // comments go here; final block saves the results to an excel file 27. selectWindow(“Summary”); 28. saveAs(“Measurements”, “C:\\...\\focicount-results.xls”); The overall diagram of the macro is shown in Figure 4. If the resulting macro is saved as a file with the “ijm” extension in the directory C:\Program Files\ImageJ\plugins, it will be installed in the Plugins menu and in the toolbar when ImageJ starts. Alternatively, the macro can be saved anywhere (e.g., in a specific experimental folder) as a plain text file (with the “txt” extension) and run manually by selecting it from Plugins>Macro>Run. Apparently, some inconvenience may be experienced if the file paths for original raw Z-planes need to be changed for every new experiment. To avoid this, it is recommended that the Z-planes are copied from their original experiment-

specific location into a temporary folder to be used only for the analysis by the presented macro. Upon completion of the analysis, images should be deleted to make room for the next sample images or for images from an entirely different experiment or study. Next, an experiment was carried out to validate the developed semi-automated foci counting method. AG01522 cells were sham-irradiated (control) or irradiated with 2 Gy gamma-radiation. At 1 h when foci numbers reach their maximum and at 24 h when the repair of DNS DSB is complete and foci disappear, the cells were fixed and immuno-labelled with anti-53BP1 antibody. Foci were scored either manually by eye using images generated at line 12 of the macro or by using the entire macro. The results indicate that the semiautomated foci counting method generates scores that are almost identical to those produced by a manual scoring method for all the groups examined (Figure 5A). Estimates of time requirements for both methods showed that the presented algorithm using the ImageJ macro took about 5 min per treatment group (50 images), including the time required for optimizing the size of a focus to use in line 24. Manual image processing and counting took on average

FIGURE 5. Comparison of manual vs. automated foci counts. AG01522 cells were sham- or gamma-irradiated, fixed and immunolabelled for 53BP1. Images were captured, processed, and quantified manually or using an ImageJ macro as described in Figures 1 and 4. Numbers of 53BP1 foci per cell generated by manual or automated counts (A) and comparison of time requirements for both counting methods and an estimate of efficiency of the automated method relative to the manual method (B) are shown. 80

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

100 min per group. Thus, the increase in the efficiency of the presented computer-based method of foci counting was 20fold compared with the manual counting (Figure 5B). Often studies of the effects of low dose radiation require, in addition to multiple doses, multiple time points after irradiation to get insights in the DNA repair kinetics and processes. For example, a detailed kinetics of DNA DSB repair requires 8 time points [24]. This significantly increases the number of samples that need to be quantified and, hence, the time required for laborious and tedious manual foci counting. This macro developed for ImageJ software significantly reduces the time for such analyses and increases the accuracy and resolution of the experiments by using more time-points and doses in a study, not to mention reducing individual-related bias in scoring.

Conclusions We presented a semi-automated method for DNA repair foci counting based on the processing of raw microscopy images using ImageJ software. The automation is represented by a macro specifically built for processing 250 raw cell images to produce 50 enhanced quality cell images to visualize foci and for counting the number of foci. The macro uses the standard functions of ImageJ and does not require knowledge of computer programming language. It is able to generate foci count results for 50 cells in less than 5 min and saves the results in an excel file. The use of this method and the macro is expected to significantly improve the quality of studies examining effects of low-dose radiation at the level of DNA damage and repair in human and mouse cells and tissues. It does not require highly expensive equipment (e.g., confocal laser scanning microscope or high-throughput high-content image analysis systems) or software packages (ImageJ is free software), and it should be available for any lowto-middle budget laboratory. Finally, by allowing the use of multiple time and dose points, thus improving resolution and accuracy of experiments, this method can contribute to generating the knowledge that is lacking on the effects of low-dose radiation.

REFERENCES [1] P. Jeggo and M. Lobrich, 2006, “Radiation-induced DNA Damage Responses”, Radiation Protection Dosimetry, 122(1–4), pp. 124–127. doi: 10.1093/rpd/ncl495. [2] J.H. Hoeijmakers, 2001, “Genome Maintenance Mechanisms for Preventing Cancer”, Nature, 411(6835), pp. 366–374. PMID: 11357144. doi: 10.1038/ 35077232. [3] D.C. van Gent, J.H. Hoeijmakers and R. Kanaar, 2001, “Chromosomal Stability and the DNA Double-stranded Break Connection”, Nature Reviews Genetics, 2(3), pp. 196–206. doi: 10.1038/35056049. [4] D.G. Albertson, C. Collins, F. McCormick and J.W. Gray, 2003, “Chromosome Aberrations in Solid Tumors”, Nature Genetics, 34(4), pp. 369–376. doi: 10.1038/ng1215.

[5] E.P. Rogakou, D.R. Pilch, A.H. Orr, V.S. Ivanova and W.M. Bonner, 1998, “DNA Double-stranded Breaks Induce Histone H2AX Phosphorylation on Serine 139”, Journal of Biological Chemistry, 273(10), pp. 5858–5868. doi: 10.1074/jbc.273.10.5858. [6] J. Lukas, C. Lukas and J. Bartek, 2011, “More Than Just a Focus: The Chromatin Response to DNA Damage and Its Role in Genome Integrity Maintenance”, Nature Cell Biology, 13(10), pp. 1161–1169. PMID: 21968989. doi: 10.1038/ncb2344. [7] T.T. Paull, E.P. Rogakou, V. Yamazaki, C.U. Kirchgessner, M. Gellert and W. M. Bonner, 2000, “A Critical Role for Histone H2AX in Recruitment of Repair Factors to Nuclear Foci After DNA Damage”, Current Biology: CB, 10(15), pp. 886–895. [8] T. Haaf, E.I. Golub, G. Reddy, C.M. Radding and D.C. Ward, 1995, “Nuclear Foci of Mammalian Rad51 Recombination Protein in Somatic Cells After DNA Damage and Its Localization in Synaptonemal Complexes”, Proceedings of the National Academy of Sciences USA, 92(6), pp. 2298–2302. [9] D.J. Derbyshire, B.P. Basu, L.C. Serpell, W.S. Joo, T. Date, K. Iwabuchi and A.J. Doherty, 2002, “Crystal Structure of Human 53BP1 BRCT Domains Bound to p53 Tumour Suppressor”, EMBO Journal, 21(14), pp. 3863–3872. doi: 10.1093/emboj/cdf383. [10] R.S. Maser, K.J. Monsen, B.E. Nelms and J.H. Petrini, 1997, “hMre11 and hRad50 Nuclear Foci Are Induced during the Normal Cellular Response to DNA Double-strand Breaks”, Molecular and Cellular Biology, 17(10), pp. 6087–6096. [11] S. Bekker-Jensen and N. Mailand, 2010, “Assembly and Function of DNA Double-strand Break Repair Foci in Mammalian Cells”, DNA Repair (Amst), 9(12), pp. 1219–1228. PMID: 21035408. doi: 10.1016/j. dnarep.2010.09.010. [12] M. Moroni, D. Maeda, M.H. Whitnall, W.M. Bonner and C.E. Redon, 2013, “Evaluation of the Gamma-H2AX Assay for Radiation Biodosimetry in a Swine Model”, International Journal of Molecular Sciences, 14(7), pp. 14119–14135. doi: 10.3390/ijms140714119. [13] E. Flockerzi, S. Schanz and C.E. Rube, 2014, “Even Low Doses of Radiation Lead to DNA Damage Accumulation in Lung Tissue According to the Genetically-defined DNA Repair Capacity”, Radiotherapy & Oncology, 111(2), pp. 212–218. PMID: 24746565. doi: 10.1016/j.radonc.2014.03.011. [14] K. Rothkamm and M. Lobrich, 2003, “Evidence for a Lack of DNA Doublestrand Break Repair in Human Cells Exposed to Very Low x-ray Doses”, Proceedings of the National Academy of Sciences USA, 100(12679524), pp. 5057–5062. PMID: 12679524. doi: 10.1073/pnas.0830918100. [15] A. Jucha, A. Wegierek-Ciuk, Z. Koza, H. Lisowska, A. Wojcik, M. Wojewodzka and A. Lankoff, 2010, “FociCounter: A Freely Available PC Programme for Quantitative and Qualitative Analysis of Gamma-H2AX Foci”, Mutation Research, 696(1), pp. 16–20. PMID: 20018253. doi: 10.1016/ j.mrgentox.2009.12.004. [16] G. Garty, Y. Chen, A. Salerno, H. Turner, J. Zhang, O. Lyulko, A. Bertucci, Y. Xu, H. Wang, N. Simaan, G. Randers-Pehrson, Y.L. Yao, S.A. Amundson and D.J. Brenner, 2010, “The RABIT: A Rapid Automated Biodosimetry Tool for Radiological Triage”, Health Physics, 98(2), pp. 209–217. PMID: 20065685. doi: 10.1097/HP.0b013e3181ab3cb6. [17] H.C. Turner, P. Sharma, J.R. Perrier, A. Bertucci, L. Smilenov, G. Johnson, M. Taveras, D.J. Brenner and G. Garty, 2014, “The RABiT: High-throughput Technology for Assessing Global DSB Repair”, Radiation and Environmental Biophysics, 53(2), pp. 265–272. PMID: 24477408. doi: 10.1007/s00411014-0514-0. [18] W. Bocker and G. Iliakis, 2006, “Computational Methods for Analysis of Foci: Validation for Radiation-induced Gamma-H2AX Foci in Human Cells”, Radiation Research, 165(1), pp. 113–124. PMID: 16392969. doi: RR3486[pii]. [19] A.N. Ivashkevich, O.A. Martin, A.J. Smith, C.E. Redon, W.M. Bonner, R.F. Martin and P.N. Lobachevsky, 2011, “GammaH2AX Foci as a Measure of DNA Damage: A Computational Approach to Automatic Analysis”, Mutation Research, 711(1–2), pp. 49–60. PMID: 21216255. doi: 10.1016/j. mrfmmm.2010.12.015. [20] E. Markova, N. Schultz and I.Y. Belyaev, 2007, “Kinetics and Dose-response of Residual 53BP1/gamma-H2AX Foci: Co-localization, Relationship with DSB Repair and Clonogenic Survival”, International Journal Radiation Biology, 83(5), pp. 319–329. PMID: 17457757. doi: 10.1080/ 09553000601170469.

AECL NUCLEAR REVIEW

81

AECL NUCLEAR REVIEW VOL 4, NUMBER 1, JUNE 2015

AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING – DMITRY KLOKOV AND ROOPA SUPPIAH

AECL Nuclear Review Downloaded from pubs.aecl.ca by Canadian Science Publishing on 08/24/15 For personal use only.

[21] L.R. van Veelen, T. Cervelli, M.W. van de Rakt, A.F. Theil, J. Essers and R. Kanaar, 2005, “Analysis of Ionizing Radiation-induced Foci of DNA Damage Repair Proteins”, Mutation Research, 574(1–2), pp. 22–33. PMID: 15914204. doi: 10.1016/j.mrfmmm.2005.01.019. [22] E.P. Rogakou, C. Boon, C. Redon and W.M. Bonner, 1999, “Megabase Chromatin Domains Involved in DNA Double-strand Breaks in Vivo”, Journal of Cell Biology, 146(10477747), pp. 905–916. PMID: 10477747.

82

[23] C.A. Schneider, W.S. Rasband and K.W. Eliceiri, 2012, “NIH Image to ImageJ: 25 Years of Image Analysis”, Nature Methods, 9(7), pp. 671–675. PMID: 22930834. [24] M.S.J. Blimkie, L.C.W. Fung, E.S. Petoukhov, C. Girard and D. Klokov, 2014, “Repair of DNA Double-Strand Breaks is Not Modulated by LowDose Gamma Radiation in C57BL/6J Mice”, Radiation Research, 181(5), pp. 548–559. PMID: 24785832. doi: 10.1667/rr13324.1.