Simultaneous Multi-Omics Analysis by Direct Infusion Mass Spectrometry (SMAD-MS).

Combined multi-omics analysis of proteomics, polar metabolomics, and lipidomics requires separate liquid chromatography-mass spectrometry (LC-MS) platforms for each omics layer. This requirement for different platforms limits throughput and increases costs, preventing the application of mass spectrometry-based multi-omics to large scale drug discovery or clinical cohorts. Here, we present an innovative strategy for simultaneous multi-omics analysis by direct infusion (SMAD) using one single injection without liquid chromatography. SMAD allows quantification of over 9,000 metabolite m/z features and over 1,300 proteins from the same sample in less than five minutes. We validated the efficiency and reliability of this method and then present two practical applications: mouse macrophage M1/M2 polarization and high throughput drug screening in human 293T cells. Finally, we demonstrate relationships between proteomic and metabolomic data are discovered by machine learning.

Lung Adenocarcinoma Transcriptomic Analysis Predicts Adenylate Kinase Signatures Contributing to Tumor Progression and Negative Patient Prognosis.

The ability to detect and respond to hypoxia within a developing tumor appears to be a common feature amongst most cancers. This hypoxic response has many molecular drivers, but none as widely studied as Hypoxia-Inducible Factor 1 (HIF-1). Recent evidence suggests that HIF-1 biology within lung adenocarcinoma (LUAD) may be associated with expression levels of adenylate kinases (AKs). Using LUAD patient transcriptome data, we sought to characterize AK gene signatures related to lung cancer hallmarks, such as hypoxia and metabolic reprogramming, to identify conserved biological themes across LUAD tumor progression. Transcriptomic analysis revealed perturbation of HIF-1 targets to correlate with altered expression of most AKs, with AK4 having the strongest correlation. Enrichment analysis of LUAD tumor AK4 gene signatures predicts signatures involved in pyrimidine, and by extension, nucleotide metabolism across all LUAD tumor stages. To further discriminate potential drivers of LUAD tumor progression within AK4 gene signatures, partial least squares discriminant analysis was used at LUAD stage-stage interfaces, identifying candidate genes that may promote LUAD tumor growth or regression. Collectively, these results characterize regulatory gene networks associated with the expression of all nine human AKs that may contribute to underlying metabolic perturbations within LUAD and reveal potential mechanistic insight into the complementary role of AK4 in LUAD tumor development.