TY - JOUR
T1 - A metabologenomic approach reveals changes in the intestinal environment of mice fed on american diet
AU - Ishii, Chiharu
AU - Nakanishi, Yumiko
AU - Murakami, Shinnosuke
AU - Nozu, Ryoko
AU - Ueno, Masami
AU - Hioki, Kyoji
AU - Aw, Wanping
AU - Hirayama, Akiyoshi
AU - Soga, Tomoyoshi
AU - Ito, Mamoru
AU - Tomita, Masaru
AU - Fukuda, Shinji
N1 - Funding Information:
This study was supported in part by JSPS KAKENHI (grants no. 16H04901, 17H05654 and 18H04805 to S.F.); JST PRESTO (grant no. JPMJPR1537 to S.F.); Taikichiro Mori Memorial Research Grants (to C.I.); the Yamagata Prefectural Government; and the City of Tsuruoka (to M.T.).
Funding Information:
Funding: This study was supported in part by JSPS KAKENHI (grants no. 16H04901, 17H05654 and 18H04805 to S.F.); JST PRESTO (grant no. JPMJPR1537 to S.F.); Taikichiro Mori Memorial Research Grants (to C.I.); the Yamagata Prefectural Government; and the City of Tsuruoka (to M.T.).
Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2018
Y1 - 2018
N2 - Intestinal microbiota and their metabolites are strongly associated with host physiology. Developments in DNA sequencing and mass spectrometry technologies have allowed us to obtain additional data that enhance our understanding of the interactions among microbiota, metabolites, and the host. However, the strategies used to analyze these datasets are not yet well developed. Here, we describe an original analytical strategy, metabologenomics, consisting of an integrated analysis of mass spectrometry-based metabolome data and high-throughput-sequencing-based microbiome data. Using this approach, we compared data obtained from C57BL/6J mice fed an American diet (AD), which contained higher amounts of fat and fiber, to those from mice fed control rodent diet. The feces of the AD mice contained higher amounts of butyrate and propionate, and higher relative abundances of Oscillospira and Ruminococcus. The amount of butyrate positively correlated with the abundance of these bacterial genera. Furthermore, integrated analysis of the metabolome data and the predicted metagenomic data from Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) indicated that the abundance of genes associated with butyrate metabolism positively correlated with butyrate amounts. Thus, our metabologenomic approach is expected to provide new insights and understanding of intestinal metabolic dynamics in complex microbial ecosystems.
AB - Intestinal microbiota and their metabolites are strongly associated with host physiology. Developments in DNA sequencing and mass spectrometry technologies have allowed us to obtain additional data that enhance our understanding of the interactions among microbiota, metabolites, and the host. However, the strategies used to analyze these datasets are not yet well developed. Here, we describe an original analytical strategy, metabologenomics, consisting of an integrated analysis of mass spectrometry-based metabolome data and high-throughput-sequencing-based microbiome data. Using this approach, we compared data obtained from C57BL/6J mice fed an American diet (AD), which contained higher amounts of fat and fiber, to those from mice fed control rodent diet. The feces of the AD mice contained higher amounts of butyrate and propionate, and higher relative abundances of Oscillospira and Ruminococcus. The amount of butyrate positively correlated with the abundance of these bacterial genera. Furthermore, integrated analysis of the metabolome data and the predicted metagenomic data from Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) indicated that the abundance of genes associated with butyrate metabolism positively correlated with butyrate amounts. Thus, our metabologenomic approach is expected to provide new insights and understanding of intestinal metabolic dynamics in complex microbial ecosystems.
KW - American diet
KW - CE-TOFMS
KW - Intestinal microbiota
KW - Metabologenomics
KW - Metabolome
KW - Microbiome
KW - Multi-omics
KW - Next-generation sequencing
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U2 - 10.3390/ijms19124079
DO - 10.3390/ijms19124079
M3 - Article
C2 - 30562947
AN - SCOPUS:85058877089
SN - 1661-6596
VL - 19
JO - International journal of molecular sciences
JF - International journal of molecular sciences
IS - 12
M1 - 4079
ER -