Short-chain fatty acids (SCFAs) and the tricarboxylic acid (TCA) cycle metabolites aresmall hydrophilic compounds that play crucial roles in biological species ranging fromenergy metabolism, immune homeostasis to cellular signalling. There is a need for reliableand precise quantification of these metabolites in biological matrices as they can providecrucial information of metabolic status and potentially be used as diagnostic biomarkersfor different pathological and physiological conditions. However, their retention andseparation in traditional reversed-phase system, without chemical derivatization, is oftenproblematic due to their volatile and hydrophilic characteristics. The aim of this studywas to implement a facile and effective derivatization method for the simultaneousquantitation of SCFAs and TCA cycle metabolites by LC-qToF-MS in negative ion mode. Inthis work, 3-nitrophenylhydrazine (3-NPH) was employed for preanalyticalderivatization to convert the compounds to their respective 3-nitrophenylhydrazones.Analytical standards and faecal samples were used to assess the linearity, matrix effect,accuracy, extraction efficiency, precision, retention-time shift and short-term stability.The compounds were successfully separated within 6 minutes on a reverse-phase C18column. All the compounds showed good linearity (R2≥ 0.97) in both solvent-only andfaecal samples. The matrix effect was minimal and did not affect the compoundsquantitation. The extraction efficiency ranged from 80% to 110% (CV≤9.7%, n = 6). Theaccuracy of quantitation was determined to be between 82.8% to 113.8% (CV≤9.0%, n =6). The intra-day (CV%) demonstrated good precision for all analytes, the inter-day (%)were more variable due to the derivatives’ chemical instability. However, most of thederivatives were chemical stable up to 5 days in the autosampler (10°C). The method wasalso applied to explore the levels of these metabolites in human faecal samples and mousebrain samples.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:oru-93417 |
Date | January 2021 |
Creators | Levisson, Renée |
Publisher | Örebro universitet, Institutionen för naturvetenskap och teknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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