PROJECT SUMMARY Metabolomics offers a comprehensive analysis of thousands of small molecules in biological samples. It plays an indispensable role in the growing systems biology approaches to unravel the relationships between metabolites and diseases. Liquid chromatography coupled to mass spectrometry (LC-MS) and gas chromatography coupled to mass spectrometry (GC-MS) have been used for high-throughput analysis of thousands of metabolites. However, the potential values of many disease-associated metabolites discovered by using these platforms have been inadequately explored in systems biology approaches for biomarker discovery due to lack of computational tools and resources to: (1) accurately determine the identity of most of the analytes; (2) investigate the rewiring interactions among the metabolites due to diseases; and (3) integrate metabolite profiles with other omics studies to evaluate the relationships between the metabolites and the diseases at the systems level. Partly due to these limitations, poor generalizability of previously identified metabolite biomarker candidates has been observed, especially when they are evaluated through independent platforms and validation sets. The parent award aims to fill the gaps in metabolite identification and multi-omics integration by using systems metabolomics approaches that enhance the role of metabolomics in systems biology approaches for biomarker discovery. Specifically, it utilizes multiple resources (biological databases, mass spectral libraries, etc.) and innovative statistical, deep learning, and network-based methods for: (1) developing a comprehensive workflow for ranking putative metabolite IDs; (2) differential analysis of metabolite profiles and integration of metabolomics data with proteomics, glycomics, glycoproteomics. and phosphoproteomics data to identify highly promising metabolite biomarker candidates. The selected candidates are evaluated by targeted quantitation using independent samples and platforms compared to those used for discovery. However, the successful implementation of one of the critical tasks proposed in the parent award relies heavily on analytical platforms that have high resolution, mass accuracy, and sensitivity for identification and quantitation of various analytes. To this end, in this administrative supplement application, we request support to purchase the Thermo Scientific Orbitrap Exploris Mass Spectrometer that offers the resolution, accuracy, sensitivity, and throughput needed by our multi-omics approach for biomarker discovery. Availability of this instrument will not only provide the much needed sensitive, robust, and reliable platform but also address unforeseen circumstances that occurred due to the significant amount of machine time required to develop instrument methods for the identification and quantitation of biomarker candidates relevant to the parent award.