Protein-mediated interactions in the dynamic regulation of acute inflammation

Protein-mediated interactions are the fundamental mechanism through which cells regulate health and disease. These interactions require physical contact between proteins and their respective targets of interest. These targets include not only other proteins but also nucleic acids and other important molecules as well. These proteins are often involved in multibody complexes that work dynamically to regulate cellular health and function. Various techniques have been adapted to study these important interactions, such as affinity-based assays, mass spectrometry, and fluorescent detection. The application of these techniques has led to a greater understanding of how protein interactions are responsible for both the instigation and resolution of acute inflammatory diseases. These pursuits aim to provide opportunities to target specific protein interactions to alleviate acute inflammation.

Long non-coding RNA CYTOR modulates cancer progression through miR-136-5p/MAT2B axis in renal cell carcinoma

BACKGROUND

To explore the role of long noncoding RNAs (lncRNAs) cytoskeleton regulator RNA (CYTOR) in renal cell carcinoma (RCC).

METHODS

The levels of CYTOR in RCC tissues and cell lines were detected by RT-qPCR. 786-O and Caki-1 cells were transfected with CYTOR-shRNA or pcDNA-CYTOR respectively, or co-transfected with CYTOR-shRNA and miR-136-5p inhibitor, or co-transfected with miR-136-5p mimic and pcDNA-MAT2B. MTT assay, Transwell assay and flow cytometry were used to evaluate cell proliferation, invasion and apoptosis. The relationship between lncRNA CYTOR and miRNA-136-5p was detected by dual luciferase reporter gene and RNA pull down assays, and the targeted relationship between miRNA-136-5p and MAT2B was verified by dual luciferase reporter gene assay. The interaction between MAT2B and BAG3 protein was verified by co-IP experiment. The role of lncRNA CYTOR in vivo was also examined.

RESULTS

LncRNA CYTOR was up-regulated in RCC tissues and cell lines, and miR-136-5p was down-regulated in renal carcinoma cell lines and tissues. Downregulation of CYTOR inhibited cell proliferation and invasion and promoted apoptosis. miR-136-5p was sponged by lncRNA CYTOR, which negatively regulated the development of RCC. MAT2B was a target gene of miR-136-5p. MAT2B protein interacted directly with BAG3 protein to affect the proliferation, invasion and apoptosis of RCC cells. In vivo experiments showed that the expression level of miR-136-5p was increased, and MAT2B expression was decreased after CYTOR knockdown, thereby inhibiting the development of RCC.

CONCLUSIONS

LncRNA CYTOR promoted the progression of RCC by targeting miR-136-5p to regulate the target gene MAT2B, which interacted with BAG3 protein.

Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases

BACKGROUND

While genome-wide association studies (GWAS) of complex traits have revealed thousands of reproducible genetic associations to date, these loci collectively confer very little of the heritability of their respective diseases and, in general, have contributed little to our understanding the underlying disease biology. Physical protein interactions have been utilized to increase our understanding of human Mendelian disease loci but have yet to be fully exploited for complex traits.

METHODS

We hypothesized that protein interaction modeling of GWAS findings could highlight important disease-associated loci and unveil the role of their network topology in the genetic architecture of diseases with complex inheritance.

RESULTS

Network modeling of proteins associated with the intragenic single nucleotide polymorphisms of the National Human Genome Research Institute catalog of complex trait GWAS revealed that complex trait associated loci are more likely to be hub and bottleneck genes in available, albeit incomplete, networks (OR=1.59, Fisher's exact test p < 2.24 × 10(-12)). Network modeling also prioritized novel type 2 diabetes (T2D) genetic variations from the Finland-USA Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics and the Wellcome Trust GWAS data, and demonstrated the enrichment of hubs and bottlenecks in prioritized T2D GWAS genes. The potential biological relevance of the T2D hub and bottleneck genes was revealed by their increased number of first degree protein interactions with known T2D genes according to several independent sources (p<0.01, probability of being first interactors of known T2D genes).

CONCLUSION

Virtually all common diseases are complex human traits, and thus the topological centrality in protein networks of complex trait genes has implications in genetics, personal genomics, and therapy.