Decoding the differentiation of mesenchymal stem cells into mesangial cells at the transcriptomic level

Abstract

Background: Mesangial cells play an important role in the glomerulus to provide mechanical support and maintaine efficient ultrafiltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic profiling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells, to understand the involvement of transcription factor (TF) along the differentiation process, and finally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results: Several ascending and descending monotonic key genes were identified by Monotonic Feature Selector. The identified descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. TO-GCN analysis can classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation. Furthermore, it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic profiling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identified and the related biological implications have been discussed. Finally, we further elucidated for the first time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes involved in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts during the differentiation of MSC into mesangial cells.

Combining single-cell transcriptomics and CellTagging to identify differentiation trajectories of human adipose-derived mesenchymal stem cells

“…Compared with the P0 sample, many new functional subgroups appeared after the expansion of the cells [ 35 ]. This remarkable result indicates that, in the process of proliferation in vitro, the cells spontaneously differentiate and the identity characteristics of the cells change in many aspects.…”

Generating transcriptional regulatory networks from time-ordered stem cell differentiation RNA sequencing data

“…TO-GCN recommends to use normalized quantitative measures, e.g., TPM but also accepts normalized read counts. In this protocol, we use an RNA sequencing dataset from our previous study ( Wong et al., 2020 ) as an example. It is the dataset of mesenchymal stem cells differentiated into mesangial cells.…”

“… Summary We describe steps to 1) identify ascending and descending monotonic key genes from time-ordered stem cell differentiation expression data, 2) construct time-ordered transcriptional regulatory networks, and 3) infer the involvement of transcription factors along the differentiation process. For complete details on the use and execution of this protocol, please refer to Wong et al. (2020) .…”

“…For complete details on the use and execution of this protocol, please refer to Wong et al. (2020) .…”

Current advances of stem cell-based therapy for kidney diseases

“…Numerous studies have demonstrated that MSCs can either differentiate into renal cells in general[ 76 ] or specifically into kidney component cells such as renal epithelial cells[ 77 - 80 ], mesangial cells[ 81 , 82 ], and endothelial cells[ 83 , 84 ].…”