High-Coverage Serum Metabolomics Reveals Metabolic Pathway Dysregulation in Diabetic Retinopathy: A Propensity Score-Matched Study.

Background: Diabetic retinopathy (DR) is a major diabetes-related disease linked to metabolism. However, the cognition of metabolic pathway alterations in DR remains scarce. We aimed to corroborate alterations of metabolic pathways identified in prior studies and investigate novel metabolic dysregulations that may lead to new prevention and treatment strategies for DR. Methods: In this case-control study, we tested 613 serum metabolites in 69 pairs of type 2 diabetic patients (T2DM) with DR and propensity score-matched T2DM without DR via ultra-performance liquid chromatography-tandem mass spectrometry system. Metabolic pathway dysregulation in DR was thoroughly investigated by metabolic pathway analysis, chemical similarity enrichment analysis (ChemRICH), and integrated pathway analysis. The associations of ChemRICH-screened key metabolites with DR were further estimated with restricted cubic spline analyses. Results: A total of 89 differentially expressed metabolites were identified by paired univariate analysis and partial least squares discriminant analysis. We corroborated biosynthesis of unsaturated fatty acids, glycine, serine and threonine metabolism, glutamate and cysteine-related pathways, and nucleotide-related pathways were significantly perturbed in DR, which were identified in prior studies. We also found some novel metabolic alterations associated with DR, including the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives in DR. Conclusions: The results suggest that the metabolism disorder in DR can be better understood through integrating multiple biological knowledge databases. The progression of DR is associated with the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives.

Unraveling Pathways of Health and Lifespan with Integrated Multiomics Approaches.

Distinct and shared pathways of health and lifespan can be untangled following a concerted approach led by experimental design and a rigorous analytical strategy where the confounding effects of diet and feeding regimens can be dissected. In this chapter, we use integrated analysis of multiomics (transcriptomics-metabolomics) data in liver from mice to gain insight into pathways associated with improved health and survival. We identify a unique metabolic hub involving glycine-serine-threonine metabolism at the core of lifespan, and a pattern of shared pathways related to improved health.

Metabolomic and Proteomic Profiles Associated With Ketosis in Dairy Cows.

Ketosis is a common metabolic disease in dairy cows during early lactation. However, information about the metabolomic and proteomic profiles associated with the incidence and progression of ketosis is still limited. In this study, an integrated metabolomics and proteomics approach was performed on blood serum sampled from cows diagnosed with clinical ketosis (case, ≥ 2.60 mmol/L plasma ß-hydroxybutyrate; BHBA) and healthy controls (control, < 1.0 mmol/L BHBA). Samples were taken 2 weeks before parturition and 2 weeks after parturition from 19 animals (nine cases, 10 controls). All serum samples (n = 38) were subjected to Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomic analysis, and 20 samples underwent Data-Independent Acquisition (DIA) LC-MS based proteomic analysis. A total of 97 metabolites and 540 proteins were successfully identified, and multivariate analysis revealed significant differences in both metabolomic and proteomic profiles between cases and controls. We investigated clinical ketosis-associated metabolomic and proteomic changes using statistical analyses. Correlation analysis of statistically significant metabolites and proteins showed 78 strong correlations (correlation coefficient, R ≥ 0.7) between 38 metabolites and 25 proteins, which were then mapped to pathways using IMPaLA. Results showed that ketosis altered a wide range of metabolic pathways, such as metabolism, metabolism of proteins, gene expression and post-translational protein modification, vitamin metabolism, signaling, and disease related pathways. Findings presented here are relevant for identifying molecular targets for ketosis and biomarkers for ketosis detection during the transition period.

Proteomic analysis of Rac1 signaling regulation by guanine nucleotide exchange factors.

The small GTPase Rac1 is implicated in various cellular processes that are essential for normal cell function. Deregulation of Rac1 signaling has also been linked to a number of diseases, including cancer. The diversity of Rac1 functioning in cells is mainly attributed to its ability to bind to a multitude of downstream effectors following activation by Guanine nucleotide Exchange Factors (GEFs). Despite the identification of a large number of Rac1 binding partners, factors influencing downstream specificity are poorly defined, thus hindering the detailed understanding of both Rac1's normal and pathological functions. In a recent study, we demonstrated a role for 2 Rac-specific GEFs, Tiam1 and P-Rex1, in mediating Rac1 anti- versus pro-migratory effects, respectively. Importantly, via conducting a quantitative proteomic screen, we identified distinct changes in the Rac1 interactome following activation by either GEF, indicating that these opposing effects are mediated through GEF modulation of the Rac1 interactome. Here, we present the full list of identified Rac1 interactors together with functional annotation of the differentially regulated Rac1 binding partners. In light of this data, we also provide additional insights into known and novel signaling cascades that might account for the GEF-mediated Rac1-driven cellular effects.