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. 2020 Jul 7;21(1):467.
doi: 10.1186/s12864-020-06868-5.

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

Chee-Yin Wong  1 , Yao-Ming Chang  2 , Yu-Shuen Tsai  3 , Wailap Victor Ng  4 , Soon-Keng Cheong  1 , Ting-Yu Chang  5 , I-Fang Chung  6   7   8 , Yang-Mooi Lim  9
Affiliations

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

Chee-Yin Wong et al. BMC Genomics. .

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.

Keywords: Differentiation; Mesangial cell; Mesenchymal stem cell; Monotonic feature selector; Time-ordered gene co-expression network; Transcriptomic.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
TO-GCN with 9 levels was constructed from 1191 TF genes. FOSL1, a TF with the strongest monotonic descending pattern (DE = 0), was used as initial TF gene. All TFs were linked together by co-expression relationship (gray line), while some of the co-expression were reported with TRR database support (blue line). TF coloured with green and purple are the TF genes with DE ≤ 4 in descending and ascending pattern respectively. The numbers stated in the middle of each level represent the number of TFs, and TFs with DE ≤ 4 (in parentheses) for that particular level
Fig. 2
Fig. 2
a Evaluation of key genes and biomarkers of MSC down-regulated during the differentiation process. b The connection of these selected descending key genes with their upstream regulators/TFs. These co-expression TFs and key genes were supported with TRR database
Fig. 3
Fig. 3
a Biomarkers or key genes involved in the mesangial cell characteristic and functions were up-regulated during the differentiation process. The expression of these selected key genes in mesangial cells are also being reported in other research. b The connection between these selected ascending key genes and their upstream regulators/TFs. These co-expression TFs and key genes were supported with TRR database
Fig. 4
Fig. 4
Immunohistochemistry showing glomerular expression patterns of the selected monotonic ascending pattern target genes with DE ≤ 4. These genes were expressed in human mesangial cells in glomeruli. These images were collected from the Human Protein Atlas (www.proteinatlas.org) after cropping the glomeruli from the original full images
Fig. 5
Fig. 5
Selected analysis of functional pathways for each level. Three developmental-stage transitions can be observed. Stage 1: differentiation preparation stage (orange); pathways related to cell proliferation have been enriched. Stage 2: differentiation initiation stage (red); pathways related to regulating or driving differentiation have been enriched. Stage 3: maturation stage (green); pathways related to mesangial cell function and characteristics have been enriched
Fig. 6
Fig. 6
For purposes of validating one of the KEGG functional pathway: Vascular smooth muscle contraction (hsa04270), has been enriched in differentiated cells by bioinformatics analysis. MSC co-cultured with injured mesangial cells were treated with AngII; cell contraction was observed as indicated by white arrows. Pure MSC (Control) did not show any contraction after treated with AngII
Fig. 7
Fig. 7
Co-expression network of selected vascular smooth muscle contraction related biomarkers with their upstream regulators/TFs. Co-expression with TRR database support between TF-TF genes were linked with blue lines. While co-expression with TRR database support between TF-non TF genes were linked with red lines
Fig. 8
Fig. 8
Experimental design of the study. a MSC were co-cultured with injured mesangial cells. On indicated days, co-cultured MSC were harvested and RNA was extracted. cDNA was synthesised and subsequently underwent RNA-seq. b After RNA-seq, raw data was processed by initial read processing and normalizations before the data were further analyzed simultaneously using two methods. c Key genes related to MSC or mesangial cells with ascending or descending monotonic patterns over the differentiation process were identified with MFSelector. d Co-expression patterns between TF and construction TF co-expression network were determined by TO-GCN. Once the data from both methods was generated, both sets of data were analysed synergistically (e). The data obtained from both methods were used to correlate the key genes at specific time points to the TO-GCN at different levels. This helps to elucidate the network interaction between TF-TF and TF-key genes at each level of TO-GCN. Additionally, this builds our understanding of the overall gene expression during the MSC differentiation into mesangial cells
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