Fungal exosome-like nanoparticles ameliorate exercise capacity and metabolic health in sleep-deprived mice by modulating the gut microbiota

Abstract

Fungal exosome-like nanoparticles (FELNs) derived from black truffles represent an emerging class of bioactive nanovesicles with potential therapeutic applications, yet their effects on sleep deprivation (SD)-induced impairments remain unexplored. Here, we isolated and characterized FELNs from black truffles and investigated their protective effects in an acute SD mouse model. Oral administration of FELNs for seven consecutive days significantly ameliorated SD-induced declines in grip strength and rotarod endurance, restored blood glucose and glycogen stores, attenuated systemic inflammation, and alleviated oxidative stress Mechanistically, FELNs preserved intestinal barrier integrity by upregulating tight junction proteins ZO-1 and Occludin, as revealed by histology and qPCR. 16S rRNA sequencing demonstrated that FELNs reshaped the gut microbiota by increasing α-diversity, enriching beneficial genera, and suppressing opportunistic pathogens. Untargeted metabolomics further showed that FELNs restored SD-disrupted metabolic pathways, notably sphingolipid metabolism. Correlation analyses linked gut microbiota remodeling to improved energy metabolism, reduced inflammation, and enhanced exercise performance. Collectively, these findings demonstrate that FELNs ameliorate exercise capacity and metabolic health in sleep-deprived mice, highlighting their potential as a natural intervention for SD-related disorders.

Graphical abstract: Fungal exosome-like nanoparticles ameliorate exercise capacity and metabolic health in sleep-deprived mice by modulating the gut microbiota

Supplementary files

Article information

Article type
Paper
Submitted
27 Dec 2025
Accepted
30 Apr 2026
First published
12 May 2026

Food Funct., 2026, Advance Article

Fungal exosome-like nanoparticles ameliorate exercise capacity and metabolic health in sleep-deprived mice by modulating the gut microbiota

H. Zhao, W. Sun, G. Yin, F. Zhang, H. Zhu, C. Liu and N. Lu, Food Funct., 2026, Advance Article , DOI: 10.1039/D5FO05659D

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