The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Pooled tagging and hydrophobic targeting of endogenous proteins for unbiased mapping of unfolded protein responses
Open accessPreprint — published as 10.1016/j.molcel.2025.04.002
Abstract
System-level understanding of proteome organization and function requires methods for direct visualization and manipulation of proteins at scale. We developed an approach enabled by high-throughput gene tagging for the generation and analysis of complex cell pools with endogenously tagged proteins. Proteins are tagged with HaloTag to enable visualization or direct perturbation. Fluorescent labeling followed by in situ sequencing and deep learning-based image analysis identifies the localization pattern of each tag, providing a bird’s-eye-view of cellular organization. Next, we use a hydrophobic HaloTag ligand to misfold tagged proteins, inducing spatially restricted proteotoxic stress that is read out by single cell RNA sequencing. By integrating optical and perturbation data, we map compartment-specific responses to protein misfolding, revealing inter-compartment organization and direct crosstalk, and assigning proteostasis functions to uncharacterized genes. Altogether, we present a powerful and efficient method for large-scale studies of proteome dynamics, function, and homeostasis.
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
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Flagged first, then by citations
Research works printed but not linked: 99
- 10.1038/s41587-022-01448-2 · DOI · Paper page
- 10.1021/acs.analchem.7b04733 · DOI
- 2023, Recent advances in mass spectrometry imaging of single cells, Anal. Bioanal. Chem, 10, 1007
- 10.1038/s43586-022-00098-7 · DOI
- 10.1038/nrg.2017.97 · DOI · Paper page
- 10.1038/nrg3899 · DOI · Paper page
- 10.1016/j.cell.2019.11.031 · DOI · Paper page
- 10.1021/acs.bioconjchem.5b00191 · DOI
- 10.1073/pnas.1606731113 · DOI
- Cho, N.H. , Cheveralls, K.C. , Brunner, A.-D. , Kim, K. , Michaelis, A.C. , Raghavan, P. , Kobayashi, H. , Savy, L. , Li, J.Y. , Canaj, H. , et al. (2022). OpenCell: Endogenous tagging for the cartography of human cellular organization. Science 375, eabi6983. · DOI · Paper page
- 10.1101/gr.246413.118 · DOI
- 10.1101/gr.261503.120 · DOI
- 10.1021/cb800025k · DOI · Paper page
- 10.1038/s41580-020-0250-z · DOI · Paper page
- 10.1126/science.1209038 · DOI
- 10.1038/nrm.2017.110 · DOI
- 2019, Biomolecular condensates in neurodegeneration and cancer, Traffic, 20, 890, 10.1111/tra.12704 · DOI
- 10.1101/cshperspect.a041259 · DOI
- 10.1016/j.ceb.2014.04.010 · DOI
- 10.1038/nchembio.1638 · DOI
- 10.1091/mbc.E17-11-0693 · DOI
- 10.1091/mbc.E19-01-0069 · DOI
- 10.1038/nchembio.597 · DOI · Paper page
- 10.1021/cb400569k · DOI
- 10.1016/j.cell.2019.09.016 · DOI · Paper page
- 10.1006/excr.1999.4656 · DOI
- 10.1038/nature10348 · DOI
- 10.1016/j.cell.2017.06.010 · DOI · Paper page
- 2019, Chromatin accessibility and the regulatory epigenome, Nat. Rev. Genet, 20, 207, 10.1038/s41576-018-0089-8 · DOI · Paper page
- 10.3390/molecules25112496 · DOI
- 10.1038/emboj.2011.295 · DOI
- 10.1073/pnas.1016071107 · DOI · Paper page
- 2022, Decorating chromatin for enhanced genome editing using CRISPR-Cas9, Proc. Natl. Acad. Sci. U. S. A, 119, e2204259119, 10.1073/pnas.2204259119 · DOI
- 10.1101/2023.04.12.536587 · DOI
- 10.1038/s41467-018-07901-8 · DOI · Paper page
- 10.1038/s41596-021-00653-8 · DOI · Paper page
- 10.1038/nmeth.2563 · DOI · Paper page
- 2022, Self-supervised deep learning encodes high-resolution features of protein subcellular localization, Nat. Methods, 19, 995, 10.1038/s41592-022-01541-z · DOI
- McInnes, L. , Healy, J. , and Melville, J . (2018). UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. arXiv [stat.ML]. · DOI · Paper page
- 2017, hdbscan: Hierarchical density based clustering, J. Open Source Softw, 2, 205, 10.21105/joss.00205 · DOI · Paper page
- 10.1038/75556 · DOI · Paper page
- 10.1093/genetics/iyad031 · DOI
- 10.1101/2022.08.30.505920 · DOI
- 10.1101/2023.03.22.533675 · DOI
- 10.1038/s41580-018-0040-z · DOI · Paper page
- 10.1038/nature21695 · DOI
- 10.1038/s41586-023-06142-0 · DOI
- 2021, ER-misfolded proteins become sequestered with mitochondria and impair mitochondrial function, Commun Biol, 4, 1350, 10.1038/s42003-021-02873-w · DOI
- 10.1083/jcb.201709172 · DOI
- 10.15252/embr.201642195 · DOI · Paper page
- 2020, Mitochondrial stress is relayed to the cytosol by an OMA1-DELE1-HRI pathway, Nature, 579, 427, 10.1038/s41586-020-2078-2 · DOI · Paper page
- 2021, Mitochondria Associated Membranes (MAMs): Architecture and physiopathological role, Cell Calcium, 94, 102343, 10.1016/j.ceca.2020.102343 · DOI
- 10.1038/nature18302 · DOI
- 10.1016/j.molcel.2019.09.026 · DOI
- 2022, Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq, Cell, 185, 2559, 10.1016/j.cell.2022.05.013 · DOI · Paper page
- 2021, Programmable human histone phosphorylation and gene activation using a CRISPR/Cas9-based chromatin kinase, Nat. Commun, 12, 896, 10.1038/s41467-021-21188-2 · DOI
- 10.1038/nmeth.3256 · DOI
- 2019, Rational Design of Fluorogenic and Spontaneously Blinking Labels for Super-Resolution Imaging, ACS Cent Sci, 5, 1602, 10.1021/acscentsci.9b00676 · DOI
- 10.1101/2022.12.27.522042 · DOI
- 10.1016/s0021-9258(18)53882-5 · DOI
- 2023, Small heat shock proteins operate as molecular chaperones in the mitochondrial intermembrane space, Nat. Cell Biol, 25, 467, 10.1038/s41556-022-01074-9 · DOI
- 2023, HaloTag-Based Reporters for Fluorescence Imaging and Biosensing, Chembiochem, 24, e202300022, 10.1002/cbic.202300022 · DOI
- 2022, Quality control of cytoplasmic proteins inside the nucleus, Comput. Struct. Biotechnol. J, 20, 4618, 10.1016/j.csbj.2022.08.033 · DOI
- 10.1371/journal.pone.0076941 · DOI · Paper page
- 10.3390/biom11020173 · DOI
- 10.1038/ncb2738 · DOI · Paper page
- 10.1093/NAR/GKAB1061 · DOI · Paper page
- 10.1021/acschembio.5b00442 · DOI · Paper page
- 10.1021/acschembio.1c00693 · DOI · Paper page
- Serebrenik, Y.V. , Mani, D. , Maujean, T. , Burslem, G.M. , and Shalem, O . (2023). Pooled endogenous protein recruitment identifies CTLH E3 ligase complex members as potent effectors for targeted protein degradation. BioRxiv.
- 10.1126/science.1247005 · DOI · Paper page
- 10.1038/nbt.3437 · DOI · Paper page
- 10.1038/nmeth.3047 · DOI · Paper page
- 2012, Identification of hydrophobic tags for the degradation of stabilized proteins, Chembiochem, 13, 538, 10.1002/cbic.201100793 · DOI
- 2023, UniProt: the Universal Protein Knowledgebase in 2023, Nucleic Acids Res, 51, D523, 10.1093/nar/gkac1052 · DOI · Paper page
- 10.1074/mcp.M500279-MCP200 · DOI
- 10.1126/science.aal3321 · DOI · Paper page
- 10.1038/s41586-022-04558-8 · DOI · Paper page
- 10.1093/nar/gkab1058 · DOI
- 10.1093/NAR/GKAB1049 · DOI · Paper page
- 10.1038/nbt.3804 · DOI
- 2017, Flexible CRISPR library construction using parallel oligonucleotide retrieval, Nucleic Acids Res, 45, e101, 10.1093/nar/gkx181 · DOI
- 10.1101/gr.245571.118 · DOI
- 2019, NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning, Proteins, 87, 520, 10.1002/prot.25674 · DOI
- 10.1093/nar/gkh103 · DOI
- 10.1038/s41592-020-01018-x · DOI · Paper page
- 10.1038/s41592-022-01663-4 · DOI · Paper page
- 2021, Parametric UMAP Embeddings for Representation and Semisupervised Learning, Neural Comput, 33, 2881
- 10.1038/ncomms14049 · DOI · Paper page
- 10.1093/biostatistics/kxj037 · DOI · Paper page
- 2019, DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors, Cell Syst, 8, 329, 10.1016/j.cels.2019.03.003 · DOI · Paper page
- 10.1093/nar/gkm226 · DOI
- 10.1038/s41587-020-0439-x · DOI
- 10.1093/bioinformatics/bts635 · DOI · Paper page
- 10.1038/nmeth.4197 · DOI · Paper page
- 10.1093/bioinformatics/btp352 · DOI · Paper page
- 10.1093/bioinformatics/bts356 · DOI
- 10.1093/bioinformatics/bts503 · DOI
- 10.1038/nmeth.2375 · DOI
Cited by
Sorted by citations
Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView
Kudo, T., Meireles, A. M., Moncada, R., Chen, Y., Wu, P., Gould, J., Hu, X., Kornfeld, O., Jesudason, R., Foo, C., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02391-0 · Cited by 74
Metadata
- Authors
- Sansbury, S. E., Serebrenik, Y. V., Lapidot, T., Burslem, G. M., & Shalem, O.
- Affiliations
- Children's Hospital of Philadelphia (US)
- University of Pennsylvania (US)
- Corresponding author
- Serebrenik, Yevgeniy V.
- Shalem, Ophir
- Venue
- Molecular Cell
- Publisher
- openRxiv
- Published
- 2023-07-14
- Volume
- 85
- Issue
- 9
- Pages
- 1868-1886.e12
- ISSN
- 1097-2765 (ISSN-L)
- PMC
- PMC12115883
- OpenAlex
- W4409730592
- Cited by
- 21
- References
- 1
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 7 · 2023: 1
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Cell (acceptedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- SSRN Electronic Journal (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- Pennsylvania Department of Health
- Center for Strategic Scientific Initiatives, National Cancer Institute (F32CA239499)
- National Institutes of Health
- National Institute on Aging (K99AG075256, R00AG075256)
- National Human Genome Research Institute (F31HG011185)
- National Cancer Institute (F32CA239499)
- National Institute of General Medical Sciences (4100083086, T32GM008216, DP2GM137416, R35GM142505)
- National Institute of Neurological Disorders and Stroke (R03NS111447)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Lipid Membrane Structure and Behavior
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular transport and secretion
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Endoplasmic Reticulum Stress and Disease
- Keywords
- membrane tubulation, glycocalyx, glycopolymers, spontaneous curvature, line tension, polymer physics, Golgi apparatus, endoplasmic reticulum
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