Alcohol Induced Alterations to the Human Fecal VOC Metabolome

<div><p>Studies have shown that excessive alcohol consumption impacts the intestinal microbiota composition, causing disruption of homeostasis (dysbiosis). However, this observed change is not indicative of the dysbiotic intestinal microbiota function that could result in the production of injurious and toxic products. Thus, knowledge of the effects of alcohol on the intestinal microbiota function and their metabolites is warranted, in order to better understand the role of the intestinal microbiota in alcohol associated organ failure. Here, we report the results of a differential metabolomic analysis comparing volatile organic compounds (VOC) detected in the stool of alcoholics and non-alcoholic healthy controls. We performed the analysis with fecal samples collected after passage as well as with samples collected directly from the sigmoid lumen. Regardless of the approach to fecal collection, we found a stool VOC metabolomic signature in alcoholics that is different from healthy controls. The most notable metabolite alterations in the alcoholic samples include: (1) an elevation in the oxidative stress biomarker tetradecane; (2) a decrease in five fatty alcohols with anti-oxidant property; (3) a decrease in the short chain fatty acids propionate and isobutyrate, important in maintaining intestinal epithelial cell health and barrier integrity; (4) a decrease in alcohol consumption natural suppressant caryophyllene; (5) a decrease in natural product and hepatic steatosis attenuator camphene; and (6) decreased dimethyl disulfide and dimethyl trisulfide, microbial products of decomposition. Our results showed that intestinal microbiota function is altered in alcoholics which might promote alcohol associated pathologies.</p></div

The Approach to Sample Acquisition and Its Impact on the Derived Human Fecal Microbiome and VOC Metabolome

<div><p>Recent studies have illustrated the importance of the microbiota in maintaining a healthy state, as well as promoting disease states. The intestinal microbiota exerts its effects primarily through its metabolites, and metabolomics investigations have begun to evaluate the diagnostic and health implications of volatile organic compounds (VOCs) isolated from human feces, enabled by specialized sampling methods such as headspace solid-phase microextraction (hSPME). The approach to stool sample collection is an important consideration that could potentially introduce bias and affect the outcome of a fecal metagenomic and metabolomic investigation. To address this concern, a comparison of endoscopically collected (<i>in vivo</i>) and home collected (<i>ex vivo</i>) fecal samples was performed, revealing slight variability in the derived microbiomes. In contrast, the VOC metabolomes differ widely between the home collected and endoscopy collected samples. Additionally, as the VOC extraction profile is hyperbolic, with short extraction durations more vulnerable to variation than extractions continued to equilibrium, a second goal of our investigation was to ascertain if hSPME-based fecal metabolomics studies might be biased by the extraction duration employed. As anticipated, prolonged extraction (18 hours) results in the identification of considerably more metabolites than short (20 minute) extractions. A comparison of the metabolomes reveals several analytes deemed unique to a cohort with the 20 minute extraction, but found common to both cohorts when the VOC extraction was performed for 18 hours. Moreover, numerous analytes perceived to have significant fold change with a 20 minute extraction were found insignificant in fold change with the prolonged extraction, underscoring the potential for bias associated with a 20 minute hSPME.</p> </div

Fold change analysis of the metabolite abundance between the healthy and alcoholic fecal samples.

<p>The fold change (FC) is calculated as the log transformation of the ratio between the mean metabolite abundance in the alcoholic cohort relative to the healthy cohort. The analysis was performed with both the endoscopy (A) and home passage collected (B) metabolomes. A log₂(FC) greater than 1.5 is deemed significant (equivalent to a threefold or greater change in metabolite abundance). A fold change analysis comparing median analyte values produces similar results (not shown).</p

Comparison of SCFA abundance among the cohorts.

<p>Box plots are presented, depicted as described in Fig.8. A) Among the endoscopy collected samples, while most of the SCFAs are comparable in abundance within the healthy and alcoholic cohorts, propanoic acid demonstrates a statistically significant reduction in median abundance in the alcoholic cohort relative to the healthy cohort (<i>p</i> = 0.03, fold change = 2.32). B) In the home collected samples, butyrate has a 1.6 fold reduction in median abundance, while the remaining SCFAs are very similar between the healthy and alcoholic fecal samples. See text for further discussion.</p

Heat map showing the unsupervised hierarchical clustering of the fecal samples according to the similarity of metabolome composition.

<p>The endoscopy collected fecal metabolomes are compared in (A) while the home collected fecal metabolomes are compared in (B). The samples are arranged in rows, the metabolites in columns, and shades of red represent elevation of a metabolite while shades of green represent decrease of a metabolite, relative to the median metabolite levels (see color scale). In the dendrograms, the clustering clearly differentiates the alcoholic and healthy fecal samples.</p

Principle component analysis of the VOC metabolomes identified in the passage and endoscopy collected human fecal samples.

<p>PCA plots derived from the identified metabolites and their abundance are presented. The first (PC1) and second (PC2) principle components are shown. In contrast to the microbiome (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081163#pone-0081163-g001" target="_blank">Figure 1</a>), the PCA of the VOC metabolomes indicates significant differences among the home passage and endoscopy collected samples, as the samples clearly segregate according to collection technique. Analyzed were the VOC metabolomes obtained with either a 20 minute (A) or 18 hour (B) hSPME extraction. The infrequent metabolites were disregarded by restricting the analysis to analytes that appeared in a minimum of 20% of all samples in each cohort. Home collected samples are indicated as red diamonds, while endoscopy collected samples are denoted as blue circles. The naming and numbering convention of the samples is described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081163#pone-0081163-g001" target="_blank">Figure 1</a>. See text for further discussion.</p

Fold change analysis of the metabolite abundance between the endoscopy and home passage collected samples.

<p>The fold change (FC) is calculated as the log transformation of the ratio between the mean metabolite abundance in the endoscopy cohort relative to the home passage collected cohort. The analysis was performed with both the 20 minute (A) and 18 hour (B) metabolomes. </p

Principle component analysis of the microbiomes identified in the home passage and endoscopy collected human fecal samples.

<p>A) PCA plot derived from the identified taxa and their abundance. The first (PC1) and second (PC2) principle components are shown, which represent the two largest contributions to variation among the samples. B) Biplot containing a magnified view of the clustered region seen in A). The taxa that impart the greatest contribution towards the two principle components are indicated, with vectors indicating the magnitude and direction of the factor loadings. While the two cohorts generally appear clustered in A), a pairwise comparison of matched home passage and endoscopy collected samples in B) reveals some variation in the derived microbiomes. Home collected samples (red diamonds) have a name designation containing the letter B. Endoscopy collected samples (blue circles) have a name designation containing the letter A. Matched samples have the same number designation. See text for further discussion.</p

ROC curve of dimethyl disulfide and dimethyl trisulfide.

<p>The area under the curve is 0.80 and 0.77, respectively, which are indicative of a fairly good diagnostic test (albeit not excellent).</p

Metabolites with a statistically significant difference in abundance between the healthy and alcoholic cohorts (<i>p</i><0.05; <i>p</i>

<p>Metabolites with a statistically significant difference in abundance between the healthy and alcoholic cohorts (<i>p</i><0.05; <i>p</i></p