Elucidation of Prebiotics, Probiotics, Postbiotics, and Target from Gut Microbiota to Alleviate Obesity via Network Pharmacology Study

被引:15
作者
Oh, Ki-Kwang [1 ]
Gupta, Haripriya [1 ]
Min, Byeong-Hyun [1 ]
Ganesan, Raja [1 ]
Sharma, Satya Priya [1 ]
Won, Sung-Min [1 ]
Jeong, Jin-Ju [1 ]
Lee, Su-Been [1 ]
Cha, Min-Gi [1 ]
Kwon, Goo-Hyun [1 ]
Jeong, Min-Kyo [1 ]
Hyun, Ji-Ye [1 ]
Eom, Jung-A [1 ]
Park, Hee-Jin [1 ]
Yoon, Sang-Jun [1 ]
Choi, Mi-Ran [1 ]
Kim, Dong Joon [1 ]
Suk, Ki-Tae [1 ]
机构
[1] Hallym Univ, Coll Med, Inst Liver & Digest Dis, Chunchon 24252, South Korea
基金
新加坡国家研究基金会;
关键词
gut microbiota; obesity; equol; isoflavone; Lactobacillus paracasei [!text type='JS']JS[!/text]1; IL6; PROTEIN; GENES;
D O I
10.3390/cells11182903
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The metabolites produced by the gut microbiota have been reported as crucial agents against obesity; however, their key targets have not been revealed completely in complex microbiome systems. Hence, the aim of this study was to decipher promising prebiotics, probiotics, postbiotics, and more importantly, key target(s) via a network pharmacology approach. First, we retrieved the metabolites related to gut microbes from the gutMGene database. Then, we performed a meta-analysis to identify metabolite-related targets via the similarity ensemble approach (SEA) and SwissTargetPrediction (STP), and obesity-related targets were identified by DisGeNET and OMIM databases. After selecting the overlapping targets, we adopted topological analysis to identify core targets against obesity. Furthermore, we employed the integrated networks to microbiota-substrate-metabolite-target (MSMT) via R Package. Finally, we performed a molecular docking test (MDT) to verify the binding affinity between metabolite(s) and target(s) with the Autodock 1.5.6 tool. Based on holistic viewpoints, we performed a filtering step to discover the core targets through topological analysis. Then, we implemented protein-protein interaction (PPI) networks with 342 overlapping target, another subnetwork was constructed with the top 30% degree centrality (DC), and the final core networks were obtained after screening the top 30% betweenness centrality (BC). The final core targets were IL6, AKT1, and ALB. We showed that the three core targets interacted with three other components via the MSMT network in alleviating obesity, i.e., four microbiota, two substrates, and six metabolites. The MDT confirmed that equol (postbiotics) converted from isoflavone (prebiotics) via Lactobacillus paracasei JS1 (probiotics) can bind the most stably on IL6 (target) compared with the other four metabolites (3-indolepropionic acid, trimethylamine oxide, butyrate, and acetate). In this study, we demonstrated that the promising substate (prebiotics), microbe (probiotics), metabolite (postbiotics), and target are suitable for obsesity treatment, providing a microbiome basis for further research.
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页数:14
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