Single-site iron-anchored amyloid hydrogels as catalytic platforms for alcohol detoxification.


Journal

Nature nanotechnology
ISSN: 1748-3395
Titre abrégé: Nat Nanotechnol
Pays: England
ID NLM: 101283273

Informations de publication

Date de publication:
13 May 2024
Historique:
received: 10 10 2023
accepted: 21 03 2024
medline: 14 5 2024
pubmed: 14 5 2024
entrez: 13 5 2024
Statut: aheadofprint

Résumé

Constructing effective antidotes to reduce global health impacts induced by alcohol prevalence is a challenging topic. Despite the positive effects observed with intravenous applications of natural enzyme complexes, their insufficient activities and complicated usage often result in the accumulation of toxic acetaldehyde, which raises important clinical concerns, highlighting the pressing need for stable oral strategies. Here we present an effective solution for alcohol detoxification by employing a biomimetic-nanozyme amyloid hydrogel as an orally administered catalytic platform. We exploit amyloid fibrils derived from β-lactoglobulin, a readily accessible milk protein that is rich in coordinable nitrogen atoms, as a nanocarrier to stabilize atomically dispersed iron (ferrous-dominated). By emulating the coordination structure of the horseradish peroxidase enzyme, the single-site iron nanozyme demonstrates the capability to selectively catalyse alcohol oxidation into acetic acid, as opposed to the more toxic acetaldehyde. Administering the gelatinous nanozyme to mice suffering from alcohol intoxication significantly reduced their blood-alcohol levels (decreased by 55.8% 300 min post-alcohol intake) without causing additional acetaldehyde build-up. Our hydrogel further demonstrates a protective effect on the liver, while simultaneously mitigating intestinal damage and dysbiosis associated with chronic alcohol consumption, introducing a promising strategy in effective alcohol detoxification.

Identifiants

pubmed: 38740933
doi: 10.1038/s41565-024-01657-7
pii: 10.1038/s41565-024-01657-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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Auteurs

Jiaqi Su (J)

Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland. jiaqi.su@hest.ethz.ch.
Particle and Interfacial Technology Group, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium. jiaqi.su@hest.ethz.ch.

Pengjie Wang (P)

Department of Nutrition and Health, Beijing Higher Institution Engineering Research Center of Animal Products, China Agricultural University, Beijing, China.

Wei Zhou (W)

Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland.

Mohammad Peydayesh (M)

Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Jiangtao Zhou (J)

Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Tonghui Jin (T)

Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Felix Donat (F)

Institute of Energy and Process Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.

Cuiyuan Jin (C)

Institute of Translational Medicine, Zhejiang Shuren University, Zhejiang, China.

Lu Xia (L)

ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain.

Kaiwen Wang (K)

ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain.

Fazheng Ren (F)

Department of Nutrition and Health, Beijing Higher Institution Engineering Research Center of Animal Products, China Agricultural University, Beijing, China.

Paul Van der Meeren (P)

Particle and Interfacial Technology Group, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.

F Pelayo García de Arquer (FP)

ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain.

Raffaele Mezzenga (R)

Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland. raffaele.mezzenga@hest.ethz.ch.
Department of Materials, ETH Zurich, Zurich, Switzerland. raffaele.mezzenga@hest.ethz.ch.

Classifications MeSH