Integrative transcriptome analysis reveals TEKT2 and PIAS2 involvement in diabetic nephropathy

Brief biology and pathophysiology of Tekt bundles

Tektins, a family of microtubule-stabilizing proteins, are critical for cilia and flagella assembly in mammals. They maintain doublet microtubule stability and ciliary/flagellar motility. Loss of Tekt1-5 causes microtubule instability, impaired motility, and diseases like infertility, retinal degeneration, Mainzer-Saldino syndrome, and diabetic nephropathy. Pathophysiological stimuli regulate Tektin expression through transcriptional, posttranscriptional, translational, and posttranslational modifications. This review summarizes the latest findings on Tektin functions and their role in diseases.

Integrative transcriptome analysis reveals Serpine2 promotes glomerular mesangial cell proliferation and extracellular matrix accumulation via activating ERK1/2 signalling pathway in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN) is one of the main causes of end-stage renal disease (ESRD), but its mechanism has not been clearly studied. We utilized integrative transcriptome analysis to explore the pathogenesis of DN.

METHODS

We conducted an analysis by combining bulk dataset and single-cell transcriptome dataset. Through this approach, we identified that Serpine2 may regulate the 'collagen-containing extracellular matrix' pathway involved in DN. Subsequently, we established DN animal and cell models using db/db mice and mesangial cells (MCs) to validate the role of Serpine2 in DN. In the animal model, we detected the expression level of Serpine2 in DN using western blotting (WB) and immunofluorescence (IF) assays. To further clarify the molecular mechanism of Serpine2 in DN, we knocked down Serpine2 and observed its effects on MCs proliferation and extracellular matrix (ECM) accumulation.

RESULTS

Our single-cell analysis of DN models highlighted a pivotal role for MCs in the disease's initiation. Next, through Cytoscape analysis of differentially expressed genes (DEGs) in MCs, we identified the following 10 hub genes: Acta2, Angpt2, Ccn1, Col4a1, Col4a2, Col8a1, Kdr, Thbs1, Tpm4 and Serpine2. Subsequently, we identified that Serpine2 and Kdr were also significantly DEGs in the bulk analysis of glomeruli. Additionally, our integrated gene set enrichment analysis of bulk dataset and single-cell RNA dataset revealed that the 'collagen-containing extracellular matrix' was a key pathway in DN progression. Serpine2 was one of the crucial genes involved in regulating this pathway. Therefore, we speculated that the regulation of the 'collagen-containing extracellular matrix' pathway by Serpine2 was an important mechanism. Importantly, WB and IF staining confirmed that Serpine2 expression was upregulated in the MCs of diabetic mice. Knockdown of Serpine2 in cultured MCs alleviated high-glucose-induced excessive MCs proliferation and ECM accumulation. Finally, we found that ERK agonist Ro 67-7476 eliminated the effect of Serpine2 siRNA.

CONCLUSIONS

In summary, Serpine2 regulates MCs proliferation and ECM synthesis through activation of the ERK1/2 pathway, which is an important pathogenesis mechanism of DN. These findings offer fresh perspectives on the mechanisms of glomerulosclerosis in DN pathogenesis and may provide new targets for treating DN.

Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy

The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.

The advance of single cell transcriptome to study kidney immune cells in diabetic kidney disease

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and a primary cause of end-stage renal disease (ESRD). Increasing studies suggest that immune cells are involved in regulating renal inflammation, which contributes to the progression of DKD. Compared with conventional methods, single-cell sequencing technology is more developed technique that has advantages in resolving cellular heterogeneity, parallel multi-omics studies, and discovering new cell types. ScRNA-seq helps researchers to analyze specifically gene expressions, signaling pathways, intercellular communication as well as their regulations in various immune cells of kidney biopsy and urine samples. It is still challenging to investigate the function of each cell type in the pathophysiology of kidney due to its complex and heterogeneous structure and function. Here, we discuss the application of single-cell transcriptomics in the field of DKD and highlight several recent studies that explore the important role of immune cells including macrophage, T cells, B cells etc. in DKD through scRNA-seq analyses. Through combing the researches of scRNA-seq on immune cells in DKD, this review provides novel perspectives on the pathogenesis and immune therapeutic strategy for DKD.

The role of intercellular communication in diabetic nephropathy

Diabetic nephropathy, a common and severe complication of diabetes, is the leading cause of end-stage renal disease, ultimately leading to renal failure and significantly affecting the prognosis and lives of diabetics worldwide. However, the complexity of its developmental mechanisms makes treating diabetic nephropathy a challenging task, necessitating the search for improved therapeutic targets. Intercellular communication underlies the direct and indirect influence and interaction among various cells within a tissue. Recently, studies have shown that beyond traditional communication methods, tunnel nanotubes, exosomes, filopodial tip vesicles, and the fibrogenic niche can influence pathophysiological changes in diabetic nephropathy by disrupting intercellular communication. Therefore, this paper aims to review the varied roles of intercellular communication in diabetic nephropathy, focusing on recent advances in this area.

The Glomerulus Multiomics Analysis Provides Deeper Insights into Diabetic Nephropathy

Although diabetic nephropathy (DN) is the leading cause of the end-stage renal disease, the exact regulation mechanisms remain unknown. In this study, we integrated the transcriptomics and proteomics profiles of glomeruli isolated from 50 biopsy-proven DN patients and 25 controls to investigate the latest findings about DN pathogenesis. First, 1152 genes exhibited differential expression at the mRNA or protein level, and 364 showed significant association. These strong correlated genes were divided into four different functional modules. Moreover, a regulatory network of the transcription factors (TFs)-target genes (TGs) was constructed, with 30 TFs upregulated at the protein levels and 265 downstream TGs differentially expressed at the mRNA levels. These TFs are the integration centers of several signal transduction pathways and have tremendous therapeutic potential for regulating the aberrant production of TGs and the pathological process of DN. Furthermore, 29 new DN-specific splice-junction peptides were discovered with high confidence; these peptides may play novel functions in the pathological course of DN. So, our in-depth integrative transcriptomics-proteomics analysis provided deeper insights into the pathogenesis of DN and opened the potential avenue for finding new therapeutic interventions. MS raw files were deposited into the proteomeXchange with the dataset identifier PXD040617.

Integrative analyses of biomarkers and pathways for diabetic nephropathy

Background: Diabetic nephropathy (DN) is a widespread diabetic complication and a major cause of terminal kidney disease. There is no doubt that DN is a chronic disease that imposes substantial health and economic burdens on the world's populations. By now, several important and exciting advances have been made in research on etiopathogenesis. Therefore, the genetic mechanisms underlying these effects remain unknown. Methods: The GSE30122, GSE30528, and GSE30529 microarray datasets were downloaded from the Gene Expression Omnibus database (GEO). Analyses of differentially expressed genes (DEGs), enrichment of gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed. Protein-protein interaction (PPI) network construction was completed by the STRING database. Hub genes were identified by Cytoscape software, and common hub genes were identified by taking intersection sets. The diagnostic value of common hub genes was then predicted in the GSE30529 and GSE30528 datasets. Further analysis was carried out on the modules to identify transcription factors and miRNA networks. As well, a comparative toxicogenomics database was used to assess interactions between potential key genes and diseases associated upstream of DN. Results: Samples from 19 DNs and 50 normal controls were identified in the GSE30122 dataset. 86 upregulated genes and 34 downregulated genes (a total of 120 DEGs). GO analysis showed significant enrichment in humoral immune response, protein activation cascade, complement activation, extracellular matrix, glycosaminoglycan binding, and antigen binding. KEGG analysis showed significant enrichment in complement and coagulation cascades, phagosomes, the Rap1 signaling pathway, the PI3K-Akt signaling pathway, and infection. GSEA was mainly enriched in the TYROBP causal network, the inflammatory response pathway, chemokine receptor binding, the interferon signaling pathway, ECM receptor interaction, and the integrin 1 pathway. Meanwhile, mRNA-miRNA and mRNA-TF networks were constructed for common hub genes. Nine pivotal genes were identified by taking the intersection. After validating the expression differences and diagnostic values of the GSE30528 and GSE30529 datasets, eight pivotal genes (TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8) were finally identified as having diagnostic values. Conclusion: Pathway enrichment analysis scores provide insight into the genetic phenotype and may propose molecular mechanisms of DN. The target genes TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8 are promising new targets for DN. SPI1, HIF1A, STAT1, KLF5, RUNX1, MBD1, SP1, and WT1 may be involved in the regulatory mechanisms of DN development. Our study may provide a potential biomarker or therapeutic locus for the study of DN.