Fucoidan Inhibits NLRP3 Inflammasome Activation by Enhancing p62/SQSTM1-Dependent Selective Autophagy to Alleviate Atherosclerosis.
Yufei ChengXudong PanJing WangXu LiShaonan YangRuihua YinAijun MaXiaoyan ZhuPublished in: Oxidative medicine and cellular longevity (2020)
NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome activation contributes to the progression of atherosclerosis, and autophagy inhibits inflammasome activation by targeting macrophages. We investigated whether fucoidan, a marine sulfated polysaccharide derived from brown seaweeds, could reduce NLRP3 inflammasome activation by enhancing sequestosome 1 (p62/SQSTM1)-dependent selective autophagy to alleviate atherosclerosis in high-fat-fed ApoE-/- mice with partial carotid ligation and differentiated THP-1 cells incubated with oxidized low-density lipoprotein (oxLDL). Fucoidan significantly ameliorated lipid accumulation, attenuated progression of carotid atherosclerotic plaques, deregulated the expression of NLRP3 inflammasome, autophagy receptor p62, and upregulated microtubule-associated protein light chain 3 (LC3)-II/I levels. Transmission electron microscopy and GFP-RFP-LC3 lentivirus transfection further demonstrated that fucoidan could activate autophagy. Mechanistically, fucoidan remarkably inhibited NLRP3 inflammasome activation, which was mostly dependent on autophagy. The inhibitory effects of fucoidan on NLRP3 inflammasome were enhanced by autophagy activator rapamycin (Rapa) and alleviated by autophagy inhibitor 3-methyladenine (3-MA). Fucoidan promoted the colocalization of NLRP3 and p62. Knockdown of p62 and ATG5 by small interfering RNA significantly reduced the inhibitory effects of fucoidan treatment on NLRP3 inflammasome. The data suggest that fucoidan can inhibit NLRP3 inflammasome activation by enhancing p62/SQSTM1-dependent selective autophagy to alleviate atherosclerosis.
Keyphrases
- nlrp inflammasome
- cell death
- endoplasmic reticulum stress
- signaling pathway
- oxidative stress
- induced apoptosis
- cardiovascular disease
- cell cycle arrest
- type diabetes
- machine learning
- immune response
- skeletal muscle
- electronic health record
- metabolic syndrome
- poor prognosis
- insulin resistance
- deep learning
- long non coding rna
- artificial intelligence
- smoking cessation
- cognitive decline
- nuclear factor