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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.
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.
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 cancers2,3. 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 lesions4,5. 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 damage1,7. 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 ssDNA8,9.
(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 behind13,14.
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 cells15,16.
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 kinase17,18,19,20,21. 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.
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
2. Pulsing cells with IdU
3. Fixation
4. Permeabilization and blocking
5. Immunostaining with the IdU antibody
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.
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.
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 quanti...
None.
PV is supported by the Inaugural Pedal the Cause Grant by the Alvin J. Siteman Cancer Center through The Foundation for Barnes-Jewish Hospital, Pilot Research Grant from Marsha Rivkin Center for Ovarian Cancer Research, Cancer Research Grant from Mary Kay Ash Foundation and V-Foundation. NR is supported by the NIH Cell and Molecular Biology training T32 grant to Washington University, St. Louis.
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 |
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