Abstract
The evolutionarily conserved TREX complex plays central roles during mRNP (messenger ribonucleoprotein) maturation and export from the nucleus to the cytoplasm. In yeast, TREX is composed of the THO sub-complex (Tho2, Hpr1, Tex1, Mft1, and Thp2), the DEAD box ATPase Sub2, and Yra1. Here we present a 3.7 Å cryo-EM structure of the yeast THO•Sub2 complex. The structure reveals the intimate assembly of THO revolving around its largest subunit Tho2. THO stabilizes a semi-open conformation of the Sub2 ATPase via interactions with Tho2. We show that THO interacts with the SR-like protein Gbp2 through both the RS domain and RRM domains of Gbp2. Crosslinking mass spectrometry analysis supports the extensive interactions between THO and Gbp2, further revealing that RRM domains of Gbp2 are in close proximity to the C-terminal domain of Tho2. We propose that THO serves as a landing pad to configure Gbp2 to facilitate its loading onto mRNP.
Data availability
The cryo-EM density maps have been deposited in the Electron Microscopy Data Bank under the accession number EMD-23527. The coordinates of the THO•Sub2 complex has be deposited in the Protein Data Bank under the accession number 7LUV.
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Cryo-EM structure of the yeast THO-Sub2 complexElectron Microscopy Data Bank, EMD-23527.
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Cryo-EM structure of the yeast THO-Sub2 complexProtein Data Bank, 7LUV.
Article and author information
Author details
Funding
National Institute of General Medical Sciences (GM133743)
- Yihu Xie
- Bradley P Clarke
- Austin L Ivey
- Pate S Hill
- Yi Ren
National Institute of General Medical Sciences (GM137905)
- Yong Joon Kim
- Yi Shi
National Cancer Institute (T32CA119925)
- Bradley P Clarke
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Xie et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Cryo-EM structure of the yeast TREX complex and coordination with the SR-like protein Gbp2
eLife 10:e65699.
https://doi.org/10.7554/eLife.65699
Further reading
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- Structural Biology and Molecular Biophysics
In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5′ end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism, including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5′ end of mRNA. However, the molecular mechanism for CBC-mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.
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- Structural Biology and Molecular Biophysics
Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.
