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Abstract

Selective autophagy involves the recognition and targeting of specific cargo, such as damaged organelles, misfolded proteins, or invading pathogens for lysosomal destruction1,2,3,4. Yeast genetic screens have identified proteins required for different forms of selective autophagy, including cytoplasm-to-vacuole targeting, pexophagy and mitophagy, and mammalian genetic screens have identified proteins required for autophagy regulation5. However, there have been no systematic approaches to identify molecular determinants of selective autophagy in mammalian cells. Here, to identify mammalian genes required for selective autophagy, we performed a high-content, image-based, genome-wide small interfering RNA screen to detect genes required for the colocalization of Sindbis virus capsid protein with autophagolysosomes. We identified 141 candidate genes required for viral autophagy, which were enriched for cellular pathways related to messenger RNA processing, interferon signalling, vesicle trafficking, cytoskeletal motor function and metabolism. Ninety-six of these genes were also required for Parkin-mediated mitophagy, indicating that common molecular determinants may be involved in autophagic targeting of viral nucleocapsids and autophagic targeting of damaged mitochondria. Murine embryonic fibroblasts lacking one of these gene products, the C2-domain containing protein, SMURF1, are deficient in the autophagosomal targeting of Sindbis and herpes simplex viruses and in the clearance of damaged mitochondria. Moreover, SMURF1-deficient mice accumulate damaged mitochondria in the heart, brain and liver. Thus, our study identifies candidate determinants of selective autophagy, and defines SMURF1 as a newly recognized mediator of both viral autophagy and mitophagy.

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Change history

  • 01 December 2011

    Two minor text corrections were made in paragraphs beginning 'Screening of a human siGenome library...' and 'However, a significant decrease...', respectively.

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Acknowledgements

We thank M. Vishwanath, S. Wei and B. Posner for assistance with high-throughput siRNA screening; W. Sun for information technology support; K. Scudder for assistance with image analysis algorithms; A. Diehl for expert medical illustration; V. Stollar, M. McDonald, R. Kuhn and R. Youle for helpful discussions and providing reagents; A. Bugde for assistance in the UTSW Live Cell Imaging Facility; and L. Mueller and T. Januszewski for assistance with electron microscopy. This work was supported by NIH grants AI109617 (B.L.), CA84254 (B.L.), UL1 RR024982 (G.X., Y.X.), AI062773 (R.J.X.), DK83756 (R.J.X.), DK086502 (R.J.X.) and DK043351 (R.J.X. and A.N.); NSF grant DMS-0907562 (G.X.); and the Center for Cancer Research, National Cancer Institute Intramural Research Program (Y.E.Z.).

Author information

Author notes

    • Anthony Orvedahl
    •  & Rhea Sumpter Jr

    These authors contributed equally to this work.

Affiliations

  1. Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Anthony Orvedahl
    • , Rhea Sumpter Jr
    • , Zhongju Zou
    • , Qihua Sun
    •  & Beth Levine
  2. Department of Microbiology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Anthony Orvedahl
    •  & Beth Levine
  3. Center for Autophagy Research, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Rhea Sumpter Jr
    • , Zhongju Zou
    • , Qihua Sun
    •  & Beth Levine
  4. Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Guanghua Xiao
    • , Christian V. Forst
    •  & Yang Xie
  5. Center for Computational and Integrative Biology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA

    • Aylwin Ng
    •  & Ramnik J. Xavier
  6. Gastrointestinal Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA

    • Aylwin Ng
    •  & Ramnik J. Xavier
  7. Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA

    • Aylwin Ng
    •  & Ramnik J. Xavier
  8. Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Zhongju Zou
    •  & Beth Levine
  9. Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA

    • Yi Tang
    •  & Ying E. Zhang
  10. Center for Systems Biology, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario M5G 1X5, Canada

    • Masahiro Narimatsu
    •  & Jeffrey L. Wrana
  11. Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Christopher Gilpin
    •  & Katherine Luby-Phelps
  12. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Michael Roth
  13. Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9113, USA

    • Michael Roth
    • , Yang Xie
    •  & Beth Levine
  14. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada

    • Jeffrey L. Wrana

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Contributions

A.O., R.S., M.N., M.R., J.L.W., Y.E.Z., K.L.-P., C.G. and B.L. designed the experiments. A.O., R.S., Z.Z. Q.S. and Y.T. performed the experiments. G.X., A.N., C.V.F., R.J.X. and Y.X. performed statistical and bioinformatic analyses. A.O., R.S. and B.L. wrote the manuscript. G.X. and A.N. contributed equally to the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Beth Levine.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    The file contains Supplementary Methods, Supplementary References and Supplementary Figures 1-12 with legends. The original file posted online was corrupted and has been replaced on 23 November 2011.

Excel files

  1. 1.

    Supplementary Table 1

    This table lists the primary data for the virus capsid/autophagosome colocalization screen. Shown are the z-scores for each replicate for each gene in the Dharmacon siRNA library. “NA” denotes insufficient numbers of green or red puncta per cell or total number of cells per well for analysis.

  2. 2.

    Supplementary Table 2

    This table lists the data for the virus capsid/autophagosome colocalization confirmation screen, using a customized library (from Dharmacon) composed of individual siRNAs from the pool of 4 siRNAs targeting each gene that scored “positive” in the primary co-localization screen. Genes with p-values of <0.05 for 2 or more individual siRNAs were considered confirmed colocalization hits. “NA” denotes insufficient numbers of green or red dots per cell or total number of cells per well for analysis

  3. 3.

    Supplementary Table 3

    This table lists the results for each individual siRNA from a pool of 4 targeting each gene that scored positive in the primary screen for viral capsid/autophagosome colocalization, with respect to whether they scored positive in the confirmation screen of viral capsid/ autophagosome colocalization (C) screen, the secondary screen for survival of virus-infected cells (S) and the secondary screen for Parkin-mediated mitophagy (M). siRNA sequences are listed in column J. For each siRNA, this table also lists the number of 7-8mer miRNA seed sequences (positions 2-8 on mature miRNA) contained in each siRNA oligo (column K), the identity of such seed sequences (columns L-0), and the specific miRNAs that contain the seed sequences (columns P-S). The confirmed siRNAs in each screen are not enriched for siRNAs containing miRNA seed sequences (P=0.95 for colocalization screen; P=0.71 for cell survival screen; and P=0.97 for mitophagy screen)

  4. 4.

    Supplementary Table 4

    This table lists the predicted targets (identified using TargetScan) for each miRNA seed sequence listed in Supplementary Table 3 (MS Excel spreadsheet, 302 KB).

  5. 5.

    Supplementary Table 5

    This table lists the molecular function and biological process categories from Panther and Gene Ontology, and protein class and pathway assignments from Panther for the siRNA hits in the viral capsid/ autophagosome colocalization screen. Clusters listed correspond to graphical representation in Supplementary Figure 3a (MS Excel spreadsheet, 36 KB).

  6. 6.

    Supplementary Table 6

    This table lists the data from the cell survival screen, using a using a customized library (from Dharmacon) composed of individual siRNAs from the pool of 4 siRNAs targeting each gene that scored “positive” in the primary colocalization screen. Genes with p-values of <0.05 for 2 or more individual siRNAs were considered to be confirmed cell survival factors during viral infection (MS Excel spreadsheet, 36 KB).

  7. 7.

    Supplementary Table 7

    This table lists the data from the mitophagy screen, using a customized library (from Dharmacon) composed of individual siRNAs from the pool of 4 siRNAs targeting each gene that scored “positive” in the primary colocalization screen. Genes with p-values of <0.05 for 2 or more individual siRNAs were considered to be confirmed mitophagy factors.

  8. 8.

    Supplementary Table 8

    This table includes the data in Figure 2a of the main text, with additional details for each gene including Locus ID, Gene Accession numbers, and Gene Annotations from Panther Molecular Function (MF), Panther Biological Process (BP), and UniProt.

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DOI

https://doi.org/10.1038/nature10546

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