Proteomic Insights into Cardiac Fibrosis: From Pathophysiological Mechanisms to Therapeutic Opportunities

The disordered extracellular matrix landscape induced endometrial fibrosis of sheep: A multi-omics integrative analysis

Endometrial fibrosis leads to the destruction of endometrial function and affects reproductive performance. However, mechanisms underlying the development of endometrial fibrosis in sheep remain unclear. We use transcriptomic, proteomic, and metabolomic studies to reveal the formation mechanisms of endometrial fibrosis. The results showed that the fibrotic endometrial tissue phenotype presented fewer glands, accompanied by collagen deposition. Transcriptomic results indicated alterations in genes associated with the synthesis and degradation of extracellular matrix components, which alter metabolite homeostasis, especially in glycerophospholipid metabolism. Moreover, differentially expressed metabolites may play regulatory roles in key metabolic processes during fibrogenesis, including protein digestion and absorption, and amino acid synthesis. Affected by the aberrant genes, protein levels related to the extracellular matrix components were altered. In addition, based on Kyoto Encyclopedia of Genes and Genomes analysis of differentially expressed genes, metabolites and proteins, amino acid biosynthesis, glutathione, glycerophospholipid, arginine and proline metabolism, and cell adhesion are closely associated with fibrogenesis. Finally, we analyzed the dynamic changes in serum differential metabolites at different time points during fibrosis. Taken together, fibrosis development is related to metabolic obstacles in extracellular matrix synthesis and degradation triggered by disturbed gene and protein levels.

Transcriptomic profile of the mechanosensitive ion channelome in human cardiac fibroblasts

Human cardiac fibroblasts (HCFs) have mRNA transcripts that encode different mechanosensitive ion channels and channel regulatory proteins whose functions are not known yet. The primary goal of this work was to define the mechanosensitive ion channelome of HCFs. The most common type of cationic channel is the transient receptor potential (TRP) family, which is followed by the TWIK-related K+ channel (TREK), transmembrane protein 63 (TMEM63), and PIEZO channel (PIEZO) families. In the sodium-dependent NON-voltage-gated channel (SCNN) subfamily, only SCNN1D was shown to be highly expressed. Particular members of the acid-sensing ion channel (ASIC) (ASIC1 and ASIC3) subfamilies were also significantly expressed. The transcripts per kilobase million (TPMs) for Piezo 2 were almost 100 times less abundant than those for Piezo 1. The tandem of P domains in a weak inward rectifying K+ channel (TWIK)-2 channel, TWIK-related acid-sensitive K+ channel (TASK)-5, TASK-1, and the TWIK-related K1 (TREK-1) channel were the four most prevalent types in the K2P subfamily. The highest expression in the TRPP subfamily was found for PKD2 and PKD1, while in the TRPM subfamily, it was found for TRPM4, TRPM7, and TRPM3. TRPV2, TRPV4, TRPV3, and TRPV6 (all members of the TRPV subfamily) were also substantially expressed. A strong expression of the TRPC1, TRPC4, TRPC6, and TRPC2 channels and all members of the TRPML subfamily (MCOLN1, MCOLN2, and MCOLN3) was also shown. In terms of the transmembrane protein 16 (TMEM16) family, the HCFs demonstrated significant expression of the TMEM16H, TMEM16F, TMEM16J, TMEM16A, and TMEM16G channels. TMC3 is the most expressed channel in HCFs of all known members of the transmembrane channel-like protein (TMC) family. This analysis of the mechanosensitive ionic channel transcriptome in HCFs: (1) agrees with previously documented findings that all currently identified mechanosensitive channels play a significant and well recognized physiological function in elucidating the mechanosensitive characteristics of HCFs; (2) supports earlier preliminary reports that point to the most common expression of the TRP mechanosensitive family in HCFs; and (3) points to other new mechanosensitive channels (TRPC1, TRPC2, TWIK-2, TMEM16A, ASIC1, and ASIC3).