Proteome Coverage after Simultaneous Proteo-Metabolome Liquid-Liquid Extraction

MS based foodomics: An edge tool integrated metabolomics and proteomics for food science

Foodomics has become a popular methodology in food science studies. Mass spectrometry (MS) based metabolomics and proteomics analysis played indispensable roles in foodomics research. So far, several methodologies have been developed to detect the metabolites and proteins in diets and consumers, including sample preparation, MS data acquisition, annotation and interpretation. Moreover, multiomics analysis integrated metabolomics and proteomics have received considerable attentions in the field of food safety and nutrition, because of more comprehensive and deeply. In this context, we intended to review the emerging strategies and their applications in MS-based foodomics, as well as future challenges and trends. The principle and application of multiomics were also discussed, such as the optimization of data acquisition, development of analysis algorithm and exploration of systems biology.

Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

Windows Scanning Multiomics: Integrated Metabolomics and Proteomics

Metabolomics and proteomics offer significant advantages in understanding biological mechanisms at two hierarchical levels. However, conventional single omics analysis faces challenges due to the high demand for specimens and the complexity of intrinsic associations. To obtain comprehensive and accurate system biological information, we developed a multiomics analytical method called Windows Scanning Multiomics (WSM). In this method, we performed simultaneous extraction of metabolites and proteins from the same sample, resulting in a 10% increase in the coverage of the identified biomolecules. Both metabolomics and proteomics analyses were conducted by using ultrahigh-performance liquid chromatography mass spectrometry (UPLC-MS), eliminating the need for instrument conversions. Additionally, we designed an R-based program (WSM.R) to integrate mathematical and biological correlations between metabolites and proteins into a correlation network. The network created from simultaneously extracted biomolecules was more focused and comprehensive compared to those from separate extractions. Notably, we excluded six pairs of false-positive relationships between metabolites and proteins in the network established using simultaneously extracted biomolecules. In conclusion, this study introduces a novel approach for multiomics analysis and data processing that greatly aids in bioinformation mining from multiomics results. This method is poised to play an indispensable role in systems biology research.

α-Tocopherol-13'-Carboxychromanol Induces Cell Cycle Arrest and Cell Death by Inhibiting the SREBP1-SCD1 Axis and Causing Imbalance in Lipid Desaturation

α-Tocopherol-13'-carboxychromanol (α-T-13'-COOH) is an endogenously formed bioactive α-tocopherol metabolite that limits inflammation and has been proposed to exert lipid metabolism-regulatory, pro-apoptotic, and anti-tumoral properties at micromolar concentrations. The mechanisms underlying these cell stress-associated responses are, however, poorly understood. Here, we show that the induction of G₀/G₁ cell cycle arrest and apoptosis in macrophages triggered by α-T-13'-COOH is associated with the suppressed proteolytic activation of the lipid anabolic transcription factor sterol regulatory element-binding protein (SREBP)1 and with decreased cellular levels of stearoyl-CoA desaturase (SCD)1. In turn, the fatty acid composition of neutral lipids and phospholipids shifts from monounsaturated to saturated fatty acids, and the concentration of the stress-preventive, pro-survival lipokine 1,2-dioleoyl-sn-glycero-3-phospho-(1'-myo-inositol) [PI(18:1/18:1)] decreases. The selective inhibition of SCD1 mimics the pro-apoptotic and anti-proliferative activity of α-T-13'-COOH, and the provision of the SCD1 product oleic acid (C18:1) prevents α-T-13'-COOH-induced apoptosis. We conclude that micromolar concentrations of α-T-13'-COOH trigger cell death and likely also cell cycle arrest by suppressing the SREBP1-SCD1 axis and depleting cells of monounsaturated fatty acids and PI(18:1/18:1).