Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.

Construction of gene/protein interaction networks and enrichment pathway analysis for paroxysmal nocturnal hemoglobinuria and aplastic anemia

Background:To develop a protein-protein interaction network of Paroxysmal nocturnal hemoglobinuria(PNH)and Aplastic anemia(AA)based on genetic genes and to predict pathways underlying the molecular complexes in the network.Methods:In this research,the PNH and AA-related genes were screened through Online Mendelian Inheritance in Man(OMIM).The plugins and Cytoscape were used to search literature and build a protein-protein interaction network.Results:The protein-protein interaction network contains two molecular complexes that are five higher than the correlation integral values.The target genes of this study were obtained:CD59,STAT3,TERC,TNF,AKT1,C5AR1,EPO,IL6,IL10 and so on.We also found that many factors regulate biological behaviors:neutrophils,macrophages,vascular endothelial growth factor,immunoglobulin,interleukin,cytokine receptor,interleukin-6 receptor,tumor necrosis factor,and so on.This research provides a bioinformatics foundation for further explaining the mechanism of common development of both.Conclusion:This indicates that the PNH and AA is a complex process regulated by many cellular pathways and multiple genes.

Network pharmacology-based virtual screening of natural products from Peperomia dindygulensis for the application to treat liver cancer

Traditional Chinese medicine plays an increasingly important role in cancer treatment for the property of the complex components and multi-targets.Peperomia dindygulensis,belonging to Piperaceae family,was proved to be effective to the treatment of cancer,but the action mechanism is incomprehensive.In this study,we employed molecular docking and network pharmacology methods to predict the effective compositions,potential target proteins and potential biological pathways.Six compounds were predicted to have potential activity for liver-cancer target proteins.Meanwhile,we analyzed the biological pathways based on compounds-target network,which may be play an important role in liver cancer.This article is presented to explore the active ingredients of P.dindygulensis and provide crucial material for the further research and development of the plant.

Preterm Birth,From the Biological Knowledges to the Prevention:An Overview

The time of birth is a critical determinant of perinatal and long-term outcomes,and even trans-generational effects.Preterm birth is still the leading cause of infant mortality and morbidity.Unfortunately,rates of preterm birth remain high worldwide.Preterm parturition is a complex syndrome,which can be induced by several factors such as infection,cervical pathology,uterine overdistension,progesterone deficiency,vascular alterations(utero-placental ischemia,decidual hemorrhage),maternal and fetal stress,allograft reaction,allergic phenomena,and probably other several unknown factors.The mechanisms responsible for early labor activation have been partially identified and involve receptors,chemokines,and inflammatory cytokines.It is very useful to understand the cellular and biochemical pathways responsible for preterm labor activation to identify,treat,and prevent negative outcome in a timely manner.Researchers and clinicians play a key role in improving biochemical knowledge on preterm delivery,identifying risk factors,and applying multilevel preventive strategies.

Global Genomic Arrangement of Bacterial Genes Is Closely Tied with the Total Transcriptional Efficiency

The availability of a large number of sequenced bacterial genomes allows researchers not only to derive functional and regulation information about specific organisms but also to study the fundamental properties of the organization of a genome. Here we address an important and chal- lenging question regarding the global arrangement of operons in a bacterial genome： why operons in a bacterial genome are arranged in the way they are. We have previously studied this question and found that operons of more frequently activated pathways tend to be more clustered together in a genome. Specifically, we have developed a simple sequential distance-based pseudo energy func- tion and found that the arrangement of operons in a bacterial genome tend to minimize the clus- teredness function （C value） in comparison with artificially-generated alternatives, for a variety of bacterial genomes. Here we extend our previous work, and report a number of new observations： （a） operons of the same pathways tend to group into a few clusters rather than one; and （b） the global arrangement of these operon clusters tend to minimize a new ＂energy＂ function （C＋ value） that reflects the efficiency of the transcriptional activation of the encoded pathways. These obser- vations provide insights into further study of the genomic organization of genes in bacteria.

Integrated transcriptomic and proteomic study on the different molecular mechanisms of PC12 cell growth on chitosan and collagen/chitosan films

The purpose of this article is to integrate the transcriptomic analysis and the proteomic profiles and to reveal and compare the different molecular mechanisms of PC12 cell growth on the surface of chitosan films and collagen/chitosan films.First,the chitosan films and the collagen/chitosan films were prepared.Subsequently,the cell viability assay was performed;the cell viability of the PC12 cells cultured on the collagen/chitosan films for 24 h was significantly higher than that on the chitosan films.Then,with cDNA microarray,the numbers of differentially expressed genes of PC12 cells on the surface of chitosan and collagen/chitosan films were 13349 and 5165,respectively.Next,the biological pathway analysis indicated that the differentially expressed genes were involved in 40 pathways directly related to cell adhesion and growth.The integrated transcriptomic and our previous proteomic analysis revealed that three biological pathways-extracellular matrix-receptor interaction,focal adhesion and regulation of actin cytoskeleton-were regulated in the processes of protein adsorption,cell adhesion and growth.The adsorbed proteins on the material surfaces further influenced the expression of important downstream genes by regulating the expression of related receptor genes in these three pathways.In comparison,chitosan films had a strong inhibitory effect on PC12 cell adhesion and growth,resulting in the significantly lower cell viability on its surface;on the contrary,collagen/chitosan films were more conducive to promoting PC12 cell adhesion and growth,resulting in higher cell viability.

Computational Challenges in Deciphering Genomic Structures of Bacteria

This article addresses how the functionalities of the cellular machinery of a bacterium might have constrained the genomic arrangement of its genes during evolution and how we can study such problems using computational approaches, taking full advantage of the rapidly increasing pool of the sequenced bacterial genomes, potentially leading to a much improved understanding of why a bacterial genome is organized in the way it is. This article discusses a number of challenging computational problems in elucidating the genomic structures at multiple levels and the information that is encoded through these genomic structures, gearing towards the ultimate understanding of the governing rules of bacterial genome organization.

PMTDS： a computational method based on genetic interaction networks for Precision Medicine Target-Drug Selection in cancer

Background： Precision medicine attempts to tailor the right therapy for the right patient. Recent progress in large- scale collection of patents＇ tumor molecular profiles in The Cancer Genome Atlas （TCGA） provides a foundation for systematic discovery of potential drug targets specific to different types of cancer. However, we still lack powerful computational methods to effectively integrate multiple omics data and protein-protein interaction network technology for an optimum target and drug recommendation for an individual patient. Methods： In this study, a computation method, Precision Medicine Target-Drug Selection （PMTDS） based on genetic interaction networks is developed to select the optimum targets and associated drugs for precision medicine style treatment of cancer. The PMTDS system includes three parts： a personalized medicine knowledgebase for each cancer type, a genetic interaction network-based algorithm and a single patient molecular profiles. The knowledgebase integrates cancer drugs, drug-target databases and gene biological pathway networks. The molecular profiles of each tumor consists of DNA copy number alteration, gene mutation, and tumor gene expression variation compared to its adjacent normal tissue. Results： The novel integrated PMTDS system is applied to select candidate target-drug pairs for 178 TCGA pancreatic adenocarcinoma （PDAC） tumors. The experiment results show known drug targets （EGFR, IGF1R, ERBB2, NRII2 and AKR1B1） of PDAC treatment are identified, which provides important evidence of the PMTDS algorithm＇s accuracy. Other potential targets PTK6, ATF, SYK are, also, recommended for PDAC. Further validation is provided by comparison of selected targets with, both, cell line molecular profiles from the Cancer Cell Line Encyclopedia （CCLE） and drug response data from the Cancer Therapeutics Response Portal （CTRP）. Results from experimental analysis of forty six individual pancreatic cancer samples show that drugs selected by PMTDS have more sample-specific efficacy than the current clinical PDAC therapies. Conclusions： A novelty target and drug priority algorithm PMTDS is developed to identify optimum target-drug pairs by integrating the knowledgebase base with a single patient＇s genomics. The PMTDS system provides an accurate and reliable source for target and off-label drug selection for precision cancer medicine.

A high-throughput study on endothelial cell adhesion and growth mediated by adsorbed serum protein via signaling pathway PCR array

The purpose of this paper is to utilize the signaling pathway polymerase chain reaction(PCR)arrays to investigate the activation of two important biological signaling pathways in endothelial cell adhesion and growth mediated by adsorbed serum protein on the surface of bare and titanium nitride(TiN)-coated nickel titanium(NiTi)alloys.First,the endothelial cells were cultured on the bare and TiN-coated NiTi alloys and chitosan films as control for 4 h and 24 h,respectively.Then,the total RNA of the cells was collected and the PCR arrays were performed.After that,the differentially expressed genes in the transforming growth factor beta(TGF-b)signaling pathway and the regulation of actin cytoskeleton pathway were screened out;and the further bioinformatics analyses were performed.The results showed that both TGF-b signaling pathway and regulation of actin cytoskeleton pathway were activated in the cells after 4 h and 24 h culturing on the surface of bare and TiN-coated NiTi alloys compared to the chitosan group.The activated TGF-b signaling pathway promoted cell adhesion;the activated regulation of actin cytoskeleton pathway promoted cell adhesion,spreading,growth and motility.In addition,the activation of both pathways was much stronger in the cells cultured for 24 h versus 4 h,which indicated that cell adhesion and growth became more favorable with longer time on the surface of two NiTi alloy materials.