ArticleFrontiers in bioengineering and biotechnology2021
A LCMS Metabolomic Workflow to Investigate Metabolic Patterns in Human Intestinal Cells Exposed to Hydrolyzed Crab Waste Materials.
Article in Frontiers in bioengineering and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research.ACS measurement science au · 2024Review
- Microbiota independent effects of oligosaccharides on Caco-2 cells -A semi-targeted metabolomics approach using DI-FT-ICR-MS coupled with pathway enrichment analysis.Frontiers in molecular biosciences · 2022Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a LCMS metabolomic workflow to investigate metabolic patterns from human intestinal cells treated with simulated gastrointestinal-digested hydrolyzed crab waste materials. This workflow facilitates smart and reproducible comparisons of cell cultures exposed to different treatments. In this case the variable was the hydrolysis methods, also accounting for the GI digestion giving an output of direct correlation between cellular metabolic patterns caused by the treatments. In addition, we used the output from this workflow to select treatments for further evaluation of the Caco-2 cell response in terms of tentative anti-inflammatory activity in the hopes to find value in the crab waste materials to be used for food products. As hypothesized, the treatment identified to change the cellular metabolomic pattern most readily, was also found to cause the greatest effect in the cells, although the response was pro-inflammatory rather than anti-inflammatory, it proves that changes in cellular metabolic patterns are useful predictors of bioactivity. We conclude that the developed workflow allows for cost effective, rapid sample preparation as well as accurate and repeatable LCMS analysis and introduces a data pipeline specifically for probe the novel metabolite patterns created as a means to assess the performing treatments.
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