Rabbit Anti-Human AKAP10 Polyclonal Antibody

Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.

Sudden cardiac death due to abnormal heart rhythm kills 400,000-460,000 Americans each year. To identify genes that regulate heart rhythm, we are developing a screen that uses mouse embryonic stem cells (mESCs) with gene disruptions that can be differentiated into cardiac cells for phenotyping. Here, we show that the heterozygous disruption of the Akap10 (D-AKAP2) gene that disrupts the final 51 aa increases the contractile response of cultured cardiac cells to cholinergic signals. In both heterozygous and homozygous mutant mice derived from these mESCs, the same Akap10 disruption increases the cardiac response to cholinergic signals, suggesting a dominant interfering effect of the Akap10 mutant allele. The mutant mice have cardiac arrhythmias and die prematurely. We also found that a common variant of AKAP10 in humans (646V, 40% of alleles) was associated with increased basal heart rate and decreased heart rate variability (markers of low cholinergic/vagus nerve sensitivity). These markers predict an increased risk of sudden cardiac death. Although the molecular mechanism remains unknown, our findings in mutant mESCs, mice, and a common human AKAP10 SNP all suggest a role for AKAP10 in heart rhythm control. Our stem cell-based screen may provide a means of identifying other genes that control heart rhythm.