An integrative multi-omic analysis defines gut microbiota, mycobiota, and metabolic fingerprints in ulcerative colitis patients

被引:3
|
作者
Scanu, Matteo [1 ]
Toto, Francesca [1 ]
Petito, Valentina [2 ]
Masi, Letizia [2 ]
Fidaleo, Marco [3 ,4 ]
Puca, Pierluigi [2 ,5 ]
Baldelli, Valerio [1 ]
Reddel, Sofia [1 ]
Vernocchi, Pamela [1 ]
Pani, Giovambattista [5 ]
Putignani, Lorenza [6 ,7 ]
Scaldaferri, Franco [2 ,5 ]
Del Chierico, Federica [1 ]
机构
[1] Bambino Gesu Pediat Hosp, Unit Human Microbiome, Immunol Rheumatol & Infect Dis Res Area, IRCCS, Rome, Italy
[2] Fdn Policlin Univ Agostino Gemelli IRCCS, Dipartimento Sci Med & Chirurg, Unita Operat Semplice Malattie Infiammatorie Cron, Unita Operat Complessa Med Interna & Gastroenterol, Rome, Italy
[3] Sapienza Univ Rome, Dept Biol & Biotechnol Charles Darwin, Rome, Italy
[4] Sapienza Univ Rome, CNIS Res Ctr Nanotechnol Appl Engn, Rome, Italy
[5] Univ Cattolica Sacro Cuore, Dipartimento Med & Chirurg Traslaz, Rome, Italy
[6] Bambino Gesu Pediat Hosp, Unit Microbiol & Diagnost Immunol, Unit Microbi, IRCCS, Rome, Italy
[7] Bambino Gesu Pediat Hosp, Unit Human Microbiome, Res Area Immunol Rheumatol & Infect Dis, IRCCS, Rome, Italy
关键词
inflammatory bowel disease; ulcerative colitis; dysbiosis; gut microbiota; gut metabolism; intestinal biomarkers; multi-omic integrated approaches; 16S RIBOSOMAL-RNA; MUCIN SULFATASE; DISEASE; FECES;
D O I
10.3389/fcimb.2024.1366192
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background Ulcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD) that affects the large intestine with superficial mucosal inflammation. A dysbiotic gut microbial profile has been associated with UC. Our study aimed to characterize the UC gut bacterial, fungal, and metabolic fingerprints by omic approaches.Methods The 16S rRNA- and ITS2-based metataxonomics and gas chromatography-mass spectrometry/solid phase microextraction (GC-MS/SPME) metabolomic analysis were performed on stool samples of 53 UC patients and 37 healthy subjects (CTRL). Univariate and multivariate approaches were applied to separated and integrated omic data, to define microbiota, mycobiota, and metabolic signatures in UC. The interaction between gut bacteria and fungi was investigated by network analysis.Results In the UC cohort, we reported the increase of Streptococcus, Bifidobacterium, Enterobacteriaceae, TM7-3, Granulicatella, Peptostreptococcus, Lactobacillus, Veillonella, Enterococcus, Peptoniphilus, Gemellaceae, and phenylethyl alcohol; and we also reported the decrease of Akkermansia; Ruminococcaceae; Ruminococcus; Gemmiger; Methanobrevibacter; Oscillospira; Coprococus; Christensenellaceae; Clavispora; Vishniacozyma; Quambalaria; hexadecane; cyclopentadecane; 5-hepten-2-ol, 6 methyl; 3-carene; caryophyllene; p-Cresol; 2-butenal; indole, 3-methyl-; 6-methyl-3,5-heptadiene-2-one; 5-octadecene; and 5-hepten-2-one, 6 methyl. The integration of the multi-omic data confirmed the presence of a distinctive bacterial, fungal, and metabolic fingerprint in UC gut microbiota. Moreover, the network analysis highlighted bacterial and fungal synergistic and/or divergent interkingdom interactions.Conclusion In this study, we identified intestinal bacterial, fungal, and metabolic UC-associated biomarkers. Furthermore, evidence on the relationships between bacterial and fungal ecosystems provides a comprehensive perspective on intestinal dysbiosis and ecological interactions between microorganisms in the framework of UC.
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页数:13
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