bioRxivBiophysics
The energy landscape for R-loop formation by the CRISPR-Cas Cascade complex
D. J. Kauert, J. Madariaga Marcos, M. Rutkauskas, A. Wulfken, I. Songailiene, T. Sinkunas, V. Siksnys, R. Seidel
Abstract
The discovery1,2 and the pioneering applications3 of CRISPR-Cas effector complexes have provided powerful gene-editing tools. The effector complexes are guided to the targeted genomic locus by the complementarity of their CRISPR RNA (crRNA)4,5. Recognition of double-stranded DNA targets proceeds via DNA unwinding and base-pairing between crRNA and the DNA target strand resulting in the formation of an R-loop structure5,6. Full R-loop formation is the prerequisite for the subsequent DNA cleavage. While the CRISPR-Cas technology is easy to use, efficient and highly versatile, therapeutic applications are hampered by the off-target effects due to the recognition of unintended sequences with multiple mismatches7. This process is still poorly understood on a mechanistic level8,9. Particularly, the lack of insight into the energetics and dynamics of the R-loop formation hinders a direct modelling of the R-loop formation for off-target prediction. Here we set up ultrafast DNA unwinding experiments based on plasmonic DNA nanorotors to follow the R-loop formation by the Cascade effector complex in real time, close to base pair resolution. We directly resolve a weak global downhill bias of the energy landscape of the forming R-loop followed by a steep uphill bias for the final base pairs. We furthermore show a modulation of the landscape by base flips and mismatches. These data provide that Cascade-mediated R-loop formation occurs on short time scales in single base pair steps of sub-millisecond duration, but on longer time scales in six-base pair intermediate steps in agreement with the structural periodicity of the crRNA-DNA hybrid. We expect that the knowledge about the energy landscapes of R-loop formation of CRISPR-Cas effector complexes will pave the way for a detailed understanding and prediction of off-target recognition10.
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