Cellular energy regulates mRNA degradation in a codon-specific manner.

mRNA Stability; Cellular Energy Metabolism; Tissue-specific Regulation; Codon Usage Bias; Codon Optimality-mediated mRNA Degradation

Journal

Molecular systems biology
ISSN: 1744-4292
Titre abrégé: Mol Syst Biol
Pays: England
ID NLM: 101235389

Informations de publication

Date de publication:
15 Mar 2024
Historique:
received: 04 07 2023
accepted: 20 02 2024
revised: 19 02 2024
medline: 16 3 2024
pubmed: 16 3 2024
entrez: 16 3 2024
Statut: aheadofprint

Résumé

Codon optimality is a major determinant of mRNA translation and degradation rates. However, whether and through which mechanisms its effects are regulated remains poorly understood. Here we show that codon optimality associates with up to 2-fold change in mRNA stability variations between human tissues, and that its effect is attenuated in tissues with high energy metabolism and amplifies with age. Mathematical modeling and perturbation data through oxygen deprivation and ATP synthesis inhibition reveal that cellular energy variations non-uniformly alter the effect of codon usage. This new mode of codon effect regulation, independent of tRNA regulation, provides a fundamental mechanistic link between cellular energy metabolism and eukaryotic gene expression.

Identifiants

pubmed: 38491213
doi: 10.1038/s44320-024-00026-9
pii: 10.1038/s44320-024-00026-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Deutsche Forschungsgemeinschaft (DFG)
ID : 403584255
Organisme : Deutsche Forschungsgemeinschaft (DFG)
ID : 403584255
Organisme : Bundesministerium für Bildung und Forschung (BMBF)
ID : 031L0174A
Organisme : Vetenskapsrådet (VR)
ID : VR 2020-01480 and VR 2021-06112
Organisme : Wallenberg Academy Fellowship
ID : KAW 2021.0167
Organisme : VINNOVA (Swedish Governmental Agency for Innovation Systems)
ID : 2020-03620

Informations de copyright

© 2024. The Author(s).

Références

Allen SR, Stewart RK, Rogers M, Ruiz IJ, Cohen E, Laederach A, Counter CM, Sawyer JK, Fox DT (2022) Distinct responses to rare codons in select Drosophila tissues. Elife 11(2022):e76893
Almanzar N, Antony J, Baghel AS, Bakerman I, Bansal I, Barres BA, Beachy PA, Berdnik D, Bilen B, Brownfield D et al (2020) A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. Nature 583:590–595
doi: 10.1038/s41586-020-2496-1
Bae H, Coller J (2022) Codon optimality-mediated mRNA degradation: linking translational elongation to mRNA stability. Mol Cell 82:1467–1476
pubmed: 35452615 pmcid: 10111967 doi: 10.1016/j.molcel.2022.03.032
Behrens A, Rodschinka G, Nedialkova DD (2021) High-resolution quantitative profiling of tRNA abundance and modification status in eukaryotes by mim-tRNAseq. Mol Cell 81:1802–1815.e7
pubmed: 33581077 pmcid: 8062790 doi: 10.1016/j.molcel.2021.01.028
Boissan M, Schlattner U, Lacombe M-L (2018) The NDPK/NME superfamily: state of the art. Lab Invest 98:164–174
pubmed: 29451272 doi: 10.1038/labinvest.2017.137
Burow DA, Martin S, Quail JF, Alhusaini N, Coller J, Cleary MD (2018a) Attenuated codon optimality contributes to neural-specific mRNA decay in Drosophila. Cell Rep 24:1704–1712
pubmed: 30110627 doi: 10.1016/j.celrep.2018.07.039
Burow DA, Martin S, Quail JF, Alhusaini N, Coller J, Cleary MD (2018b) Attenuated codon optimality contributes to neural-specific mRNA decay in Drosophila. Cell Rep 24:1704–1712
pubmed: 30110627 doi: 10.1016/j.celrep.2018.07.039
Buschauer R, Matsuo Y, Sugiyama T, Chen Y-H, Alhusaini N, Sweet T, Ikeuchi K, Cheng J, Matsuki Y, Nobuta R et al (2020) The Ccr4-Not complex monitors the translating ribosome for codon optimality. Science 368:eaay6912
pubmed: 32299921 pmcid: 8663607 doi: 10.1126/science.aay6912
Buttgereit F, Brand MD (1995) A hierarchy of ATP-consuming processes in mammalian cells. Biochem J 312:163–167
pubmed: 7492307 pmcid: 1136240 doi: 10.1042/bj3120163
Chen C, Stevens B, Kaur J, Smilansky Z, Cooperman BS, Goldman YE (2011) Allosteric vs. spontaneous exit-site (E-site) tRNA dissociation early in protein synthesis. Proc Natl Acad Sci USA 108:16980–16985
pubmed: 21969541 pmcid: 3193197 doi: 10.1073/pnas.1106999108
Chu D, Barnes DJ, von der Haar T (2011) The role of tRNA and ribosome competition in coupling the expression of different mRNAs in Saccharomyces cerevisiae. Nucleic Acids Res 39:6705–6714
pubmed: 21558172 pmcid: 3159466 doi: 10.1093/nar/gkr300
Dana A, Tuller T (2015) Mean of the typical decoding rates: a new translation efficiency index based on the analysis of ribosome profiling data. G3 GenesGenomesGenetics 5:73–80
doi: 10.1534/g3.114.015099
Darnell AM, Subramaniam AR, O’Shea EK (2018) Translational control through differential ribosome pausing during amino acid limitation in mammalian cells. Mol Cell 71:229–243.e11
pubmed: 30029003 pmcid: 6516488 doi: 10.1016/j.molcel.2018.06.041
Dever TE, Dinman JD, Green R (2018) Translation elongation and recoding in eukaryotes. Cold Spring Harb Perspect Biol 10:a032649
pubmed: 29610120 pmcid: 6071482 doi: 10.1101/cshperspect.a032649
Dever TE, Green R (2012) The elongation, termination, and recycling phases of translation in eukaryotes. Cold Spring Harb Perspect Biol 4:a013706
pubmed: 22751155 pmcid: 3385960 doi: 10.1101/cshperspect.a013706
Duan J, Shi J, Ge X, Dölken L, Moy W, He D, Shi S, Sanders AR, Ross J, Gejman PV (2013) Genome-wide survey of interindividual differences of RNA stability in human lymphoblastoid cell lines. Sci Rep 3:1318
pubmed: 23422947 pmcid: 3576867 doi: 10.1038/srep01318
Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210
pubmed: 11752295 pmcid: 99122 doi: 10.1093/nar/30.1.207
Eser P, Demel C, Maier KC, Schwalb B, Pirkl N, Martin DE, Cramer P, Tresch A (2014) Periodic mRNA synthesis and degradation co‐operate during cell cycle gene expression. Mol Syst Biol 10:717
pubmed: 24489117 pmcid: 4023403 doi: 10.1002/msb.134886
Ferreira PG, Muñoz-Aguirre M, Reverter F, Sá Godinho CP, Sousa A, Amadoz A, Sodaei R, Hidalgo MR, Pervouchine D, Carbonell-Caballero J et al (2018) The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat Commun 9:490
pubmed: 29440659 pmcid: 5811508 doi: 10.1038/s41467-017-02772-x
Frankish A, Diekhans M, Jungreis I, Lagarde J, Loveland JE, Mudge JM, Sisu C, Wright JC, Armstrong J, Barnes I et al (2021) GENCODE 2021. Nucleic Acids Res 49:D916–D923
pubmed: 33270111 doi: 10.1093/nar/gkaa1087
Gaidatzis D, Burger L, Florescu M, Stadler MB (2015) Analysis of intronic and exonic reads in RNA-seq data characterizes transcriptional and post-transcriptional regulation. Nat Biotechnol 33:722–729
pubmed: 26098447 doi: 10.1038/nbt.3269
García-Martínez J, Medina DA, Bellvís P, Sun M, Cramer P, Chávez S, Pérez-Ortín JE (2021) The total mRNA concentration buffering system in yeast is global rather than gene-specific. RNA 27:1281–1290
pubmed: 34272303 pmcid: 8456998 doi: 10.1261/rna.078774.121
Gingold H, Tehler D, Christoffersen NR, Nielsen MM, Asmar F, Kooistra SM, Christophersen NS, Christensen LL, Borre M, Sørensen KD et al (2014) A dual program for translation regulation in cellular proliferation and differentiation. Cell 158:1281–1292
pubmed: 25215487 doi: 10.1016/j.cell.2014.08.011
Gomez MAR, Ibba M (2020) Aminoacyl-tRNA synthetases. RNA 26:910–936
doi: 10.1261/rna.071720.119
Goodarzi H, Nguyen HCB, Zhang S, Dill BD, Molina H, Tavazoie SF (2016) Modulated expression of specific tRNAs drives gene expression and cancer progression. Cell 165:1416–1427
pubmed: 27259150 pmcid: 4915377 doi: 10.1016/j.cell.2016.05.046
Greiner JV, Glonek T (2021) Intracellular ATP concentration and implication for cellular evolution. Biology 10:1166
pubmed: 34827159 pmcid: 8615055 doi: 10.3390/biology10111166
Guimaraes JC, Mittal N, Gnann A, Jedlinski D, Riba A, Buczak K, Schmidt A, Zavolan M (2020) A rare codon-based translational program of cell proliferation. Genome Biol 21:44
pubmed: 32102681 pmcid: 7045563 doi: 10.1186/s13059-020-1943-5
Hanson G, Coller J (2018) Codon optimality, bias and usage in translation and mRNA decay. Nat Rev Mol Cell Biol 19:20–30
pubmed: 29018283 doi: 10.1038/nrm.2017.91
Hernandez-Alias X, Benisty H, Schaefer MH, Serrano L (2020) Translational efficiency across healthy and tumor tissues is proliferation-related. Mol Syst Biol 16:e9275
pubmed: 32149479 pmcid: 7061310 doi: 10.15252/msb.20199275
Hoekema A, Kastelein RA, Vasser M, de Boer HA (1987) Codon replacement in the PGK1 gene of Saccharomyces cerevisiae: experimental approach to study the role of biased codon usage in gene expression. Mol Cell Biol 7:2914–2924
pubmed: 2823108 pmcid: 367910
Jackson RJ, Hellen CUT, Pestova TV (2010) The mechanism of eukaryotic translation initiation and principles of its regulation. Nat Rev Mol Cell Biol 11:113–127
pubmed: 20094052 pmcid: 4461372 doi: 10.1038/nrm2838
Koç A, Wheeler LJ, Mathews CK, Merrill GF (2004) Hydroxyurea arrests DNA replication by a mechanism that preserves basal dNTP pools. J Biol Chem 279:223–230
pubmed: 14573610 doi: 10.1074/jbc.M303952200
Laplante M, Sabatini DM (2012) mTOR signaling in growth control and disease. Cell 149:274–293
pubmed: 22500797 pmcid: 3331679 doi: 10.1016/j.cell.2012.03.017
La Manno G, Soldatov R, Zeisel A, Braun E, Hochgerner H, Petukhov V, Lidschreiber K, Kastriti ME, Lönnerberg P, Furlan A et al (2018) RNA velocity of single cells. Nature 560:494–498
pubmed: 30089906 pmcid: 6130801 doi: 10.1038/s41586-018-0414-6
Ling JP, Wilks C, Charles R, Leavey PJ, Ghosh D, Jiang L, Santiago CP, Pang B, Venkataraman A, Clark BS et al (2020) ASCOT identifies key regulators of neuronal subtype-specific splicing. Nat Commun 11:137
pubmed: 31919425 pmcid: 6952364 doi: 10.1038/s41467-019-14020-5
Liu R, Proud CG (2016) Eukaryotic elongation factor 2 kinase as a drug target in cancer, and in cardiovascular and neurodegenerative diseases. Acta Pharmacol Sin 37:285–294
pubmed: 26806303 pmcid: 4775846 doi: 10.1038/aps.2015.123
Marcussen M, Larsen PJ (1996) Cell cycle-dependent regulation of cellular ATP concentration, and depolymerization of the interphase microtubular network induced by elevated cellular ATP concentration in whole fibroblasts. Cell Motil 35:94–99
doi: 10.1002/(SICI)1097-0169(1996)35:2<94::AID-CM2>3.0.CO;2-I
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17:10–12
doi: 10.14806/ej.17.1.200
Milo R, Jorgensen P, Moran U, Weber G, Springer M (2010) BioNumbers—the database of key numbers in molecular and cell biology. Nucleic Acids Res 38:D750–D753
pubmed: 19854939 doi: 10.1093/nar/gkp889
Nersisyan L, Ropat M, Pelechano V (2020) Improved computational analysis of ribosome dynamics from 5’P degradome data using fivepseq. NAR Genom Bioinform 2:lqaa099
pubmed: 33575643 pmcid: 7685019 doi: 10.1093/nargab/lqaa099
Parsyan A, Svitkin Y, Shahbazian D, Gkogkas C, Lasko P, Merrick WC, Sonenberg N (2011) mRNA helicases: the tacticians of translational control. Nat Rev Mol Cell Biol 12:235–245
pubmed: 21427765 doi: 10.1038/nrm3083
Pelechano V, Wei W, Steinmetz LM (2015) Widespread co-translational RNA decay reveals ribosome dynamics. Cell 161:1400–1412
pubmed: 26046441 pmcid: 4461875 doi: 10.1016/j.cell.2015.05.008
Pelechano V, Wei W, Steinmetz LM (2016) Genome-wide quantification of 5′-phosphorylated mRNA degradation intermediates for analysis of ribosome dynamics. Nat Protoc 11:359–376
pubmed: 26820793 pmcid: 4732566 doi: 10.1038/nprot.2016.026
Pinkard O, McFarland S, Sweet T, Coller J (2020) Quantitative tRNA-sequencing uncovers metazoan tissue-specific tRNA regulation. Nat Commun 11:4104
pubmed: 32796835 pmcid: 7428014 doi: 10.1038/s41467-020-17879-x
Presnyak V, Alhusaini N, Chen Y-H, Martin S, Morris N, Kline N, Olson S, Weinberg D, Baker KE, Graveley BR et al (2015) Codon optimality is a major determinant of mRNA stability. Cell 160:1111–1124
pubmed: 25768907 pmcid: 4359748 doi: 10.1016/j.cell.2015.02.029
Pujar S, O’Leary NA, Farrell CM, Loveland JE, Mudge JM, Wallin C, Girón CG, Diekhans M, Barnes I, Bennett R et al (2018) Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation. Nucleic Acids Res 46:D221–D228
pubmed: 29126148 doi: 10.1093/nar/gkx1031
Rabani M, Levin JZ, Fan L, Adiconis X, Raychowdhury R, Garber M, Gnirke A, Nusbaum C, Hacohen N, Friedman N et al (2011) Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells. Nat Biotechnol 29:436–442
pubmed: 21516085 pmcid: 3114636 doi: 10.1038/nbt.1861
Rodriguez JM, Maietta P, Ezkurdia I, Pietrelli A, Wesselink J-J, Lopez G, Valencia A, Tress ML (2013) APPRIS: annotation of principal and alternative splice isoforms. Nucleic Acids Res 41:D110–D117
pubmed: 23161672 doi: 10.1093/nar/gks1058
Roux PP, Topisirovic I (2012) Regulation of mRNA translation by signaling pathways. Cold Spring Harb Perspect Biol 4:a012252
pubmed: 22888049 pmcid: 3536343 doi: 10.1101/cshperspect.a012252
Rudorf S, Lipowsky R (2015) Protein synthesis in E. coli: dependence of codon-specific elongation on tRNA concentration and codon usage. PLOS ONE 10:e0134994
pubmed: 26270805 pmcid: 4535986 doi: 10.1371/journal.pone.0134994
Schmitt BM, Rudolph KLM, Karagianni P, Fonseca NA, White RJ, Talianidis I, Odom DT, Marioni JC, Kutter C (2014) High-resolution mapping of transcriptional dynamics across tissue development reveals a stable mRNA–tRNA interface. Genome Res 24:1797–1807
pubmed: 25122613 pmcid: 4216921 doi: 10.1101/gr.176784.114
Smith T, Heger A, Sudbery I (2017) UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res 27:491–499
pubmed: 28100584 pmcid: 5340976 doi: 10.1101/gr.209601.116
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102:15545–15550
pubmed: 16199517 pmcid: 1239896 doi: 10.1073/pnas.0506580102
Sun M, Schwalb B, Schulz D, Pirkl N, Etzold S, Larivière L, Maier KC, Seizl M, Tresch A, Cramer P (2012) Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation. Genome Res 22:1350–1359
pubmed: 22466169 pmcid: 3396375 doi: 10.1101/gr.130161.111
Sun N, Youle RJ, Finkel T (2016) The mitochondrial basis of aging. Mol Cell 61:654–666
pubmed: 26942670 pmcid: 4779179 doi: 10.1016/j.molcel.2016.01.028
Swaffer MP, Marinov GK, Zheng H, Valenzuela LF, Tsui CY, Jones AW, Greenwood J, Kundaje A, Greenleaf WJ, Reyes-Lamothe R et al (2023) RNA polymerase II dynamics and mRNA stability feedback scale mRNA amounts with cell size. Cell 186:5254–5268.e26
pubmed: 37944513 doi: 10.1016/j.cell.2023.10.012
Takaine M, Imamura H, Yoshida S (2022) High and stable ATP levels prevent aberrant intracellular protein aggregation in yeast. eLife 11:e67659
pubmed: 35438635 pmcid: 9018071 doi: 10.7554/eLife.67659
Trösemeier J-H, Rudorf S, Loessner H, Hofner B, Reuter A, Schulenborg T, Koch I, Bekeredjian-Ding I, Lipowsky R, Kamp C (2019) Optimizing the dynamics of protein expression. Sci Rep 9:7511
pubmed: 31101858 pmcid: 6525252 doi: 10.1038/s41598-019-43857-5
Uvarovskii A, Vries ISN, Dieterich C (2019) On the optimal design of metabolic RNA labeling experiments. PLOS Comput Biol 15:e1007252
pubmed: 31390362 pmcid: 6699717 doi: 10.1371/journal.pcbi.1007252
Walther F (2010) Control of ATP homeostasis during the respiro-fermentative transition in yeast. Mol Syst Biol 6:344
pubmed: 20087341 pmcid: 2824524 doi: 10.1038/msb.2009.100
Wolf FA, Angerer P, Theis FJ (2018) SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19:15
pubmed: 29409532 pmcid: 5802054 doi: 10.1186/s13059-017-1382-0
Wu Q, Medina SG, Kushawah G, DeVore ML, Castellano LA, Hand JM, Wright M, Bazzini AA (2019) Translation affects mRNA stability in a codon-dependent manner in human cells. eLife 8:e45396
pubmed: 31012849 pmcid: 6529216 doi: 10.7554/eLife.45396
Zhang Y, Pelechano V (2021) High-throughput 5′P sequencing enables the study of degradation-associated ribosome stalls. Cell Rep Methods 1:100001
pubmed: 35474692 pmcid: 9017187 doi: 10.1016/j.crmeth.2021.100001

Auteurs

Pedro Tomaz da Silva (P)

School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
Munich Center for Machine Learning, Munich, Germany.

Yujie Zhang (Y)

Scilifelab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.

Evangelos Theodorakis (E)

School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.

Laura D Martens (LD)

School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany.

Vicente A Yépez (VA)

School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.

Vicent Pelechano (V)

Scilifelab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.

Julien Gagneur (J)

School of Computation, Information and Technology, Technical University of Munich, Garching, Germany. gagneur@in.tum.de.
Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany. gagneur@in.tum.de.
Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany. gagneur@in.tum.de.

Classifications MeSH