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Intrinsic cleavage of RNA polymerase II adopts a nucleobase-independent mechanism assisted by transcript phosphate

Nature Catalysis volume 2, pages 228–235 (2019)Cite this article

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Abstract

RNA polymerase II (Pol II) utilizes the same active site for polymerization and intrinsic cleavage. Pol II proofreads the nascent transcript via its intrinsic nuclease activity to maintain high transcriptional fidelity critical for cell growth and viability. The detailed catalytic mechanism of intrinsic cleavage remains unknown. Here, we combined ab initio quantum mechanics/molecular mechanics studies and biochemical cleavage assays to show that Pol II utilizes downstream phosphate oxygen to activate the attacking nucleophile in hydrolysis, while the newly formed 3′-end is protonated through active-site water without a defined general acid. Experimentally, alteration of downstream phosphate oxygen either by 2′-5′ sugar linkage or stereo-specific thio-substitution of phosphate oxygen drastically reduced cleavage rate. We showed by N7-modification that guanine nucleobase is not directly involved as an acid–base catalyst. Our proposed mechanism provides important insights into the intrinsic transcriptional cleavage reaction, an essential step in transcriptional fidelity control.

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Fig. 1: Elucidating the Pol II intrinsic cleavage mechanism using aiQM/MM–MD simulations.
Fig. 2: Identifying reaction pathway using free-energy profiles.
Fig. 3: Structural representation along the reaction pathway.
Fig. 4: Alteration of the RNA 3′-terminal linkage reduces the intrinsic cleavage rate.
Fig. 5: The effect of thio-substitution of non-bridging phosphate oxygen on intrinsic cleavage.

Code availability

Custom computer code used to analyse simulation data is available from the corresponding author on request.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank Z. Lin for helpful discussions. This work was supported by the Hong Kong Research Grant Council (grant nos. HKUST C6009-15G and AoE/P-705/16 to X.H. and X.L.; 16302214 and T31-605/18-W to X.H.), the King Abdullah University of Science and Technology Office of Sponsored Research (OSR) (OSR-2016-CRG5-3007 to X.H. and X.G.), the Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121 to X.H.), the Innovation and Technology Commission (ITC-CNERC14SC01 to X.H.), and the National Institutes of Health (grant no. R35-GM127040 to Y.Z.; grant no. GM102362 to D.W.). X.H. is the Padma Harilela Associate Professor of Science. This research made use of the computing resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology.

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Author notes

  1. These authors contributed equally: Carmen Ka Man Tse, Jun Xu.

Authors and Affiliations

  1. Department of Chemistry, Centre of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Kowloon, Hong Kong

    Carmen Ka Man Tse, Fu Kit Sheong, Peter Pak-Hang Cheung & Xuhui Huang

  2. Department of Cellular and Molecular Medicine, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA

    Jun Xu, Liang Xu & Dong Wang

  3. Department of Chemistry, Sun Yat-Sen University, Guangzhou, China

    Liang Xu

  4. Department of Chemistry, New York University, New York, NY, USA

    Shenglong Wang & Yingkai Zhang

  5. Department of Chemistry, State Key Lab of Synthetic Chemistry, The University of Hong Kong, Pok Fu Lam, Hong Kong

    Hoi Yee Chow & Xuechen Li

  6. Computational Bioscience Research Centre, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

    Xin Gao

  7. NYU-ECNU Centre for Computational Chemistry at NYU Shanghai, Shanghai, China

    Yingkai Zhang

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Contributions

J.X. and X.L prepared the proteins and performed the biochemical analyses. C.K.M.T., X.G. and S.W. performed aiQM/MM–MD simulations. H.Y.C. and X.L. performed reverse phase-FPLC purification of thio-substituted oligonucleotides. C.K.M.T., J.X., P.P-H.C., F.K.S., D.W., Y.Z., and X.H. analysed the data. C.K.M.T., J.X., P.P-H.C., D.W., Y.Z., and X.H. wrote the manuscript with inputs from all authors. D.W., Y.Z. and X.H. directed and supervised the research.

Corresponding authors

Correspondence to Peter Pak-Hang Cheung, Dong Wang, Yingkai Zhang or Xuhui Huang.

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Supplementary information

Supplementary Information

Supplementary Notes 1–13, Supplementary Figures 1–19, Supplementary References.

Supplementary Data 1

Initial model.

Supplementary Data 2

RS structure.

Supplementary Data 3

TS1 structure.

Supplementary Data 4

IS structure.

Supplementary Data 5

TS2 structure.

Supplementary Data 6

PS structure.

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Tse, C.K.M., Xu, J., Xu, L. et al. Intrinsic cleavage of RNA polymerase II adopts a nucleobase-independent mechanism assisted by transcript phosphate. Nat Catal 2, 228–235 (2019). https://doi.org/10.1038/s41929-019-0227-5

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