Quantifying Replication Stress in Ovarian Cancer Cells Using Single-Stranded DNA Immunofluorescence

Summary

Here, we describe an immunofluorescence-based method to quantify the levels of single-stranded DNA in cells. This efficient and reproducible method can be utilized to examine replication stress, a common feature in several ovarian cancers. Additionally, this assay is compatible with an automated analysis pipeline, which further increases its efficiency.

Abstract

Replication stress is a hallmark of several ovarian cancers. Replication stress can emerge from multiple sources, including double-strand breaks, transcription-replication conflicts, or amplified oncogenes, inevitably resulting in the generation of single-stranded DNA (ssDNA). Quantifying ssDNA, therefore, presents an opportunity to assess the level of replication stress in different cell types and under various DNA-damaging conditions or treatments. Emerging evidence also suggests that ssDNA can be a predictor of responses to chemotherapeutic drugs that target DNA repair. Here, we describe a detailed immunofluorescence-based methodology to quantify ssDNA. This methodology involves labeling the genome with a thymidine analog, followed by the antibody-based detection of the analog at the chromatin under non-denaturing conditions. Stretches of ssDNA can be visualized as foci under a fluorescence microscope. The number and intensity of the foci directly co-relate with the level of ssDNA present in the nucleus. We also describe an automated pipeline to quantify the ssDNA signal. The method is rapid and reproducible. Furthermore, the simplicity of this methodology makes it amenable to high-throughput applications such as drug and genetic screens.

Introduction

Genomic DNA is frequently exposed to multiple assaults from various endogenous and exogenous sources¹. The frequency of endogenous damage directly correlates with the levels of metabolic byproducts, such as reactive oxygen species or aldehydes, which are intrinsically higher in multiple cancer types, including ovarian cancers^2,3. It is imperative that DNA damage is efficiently resolved; otherwise, it can foster genotoxic lesions and, consequently, mutagenesis. The ability of cells to repair genotoxic lesions is reliant on the functionality of error-free DNA repair pathways and the efficient regulation of cell cycle progression in response to DNA damage. Notably, many ovarian cancers bear functionally inactivating mutations in p53 and, thus, have a defective G1/S checkpoint, leading the cells to initiate DNA replication despite the presence of unrepaired genomic lesions^4,5. The degree of DNA damage in ovarian cancers is further compounded by the observation that more than 50% of high-grade serous ovarian carcinoma (HGSOC) have defects in BRCA1- and BRCA2-mediated homologous recombination, the error-free DNA repair pathway, and around 20% have amplification in the gene CCNE1, which prematurely pushes G1 cells into the S-phase⁶. Together the high frequency of endogenous DNA damage, defective checkpoints, and malfunctioning repair pathways exponentially enhance the accumulation of genomic lesions in ovarian cancers. These lesions can serve as impediments to the progression of critical cellular processes such as DNA replication and transcription. As discussed below, such impediments catalyze the generation of single-stranded DNA (ssDNA) in cells.

The double helix of DNA is critical for safeguarding the genome from multiple mutagenic processes, such as spontaneous depurination and depyrimidination, the activity of cytosine deaminases, and oxidative DNA damage^1,7. In contrast, ssDNA is highly vulnerable to these mutational events. Multiple processes in cells can result in the generation of ssDNA (Figure 1). These include the following:

(i) Stalling of the DNA replication machinery: This leads to an uncoupling of the DNA helicase and polymerase, leaving stretches of ssDNA^8,9.

(ii) Stalling of the transcription machinery: Persistent stalling of RNA polymerase leads to the generation of three-stranded hybrid DNA/RNA structures called R-loops. R-loop formation exposes the displaced, non-transcribed DNA as a single strand¹⁰.

(iii) DNA end-resection: The initiation of homology-directed repair requires the generation of a 3' ssDNA to catalyze the search for a homologous sequence¹¹.

(iv) D-loop: Strand invasion during homologous recombination can result in the displacement of the non-template complementary strand, resulting in ssDNA¹².

(v) Replication-coupled gaps: During DNA replication, lagging strand synthesis happens in a discontinuous fashion, whereby Okazaki fragments are first generated and then ligated. A delay or defect in processing the Okazaki fragments can also result in ssDNA formation. Finally, if the replication fork on a leading strand encounters a stalling lesion, DNA polymerase, and primase, PRIMPOL can reprime the synthesis downstream, leaving an ssDNA gap behind^13,14.

Evidently, most of these events either happen when the DNA replication machinery faces genomic lesions or during replication-coupled repair, suggesting that higher DNA damage leads to increased levels of ssDNA. As many of these events are replication-associated, the formation of ssDNA is considered the marker of "replication stress" in cells^15,16.

Here, we describe an assay that can be used to reliably quantify ssDNA in cells. The simplicity, reproducibility, and cost benefits of this approach make it amenable to be used for assessing the replication-stress response in cells. Emerging studies have revealed that the level of ssDNA can also be a predictor of responses to chemotherapy, such as inhibitors of PARP1/2 enzymes, ATR, and Wee1 kinase^{17,18,19,20,21}. These inhibitors are being pursued in the treatment regimen of several HGSOCs²². Therefore, this assay can also be a useful tool to predict chemotherapeutic responses in ovarian cancer cells.

Protocol

NOTE: The ovarian cancer cell line, OVCAR3, was used in these steps, but this protocol is broadly applicable to multiple other cell lines, including those derived from non-ovarian sources. A schematic of the protocol is shown in Figure 2.

1. Plating the cells

1. Make poly-L-lysine coated coverslips.
   1. Add autoclaved 12 mm diameter coverslips to a 50 mL conical tube with poly-L-lysine solution, and place on a rocker for 15 min.
   2. Aspirate the solution in a tissue culture hood. Wash the coverslips by adding sterile water, and place the tube containing the coverslips back on the rocker for 5 min. Repeat this wash step three times.
   3. Spread the coated coverslips on a sterile dish, and aspirate any remaining water. Let the coverslips dry in the tissue culture hood for 1 h or until no water droplets remain. Once dry, seal the dish with parafilm, and place at 4 °C.
2. Place one poly-L-lysine-coated coverslip in each well of a 24-well plate. The use of poly-lysine coverslips is critical to prevent the detachment of the cells from the coverslips during the pre-extraction step.
3. Trypsinize OVCAR3 cells once they reach 70%-80% confluency.
   1. To trypsinize a 10 cm culture dish that is 70%-80% confluent, aspirate the medium from the plate, and wash with 5-7 mL of PBS.
   2. Aspirate the PBS, add 1 mL of 0.25% trypsin, and place the dish in a 37 °C incubator for 8-10 min, or until cells lift off from the bottom of the plate.
   3. Collect the cells with 5-10 mL of medium, and add to a conical tube.
   4. Count the cells manually with a hemocytometer using standard procedures.
4. Make a dilution of 25,000 cells/mL, and add 1 mL of the cells on poly-L-lysine coverslips placed in the wells of 24-well plates. For any other cell line, determine a number such that the cells are about 70%-80% confluent after three population doublings.
5. Grow the cells in the culture medium under standard conditions.

2. Pulsing cells with IdU

1. For the cells to properly spread onto the coverslips, one population doubling is enough. After one population doubling, pulse the cells with 10 µM 5-iodo-2'-deoxyuridine (IdU) (see Table of Materials on how to reconstitute IdU) for the two subsequent population doublings.
   NOTE: We have tried different thymidine analogs, including bromodeoxyuridine (BrdU), 5-chloro-2′-deoxyuridine (CIdU), and IdU. Amongst the three analogs, IdU gives the best signal-to-noise ratio. Comparative images of cells pulsed with the three different analogs are shown in Figure 3. We recommend the use of two negative controls: (i) a no IdU pulsed sample, and (ii) a no primary antibody control. If the formation of ssDNA needs to be assessed due to a given treatment, we recommend adding the drug after the first round of IdU doubling.
2. After pulsing with IdU for two population doublings, harvest the cells for imaging.
   1. Replace the medium with ice-cold 0.5% PBSTx (PBS + 0.5% Triton X-100) on ice for 5 min. This pre-extraction step helps to release cytoplasmic and non-chromatin-bound proteins, leaving chromatin-bound proteins intact. Certain cell lines can easily peel off during pre-extraction. In such a scenario one can use 0.5% CSK buffer (10 mM PIPES (pH 6.8),100 mM NaCl, 300 mM sucrose, 3 mM MgCl₂, 1 mM EGTA and 0.5% Triton X-100).

3. Fixation

1. Aspirate PBSTx, and incubate for 15 min with 3% PFA (Table of Materials) at room temperature, followed by three to four washes with 1x PBS. The fixed cells can be kept at 4 °C until further steps.
   ​CAUTION: PFA is highly toxic and carcinogenic. Avoid contact with skin, eyes, and mucous membranes. Perform all the steps with PFA in a fume hood, and dispose of the materials properly.

4. Permeabilization and blocking

1. After fixation, permeabilize the cells using 0.5% PBSTx on ice for 5 min. Use enough volume to cover the entire coverslip (typically between 500 µL and 1 mL).
2. Wash the cells three to four times with 0.2% PBST (1X PBS + 0.2% Tween-20) at room temperature. One mL of PBST is enough for washing each well. Perform the washes back to back without any incubations.
3. Aspirate the PBST, and block the samples using 5% BSA (Table of Materials) made in 1x PBS (blocking buffer) for 30 min at room temperature.

5. Immunostaining with the IdU antibody

1. For immunostaining, prepare a humidified chamber (wet paper towel on a flat-bottom Tupperware). Cover the lid of the 24-well plate with parafilm, place in the humidified chamber, and lay down the coverslips on the plate lid.
2. Prepare the anti-BrdU primary mouse antibody (Table of Materials) by diluting it 1:200 in the blocking buffer from step 4.2.The anti-BrdU antibody has previously been shown to detect IdU.
3. Add 60 µL of IdU antibody dilution on the top of the coverslips. Incubate the coverslips for 1 h at 37 °C.
   1. Alternatively, use less antibody solution if the coverslips are flipped onto a drop (20-25 µL) of 1:200 antibody dilution pipetted onto parafilm. This also decreases the likelihood of the solution drying out during the incubation.
4. After the 1 h incubation, aspirate the primary antibody. Return the coverslips back to a 24-well plate, and wash them four times with 0.2% PBST.
5. For the secondary antibody, use the same humidified chamber described in step 5.1. Dilute anti-mouse conjugated secondary antibody (Table of Materials) in the blocking buffer (1:200). Add 60 µL of secondary antibody to the coverslips, and incubate at room temperature in the dark for 1 h.This secondary antibody is light-sensitive.
6. Aspirate the secondary antibody. Return the coverslips back to the 24-well plate, and wash four times with 0.2% PBST.
7. Label microscope slides, and mount the coverslips on the slides with DAPI mounting medium (Table of Materials). Store slides in the dark at room temperature for 24 h. The 24 h incubation is recommended if the mounting medium needs to be cured or hardened.
   NOTE: The slides can then be stored in 4 °C before being imaged on a fluorescence microscope. A representative image is shown in Figure 4.

6. Automated quantification of IdU foci

NOTE: The power of this assay lies in the ability to automate the analysis for quick and efficient quantification. We present here an automated analysis pipeline that can be used to quantify IdU foci in a given image field. It is important that all the images within a given experiment are taken with the same exposure settings; otherwise, the quantification will not be reliable. It may also be valuable to include a non-stained control as a negative control, at least for the first time this experiment is run (Figure 5). The protocol below is specific for NIS General Analysis Software, but the same principles can be applied with other commercial software as well.

1. In the View tab, go to Analysis Controls | Analysis Explorer. This opens a new side window called Analysis Explorer. Click on Create New | General Analysis 3. This opens the Analysis Explorer flowchart creation software.
2. Go to the Sources tab, and drag the Channels command from the left menu into the working area. The two channels for the DAPI and IdU foci will automatically pop up as binary boxes (shown in Figure 5 as boxes with red outlines).
3. Go to the Preprocessing tab, and drag the Local Contrast command from the left menu to the working area. Connect the Local Contrast with the IdU foci channel. From the Segmentation tab, drag the Threshold command (one for each channel).
4. Connect each channel to a Threshold command. To eliminate any nuclei at the border of an image, go to the Binary Processing tab, drag the Touching Borders command, and connect to the DAPI threshold.
5. Merge the data from the two channels by using the Aggregate Children command in the Measurement tab. Define the DAPI channel as Parent (A) and the foci channel as Child (B). In the dropdown menu in the Aggregate Children command, select the option child is inside the parent. This step helps to count the number of foci (child) per nucleus (parent).
   1. To export the data in a tabular format, click on the Modify Columns command in the Data Management tab. In the dropdown menu from the Modify Columns command, select DAPI-ID (this helps to assign a unique number to each nucleus within a given image) and IdU count (this provides the number of IdU foci in each nucleus). To export the data in a CSV format, use the Table To CSV command in the Reference tab. The GA3 can now be saved with a descriptive title.
6. For the analysis, open an image in the software.
   1. Open the Analysis Explorer tab as was done in step 6.1, and locate the newly made GA3. Double-click on the GA3 file, which opens a new window called GA3 Wizard where one can set the threshold for the DAPI and the IdU channels.
   2. Use the slider in the window to set the minimum and maximum threshold for each channel and, hence, define the signal. A good thresholding value is where the boundaries for each nucleus and IdU focus are clearly defined. Once satisfied with threshold values, retain these numbers for analyzing all the files in a given experiment.
   3. Click on the Run button to obtain the count of IdU foci/per nucleus.
      NOTE: The software generates a table of foci per nucleus, which can thereafter be used for any graphing purposes (Figure 5).

Representative Results

Representative images and the quantification of IdU foci from the nuclei derived from the untreated cells and cells treated with 0.5 mM hydroxyurea for 24 h are shown in Figure 4. Both nuclei are stained and identifiable in the DAPI channel. The analysis of these images consists of quantifying the number of foci in each nucleus. The number of foci is proportional to the degree of replication stress.

Figure 1: Mechanisms of ssDNA generation. Schematic to show different mechanisms by which ssDNA can be generated in the cell. This includes (A) stalling of the replication machinery, (B) stalling of the transcription machinery, resulting in R-loops, (C) DNA end resection, (D) the formation of D-loops, or (E) replication-coupled gaps. Please click here to view a larger version of this figure.

Figure 2: IdU labeling schematic. Cells are pulsed with IdU for two population doublings. If any drug treatment is needed, it should be administered after the first population doubling in the presence of IdU. Please click here to view a larger version of this figure.

Figure 3: Comparison of the foci signal obtained after pulsing with IdU, BrdU, or CldU. Representative images of cells pulsed with three different thymidine analogs. The DAPI, GFP (representing Alexa-488-labeled IdU foci), and merged channels are shown. Scale bar: 10 µm. Please click here to view a larger version of this figure.

Figure 4: Increased IdU foci in OVCAR3 cells caused by replication stress. (A) Representative IdU and DAPI-stained nuclei images and (B) quantification of the cells treated with 0.5 mM hydroxyurea for 24 h. **** p < 0.0001 (Mann-Whitney test). Scale bar: 10 µm. Please click here to view a larger version of this figure.

Figure 5: Representative automated analysis GA3 pipeline. GA3 automated analysis can be accomplished by generating a pipeline to threshold the nuclei based on DAPI (shown in orange) and IdU foci (shown in yellow). Aggregating these two thresholds populates the number of IdU foci per nucleus. Please click here to view a larger version of this figure.

Discussion

As was mentioned in the protocol, it is valuable to include a few experimental controls to ensure that the assay is working. These include a no IdU treated sample as well as a no primary antibody treated sample. Both negative controls should yield cells that are stained by DAPI but contain no IdU signal.

Based on the experimental conditions and cell lines used, different antibody dilutions may be needed to obtain the best fluorescent signal. Too much signal may result in an inability to quantify individual foci, whereas too little signal may mean experimental differences between the samples cannot be identified. Adjusting the pre-extraction and permeabilization times may also help if there is too much background signal, which could arise from unextracted nucleoplasmic contents.

Since this protocol requires IdU incorporation over two population doublings, it is important to account for each cell line's doubling time. When comparing two cell lines that have different doubling times, it is imperative to adjust the length of the IdU pulsing to each cell line's doubling time. However, this can introduce some level of variation. Thus, the application of this assay is most effective when comparing cell lines with similar doubling times. If the doubling times are not known, this may require prior experimental optimization.

Additionally, this assay may underestimate the amount of ssDNA that is present in the cell at any given time. ssDNA is only identifiable as foci when the opposite strand has been labeled with IdU. Thus, if the strand opposite to the ssDNA has not been labeled, it will not be detected. For instance, if the parental non-labeled DNA has lesions that give rise to gaps, those lesions will not be detected (Figure 2). For a more sensitive analysis, an alternative approach would be to probe the cells for replication protein A (RPA). RPA is a DNA binding protein that preferentially coats ssDNA to prevent it from forming secondary structures and protect from nuclease activity^23,24. During replication-coupled damage, RPA is phosphorylated at serine 33, and, hence, pRPA S33 can be used as a marker for replication stress. Under conditions of excessive damage, pRPA S33 is further phosphorylated on S4/S8 by DNA-PK²⁵. Hence, by probing different forms of RPA bound to the chromatin, one can assess various replication stress responses in cells. These two complementary approaches (IdU foci and RPA staining) can be performed in parallel to validate the levels of ssDNA using distinct methodologies.

This assay provides an easy-to-follow, highly reproducible, and efficient method to quantify ssDNA in a given cell type. It can be adjusted to allow for the application of different drug treatments, various cell types, and multiple analysis tools. It is amenable to various automated quantification methods, including the NIS analysis software. Unlike other techniques to quantify ssDNA, such as the COMET-based assay, the IdU foci assay is more feasible for high-throughput applications.

This assay can be used for a multitude of applications. An increased presence of ssDNA can be used as a marker of replication stress and for predicting chemotherapy responses in various ovarian cancers. Furthermore, the amplification of oncogenes that are known to disrupt replication or cell cycle regulation can cause the accumulation of lesions that result in increased ssDNA. This assay, therefore, could also be used to examine the effect that the amplification of oncogenes has on the accumulation of ssDNA.

Materials

Name	Company	Catalog Number	Comments
3% Paraformaldehyde (PFA)	Fisher Scientific	NC0179595	10 g sucrose + 100 mL 10X PBS + water to make volume to 925 mL. Add 75 mL 40% Methanol free PFA, mix, and make aliquots of 50 mL before storage Storage: Store in -20 °C
5-iodo-2'-deoxyuridine (IdU)	Sigma Aldrich	I7125-5G	MW = 354.10 g/mol.For 10 mM stock: dissolve 3.541 mg IdU to 1 mL 1 N liquid ammonia Storage: Stored in -20 °C
Anti-BrdU antibody	BD Biosciences	347580	Storage: Store in 4 °C
Anti-mouse Alexa Fluor Plus 488 secondary antibody	Thermo Scientific	A32766	Light sensitive - keep in dark Storage: Store in 4 °C
Bovine Serum Albumin (BSA)	Sigma Aldrich	A7906-100G	Made by adding specific mass to volume of PBS Storage: Store in 4 °C
Circular Cover Glass	Electron Microscopy Sciences	72230-01
NIS GA3 Software	Nikon	77010604
OVCAR3	ATCC	HTB-161	Growth Media: RPMI supplemented with L-glutamine, 0.01 mg/mL bovine insulin; fetal bovine serum to a final concentration of 20% and 1X Pen Strep Storage: Freezing Media: growth media + 5% DMSO and stored in -80 °C
Poly-L-Lysine solution	Sigma Aldrich	P4832-50ML	Storage: Store in 4 °C
ProLong Diamond Antifade Mountant with DAPI	Thermo Scientific	P36962	Storage: Store in 4 °C
Trypsin-EDTA, 0.25%	Genesee Scientific	25-510	Storage: Store in 4 °C
Water, sterile-filtered	Sigma Aldrich	W3500-6X500ML	Storage: Store in 4 °C