DataSheet_1_Integration of Metabolomics and Proteomics in Exploring the Endothelial Dysfunction Mechanism Induced by Serum Exosomes From Diabetic Retinopathy and Diabetic Nephropathy Patients.zip

BackgroundThe 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.AimThe aim of this study is to explore the endothelial dysfunction mechanisms of serum exosomes (SExos) extracted from DR and DN (DRDN) patients.MethodsIn 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.ResultsIt 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.ConclusionFIBA overexpression and 1-MH loss may be linked to the pathogenicity of diabetic endothelial dysfunction in DR/DN, implying that 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.</p

Table1_NLRP3-mediated pyroptosis in diabetic nephropathy.DOCX

Diabetic nephropathy (DN) is the main cause of end-stage renal disease (ESRD), which is characterized by a series of abnormal changes such as glomerulosclerosis, podocyte loss, renal tubular atrophy and excessive deposition of extracellular matrix. Simultaneously, the occurrence of inflammatory reaction can promote the aggravation of DN-induced kidney injury. The most important processes in the canonical inflammasome pathway are inflammasome activation and membrane pore formation mediated by gasdermin family. Converging studies shows that pyroptosis can occur in renal intrinsic cells and participate in the development of DN, and its activation mechanism involves a variety of signaling pathways. Meanwhile, the activation of the NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome can not only lead to the occurrence of inflammatory response, but also induce pyroptosis. In addition, a number of drugs targeting pyroptosis-associated proteins have been shown to have potential for treating DN. Consequently, the pathogenesis of pyroptosis and several possible activation pathways of NLRP3 inflammasome were reviewed, and the potential drugs used to treat pyroptosis in DN were summarized in this review. Although relevant studies are still not thorough and comprehensive, these findings still have certain reference value for the understanding, treatment and prognosis of DN.</p

Chemical Method for Nitrogen Isotopic Analysis of Ammonium at Natural Abundance

We report a new chemical method to determine the ¹⁵N natural abundance (δ¹⁵N) for ammonium (NH₄⁺) in freshwater (e.g., precipitation) and soil KCl extract. This method is based on the isotopic analysis of nitrous oxide (N₂O). Ammonium is initially oxidized to nitrite (NO₂^–) by hypobromite (BrO^–) using previously established procedures. NO₂^– is then quantitatively converted into N₂O by hydroxylamine (NH₂OH) under strongly acid conditions. The produced N₂O is analyzed by a commercially available purge and cryogenic trap system coupled to an isotope ratio mass spectrometer (PT-IRMS). On the basis of a typical analysis size of 4 mL, the standard deviation of δ¹⁵N measurements is less than 0.3‰ and often better than 0.1‰ (3 to 5 replicates). Compared to previous methods, the technique here has several advantages and the potential to be used as a routine method for ¹⁵N/¹⁴N analysis of NH₄⁺: (1) substantially simplified preparation procedures and reduced preparation time particularly compared to the methods in which diffusion or distillation is involved since all reactions occur in the same vial and separation of NH₄⁺ from solution is not required; (2) more suitability for low volume samples including those with low N concentration, having a blank size of 0.6 to 2 nmol; (3) elimination of the use of extremely toxic reagents (e.g., HN₃) and/or the use of specialized denitrifying bacterial cultures which may be impractical for many laboratories

Harsh Sensitivity and Mechanism Exploration of an Antibacterial Peptide Extracted from Walnut Oil Residue Derived from Agro-Industrial Waste

Walnut (Juglans regia L.) cake meal constitutes a significant amount of solid byproduct from the production of walnut oil, comprising more than 40% protein. However, it is usually not well utilized. Therefore, an antibacterial peptide was obtained by hydrolyzing walnut oil residue protein with pepsin based on the diameter parameters of the antibacterial zone in this research. The purified antibacterial peptide WRPH-II-6 was obtained by two-part purification (ultrafiltration and reversed-phase liquid chromatography) and possessed higher antibacterial activity against Escherichia coli (MIC = 1.33 mg/mL), Staphylococcus aureus (MIC = 0.33 mg/mL), and Bacillus subtilis (MIC = 0.66 mg/mL). The amino acid sequence of WRPH-II-6 was identified as TGSAVPSPRASATATMEMAAAMGLMPGSPSSVSAVMSPF, where the presence of a large proportion of hydrophobic amino acid residues, such as alanine, proline, and methionine, explained the marked antibacterial activity of WRPH-II-6. The harsh sensitivity experiment demonstrated that WRPH-II-6 retains the stability of antibacterial activity when exposed to broad-spectrum pH values, variable temperatures, and long-lasting UV irradiation. The antibacterial mechanism of the WRPH-II-6 peptide against S. aureus and B. subtilis involves nonmembrane disruption: the contact of anions and cations causes the folding and collapse of the bacterial cell membrane to achieve the inhibitory effect. The antibacterial mechanism against E. coli is membrane disruption, which markedly disrupts the bacterial cell membrane to achieve the bactericidal effect. Significantly, the walnut residual protein hydrolysate is a potent preservative and antibacterial agent

Data_Sheet_1_Prediction and Risk Stratification of Cardiovascular Disease in Diabetic Kidney Disease Patients.doc

BackgroundDiabetic kidney disease (DKD) patients are facing an extremely high risk of cardiovascular disease (CVD), which is a major cause of death for DKD patients. We aimed to build a deep learning model to predict CVD risk among DKD patients and perform risk stratifying, which could help them perform early intervention and improve personal health management.MethodsA retrospective cohort study was conducted to assess the risk of the occurrence of composite cardiovascular disease, which includes coronary heart disease, cerebrovascular diseases, congestive heart failure, and peripheral artery disease, in DKD patients. A least absolute shrinkage and selection operator (LASSO) regression was used to perform the variable selection. A deep learning-based survival model called DeepSurv, based on a feed-forward neural network was developed to predict CVD risk among DKD patients. We compared the model performance with the conventional Cox proportional hazards (CPH) model and the Random survival forest (RSF) model using the concordance index (C-index), the area under the curve (AUC), and integrated Brier scores (IBS).ResultsWe recruited 890 patients diagnosed with DKD in this retrospective study. During a median follow-up of 10.4 months, there are 289 patients who sustained a subsequent CVD. Seven variables, including age, high density lipoprotein (HDL), hemoglobin (Hb), systolic blood pressure (SBP), smoking status, 24 h urinary protein excretion, and total cholesterol (TC), chosen by LASSO regression were used to develop the predictive model. The DeepSurv model showed the best performance, achieved a C-index of 0.767(95% confidence intervals [CI]: 0.717–0.817), AUC of 0.780(95%CI: 0.721–0.839), and IBS of 0.067 in the validation set. Then we used the cut-off value determined by ROC (receiver operating characteristic) curve to divide the patients into different risk groups. Moreover, the DeepSurv model was also applied to develop an online calculation tool for patients to conduct risk monitoring.ConclusionA deep-learning-based predictive model using seven clinical variables can effectively predict CVD risk among DKD patients and perform risk stratification. An online calculator allows its easy implementation.</p

DataSheet1_Analysis of the temporal and spatial pattern of air pollution and the heterogeneity of its influencing factors in central Inner Mongolia from 2016 to 2018.DOCX

The central region of Inner Mongolia is the northern ecological safety barrier of Beijing and even the whole country. It is one of the main sources of dust in North China, and air pollution control is the top priority in this region. In this study, the central region of Inner Mongolia was selected as the study area, multiple auxiliary variables were used to estimate the spatial distribution of PM2.5 concentration from 2016 to 2018 by geographically weighted regression, and the socioeconomic determinants of PM2.5 concentration were analyzed by geographic detectors. The results show that: 1) the established model can better estimate the spatial distribution of PM2.5 concentration in the study area, and the monthly mean correlation coefficient R of the verification parameters is stable, ranging from 0.58 to 0.66. 2) PM2.5 concentration in central Inner Mongolia showed significant temporal and spatial variation. The mean annual PM2.5 concentration along the Yellow River basin is the highest in the study area. PM2.5 concentration first increased and then decreased from 2016 to 2018. 3) Urban built-up area, permanent population and per capita GDP are the key factors affecting the spatial and temporal distribution of PM2.5 concentration in the study area. The results of this study provide theoretical basis and technical support for air pollution monitoring, management and prevention in central Inner Mongolia.</p

Data_Sheet_1_Metabolomic Profiling of Amino Acids in Human Plasma Distinguishes Diabetic Kidney Disease From Type 2 Diabetes Mellitus.docx

Background: Diabetic kidney disease (DKD) is a highly prevalent complication in patients with type 2 diabetes mellitus (T2DM). Patients with DKD exhibit changes in plasma levels of amino acids (AAs) due to insulin resistance, reduced protein intake, and impaired renal transport of AAs. The role of AAs in distinguishing DKD from T2DM and healthy controls has yet to be elucidated. This study aimed to investigate the metabolomic profiling of AAs in the plasma of patients with DKD.Methods: We established an ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method to detect the plasma levels of the 20 AAs in healthy controls (n = 112), patients with T2DM (n = 101), and patients with DKD (n = 101). The key AAs associated with DKD were identified by orthogonal partial least-squares discriminant analysis (OPLS-DA) models with loading plots, shared and unique structures (SUS) plots, and variable importance in projection (VIP) values. The discrimination accuracies of these key AAs were then determined by analyses of receiver-operating characteristic (ROC) curves.Results: Metabolomic profiling of plasma revealed significant alterations in levels of the 20 AAs in patients with DKD when compared to those in either patients with T2DM or healthy controls. Metabolomic profiling of the 20 AAs showed a visual separation of patients with DKD from patients with T2DM and healthy controls in OPLS-DA models. Based on loading plots, SUS plots, and VIP values in the OPLS-DA models, we identified valine and cysteine as potential contributors to the progression of DKD from patients with T2DM. Histidine was identified as a key mediator that could distinguish patients with DKD from healthy controls. Plasma levels of histidine and valine were decreased significantly in patients with DKD with a decline in kidney function, and had excellent performance in distinguishing patients with DKD from patients with T2DM and healthy controls according to ROC curves.Conclusion: Plasma levels of histidine and valine were identified as the main AAs that can distinguish patients with DKD. Our findings provide new options for the prevention, treatment, and management of DKD.</p

Image6_Lysine Acetylation in the Proteome of Renal Tubular Epithelial Cells in Diabetic Nephropathy.TIF

Diabetic nephropathy is considered one of the most common microvascular complications of diabetes and the pathophysiology involves multiple factors. Progressive diabetic nephropathy is believed to be related to the structure and function of the tubular epithelial cells in the kidney. However, the role of lysine acetylation in lesions of the renal tubular epithelial cells arising from hyperglycemia is poorly understood. Consequently, in this study, we cultured mouse renal tubular epithelial cells in vitro under high glucose conditions and analyzed the acetylation levels of proteins by liquid chromatography-high-resolution mass spectrometry. We identified 48 upregulated proteins and downregulated 86 proteins. In addition, we identified 113 sites with higher acetylation levels and 374 sites with lower acetylation levels. Subcellular localization analysis showed that the majority of the acetylated proteins were located in the mitochondria (43.17%), nucleus (28.57%) and cytoplasm (16.19%). Enrichment analysis indicated that these acetylated proteins are primarily associated with oxidative phosphorylation, the citrate cycle (TCA cycle), metabolic pathways and carbon metabolism. In addition, we used the MCODE plug-in and the cytoHubba plug-in in Cytoscape software to analyze the PPI network and displayed the first four most compact MOCDEs and the top 10 hub genes from the differentially expressed proteins between global and acetylated proteomes. Finally, we extracted 37 conserved motifs from 4915 acetylated peptides. Collectively, this comprehensive analysis of the proteome reveals novel insights into the role of lysine acetylation in tubular epithelial cells and may make a valuable contribution towards the identification of the pathological mechanisms of diabetic nephropathy.</p

Image7_Lysine Acetylation in the Proteome of Renal Tubular Epithelial Cells in Diabetic Nephropathy.TIF

Diabetic nephropathy is considered one of the most common microvascular complications of diabetes and the pathophysiology involves multiple factors. Progressive diabetic nephropathy is believed to be related to the structure and function of the tubular epithelial cells in the kidney. However, the role of lysine acetylation in lesions of the renal tubular epithelial cells arising from hyperglycemia is poorly understood. Consequently, in this study, we cultured mouse renal tubular epithelial cells in vitro under high glucose conditions and analyzed the acetylation levels of proteins by liquid chromatography-high-resolution mass spectrometry. We identified 48 upregulated proteins and downregulated 86 proteins. In addition, we identified 113 sites with higher acetylation levels and 374 sites with lower acetylation levels. Subcellular localization analysis showed that the majority of the acetylated proteins were located in the mitochondria (43.17%), nucleus (28.57%) and cytoplasm (16.19%). Enrichment analysis indicated that these acetylated proteins are primarily associated with oxidative phosphorylation, the citrate cycle (TCA cycle), metabolic pathways and carbon metabolism. In addition, we used the MCODE plug-in and the cytoHubba plug-in in Cytoscape software to analyze the PPI network and displayed the first four most compact MOCDEs and the top 10 hub genes from the differentially expressed proteins between global and acetylated proteomes. Finally, we extracted 37 conserved motifs from 4915 acetylated peptides. Collectively, this comprehensive analysis of the proteome reveals novel insights into the role of lysine acetylation in tubular epithelial cells and may make a valuable contribution towards the identification of the pathological mechanisms of diabetic nephropathy.</p

Table2_Lysine Acetylation in the Proteome of Renal Tubular Epithelial Cells in Diabetic Nephropathy.xls

Diabetic nephropathy is considered one of the most common microvascular complications of diabetes and the pathophysiology involves multiple factors. Progressive diabetic nephropathy is believed to be related to the structure and function of the tubular epithelial cells in the kidney. However, the role of lysine acetylation in lesions of the renal tubular epithelial cells arising from hyperglycemia is poorly understood. Consequently, in this study, we cultured mouse renal tubular epithelial cells in vitro under high glucose conditions and analyzed the acetylation levels of proteins by liquid chromatography-high-resolution mass spectrometry. We identified 48 upregulated proteins and downregulated 86 proteins. In addition, we identified 113 sites with higher acetylation levels and 374 sites with lower acetylation levels. Subcellular localization analysis showed that the majority of the acetylated proteins were located in the mitochondria (43.17%), nucleus (28.57%) and cytoplasm (16.19%). Enrichment analysis indicated that these acetylated proteins are primarily associated with oxidative phosphorylation, the citrate cycle (TCA cycle), metabolic pathways and carbon metabolism. In addition, we used the MCODE plug-in and the cytoHubba plug-in in Cytoscape software to analyze the PPI network and displayed the first four most compact MOCDEs and the top 10 hub genes from the differentially expressed proteins between global and acetylated proteomes. Finally, we extracted 37 conserved motifs from 4915 acetylated peptides. Collectively, this comprehensive analysis of the proteome reveals novel insights into the role of lysine acetylation in tubular epithelial cells and may make a valuable contribution towards the identification of the pathological mechanisms of diabetic nephropathy.</p