Optimized Urinary Organic Acids Analysis

The extraction and derivatization protocol for urinary organic acids was optimized based on a previously reported method (17 (link)). Derivatized extracts (e.g., organic acids) were injected by an Agilent 7683 Series autosampler (Agilent Technologies, Palo Alto, CA, USA) followed by the analysis employing Agilent 6890N GC system coupled with electron impact (EI) ionization mode 5973N mass selective detector (Agilent Technologies, Palo Alto, CA, USA). Raw GC-MS data (“.D” file format) were first transformed into CDF format by the ChemStation Data Analysis software (Agilent Technologies, Palo Alto, CA, USA) prior to data pretreatment. Identification and quantification of metabolites was firstly processed and analyzed automatically by a web-based software called GC-AutoFit (http://gcms.wishartlab.com/) and results were further confirmed manually following the method as previously described (18 (link)). Further details on the organic acid extraction, derivatization, separation, and GC-MS data processing of urine samples were elaborated previously (19 (link)).

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Zhang G., Mandal R., Wishart D.S, & Ametaj B.N. (2021). A Multi-Platform Metabolomics Approach Identifies Urinary Metabolite Signatures That Differentiate Ketotic From Healthy Dairy Cows. Frontiers in Veterinary Science, 8, 595983.

Publication 2021

Agilent 7683 Series autosampler Agilent 6890N GC system ChemStation Data Analysis software

Acid Electron Gc ms Urine

Corresponding Organization :

Other organizations : University of Alberta

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Variable analysis

independent variables

None explicitly mentioned

dependent variables

Extraction and derivatization of urinary organic acids
Identification and quantification of metabolites

control variables

None explicitly mentioned

controls

Previously reported method (17) was used as a reference for optimizing the extraction and derivatization protocol
Results from the automated GC-AutoFit software were further confirmed manually following the method as previously described (18)

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