Separation and Analysis of Low Molecular Weight Organic Acid Metabolites by Mixed-Mode Chromatography Coupled to Mass Spectrometry

Importance of the Topic

The tricarboxylic acid (TCA) cycle comprises small, highly polar organic acids that play central roles in cellular metabolism. Reliable separation and quantification of these metabolites are critical for studies in biochemistry, clinical diagnostics, and metabolic profiling. Traditional reversed-phase methods often fail to retain or resolve key TCA components, such as the isobaric pair citric acid/isocitric acid, limiting accurate measurement in complex biological samples.

Objectives and Study Overview

This study aimed to develop and validate a mixed-mode chromatographic method coupled with mass spectrometry for direct analysis of underivatized low molecular weight organic acids in human urine. The method was applied to compare metabolic profiles of breast cancer positive and non-disease female urine samples, enabling discovery of potential biomarkers without ion-pairing reagents or derivatization.

Methodology

Sample Preparation:

• Ten-fold dilution of urine with ultrapure water.
• Centrifugation at 4 °C, 21130 rcf for 10 min.
• Transfer of supernatant to silanized vials for injection.

Chromatographic Conditions:

• Column: ACQUITY UPLC CSH Phenyl-Hexyl, 2.1×100 mm, 1.7 µm.
• Mobile phases: 0.1% formic acid in water (A) and acetonitrile (B).
• Gradient: 0–25% B over 4 min; flow rate 0.4 mL/min; column temperature 60 °C.

Data Acquisition and Processing:

• Xevo G2-XS QTof MS in negative ionization, MSe mode.
• Data processing with MassLynx 4.1, Progenesis QI, and EZinfo.

Used Instrumentation

• ACQUITY I-Class UPLC system.
• ACQUITY UPLC CSH Phenyl-Hexyl column (2.1×100 mm, 1.7 µm).
• Xevo G2-XS QTof mass spectrometer.
• MassLynx 4.1, Progenesis QI 3.0.3, EZinfo software.

Main Results and Discussion

The method achieved sufficient retention and chromatographic resolution of key TCA metabolites, including lactate, malate, succinate, citrate/isocitrate, fumarate, and α-ketoglutarate. PCA and OPLS-DA models clearly distinguished breast cancer positive from non-disease urine samples. Several features showed high statistical significance and were tentatively identified via library searches (HMDB, KEGG, METLIN) as xanthosine monophosphate and an aspartate‐tyrosine dipeptide. Extracted ion chromatograms confirmed differential abundance patterns across sample groups.

Benefits and Practical Applications

This mixed-mode UPLC-MS approach offers:

• Direct analysis of underivatized organic acids, reducing sample preparation time.
• Improved selectivity and resolution for isobaric and polar metabolites.
• High throughput suited for clinical and metabolic phenotyping studies.

Future Trends and Applications

Advancements may include integration with high-resolution MS/MS for definitive structural elucidation, expansion to other biofluids, and incorporation into routine clinical workflows. Machine learning-driven data interpretation could further enhance biomarker discovery and metabolic pathway analysis.

Conclusion

The presented mixed-mode chromatography coupled to QTof MS enables robust separation and detection of TCA cycle metabolites in urine without derivatization. Statistical analysis identified candidate biomarkers differentiating breast cancer positive and non-disease samples. The methodology holds promise for broad applications in metabolomics and clinical diagnostics.