Single-cell transcriptomic profiles in the pathophysiology within the microenvironment of early diabetic kidney disease

http://www.cell.com/article/S2589004223009549/pdf

A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery

Diabetic kidney disease (DKD) is a long-term and serious complication of diabetes that affects millions of people worldwide. It is characterized by proteinuria, glomerular damage, and renal fibrosis, leading to end-stage renal disease, and the pathogenesis is complex and involves multiple cellular and molecular mechanisms. Among three kinds of intraglomerular cells including podocytes, glomerular endothelial cells (GECs) and mesangial cells (MCs), the alterations in one cell type can produce changes in the others. The cell-to-cell crosstalk plays a crucial role in maintaining the glomerular filtration barrier (GFB) and homeostasis. In this review, we summarized the recent advances in understanding the pathological changes and interactions of these three types of cells in DKD and then focused on the signaling pathways and factors that mediate the crosstalk, such as angiopoietins, vascular endothelial growth factors, transforming growth factor-β, Krüppel-like factors, retinoic acid receptor response protein 1 and exosomes, etc. Furthermore, we also simply introduce the application of the latest technologies in studying cell interactions within glomerular cells and new promising mediators for cell crosstalk in DKD. In conclusion, this review provides a comprehensive and updated overview of the glomerular crosstalk in DKD and highlights its importance for the development of novel intervention approaches. 

Crosstalk among podocytes, glomerular endothelial cells and mesangial cells in diabetic kidney disease: an updated review

Abstract Metal regulatory transcription factor 1 (MTF1) has been reported to be correlated with several human diseases, especially like cancers. Exploring the underlying mechanisms and biological functions of MTF1 could provide novel strategies for clinical diagnosis and therapy of cancers. In this study, we conducted the comprehensive analysis to evaluate the profiles of MTF1 in pan-cancer. For example, TIMER2.0, TNMplot and GEPIA2.0 were employed to analyze the expression values of MTF1 in pan-cancer. The methylation levels of MTF1 were evaluated via UALCAN and DiseaseMeth version 2.0 databases. The mutation profiles of MTF1 in pan-cancers were analyzed using cBioPortal. GEPIA2.0, Kaplan–Meier plotter and cBioPortal were also used to explore the roles of MTF1 in cancer prognosis. We found that high MTF1 expression was related to poor prognosis of liver hepatocellular carcinoma (LIHC) and brain lower grade glioma (LGG). Also, high expression level of MTF1 was associated with good prognosis of kidney renal clear cell carcinoma (KIRC), lung cancer, ovarian cancer and breast cancer. We investigated the genetic alteration and methylation levels of MTF1 between the primary tumor and normal tissues. The relationship between MTF1 expression and several immune cells was analyzed, including T cell CD8 + and dendritic cells (DC). Mechanically, MTF1-interacted molecules might participate in the regulation of metabolism-related pathways, such as peptidyl-serine phosphorylation, negative regulation of cellular amide metabolic process and peptidyl-threonine phosphorylation. Single cell sequencing indicated that MTF1 was associated with angiogenesis, DNA repair and cell invasion. In addition, in vitro experiment indicated knockdown of MTF1 resulted in the suppressed cell proliferation, increased reactive oxygen species (ROS) and promoted cell death in LIHC cells HepG2 and Huh7. Taken together, this pan-cancer analysis of MTF1 has implicated that MTF1 could play an essential role in the progression of various human cancers. 

/pdf/the-biological-significance-of-cuproptosis-key-gene-mtf1-in-1i0kgftn.pdf

The biological significance of cuproptosis-key gene MTF1 in pan-cancer and its inhibitory effects on ROS-mediated cell death of liver hepatocellular carcinoma

Abstract The cellular diversity and complexity of the kidney are on par with its physiological intricacy. Although our anatomical understanding of the different segments and their functions is supported by a plethora of research, the identification of distinct and rare cell populations and their markers remains elusive. Here, we leverage the large number of cells and nuclei profiles using single-cell (scRNA-seq) and single-nuclei (snRNA-seq) RNA-sequencing to build a comprehensive atlas of the adult mouse kidney. We created MKA ( M ouse K idney A tlas) by integrating 59 publicly available single-cell and single-nuclei transcriptomic datasets from eight independent studies. The atlas contains more than 140.000 cells and nuclei covering different single-cell technologies, age, and tissue sections. To harmonize annotations across datasets, we constructed a hierarchical model of the cell populations present in our atlas. Using this hierarchy, we trained a model to automatically identify cells in unannotated datasets and evaluated its performance against well-established methods and annotation references. Our learnt model is dynamic, allowing the incorporation of novel cell populations and refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies and characterized well-studied and rare cell populations. This allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states. 

/pdf/a-comprehensive-mouse-kidney-atlas-enables-rare-cell-1yqhq29g.pdf

Years of research revealed that crosstalk extensively existed among kidney cells, cell factors and metabolites and played an important role in the development of diabetic kidney disease (DKD). In the last few years, single-cell RNA sequencing (scRNA-seq) technology provided new insight into cellular heterogeneity and genetic susceptibility regarding DKD at cell-specific level. The studies based on scRNA-seq enable a much deeper understanding of cell-specific processes such as interaction between cells. In this paper, we aim to review recent progress in single cell transcriptomic analyses of DKD, particularly highlighting on intra- or extra-glomerular cell crosstalk, cellular targets and potential therapeutic strategies for DKD.

/pdf/single-cell-transcriptome-helps-better-understanding-111lmzw9fr.pdf

Single Cell Transcriptome Helps Better Understanding Crosstalk in Diabetic Kidney Disease.

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Single Cell Transcriptome Helps Better Understanding Crosstalk in Diabetic Kidney Disease.