Identification of ICM-related DEPs
The proteomic analysis based on the DIA technique was performed to investigate the abundance of cardiac protein in end-stage ICM patients. As a result, a total of 28,724 unique peptides and 3419 protein groups were successfully identified. Compared with non-failing donors (control), a total of 546 proteins were differentially expressed in the ICM group, including 377 up-regulated DEPs and 169 down-regulated DEPs (Fig. 1A and 1B).
Functional enrichment analysis of ICM-related DEPs
To further understand the mechanisms involved in ICM, the GO and KEGG pathway analyses of the DEPs were explored. Through annotation on the DAVID database, a total of 149 terms of GO biological process (BP), 59 terms of GO cellular component (CC), 68 terms of molecular function (MF), and 34 terms of KEGG pathway were significantly enriched (Additional file 1). Regarding the GO-BP terms, the ICM-related DEPs were mainly involved in mitochondria function (GO:0070125, GO:0070126, GO:0032543, etc.), DNA activity (GO:0006336, GO:0006334, GO:0006352, GO:0000183, GO:0045815, etc.), muscle contraction (GO:0060048, GO:0002026, GO:0010881, etc.), response to stress, such as hypoxia and reactive oxygen species (GO:0098869, GO:0055114, GO:0071260, GO:0000302, etc.), and energy and lipid mentalism (GO:0006099, GO:0006635, GO:0046034, etc.) (Fig. 2A and Additional file 1). The variations in CC of DEPs were predominantly enriched in extracellular space (GO:0070062, GO:0031012, GO:0005615, etc.), mitochondrion (GO:0005739, GO:0005759, GO:0005743, etc.), ribosome (GO:0005840, GO:0005761, etc.), and cardiac structural framework (GO:0030018, GO:0031430, GO:0030315, etc.) (Fig. 2B and Additional file 1). The variations in MF were markedly enriched in banding activities, such as poly(A) RNA binding (GO:0044822), protein binding (GO:0005515), histone binding (GO:0042393), receptor binding (GO:0005102), etc. (Fig. 2C and Additional file 1). The KEGG pathway analysis results revealed that the ICM-related DEPs were mainly involved in autoimmune response, substance and energy metabolism, such as Systemic lupus erythematosus (hsa05322), Complement and coagulation cascades (hsa04610), Carbon metabolism (hsa01200), Fatty acid degradation (hsa00071), Citrate cycle (TCA cycle) (hsa00020), etc. (Fig. 2D and Additional file 1)
Furthermore, similar results were observed in the analysis of Metascape. As shown in Fig. 2E and 2F, the ICM-related DEPs were markedly enriched in cardiac muscle structure development/organization and contraction, oxidative stress, energy metabolism, lipid metabolism, responses to stress, nucleotide metabolism, ECM (extracellular matrix) organization, immune responses, and so on.
Identification of ICM-related DEGs and the common enriched functions between DEGs and DEPs
To investigate the transcriptomic variations of ICM, the RNA-seq technology was performed. After filtration, an average yield of 70 M clean reads was obtained, with an average alignment rate of 97.38% of each sample. After analysis of the expression level, a total of 1080 DEGs were identified, including 609 up-regulated and 471 down-regulated DEGs in ICM compared with control (Fig. 3A and 3B).
Moreover, the functions of these DEGs were investigated, and a total of 129 BP, 35 CC, 33 MF, and 17 KEGG pathways were enriched (Additional file 2). Similar to DEPs, the biological function of the DEGs were mainly involved in inflammatory/immune response, response to stress, and fibrosis, such as inflammatory response (GO:0006954), T cell activation (GO:0042110), response to hydrogen peroxide (GO:0042542), bone mineralization (GO:0030282), ECM-receptor interaction (hsa04512) (Additional file 2).
The common enriched terms of the DEGs and DEPs were shown in Fig. 3C to 3F. The common BP showed that the ICM-related DEGs or DEPs were involved in the processes of translation (GO:0006412), extracellular matrix organization (GO:0030198), muscle contraction (GO:0003009), and response to stimulators, such as calcium ion or ethanol (GO:0051592, GO:0045471, etc.) (Fig. 3C). The common variations in CC were mainly enriched in extracellular region (GO:0005576) and membrane, such as basement membrane (GO:0005604), cell-cell adherent junction (GO:0005913), apical plasma membrane (GO:0016324) (Fig. 3D). The common MF enrichment results were mainly involved in bind activities, such as protein binding (GO:0005515), calcium ion binding (GO:0005509), and actin filament binding (GO:0051015) (Figure 3E). The common enriched KEGG pathways were Ribosome (hsa03010), Complement and coagulation cascades (hsa04610), Systemic lupus erythematosus (hsa05322) (Fig. 3F).
Integrated analysis of proteome and transcriptome
The integrated analysis of transcriptome and proteome can provide a more comprehensive insight into the gene transcriptional profile and post-transcriptional regulation. In the present study, the expression data of transcriptome and proteome were combined together, and the correlation between the two profiles was calculated. As shown in Fig. 4A, there was no significant correlation between the transcriptome and proteome (r = 0.23). According to the threshold of fold change, the integrated data could be divided into nine quadrants. The third and seventh quadrants represented the same trend for transcriptome and proteome expression, and a total of 28 significantly co-up regulated genes, as well as 13 significantly co-down regulated genes, were identified (Fig. 4A).
The functions of these co-regulated genes were mainly involved in response to hypoxia or oxidative stress, muscle contraction, and the complement cascade, such as HIF-1 signaling pathway, oxidation-reduction process, response to hydrogen peroxide, straited muscle contraction, and complement activation (Fig. 4B). The interactions of these co-regulated genes/proteins were shown the Fig. 4C, and only 18 interactions among 19 proteins were identified. The co-regulated genes with the top 10 degrees were shown in Fig. 4D, and HSP90AA1 showed a central position in the PPI network.
Identification of the DELs and differentially expressed lncRNA-mRNA-protein network construction
Increasing evidence has suggested the crucial role of lncRNA in regulating the transcriptional and post-transcriptional expression of coding genes through three main types, including antisense-, cis-, and trans- regulation[6, 16]. In the present study, a total of 1227 lncRNAs differentially expressed in ICM compared with control, including 626 up-regulated DELs and 601 down-regulated DELs (Fig. 5A and 5B). Moreover, 12 of lncRNA:antisense-mRNA pairs, 37 of lncRNA:cis-mRNA pairs, and 4283 of lncRNA:trans-mRNA pairs were identified between the DEGs and DELs. Additionally, the co-regulated genes between transcriptome and proteome with their regulatory lncRNA were extracted out, and their network was constructed. As shown in Fig. 5C, 13 DELs (DNM1P46-201, SNHG32-204, ZFAS1-204, CLASP1-205, PSMG3-AS1-203, LINC00881-202, GPAM-203, CHTOP-206, HLA-DPB1-217, AL513365.2-202, SNHG5-277, Z99127.4-201, SNHG5-283) were identified which regulated the expression of the 11 co-regulated genes (TF, CACYBP, FMOD, AOC3, TAGLN, PDK1, S100A13, S100A4, HMGN2, IGHA1, HLA-DPA1) by two antisense-, two cis-, and 13 trans- manners. For example, the decreased lncRNA of HLA-DPB1 might up-regulate the expression of the HLA-DPA1 mRNA via antisense- activity, which resulted in an increase of HLA-DPA1 protein (Fig. 5C).
Validation by qRT-PCR
To validate the expression of genes identified in the differentially expressed lncRNA-mRNA-protein network, the qRT-PCR was performed. As shown in Fig. 6, four lncRNAs (AL513365.2-202, DNM1P46-201, HLA-DPB1-217, and SNHG32-204) and one mRNA (S100A13) showed no statistical difference, while the other 9 lncRNAs and 10 mRNAs showed significant difference with the same directions as RNA-seq data.