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McNair K, Salamon P, Edwards RA, Segall AM. PRFect: a tool to predict programmed ribosomal frameshifts in prokaryotic and viral genomes. BMC Bioinformatics 2024; 25:82. [PMID: 38389044 PMCID: PMC10885494 DOI: 10.1186/s12859-024-05701-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 02/13/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence and shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain. More importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation. RESULTS Here we present PRFect, an innovative machine-learning method for the detection and prediction of PRFs in coding genes of various types. PRFect combines advanced machine learning techniques with the integration of multiple complex cellular properties, such as secondary structure, codon usage, ribosomal binding site interference, direction, and slippery site motif. Calculating and incorporating these diverse properties posed significant challenges, but through extensive research and development, we have achieved a user-friendly approach. The code for PRFect is freely available, open-source, and can be easily installed via a single command in the terminal. Our comprehensive evaluations on diverse organisms, including bacteria, archaea, and phages, demonstrate PRFect's strong performance, achieving high sensitivity, specificity, and an accuracy exceeding 90%. The code for PRFect is freely available and installs with a single terminal command. CONCLUSION PRFect represents a significant advancement in the field of PRF detection and prediction, offering a powerful tool for researchers and scientists to unravel the intricacies of programmed ribosomal frameshifting in coding genes.
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Affiliation(s)
- Katelyn McNair
- Computational Science Research Center, San Diego State University, San Diego, CA, USA.
- Department of Computational Science, University of California Irvine, Irvine, CA, USA.
| | - Peter Salamon
- Computational Science Research Center, San Diego State University, San Diego, CA, USA
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA
| | - Robert A Edwards
- College of Science and Engineering, Flinders University, Bedford Park, Adelaide, SA, 5042, Australia
| | - Anca M Segall
- Computational Science Research Center, San Diego State University, San Diego, CA, USA
- Department of Biology and Viral Information Institute, San Diego State University, San Diego, CA, USA
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McNair K, Salamon P, Edwards RA, Segall AM. PRFect: A tool to predict programmed ribosomal frameshifts in prokaryotic and viral genomes. RESEARCH SQUARE 2023:rs.3.rs-2997217. [PMID: 37333268 PMCID: PMC10274946 DOI: 10.21203/rs.3.rs-2997217/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Background One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence, shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain, but more importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation. Results Here we present PRFect, an innovative machine-learning method for the detection and prediction of PRFs in coding genes of various types. PRFect combines advanced machine learning techniques with the integration of multiple complex cellular properties, such as secondary structure, codon usage, ribosomal binding site interference, direction, and slippery site motif. Calculating and incorporating these diverse properties posed significant challenges, but through extensive research and development, we have achieved a user-friendly approach. The code for PRFect is freely available, open-source, and can be easily installed via a single command in the terminal. Our comprehensive evaluations on diverse organisms, including bacteria, archaea, and phages, demonstrate PRFect's strong performance, achieving high sensitivity, specificity, and an accuracy exceeding 90%. Conclusion PRFect represents a significant advancement in the field of PRF detection and prediction, offering a powerful tool for researchers and scientists to unravel the intricacies of programmed ribosomal frameshifting in coding genes.
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Rodnina MV. Decoding and Recoding of mRNA Sequences by the Ribosome. Annu Rev Biophys 2023; 52:161-182. [PMID: 37159300 DOI: 10.1146/annurev-biophys-101922-072452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Faithful translation of messenger RNA (mRNA) into protein is essential to maintain protein homeostasis in the cell. Spontaneous translation errors are very rare due to stringent selection of cognate aminoacyl transfer RNAs (tRNAs) and the tight control of the mRNA reading frame by the ribosome. Recoding events, such as stop codon readthrough, frameshifting, and translational bypassing, reprogram the ribosome to make intentional mistakes and produce alternative proteins from the same mRNA. The hallmark of recoding is the change of ribosome dynamics. The signals for recoding are built into the mRNA, but their reading depends on the genetic makeup of the cell, resulting in cell-specific changes in expression programs. In this review, I discuss the mechanisms of canonical decoding and tRNA-mRNA translocation; describe alternative pathways leading to recoding; and identify the links among mRNA signals, ribosome dynamics, and recoding.
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Affiliation(s)
- Marina V Rodnina
- Department of Physical Biochemistry, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany;
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Atkins JF, O’Connor KM, Bhatt PR, Loughran G. From Recoding to Peptides for MHC Class I Immune Display: Enriching Viral Expression, Virus Vulnerability and Virus Evasion. Viruses 2021; 13:1251. [PMID: 34199077 PMCID: PMC8310308 DOI: 10.3390/v13071251] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 06/11/2021] [Accepted: 06/19/2021] [Indexed: 01/02/2023] Open
Abstract
Many viruses, especially RNA viruses, utilize programmed ribosomal frameshifting and/or stop codon readthrough in their expression, and in the decoding of a few a UGA is dynamically redefined to specify selenocysteine. This recoding can effectively increase viral coding capacity and generate a set ratio of products with the same N-terminal domain(s) but different C-terminal domains. Recoding can also be regulatory or generate a product with the non-universal 21st directly encoded amino acid. Selection for translation speed in the expression of many viruses at the expense of fidelity creates host immune defensive opportunities. In contrast to host opportunism, certain viruses, including some persistent viruses, utilize recoding or adventitious frameshifting as part of their strategy to evade an immune response or specific drugs. Several instances of recoding in small intensively studied viruses escaped detection for many years and their identification resolved dilemmas. The fundamental importance of ribosome ratcheting is consistent with the initial strong view of invariant triplet decoding which however did not foresee the possibility of transitory anticodon:codon dissociation. Deep level dynamics and structural understanding of recoding is underway, and a high level structure relevant to the frameshifting required for expression of the SARS CoV-2 genome has just been determined.
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Affiliation(s)
- John F. Atkins
- Schools of Biochemistry and Microbiology, University College Cork, T12 XF62 Cork, Ireland; (K.M.O.); (P.R.B.); (G.L.)
| | - Kate M. O’Connor
- Schools of Biochemistry and Microbiology, University College Cork, T12 XF62 Cork, Ireland; (K.M.O.); (P.R.B.); (G.L.)
| | - Pramod R. Bhatt
- Schools of Biochemistry and Microbiology, University College Cork, T12 XF62 Cork, Ireland; (K.M.O.); (P.R.B.); (G.L.)
- Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, 8093 Zurich, Switzerland
| | - Gary Loughran
- Schools of Biochemistry and Microbiology, University College Cork, T12 XF62 Cork, Ireland; (K.M.O.); (P.R.B.); (G.L.)
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O'Loughlin S, Capece MC, Klimova M, Wills NM, Coakley A, Samatova E, O'Connor PBF, Loughran G, Weissman JS, Baranov PV, Rodnina MV, Puglisi JD, Atkins JF. Polysomes Bypass a 50-Nucleotide Coding Gap Less Efficiently Than Monosomes Due to Attenuation of a 5' mRNA Stem-Loop and Enhanced Drop-off. J Mol Biol 2020; 432:4369-4387. [PMID: 32454154 PMCID: PMC7245268 DOI: 10.1016/j.jmb.2020.05.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 05/08/2020] [Accepted: 05/11/2020] [Indexed: 01/03/2023]
Abstract
Efficient translational bypassing of a 50-nt non-coding gap in a phage T4 topoisomerase subunit gene (gp60) requires several recoding signals. Here we investigate the function of the mRNA stem–loop 5′ of the take-off codon, as well as the importance of ribosome loading density on the mRNA for efficient bypassing. We show that polysomes are less efficient at mediating bypassing than monosomes, both in vitro and in vivo, due to their preventing formation of a stem–loop 5′ of the take-off codon and allowing greater peptidyl-tRNA drop off. A ribosome profiling analysis of phage T4-infected Escherichia coli yielded protected mRNA fragments within the normal size range derived from ribosomes stalled at the take-off codon. However, ribosomes at this position also yielded some 53-nucleotide fragments, 16 longer. These were due to protection of the nucleotides that form the 5′ stem–loop. NMR shows that the 5′ stem–loop is highly dynamic. The importance of different nucleotides in the 5′ stem–loop is revealed by mutagenesis studies. These data highlight the significance of the 5′ stem–loop for the 50-nt bypassing and further enhance appreciation of relevance of the extent of ribosome loading for recoding. Monosomes are more efficient than polysome in mediating 50-nt translational bypassing. A 5′ mRNA stem–loop facilitates translational bypassing by monosomes. Ribosome profiling yields an extra-long, 53-nt, protected fragment of mRNA.
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Affiliation(s)
- Sinéad O'Loughlin
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland; School of Microbiology, University College Cork, Western Gateway Building, Western Road, Cork, T12 YT57, Ireland
| | - Mark C Capece
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305-4090, USA
| | - Mariia Klimova
- Department of Physical Biochemistry, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Norma M Wills
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112-5330, USA
| | - Arthur Coakley
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland
| | - Ekaterina Samatova
- Department of Physical Biochemistry, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Patrick B F O'Connor
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland
| | - Gary Loughran
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland
| | - Jonathan S Weissman
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Pavel V Baranov
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland; Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, RAS, Moscow 117997, Russia
| | - Marina V Rodnina
- Department of Physical Biochemistry, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Joseph D Puglisi
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305-4090, USA
| | - John F Atkins
- School of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland; School of Microbiology, University College Cork, Western Gateway Building, Western Road, Cork, T12 YT57, Ireland; Department of Human Genetics, University of Utah, Salt Lake City, UT 84112-5330, USA.
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