MSACL 2018 US Abstract

Topic: Metabolomics

Untargeted Metabolomics of 2400 Fecal Samples from American Gut Participants and ICU Subjects Reveals Information about Our Health, Behavior, and Microbiota

Alan Jarmusch (Presenter)
University of California, San Diego

Bio: Alan K. Jarmusch is a postdoctoral scholar at the University of California, San Diego and is mentored by Pieter C. Dorrestein. He obtained his PhD in chemistry from Purdue University in 2016 in the laboratory of R. Graham Cooks. He received his B.S. in Biochemistry, advised by Nadja B. Cech, at the University of North Carolina at Greensboro in 2011. His current research interests include metabolomics particularly the study of chronic non-transmissible disease and the implementation of ambient ionization technology for high throughput screening.

Authorship: Alan K. Jarmusch,(1) Embriette R. Hyde,(2) Alexey V. Melnik,(1) Alexander Aksenov,(1) Daniel McDonald,(2), Ricardo Da Silva,(1), Paul Wischmeyer,(3) Rob Knight,(2) and Pieter C. Dorrestein(1)
(1) Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California – San Diego, La Jolla, CA 92093 (2) Department of Pediatrics, University of California - San Diego, La Jolla, CA 92093 (3) Duke University School of Medicine, Durham, NC 27710

Short Abstract

The metabolome of our gut is complex and understudied. The American Gut, a crowd-sourced citizen scientist project, aims to explore how our health, behaviors, and environment influence our gut microbiota. Untargeted metabolomic analysis of fecal samples from >2400 subjects in the American Gut and ICU Microbiome Project revealed compounds related to health, behavior, and those created by or modified by gut microbes. Fecal samples from the United States, United Kingdom, and Australia were compared, as well as subjects with various diagnosed diseases. Molecular networking and automatic annotation of MS/MS spectra using GNPS allowed for in depth exploration of the data as well as providing the frequency of compounds detected in the cohort.

Long Abstract

Introduction

The metabolome of our gut is complex and understudied. The American Gut, a crowd-sourced citizen scientist project, aims to explore how our health, behaviors, and environment influence our gut microbiota. Untargeted metabolomic analysis of fecal samples from >2400 subjects in the American Gut and ICU Microbiome Project revealed compounds related to health, behavior, and those created by or modified by gut microbes. Fecal samples from the United States, United Kingdom, and Australia were compared, as well as subjects with various diagnosed diseases. Molecular networking and automatic annotation of MS/MS spectra using GNPS allowed for in depth exploration of the data as well as providing the frequency of compounds detected in the cohort.

Methods

American Gut fecal samples, n=2434, were provided in collection tubes with barcode that corresponded to metadata – one swab was used for 16S rRNA sequencing and the other swab was used for metabolomic analysis. Extraction for metabolomics was performed using HPLC grade ethanol-water (90%:10%), incubated overnight at 4 °C. Extracts were subsequently dried via centrifugal evaporation, and resuspended and diluted 2-fold prior to LC-MS analysis. Reverse-phase ultra high performance liquid chromatography – mass spectrometry (UHPLC-MS) was performed using a Thermo Dionex UHPLC system coupled to a Bruker Maxis Impact HD mass spectrometer. Data were acquired using data dependent acquisition at 3 Hz (m/z 80-1200) and subsequently fragmenting the five most abundant precursor ions. Feature finding was performed using mzMine2 and subsequently analyzed in R. The Global Natural Products Molecular Networking (GNPS) tool (http://gnps.ucsd.edu) was used to annotate and further analyze MS/MS data. 16S sequencing was conducted for all of the samples as a part of primary American Gut project objective and these data can be correlated with metabolomics results.

Results

The inventory of annotated compounds was developed in order to better characterize fecal constituents, exogenous and endogenous. Molecules from the following major classes of compounds were detected: lipids, small peptides, mono- and disaccharides, phytochemicals, vitamins, steroids, and others. By using the self reported data from the American Gut, including a validated food frequency questionnaire, we were able to determine that the source of these metabolites are numerous including but not limited to diet, exposure, behaviors, human-derived sources, and the gut microbiome (e.g. stercobilinogen, a catabolite of hemoglobin generated in part by gut bacteria). Molecules associated with behaviors were detected, viz. caffeine and the implied consumption of caffeinated beverages such as coffee. A broad range of prescription drugs were detected including antihypertensives, antidepressants, muscle relaxants, antibiotics, and others. Over-the-counter drugs were also frequently detected, for example fexofenadine or loratadine which were detected in ~3.5% of all samples. The metadata collected with the American Gut samples provide the ability to determine the distribution of pharmaceutical (and illicit) drug use by country - 53.4% of samples had at least 1 drug (many having more than 1). The number of drugs detected in fecal samples from subjects in the United States of America (1.7 drugs/subject) compared to the United Kingdom (1.4 drugs/subject) and Australia (1.4 drugs/subject) was statistically significant (e.g. p-value of USA to UK is p = 1.98e-6). Also, particular medications differ among countries, for example, N-butyl-scopolamine was only detected in samples from the UK which might reflect the availability of this drug as it is available over-the-counter in the UK, by prescription only in Australia, and is not available in the USA. Multivariate statistics, such as principal coordinates analysis (PCoA), revealed minor differences amongst persons from the United States (n=1425), United Kingdom (n=554), and Australia (n=134). The differences include both endogenous and exogenous metabolites, such as pharmaceutical drugs. The microbiome differences between these populations also suggests differences which could result from diet, environment, and other factors. Age was found to have a strong effect on the microbial composition of samples - the associated metabolome is ongoing. Further analysis of each population independently, with the United States being the largest cohort, reveals differences between persons diagnosed with a disease – an extreme example are patients admitted to the Intensive Care Unit versus healthy individuals.

Conclusions & Discussion

The work to be presented is the largest fecal metabolomics study that we are aware of currently, and serves to expand knowledge on the molecular composition of feces. The extensive metadata associated with the samples allowed for correlation with diet, behaviors, and health. The presence of drugs in the samples represent an object means by which to qualitatively, but objectively, assess consumption trends. We are currently exploring the connections between the microbiota and metabolome in healthy individuals and those afflicted with disease.


References & Acknowledgements:


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