Screening of organic acids for nutritional and metabolic profiling from dried urine spots using Gas Chromatograph Mass Spectrometer

Significance of the topic

Rapid and reliable profiling of microbial-derived organic acids in urine is critical for understanding metabolic status, nutritional deficiencies, and gut microbiome imbalances.

Objectives and overview

This study demonstrates a proof-of-concept method for rapid screening of 65 organic acids from dried urine spots using the Shimadzu GCMS-QP2020 NX platform coupled with the Smart Metabolites Database Ver.2 and the Automatic Adjustment of Retention Time function.

Methodology

Sample preparation involves:

• Aliquoting dried urine spots based on creatinine content and adding tridecanoic acid and margaric acid as internal standards
• Urea decomposition with urease at 37 °C for 30 min
• Protein precipitation with ethanol, centrifugation, and nitrogen evaporation
• Derivatization with BSTFA containing 1% TMCS at 80 °C for 30 min
• Injection of 1 µL of the derivatized sample into the GC-MS

Used Instrumentation

• Gas Chromatograph Mass Spectrometer Shimadzu GCMS-QP2020 NX
• Auto-injector AOC-20i+s
• Capillary column SH-Rxi-5Sil MS (30 m × 0.25 mm, 0.25 µm film)
• Electron ionization at 200 °C source; scan rate 20000 u/sec
• Oven program: 60 °C (2 min), ramp 15 °C/min to 310 °C (5 min); injector 250 °C; interface 280 °C

Results and discussion

The method enabled identification and screening of 65 organic acids, including lactic, citric, succinic, hippuric, phosphoric, and glutaric acids. The AART function, combined with linear retention indices, improved retention time prediction and identification reliability compared to conventional library searches. Representative total ion chromatograms and spectral match results confirmed accurate detection. Calibration of glutaric acid demonstrated linearity suitable for quantitative analysis. Elevated organic acid profiles were linked to conditions such as systemic lupus erythematosus, gut dysbiosis, and metabolic disorders.

Benefits and practical applications

• Rapid qualitative screening and quantitative assessment of multiple organic acids
• Minimal sample volume and simplified preparation from dried urine spots
• Enhanced identification confidence through a dedicated metabolite database and retention index adjustment
• Applications in nutritional profiling, metabolic disorder diagnostics, and microbiome research

Future trends and opportunities

Anticipated developments include expansion of metabolite libraries, integration with high-throughput automation, coupling with other omics platforms, and application of artificial intelligence for advanced data analysis and point-of-care metabolic screening.

Conclusion

The combination of the Shimadzu GCMS-QP2020 NX system with the Smart Metabolites Database and AART functionality provides a fast, reliable workflow for comprehensive organic acid profiling from dried urine spots, supporting both research and clinical diagnostics.

References

1. Naraian R, Kumari S. Microbial production of organic acids. In: Microbial Functional Foods and Nutraceuticals. 2017.
2. Suiryanrayna MV, Ramana JV. A review of the effects of dietary organic acids fed to swine. Journal of Animal Science and Biotechnology. 2015;6(1):11.
3. Yan R, Jiang H, Gu S, et al. Fecal metabolites were altered, identified as biomarkers and correlated with disease activity in patients with systemic lupus erythematosus in a GC-MS-based metabolomics study. Frontiers in Immunology. 2020;11:2138.