Deep Visual Proteomics maps proteotoxicity in a genetic liver disease
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F25%3A00085671" target="_blank" >RIV/00023001:_____/25:00085671 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11120/25:43928371
Result on the web
<a href="https://www.nature.com/articles/s41586-025-08885-4" target="_blank" >https://www.nature.com/articles/s41586-025-08885-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41586-025-08885-4" target="_blank" >10.1038/s41586-025-08885-4</a>
Alternative languages
Result language
angličtina
Original language name
Deep Visual Proteomics maps proteotoxicity in a genetic liver disease
Original language description
Protein misfolding diseases, including alpha 1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood1, 2-3. We use spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. This dataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show alpha 1-antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. This phenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10700 - Other natural sciences
Result continuities
Project
—
Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Nature
ISSN
0028-0836
e-ISSN
1476-4687
Volume of the periodical
642
Issue of the periodical within the volume
June 2025
Country of publishing house
GB - UNITED KINGDOM
Number of pages
24
Pages from-to
"484–491"
UT code for WoS article
001468265300001
EID of the result in the Scopus database
2-s2.0-105002643795