Fecal Microbiota As a Non-Invasive Biomarker to Predict the Tissue Iron Accumulation in Intestine Epithelial Cells and Liver
55 Pages Posted: 17 May 2019More...
Iron is an essential trace mineral for the growth, systemic metabolism, and immune response. Dysregulation of iron homeostasis is linked with the development and progression of various diseases. The excessive iron accumulation is highly associated with inflammatory diseases and cancer while iron deficiency leads to growth retardation. Multiple studies have suggested that iron dysbiosis results in alteration of gut microbiota, leading to the disruption of microbial diversity, increase of pathogen abundance and induction of intestinal inflammation. However, screening the widespread studies in the past decades, the association between iron availability and gut microbiota are not completely explored. Furthermore, non-invasive and convenient approach to determine the tissue iron is still limited. In the current study, a murine model for iron dysbiosis was established. 16S rRNA amplicon sequencing and innovated bioinformatic algorithms are utilized to identify key microbiota. Leveraging on these key microbiotas, we established an easily assessible prediction model, which could accurately distinguish the individual under either iron-deprived or iron-fortified condition and precisely predict the tissue iron level of intestine epithelial cells and liver. This could be further applied for early diagnosis of iron dysbiosis-related diseases as a non-invasive approach.
Funding Statement: This work was support by ‘GDAS’ Project of Science and Technology Development (Grant No. 2018GDASCX-0806) to Liwei Xie and supported by National Natural Science Foundation of China (Grant No.: 8187050617) to Jiyang Pan.
Declaration of Interests: The authors declare that there is no conflict of financial or research interest.
Ethics Approval Statement: The animal protocol was proved by the Institute Animal Care Use Committees of GDIM (Permission #: GT-IACUC201704071).
Keywords: Gut microbiota, Iron, RDA, Random forest, LASSO, Ferritin assay, Tissue biopsies
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