Abstract
The gut microbiome plays a fundamental role in host health and the fecal metabolome can be analysed to assess microbial activity and can be used as an intermediate phenotype monitoring the host-microbiome relationship. However, there is no established extraction protocol to study the fecal metabolome of giant pandas. The aim of this research is to optimize extraction of the fecal metabolome from adult and baby pandas for high throughput metabolomics analysis using gas chromatography-mass spectrometry (GC-MS). Fecal samples were collected from eight adult pandas and a pair of twin baby pandas. Six different extraction solvents were investigated and evaluated for their reproducibility, metabolite coverage, and extraction efficiency, particularly in relation to the biochemical compound classes such as amino acids, tricarboxylic acid (TCA) cycle intermediates, fatty acids, secondary metabolites, and vitamin and cofactors. Our GC-MS results demonstrated that the extraction solvents with isopropanol: acetonitrile: water (3:2:2 ratio) and 80% methanol were the most appropriate for studying the fecal metabolome of adult and baby giant pandas respectively. These extraction solvents can be used in future study protocols for the analysis of the fecal metabolome in giant pandas.
Highlights
There is increasing evidence that the gut microbiome plays a fundamental role in host health[1]
The gut microbiome is known to be closely associated with host health, physiology, and disease, there are no reported studies of the giant panda’s fecal metabolome
The protocol resulting from our findings could be used to analyze the fecal metabolome of giant pandas which could in turn serve as a functional reflection of the gut microbiome and be used to further understand the influence of the gut microbiome on giant panda health
Summary
There is increasing evidence that the gut microbiome plays a fundamental role in host health[1]. This study was the first to evaluate different extraction solvents to be applied in the process of analyzing the fecal metabolome of adult and baby giant pandas using GC-MS.
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