Presented here is sgRNA/CAS9 endonuclease and next-generation sequencing protocol that can be used to identify the mutations associated with double strand break repair near the CD4 promoter.
Double strand breaks (DSBs) in DNA are the most cytotoxic type of DNA damage. Because a myriad of insults can result in these lesions (e.g., replication stress, ionizing radiation, unrepaired UV damage), DSBs occur in most cells each day. In addition to cell death, unrepaired DSBs reduce genome integrity and the resulting mutations can drive tumorigenesis. These risks and the prevalence of DSBs motivate investigations into the mechanisms by which cells repair these lesions. Next generation sequencing can be paired with the induction of DSBs by ionizing radiation to provide a powerful tool to precisely define the mutations associated with DSB repair defects. However, this approach requires computationally challenging and cost prohibitive whole genome sequencing to detect the repair of the randomly occurring DSBs associated with ionizing radiation. Rare cutting endonucleases, such as I-Sce1, provide the ability to generate a single DSB, but their recognition sites must be inserted into the genome of interest. As a result, the site of repair is inherently artificial. Recent advances allow guide RNA (sgRNA) to direct a Cas9 endonuclease to any genome locus of interest. This could be applied to the study of DSB repair making next generation sequencing more cost effective by allowing it to be focused on the DNA flanking the Cas9-induced DSB. The goal of the manuscript is to demonstrate the feasibility of this approach by presenting a protocol that can define mutations that stem from the repair of a DSB upstream of the CD4 gene. The protocol can be adapted to determine changes in the mutagenic potential of DSB associated with exogenous factors, such as repair inhibitors, viral protein expression, mutations, and environmental exposures with relatively limited computation requirements. Once an organism’s genome has been sequenced, this method can be theoretically employed at any genomic locus and in any cell culture model of that organism that can be transfected. Similar adaptations of the approach could allow comparisons of repair fidelity between different loci in the same genetic background.
Maintaining genomic stability is critical for all living organisms. Accurate DNA replication and a robust DNA damage response (DDR) are necessary to faithfully propagate the genetic material1,2. DNA damages occur regularly in most cells2,3. When these damages are sensed, cell cycle progression is halted, and DNA repair mechanisms are activated. Double strand breaks in DNA or DSBs are the most toxic and mutagenic type of DNA damage3,4.
While several DDR signaling pathways can repair these lesions, the most thoroughly studied DSB repair pathways are homologous recombination (HR) and non-homologous end joining (NHEJ). HR is a largely error-free pathway that repairs a DSB using a sister chromatid as a homologous template. This tends to happen in the S phase and G2 phase of a cell cycle5,6,7. NHEJ is more error-prone, but it can happen throughout the cell cycle8,9. Various reporter assays have been developed to measure the efficiency of specific repair mechanisms10,11,12. These assays tend to rely on flow cytometry for a high throughput measurement of DSB repair pathway activity using GFP or mCherry as a readout11,13. While highly efficient, they rely on canonical repair occurring at an artificially introduced DSB.
There are a variety of other methods used to study DSB repair. Many of these rely on immunofluorescence (IF) microscopy1,14. IF microscopy detects discrete nuclear foci representative of repair complexes after DSBs are induced by exposure to genotoxic chemicals or ionizing radiation15,16. Tracking the formation and resolution of these foci provides an indication of repair initiation and completion, respectively14,17. However, these methods of DSB induction (i.e., chemicals or ionizing radiation) do not cause DSBs at defined locations in the genome. It is also functionally impossible to use them to consistently induce only a small number (e.g., 2-4) of DSBs. As a result, the most commonly used methods of inducing DSBs cause a multitude of lesions randomly distributed throughout the genome18. A small number of DSBs can be introduced by inserting the recognition site for a rare-cutting endonuclease and expressing the pertinent endonuclease, such as I-Sce119. Unfortunately, the required integration of a target site prevents the examination of DSB at endogenous genomic loci.
This manuscript describes a method to detect mutations associated with the repair of a DSB generated at a user-defined locus. We provide a representative example of the approach applied to assess the ability of a viral protein to increase the number of mutations associated with a DSB. Specifically, this manuscript describes the use of a single guide RNA (sgRNA) to direct a CAS9 endonuclease to induce a DSB at human CD4 open reading frame in human foreskin keratinocytes expressing vector control (HFK LXSN) and HFK that expresses the E6 protein of human papilloma virus type 8 (HFK 8E6). Targeted next-generation sequencing (NGS) of the region surrounding the break allows mutations associated with the repair of the lesion to be rigorously defined. These data demonstrate that the viral protein causes an approximately 20-fold increase in mutations during DSB repair. It also provides an unbiased characterization of the mutagenic consequences of DSBs at a single locus without the need for whole-genome sequencing. In principle, the protocol could be readily adapted to compare the relative risk of mutations between genome loci or cell lines.
1. Cell plating
2. Transfection
3. Measuring CAS9 expression via immunoblot
4. Nucleic acid extraction and amplicon generation
5. PCR clean-up
6. Library preparation
7. Data analysis
NOTE: All data steps are performed in the genomic data analysis software. Parentheses indicate user input. Greater than sign indicates the order of mouse clicks for any given step (e.g., 1st mouse click>2nd mouse click)
Three representative results are presented for this protocol. Figure 1 is an immunoblot confirming expression of CAS9 in HFK control (LXSN) and HFK expressing beta-HPV 8E6 (8E6). 48 h after transfection, whole cell lysates were harvested and subsequently probed with an anti-CAS9 antibody (or GAPDH as a loading control). The result shows that HFK LXSN and HFK 8E6 are expressing similar amount of CAS9 indicating that transfection efficiency is similar between two cell lines. Figure 2 is an immunofluorescence microscopy image showing CAS9 induced DSBs using pH2AX foci, a standard marker for DSBs24. This indicates that two DSBs are induced by CAS9/sgRNA and thus confirms that DSB induction is occurring as expected. Figure 3 shows that 8E6 increases genomic variations within 200 Kb around the CAS9 induced DSB22. This is consistent with the hypothesis that HPV8 E6 deregulates DSB repair and increases genomic instability. This figure shows one way in which data obtained from this approach can be displayed.
Figure 1: Representative image of immunoblot comparing CAS9 expression in untransfected and transfected HFK cells. sgRNA/CAS9 plasmids were used to transfect HFK cells. Anti-CAS9 antibody was used to detect the CAS9 protein. GAPDH is used as a loading control. Please click here to view a larger version of this figure.
Figure 2: Representative immunofluorescence image of phosphorylated histone H2AX (S139) in sgRNA/CAS9 transfected cell and untransfected control. DAPI was used to stain DNA (Blue). pH2AX (Red) is a marker for CAS9-induced DSB. This demonstrates that optimal CAS9 expression has been achieved by the absence of off-target cleavage. Depending on the number of targeted genome loci (altered by changes in ploidy of the cell, target site copy number variations, or cell cycle position), the number of foci could be higher. However, any increase should be predictable based on the cell type and target site analyzed. Please click here to view a larger version of this figure.
Figure 3: Beta-HPV 8E6 increases genomic instability during DSB repair. (A) Schematic of the placement of CAS9 induced DSB along the sequenced portion of the genome. (B) Genomic variations grouped by types of mutational events in HFK LXSN and HFK 8E6. Each group of genomic variations and total number of variations were compared between HFK LXSN and HFK 8E6. (C) Circos plot of DNA mutations in HFK LXSN (right side) and HFK 8E6 cells (left side). Black arrows indicate CAS9 cutting sites. The innermost circle displays connections between identical genomic rearrangements. The location of genomic rearrangements colored by types of genomic variations are shown in five concentric circles (blue represents SNP, green represents insertion, red represents deletion, purple represents MNV, and black represents replacement). Scatter plot in the outermost circle displays breakpoints (black), tandem duplications (red), and point indels (gray), in which the proximity to the outer edge represents high variant ratio. SNP, single nucleotide polymorphism. MNV, multi-nucleotide variation. Statistical differences between cell lines were measured using a Students' t-test. *** indicates p < 0.001". This is adapted from a previously published reference with permission22. Please click here to view a larger version of this figure.
Table 1: PCR Master mix components. Please click here to download this Table.
Table 2: PCR Program settings. Please click here to download this Table.
Table 3: Trouble shootings. Please click here to download this Table.
Supplemental Table 1: List of primer pool for PCR. Please click here to download this Table.
In addition to the depth of information provided, there are several advantages to this method. First, DSB repair, in theory, can be assessed at any genomic loci without modifying the genome of the cell of interest. Second, access to NGS analysis of repair is increased by the reduced cost and computational effort afforded by making and analyzing a single DSB targeted to a defined area. Finally, with the genomes of additional organisms routinely becoming available and multiple publications demonstrating successful transfection of diverse mammalian and non-mammalian cell lines, the utility of this approach is expected to be broad10,23,24.
This manuscript analyzed DSB repair in human foreskin keratinocytes as an illustrative example. Transfection efficiency tends to be lower in keratinocytes than other tissue types. Therefore, this protocol used a transfection approach optimized for these hard-to-transfect cells. The transfection approach should be optimized for the cell type analyzed. The ability of CAS9-induced DSB used in this protocol has been confirmed in osteosarcoma, colon cancer, lung cancer, fibroblast, embryonic kidney, and human keratinocyte cells10,23. However, before performing next generation sequencing, it is recommended that CAS9 expression and activity are confirmed.
A critical step in this protocol is when comparing between or among different samples to normalize the analysis to account for differences in CAS9 transfection efficiency. To do that, relative CAS9 protein level should be measured by immunoblotting and densitometry (Figure 1). It is also important to ensure the specificity of CAS9 cleavage as indicated by distinct pH2AX (S139) foci formation, detectable by IF microscopy14 (Figure 3). Alternatively, the T7 endonuclease assay can be used to examine CRISPR/Cas9 activity and sgRNA efficiency.
A notable limitation of this approach is that CAS9-induced DSB tend to be “cleaner” than DSB caused by radiation or similar physiological damage. Therefore, the method described here may underestimate the number or severity of the mutations associated with the repair of naturally occurring lesions. The use of other sequence specific nucleases that induce DSB with longer overhangs may help overcome this limitation26. Moreover, it is not fully understood whether chromatin region (e.g., heterochromatin and euchromatin) affects CAS9 activity. Thus, the user should be careful to confirm equivalent CAS9 activity when comparing mutations at different sites.
The method described here can be used to define the relative mutagenic consequences of repairing DSBs in a variety of contexts. For example, it could facilitate examination of novel small molecule DNA repair inhibitors. This would allow inhibitors that are more mutagenic in transformed (compared to untransformed) cells to be prioritized for development as chemotherapeutic agents. This approach may also be useful to compare within the same genomic background to determine the frequency of mutations associated with DSB repair at different gene contexts (e.g., near a promoter, enhancer, or repressor), between cells with different mutations (e.g., signaling genes that are constitutively active or missense mutations), or other similar permutations. The flexibility and affordability of the approach provides a powerful tool for future analyses.
The authors have nothing to disclose.
Research reported in this manuscript was supported by the National Institute of General Medical Sciences of the National Institutes of Health (P20GM130448) (NAW and RP); National Cancer Institute of the National Institutes of Health (NCI R15 CA242057 01A1); Johnson Cancer Research Center in Kansas State University; and the U.S. Department of Defense (CMDRP PRCRP CA160224 (NAW)). We appreciate KSU-CVM Confocal Core and Joel Sanneman for our immunofluorescence microscopy. The content is solely the responsibility of the authors and does not necessarily represent the official views of these funding agencies.
6 Well Tissue Culture Plate | Celltreat | 229106 | Cell culture plate |
BCA Kit | VWR | 89167-794 | BCA assay kit |
Centrifuge 5910 R | Eppendorf | 2231000772 | Tabletop Centrifuge |
CLC Genomic Workbench | Qiagen | 832001 | deep sequence data analysis software/indel caller/variant caller |
Digital Microplate Genie pulse | Scientific industries | SI-400A | Plate shaker |
DYKDDDDK Tag Monoclonal Antibody (FG4R) | ThermoFisher Scientific | MA191878 | Anti-FLAG antibody |
Epilife CF Kit | ThermoFisher Scientific | MEPICF500 | Cell cultrue media and supplements |
Fetal Bovine Serum (FBS) | VWR | 89510-194 | Cell culture supplement |
Goat anti-Rabbit IgG | ThermoFisher Scientific | A-11012 | Secondary antibody |
HighPrep PCR Clean-up system | MagBio | AC-60005 | Bead-based PCR cleanup kit |
KAPA HiFi HotStart ReadyMix PCR Kit | KAPA Biosystems | KK2600 | PCR mastermix/PCR assay |
MagAttract HMW DNA kit | Qiagen | 67563 | High Molecular Weight DNA extraction kit |
Magnetic Stand-96 | Thermo Fisher Scientific | AM10027 | 96-Well Magnetic Rack |
MiniAmp Thermal Cycler | Applied Biosystems | A37834 | Thermal Cycler |
Miseq | Illumina | SY-410-1003 | Sequencer |
Miseq v2 300 cycle reagent kit | Illumina | MS-102-2002 | 300-cycle cartridge/sequencing reagents |
Nextera XT DNA Library Prep kit | Illumina | FC-131-1024 | Library preparation kit |
Nextera XT Kit v2 Set A | Illumina | 20027215 | Indexes |
Nunc 96-well polypropylene DeepWell Stroage plates | Thermo Fisher Scientific | 260251 | deep well 96-well plates |
Penicillin-Streptomycin Solution (100X) | Calsson Labs | PSL02-6X100ML | Antibiotics for cell culture |
Phosphate Buffered Saline (PBS) | Bio Basic | PD8117 | PBS |
px330-CD4 | Addgen | 136938 | SgRNA/CAS9 plasmids targeting 5’- GGCGTATCTGTGTGAGGACT |
QIAxcel Advanced System | Qiagen | 9001941 | capillary electrophersis machine |
QIAxcel DNA screening kit | Qiagen | 929004 | DNA buffer/ capillary electrophersis tubes |
Qubit 1x ds HS Assay Kit | ThermoFisher Scientific | Q23851 | Fluorometer reagents/1x dsDNA solution |
Qubit 4 Fluorometer | ThermoFisher Scientific | Q33238 | Fluorometer |
Qubit Assay Tubes | Thermo Fisher Scientific | Q32856 | Fluorometer assay tubes |
RIPA Lysis Buffer | VWR | VWRVN653-100ML | Lysis buffer for protein extraction |
Trypsin-EDTA (0.05%), phenol red | ThermoFisher Scientific | 25300054 | Trypsin |
Vortex-Genie 2 | Scientific industries | SI-0236 | Vortex |
Xfect Transfection Reagent | Takara Bio | 631318 | Transfection reagent |
genomic data analysis software | QIAGEN | CLC Workbench v21.0. | Data analysis software |