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. 2021 Feb 25:9:617853.
doi: 10.3389/fcell.2021.617853. eCollection 2021.

Single-Cell RNA Sequencing and Quantitative Proteomics Analysis Elucidate Marker Genes and Molecular Mechanisms in Hypoplastic Left Heart Patients With Heart Failure

Li Ma  1   2   3 , Na Zhou  2 , Rongjun Zou  2 , Wanting Shi  4 , Yuanyuan Luo  3 , Na Du  5 , Jing Zhong  5 , Xiaodong Zhao  3 , Xinxin Chen  2 , Huimin Xia  1   3 , Yueheng Wu  6   7
Affiliations

Single-Cell RNA Sequencing and Quantitative Proteomics Analysis Elucidate Marker Genes and Molecular Mechanisms in Hypoplastic Left Heart Patients With Heart Failure

Li Ma et al. Front Cell Dev Biol. .

Abstract

Objective: To probe markers and molecular mechanisms of the hypoplastic left heart (HLH) by single-cell RNA sequencing (scRNA-seq) and quantitative proteomics analysis.

Methods: Following data preprocessing, scRNA-seq data of pluripotent stem cell (iPSC)-derived cardiomyocytes from one HLH patient and one control were analyzed by the Seurat package in R. Cell clusters were characterized, which was followed by a pseudotime analysis. Markers in the pseudotime analysis were utilized for functional enrichment analysis. Quantitative proteomics analysis was based on peripheral blood samples from HLH patients without heart failure (HLH-NHF), HLH patients with heart failure (HLH-HF), and healthy controls. Hub genes were identified by the intersection of pseudotime markers and differentially expressed proteins (DE-proteins), which were validated in the GSE77798 dataset, RT-qPCR, and western blot.

Results: Cardiomyocytes derived from iPSCs were clustered into mesenchymal stem cells, myocardium, and fibroblast cells. Pseudotime analysis revealed their differentiation trajectory. Markers in the three pseudotime clusters were significantly associated with distinct biological processes and pathways. Finally, three hub genes (MMP2, B2M, and COL5A1) were identified, which were highly expressed in the left (LV) and right (RV) ventricles of HLH patients compared with controls. Furthermore, higher expression levels were detected in HLH patients with or without HF than in controls.

Conclusion: Our findings elucidate marker genes and molecular mechanisms of HLH, deepening the understanding of the pathogenesis of HLH.

Keywords: cardiac development; heart failure; hub genes; hypoplastic left heart; quantitative proteomics analysis; single-cell RNA sequencing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The workflow of this study.
FIGURE 2
FIGURE 2
Characterization of cell cluster compositions in HLH and normal cardiomyocytes derived from iPSCs. (A) Identification of highly variable genes between different cardiomyocytes. Red dots indicate highly variable genes, and black dots indicate non-variable genes. (B) The t-SNE plot of cardiomyocyte populations. (C) Visualization of the top 20 marker genes for different cell clusters. (D–F) Pseudotime analysis results. Different colors express different states of cell clusters. The shade of the color indicates the sorting of the cells according to the pseudotime value. Each dot represents a cell, and cells with similar states are clustered together. Each branch point represents a decision point of a possible biological process.
FIGURE 3
FIGURE 3
Functional enrichment analysis of marker genes in the pseudotime clusters. GO and KEGG annotation enrichment analyses of marker genes in pseudotime cluster 1 (A,B), pseudotime cluster 2 (C,D), and pseudotime cluster 3 (E,F). GO includes biological processes (circle), cellular components (triangle), and molecular functions (rectangle).
FIGURE 4
FIGURE 4
Data-independent acquisition quantitative proteomics analysis of HLH-NHF, HLH-HF, and control plasma samples. (A) Correlation analysis of plasma proteins between the three groups of HLH-NHF, HLH-HF, and control samples. (B) The top 10 GO term enrichment analysis results of DEproteins in the three groups of HLH-NHF vs. control, HLH-HF vs. control, HLH-NHF vs. HLH-HF. (C) A heat map visualizing the top 20 DEproteins in the three groups. (D) The top 15 KEGG map enrichment analysis results of DEproteins in the three groups. (E) The COG term enrichment analysis results of DEproteins in the three groups.
FIGURE 5
FIGURE 5
Validation of hub genes from scRNA-seq and proteomics for HLH. (A) A PPI network for DEproteins between HLH-NHF and the control. (B) A PPI network for DEproteins between HLH-HF and the control. (C) A PPI network for DEproteins between HLH-NHF and HLH-HF. Each node represents a DEprotein, and the lines between nodes represent interactions between DEproteins. The darker the color, the greater the fold change of a DEprotein. (D) Venn diagram visualizing three hub genes (MMP2, COL5A1, and B2M) by the intersection of pseudotime markers and DEproteins in HLH-NHF vs. control, HLH-HF vs. control, and HLH-NHF vs. HLH-HF. (E) Validation of the hub genes in the four groups of control LV, HLH-LV, control RV, and HLH-RV from the GSE77798 dataset. (F) Results of color Doppler echocardiography among the left ventricular ejection fraction (EF) and short rate of left ventricle short axis (FS). (G) The results of color Doppler echocardiography corresponding to the left ventricular size and main pulmonary artery diameter. (H) RT-qPCR validation of the hub genes in the control, HLH-NHF, and HLH-HF groups. (I) Western blot validation of the hub genes in the control, HLH-NHF, and HLH-HF groups. #p < 0.05 and ns, no statistical significance.
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References

    1. Alphonso N., Angelini A., Barron D. J., Bellsham-Revell H., Blom N. A., Brown K., et al. (2020). Guidelines for the management of neonates and infants with hypoplastic left heart syndrome: The European Association for Cardio-Thoracic Surgery (EACTS) and the Association for European Paediatric and Congenital Cardiology (AEPC) Hypoplastic Left Heart Syndrome Guidelines Task Force. Eur. J. Cardiothorac. Surg. 58 416–499. 10.1093/ejcts/ezaa188 - DOI - PubMed
    1. Andreasová T., Vránová J. A.-O., Vondráková D., Sedláčková L., Zákostelská Z. J., Neužil P., et al. (2020). Role of biomarkers of cardiac remodeling, myofibrosis, and inflammation in assessment of disease severity in euvolemic patients with chronic stable heart failure. J. Int. Med. Res. 48:300060520947869. 10.1177/0300060520947869 - DOI - PMC - PubMed
    1. Astor B. C., Shafi T., Fau-Hoogeveen R. C., Hoogeveen R. C., Fau-Matsushita K. (2012). Novel markers of kidney function as predictors of ESRD, cardiovascular disease, and mortality in the general population. Am. J. Kidney Dis. 59 653–662. 10.1053/j.ajkd.2011.11.042 - DOI - PMC - PubMed
    1. Barrett T., Wilhite Se Fau-Ledoux P., Ledoux P., Fau-Evangelista C., Evangelista C. (2013). NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res. 41 D991–D995. 10.1093/nar/gks1193 - DOI - PMC - PubMed
    1. Barron D. J., Kilby M. D., Davies B., Wright J. G., Jones T. J., Brawn W. J. (2009). Hypoplastic left heart syndrome. Lancet 374 551–564. 10.1016/s0140-6736(09)60563-8 - DOI - PubMed