Orthogonal Comparison of GC-MS and 1H NMR Spectroscopy for Short Chain Fatty Acid Quantitation

Jingwei Cai, Jingtao Zhang, Yuan Tian, Limin Zhang, Emmanuel Hatzakis, Kristopher W. Krausz, Philip B. Smith, Frank J. Gonzalez, Andrew D. Patterson

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


Short chain fatty acids (SCFAs) are important regulators of host physiology and metabolism and may contribute to obesity and associated metabolic diseases. Interest in SCFAs has increased in part due to the recognized importance of how production of SCFAs by the microbiota may signal to the host. Therefore, reliable, reproducible, and affordable methods for SCFA profiling are required for accurate identification and quantitation. In the current study, four different methods for SCFA (acetic acid, propionic acid, and butyric acid) extraction and quantitation were compared using two independent platforms including gas chromatography coupled with mass spectrometry (GC-MS) and 1H nuclear magnetic resonance (NMR) spectroscopy. Sensitivity, recovery, repeatability, matrix effect, and validation using mouse fecal samples were determined across all methods. The GC-MS propyl esterification method exhibited superior sensitivity for acetic acid and butyric acid measurement (LOD < 0.01 μg mL-1, LOQ < 0.1 μg mL-1) and recovery accuracy (99.4%-108.3% recovery rate for 100 μg mL-1 SCFA mixed standard spike in and 97.8%-101.8% recovery rate for 250 μg mL-1 SCFAs mixed standard spike in). NMR methods by either quantitation relative to an internal standard or quantitation using a calibration curve yielded better repeatability and minimal matrix effects compared to GC-MS methods. All methods generated good calibration curve linearity (R2 > 0.99) and comparable measurement of fecal SCFA concentration. Lastly, these methods were used to quantitate fecal SCFAs obtained from conventionally raised (CONV-R) and germ free (GF) mice. Results from global metabolomic analysis of feces generated by 1H NMR and bomb calorimetry were used to further validate these approaches.

Original languageEnglish (US)
Pages (from-to)7900-7906
Number of pages7
JournalAnalytical Chemistry
Issue number15
StatePublished - Aug 1 2017

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry


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