Abstract
Reactive oxygen species (ROS) underlie human pathologies including cancer and neurodegeneration1,2. However, the proteins that sense ROS levels and regulate their production through their cysteine residues remain ill defined. Here, using systematic base-editing and computational screens, we identify cysteines in VPS35, a member of the retromer trafficking complex3, that phenocopy inhibition of mitochondrial translation when mutated. We find that VPS35 underlies a reactive metabolite-sensing pathway that lowers mitochondrial translation to decrease ROS levels. Intracellular hydrogen peroxide oxidizes cysteine residues in VPS35, resulting in retromer dissociation from endosomal membranes and subsequent plasma membrane remodelling. We demonstrate that plasma membrane localization of the retromer substrate SLC7A1 is required to sustain mitochondrial translation. Furthermore, decreasing VPS35 levels or oxidation of its ROS-sensing cysteines confers resistance to ROS-generating chemotherapies, including cisplatin, in ovarian cancer models. Thus, we identify that intracellular ROS levels are communicated to the plasma membrane through VPS35 to regulate mitochondrial translation, connecting cytosolic ROS sensing to mitochondrial ROS production.
Access through your institution
Buy or subscribe
This is a preview of subscription content, access via your institution
Access options
Access through your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Learn more
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Learn more
Buy this article
Purchase on SpringerLink
Instant access to full article PDF
Buy now
Prices may be subject to local taxes which are calculated during checkout
Additional access options:
Log in
Learn about institutional subscriptions
Read our FAQs
Contact customer support
Fig. 1: Systematic identification of cysteine residues that mediate sensitivity or resistance to an increase in steady-state cellular ROS levels.
Fig. 2: VPS35 is a cytosolic H2O2 sensor that regulates expression of mitochondrially encoded proteins.
Fig. 3: Oxidation of VPS35 regulates SLC7A1 plasma membrane localization.
Fig. 4: Oxidation of VPS35 regulates compartmentalized translation and cisplatin resistance.
Data availability
All unique and stable reagents generated in this study are available from the corresponding author (L.B.P.) with a completed Materials Transfer Agreement. Cysteine conservation analyses can be reproduced by compilation of data that are stably deposited in the UCSC genome browser (/goldenPath/hg19/multiz100way/alignments/knownCanonical.exonAA.fa.gz), and the final database is available in Supplementary Table 10. Plasma membrane proteomics were deposited in the UCSD MassIVE Database (MSV000096912) a ProteomeXchange (PXD060069). Any additional information required to reanalyse data reported in this paper is available from the corresponding author. Source data are provided with this paper.
References
Chio, I. I. C. & Tuveson, D. A. ROS in cancer: the burning question. Trends Mol. Med. 23, 411–429 (2017).
CASPubMedPubMed CentralMATHGoogle Scholar
Weinberg, F. et al. Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicity. Proc. Natl Acad. Sci. USA 107, 8788–8793 (2010).
CASPubMedPubMed CentralMATHGoogle Scholar
Williams, E. T., Chen, X. & Moore, D. J. VPS35, the retromer complex and Parkinson’s disease. J. Parkinsons Dis. 7, 219–233 (2017).
CASPubMedPubMed CentralMATHGoogle Scholar
Liu, Y. & Birsoy, K. Metabolic sensing and control in mitochondria. Mol. Cell 83, 877–889 (2023).
CASPubMedPubMed CentralMATHGoogle Scholar
Bar-Peled, L. & Kory, N. Principles and functions of metabolic compartmentalization. Nat. Metab. 4, 1232–1244 (2022).
PubMedPubMed CentralMATHGoogle Scholar
Cheung, E. C. & Vousden, K. H. The role of ROS in tumour development and progression. Nat. Rev. Cancer 22, 280–297 (2022).
CASPubMedMATHGoogle Scholar
Reczek, C. R. & Chandel, N. S. ROS-dependent signal transduction. Curr. Opin. Cell Biol. 33, 8–13 (2015).
CASPubMedGoogle Scholar
Chouchani, E. T., Kazak, L. & Spiegelman, B. M. Mitochondrial reactive oxygen species and adipose tissue thermogenesis: bridging physiology and mechanisms. J. Biol. Chem. 292, 16810–16816 (2017).
CASPubMedPubMed CentralMATHGoogle Scholar
Collins, Y. et al. Mitochondrial redox signalling at a glance. J. Cell Sci. 125, 801–806 (2012).
CASPubMedMATHGoogle Scholar
Xiao, H. et al. A quantitative tissue-specific landscape of protein redox regulation during aging. Cell 180, 968–983.e924 (2020).
CASPubMedPubMed CentralMATHGoogle Scholar
Takahashi, M. et al. DrugMap: a quantitative pan-cancer analysis of cysteine ligandability. Cell 187, 2536–2556 e2530 (2024).
CASPubMedMATHGoogle Scholar
Zhang, J. & Bar-Peled, L. Chemical biology approaches to uncovering nuclear ROS control. Curr. Opin. Chem. Biol. 76, 102352 (2023).
CASPubMedPubMed CentralGoogle Scholar
Harris, I. S. & DeNicola, G. M. The complex interplay between antioxidants and ROS in cancer. Trends Cell Biol. 30, 440–451 (2020).
CASPubMedMATHGoogle Scholar
Ge, M., Papagiannakopoulos, T. & Bar-Peled, L. Reductive stress in cancer: coming out of the shadows. Trends Cancer 10, 103–112 (2024).
CASPubMedGoogle Scholar
Murphy, M. P. How mitochondria produce reactive oxygen species. Biochem. J 417, 1–13 (2009).
CASPubMedGoogle Scholar
Brand, M. D. et al. Suppressors of superoxide-H2O2 production at site IQ of mitochondrial complex I protect against stem cell hyperplasia and ischemia-reperfusion injury. Cell Metab. 24, 582–592 (2016).
CASPubMedPubMed CentralGoogle Scholar
Ashrafi, G., Schlehe, J. S., LaVoie, M. J. & Schwarz, T. L. Mitophagy of damaged mitochondria occurs locally in distal neuronal axons and requires PINK1 and Parkin. J. Cell Biol. 206, 655–670 (2014).
CASPubMedPubMed CentralGoogle Scholar
Li, H. et al. Assigning functionality to cysteines by base editing of cancer dependency genes. Nat. Chem. Biol. 19, 1320–1330 (2023).
CASPubMedPubMed CentralMATHGoogle Scholar
Lue, N. Z. et al. Base editor scanning charts the DNMT3A activity landscape. Nat. Chem. Biol. 19, 176–186 (2023).
CASPubMedMATHGoogle Scholar
Gallon, M. & Cullen, P. J. Retromer and sorting nexins in endosomal sorting. Biochem. Soc. Trans. 43, 33–47 (2015).
CASPubMedMATHGoogle Scholar
Chandel, N. S. Evolution of mitochondria as signaling organelles. Cell Metab. 22, 204–206 (2015).
CASPubMedMATHGoogle Scholar
Yang, H. et al. The role of cellular reactive oxygen species in cancer chemotherapy. J. Exp. Clin. Cancer Res. 37, 266 (2018).
CASPubMedPubMed CentralMATHGoogle Scholar
Fu, Y. et al. The role of mitochondria in the chemoresistance of pancreatic cancer cells. Cells 10, 497 (2021).
CASPubMedPubMed CentralMATHGoogle Scholar
Zhang, J. et al. Systematic identification of anticancer drug targets reveals a nucleus-to-mitochondria ROS-sensing pathway. Cell 186, 2361–2379 e2325 (2023).
CASPubMedPubMed CentralMATHGoogle Scholar
Saeed, M. et al. Low-dose doxycycline inhibits hydrogen peroxide-induced oxidative stress, MMP-2 up-regulation and contractile dysfunction in human saphenous vein grafts. Drug Des. Devel. Ther. 13, 1791–1801 (2019).
CASPubMedPubMed CentralGoogle Scholar
Luger, A. L. et al. Doxycycline impairs mitochondrial function and protects human glioma cells from hypoxia-induced cell death: implications of using Tet-inducible systems. Int. J. Mol. Sci. 19, 1504 (2018).
PubMedPubMed CentralMATHGoogle Scholar
Suhm, T. et al. Mitochondrial translation efficiency controls cytoplasmic protein homeostasis. Cell Metab. 27, 1309–1322.e1306 (2018).
CASPubMedGoogle Scholar
Steinhorn, B. et al. Chemogenetic generation of hydrogen peroxide in the heart induces severe cardiac dysfunction. Nat. Commun. 9, 4044 (2018).
PubMedPubMed CentralMATHGoogle Scholar
Nakagawa, T. et al. Doxycycline attenuates cisplatin-induced acute kidney injury through pleiotropic effects. Am. J. Physiol. Renal Physiol. 315, F1347–f1357 (2018).
CASPubMedPubMed CentralGoogle Scholar
Bak, D. W. & Weerapana, E. Cysteine-mediated redox signalling in the mitochondria. Mol. Biosyst. 11, 678–697 (2015).
CASPubMedGoogle Scholar
Lue, N. Z. & Liau, B. B. Base editor screens for in situ mutational scanning at scale. Mol. Cell 83, 2167–2187 (2023).
CASPubMedPubMed CentralMATHGoogle Scholar
Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).
CASPubMedPubMed CentralGoogle Scholar
Gabaldón, T. & Koonin, E. V. Functional and evolutionary implications of gene orthology. Nat. Rev. Genet. 14, 360–366 (2013).
PubMedPubMed CentralMATHGoogle Scholar
Anantharaman, V., Aravind, L. & Koonin, E. V. Emergence of diverse biochemical activities in evolutionarily conserved structural scaffolds of proteins. Curr. Opin. Chem. Biol. 7, 12–20 (2003).
CASPubMedMATHGoogle Scholar
Boatner, L. M., Palafox, M. F., Schweppe, D. K. & Backus, K. M. CysDB: a human cysteine database based on experimental quantitative chemoproteomics. Cell. Chem. Biol. 30, 683–698 e683 (2023).
CASPubMedPubMed CentralGoogle Scholar
Li, C. et al. Spermine synthase deficiency causes lysosomal dysfunction and oxidative stress in models of Snyder–Robinson syndrome. Nat. Commun. 8, 1257 (2017).
PubMedPubMed CentralMATHGoogle Scholar
Kovtun, O. et al. Structure of the membrane-assembled retromer coat determined by cryo-electron tomography. Nature 561, 561–564 (2018).
CASPubMedPubMed CentralMATHGoogle Scholar
Hierro, A. et al. Functional architecture of the retromer cargo-recognition complex. Nature 449, 1063–1067 (2007).
CASPubMedPubMed CentralMATHGoogle Scholar
Haft, C. R. et al. Human orthologs of yeast vacuolar protein sorting proteins Vps26, 29, and 35: assembly into multimeric complexes. Mol. Biol. Cell 11, 4105–4116 (2000).
CASPubMedPubMed CentralMATHGoogle Scholar
Arighi, C. N., Hartnell, L. M., Aguilar, R. C., Haft, C. R. & Bonifacino, J. S. Role of the mammalian retromer in sorting of the cation-independent mannose 6-phosphate receptor. J. Cell Biol. 165, 123–133 (2004).
CASPubMedPubMed CentralGoogle Scholar
Tabuchi, M., Yanatori, I., Kawai, Y. & Kishi, F. Retromer-mediated direct sorting is required for proper endosomal recycling of the mammalian iron transporter DMT1. J. Cell Sci. 123, 756–766 (2010).
CASPubMedGoogle Scholar
Lo Conte, M. & Carroll, K. S. Chemoselective ligation of sulfinic acids with aryl-nitroso compounds. Angew. Chem. 51, 6502–6505 (2012).
CASMATHGoogle Scholar
Yin, Z. et al. Structural basis for a complex I mutation that blocks pathological ROS production. Nat. Commun. 12, 707 (2021).
CASPubMedPubMed CentralMATHGoogle Scholar
Liu, G. Y. & Sabatini, D. M. mTOR at the nexus of nutrition, growth, ageing and disease. Nat. Rev. Mol. Cell Biol. 21, 183–203 (2020).
CASPubMedPubMed CentralMATHGoogle Scholar
Pak, V. V. et al. Ultrasensitive genetically encoded indicator for hydrogen peroxide identifies roles for the oxidant in cell migration and mitochondrial function. Cell Metab. 31, 642–653.e646 (2020).
CASPubMedPubMed CentralGoogle Scholar
Gai, X. et al. Oncogenic KRAS induces arginine auxotrophy and confers a therapeutic vulnerability to SLC7A1 inhibition in non-small cell lung cancer. Cancer Res. 84, 1963–1977 (2024).
CASPubMedMATHGoogle Scholar
Jungnickel, K. E. J., Parker, J. L. & Newstead, S. Structural basis for amino acid transport by the CAT family of SLC7 transporters. Nat. Commun. 9, 550 (2018).
PubMedPubMed CentralGoogle Scholar
Atwal, S. et al. Clickable methionine as a universal probe for labelling intracellular bacteria. J. Microbiol. Methods 169, 105812 (2020).
CASPubMedPubMed CentralMATHGoogle Scholar
Kimura, Y. et al. Mito-FUNCAT-FACS reveals cellular heterogeneity in mitochondrial translation. RNA 28, 895–904 (2022).
CASPubMedPubMed CentralMATHGoogle Scholar
Hällberg, B. M. & Larsson, N. G. Making proteins in the powerhouse. Cell Metab. 20, 226–240 (2014).
PubMedMATHGoogle Scholar
Rottenberg, S., Disler, C. & Perego, P. The rediscovery of platinum-based cancer therapy. Nat. Rev. Cancer 21, 37–50 (2021).
CASPubMedGoogle Scholar
Vasan, N. & Cantley, L. C. At a crossroads: how to translate the roles of PI3K in oncogenic and metabolic signalling into improvements in cancer therapy. Nat. Rev. Clin. Oncol. 19, 471–485 (2022).
CASPubMedPubMed CentralMATHGoogle Scholar
Shaw, R. J. & Cantley, L. C. Ras, PI(3)K and mTOR signalling controls tumour cell growth. Nature 441, 424–430 (2006).
CASPubMedGoogle Scholar
Cheng, J. et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science 381, eadg7492 (2023).
CASPubMedGoogle Scholar
Cutillo, G., Simon, D. K. & Eleuteri, S. VPS35 and the mitochondria: connecting the dots in Parkinson’s disease pathophysiology. Neurobiol. Dis. 145, 105056 (2020).
CASPubMedMATHGoogle Scholar
Tang, F.-L. et al. VPS35 deficiency or mutation causes dopaminergic neuronal loss by impairing mitochondrial fusion and function. Cell Rep. 12, 1631–1643 (2015).
CASPubMedPubMed CentralMATHGoogle Scholar
Wider, C. et al. Autosomal dominant dopa-responsive parkinsonism in a multigenerational Swiss family. Parkinsonism Relat. Disord. 14, 465–470 (2008).
CASPubMedMATHGoogle Scholar
Sanmamed, M. F. & Chen, L. A paradigm shift in cancer immunotherapy: from enhancement to normalization. Cell 175, 313–326 (2018).
CASPubMedPubMed CentralMATHGoogle Scholar
Lee, M. Y., Jeon, J. W., Sievers, C. & Allen, C. T. Antigen processing and presentation in cancer immunotherapy. J. Immunother. Cancer 8, e001111 (2020).
PubMedPubMed CentralGoogle Scholar
Blanc-Durand, F., Clemence Wei Xian, L. & Tan, D. S. P. Targeting the immune microenvironment for ovarian cancer therapy. Front. Immunol. 14, 1328651 (2023).
CASPubMedPubMed CentralGoogle Scholar
Canver, M. C. et al. Integrated design, execution, and analysis of arrayed and pooled CRISPR genome-editing experiments. Nat. Protoc. 13, 946–986 (2018).
CASPubMedPubMed CentralMATHGoogle Scholar
Hanna, R. E. et al. Massively parallel assessment of human variants with base editor screens. Cell 184, 1064–1080.e1020 (2021).
CASPubMedMATHGoogle Scholar
Concordet, J. P. & Haeussler, M. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 46, W242–w245 (2018).
CASPubMedPubMed CentralMATHGoogle Scholar
Adelmann, C. H., Wang, T., Sabatini, D. M. & Lander, E. S. Genome-wide CRISPR/Cas9 screening for identification of cancer genes in cell lines. Methods Mol. Biol. 1907, 125–136 (2019).
CASPubMedMATHGoogle Scholar
Bar-Peled, L. et al. Chemical proteomics identifies druggable vulnerabilities in a genetically defined cancer. Cell 171, 696–709.e623 (2017).
CASPubMedPubMed CentralMATHGoogle Scholar
Bordier, C. Phase separation of integral membrane proteins in Triton X-114 solution. J. Biol. Chem. 256, 1604–1607 (1981).
CASPubMedMATHGoogle Scholar
Weiss-Sadan, T. et al. NRF2 activation induces NADH-reductive stress, providing a metabolic vulnerability in lung cancer. Cell Metab. 35, 722 (2023).
CASPubMedPubMed CentralMATHGoogle Scholar
Pavlova, N. N. et al. Translation in amino-acid-poor environments is limited by tRNAGln charging. eLife 9, e62307 (2020).
CASPubMedPubMed CentralMATHGoogle Scholar
Elia, I. et al. Proline metabolism supports metastasis formation and could be inhibited to selectively target metastasizing cancer cells. Nat. Commun. 8, 15267 (2017).
PubMedPubMed CentralGoogle Scholar
Oliva, C. R., Ali, M. Y., Flor, S. & Griguer, C. E. COX4-1 promotes mitochondrial supercomplex assembly and limits reactive oxide species production in radioresistant GBM. Cell Stress 6, 45–60 (2022).
CASPubMedPubMed CentralGoogle Scholar
Timón-Gómez, A. et al. Protocol for the analysis of yeast and human mitochondrial respiratory chain complexes and supercomplexes by blue native electrophoresis. STAR Protoc. 1, 100089 (2020).
PubMedPubMed CentralMATHGoogle Scholar
Nassar, L. R. et al. The UCSC Genome Browser database: 2023 update. Nucleic Acids Res. 51, D1188–d1195 (2023).
CASPubMedMATHGoogle Scholar
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).
CASPubMedMATHGoogle Scholar
Marino, S. M. & Gladyshev, V, N. Cysteine function governs its conservation and degeneration and restricts its utilization on protein surfaces. J. Mol. Biol. 404, 902–916 (2010).
Van Der Spoel, D. et al. GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701–1718 (2005).
PubMedMATHGoogle Scholar
Brooks, B. R. et al. CHARMM: the biomolecular simulation program. J. Comput. Chem. 30, 1545–1614 (2009).
CASPubMedPubMed CentralMATHGoogle Scholar
Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).
CASPubMedMATHGoogle Scholar
Download references
Acknowledgements
The authors thank all members of the Bar-Peled laboratory and D. Sabatini for helpful suggestions. This work was supported by the Damon Runyon Cancer Research Foundation (62-20 to L.B.-P. and B.L.), the American Association for Cancer Research (19-20-45-BARP), the American Cancer Society, The Krantz Family Center for Cancer Research Quantum Award (to L.B.-P., M.L. and C.J.O.), FujiFilm Therapeutics Graduate Program Fellowship (J.W.), post-baccalaureate fellowship from the UMass Boston-DF/HCC Partnership to Advance Cancer Health Equity (NIH/NCI U54CA156734 (J.M.F.)), the Melanoma Research Alliance, the Ludwig Cancer Center of Harvard Medical School, Lungevity, ALK Positive, V-Foundation, Mary Kay Foundation, Paula and Rodger Riney Foundation, the PEW-Stewart Trusts, Gary Glick, Lisa and Mark Schwartz, Eileen and Jim Rullo, Carol and Ben Monderer and the NIH/NCI (1DP2GM137494, R35GM153476 to B.L. 1R21CA226082-01, R37CA260062 to L.B.-P.), DF/HCC SPORE in Gastrointestinal Cancer, NIH/NCI (P50CA127003), Krantz Family Center for Cancer Research Breakthrough Award (to N.B. and R.M.), Massachusetts Life Sciences Center Bits to Bytes Awards (to N.B. and R.M.) and NIH grants P01 CA117969, R01 CA280085 and R01 CA215498 (to N.B.) and NIH grant 1R01CA279173 (to R.M.).
Author information
Author notes
These authors contributed equally: Junbing Zhang, Md Yousuf Ali, Harrison Byron Chong
Authors and Affiliations
Krantz Family Center for Cancer Research, Massachusetts General Hospital Cancer Center, Charlestown, MA, USA
Junbing Zhang, Md Yousuf Ali, Harrison Byron Chong, Pei-Chieh Tien, Carolina Noble, Tristan Vornbäumen, Stefan Harry, Jay Miguel Fonticella, Lina Fellah, Drew Harrison, Maolin Ge, Neha Khandelwal, Yingfei Huang, Anica Tamara Bischof, Magdy Farag Gohar, Siwen Zhang, Michael Lawrence, Nabeel Bardeesy, Christopher J. Ott & Liron Bar-Peled
CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
Junbing Zhang
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
James Woods & Brian Liau
Brigham and Women’s Hospital, Department of Pathology, Harvard Medical School, MA, USA
Zehra Ordulu
Cell Signaling Technology, Danvers, MA, USA
Anthony P. Possemato & Sean A. Beausoleil
Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, MA, USA
Maëva Chauvin & David Pépin
Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
Grace Marie Hambelton, Sara Bouberhan, Justin F. Gainor, Nabeel Bardeesy, Raul Mostoslavsky, Christopher J. Ott & Liron Bar-Peled
Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
MinGyu Choi
Division of Hematology/Oncology, Massachusetts General Hospital, Boston, MA, USA
Sara Bouberhan
Department of Medicine, Harvard Medical School, Boston, MA, USA
Sara Bouberhan, Michael Lawrence, Justin F. Gainor, Nabeel Bardeesy, Raul Mostoslavsky, Christopher J. Ott & Liron Bar-Peled
Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
Esther Oliva & Mari Mino-Kenudson
Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
Natalya N. Pavlova
Broad Institute of MIT and Harvard, Cambridge, MA, USA
Michael Lawrence
Authors
Junbing Zhang
View author publications
You can also search for this author inPubMedGoogle Scholar
2. Md Yousuf Ali
View author publications
You can also search for this author inPubMedGoogle Scholar
3. Harrison Byron Chong
View author publications
You can also search for this author inPubMedGoogle Scholar
4. Pei-Chieh Tien
View author publications
You can also search for this author inPubMedGoogle Scholar
5. James Woods
View author publications
You can also search for this author inPubMedGoogle Scholar
6. Carolina Noble
View author publications
You can also search for this author inPubMedGoogle Scholar
7. Tristan Vornbäumen
View author publications
You can also search for this author inPubMedGoogle Scholar
8. Zehra Ordulu
View author publications
You can also search for this author inPubMedGoogle Scholar
9. Anthony P. Possemato
View author publications
You can also search for this author inPubMedGoogle Scholar
10. Stefan Harry
View author publications
You can also search for this author inPubMedGoogle Scholar
11. Jay Miguel Fonticella
View author publications
You can also search for this author inPubMedGoogle Scholar
12. Lina Fellah
View author publications
You can also search for this author inPubMedGoogle Scholar
13. Drew Harrison
View author publications
You can also search for this author inPubMedGoogle Scholar
14. Maolin Ge
View author publications
You can also search for this author inPubMedGoogle Scholar
15. Neha Khandelwal
View author publications
You can also search for this author inPubMedGoogle Scholar
16. Yingfei Huang
View author publications
You can also search for this author inPubMedGoogle Scholar
17. Maëva Chauvin
View author publications
You can also search for this author inPubMedGoogle Scholar
18. Anica Tamara Bischof
View author publications
You can also search for this author inPubMedGoogle Scholar
19. Grace Marie Hambelton
View author publications
You can also search for this author inPubMedGoogle Scholar
20. Magdy Farag Gohar
View author publications
You can also search for this author inPubMedGoogle Scholar
21. Siwen Zhang
View author publications
You can also search for this author inPubMedGoogle Scholar
22. MinGyu Choi
View author publications
You can also search for this author inPubMedGoogle Scholar
23. Sara Bouberhan
View author publications
You can also search for this author inPubMedGoogle Scholar
24. Esther Oliva
View author publications
You can also search for this author inPubMedGoogle Scholar
25. Mari Mino-Kenudson
View author publications
You can also search for this author inPubMedGoogle Scholar
26. Natalya N. Pavlova
View author publications
You can also search for this author inPubMedGoogle Scholar
27. Michael Lawrence
View author publications
You can also search for this author inPubMedGoogle Scholar
28. Justin F. Gainor
View author publications
You can also search for this author inPubMedGoogle Scholar
29. Sean A. Beausoleil
View author publications
You can also search for this author inPubMedGoogle Scholar
30. Nabeel Bardeesy
View author publications
You can also search for this author inPubMedGoogle Scholar
31. Raul Mostoslavsky
View author publications
You can also search for this author inPubMedGoogle Scholar
32. David Pépin
View author publications
You can also search for this author inPubMedGoogle Scholar
33. Christopher J. Ott
View author publications
You can also search for this author inPubMedGoogle Scholar
34. Brian Liau
View author publications
You can also search for this author inPubMedGoogle Scholar
35. Liron Bar-Peled
View author publications
You can also search for this author inPubMedGoogle Scholar
Contributions
J.Z., M.Y.A., H.B.C. and L.B.-P. conceived and designed the study. J.Z. and M.Y.A performed most of the experiments with the assistance of P.-C.T., J.W., C.N., T.V., S.H., J.M.F., L.F., D.H, M.G., N.K., Y.H., M. Chauvin, A.T.B., G.M.H., M.F.G., S.Z., M. Choi, S.B., E.O., M.M.-K., N.N.P., J.F.G., N.B., R.M., D.P., C.J.O., B.L., A.P.P. and S.A.B. performed cell surface proteomics. H.B.C. and M.L. performed bioinformatics analysis. Z.O., S.B. and E.O. generated the HGSOC patient tumour samples and Z.O. analysed the immunohistochemical staining results. J.Z., M.Y.A., H.B.C. and L.B.-P. wrote the manuscript with assistance from all the coauthors. L.B.-P. supervised the studies
Corresponding authors
Correspondence to Junbing Zhang or Liron Bar-Peled.
Ethics declarations
Competing interests
L.B.-P. is a founder, consultant and holds privately held equity in Scorpion Therapeutics. A.P.P. and S.A.B. are employees of Cell Signaling Technology. B.L. is a founder, member of the scientific advisory board, and equity holder in Light Horse Therapeutics. M.M.-K. has served as a compensated consultant for AstraZeneca, Roche, BMS, Innate, Boehringer-Ingelheim, Sanofi, Daiichi-Sankyo and AbbVie and has received royalties from Elsevier. J.F.G. has served as a compensated consultant for Amgen, AstraZeneca, Mariana Therapeutics, Mirati Therapeutics, Merus Pharmaceuticals, Nuvalent, Pfizer, Novocure, AI Proteins, Novartis, Silverback Therapeutics, Sanofi, Blueprint Medicines, Bristol Myers Squibb, Genentech, Gilead Sciences, ITeos Therapeutics, Jounce Therapeutics, Karyopharm Therapeutics, Lilly/Loxo, Merck, Moderna Therapeutics and Takeda; has received honorarium from Novartis, Merck, Novartis, Pfizer, Takeda; has received institutional research funding from Adaptimmune, Alexo Therapeutics, AstraZeneca, Blueprint Medicines, Bristol Myers Squibb, Genentech, Jounce Therapeutics, Merck, Moderna Therapeutics, Novartis, NextPoint Therapeutics and Palleon Pharmaceuticals; has recreived research support from Novartis, Genentech and Takeda; has equity in AI Proteins; and has an immediate family member who has equity in and is employed by Ironwood Pharmaceuticals. All other authors declare no competing interests.
Peer review
Peer review information
Nature thanks Brett Collins, Bob Lightowlers and the other, anonymous, reviewer(s) 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 figures and tables
Extended Data Fig. 1 Mitochondrial translation regulates mitochondrial H2O2 levels which contributes to the cytotoxicity of some anti-cancer agents.
(a) Doxycycline (Doxy) treatment decreases expression of mitochondrial encoded proteins across multiple cell lines. Representative immunoblot analysis of MT-CYTB, MT-COXII, MT-ATP6 (mitochondrially encoded) or SDH8, UQCRC2, ATP5A (nuclear encoded) across the indicated cell lines treated with 2.3 µM Doxy for 72 h. (b) Doxy treatment decreases nuclear H2O2 levels. Ratiometric (Ox/Red) images of HyPer7 localized to the nucleus in K562 pre-treated with H2O or 2.3 µM Doxy (72 h) followed by treatment with DMSO, 5.1 µM ATO, 8.3 µM DDP, 2.5 µM AUR or 1.5 µM LAP (6 h). Scale bar=10 µm. (c-d) Heatmap depicting fold change in IC50-values for the indicated anti-cancer agents in cell lines which were pre-treated with the mitochondrial translation inhibitors Chloramphenicol (0.5 µM) or Tedizolid (1 µM) for 72 h. IC50-values for proliferation were determined by measuring relative ATP concentrations. (e) Doxy treatment minimally affects the cytotoxicity of anti-cancer drugs which are not known to increase steady-state ROS levels. 20 cancer cell lines were pre-treated with or without 2.3 µM Doxy for 72 h, and IC50-values for proliferation were determined by measuring relative ATP levels for the following compounds: Paclitaxel (PCX), Trametinib (TRAM), and Capivasertib (CAP). Heatmap depicts fold change in IC50 values (n = 6, mean ± SEM). (f) Blockage of mitochondrial translation decreases mitochondrial ROS. Top, cell sorting gating strategy used in this study. Bottom, K562 cells were treated with the mitochondrial translation inhibitors (2.3 µM Doxy, 0.5 µM Chloramphenicol (CHL) and 1 µM Tedizolid (TED)) for 72 h, and mitochondrial superoxide levels were determined using the mitoSOX probe and flow cytometry (see Methods). (g-h) Mitochondrial H2O2 increases cytotoxicity of anti-cancer drugs. SW620 (g) or SW756 (h) cells expressing mitochondrial matrix localized DAAO were treated with 10 mM L-Ala or D-Ala and the indicated anti-cancer agents (concentration: 5.1 µM ATO, 0.1 µM LAP, 1 µM AUR, and 0.5 µM DDP, n = 6 biologically independent samples). Proliferation was determined as described in (c). (i) Mitochondrial H2O2 functions downstream of mitochondrial translation inhibition to sensitize cells to anti-cancer agents. Heatmap depicting fold-change in IC50-values for cell lines expressing mitochondrial matrix localized DAAO and co-treated with Doxy (2.3 µM, 72 h) and L- or D-Ala (10 mM, 72 h). IC50-values for proliferation were determined by measuring relative ATP levels for the following compounds: Auranofin (AUR), Arsenic Trioxide (ATO), B-Lapachone (LAP) and Cisplatin (DDP). Inset, representative IC50 plot for LN18 cells expressing mito-DAAO (n = 6 biologically independent samples). (j) Cysteines targeted in the CBE screen are distributed across the indicated protein classes. (k) Identification of cysteines which are functionally relevant to anti-cancer agents which increase steady-state ROS levels. Positive CBE scores (in red) represent cysteines whose mutation to tyrosine results in resistance to the indicated treatments, and negative CBE scores (in blue) represent cysteines whose mutation to tyrosine sensitizes cells following treatment (see also Supplemental Table 1). (l) Bar chart depicts the number of proteins containing cysteines (i.e. n = 1, 2, 3, … cysteines) which mediate resistance in the CBE screen. (m) Molecular functions associated with cysteines that mediate resistance to increase in steady-state ROS levels (CBE z-score ≥ 2 in at least 2 treatments) (See Methods, Supplementary Table 2). (n) A subset of highly conserved cysteines exhibit altered reactivity following treatment with compounds that alter steady-state ROS levels24. (o) Left, Chord diagram highlights highly conserved cysteines whose mutation to tyrosine mediates sensitivity to the indicated perturbations, including SMS•C318Y. Right, structure of SMS (PDB: 3C6M). (p) SMS•C318Y confers sensitivity to treatment with AUR, LAP, and DDP. Relative proliferation of K562 cells depleted of endogenous SMS and expressing WT SMS or SMS•C318Y was determined following 96 h. treatment with indicated drugs by measuring relative ATP levels (n = 3 biologically independent samples). (q) Depletion of VPS35 mediates resistance to AUR. Left, relative proliferation was determined after 96 h (n = 6 biologically independent samples). Scale bar=10 µm. Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired).
Source Data
Extended Data Fig. 2 Incorporation of cysteine conservation analysis to identify functional cysteines.
(a) Tracing cysteine evolution across 102 eukaryotes. A conservation score was determined for ~250,000 human cysteines across 102 organisms and represented in a 3D embedding by UMAP. Evolutionary trajectory is indicated by arrows (see Methods). (b) Conservation entropy of individual cysteines; conservation of human-encoded cysteines across indicated organisms and examples of cysteine conservation spectra (see Methods). (c) Distribution of cysteine conservation across: amino acids immediately flanking in linear sequence, protein domains, and protein classes. (d) Structural characterization of conserved cysteines (see Methods).
Extended Data Fig. 3 Oxidation of VPS35 regulates the localization of Retromer complex.
(a) CRISPRi-depletion of Retromer subunits increases resistance to AUR. Top, representative immunoblot analysis of VPS35 (top) and β-actin (bottom) from K562-dCAS9-KRAB cells expressing sgCTRL or indicated sgRNAs. Bottom, K562-dCAS9-KRAB cells expressing sgCTRL or indicated sgRNAs were treated with AUR and relative proliferation was determined after 96 h. by measuring a change in cellular ATP concentrations (n = 6 biologically independent samples for VPS35 and VPS29 group, n = 5 biologically independent samples for VPS26 group). (b) Co-localization of Retromer subunits. Immunofluorescence analysis of K562 cells stably expressing FLAG-VPS35 and endogenous VPS26 (left) or VPS29 (right). (c-f) H2O2 treatment does not disrupt endosomal marker localization. Representative immunofluorescent images of the indicated endosomal markers: Rab5 (c), EEA1 (d) Rab7 (e) and FLAG-VPS35 (f) in K562 cells expressing FLAG-VPS35 and treated with H2O2 (100 µM, 6 h). (g-i) H2O2 treatment regulates VPS35 localization. Representative immunofluorescence images and corresponding quantification of VPS35 localization in HeLa (g), OVISE (h) and PEO1 (i) cells treated with 100 µM H2O2 for 6 h. (j-k) H2O2 treatment regulates localization of Retromer subunit VPS26 and VPS29 in K562 cells. Left, representative immunofluorescence images of K562 cells stably expressing VPS26-V5 (j) or VPS29-HA (k) treated with 100 µM H2O2 for 6 h. Right, quantification of VPS26 and VPS29 localization. (l) Representative immunofluorescence images of HeLa cells stably expressing VPS26-V5 or VPS29-HA treated with H2O or 100 µM H2O2 for 6 h. (m) Quantification of FLAG-VPS35 localization following treatment with H2O2 (see also Fig. 2a). (n) Treatment with anti-cancer agents that alter steady-state ROS levels regulates VPS35 localization. Left, representative immunofluorescence images of K562 cells stably expressing FLAG-VPS35 treated with DMSO, 5.1 µM ATO, 8.3 µM CPT, 2.5 µM AUR or 1.5 µM LAP for 6 h. Right, the quantification of VPS35 location changes after each treatment. Scale bar=10 µm. For quantification of Extended Data Fig. 3g–n, n = 100 cells examined over 3 independent experiments, Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired).
Source Data
Extended Data Fig. 4 Oxidation of VPS35•C653/673 regulates the localization of Retromer complex.
(a) Anti-oxidants rescue the localization of VPS35 following AUR treatment. Left, representative immunofluorescence images of K562 cells stably expressing FLAG-VPS35 pre-treated with the indicated compounds followed by treatment with 2.5 µM AUR for 6 h. Right, quantification of FLAG-VPS35 localization following each treatment. (b) Quantification of the localization of VPS35 or the indicated VPS35 mutant following H2O2 treatment (see also Fig. 2b). (c-d) Increasing nuclear and mitochondrial H2O2 levels is sufficient to disrupt VPS35 localization. Representative immunofluorescent images (left) and quantification (right) of K562 cells stably expressing nuclear localized DAAO (c) or mitochondrial matrix DAAO (d) following treatment with 50 mM L-Ala or D-Ala for 6 h (mean ± SEM). (e) FLAG-VPS35-DAAO is oxidized following D-Ala treatment. K562 cells expressing FLAG-VPS35-DAAO were treated L- or D-Ala, followed by NO-DTB. Sulfinic acid formation was determined following streptavidin-enrichment and immunoblot analysis. (f) NAC reverts oxidation of VPS35. K562 cells were treated with 2.5 µM AUR and 5 mM NAC followed by 500 µM NO-DTB. Oxidation was determined following streptavidin-enrichment and immunoblot analysis as in (e). (g) AUR treatment decreases the reactivity of VPS35•C653/C673. Chemical proteomic analysis of cysteine reactivity analysis of the indicated cysteines using desthiobiotin iodoacetamide in VPS35 following treatment of K562 cells with 2.5 µM AUR for 6 h (Statistical significance was determined by two-tailed, unpaired Student’s t test; see also methods). (h) H2O2 oxidizes VPS35. The indicated cells were treated with 100 µM H2O2, followed by 500 µM NO-DTB and sulfinic acid formation was determined as in (e). (i-j) H2O2 treatment blocks alkylation of VPS35. (i)K562 cells were treated with 100 µM H2O2. Cells were lysed, treated with 500 µM of the cysteine-specific desthiobiotin iodoacetamide (DBIA) probe and relative levels of streptavidin-enriched proteins were determined by immunoblot. (j) K562 cells stably expressing FLAG-VPS35 or FLAG-VPS35•C653S/C673S were treated with 100 µM H2O2 and the relative levels of FLAG-VPS35 were determined as described in (i). (k) Quantification of localization of VPS35•C653D or VPS35•C673D relative to WT VPS35 (see also Fig. 2g). (l) Representative immunofluorescence images of HeLa cells stably expressing FLAG-VPS35, FLAG-VPS35•C653D or FLAG-VPS35•C673D. (m) Analysis of VPS35 C673D mutation by molecular dynamics reveals that, on a short time scale (200 ns), replacement of cysteine with aspartate in silico induces local unpacking of coiled-coil (see Methods). Scale bar=10 µm. For quantification of Extended Data Fig. 4a–d,k, n = 100 cells examined over 3 independent experiments, mean ± SEM. For quantification of Extended Data Fig. 4g, n = 4 biologically independent samples examined. Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired).
Source Data
Extended Data Fig. 5 VPS35 oximimetics regulate ROS levels.
(a-c) Retromer complex regulates steady-state nuclear H2O2 levels. Ratiometric (Ox/Red) images of HyPer7 localized to the nucleus in K562 cell lines depleted for VPS35 (a), or expressing sgRNAs targeting VPS26 (b) or VPS29 (c) and treated with DMSO or 2.5 µM AUR for 6 h. (d-f) Mutation of VPS35•C673 regulates nuclear H2O2 levels following treatment with anti-cancer agents in HeLa (d), OVISE (e) and PEO1 (f) cells. Ratiometric (Ox/Red) images of HyPer7 localized to the nucleus in VPS35-depleted cell lines expressing indicated proteins following 6 h treatment with DMSO, 2.5 µM AUR or 1.5 µM LAP. (g) Co-localization of mitochondrial matrix targeted HyPer7 (Mito-HyPer7) with a mitochondrial specific dye (Mito Tracker Red) in K562 cells. (h) Mito matrix H2O2 levels are decreased in cells expressing VPS35•C673D. Representative images of VPS35-depleted K562 cells expressing Mito-HyPer7 and PAM mutants of VPS35 WT or VPS35•C673D which were treated with the indicated anti-cancer drugs (2.5 µM AUR, 5.1 µM ATO, 1.5 µM LAP or 8.3 µM DDP for 6 h). Mito-matrix H2O2 levels were determined by quantifying ratiometric (Ox/Red) images of Mito-HyPer7. (i-k) Loss of VPS35 or expression of VPS35 oximimetic decreases mitochondrial superoxide and ROS levels. VPS35-depleted K562 cells (i,j) expressing PAM mutants of WT or VPS35•C673D (k) were treated with AUR (2.5 µM, 6 h) and mitochondrial superoxide levels (i,k) were measured using the mitoSOX probe or total ROS levels (j) using the DCF probe by flow cytometry. Gating strategy was described as Extended Data Fig. 1f. (l-m) Depletion of Retromer subunits decreases cellular ROS levels. Cellular ROS levels were assessed by flow cytometry measuring changes in DCF fluorescence in K562 cell lines expressing sgRNAs targeting VPS26 (l) or VPS29 (m) and treated with DMSO or 2.5 µM AUR for 6 h. Gating strategy was described as Extended Data Fig. 1f. (n) Quantification of the mitochondrially translated proteins from the indicated cell lines. n = 3 independent experiments examined. Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired). Scale bar=10 µm.
Source Data
Extended Data Fig. 6 VPS35 oxidation downregulates SLC7A1 plasma membrane localization.
(a) Comparison of cell surface proteomes following loss of VPS35 or treatment with agents that increase steady-state levels of cellular ROS. The abundance of proteins at the plasma membrane in K562 cells depleted for VPS35 was determined following enrichment of plasma membrane and quantitative proteomics (see also Fig. 3a, Supplemental Table 4). (b) Metabolism focused CRISPR screen in K562 cells expressing HyPer7-NLS identifies genes that regulate basal state nuclear H2O2 levels. A positive CRISPR score (in red) represents genes whose loss increases nuclear H2O2 levels and a negative CRISPR score (in blue) represents genes whose loss decreases nuclear H2O2 levels (see also Supplemental Table 5). (c) H2O2 and AUR disrupt the plasma membrane localization of SLC7A1. Representative images of HEK-293T cells stably expressing FLAG-SLC7A1 treated with 100 µM H2O2 or 2.5 µM AUR for 6 h. (d) VPS35 is necessary for SLC7A1 localization. Left, immunoblot analysis of VPS35 in the indicated cell lines. Right, representative images of VPS35-WT or –depleted HEK-293T cells stably expressing FLAG-SLC7A1. (e) Representative images of VPS35-WT or –depleted HEK-293T cells stably expressing FLAG-SLC7A1 and RFP-PLCdPH (plasma membrane marker). Cells were treated with DAPI to image nucleus or stained with anti-FLAG antibody. Cells were stained with DAPI to image nucleus or stained with anti-FLAG antibody. (f-k) SLC7A1 localization is regulated by VPS35 in a H2O2-dependent manner. Representative images of FLAG-SLC7A1 following treatment with H2O or 100 µm H2O2 for 6 h (f, h, j) or in VPS35-depleted cell lines stably expressing VPS35– or VPS35•C673D-PAM mutants (g, I, k). (l) SLC7A1 is a substrate of the Retromer complex. K562 cells expressing FLAG-SLC7A1 were lysed and the interaction between Retromer components and FLAG-SLC7A1 was determined following immunoprecipitation with anti-FLAG M2 affinity gel by immunoblot. (m) H2O2 regulates Retromer-SLC7A1 interactions. K562 cells stably expressing FLAG-SLC7A1 were treated with 100 µM H2O2 for 6 h. anti-FLAG immunoprecipitants were generated from cellular lysate and the enriched proteins were determined by immunoblot. (n) Top, topological map of SLC7A1 indicating the location of membrane spanning passes. Bottom, sequence verification of SLC7A1-WT and SLC7A1-depleted K562 clones. Scale bar=10 µm.
Extended Data Fig. 7 SLC7A1 regulates Arg import which is sufficient to control nuclear H2O2 levels.
(a) SLC7A1 knockout reduces cellular ROS levels. ROS levels were assessed by flow cytometry measuring changes in DCF fluorescence in SLC7A1-WT or -depleted K562 cells treated with DMSO or 2.5 µM AUR for 6 h. Gating strategy was described as Extended Data Fig. 1f. (b) Arg depletion reduces cellular ROS levels. K562 cells were grown in media containing 100% Arg or 5% Arg for 72 h followed by treatment with DMSO or 2.5 µM AUR for 6 h. ROS levels were assessed as described in (a). Gating strategy was described as Extended Data Fig. 1f. (c) L-Arg is decreased in VPS35 depleted cells. Plot comparing fold change and significance of polar metabolites between K562 cells replete and depleted of VPS35. Polar metabolites (grey dots) and amino acids (black dots) were analyzed by mass spectrometry and their relative levels were normalized to total cellular protein (n = 3 biologically independent samples) (see also methods, Supplemental Table 9). (d) L-Arg is decreased in SLC7A1 depleted cells. L-Arg levels were measured as described in (c) from SLC7A1 WT or depleted K562 cells (n = 3 biologically independent samples. (e) Arg functions downstream of VPS35 in regulation of nuclear H2O2. K562 cells expressing HyPer7-NLS and WT or depleted for VPS35 were grown in media containing the indicated levels of Arg. Nuclear H2O2 levels were determined by quantifying ratiometric (Ox/Red) images of nuclear HyPer7. (f-g) A cell permeable L-Arg analog (L-Arg ethyl ester, Arg-ee) reverts a decrease in nuclear H2O2 levels following disruption of VPS35-SLC7A1 axis. K562 cells expressing HyPer7-NLS and WT or depleted for VPS35 (e) or SLC7A1 (f) were grown in media containing the indicated amino acid analogs and treated with AUR (2.5 µM, 6 h). (h) Lys depletion does not reduce nuclear H2O2 levels following anti-cancer drug treatment. K562 cells expressing HyPer7-NLS were grown in media containing the indicated levels of Lys for 72 h and then treated with DMSO, 5.1 µM ATO, 8.3 µM CPT, 2.5 µM AUR or 1.5 µM LAP for 6 h, whereupon ratiometric (Ox/Red) images of HyPer7 were obtained. (i-j) SLC7A1 loss or Arg depletion decreases mitochondrial H2O2 levels. Representative images of SLC7A1-WT or –depleted K562 cells (i) or K562 cells starved of Arg (j) and expressing Mito-HyPer7 were treated with the indicated anti-cancer agents (2.5 µM AUR or 1.5 µM LAP for 6 h). (k-l) Depletion of SLC7A1 or Arg levels decreases mitochondrial superoxide levels. SLC7A1-WT or –depleted K562 cells (k) or K562 cells starved of Arg (l) were treated with AUR (2.5 µM, 6 h) and mitochondrial superoxide levels were measured. Gating strategy was described as Extended Data Fig. 1f. (m-n) VPS35-SLC7A1 axis controls ETC levels and complex I activity. K562 cells expressing the indicated cells or grown in media as described in (j) were analyzed by blue native gel for ETC complex levels and (m) and complex I activity (n) (see methods). Scale bar=10 µm. Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired). Scale bar=10 µm.
Source Data
Extended Data Fig. 8 The Retromer-SLC7A1-Arg axis regulates mitochondrial translation.
(a) Quantification of mitochondrial and cytosolic translation in K562 cells at basal states. K562 cells were pretreated with 335.4 µM CHX to measure mitochondrial translation or 11.5 µM Doxy to measure cytosolic translation and then labeled with 250 µM L-HPG followed by bioconjugation of an azide-containing fluorescent probe (see also Fig. 4b, n = 50 cells). (b-c) VPS35 knockout decreases mitochondrial (b) but not cytosolic translation (c). Left, representative images of L-HPG incorporation into mitochondrial or cytosolically encoded proteins in K562 cells WT or depleted for VPS35. VPS35-depleted K562 cells expressing PAM-mutant WT VPS35 or VPS35•C673D were pre-treated with 11.5 µM Doxy for 1 h or 335.3 µM CHX for 1 h, followed by a release for the indicated time points. Right, quantification of compartmentalized L-HPG incorporation (n = 50 cells). (d-e) SLC7A1 depletion decreases mitochondrial (d) but not cytosolic translation (e). Left, representative images of L-HPG incorporation into mitochondrial or cytosolically encoded proteins in K562 cells WT or depleted for VPS35 which were treated as in (b-c) to measure mitochondrial or cytosolic translation rates. Right, quantification of compartmentalized L-HPG incorporation (n = 50 cells). (f-g) Arg depletion decreases mitochondrial translation (f) but not cytosolic translation (g). Left, representative images of L-HPG incorporation into mitochondrial or cytosolically encoded proteins in K562 cells grown in media containing the indicated amount of Arg. Cells were treated as in (b-c) to measure mitochondrial or cytosolic translation. Right, quantification of compartmentalized L-HPG incorporation (n = 50 cells). (h-i) HeLa (h) or OVISE (i) cells grown in media with reduced Arg levels have reduced mitochondrial translation. Left, representative immunofluorescent images of cells pre-treated with 355.4 µM CHX were exposed to 250 µM L-HPG at indicated timepoints. Right, L-HPG incorporation into newly synthesized mitochondrial proteins was quantified by bioconjugation to an azido fluorophore followed by immunostaining (n = 42 cells for 100% Arg in Hela, n = 37 cells for 5% Arg in Hela, n = 30 cells for both 100% Arg and 5% Arg examined). (j-k) VPS35-depleted HeLa (j) or OVISE (k) cell lines stably expressing VPS35– or VPS35•C673D-PAM mutants pre-treated with 355.4 µM CHX were exposed to 250 µM L-HPG at indicated timepoints (left). L-HPG incorporation into newly synthesized mitochondrial proteins was quantified by bioconjugation to an azido fluorophore followed by immunostaining (right, n = 42 cells for VPS35 WT addback in Hela, n = 37 cells for VPS35•C673D addback in VPS35-depleted Hela, n = 30 cells for both VPS35 WT and VPS35•C673D addback in VPS35-depleted OVISE examined). (l) The VPS35•C673D oxidation mutant decreases mitochondrial translation. K562 cells WT or depleted for VPS35 which were treated as in (b-c) to measure mitochondrial translation. Expression of MT-CO2 was determined by immunoblot and normalized to β-actin (see Methods). (m) Lowering Arg levels decreases mitochondrial translation. K562 cells were pre-treated with Doxy for 72 h and then grown in media containing the indicated concentrations of Arg and MT-C02 expression was determined as in (m). (n-o) Cell permeable Arg rescues mitochondrial translation inhibition upon inactivation of VPS35 (n) or SLC7A1 (o). Left, representative images of compartmentalized HPG-incorporation into K562 cells depleted for VPS35 and expressing PAM mutant VPS35 WT or VPS35•C673D (p) or depleted for SLC7A1 following growth in media supplemented with the indicated amino acids and mitochondrial translation was measured as described in (b). Right, quantification of mitochondrial HPG incorporation (n = 30 cells). Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired). Scale bar=10 µm.
Source Data
Extended Data Fig. 9 The Retromer-SLC7A1-Arg axis regulates mtRNAArg charging.
(a-b) Modulation of SLC7A1 or Arg levels disrupt mtRNAArg charging. Total RNA was isolated from SLC7A1-depleted K562 cells (a) or K562 cells grown in the indicated concentrations of Arg (b) and the relative charging of mitochondrial or cytosolic tRNAArg species was determined by qPCR with primers specific to each tRNA species (n = 3 biologically independent experiments examined, mean ± SEM). (c-h) HeLa (c-d), OVISE (e-f) or PEO1 (g-h) cells expressing VPS35•C673D oximimetic or grown in media with reduced Arg levels have decreased mitochondrial tRNAArg charging. Plot representing relative charging states of mitochondrial tRNAArg or cytosolic tRNAArg isolated from cells expressing the indicated mutants or treatment conditions. tRNA charging was determined as described in (a-b) (n = 3 biologically independent experiments examined, (mean ± SEM). (i) mt-tRNAArg charging is rescued by L-Arg ethyl ester following inactivation of SLC7A1. Total RNA was isolated from sgSLC7A1_Clone_1 K562 cells grown in media containing the indicated Arg analogs. Charging levels for each tRNA species was determined as in (a-b) (n = 3 biologically independent experiments examined, (mean ± SEM) (see also methods). (j-k) Heatmap analysis depicting the ratio of VPS35/β-actin for each cell line indicated as determined by immunoblot. (c) Cells expressing lower levels of VPS35 have higher IC50-values for anti-cancer agents. Plot comparing the IC50-values for each drug (see also Fig. 1a) between the top and bottom quartiles of cell line panel stratified based on VPS35 expression. (l) Depletion of VPS35 provides resistance to cisplatin treatment in non small cell lung cancer (NSCLC) cell lines. Cisplatin IC50-values were determined in lung cancer cell lines expressing the indicated sgRNAs by measuring relative ATP concentrations 96 h after treatment (n = 6 biologically independent samples). (m) Oxidation of VPS35•C673 provides resistance to cisplatin treatment in the NSCLC cell line H1792. Cisplatin IC50 values were determined as in (l) in VPS35-depleted H1792 cells expressing VPS35 and VPS35•C673D PAM mutants (n = 6 biologically independent samples). Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired). Scale bar=10 µm.
Source Data
Extended Data Fig. 10 Decreasing VPS35 levels mediates cisplatin resistance.
(a) Oxidation mutant of VPS35•C673 mediates resistance to cisplatin treatment in PEO1. Left, immunoblot analysis of VPS35 in VPS35-depleted PEO1 cells expressing VPS35 or VPS35•C673D PAM mutants. Right, DDP IC50-values were determined in VPS35-depleted PEO1 cells expressing VPS35–PAM and VPS35•C673D-PAM mutants (n = 6 biologically independent samples). (b) Oxidation of VPS35 decreases mitochondrial translation. Left, representative images of L-HPG incorporation into the indicated PEO1 cells lines. Right, quantification of L-HPG incorporation for the indicated cell lines (n = 30 cells). (c) Cisplatin-resistant ovarian cancers have decreased mitochondrial translation. Quantification of L-HPG incorporation into parental and DDP-resistant Kuramochi or CaOV3 ovarian cancer cell lines (see also Fig. 4k, n = 30 cells). (d-e) Immunoblot analysis of VPS35 in ovarian (d) and lung cancer (e) cell lines expressing the indicated sgRNAs. Data are represented as mean ± SEM. Statistical significance was determined by Student’s t test (two-tailed, unpaired). Scale bar=10 µm.
Source Data
Supplementary information
Supplementary Information
Supplementary Fig.1 uncropped western blot gel images.
Reporting Summary
Supplementary Tables
Supplementary Tables 1–9.
Source data
Source Data Fig. 1
Source Data Fig. 4
Source Data Extended Data Fig. 1
Source Data Extended Data Fig. 3
Source Data Extended Data Fig. 4
Source Data Extended Data Fig. 5
Source Data Extended Data Fig. 7
Source Data Extended Data Fig. 8
Source Data Extended Data Fig. 9
Source Data Extended Data Fig. 10
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
Zhang, J., Ali, M.Y., Chong, H.B. et al. Oxidation of retromer complex controls mitochondrial translation. Nature (2025). https://doi.org/10.1038/s41586-025-08756-y
Download citation
Received:04 June 2024
Accepted:07 February 2025
Published:26 March 2025
DOI:https://doi.org/10.1038/s41586-025-08756-y
Share this article
Anyone you share the following link with will be able to read this content:
Get shareable link
Sorry, a shareable link is not currently available for this article.
Copy to clipboard
Provided by the Springer Nature SharedIt content-sharing initiative