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Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings., Graphical Abstract, Highlights • Integrating protein interaction data with metabolic models expands multiomic mapping. • Proteomic profiling of tumors and cell lines reveals altered metabolic-related signatures. • Metabolite measurements validate pathway alterations in cancer cell lines and tumors., In Brief Metabolism is recognized as an important driver of complex diseases, but global metabolite profiling remains a challenge. Protein expression is a poor proxy because pathway enrichment models provide an incomplete mapping between the proteome and metabolism. We developed MOMENTA, a multiomic network approach for interrogating metabolic pathways from proteomics data. Analysis of data from cancer cell lines and human tumors reveals metabolic network rewiring and oncogene connections. The metabolic networks altered in cancer are linked to clinical outcomes.

While the response to acute stress is adaptive in nature, repeated or chronic stress can impact an animal's fitness by depleting its energy stores and suppressing immune function and reproduction. This can be especially deleterious for species that rely on energy reserves to fuel key life history stages (e.g. reproduction), already experience physiological extremes (e.g. fasting), and/or have undergone significant population declines, such as many marine mammals. However, identifying chronically stressed individuals is difficult due to the practical challenges to sample collection from large aquatic animals and a paucity of information on downstream consequences of the stress response. We previously simulated repeated stress by ACTH administration in a model marine mammal, the northern elephant seal, and showed that changes in blubber gene expression, but not circulating cortisol levels, could distinguish between single and repeated responses to ACTH. Here, we profiled changes in the proteome of the same blubber cell population and identified a set of differentially expressed proteins that included extracellular matrix components, heat shock and mitochondrial proteins, metabolic enzymes, and metabolite transporters. Differentially expressed proteins and genes shared similar functions that suggest that repeated corticosteroid elevation may affect blubber tissue proteostasis, mitochondrial activity, adipogenesis, and metabolism in marine mammals. For marine mammal species from which blubber biopsies, but not blood can be obtained by remote sampling, measurement of abundance of such proteins may serve as a novel method for identifying chronically stressed animals.

The outstanding material properties of spider dragline silk fibers have been attributed to two spidroins, major ampullate spidroins 1 and 2 (MaSp1 and MaSp2). Although dragline silk fibers have been treated with different chemical solvents to elucidate the relationship between protein structure and fiber mechanics, there has not been a comprehensive proteomic analysis of the major ampullate (MA) gland, its spinning dope, and dragline silk using a wide range of chaotropic agents, inorganic salts, and fluorinated alcohols to elucidate their complete molecular constituents. In these studies, we perform in-solution tryptic digestions of solubilized MA glands, spinning dope and dragline silk fibers using five different solvents, followed by nano liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis with an Orbitrap Fusion™ Tribrid™. To improve protein identification, we employed three different tryptic peptide fragmentation modes, which included collision-induced dissociation (CID), electron transfer dissociation (ETD), and high energy collision dissociation (HCD) to discover proteins involved in the silk assembly pathway and silk fiber. In addition to MaSp1 and MaSp2, we confirmed the presence of a third spidroin, aciniform spidroin 1 (AcSp1), widely recognized as the major constituent of wrapping silk, as a product of dragline silk. Our findings also reveal that MA glands, spinning dope, and dragline silk contain at least seven common proteins: three members of the Cysteine-Rich Protein Family (CRP1, CRP2 and CRP4), cysteine-rich secretory protein 3 (CRISP3), fasciclin and two uncharacterized proteins. In summary, this study provides a proteomic blueprint to construct synthetic silk fibers that most closely mimic natural fibers.