Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Regulators of mitonuclear balance link mitochondrial metabolism to mtDNA expression

Abstract

Mitochondrial oxidative phosphorylation (OXPHOS) complexes are assembled from proteins encoded by both nuclear and mitochondrial DNA. These dual-origin enzymes pose a complex gene regulatory challenge for cells requiring coordinated gene expression across organelles. To identify genes involved in dual-origin protein complex synthesis, we performed fluorescence-activated cell-sorting-based genome-wide screens analysing mutant cells with unbalanced levels of mitochondrial- and nuclear-encoded subunits of Complex IV. We identified genes involved in OXPHOS biogenesis, including two uncharacterized genes: PREPL and NME6. We found that PREPL specifically impacts Complex IV biogenesis by acting at the intersection of mitochondrial lipid metabolism and protein synthesis, whereas NME6, an uncharacterized nucleoside diphosphate kinase, controls OXPHOS biogenesis through multiple mechanisms reliant on its NDPK domain. Firstly, NME6 forms a complex with RCC1L, which together perform nucleoside diphosphate kinase activity to maintain local mitochondrial pyrimidine triphosphate levels essential for mitochondrial RNA abundance. Secondly, NME6 modulates the activity of mitoribosome regulatory complexes, altering mitoribosome assembly and mitochondrial RNA pseudouridylation. Taken together, we propose that NME6 acts as a link between compartmentalized mitochondrial metabolites and mitochondrial gene expression.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Genome-wide CRISPR screens identify regulators of mitonuclear balance.
Fig. 2: Summary of OXPHOS biogenesis regulators identified by CRISPR screens.
Fig. 3: PREPL, a brain-enriched, dual-localized protein, regulates Complex IV biogenesis.
Fig. 4: PREPL thioesterase activity mediates Complex IV biogenesis.
Fig. 5: Loss of NME6 disrupts OXPHOS biogenesis and mitochondrial respiration.
Fig. 6: Loss of NME6 regulates mtRNA abundance due to disruption of mitochondrial pyrimidine pools.
Fig. 7: NME6 and RCC1L together perform NDPK activity in vitro.
Fig. 8: NME6 KO disrupts mtRNA pseudouridylation levels increasing MT-CO1 RNA stability and synthesis.

Data availability

Deep-sequencing data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession code GSE224819. Mass spectrometry data have been deposited with ProteomeXchange with the primary accession code PXD044812. Metabolomics data are available in Supplementary Table 3. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Code availability

Data from TraceFinder was consolidated and normalized with an in-house R script: https://github.com/FrozenGas/KanarekLabTraceFinderRScripts/blob/main/MS_data_script_v2.4_20221018.R. Mitoribosome profiling analysis was done using the Churchman lab’s pipeline: https://github.com/churchmanlab/human-mitoribosome-profiling.

References

  1. Ryan, M. T. & Hoogenraad, N. J. Mitochondrial-nuclear communications. Annu. Rev. Biochem. 76, 701–722 (2007).

    CAS  PubMed  Google Scholar 

  2. Mottis, A., Herzig, S. & Auwerx, J. Mitocellular communication: shaping health and disease. Science 366, 827–832 (2019).

    CAS  PubMed  Google Scholar 

  3. Isaac, R. S., McShane, E. & Churchman, L. S. The multiple levels of mitonuclear coregulation. Annu. Rev. Genet. 52, 511–533 (2018).

    CAS  PubMed  Google Scholar 

  4. Chan, D. C. Mitochondria: dynamic organelles in disease, aging, and development. Cell 125, 1241–1252 (2006).

    CAS  PubMed  Google Scholar 

  5. Wallace, D. C. A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. Annu. Rev. Genet. 39, 359–407 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Suomalainen, A. & Battersby, B. J. Mitochondrial diseases: the contribution of organelle stress responses to pathology. Nat. Rev. Mol. Cell Biol. 19, 77–92 (2018).

    CAS  PubMed  Google Scholar 

  7. Vafai, S. B. & Mootha, V. K. Mitochondrial disorders as windows into an ancient organelle. Nature 491, 374–383 (2012).

    CAS  PubMed  Google Scholar 

  8. Nunnari, J. & Suomalainen, A. Mitochondria: in sickness and in health. Cell 148, 1145–1159 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Rackham, O. & Filipovska, A. Organization and expression of the mammalian mitochondrial genome. Nat. Rev. Genet. 23, 606–623 (2022).

    CAS  PubMed  Google Scholar 

  10. Kummer, E. & Ban, N. Mechanisms and regulation of protein synthesis in mitochondria. Nat. Rev. Mol. Cell Biol. 22, 307–325 (2021).

    CAS  PubMed  Google Scholar 

  11. Soto, I. et al. Balanced mitochondrial and cytosolic translatomes underlie the biogenesis of human respiratory complexes. Genome Biol. 23, 170 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Kujoth, G. C. et al. Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian aging. Science 309, 481–484 (2005).

    CAS  PubMed  Google Scholar 

  13. Gomes, A. P. et al. Declining NAD+ induces a pseudohypoxic state disrupting nuclear-mitochondrial communication during aging. Cell 155, 1624–1638 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Molenaars, M., Daniels, E. G., Meurs, A., Janssens, G. E. & Houtkooper, R. H. Mitochondrial cross-compartmental signalling to maintain proteostasis and longevity. Philos. Trans. R. Soc. Lond. B 375, 20190414 (2020).

    CAS  Google Scholar 

  15. Haynes, C. M. & Ron, D. The mitochondrial UPR – protecting organelle protein homeostasis. J. Cell Sci. 123, 3849–3855 (2010).

    CAS  PubMed  Google Scholar 

  16. Sutandy, F. X. R., Gößner, I., Tascher, G. & Münch, C. A cytosolic surveillance mechanism activates the mitochondrial UPR. Nature 618, 849–854 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Szczepanowska, K. & Trifunovic, A. Tune instead of destroy: how proteolysis keeps OXPHOS in shape. Biochim. Biophys. Acta Bioenerg. 1862, 148365 (2021).

    CAS  PubMed  Google Scholar 

  18. Houtkooper, R. H. et al. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature 497, 451–457 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Heeren, G. et al. The mitochondrial ribosomal protein of the large subunit, Afo1p, determines cellular longevity through mitochondrial back-signaling via TOR1. Aging 1, 622–636 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Delaney, J. R. et al. Stress profiling of longevity mutants identifies Afg3 as a mitochondrial determinant of cytoplasmic mRNA translation and aging. Aging Cell 12, 156–166 (2013).

    CAS  PubMed  Google Scholar 

  21. Caballero, A. et al. Absence of mitochondrial translation control proteins extends life span by activating sirtuin-dependent silencing. Mol. Cell 42, 390–400 (2011).

    CAS  PubMed  Google Scholar 

  22. Boissan, M., Schlattner, U. & Lacombe, M.-L. The NDPK/NME superfamily: state of the art. Lab Invest. 98, 164–174 (2018).

    CAS  PubMed  Google Scholar 

  23. Mehus, J. G., Deloukas, P. & Lambeth, D. O. NME6: a new member of the nm23/nucleoside diphosphate kinase gene family located on human chromosome 3p21.3. Hum. Genet. 104, 454–459 (1999).

    CAS  PubMed  Google Scholar 

  24. Tsuiki, H. et al. A novel human nucleoside diphosphate (NDP) kinase, Nm23-H6, localizes in mitochondria and affects cytokinesis. J. Cell. Biochem. 76, 254–269 (1999).

    CAS  PubMed  Google Scholar 

  25. Signes, A. & Fernandez-Vizarra, E. Assembly of mammalian oxidative phosphorylation complexes I-V and supercomplexes. Essays Biochem. 62, 255–270 (2018).

    PubMed  PubMed Central  Google Scholar 

  26. Richter-Dennerlein, R. et al. Mitochondrial protein synthesis adapts to influx of nuclear-encoded protein. Cell 167, 471–483.e10 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Morgens, D. W. et al. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens. Nat. Commun. 8, 15178 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Rath, S. et al. MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Res. 49, D1541–D1547 (2021).

    CAS  PubMed  Google Scholar 

  29. Jaeken, J. et al. Deletion of PREPL, a gene encoding a putative serine oligopeptidase, in patients with hypotonia-cystinuria syndrome. Am. J. Hum. Genet. 78, 38–51 (2006).

    CAS  PubMed  Google Scholar 

  30. Régal, L. et al. PREPL deficiency with or without cystinuria causes a novel myasthenic syndrome. Neurology 82, 1254–1260 (2014).

    PubMed  PubMed Central  Google Scholar 

  31. Régal, L. et al. PREPL deficiency: delineation of the phenotype and development of a functional blood assay. Genet. Med. 20, 109–118 (2018).

    PubMed  Google Scholar 

  32. Chabrol, B. et al. Deletion of C2orf34, PREPL and SLC3A1 causes atypical hypotonia–cystinuria syndrome. BMJ Case Rep. 2009, bcr0820080719 (2009).

  33. Yang, Q. et al. PREPL deficiency: a homozygous splice site PREPL mutation in a patient with congenital myasthenic syndrome and absence of ovaries and hypoplasia of uterus. Front. Genet. 11, 198 (2020).

    PubMed  PubMed Central  Google Scholar 

  34. Parvari, R. et al. A recessive contiguous gene deletion of chromosome 2p16 associated with cystinuria and a mitochondrial disease. Am. J. Hum. Genet. 69, 869–875 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Rosier, K. et al. Prolyl endopeptidase-like is a (thio)esterase involved in mitochondrial respiratory chain function. iScience 24, 103460 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Rossiter, N. J. et al. CRISPR screens in physiologic medium reveal conditionally essential genes in human cells. Cell Metab. 33, 1248–1263.e9 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Wolf, A. R. & Mootha, V. K. Functional genomic analysis of human mitochondrial RNA processing. Cell Rep. 7, 918–931 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Chen, W. W., Freinkman, E. & Sabatini, D. M. Rapid immunopurification of mitochondria for metabolite profiling and absolute quantification of matrix metabolites. Nat. Protoc. 12, 2215–2231 (2017).

    PubMed  PubMed Central  Google Scholar 

  39. Proust, B. et al. NME6 is a phosphotransfer-inactive, monomeric NME/NDPK family member and functions in complexes at the interface of mitochondrial inner membrane and matrix. Cell Biosci. 11, 195 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Reyes, A., Favia, P., Vidoni, S., Petruzzella, V. & Zeviani, M. RCC1L (WBSCR16) isoforms coordinate mitochondrial ribosome assembly through their interaction with GTPases. PLoS Genet. 16, e1008923 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Huang, G. et al. WBSCR16 Is a guanine nucleotide exchange factor important for mitochondrial fusion. Cell Rep. 20, 923–934 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Antonicka, H. et al. A high-density human mitochondrial proximity interaction network. Cell Metab. 32, 479–497.e9 (2020).

    CAS  PubMed  Google Scholar 

  43. Antonicka, H. et al. A pseudouridine synthase module is essential for mitochondrial protein synthesis and cell viability. EMBO Rep. 18, 28–38 (2017).

    CAS  PubMed  Google Scholar 

  44. Arroyo, J. D. et al. A genome-wide CRISPR death screen identifies genes essential for oxidative phosphorylation. Cell Metab. 24, 875–885 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Dai, Q. et al. Quantitative sequencing using BID-seq uncovers abundant pseudouridines in mammalian mRNA at base resolution. Nat. Biotechnol. 41, 344–354 (2022).

    PubMed  PubMed Central  Google Scholar 

  46. Martinez, N. M. et al. Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect pre-mRNA processing. Mol. Cell 82, 645–659.e9 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Svitkin, Y. V. et al. N1-methyl-pseudouridine in mRNA enhances translation through eIF2α-dependent and independent mechanisms by increasing ribosome density. Nucleic Acids Res. 45, 6023–6036 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Svitkin, Y. V., Gingras, A.-C. & Sonenberg, N. Membrane-dependent relief of translation elongation arrest on pseudouridine- and N1-methyl-pseudouridine-modified mRNAs. Nucleic Acids Res. 22, 7202–7215 (2021).

    Google Scholar 

  49. Nance, K. D. & Meier, J. L. Modifications in an emergency: the role of N1-methylpseudouridine in COVID-19 vaccines. ACS Cent. Sci. 7, 748–756 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Kim, K. Q. et al. N1-methylpseudouridine found within COVID-19 mRNA vaccines produces faithful protein products. Cell Rep. 40, 111300 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Bonekamp, N. A. et al. Small-molecule inhibitors of human mitochondrial DNA transcription. Nature 588, 712–716 (2020).

    CAS  PubMed  Google Scholar 

  52. To, T.-L. et al. A compendium of genetic modifiers of mitochondrial dysfunction reveals intra-organelle buffering. Cell 179, 1222–1238.e17 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Replogle, J. M. et al. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell 185, 2559–2575.e28 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Lone, A. M. et al. Deletion of PREPL causes growth impairment and hypotonia in mice. PLoS One 9, e89160 (2014).

    PubMed  PubMed Central  Google Scholar 

  55. Martens, K. et al. PREPL: a putative novel oligopeptidase propelled into the limelight. Biol. Chem. 387, 879–883 (2006).

    CAS  PubMed  Google Scholar 

  56. Szeltner, Z., Alshafee, I., Juhász, T., Parvari, R. & Polgár, L. The PREPL A protein, a new member of the prolyl oligopeptidase family, lacking catalytic activity. Cell. Mol. Life Sci. 62, 2376–2381 (2005).

    CAS  PubMed  Google Scholar 

  57. Tang, J. X., Thompson, K., Taylor, R. W. & Oláhová, M. Mitochondrial OXPHOS biogenesis: co-regulation of protein synthesis, import, and assembly pathways. Int. J. Mol. Sci. 21, 3820 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Van Vranken, J. G. et al. ACP acylation is an acetyl-CoA-dependent modification required for electron transport chain assembly. Mol. Cell 71, 567–580.e4 (2018).

    PubMed  PubMed Central  Google Scholar 

  59. Busch, J. D. et al. MitoRibo-Tag mice provide a tool for in vivo studies of mitoribosome composition. Cell Rep. 29, 1728–1738.e9 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Grotehans, N. et al. Ribonucleotide synthesis by NME6 fuels mitochondrial gene expression. EMBO J. 13, e113256 (2023).

    Google Scholar 

  61. Schlattner, U. The complex functions of the NME family-a matter of location and molecular activity. Int. J. Mol. Sci. 22, 13083 (2021).

    PubMed  PubMed Central  Google Scholar 

  62. Bar-Peled, L. & Kory, N. Principles and functions of metabolic compartmentalization. Nat. Metab. 4, 1232–1244 (2022).

    PubMed  PubMed Central  Google Scholar 

  63. Solmonson, A. et al. Compartmentalized metabolism supports midgestation mammalian development. Nature 604, 349–353 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Zhu, J. et al. Mitochondrial NADP(H) generation is essential for proline biosynthesis. Science 372, 968–972 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Tran, D. H. et al. Mitochondrial NADP+ is essential for proline biosynthesis during cell growth. Nat. Metab. 3, 571–585 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Pal, S. et al. A druggable addiction to de novo pyrimidine biosynthesis in diffuse midline glioma. Cancer Cell 40, 957–972.e10 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Kramer, N. J. et al. CRISPR–Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity. Nat. Genet. 50, 603–612 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Morgens, D. W., Deans, R. M., Li, A. & Bassik, M. C. Systematic comparison of CRISPR/Cas9 and RNAi screens for essential genes. Nat. Biotechnol. 34, 634–636 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Kim, G. et al. Genome-wide CRISPR screen reveals v-ATPase as a drug target to lower levels of ALS protein ataxin-2. Cell Rep. 41, 111508 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Li, W. et al. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biol. 15, 554 (2014).

    PubMed  PubMed Central  Google Scholar 

  71. Salabei, J. K., Gibb, A. A. & Hill, B. G. Comprehensive measurement of respiratory activity in permeabilized cells using extracellular flux analysis. Nat. Protoc. 9, 421–438 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Carlile, T. M., Rojas-Duran, M. F. & Gilbert, W. V. in Methods in Enzymology (ed. He, C.) Vol. 560, Ch. 11, 219–245 (Academic, 2015).

  73. Smalec, B. M. et al. Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle. Preprint at bioRxiv https://doi.org/10.1101/2022.08.21.504696 (2022).

  74. Jha, P., Wang, X. & Auwerx, J. Analysis of mitochondrial respiratory chain supercomplexes using blue native polyacrylamide gel electrophoresis (BN-PAGE). Curr. Protoc. Mouse Biol. 6, 1–14 (2016).

    PubMed  PubMed Central  Google Scholar 

  75. Koyama, M., Sasaki, T., Sasaki, N. & Matsuura, Y. Crystal structure of human WBSCR16, an RCC1-like protein in mitochondria. Protein Sci. 26, 1870–1877 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Workman, R. E. et al. Nanopore native RNA sequencing of a human poly(A) transcriptome. Nat. Methods 16, 1297–1305 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Jiang, S. et al. TEFM regulates both transcription elongation and RNA processing in mitochondria. EMBO Rep. 20, e48101 (2019).

    PubMed  PubMed Central  Google Scholar 

  79. Xia, J., Sinelnikov, I. V., Han, B. & Wishart, D. S. MetaboAnalyst 3.0–making metabolomics more meaningful. Nucleic Acids Res. 43, W251–W257 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Salek, R. M., Steinbeck, C., Viant, M. R., Goodacre, R. & Dunn, W. B. The role of reporting standards for metabolite annotation and identification in metabolomic studies. Gigascience 2, 13 (2013).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank C. Guegler for critical reading of the manuscript, S. Adamson for advice on BN-PAGE experiments, P. Kranzusch for advice on TLC assays, and J. Warner for help with fast protein liquid chromatography protein purification. This research was conducted with support from the HMS Electron Microscopy Facility, the HMS Taplin Mass Spectrometry Facility, the HMS MicRoN and Neurobiology Imaging facilities, the Bauer Core facility of Harvard University and the Boston Children’s Hospital Molecular Genetics Core. This work was supported by the National Institutes of Health (R01-GM123002 to L.S.C., F32-GM139244 to N.J.K.) and the Ludwig Neurodegenerative Disease Seed Grants Program at Harvard Medical School. K.C. is supported by post-doctoral fellowships from the Fonds de Recherche du Québec - Santé and the Canadian Institutes of Health Research. B.P. and N.K. are supported by the Smith Family Foundation. N.K. is a Pew Scholar.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization was performed by N.J.K. and L.S.C. Experimental investigation was performed by N.J.K., G.P., R.S.I. and I.S. Software/formal analysis was performed by N.J.K, G.P., K.C. and H.E.M. Metabolite profiling was performed by B.P. and N.K. The Article was written by N.J.K., G.P., and L.S.C. All authors reviewed and edited the Article.

Corresponding author

Correspondence to L. Stirling Churchman.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1

(a) Gating strategies used during flow cytometry depicting populations sorted for analysis in CRISPR screens. (b, c) Volcano plots of gene effect score (enrichment or depletion of sgRNAs in the sorted population relative to unsorted controls) vs confidence scores of genes identified in Population A and Population C. Coloured points = genes passing a 10% FDR threshold. (d) Quality control metrics for CRISPR screens showing violin plots of the beta scores (degree of selection, negative values = negative selection, positive values = positive selection; MAGeCK) for all genes (left; n = 20,467 genes) or known essential genes (right) for each sample after 10 days in culture (T10) relative to screen day 0 (T0). sgRNAs targeting known essential genes were negatively selected over time indicating functional Cas9 activity and consistent sgRNA library behaviour (n = 625 genes). Box plots: centre line, median; box limits, upper and lower quartiles; whiskers, 1.5 × interquartile range. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 2

(a) Western blot validation of screen hits after individual sgRNA transductions (NT sgRNA). Representative blots from 2 independent experiments. (b) TFAM and Complex V subunit levels (mito-encoded ATP6, nuclear-encoded ATP5H) levels in selected hits measured by western blotting. Representative blots from 2 independent experiments. (c) FACS analysis of live cells transduced with individual sgRNAs and stained with MitoTrackerRed CMXros (data are median fluorescence intensities from 20,000 analysed cells). Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 3

(a) Representative STED micrograph of LRPPRC (magenta; matrix marker) and PREPL(L)-Flag (green) co-staining. Quantification of line scans (across indicated dashed line) of pixel intensity for each fluorescence channel appear in Fig. 3d. Experiment repeated twice. (b) STED micrograph showing raw signal compared to deconvolved images using Hyugen’s deconvolution (default parameters, Scientific Volume Imaging; scale bars = 500 nm). Experiment repeated twice. (c) 35S-methionine gels to analyse newly synthesized mitochondrial translation products (replicate gels used in quantification presented in Fig. 4f). (d) Immunoblot analysis of PREPL high molecular weight species (potential dimer from purified mitochondrial lysates (K562 endogenous PREPL, left; K562 cells expressing PREPL-Flag, right). Representative blots from 3 independent experiments. (e) Immunoblot analysis of PREPL putative dimerization after PREPL-Flag IP with or without cross-linking (x-link = crosslinked with 1 mM DSP (dithiobis(succinimidyl propionate, 2 hr. at 4 C and quenched with Tris pH 7.5) and then treated −/+ reducing agent DTT (50 mM, 95 C for 10 min) after IP. Representative blots from 2 independent experiments. Unprocessed blots are available in source data.

Source data

Extended Data Fig. 4

(a) Mass spectrometry identification of proteins in anti-Flag IPs from PREPL KO or PREPL KO + PREPL(L)-Flag whole cell lysates (PREPL(L)-Flag = bait in blue; n = 3 replicates, two-tailed Welch’s t-test). (b) Co-IP (PREPL-Flag = bait) and western blot analysis of selected mass spectrometry-identified proteins, FASTKD4/TBRG4 and LARS2. Experiment repeated twice. (c, d) Sucrose gradient centrifugation and fractionation with western blot detection of mitoribosome subunits, as well as (c) PREPL(L)-Flag and FASTKD4 (MRPS18B = small mitoribosome subunit, MRPL12 = large mitoribosome subunits), and (d) endogenous PREPL. Experiment repeated twice. (e) MitoStrings measurements of mtRNA abundance in control and PREPL KO cells (n = 4 replicates from 2 independent experiments, data are means −/+ SEM). (f) qPCR measurements of mtDNA levels normalized to nuclear DNA content (mito target = MT-TL1, nuclear target = B2M; n = 4 replicates from 2 independent experiments, two-tailed t-test, data are means +/− SD). (g) Western blot analysis of OXPHOS subunits in NT, PREPL KO, KO + PREPL-WT, and KO + PREPL-S559A, in HPLM media supplemented with charcoal-stripped FBS. Representative blots from 2 independent experiments. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 5

Direct RNA nanopore sequencing in control (NT), PREPL KO and NME6 KO cells. (a) Measurement of 5′-end processing levels for mt-mRNAs encoded on the heavy strand and (b) poly(A) tail lengths of mt-mRNAs in control, NME6 KO and PREPL KO cells. n = 2 biological replicate samples sequenced independently, shown as dots in (a) and side-by-side in (b). Box plots: center line, median; box limits, upper and lower quartiles; whiskers, 1.5 × interquartile range. Source numerical data are available in source data.

Source data

Extended Data Fig. 6

Mitochondrial protein turnover assays in (a) PREPL KO cells or (b) NME6 KO cells. Left panels: Cells were pulsed with 200 µg ml–1 CAP to inhibit new mitochondrial protein synthesis for 0, 24 hr, 48 hr, or 72 hr., and proteins were detected via western blotting. Right panels: Quantifications of COX1 bands by densitometry were normalized to ACTB levels and plotted directly or normalized to time = 0 time points for each genotype to correct for the steady-state subunit abundance levels in PREPL or NME6 KO cells. Representative blots from 2 independent experiments. (c) Western blot analysis of TACO1 levels in PREPL KO or NME6 KO cells, MRPS18B and MRPL12 were used for loading controls. Representative blots from 2 independent experiments. (d) Complex IV enzymatic activity measured colorimetrically by monitoring the oxidation of reduced cytochrome c over time from mitochondrial lysates immunocaptured on microplate wells coated with anti-Complex IV antibodies (n = 2 independent biological replicate lysates; related to Fig. 5j). Shown here are the activities for 10 µg mitochondrial protein added per well in control and NME6 KO cells. Activities in OD/min were determined for Fig. 5j by calculating the slope between 2 time points within the linear range of activity. (e) MitoStrings quantifications of RNA transcript abundance in control (NT) or TFB2M pooled CRISPR knock-down cells (bar plots represent the means of the replicates, n = 2 independent cultures). Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 7

In organello mitochondrial transcription visualized by 32P-UTP labelling in purified mitochondria. RNA was visualized using TBE-urea PAGE, followed by autoradiography of newly synthesized mtRNA. SYBR gold staining of total RNA and western blots on input mitochondrial lysates were included for controls. (a) IMT1B was used as a positive control to inhibit mitochondrial transcription in NT control cells (5uM, 2 hr. pre-treatment in culture and maintained in labelling reaction). Representative gels from 3 independent experiments. (b) Transcription assays from fractionated or mt-IP purified mitochondria in NT and NME6 KO cells. Representative gels from 2 independent experiments. (c) Left, ribosome profiling analysis plotting synthesis (TPM = transcript per million) using mitoribosome protected footprints mapped to mitochondrial RNAs and Right, translation efficiency (ribosome footprints normalized by total RNA abundance; n = 2 independently sequenced libraries; related to Fig. 8c). Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 8

(a) Metabolite levels quantified by mass spectrometry in whole cell extractions from NT, NME6 KO, and WT/H137A rescue cell lines (relative to NT; n = 3 independent cultures; two-way ANOVA with Dunnett’s multiple comparisons correction, *** p = 0.0001, **** p < 0.0001, data are means +/− SD). (b) Metabolite levels in NT or NME6 KO mt-IP cell lines after HA-IP (relative to NT; n = 4 independent cultures; data are means +/− SD). SAM = S‐adenosylmethionine, SAH = S-adenosylhomocysteine. (c-f) Isotope tracing using 13C-labelled glucose (22 hr. labelling) and mass spectrometry detection of labelling efficiency for plotted metabolites (c-d = whole cell lysates, e-f = mt-IP lysates; n = 4 independent cultures, two-way ANOVA with Sidak’s multiple comparisons correction, **** p < 0.0001). (g) Volcano plot for all confidently detected metabolites in mt-IP extracts comparing fold change in metabolites (NME6 KO/NT) vs significance values (two-tailed t-test with FDR correction). (h) Malachite green phosphate assay showing background control values for data presented in Fig. 7e. Data are means +/− SD. Source numerical data are available in source data.

Source data

Extended Data Fig. 9

(a) Western blot analysis of HEK293T cells transduced with indicated sgRNAs (AAVS1 = control sgRNA). (b-e) Sucrose gradient centrifugation and fractionation followed by western blotting. (b) NME6 co-sedimentation with mitoribosomes in K562 cells expressing NME6-Flag. (c-e) Mitoribosome assembly phenotypes detected by western blotting after sucrose gradient centrifugation and fractionation using antibodies for small (MRPS18B) and large (MRPL12) mitoribosome subunits to monitor mitoribosome assembly in (c, d) NME6 KO K562 cells and (e) NME6 sgRNA-transduced pooled knock-down (KD) HEK293T cells. (f) Western blot analysis of steady-state mitoribosome subunit levels in control (NT) and NME6 KO cells. All experiments repeated at least twice independently. Unprocessed blots are available in source data.

Source data

Extended Data Fig. 10

(a) qRT-PCR for MT-CO1 levels (left) or MT-RNR2 levels (right) in NT (control), NME6 KO, or K562 pooled CRISPR knock-down cells with the indicated sgRNAs targeting TRUB2, RCC1L, or RPUSD3 (n = 3 independent replicates for each sgRNA, data are means −/+ SD). (b, c) Western blot analysis of RCC1L-Flag IPs in NT (control) or NME6 KO cell backgrounds in K562 and HEK293T, respectively. Representative blots from 2 independent experiments. Source numerical data and unprocessed blots are available in source data.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Gene-level data of CRISPR screen hits.

Supplementary Table 2

Identified proteins from IP–mass spectrometry experiments.

Supplementary Table 3

Metabolite profiling by mass spectrometry: whole cell and mt-IP.

Supplementary Table 4

List of sgRNA sequences used in this study.

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kramer, N.J., Prakash, G., Isaac, R.S. et al. Regulators of mitonuclear balance link mitochondrial metabolism to mtDNA expression. Nat Cell Biol 25, 1575–1589 (2023). https://doi.org/10.1038/s41556-023-01244-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-023-01244-3

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing