已发表论文

肠道微生物群、尿液代谢组和血浆蛋白质组的多组学分析显示,色氨酸吲哚衍生物引起的过敏发生了显著变化

 

Authors Zhen J, Zhao P, Li Y, Cai Y, Yu W, Wang W, Zhao L, Wang H, Huang G, Xu A

Received 18 August 2021

Accepted for publication 18 January 2022

Published 29 January 2022 Volume 2022:15 Pages 117—131

DOI https://doi.org/10.2147/JAA.S334752

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 4

Editor who approved publication: Dr Luis Garcia-Marcos

Objective: To explore changes in the gut microbiota (GM), urine metabolome and plasma proteome in individuals with allergies using multiomics analyses, and identify the key components and mechanism.
Methods: This was a cross-sectional study. All subjects were recruited to collect fecal, urine and blood samples. 16S rDNA sequencing was used to analyze the structure and function of the GM, liquid chromatography mass spectrometry was used to quantify metabolites in the urine, and data-independent acquisition quantitative proteome analysis was used to detect proteins in the plasma. Differences in GM, urine metabolites and plasma proteins between allergic and healthy individuals were displayed using principal component analysis (PCoA) and heatmap, and the co-occurrence network was visualized in Cytoscape using Spearman correlation among differential predominant genera, metabolites and proteins. The functional analysis was performed according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) dataset. The allergy-related cytokines, IL-4, IL-6 and IL-13, were measured to evaluate the effect of indole derivatives on LPS-induced macrophage activation.
Results: GM α indexes, β distances and the relative abundance of the core differential genera in the allergic group were different from those of healthy individuals, which resulted in a separate distribution in the PCoA and enterotypes. Similarly, the concentrations of 393 metabolites and 144 proteins were different between allergic and healthy individuals. Then, 634 significant correlations were identified among 6 predominant differential genera, 24 differential metabolites and 104 differential proteins, 301 of which were negative and 333 of which were positive. Notably, a core network centered on tryptophan metabolites, indole-3-butyric acid (IBA) and indole-3-lactic acid (ILA), displayed high consistency with the results of KEGG pathway analysis. In the LPS-stimulated macrophages, IBA reduced the expression of IL-4 and IL-6, and ILA inhibited the upregulation of IL-6.
Conclusion: The GM, urine metabolome and plasma proteome underwent systematic change in allergic individuals compared to healthy individuals, among which indole derivatives from tryptophan metabolism might play key roles in the progression of allergies and could serve as therapeutic targets of allergy.
Keywords: allergy, multiomics, gut microbiota, urine metabolome, plasma proteome