Integrated proteome and malonylome analyses reveal the potential meaning of TLN1 and ACTB in end-stage renal disease.

BACKGROUND: End-stage renal disease (ESRD) is a condition that is characterized by the loss of kidney function. ESRD patients suffer from various endothelial dysfunctions, inflammation, and immune system defects. Lysine malonylation (Kmal) is a recently discovered post-translational modification (PTM). Although Kmal has the ability to regulate a wide range of biological processes in various organisms, its specific role in ESRD is limited. METHODS: In this study, the affinity enrichment and liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have been used to create the first global proteome and malonyl proteome (malonylome) profiles of peripheral blood mononuclear cells (PBMCs) from twenty patients with ESRD and eighty-one controls. RESULTS: On analysis, 793 differentially expressed proteins (DEPs) and 12 differentially malonylated proteins (DMPs) with 16 Kmal sites were identified. The Rap1 signaling pathway and platelet activation pathway were found to be important in the development of chronic kidney disease (CKD), as were DMPs TLN1 and ACTB, as well as one malonylated site. One conserved Kmal motif was also discovered. CONCLUSIONS: These findings provided the first report on the Kmal profile in ESRD, which could be useful in understanding the potential role of lysine malonylation modification in the development of ESRD.

Dysregulation of lipid metabolism in the pseudolobule promotes region-specific autophagy in hepatitis B liver cirrhosis.

BACKGROUND: Chronic hepatitis B (CHB) infection leads to liver cirrhosis (LC), the end stage of liver fibrosis. The precise diagnosis and effective therapy for hepatitis B cirrhosis are still lacking. It is highly necessary to elucidate the metabolic alteration, especially the spatial distribution of metabolites, in LC progression. METHODS: In this study, LC-MS/MS together with an airflow-assisted ionization mass spectrometry imaging system was applied to analyze and compare the metabolites' spatial distribution in healthy control (HC) and hepatitis B LC tissue samples. The liver samples were further divided into several subregions in HC and LC groups based on the anatomical characteristics and clinical features. RESULTS: Both the LC-MS/MS and mass spectrometry imaging results indicated separated metabolite clusters between the HC and LC groups. The differential metabolites were mainly concentrated in lipid-like molecules and amino acids. The phosphatidylcholines (PCs), lysoPCs, several fatty acids, and amino acids reduced expression in the LC group with region specific. Acyl-CoA thioesterase 2 and choline/ethanolamine phosphotransferase 1, which regulate PC and fatty acid metabolism, were significantly decreased in the pseudolobule. Meanwhile, the increased expression of LC3B and p62 in the pseudolobule indicated the upregulation of autophagy. CONCLUSIONS: Hepatitis B LC induced region-specific autophagy by increasing the expression of LC3B and p62 in the pseudolobule and by dysregulation of unsaturated fatty acids, amino acids, and PC metabolism. The mass spectrometry imaging system provided additional metabolites' spatial information, which can promote biomarker screening technology and support the exploration of novel mechanisms in LC.

Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells.

Background: Sjögren's syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis. Methods: We downloaded three datasets of SS patients' and healthy pepole's whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers' diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied. Results: We obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2. Conclusion: In this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

Integrated computer analysis and a self-built Chinese cohort study identified GSTM2 as one survival-relevant gene in human colon cancer potentially regulating immune microenvironment.

According to a recent report by GLOBOCAN, colorectal cancer is the third most common and second most deadly cancer in 2020. In our previous proteomic study, we found that the expression of GSTM2 in colon tissues was significantly lower than that in para-cancer tissues, and its lower expression was associated with reduced overall survival rate of patients, suggesting that this gene might play a role in the occurrence of colon cancer. As a member of the detoxifying enzyme family, GSTM2 is likely to play an important role in the initiation of tumors. Whereas, the functions of GSTM2 in colon cancer are barely known. In this study, using the RNA-Seq datasets of colon cancer patients from public database (ntumor = 457, nnormal = 41), we confirmed the reduced expression of GSTM2 and its prognostic value in colon cancer. Furthermore, we used our own Chinese cohort (ntumor = 100, nnormal = 72) verified the lower GSTM2 expression in colon cancer, and also its effects on patient prognosis. Subsequently, we uncovered two potential reasons for the lower expression of GSTM2 in colon cancer tissues, including the deep deletion of GSTM2 on genome, and the up-regulation of RAD21 or SP1. Moreover, we disclosed that GSTM2 might be involved in several immune-related pathways in colon cancer, such as chemokine signaling and leukocyte transendothelial migration. Finally, we revealed that the GSTM2 expression was closely related to the immune-related scores of colon cancer and the infiltration ratios of various immune cells, suggesting that GSTM2 might regulate the development of colon cancer by modulating immune microenvironment. In conclusion, we uncovered the prognostic value of GSTM2 based on the public data and our own data, revealed its potential regulatory role in tumor immune microenvironment, and disclosed the probable reasons for its lower expression in colon cancer. The findings of our study provide a potential prognostic biomarker and drug target for clinical diagnosis and treatment of colon cancer.

Multi-platform-based characterization of ferroptosis in human colorectal cancer.

Ferroptosis is a type of programmed cell death potentially playing an important role in colorectal cancer (CRC) development. However, comprehensive investigations toward ferroptosis in human CRC are lacking. Here, we performed multiple investigations on cancer and para-cancer tissues. We demonstrated that the changes of structural variation and chromatin accessibility in CRC were more associated with the altered mRNA expression of ferroptosis-related genes (FRGs), and the expression of CDKN2A, GPX4, ALOXE3, and LINC00336 was related to the overall survival rates. Subsequently, we revealed that CYBB and YAP1 were potentially the hub genes, and that HSF1 and STAT2 were potentially FRGs' upstream transcription factors. Finally, we depicted the crosstalk between ferroptosis and necrosis, autophagy, and apoptosis. Based on multi-dimensional analyses, we characterized ferroptosis, probable core genes, and the upstream regulators in human CRC. The findings here may improve our understanding of ferroptosis in CRC and provide new opportunities for clinical diagnosis and treatment.

Screening Biomarkers for Systemic Lupus Erythematosus Based on Machine Learning and Exploring Their Expression Correlations With the Ratios of Various Immune Cells.

Background: Systemic lupus erythematosus (SLE) is an autoimmune illness caused by a malfunctioning immunomodulatory system. China has the second highest prevalence of SLE in the world, from 0.03% to 0.07%. SLE is diagnosed using a combination of immunological markers, clinical symptoms, and even invasive biopsy. As a result, genetic diagnostic biomarkers for SLE diagnosis are desperately needed. Method: From the Gene Expression Omnibus (GEO) database, we downloaded three array data sets of SLE patients' and healthy people's peripheral blood mononuclear cells (PBMC) (GSE65391, GSE121239 and GSE61635) as the discovery metadata (nSLE = 1315, nnormal = 122), and pooled four data sets (GSE4588, GSE50772, GSE99967, and GSE24706) as the validate data set (nSLE = 146, nnormal = 76). We screened the differentially expressed genes (DEGs) between the SLE and control samples, and employed the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine recursive feature elimination (SVM-RFE) analyze to discover possible diagnostic biomarkers. The candidate markers' diagnostic efficacy was assessed using the receiver operating characteristic (ROC) curve. The reverse transcription quantitative polymerase chain reaction (RT-qPCR) was utilized to confirm the expression of the putative biomarkers using our own Chinese cohort (nSLE = 13, nnormal = 10). Finally, the proportion of 22 immune cells in SLE patients was determined using the CIBERSORT algorithm, and the correlations between the biomarkers' expression and immune cell ratios were also investigated. Results: We obtained a total of 284 DEGs and uncovered that they were largely involved in several immune relevant pathways, such as type І interferon signaling pathway, defense response to virus, and inflammatory response. Following that, six candidate diagnostic biomarkers for SLE were selected, namely ABCB1, EIF2AK2, HERC6, ID3, IFI27, and PLSCR1, whose expression levels were validated by the discovery and validation cohort data sets. As a signature, the area under curve (AUC) values of these six genes reached to 0.96 and 0.913, respectively, in the discovery and validation data sets. After that, we checked to see if the expression of ABCB1, IFI27, and PLSCR1 in our own Chinese cohort matched that of the discovery and validation sets. Subsequently, we revealed the potentially disturbed immune cell types in SLE patients using the CIBERSORT analysis, and uncovered the most relevant immune cells with the expression of ABCB1, IFI27, and PLSCR1. Conclusion: Our study identified ABCB1, IFI27, and PLSCR1 as potential diagnostic genes for Chinese SLE patients, and uncovered their most relevant immune cells. The findings in this paper provide possible biomarkers for diagnosing Chinese SLE patients.

Multi-Platform-Based Analysis Characterizes Molecular Alterations of the Nucleus in Human Colorectal Cancer.

Background: The disturbed molecular alterations of nucleus may promote the development of colorectal cancer (CRC). A multi-platform-based analysis of nucleus of CRC patients helps us to better understand the underlying mechanism of CRC and screen out the potential drug targets for clinical treatment. However, such studies on nucleus in human CRC are still lacking. Methods: We collected the cancerous and para-cancerous tissues from eight CRC patients and performed a multiplex analysis of the molecular changes of the nucleus, including structural variations (SVs), DNA methylation, chromatin accessibility, proteome and phosphorproteome. Results: In our study, we revealed a significant molecular change of nucleus of CRC patients using our original proteomic and phosphorylomic datasets. Subsequently, we characterized the molecular alterations of nucleus of CRC patients at multiple dimensionalities, including DNA, mRNA, protein and epigenetic modification. Next, we found that the great molecular changes of nucleus might affect the biological processes named endocytosis and ubiquitin-mediated proteolysis. Besides, we identified DYNC1LI2 and TPR as the potentially hub proteins within the network of nuclear genes in CRC cells. Furthermore, we identified 1905 CRC-specific SVs, and proclaimed 17 CRC-specific SVs were probably associated with the disturbance of immune microenvironment of CRC patients. We also revealed that the SVs of CXCL5, CXCL10 and CXCL11 might be the core SVs among all the immune-relevant SVs. Finally, we identified seven genes as the upstream transcriptional factors potentially regulating the expression of nuclear genes, such as YY1 and JUN, using a multi-omics approach. Conclusion: Here, we characterized the molecular changes of nucleus of CRC patients, disclosed the potentially core nuclear genes within the network, and identified the probable upstream regulator of nucleus. The findings of this study are helpful to understand the pathogenic molecular changes of nucleus in CRC patients and provide a functional context for drug development in future.

Projected Influences of Changes in Weather Severity on Autumn-Winter Distributions of Dabbling Ducks in the Mississippi and Atlantic Flyways during the Twenty-First Century.

Projected changes in the relative abundance and timing of autumn-winter migration are assessed for seven dabbling duck species across the Mississippi and Atlantic Flyways for the mid- and late 21st century. Species-specific observed relationships are established between cumulative weather severity in autumn-winter and duck population rate of change. Dynamically downscaled projections of weather severity are developed using a high-resolution regional climate model, interactively coupled to a one-dimensional lake model to represent the Great Lakes and associated lake-effect snowfall. Based on the observed relationships and downscaled climate projections of rising air temperatures and reduced snow cover, delayed autumn-winter migration is expected for all species, with the least delays for the Northern Pintail and the greatest delays for the Mallard. Indeed, the Mallard, the most common and widespread duck in North America, may overwinter in the Great Lakes region by the late 21st century. This highlights the importance of protecting and restoring wetlands across the mid-latitudes of North America, including the Great Lakes Basin, because dabbling ducks are likely to spend more time there, which would impact existing wetlands through increased foraging pressure. Furthermore, inconsistency in the timing and intensity of the traditional autumn-winter migration of dabbling ducks in the Mississippi and Atlantic Flyways could have social and economic consequences to communities to the south, where hunting and birdwatching would be affected.