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Guide-target mismatch effects on dCas9-sgRNA binding activity in living bacterial cells
Huibao Feng1, Jiahui Guo1, Tianmin Wang2
1MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China.
Nucleic Acids Research
|January 27, 2021
Summary
CRISPR-Cas9 off-target effects stem from guide-target mismatches. This study reveals synergistic effects of double mutations and establishes a biophysical model to predict guide RNA efficacy in bacterial CRISPR interference.
Area of Science:
- Molecular Biology
- Biotechnology
- Genetics
Background:
- CRISPR-Cas9 is a powerful DNA targeting tool with broad biotechnological applications.
- Off-target effects due to guide-target mismatches limit CRISPR system engineering.
- Understanding mismatch tolerance is crucial for improving CRISPR specificity.
Purpose of the Study:
- To comprehensively profile in vivo binding affinity of dCas9 with sgRNAs containing single and double nucleotide mismatches.
- To establish a biophysical model explaining the relationship between mismatches and dCas9 binding.
- To develop a predictive tool for rational sgRNA design in bacterial CRISPR interference.
Main Methods:
- Construction of sgRNA libraries with saturated single and double nucleotide mismatches.
- Profiling in vivo binding affinity of dCas9 in living bacterial cells.
- Development of a biophysical model and a convolutional neural network for prediction.
Main Results:
- Observed synergistic activity loss from combinatorial double mutations in the seed region.
- Identified dDrG mismatches as causing only moderate binding impairment.
- Demonstrated that thermodynamic properties and strand invasion largely explain the mismatch-activity landscape.
Conclusions:
- The biophysical model accurately accounts for observed mismatch effects on dCas9 binding.
- A predictive tool combining the model and a CNN can guide rational sgRNA design.
- This work enhances the specificity and reliability of bacterial CRISPR interference systems.
