Issue 18, 2022

Selenium-enriched soybean peptides pretreatment attenuates lung injury in mice induced by fine particulate matters (PM2.5) through inhibition of TLR4/NF-κB/IκBα signaling pathway and inflammasome generation

Abstract

This study aimed to identify and prepare peptides from selenium (Se)-enriched soybeans and determine whether dietary Se-enriched soybean peptides (Se-SPep) could inhibit lung injury in mice induced by fine particulate matter 2.5 (PM2.5). BALB/c mice were randomly divided into six groups. The mice in the prevention groups were pretreated with 378 mg kg−1 of Se-SPep, soybean peptides (SPep), and Se-enriched soybean protein (Se-SPro), respectively, for four weeks. The mice in the PM2.5 exposure group received concentrated PM2.5 (15 μg per day mice) for 1 h daily from the third week for two weeks. The results showed that the leukocyte and cytokine (IL-1β, IL-6, TNF-α) levels in the bronchoalveolar lavage fluid (BALF) of the PM2.5 exposure group were higher than those in the control group. Se-SPep pretreatment decreased the IL-1β, IL-6, and TNF-α levels compared with the PM2.5 exposure group. Additionally, Se-SPep pretreatment inhibited TLR4/NF-κB/IκBα and NLRP3/ASC/caspase-1 protein expression in the lungs. In conclusion, Se-SPep pretreatment may protect the lungs of the mice against PM2.5-induced inflammation, suggesting that Se-SPep represents a potential preventative agent to inhibit PM2.5-induced lung injury.

Graphical abstract: Selenium-enriched soybean peptides pretreatment attenuates lung injury in mice induced by fine particulate matters (PM2.5) through inhibition of TLR4/NF-κB/IκBα signaling pathway and inflammasome generation

Article information

Article type
Paper
Submitted
09 Jun 2022
Accepted
12 Aug 2022
First published
13 Aug 2022

Food Funct., 2022,13, 9459-9469

Selenium-enriched soybean peptides pretreatment attenuates lung injury in mice induced by fine particulate matters (PM2.5) through inhibition of TLR4/NF-κB/IκBα signaling pathway and inflammasome generation

J. Zhang, X. Chen, H. Li, W. Liu, X. Liu, Y. Song and X. Cong, Food Funct., 2022, 13, 9459 DOI: 10.1039/D2FO01585D

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