| Abstract [eng] |
In bacteria, the clustered regularly interspaced short palindromic repeats (CRISPR) system with its associated protein 9 (CRISPR-Cas9) can recognize genetic material of invading bacteriophages and neutralize it. The CRISPR-Cas9 system is guided to its target with the help of guide RNA (gRNA), which makes it easily reprogrammable to a new target with just another gRNA and thus appealing for eukaryotic genome editing. However, a bacterial nuclease encounters different DNA topology when applied in a eukaryotic environment. The differences include different methylation patterns, as bacteria have cytosine and adenine methylation while eukaryotes only have cytosine methylation. Additionally, eukaryotic environment allows short-lived positive supercoils in addition to usual negative supercoils as opposed to bacteria. It has been shown that negative supercoiling is more off-target permissive (Ivanov et al., 2020), yet the magnitude of this effect is unknown. Therefore, the aim of the study is to evaluate if the topology (methylation and supercoiling) of on-target and off-target DNAs impacts their recognition and cleavage by CRISPR-Cas9 from Streptococcus pyogenes. First, the study analyzed if cytosine or adenine methylation affected on- and off-target cleavage rates compared to unmethylated linear target DNAs. This work showed that CRISPR-Cas9 does not typically sense methylation on either nucleotide in its on-targets, with the exception of one out of five targets tested. Off-target cleavage rates are unaffected when methylated, with gRNA bulge forming off-targets having slower cleavage rate than DNA bulge forming off-targets. It was also analyzed if negatively supercoiling DNA promotes CRISPR-Cas9 off-target cleavage when compared to relaxed DNA. Linear DNA target library was successfully inserted into a plasmid, amplified, then fully relaxed and supercoiled. Future work will describe cleavage rates, sites, and trimming for different targets and will produce a biophysical model of CRISPR-Cas9 cleavage specificity. The data will expand our knowledge on nuclease’s specificity and help to choose the most specifically targeted places within the genome. |
