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2021
Hayek H, Gross L, Janvier A, Schaeffer L, Martin F, Eriani G, Allmang C
eIF3 interacts with histone H4 messenger RNA to regulate its translation Journal Article
In: J Biol Chem, vol. 296, pp. 100578, 2021, ISBN: 33766559, (1083-351X (Electronic) 0021-9258 (Linking) Journal Article).
Abstract | Links | BibTeX | Tags: ERIANI, eukaryotic initiation factor, histone mRNA, protein synthesis, RNA protein interaction, RNA structure, translation initiation, translation regulation
@article{Hayek2021,
title = {eIF3 interacts with histone H4 messenger RNA to regulate its translation},
author = {H Hayek and L Gross and A Janvier and L Schaeffer and F Martin and G Eriani and C Allmang},
url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=33766559},
doi = {10.1016/j.jbc.2021.100578},
isbn = {33766559},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {J Biol Chem},
volume = {296},
pages = {100578},
abstract = {In eukaryotes, various alternative translation initiation mechanisms have been unveiled for the translation of specific mRNAs. Some do not conform to the conventional scanning-initiation model. Translation initiation of histone H4 mRNA combines both canonical (cap-dependent) and viral initiation strategies (no-scanning, internal recruitment of initiation factors). Specific H4 mRNA structures tether the translation machinery directly onto the initiation codon and allow massive production of histone H4 during the S phase of the cell cycle. The human eukaryotic translation initiation factor 3 (eIF3), composed of 13 subunits (a-m), was shown to selectively recruit and control the expression of several cellular mRNAs. Whether eIF3 mediates H4 mRNA translation remains to be elucidated. Here, we report that eIF3 binds to a stem-loop structure (eIF3-BS) located in the coding region of H4 mRNA. Combining cross-linking and ribonucleoprotein immunoprecipitation experiments in vivo and in vitro, we also found that eIF3 binds to H1, H2A, H2B and H3 histone mRNAs. We identified direct contacts between eIF3c, d, e, g subunits and histone mRNAs but observed distinct interaction patterns to each histone mRNA. Our results show that eIF3 depletion in vivo reduces histone mRNA binding and modulates histone neosynthesis, suggesting that synthesis of histones is sensitive to the levels of eIF3. Thus, we provide evidence that eIF3 acts as a regulator of histone translation.},
note = {1083-351X (Electronic)
0021-9258 (Linking)
Journal Article},
keywords = {ERIANI, eukaryotic initiation factor, histone mRNA, protein synthesis, RNA protein interaction, RNA structure, translation initiation, translation regulation},
pubstate = {published},
tppubtype = {article}
}
In eukaryotes, various alternative translation initiation mechanisms have been unveiled for the translation of specific mRNAs. Some do not conform to the conventional scanning-initiation model. Translation initiation of histone H4 mRNA combines both canonical (cap-dependent) and viral initiation strategies (no-scanning, internal recruitment of initiation factors). Specific H4 mRNA structures tether the translation machinery directly onto the initiation codon and allow massive production of histone H4 during the S phase of the cell cycle. The human eukaryotic translation initiation factor 3 (eIF3), composed of 13 subunits (a-m), was shown to selectively recruit and control the expression of several cellular mRNAs. Whether eIF3 mediates H4 mRNA translation remains to be elucidated. Here, we report that eIF3 binds to a stem-loop structure (eIF3-BS) located in the coding region of H4 mRNA. Combining cross-linking and ribonucleoprotein immunoprecipitation experiments in vivo and in vitro, we also found that eIF3 binds to H1, H2A, H2B and H3 histone mRNAs. We identified direct contacts between eIF3c, d, e, g subunits and histone mRNAs but observed distinct interaction patterns to each histone mRNA. Our results show that eIF3 depletion in vivo reduces histone mRNA binding and modulates histone neosynthesis, suggesting that synthesis of histones is sensitive to the levels of eIF3. Thus, we provide evidence that eIF3 acts as a regulator of histone translation.
2020
Li B, Cao Y, Westhof E, Miao Z
Advances in RNA 3D Structure Modeling Using Experimental Data Journal Article
In: Front Genet ., vol. 11, no. 574485, 2020.
Abstract | Links | BibTeX | Tags: 3D shape, chemical probing, RNA structure, RNA-puzzles, structure prediction, Unité ARN, WESTHOF
@article{B2020b,
title = {Advances in RNA 3D Structure Modeling Using Experimental Data},
author = {B Li and Y Cao and E Westhof and Z Miao},
doi = {https://doi.org/10.3389/fgene.2020.574485},
year = {2020},
date = {2020-11-23},
journal = {Front Genet .},
volume = {11},
number = {574485},
abstract = {RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.},
keywords = {3D shape, chemical probing, RNA structure, RNA-puzzles, structure prediction, Unité ARN, WESTHOF},
pubstate = {published},
tppubtype = {article}
}
RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.
