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An effective combination of multi-omic datasets can enhance our understanding of complex biological phenomena. To build a context-dependent network with multiple omic layers, i.e., a trans-omic network, we perform phosphoproteomics, transcriptomics, proteomics, and metabolomics of murine liver for 4 h after insulin administration and integrate the resulting time series. Structural characteristics and dynamic nature of the network are analyzed to elucidate the impact of insulin. Early and prominent changes in protein phosphorylation and persistent and asynchronous changes in mRNA and protein levels through non-transcriptional mechanisms indicate enhanced crosstalk between phosphorylation-mediated signaling and protein expression regulation. Metabolic response shows different temporal regulation with transient increases at early time points across categories and enhanced response in the amino acid and nucleotide categories at later time points as a result of process convergence. This extensive and dynamic view of the trans-omic network elucidates prominent regulatory mechanisms that drive insulin responses through intricate interlayer coordination., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The thymic function to produce self-protective and self-tolerant T cells is chiefly mediated by cortical thymic epithelial cells (cTECs) and medullary TECs (mTECs). Recent studies including single-cell transcriptomic analyses have highlighted a rich diversity in functional mTEC subpopulations. Because of their limited cellularity, however, the biochemical characterization of TECs, including the proteomic profiling of cTECs and mTECs, has remained unestablished. Utilizing genetically modified mice that carry enlarged but functional thymuses, here we show a combination of proteomic and transcriptomic profiles for cTECs and mTECs, which identified signature molecules that characterize a developmental and functional contrast between cTECs and mTECs. Our results reveal a highly specific impact of the thymoproteasome on proteasome subunit composition in cTECs and provide an integrated trans-omics platform for further exploration of thymus biology., (Published by Elsevier Inc.)

Aims: In this study, we applied quantitative proteomic analysis to identify urinary proteins associated with diabetic nephropathy (DN)., Methods: Two-dimensional image-converted analysis of liquid chromatography and mass spectrometry detected the proteins differentially excreted between normoalbuminuric and macroalbuminuric patients with type 2 diabetes mellitus (T2DM) (n = 6 each). Urinary levels of excreted proteins were measured by multiple reaction monitoring (MRM) analysis using an independent sample set (n = 77). Urinary afamin levels were measured by ELISA in T2DM and DN patients enrolled in this cohort study (n = 203)., Results: One-hundred-four proteins displayed significant alterations in excretion. Nine of these candidates were validated by MRM analysis. Among them, the levels of afamin, CD44 antigen, and lysosome-associated membrane glycoprotein 2, which have not previously been implicated in DN, were significantly associated with both the urinary albumin to creatinine ratio (ACR) and eGFR. We further measured afamin levels in urine collected from T2DM patients who did not yet have significant kidney disease (ACR < 300 mg/g or eGFR change rate ≤ 3.3%/year). The urinary afamin to creatinine ratio (Afa/Cre) was significantly higher in patients who progressed to a more severe DN stage or had early renal decline than in patients who did not., Conclusions: Afa/Cre was significantly increased in T2DM patients who subsequently developed DN. Afa/Cre may be useful to predict patients with T2DM at high risk of nephropathy before the development of macroalbuminuria or reduced kidney function, although further validation studies in a larger population are needed., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Cellular signaling regulates various cellular functions via protein phosphorylation. Phosphoproteomic data potentially include information for a global regulatory network from signaling to cellular functions, but a procedure to reconstruct this network using such data has yet to be established. In this paper, we provide a procedure to reconstruct a global regulatory network from signaling to cellular functions from phosphoproteomic data by integrating prior knowledge of cellular functions and inference of the kinase-substrate relationships (KSRs). We used phosphoproteomic data from insulin-stimulated Fao hepatoma cells and identified protein phosphorylation regulated by insulin specifically over-represented in cellular functions in the KEGG database. We inferred kinases for protein phosphorylation by KSRs, and connected the kinases in the insulin signaling layer to the phosphorylated proteins in the cellular functions, revealing that the insulin signal is selectively transmitted via the Pi3k-Akt and Erk signaling pathways to cellular adhesions and RNA maturation, respectively. Thus, we provide a method to reconstruct global regulatory network from signaling to cellular functions based on phosphoproteomic data., (© 2018 Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.)

Aims/introduction: To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus, differential serum proteomic analysis was carried out on a spontaneous animal model of type 2 diabetes mellitus without obesity, the Long-Evans Agouti (LEA) rat., Materials and Methods: We carried out quantitative proteomic analysis using serum samples from 8- and 16-week-old LEA and control Brown Norway (BN) rats (n = 4/group). Differentially expressed proteins were validated by multiple reaction monitoring analysis using the sera collected from 8-, 16-, and 24-week-old LEA (n = 4/each group) and BN rats (n = 5/each group). Among the validated proteins, we also examined the possible relevance of the human homolog of serine protease inhibitor A3 (SERPINA3) to type 2 diabetes mellitus., Results: The use of 2-D fluorescence difference gel electrophoresis analysis and the following liquid chromatography-multiple reaction monitoring analysis showed that the serum levels of five proteins were differentially changed between LEA rats and BN rats at all three time-points examined. Among the five proteins, SERPINA3N was increased significantly in the sera of LEA rats compared with age-matched BN rats. The serum level of SERPINA3 was also found to be significantly higher in type 2 diabetes mellitus patients than in healthy control participants. Furthermore, glycated hemoglobin, fasting insulin and estimated glomerular filtration rate were independently associated with the SERPINA3 levels., Conclusions: These findings suggest a possible role for SERPINA3 in the development of the early stages of type 2 diabetes mellitus, although further replication studies and functional investigations regarding their role are required., (© 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.)

To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus (T2DM), we carried out differential proteomic analysis using the KK-A(y) mouse, an animal model of T2DM with obesity. We employed an iTRAQ-based quantitative proteomic approach to analyze the proteomic changes in the sera collected from a pair of 4-week-old KK-A(y) versus C57BL/6 mice. Among the 227 proteins identified, a total of 45 proteins were differentially expressed in KK-A(y) versus C57BL/6 mice. We comparatively analyzed a series of the sera collected at 4 and 12weeks of age from KK-A(y) and C57BL/6 mice for the target protein using multiple reaction monitoring analysis, and identified 8 differentially expressed proteins between the sera of these mice at both time points. Among them, serine (or cysteine) peptidase inhibitor, clade A, member 3K (SERPINA3K) levels were elevated significantly in the sera of KK-A(y) mice compared to C57BL/6 mice. An in vitro assay revealed that the human homologue SERPINA3 increased the transendothelial permeability of retinal microvascular endothelial cells, which may be involved in the pathogenesis of diabetes and/or diabetic retinopathy. With the identified proteins, our proteomics study could provide valuable clues for a better understanding of the underlying mechanisms associated with T2DM., Biological Significance: In this paper, we investigated the serum proteome of KK-A(y) mice in a pre-diabetic state compared to that of wild type controls in an attempt to uncover early diagnostic markers of diabetes that are maintained through a diabetic phenotype. We used iTRAQ-based two-dimensional LC-MS/MS serum profiling, and identified several differentially expressed proteins at the pre-diabetic stage. The differential expression was confirmed by multiple reaction monitoring assay, which is fast gaining ground as a sensitive, specific, and cost-effective methodology for relative quantification of the candidate proteins. Using these techniques, we have identified eight candidate proteins of interest including SERPINA3K, which may be important in the pathology of T2DM and/or diabetic retinopathy., (Copyright © 2013 Elsevier B.V. All rights reserved.)

We propose ‘trans-omic’ analysis for reconstructing global biochemical networks across multiple omic layers by use of both multi-omic measurements and computational data integration. We introduce technologies for connecting multi-omic data based on prior knowledge of biochemical interactions and characterize a biochemical trans-omic network by concepts of a static and dynamic nature. We introduce case studies of metabolism-centric trans-omic studies to show how to reconstruct a biochemical trans-omic network by connecting multi-omic data and how to analyze it in terms of the static and dynamic nature. We propose a trans-ome-wide association study (trans-OWAS) connecting phenotypes with trans-omic networks that reflect both genetic and environmental factors, which can characterize several complex lifestyle diseases as breakdowns in the trans-omic system. [ABSTRACT FROM AUTHOR]

Abstract: To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus (T2DM), we carried out differential proteomic analysis using the KK-Ay mouse, an animal model of T2DM with obesity. We employed an iTRAQ-based quantitative proteomic approach to analyze the proteomic changes in the sera collected from a pair of 4-week-old KK-Ay versus C57BL/6 mice. Among the 227 proteins identified, a total of 45 proteins were differentially expressed in KK-Ay versus C57BL/6 mice. We comparatively analyzed a series of the sera collected at 4 and 12weeks of age from KK-Ay and C57BL/6 mice for the target protein using multiple reaction monitoring analysis, and identified 8 differentially expressed proteins between the sera of these mice at both time points. Among them, serine (or cysteine) peptidase inhibitor, clade A, member 3K (SERPINA3K) levels were elevated significantly in the sera of KK-Ay mice compared to C57BL/6 mice. An in vitro assay revealed that the human homologue SERPINA3 increased the transendothelial permeability of retinal microvascular endothelial cells, which may be involved in the pathogenesis of diabetes and/or diabetic retinopathy. With the identified proteins, our proteomics study could provide valuable clues for a better understanding of the underlying mechanisms associated with T2DM. Biological significance: In this paper, we investigated the serum proteome of KK-Ay mice in a pre-diabetic state compared to that of wild type controls in an attempt to uncover early diagnostic markers of diabetes that are maintained through a diabetic phenotype. We used iTRAQ-based two-dimensional LC–MS/MS serum profiling, and identified several differentially expressed proteins at the pre-diabetic stage. The differential expression was confirmed by multiple reaction monitoring assay, which is fast gaining ground as a sensitive, specific, and cost-effective methodology for relative quantification of the candidate proteins. Using these techniques, we have identified eight candidate proteins of interest including SERPINA3K, which may be important in the pathology of T2DM and/or diabetic retinopathy. [Copyright &y& Elsevier]