| Literature DB >> 31404873 |
Julia M Gauglitz1, Christine M Aceves2, Alexander A Aksenov3, Gajender Aleti4, Jehad Almaliti5, Amina Bouslimani3, Elizabeth A Brown2, Anaamika Campeau6, Andrés Mauricio Caraballo-Rodríguez3, Rama Chaar7, Ricardo R da Silva3, Alyssa M Demko8, Francesca Di Ottavio9, Emmanuel Elijah3, Madeleine Ernst3, L Paige Ferguson7, Xavier Holmes3, Alan K Jarmusch3, Lingjing Jiang10, Kyo Bin Kang3, Irina Koester8, Brian Kwan10, Jie Li8, Yueying Li8, Alexey V Melnik11, Carlos Molina-Santiago12, Bohan Ni8, Aaron L Oom13, Morgan W Panitchpakdi3, Daniel Petras14, Robert Quinn3, Nicole Sikora7, Katharina Spengler2, Bahar Teke8, Anupriya Tripathi3, Sabah Ul-Hasan15, Justin J J van der Hooft16, Fernando Vargas17, Alison Vrbanac18, Anthony Q Vu18, Steven C Wang19, Kelly Weldon11, Kayla Wilson8, Jacob M Wozniak6, Michael Yoon7, Nuno Bandeira20, Pieter C Dorrestein21.
Abstract
In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.Keywords: Fermentation; Food; LC-MS/MS; Metabolomics; Molecular networking; Tea; Untargeted mass spectrometry; Yogurt
Mesh:
Year: 2019 PMID: 31404873 DOI: 10.1016/j.foodchem.2019.125290
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514