Identifying significant genes and functionally enriched pathways in familial hypercholesterolemia using integrated gene co-expression network analysis

Familial hypercholesterolemia (FH) is a monogenic lipid disorder which promotes atherosclerosis and cardiovascular diseases. Owing to the lack of sufficient published information, this study aims to identify the potential genetic biomarkers for FH by studying the global gene expression profile of blood cells. The microarray expression data of FH patients and controls was analyzed by different computational biology methods like differential expression analysis, protein network mapping, hub gene identification, functional enrichment of biological pathways, and immune cell restriction analysis. Our results showed the dysregulated expression of 115 genes connected to lipid homeostasis, immune responses, cell adhesion molecules, canonical Wnt signaling, mucin type O-glycan biosynthesis pathways in FH patients. The findings from expanded protein interaction network construction with known FH genes and subsequent Gene Ontology (GO) annotations have also supported the above findings, in addition to identifying the involvement of dysregulated thyroid hormone and ErbB signaling pathways in FH patients. The genes like CSNK1A1, JAK3, PLCG2, RALA, and ZEB2 were found to be enriched under all GO annotation categories. The subsequent phenotype ontology results have revealed JAK3I, PLCG2, and ZEB2 as key hub genes contributing to the inflammation underlying cardiovascular and immune response related phenotypes. Immune cell restriction findings show that above three genes are highly expressed by T-follicular helper CD4⁺ T cells, naïve B cells, and monocytes, respectively. These findings not only provide a theoretical basis to understand the role of immune dysregulations underlying the atherosclerosis among FH patients but may also pave the way to develop genomic medicine for cardiovascular diseases.     

Gene microarray analysis of expression profiles in Suberoyllanilide hyroxamic acid-treated Dendritic cells

Objective

The purpose of this study is to provide a further theoretical basis for the role of Suberoyllanilide hyroxamic acid (SAHA) affect on Dendritic cells (DCs).

Mapping the Polarity Interactome

Interactions between proteins are an essential part of biology, and the desire to identify these interactions has led to the development of numerous technologies to systematically map protein–protein interactions at a large scale. As in most cellular processes, protein interactions are central to the control of cell polarity, and a full understanding of polarity will require comprehensive knowledge of the protein interactions involved. At its core, cell polarity is established through carefully regulated mutually inhibitory interactions between several groups of cortical proteins. While several interactions have been identified, the dynamics and molecular mechanisms that control these interactions are not well understood. Cell polarity also needs to be integrated with cellular processes including junction formation, cytoskeletal organization, organelle positioning, protein trafficking, and functional specialization of membrane domains. Moreover, polarized cells need to respond to external cues that coordinate polarity at the tissue level. Identifying the protein–protein interactions responsible for integrating polarity with all of these processes remains a major challenge, in part because the mechanisms of polarity control vary in different contexts and with developmental times. Because of their unbiased nature, systematic large-scale protein–protein interaction mapping approaches can be particularly helpful to identify such mechanisms. Here, we discuss methods commonly used to generate proteome-wide interactome maps, with an emphasis on advances in our understanding of cell polarity that have been achieved through application of such methods.     

Glucose inhibits insulin release when not promoting the entry of calcium into the beta-cells

The effect of antigen on the metabolism of polyphosphoinositides was investigated in sensitized rat peritoneal mast cells. Addition of antigen to rat peritoneal mast cells prelabelled with [3H]arachidonic acid resulted in a very rapid decrease in the level of phosphatidylinositol 4-phosphate (DPI) within 5 sec, which appeared to precede the breakdown of phosphatidylinositol (PI), while there was no significant decline of PI 4,5-bisphosphate (TPI). The reduced levels of these phosphoinositides returned almost to control or even slightly higher values by 300 sec in parallel with the antigen-stimulated [32P]phosphate incorporation into these lipids. This early and transient disappearance in DPI prior to that in PI was also observed in [3H]glycerol-prelabelled cells. These data suggest that DPI degradation upon stimulation by antigen in mast cells may be an initial step in the histamine release process.     

Protein-protein interaction network-based detection of functionally similar proteins within species

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent.     

Coevolution is a short-distance force at the protein interaction level and correlates with the modular organization of protein networks

We investigated what roles coevolution plays in shaping yeast protein interaction network (PIN). We found that the extent of coevolution between two proteins decreases rapidly as their interacting distance on the PIN increases, suggesting coevolutionary constraint is a short-distance force at the molecular level. We also found that protein-protein interactions (PPIs) with strong coevolution tend to be enriched in interconnected clusters, whereas PPIs with weak coevolution are more frequently present at inter-cluster region. The findings indicate the close relationship between coevolution and modular organization of PINs, and may provide insights into evolution and modularity of cellular networks.     

Systematic analysis to identify novel disease indications and plausible potential chemical leads of glutamate ionotropic receptor NMDA type subunit 1, GRIN1

Schizophrenia is a mental illness affecting the normal lifestyle of adults and early adolescents incurring major symptoms as jumbled speech, involvement in everyday activities eventually got reduced, patients always struggle with attention and memory, reason being both the genetic and environmental factors responsible for altered brain chemistry and structure, resulting in schizophrenia and associated orphan diseases. The network biology describes the interactions among genes/proteins encoding molecular mechanisms of biological processes, development, and diseases. Besides, all the molecular networks, protein-protein Interaction Networks have been significant in distinguishing the pathogenesis of diseases and thereby drug discovery. The present meta-analysis prioritizes novel disease indications viz. rare and orphan diseases associated with target Glutamate Ionotropic Receptor NMDA Type Subunit 1, GRIN1 using text mining knowledge-based tools. Furthermore, ZINC database was virtually screened, and binding conformation of selected compounds was performed and resulted in the identification of Narciclasine (ZINC04097652) and Alvespimycin (ZINC73138787) as potential inhibitors. Furthermore, docked complexes were subjected to MD simulation studies which suggests that the identified leads could be a better potential drug to recuperate schizophrenia.     

ATG7(2) Interacts With Metabolic Proteins and Regulates Central Energy Metabolism

Macroautophagy/autophagy is an essential catabolic process that targets a wide variety of cellular components including proteins, organelles, and pathogens. ATG7, a protein involved in the autophagy process, plays a crucial role in maintaining cellular homeostasis and can contribute to the development of diseases such as cancer. ATG7 initiates autophagy by facilitating the lipidation of the ATG8 proteins in the growing autophagosome membrane. The noncanonical isoform ATG7(2) is unable to perform ATG8 lipidation; however, its cellular regulation and function are unknown. Here, we uncovered a distinct regulation and function of ATG7(2) in contrast with ATG7(1), the canonical isoform. First, affinity-purification mass spectrometry analysis revealed that ATG7(2) establishes direct protein–protein interactions (PPIs) with metabolic proteins, whereas ATG7(1) primarily interacts with autophagy machinery proteins. Furthermore, we identified that ATG7(2) mediates a decrease in metabolic activity, highlighting a novel splice-dependent function of this important autophagy protein. Then, we found a divergent expression pattern of ATG7(1) and ATG7(2) across human tissues. Conclusively, our work uncovers the divergent patterns of expression, protein interactions, and function of ATG7(2) in contrast to ATG7(1). These findings suggest a molecular switch between main catabolic processes through isoform-dependent expression of a key autophagy gene.     

Some protein interaction data do not exhibit power law statistics

It has been claimed that protein-protein interaction (PPI) networks are scale-free, and that identifying high-degree "hub" proteins reveals important features of PPI networks. In this paper, we evaluate the claims that PPI node degree sequences follow a power law, a necessary condition for networks to be scale-free. We provide two PPI network examples which clearly do not have power laws when analyzed correctly, and thus at least these PPI networks are not scale-free. We also show that these PPI networks do appear to have power laws according to methods that have become standard in the existing literature. We explain the source of this error using numerically generated data from analytic formulas, where there are no sampling or noise ambiguities.     

Optimization and bioevaluation of Cdc37-derived peptides: An insight into Hsp90-Cdc37 protein-protein interaction modulators

Targeting Hsp90-Cdc37 protein-protein interaction (PPI) is becoming an alternative approach for future anti-cancer drug development. We previously reported the discovery of an eleven-residue peptide (Pep-1) with micromolar activity for the disruption of Hsp90-Cdc37 PPI. Efforts to improve upon the Pep-1 led to the discovery of more potent modulators for Hsp90-Cdc37 PPI. Through the analysis of peptides binding patterns, more peptides were designed for further verification which resulted in Pep-5, the shortest peptide targeting Hsp90-Cdc37, exerting the optimal structure and the most efficient binding mode. Subsequent MD simulation analysis also confirmed that Pep-5 could perform more stable binding ability and better ligand properties than Pep-1. Under the premise of retentive binding capacity, Pep-5 exhibited lower molecular weight and higher ligand efficiency with a K_d value of 5.99 μM (Pep-1 K_d = 6.90 μM) in both direct binding determination and biological evaluation. The optimal and shortest Pep-5 might provide a breakthrough and a better model for the future design of small molecule inhibitors targeting Hsp90-Cdc37 PPI.