= Emerging. More than 5 years before clinical availability. (24.37%, 2023)
= Expected to be clinically available in 1 to 4 years. (39.50%, 2023)
= Clinically available now. (36.13%, 2023)
MSACL 2023 : Guiberson

MSACL 2023 Abstract

Self-Classified Topic Area(s): Microbiology > Metabolomics

Podium Presentation in Colton on Thursday at 16:50 (Chair: Liam Heaney / Iulia Macavei)

Microbiota-Dependent Metabolomic Changes After Nutritional Intervention During Pregnancy

Emma R Guiberson (1), Matthew Olm (1), Brian DeFelice (2), Josh Elias (2), Justin Sonnenburg (1,2,3)
(1) Department of Microbiology and Immunology, Stanford University, Palo Alto, CA (2) Chan-Zuckerburg Biohub, San Francisco, CA (3) Center for Human Microbiome Studies, Stanford University, Palo Alto, CA

Emma Guiberson, PhD (Presenter)
Stanford University

Presenter Bio: Emma completed her B.S. in Chemistry and Philosophy at the University of Notre Dame, conducting research in organic chemistry and chemistry education research, before pursuing a PhD in Chemistry at Vanderbilt University. As a graduate student in the labs of Dr. Richard Caprioli and Dr. Jeff Spraggins, her research focused primarily on the application of imaging mass spectrometry to the gastrointestinal tract (Guiberson, et. al. JASMS 2022) and utilizing targeted small molecule analysis to better study bile acids in the gastrointestinal tract during Clostridioides difficile infection (Wexler and Guiberson, et. al. Cell Reports 2021). Additionally, she worked on utilizing spatial proteomics to understand abscess formation during Staphylococcus aureus infections (Guiberson and Weiss, et. al. ACS Infectious Diseases 2020). This work led to an interest in the gut microbiome and the metabolites produced by microbes in the gastrointestinal tract. After defending her PhD in August of 2022, Emma then joined the lab of Dr. Justin Sonnenburg at Stanford University to study microbial-derived metabolites. Her current work in the Sonnenburg lab focuses on both untargeted metabolomics using a library of microbiome-derived metabolites (Han, Guiberson, Sonnenburg, Protocol Exchange, 2022), as well as necessary targeted methods for quantitative analyses of metabolites of interest that accumulate as uremic toxins during kidney disease. Emma plans to combine these training experiences one day in her own independent research group studying host-pathogen-microbiome interactions in the human gut.


The human gut microbiome consists of hundreds of bacterial species that interface with the host and environment, including through the production of microbiota-dependent metabolites (MDMs). These metabolites can be absorbed into host tissue, alter host physiology, and travel throughout the body via biofluids. Many of these MDMs are associated with inflammation either as inflammatory or anti-inflammatory metabolites, which can impact the immune status of both the mother and infant. While the microbiota is unique to individuals and communities, they can be modulated by a variety of factors including diet, which plays a major role. Many studies in the lab have seen wide-scale changes in microbial communities and resulting metabolites as a result of dietary interventions. As a portion of the infant microbiome is acquired from the mother, and this first microbiome plays a crucial role in many health conditions, understanding changes to the microbiome and MDMs of pregnant mothers is a rich area to study. Studies in this are have shown that maternal metabolites, and resulting inflammatory status of the mother, can impact the fetus as well, making the microbiome of pregnant mothers a highly impactful niche. In this study, we investigated longitudinal changes in metabolites produced by the microbiome in pregnant women as a result of nutritional interventions during pregnancy, to further elucidate the impact of diet on the microbiome.

Previously the lab has developed an MDM-focused library for analysis of untargeted metabolomics data from biological samples (Han and Van Treuren, et. al. Nature (2021)). Study participants either received a nutritional intervention (a fortified balanced energy-protein supplement) during their pregnancy, or continued on an existing dietary program. Fecal samples were collected prior to the interventions and periodically throughout the pregnancy. Samples were analyzed using metagenomics for strain identification and using LC-MS for untargeted metabolomics analysis. For metabolomics, fecal samples were homogenized using a bead beater and glass beads in a protein extraction buffer to precipitate proteins, then supernatants were dried down under air. Samples were then resuspended in a buffer containing select internal standards and filtered via centrifugation and a 0.22 μm filter plate. Extracted metabolites were then analyzed via liquid chromatography mass spectrometry using a UPLC (Agilent 1290 Infinity II UHPLC) coupled to a QTOF instrument (Agilent QTOF 6545) in reverse phase and HILIC phase in both positive and negative mode. Data were then converted to a vender-neutral format using MS-Dial and compared against previously-collected library spectra for identification using exact mass and retention time. Metabolites of interest were then compared against standards and analyzed using a triple quadrupole MS (Agilent 6470 QQQ) for quantitative analysis.

Results and Discussion:
This semi-targeted metabolomics pipeline method has routinely enabled the detection of many microbial dependent metabolites from biological samples, many of which change as a result of dietary interventions. In this pilot study cohort, we were able to detect dozens of MDMs from our library within fecal samples from pregnant subjects. While there was interpersonal variation in a large proportion of metabolites between study participants, there was also a group of metabolites conserved across samples. Additionally, we detected some metabolites that changed in abundance over 2-fold after dietary intervention, either increasing or decreasing in abundance. These metabolomic changes are consistent with changes in the microbial communities present in study subjects resulting from dietary intervention. Overall, these data suggest that a dietary intervention during pregnancy can impact gut microbiome diversity, resulting in changes to the metabolites present during and after pregnancy. These changes can potentially be passed onto infants during birth, leading to lifelong microbial implications. An important next step of this work is to determine how such diet-induced microbiome modification during pregnancy impacts infant microbiome, metabolome, and overall health.

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