High-Throughput Analysis of TUNEL-Stained Sperm Using Image Cytometry

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1 High-Throughput Analysis of TUNEL-Stained Sperm Using Image Cytometry E. A. Arifulin, 1,2 * E. E. Bragina, 1,3 L. F. Kurilo, 3 E. V. Sheval 1,4 1 A.N. Belozersky Institute of Physico- Chemical Biology, M.V. Lomonosov Moscow State University, Moscow , Russian Federation 2 eoples Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow , Russian Federation 3 Federal State Budgetary Institution Research Centre for Medical Genetics, Moscow, Russian Federation 4 LIA 1066 LFR2O French-Russian Joint Cancer Research Laboratory, Villejuif, Paris, France Received 10 March 2017; Revised 6 June 2017; Accepted 11 June 2017 Grant sponsor: Russian Science Foundation, Grant number: Grant sponsor: Ministry of Education and Science of the Russian Federation, Grant number: 02.A Additional Supporting Information may be found in the online version of this article *Correspondence to: Eugene A. Arifulin, A.N. Belozersky Institute of Physico- Chemical Biology, M.V. Lomonosov Moscow State University, Moscow, Russian Federation. woodruff@ belozersky.msu.ru Published online 5 July 2017 in Wiley Online Library (wileyonlinelibrary.com) DOI: /cyto.a VC 2017 International Society for Advancement of Cytometry Abstract Sperm DNA integrity is an essential factor for successful fertilization and proper pregnancy progression. The terminal deoxynucleotidyl transferase dutp nick end-labeling (TUNEL) assay is commonly used for the estimation of the DNA fragmentation index. Analysis of TUNEL-stained sperm is often performed by flow cytometry, an approach that allows high-throughput analysis but in which any morphological information is lost. In this study, results of an automated image cytometry estimation of TUNELstained sperms were presented. The results of visual counting and automatic analysis were closely correlated, indicating that image cytometry is suitable for such analysis and may be applied in a clinical setting. VC 2017 International Society for Advancement of Cytometry Key terms image cytometry; spermatozoa; DNA fragmentation; TUNEL INTRODUCTION SPERM DNA integrity is an essential factor for successful fertilization and proper pregnancy progression (1 3). The processes that mediate DNA strand breakage in sperm nuclei are obscure, but some data indicate that it may be a consequence of reactive oxygen species (ROS) attack (4,5), abnormal spermatid maturation (6,7), or apoptosis (4,8). Despite this ambiguity, the DNA fragmentation index appears to have a clinical significance (9,10). Numerous clinical studies empirically established a threshold above which DNA fragmentation is likely to be a cause of fertilization failure (10,11). Therefore, laboratory approaches for DNA integrity evaluation are widely used in the diagnosis of infertile patients. Several approaches to evaluate DNA fragmentation (10,12), including sperm chromatin structure assay (SCSA) (13,14), single-cell gel electrophoresis assay (COMET) (15,16), sperm chromatin dispersion (SCD) test in various modifications (17,18), and terminal deoxynucleotidyl transferase dutp nick end-labeling (TUNEL) (19,20) have been developed. The TUNEL assay is one of the most used methods for assessment of DNA strand breaks in both somatic (21) and sperm cells (22). This approach allows for estimating sperm DNA quality with the accuracy required by reproduction laboratories (10,12,19,20). The results of the TUNEL assay can be measured using either optical microscopy or flow cytometry (9,20). It was demonstrated that although the percentage obtained by optical microscopy and flow cytometry are different, there is a good correlation between results obtained by these techniques (9). In worldwide clinical practice, flow cytometry is a common choice for such analysis (19,23). Although microscopic analysis is usually more time and effort consuming, and does not allow the ability of gathering large amounts of statistical data, it can provide morphological information (i.e., information about sperm morphology and TUNEL nuclear localization). The distribution of DNA breaks across the nucleus, which are usually Cytometry Part A 91A: , 2017

2 ignored in clinical practice, could potentially offer information about damaged chromosome loci or even help to understand the nature of the damage. In recent years, image cytometry has become a method widely used in clinical and scientific settings, allowing researchers to combine precise image analysis with statistically reliable sampling. Image cytometry has been successfully used for DNA ploidy evaluation (24), quantitative FISH analysis (25), DNA damage detection in somatic cells (26), multiparameter analysis (27), etc. In this study, we presented results of the automated image cytometry estimation of TUNELstained sperms and demonstrated that this high-throughput method is appropriate for analysis of DNA fragmentation inside sperm nuclei. MATERIALS AND METHODS Sperm Smear Preparation Sperm samples were collected from twenty patients with normozoospermia and unidentified causes of infertility. All patients signed informed consent forms. The collected ejaculates were stored at 378C for 30 min until liquefaction. After liquefaction, samples were washed twice in PBS (MP Biomedicals, The United States). For smears preparation, we used suspensions with sperm concentration below /ml. Smears were made of 10 ml drops on polylysine covered glasses (Marienfeld-Superior, Germany) and left at room temperature until completely dried. Slides were packed in aluminum foil and stored at 2208C until the day of the experiment. We analyzed sperm morphology on air-dried fixed smears using the following criteria recommended by WHO: (a) head shape and size, number and size of vacuoles, acrosome shape; (b) midpiece length, direction comparing head major axis, and residual cytoplasm abundance; (c) tail length, thickness, shape, and integrity (28). TUNEL Staining To avoid water condensation, the samples were prewarmed to room temperature before unpacking. Dry slides were rehydrated in PBS. For DNA breaks detection we used DeadEnd Fluorometric TUNEL System kit (Promega, The United States) according to the manufacturer s protocol. Briefly, samples were fixed in 4% formaldehyde solution in PBS for 25 min at 148C, washed twice in PBS and then treated with 0.2% Triton X-100 in PBS for 5 min. After double wash in PBS, samples were incubated in equilibration buffer from the staining kit for 10 min. The reaction mix was prepared according to manufacturer s protocol. Staining was carried out at 378C for 60 min in humidified chamber protected from light. The reaction was arrested by 15 min incubation in 23SSC. After triple wash in PBS, samples were stained with DAPI (0.1 mg/ml) in PBS for 10 min and embedded in Mowiol (Calbiochem, The United States) containing an antibleaching agent, DABCO (Sigma, The United States). For negative control, we incubated an additional slide in reaction mix containing all components excluding rtdt enzyme. For positive control, the slides were treated after permeabilization with DNase I (10 units/ml) for 10 min. Image Cytometry Cytell Cell Imaging System (GE Healthcare, The United States) was used for image acquisition and analysis. Nine randomly placed fields were photographed on each sample in both FITC and DAPI channels using a Nikon 103/0.45, Plan Apo, CFI/60 objective lens. To collect all TUNEL-positive sperm cells, we had to perform two rounds of recognition procedure (Supporting Information Fig. 1). Round 1. Identification of sperm nuclei in the DAPI channel (DAPI_all in formula). Adjusting size and brightness parameters in the DAPI channel allowed us to exclude somatic nuclei, spermatids, and overlapping sperm nuclei as well as fluorescent debris. Unfortunately, pale-stained sperm nuclei were also excluded. On the second step of analysis procedure, we selected TUNEL-stained nuclei among previously identified DAPI-positive nuclei by adjustment of brightness parameter in FITC channel. Round 2. Identification of sperm nuclei in the FITC channel (TUNEL_all in formula). Here we identified all TUNEL-stained nuclei (including those that were pale-stained with DAPI) by size and brightness parameters in FITC channel. Further, adjusting brightness parameter in DAPI channel allowed us to divide all TUNELstained nuclei on DAPI-pale and DAPI-bright (DAPI_TUNEL in formula) fractions. The percentage of TUNEL positive cells was calculated by the following formula: DNA fragmentation index 5 ðtunel allþ= ðdapi all 1 TUNEL all 2 DAPI TUNELÞ: Manual Analysis For visual measurements, we selected random images acquired during image cytometry procedure and analyzed them in ImageJ software ( Such technique allows for more reproducible results than visual analysis under a microscope due to a lower influence of the observer. Since manual analysis was substantially more timeconsuming, we limited our estimation to approximately 1,000 sperms per sample. All estimations were carried out by one observer in blind experiment. Statistical Analysis All statistical analyses were carried out using GraphPad Prism 6.01 and Microsoft Excel. We used linear regression approximation to evaluate the correlation between data samples. RESULTS AND DISCUSSION TUNEL staining has the ability to detect sperm cells with fragmented DNA in smears using fluorescence microscopy. In the majority of TUNEL-positive cells, the TUNEL label was distributed homogenously through the nucleus (Fig. 1a, pattern 1), but in some cases, the TUNEL label accumulated at the nuclear periphery or inside the nucleoplasm (Fig. 1a, pattern 2). In 5.4% % (mean 6 SE) of cells demonstrating bright TUNEL staining, DAPI fluorescence was pale, Cytometry Part A 91A: ,

3 Figure 1. (A) Major patterns of sperm nucleus staining by TUNEL: Pattern 1 homogeneous DNA breaks distribution accompanied by bright DAPI fluorescence; Pattern 2 DNA breaks localize on the nuclear and vacuole periphery; Pattern 3 TUNEL staining in case of pale DAPI fluorescence. Left column contains TUNEL images, middle column DAPI images, right column merge of DAPI (blue), TUNEL (green), and phase contrast images. TUNEL stained nuclei are marked by arrowheads, reference sperm with normal DAPI fluorescence is marked by arrow. (B) Graph depicting the percentage of TUNEL-positive cells after manual and image cytometry analysis, and percentage of sperms with normal morphology. (C) Two-dimensional diagram describing linear correlation (R , P values <0.05) of fragmentation indexes obtained by manual and automatic analysis. [Colour figure can be viewed at wileyonlinelibrary.com] 856 Sperm TUNEL by image cytometry

4 indicating total DNA degradation (Fig. 1a, pattern 3). Since the positioning of chromosomes in sperm nucleus is studied (29 31), the pattern of DNA breaks can help to localize damaged genes and structures. It was also recently discussed that TUNEL staining patterns may reflect early and late stages of apoptotic degradation (32). However, different patterns of DNA break distribution may also indicate various mechanisms of DNA degradation. Determining this will be the object of our further work. Visual analysis of sperm smears is time-consuming and strongly depends on the observer s experience. Therefore, flow cytometry is a common method of choice for TUNEL analysis. In the present study, we used image cytometry for the analysis of such samples. Using this approach, it was possible to analyze thousands of cells in a relatively short amount of time, and it was only slightly slower than flow cytometry. To quantify the results of the TUNEL assay, we counted TUNELpositive and TUNEL-negative cells in images acquired by the image cytometry system. Image cytometry analysis is more throughput compared with the visual observation and potentially provides more reproducible results due to the partial automatization of the process. We examined a total of twenty different samples using an automated scanning procedure in an image cytometry system (Fig. 1b). The total amount of analyzed cells per sample varied from approximately 2,200 to 63,500 depending on sperm density in the smear. Even in cases of the lowest sperm density, it was still twice as large as the average quantity used for visual measurements (1,000 cells). The percentage of TUNEL-positive sperm cells differed depending on, if the estimation was made manually or automatically using image cytometry. The mean percentage of cells with DNA fragmentation established by image cytometry was approximately 1.5-times higher than that estimated manually (Table 1). However, we observed a strong correlation (R , P values <0.05) between the results obtained by manual and automated analysis (Fig. 1c). Similar results have been described in previous studies, where the microscopic analysis of TUNEL stained samples was compared with the flow cytometry method (9). It seems that both flow cytometry and image cytometry methods led to the higher TUNEL values as compared with the visual analysis method. Additionally, we estimated the fraction of sperm cells with morphology that would be considered normal according to WHO criteria (Fig. 1b). There was no correlation between the percentage of cells with normal morphology and TUNEL staining (R ). This observation is in agreement with other studies (9,33) where basic sperm parameters were compared with the DNA fragmentation index. This confirms that DNA fragmentation is an independent parameter, and it is impossible to select cells with DNA fragmentation based on morphological criteria. The positive correlation between TUNEL results measured by visual analysis and cell cytometry indicates that the data obtained by the latter method can be used for sperm analysis. However, it requires certain conditions to be met. We found that the accuracy of calculation strongly depends on Table 1. Overall statistical descriptors for all samples Manual counting Image cytometry Normal morphology MEAN SD MINIMUM MAXIMUM SAMPLE SIZE MEAN (CELL) , , smear quality. In high-density samples, neighboring cells could sometimes be identified as one, and in low-density smears, more time was required for analysis. Uniform smears with moderate density are preferable. Moreover, the purity of cell suspension influences the quality of staining since the presence of slime significantly lowers fluorescent contrast. 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