The human faecal metabolome is complex, but rich in information and allows investigation of the host metabolism as a function of diet and health. The faecal metabolome is still much less explored than the plasma and urine metabolome, and in order to generate comparable data across laboratories and cohorts, standard operating procedures are required. This study evaluates 10 protocols, using different extraction solvents and sample processing methods for measuring the human faecal metabolome using proton nuclear magnetic resonance (1H NMR) spectroscopy. Three solvents: water, methanol, and dimethyl sulfoxide (DMSO) were investigated at varying concentrations for their ability to extract metabolites directly from faecal slurry or after freeze-drying. The protocols were evaluated on four different pools of human feces. The study also demonstrates a novel signature mapping (SigMa) method for rapid and unbiased processing of complex NMR spectra applied for the first time to human faecal metabolomics. The method is provided with a library containing the chemical shift ranges of 81 common faecal metabolites for future unambiguous and rapid faecal metabolite annotations. The result from the 10 faecal extraction protocols were investigated in terms of reproducibility, coverage, and ability to extract low concentration metabolites. The solvent type was shown to induce the highest variation in the data (45.7%) and the water based extractions allowed detection of the greatest number of metabolites and resulted in the highest reproducibility. Direct extraction of faecal slurry was proved to be more reproducible than freeze-drying. In addition, freeze-drying caused a relative loss of short chain fatty acids (SCFA). DMSO was used for the first time to extract faecal metabolites and enabled the detection of certain bile acids. Some derivatives of SCFA were only detected using methanol as solvent.

The human fecal metabolome is increasingly studied to explore the impact of diet and lifestyle on health and the gut microbiome. However, systematic differences and confounding factors related to age, sex, and diet remain largely unknown. In this study, absolute concentrations of fecal metabolites from 205 healthy Danes (105 males and 100 females, 49 ± 31 years old) were quantified using 1 H NMR spectroscopy and the newly developed SigMa software. The largest systemic variation was found to be highly related to age. Fecal concentrations of short-chain fatty acids (SCFA) were higher in the 18 years old group, while amino acids (AA) were higher in the elderly. Sex-related metabolic differences were weak but significant and mainly related to changes in SCFA. The concentrations of butyric, valeric, propionic, and isovaleric acids were found to be higher in males compared to females. Sex differences were associated with a stronger, possibly masking, effect from differential intake of macronutrients. Dietary fat intake decreased levels of SCFA and AA of both sexes, while carbohydrate intake showed weak correlations with valeric and isovaleric acids in females. This study highlights some possible demographic confounders linked to diet, disease, lifestyle, and microbiota that have to be taken into account when analyzing fecal metabolome data.

This study investigated how body mass index (BMI), physical fitness, and blood plasma lipoprotein levels are related to the fecal metabolome in older adults. The fecal metabolome data were acquired using proton nuclear magnetic resonance spectroscopy and gas chromatography–mass spectrometry on 163 healthy older adults (65–80 years old, 80 females and 83 males). Overweight and obese subjects (BMI ≥ 27) showed higher levels of fecal amino acids (AAs) (valine, alanine, and phenylalanine) compared to normal-weight subjects (BMI ≤ 23.5). Adults classified in the high-fitness group displayed slightly lower concentrations of fecal short-chain fatty acids, propionic acid, and AAs (methionine, leucine, glutamic acid, and threonine) compared to the low-fitness group. Subjects with lower levels of cholesterol in low-density lipoprotein particles (LDLchol, ≤2.6 mmol/L) displayed higher fecal levels of valine, glutamic acid, phenylalanine, and lactic acid, while subjects with a higher level of cholesterol in high-density lipoprotein particles (HDLchol, ≥2.1 mmol/L) showed lower fecal concentration of isovaleric acid. The results from this study suggest that the human fecal metabolome, which primarily represents undigested food waste and metabolites produced by the gut microbiome, carries important information about human health and should be closely integrated to other omics data for a better understanding of the role of the gut microbiome and diet on human health and metabolism.

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