Document Type

Oral Presentation

Location

Oxford Conference Center

Event Website

https://oxfordicsb.org/

Start Date

23-4-2026 10:50 AM

End Date

23-4-2026 11:10 AM

Description

Ashwagandha (Withania somnifera) is a widely consumed botanical supplement recognized for its anti-inflammatory, antioxidant, and anti-aging properties. Despite its extensive use, limited information exists on how its complex chemical composition changes during gastrointestinal digestion. An untargeted UPLC-MS/MS-based metabolomics approach enables analysis of discrete changes in complex mixtures. Previous in vitro studies of W. somnifera relied on simulated gastric and intestinal models composed primarily of buffers and digestive enzymes. This study advances those methods by incorporating bile salts and phospholipids under fasted and fed conditions to better simulate physiological digestion of aqueous and ethanolic extracts of W. somnifera root and leaf. Further, passive permeability after digestion was evaluated using PAMPA and subsequent LCMS analysis. Feature-based molecular networking facilitated comparison of features before and after digestion, identifying relationships between parent compounds and transformation products. Compound class annotation was supported by SIRIUS analysis of MS/MS fragmentation data. Results indicate that fed conditions limit metabolite transformations by digestion relative to the fasted condition.  The scalability of this method coupled with detailed feature annotation will yield important targets for downstream confirmatory investigations with in vivo studies and applicability to other complex botanical metabolite mixtures.

Comments

Ms. Barr is currently a Ph.D. candidate in Pharmaceutical Chemistry at the University of North Carolina Wilmington (UNCW), where she conducts research in the Drug Discovery Laboratory under the mentorship of Dr. Wendy Strangman. Her academic journey began with a Bachelor of Science in Aerospace Engineering from the University of Michigan. After graduation, she spent over a decade in the aerospace industry, contributing to a range of commercial aircraft and spacecraft projects. Her work in this sector emphasized systems integration, risk management, and performance optimization – skills that have seamlessly translated into her current focus on complex biological systems and analytical method development. Sarah is supported by an RO3 award from NIH’s NCCIH and ODS as part of the CARBON Centers in collaboration with BENFRA Center (Botanicals Enhancing Neurological and Functional Resilience in Aging). Her doctoral work centers on analysis of medicinal plant extracts and their chemical transformations during gastrointestinal processing with in vitro digestion models coupled with analytical techniques such as liquid chromatography – mass spectrometry (LC-MS/MS) and molecular networking, using Withania somnifera (Ashwagandha) as a model system. Looking ahead, Ms. Barr aims to apply her degree and analytical skills in the pharmaceutical or dietary supplement industry, where she hopes to contribute to the development of evidence-based therapeutics.

Publication Date

April 2026

Accessibility Status

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Apr 23rd, 10:50 AM Apr 23rd, 11:10 AM

Evaluation of Fasted and Fed Gastrointestinal Transformation of Withania somnifera Plant Extracts and Bioactive Compounds via UPLC-MS/MS and Untargeted Metabolomics

Oxford Conference Center

Ashwagandha (Withania somnifera) is a widely consumed botanical supplement recognized for its anti-inflammatory, antioxidant, and anti-aging properties. Despite its extensive use, limited information exists on how its complex chemical composition changes during gastrointestinal digestion. An untargeted UPLC-MS/MS-based metabolomics approach enables analysis of discrete changes in complex mixtures. Previous in vitro studies of W. somnifera relied on simulated gastric and intestinal models composed primarily of buffers and digestive enzymes. This study advances those methods by incorporating bile salts and phospholipids under fasted and fed conditions to better simulate physiological digestion of aqueous and ethanolic extracts of W. somnifera root and leaf. Further, passive permeability after digestion was evaluated using PAMPA and subsequent LCMS analysis. Feature-based molecular networking facilitated comparison of features before and after digestion, identifying relationships between parent compounds and transformation products. Compound class annotation was supported by SIRIUS analysis of MS/MS fragmentation data. Results indicate that fed conditions limit metabolite transformations by digestion relative to the fasted condition.  The scalability of this method coupled with detailed feature annotation will yield important targets for downstream confirmatory investigations with in vivo studies and applicability to other complex botanical metabolite mixtures.

https://egrove.olemiss.edu/icsb/2026_ICSB/Schedule/34