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Giambruno R, Nicassio F. Proximity-dependent biotinylation technologies for mapping RNA-protein interactions in live cells. Front Mol Biosci 2022; 9:1062448. [PMID: 36452457 PMCID: PMC9702341 DOI: 10.3389/fmolb.2022.1062448] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 10/25/2022] [Indexed: 12/01/2023] Open
Abstract
Proximity ligation technologies are extremely powerful tools for unveiling RNA-protein interactions occurring at different stages in living cells. These approaches mainly rely on the inducible activity of enzymes (biotin ligases or peroxidases) that promiscuously biotinylate macromolecules within a 20 nm range. These enzymes can be either fused to an RNA binding protein or tethered to any RNA of interest and expressed in living cells to biotinylate the amino acids and nucleic acids of binding partners in proximity. The biotinylated molecules can then be easily affinity purified under denaturing conditions and analyzed by mass spectrometry or next generation sequencing. These approaches have been widely used in recent years, providing a potent instrument to map the molecular interactions of specific RNA-binding proteins as well as RNA transcripts occurring in mammalian cells. In addition, they permit the identification of transient interactions as well as interactions among low expressed molecules that are often missed by standard affinity purification strategies. This review will provide a brief overview of the currently available proximity ligation methods, highlighting both their strengths and shortcomings. Furthermore, it will bring further insights to the way these technologies could be further used to characterize post-transcriptional modifications that are known to regulate RNA-protein interactions.
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Affiliation(s)
- Roberto Giambruno
- Center for Genomic Science of IIT@SEMM, Fondazione Istituto Italiano di Tecnologia, Milano, Italy
- Institute of Biomedical Technologies, National Research Council, Segrate, Italy
| | - Francesco Nicassio
- Center for Genomic Science of IIT@SEMM, Fondazione Istituto Italiano di Tecnologia, Milano, Italy
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Yang LZ, Gao BQ, Huang Y, Wang Y, Yang L, Chen LL. Multi-color RNA imaging with CRISPR-Cas13b systems in living cells. Cell Insight 2022; 1:100044. [PMID: 37192858 PMCID: PMC10120316 DOI: 10.1016/j.cellin.2022.100044] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 05/18/2023]
Abstract
Visualizing RNA dynamics is important for understanding RNA function. Catalytically dead (d) CRISPR-Cas13 systems have been established to image and track RNAs in living cells, but efficient dCas13 for RNA imaging is still limited. Here, we analyzed metagenomic and bacterial genomic databases to comprehensively screen Cas13 homologies for their RNA labeling capabilities in living mammalian cells. Among eight previously unreported dCas13 proteins that can be used for RNA labeling, dHgm4Cas13b and dMisCas13b displayed comparable, if not higher, efficiencies to the best-known ones when targeting endogenous MUC4 and NEAT1_2 by single guide (g) RNAs. Further examination of the labeling robustness of different dCas13 systems using the GCN4 repeats revealed that a minimum of 12 GCN4 repeats was required for dHgm4Cas13b and dMisCas13b imaging at the single RNA molecule level, while >24 GCN4 repeats were required for reported dLwaCas13a, dRfxCas13d and dPguCas13b. Importantly, by silencing pre-crRNA processing activity of dMisCas13b (ddMisCas13b) and further incorporating RNA aptamers including PP7, MS2, Pepper or BoxB to individual gRNAs, a CRISPRpalette system was developed to successfully achieve multi-color RNA visualization in living cells.
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Affiliation(s)
- Liang-Zhong Yang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Bao-Qing Gao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Youkui Huang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ying Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Li Yang
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
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