Abstract:

The prevalence of diabetic microvascular diseases has increased significantly worldwide, the most common of which are diabetic nephropathy (DN) and diabetic retinopathy (DR). Microvascular endothelial cells are thought to be major targets of hyperglycemic damage, while the underlying mechanism of diffuse endothelial dysfunction in multiple organs needs to be further investigated. The aim of this study is to explore the endothelial dysfunction mechanisms of serum exosomes (SExos) extracted from DR and DN (DRDN) patients. In this study, human glomerular endothelial cells (HGECs) were used as the cell model. Metabolomics ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and proteomics tandem mass tag (TMT)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) together with bioinformatics, the correlation analysis, and the joint pathway analysis were employed to discover the underlying mechanisms of endothelial dysfunction caused by patient’s SExos. From the results, it can be assumed that serum exosomes extracted by DRDN patients might cause endothelial dysfunction mainly by upregulating alpha subunit of the coagulation factor fibrinogen (FIBA) and downregulating 1-methylhistidine (1-MH). Bioinformatics analysis pointed to an important role in reducing excess cysteine and methionine metabolism. A cohort study is needed to further investigate the role of FIBA and 1-MH in the development of DN and DR, as well as the related pathways between the two proteins.

Integration analysis between metabolomics and proteomics.

Abstract:

Intensive production can cause immunological stress in commercial broilers. Chlorogenic acid (CGA) regulates the intestinal microbiota, barrier function, and immune function in chickens. As complex interrelations regulate the dynamic interplay between gut microbiota, the host, and diverse health outcomes, the aim of this study was to elucidate the immunoregulatory mechanisms of CGA using multi-omics approaches. A total of 240 one-day-old male broilers were assigned to a 2 × 2 factorial design with 2 CGA levels (0 or 500 mg/kg) either with or without dexamethasone (DEX) injection for a 21-day experimental period. Therefore, there were 4 dietary treatments: control, DEX, CGA, and DEX + CGA, with 6 replicates per treatment. CGA supplementation improved (P < 0.05) growth performance, jejunal morphology, jejunal barrier function, and immune function in DEX-treated broilers. Moreover, in DEX + CGA-treated broilers, the increase in gut microbiome diversity (P < 0.05) was consistent with a change in taxonomic composition, especially in the Clostridiales vadin BB60_group. Additionally, the levels of short-chain fatty acids increased remarkably (P < 0.01) after CGA supplementation. This was consistent with the Kyoto Encyclopedia of Genes and Genomes analysis results that the “pyruvate fermentation to butanoate” pathway was more enriched (P < 0.01) in the DEX + CGA group than in the DEX group. Proteomics revealed that CGA treatment increased the expression of several health-promoting proteins, thymosin beta (TMSB4X) and legumain (LGMN), which were verified by multiple reaction monitoring. Metabolomics revealed that CGA treatment increased the expression of health-promoting metabolites (2,4-dihydroxy benzoic acid and homogentisic acid). Proteomic and metabolic analyses showed that CGA treatment regulated the peroxisome proliferator-activated receptor (PPAR) and mitogen-activated protein kinase (MAPK) pathways. Western blotting results support these findings. Pearson’s correlation analyses showed correlations (P < 0.01) between altered immune function, jejunal barrier function, different microbiota, proteins, and metabolites parameters. Overall, our data indicate that CGA treatment increased growth performance and improved the immunological functions of DEX-treated broilers by regulating gut microbiota and the PPAR and MAPK pathways. The results offer novel insights into a CGA-mediated improvement in immune function and intestinal health.

Analysis of proteomics, metabolomics and experimental validation

Abstract:

Cholelithiasis is a gastrointestinal disease that is associated with the highest socioeconomic cost. A diagnosis of cholelithiasis based on clinical features is significantly limited, and direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters are unclear. The aim of this study is to uncover direct molecular insights into cholelithiasis and the relationship between cholelithiasis and clinical biochemical parameters, then identify sensitive and specific biomarkers for this disease. In this study, parallel metabolomic and proteomic analyses of plasma from cholelithiasis patients (CPs) and healthy control individuals (HCs) without cholelithiasis were performed using ultrahigh-performance liquid chromatography-tandem mass spectrometry. A multimodule coexpression network analysis and integrated machine learning methods, including least absolute shrinkage and selection operator, random forest, and support vector machine, were used for bioinformatic analyses. An independent cohort and the cross-validation of the combination of two cohorts were used to evaluate the diagnostic performance of the panel. The results showed arachidonic acid metabolism was significantly different between the CP and HC groups. Glyceraldehyde-3-phosphate dehydrogenase, actin beta, phosphoglycerate mutase 1, Enolase 1, Myeloperoxidase, and actin alpha 1 were identified as potential proteins related to cholelithiasis. The correlation between the merged modules and clinical biochemical tests was calculated. A diagnostic panel composed of four candidate biomarkers, including 3-oxotetradecanoic acid, 12-hydroxydodecanoic acid, hemoglobin subunit delta (HBD), and fibrinogen beta chain (FGB), was proposed based on three modules that were significantly associated with cholelithiasis. This study provided some direct molecular insights into cholelithiasis by showing the differences in plasma metabolic and protein profiles between CPs and HCs and presented a potential biomarker panel with two metabolites (3-oxotetradecanoic acid, 12-hydroxydodecanoic acid) and two proteins (HBD, FGB) for predicting cholelithiasis. We also explored the potential correlation of clinical biochemical parameters with combined modules. These findings may provide some reference for the diagnosis of cholelithiasis in clinical practice.

Integrome analysis of Proteomics and Metabolomics.