The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
A cross-kingdom conserved ER-phagy receptor maintains endoplasmic reticulum homeostasis during stress
Open accessAbstract
Eukaryotes have evolved various quality control mechanisms to promote proteostasis in the endoplasmic reticulum (ER). Selective removal of certain ER domains via autophagy (termed as ER-phagy) has emerged as a major quality control mechanism. However, the degree to which ER-phagy is employed by other branches of ER-quality control remains largely elusive. Here, we identify a cytosolic protein, C53, that is specifically recruited to autophagosomes during ER-stress, in both plant and mammalian cells. C53 interacts with ATG8 via a distinct binding epitope, featuring a shuffled ATG8 interacting motif (sAIM). C53 senses proteotoxic stress in the ER lumen by forming a tripartite receptor complex with the ER-associated ufmylation ligase UFL1 and its membrane adaptor DDRGK1. The C53/UFL1/DDRGK1 receptor complex is activated by stalled ribosomes and induces the degradation of internal or passenger proteins in the ER. Consistently, the C53 receptor complex and ufmylation mutants are highly susceptible to ER stress. Thus, C53 forms an ancient quality control pathway that bridges selective autophagy with ribosome-associated quality control in the ER.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Floral dip: a simplified method forAgrobacterium‐mediated transformation ofArabidopsis thaliana
Clough, S. J., & Bent, A. F. (1998) · The Plant Journal · doi:10.1046/j.1365-313x.1998.00343.x · Cited by 21,934
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
The Unfolded Protein Response: From Stress Pathway to Homeostatic Regulation
Walter, P., & Ron, D. (2011) · Science · doi:10.1126/science.1209038 · Cited by 5,924
A guided tour into subcellular colocalization analysis in light microscopy
BOLTE, S., & CORDELIÈRES, F. P. (2006) · Journal of Microscopy · doi:10.1111/j.1365-2818.2006.01706.x · Cited by 5,324
SignalP 5.0 improves signal peptide predictions using deep neural networks
Almagro Armenteros, J. J., Tsirigos, K. D., Sønderby, C. K., Petersen, T. N., Winther, O., Brunak, S., von Heijne, G., & Nielsen, H. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0036-z · Cited by 4,284
The EMBL-EBI search and sequence analysis tools APIs in 2019
Madeira, F., Park, Y. M., Lee, J., Buso, N., Gur, T., Madhusoodanan, N., Basutkar, P., Tivey, A. R. N., Potter, S. C., Finn, R. D., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz268 · Cited by 4,167
Mechanism and medical implications of mammalian autophagy
Dikic, I., & Elazar, Z. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0003-4 · Cited by 2,771
Semi-supervised learning for peptide identification from shotgun proteomics datasets
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S., & MacCoss, M. J. (2007) · Nature Methods · doi:10.1038/nmeth1113 · Cited by 2,424
Cited by
The mechanisms and roles of selective autophagy in mammals
Vargas, J. N. S., Hamasaki, M., Kawabata, T., Youle, R. J., & Yoshimori, T. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-022-00542-2 · Cited by 1,016
Russo, S., Kwiatkowski, M., Govorukhina, N., Bischoff, R., & Melgert, B. N. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.746151 · Cited by 269
Autophagy and organelle homeostasis in cancer
Miller, D. R., & Thorburn, A. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.02.010 · Cited by 258
Human UFSP1 is an active protease that regulates UFM1 maturation and UFMylation
Millrine, D., Cummings, T., Matthews, S. P., Peter, J. J., Magnussen, H. M., Lange, S. M., Macartney, T., Lamoliatte, F., Knebel, A., & Kulathu, Y. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111168 · Cited by 71
Shuffled ATG8 interacting motifs form an ancestral bridge between UFMylation and autophagy
Picchianti, L., Sánchez de Medina Hernández, V., Zhan, N., Irwin, N. A., Groh, R., Stephani, M., Hornegger, H., Beveridge, R., Sawa‐Makarska, J., Lendl, T., et al. (2023) · The EMBO Journal · doi:10.15252/embj.2022112053 · Cited by 50
Self-citation
Metadata
- Authors
- Stephani, M., Picchianti, L., Gajic, A., Beveridge, R., Skarwan, E., Sanchez de Medina Hernandez, V., Mohseni, A., Clavel, M., Zeng, Y., Naumann, C., Matuszkiewicz, M., Turco, E., Loefke, C., Li, B., Dürnberger, G., Schutzbier, M., Chen, H. T., Abdrakhmanov, A., Savova, A., Chia, K.-S., Djamei, A., Schaffner, I., Abel, S., Jiang, L., Mechtler, K., Ikeda, F., Martens, S., Clausen, T., & Dagdas, Y.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2020-08-27
- Volume
- 9
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W3080457712
- Cited by
- 253
- References
- 76
- FWCI
- 21.81
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A cross-kingdom conserved ER-phagy receptor maintains endoplasmic reticulum homeostasis during stress. https://app.cochat.ai/papers/10.7554/elife.58396
- The paper
- Stephani, M., Picchianti, L., Gajic, A., Beveridge, R., Skarwan, E., Sanchez de Medina Hernandez, V., Mohseni, A., Clavel, M., Zeng, Y., Naumann, C., Matuszkiewicz, M., Turco, E., Loefke, C., Li, B., Dürnberger, G., Schutzbier, M., Chen, H. T., Abdrakhmanov, A., Savova, A., . . . Dagdas, Y. (2020). A cross-kingdom conserved ER-phagy receptor maintains endoplasmic reticulum homeostasis during stress. eLife. https://doi.org/10.7554/elife.58396
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
