Strategy for an Association Study of the Intestinal Microbiome and Brain Metabolome Across the Lifespan of Rats

Chen, Tianlu; You, Yijun; Xie, Guoxiang; Zheng, Xiaojiao; Zhao, Aihua; Liu, Jiajian; Zhao, Qing; Wang, Shouli; Huang, Fengjie; Rajani, Cynthia; Wang, Congcong; Chen, Shaoqiu; Ni, Yan; Yu, Herbert; Deng, Youping; Wang, Xiaoyan; Wang, Jia

doi:10.1021/acs.analchem.7b02859

Cited by 34 publications

(29 citation statements)

References 40 publications

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“…2 i). The correlation pairs identified by GRaMM are in line with some previous reports [ 22 , 43 ]. For example, the metabolite DHA and microbial phylum Firmicutes showed a significant nonlinear relationship.…”

Section: Resultssupporting

confidence: 91%

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IP4M: an integrated platform for mass spectrometry-based metabolomics data mining

Liang

Quan²,

Zhou³

et al. 2020

BMC Bioinformatics

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Background Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. Results Integrated mass spectrometry-based untargeted metabolomics data mining (IP4M) software was designed and developed. The IP4M, has 62 functions categorized into 8 modules, covering all the steps of metabolomics data mining, including raw data preprocessing (alignment, peak de-convolution, peak picking, and isotope filtering), peak annotation, peak table preprocessing, basic statistical description, classification and biomarker detection, correlation analysis, cluster and sub-cluster analysis, regression analysis, ROC analysis, pathway and enrichment analysis, and sample size and power analysis. Additionally, a KEGG-derived metabolic reaction database was embedded and a series of ratio variables (product/substrate) can be generated with enlarged information on enzyme activity. A new method, GRaMM, for correlation analysis between metabolome and microbiome data was also provided. IP4M provides both a number of parameters for customized and refined analysis (for expert users), as well as 4 simplified workflows with few key parameters (for beginners who are unfamiliar with computational metabolomics). The performance of IP4M was evaluated and compared with existing computational platforms using 2 data sets derived from standards mixture and 2 data sets derived from serum samples, from GC–MS and LC–MS respectively. Conclusion IP4M is powerful, modularized, customizable and easy-to-use. It is a good choice for metabolomics data processing and analysis. Free versions for Windows, MAC OS, and Linux systems are provided.

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Section: Resultssupporting

confidence: 91%

“…Two real world data sets from our previous animal study were used to validate the performance of the peak table statistical analysis and interpretation [43]. The study was approved by the ethical committee of our hospital.…”

Section: An Application Using Real World Data Setsmentioning

confidence: 99%

IP4M: an integrated platform for mass spectrometry-based metabolomics data mining

Liang

Quan²,

Zhou³

et al. 2020

BMC Bioinformatics

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“…Bile acids in serum, liver, and intestine were measured according to methods previously established by our laboratory [31,32]. An aliquot of 25 µL of serum sample was mixed with 150 µL acetonitrile-methanol (8:2 v/v) containing 6 internal standards (IS) (D4-GCA, D4-GDCA, D4-CA, D4-UDCA, D4-LCA, and D4-GCDCA, 50 nM for each).…”

Section: Measurement Of Basmentioning

confidence: 99%

Anti-Adipogenic Effect of Theabrownin Is Mediated by Bile Acid Alternative Synthesis via Gut Microbiota Remodeling

et al. 2020

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Theabrownin is one of the most bioactive compounds in Pu-erh tea. Our previous study revealed that the hypocholesterolemic effect of theabrownin was mediated by the modulation of bile salt hydrolase (BSH)-enriched gut microbiota and bile acid metabolism. In this study, we demonstrated that theabrownin ameliorated high-fat-diet (HFD)-induced obesity by modifying gut microbiota, especially those with 7α-dehydroxylation on the species level, and these changed microbes were positively correlated with secondary bile acid (BA) metabolism. Thus, altered intestinal BAs resulted in shifting bile acid biosynthesis from the classic to the alternative pathway. This shift changed the BA pool by increasing non-12α-hydroxylated-BAs (non-12OH-BAs) and decreasing 12α-hydroxylated BAs (12OH-BAs), which improved energy metabolism in white and brown adipose tissue. This study showed that theabrownin was a potential therapeutic modality for obesity and other metabolic disorders via gut microbiota-driven bile acid alternative synthesis.

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“…Lipids are a group of metabolites with multiple biological functions that are closely related to various metabolites [46]. Based on accumulating evidence, the gut microbiota, as an environmental factor, modulates the processing, absorption, metabolism, storage, clearance, and other systemic functions of host lipids in the elderly [47][48][49]. Fatty acids are a group of carboxylic acids with different numbers of aliphatic chains that are either saturated or unsaturated.…”

Section: Discussionmentioning

confidence: 99%

Oligosaccharides from Morinda officinalis Slow the Progress of Aging Mice by Regulating the Key Microbiota-Metabolite Pairs

Yang

Chen

et al. 2019

Evidence-Based Complementary and Alternative Medicine

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The gut microbiota is considered an important factor in the progression of Alzheimer’s disease (AD). Active research on the association between the metabolome and the gut microbiome is ongoing and can provide a large amount of beneficial information about the interactions between the microbiome and the metabolome. Previous studies have shown that the oligosaccharides from Morinda officinalis (OMO) can delay the progress of AD in model animals by regulating the diversity of the gut microbiome and metabolic components, and the correlation between the gut microbiome and metabolic components still needs to be further verified. This study applied a new two-level strategy to investigate and ensure the accuracy and consistency of the results. This strategy can be used to determine the association between the gut microbiome and serum metabolome in APP/PS1 transgenic mice and C57BL/6J male mice. The “4C0d-2 spp.-Cholesterol,” “CW040 spp.-L-valine,” “CW040 spp.-L-acetylcarnitine,” “RF39 spp.-L-valine,” “TM7-3 spp.-L-valine,” and “TM7-3 spp.-L-acetylcarnitine” associations among specific “microbiota-metabolite” pairs were further identified based on univariate and multivariate correlation analyses and functional analyses. The key relevant pairs were verified by an independent oligosaccharide intervention study, and the gut microbiome and serum metabolome of the OMO intervention group were similar to those of the normal group. The results indicate that OMO can significantly suppress Alzheimer’s disease by regulating the key microbiota-metabolite pairs. Therefore, this two-level strategy is effective in identifying the principal correlations in large datasets obtained from combinations of multiomic studies and further enhancing our understanding of the correlation between the brain and gut in patients with AD.

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Strategy for an Association Study of the Intestinal Microbiome and Brain Metabolome Across the Lifespan of Rats

Cited by 34 publications

References 40 publications

IP4M: an integrated platform for mass spectrometry-based metabolomics data mining

IP4M: an integrated platform for mass spectrometry-based metabolomics data mining

Anti-Adipogenic Effect of Theabrownin Is Mediated by Bile Acid Alternative Synthesis via Gut Microbiota Remodeling

Oligosaccharides from Morinda officinalis Slow the Progress of Aging Mice by Regulating the Key Microbiota-Metabolite Pairs

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