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The application of metabolomics in translational research suffers from several technological bottlenecks, such as data reproducibility issues and the lack of standardization of sample profiling procedures. Here, we report an automated high-throughput metabolite array technology that can rapidly and quantitatively determine 324 metabolites including fatty acids, amino acids, organic acids, carbohydrates, and bile acids. Metabolite identification and quantification is achieved using the Targeted Metabolome Batch Quantification (TMBQ) software, the first cross-vendor data processing pipeline. A test of this metabolite array was performed by analyzing serum samples from patients with chronic liver disease (N = 1234). With high detection efficiency and sensitivity in serum, urine, feces, cell lysates, and liver tissue samples and suitable for different mass spectrometry systems, this metabolite array technology holds great potential for biomarker discovery and high throughput clinical testing. Additionally, data generated from such standardized procedures can be used to generate a clinical metabolomics database suitable for precision medicine in next-generation healthcare.
Xie et al. (Fri,) studied this question.