Integrated network analysis of transcriptomic and protein-protein interaction data in taurine-treated hepatic stellate cells

BACKGROUND Studies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells(HSCs). Since the molecular mechanism of taurine-mediated antifibrotic activity has not been fully unveiled and is little studied, it is imperative to use "omics" methods to systematically investigate the molecular mechanism by which taurine inhibits liver fibrosis.AIM To establish a network including transcriptomic and protein-protein interaction data to elucidate the molecular mechanism of taurine-induced HSC apoptosis.METHODS We used microarrays, bioinformatics, protein-protein interaction(PPI) network,and sub-modules to investigate taurine-induced changes in gene expression in human HSCs(LX-2). Subsequently, all of the differentially expressed genes(DEGs) were subjected to gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Furthermore, the interactions of DEGs were explored in a human PPI network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software.RESULTS A total of 635 DEGs were identified in taurine-treated HSCs when compared with the controls. Of these, 304 genes were statistically significantly up-regulated, and 331 down-regulated. Most of these DEGs were mainly located on the membrane and extracellular region, and are involved in the biological processes of signal transduction, cell proliferation, positive regulation of extracellular regulated protein kinases 1(ERK1) and ERK2 cascade, extrinsic apoptotic signaling pathway and so on. Fifteen significantly enriched pathways with DEGs were identified, including mitogen-activated protein kinase(MAPK) signaling pathway, peroxisome proliferators-activated receptor signaling pathway,estrogen signaling pathway, Th1 and Th2 cell differentiation, cyclic adenosine monophosphate signaling pathway and so on. By integrating the transcriptomics and human PPI data, nine critical genes, including MMP2, MMP9, MMP21,TIMP3, KLF10, CX3CR1, TGFB1, VEGFB, and EGF, were identified in the PPI network analysis.CONCLUSION Taurine promotes the apoptosis of HSCs via up-regulating TGFB1 and then activating the p38 MAPK-JNK-Caspase9/8/3 pathway. These findings enhance the understanding of the molecular mechanism of taurine-induced HSC apoptosis and provide references for liver disorder therapy.

Transcriptome Profile Based on Protein-Protein Interaction Networks Provides a Set of Core Genes for Understanding the Metabolic Mechanisms of the Egg-Protecting Behavior in Amphioctopus fangsiao

Marine organisms cannot grow and reproduce without proper metabolic regulation.Within a metabolic network,problems with a given link will affect the normal life activities of the organism.Many metabolic mechanisms associated with behaviors of Am-phioctopus fangsiao are still unclear.Moreover,as a factor affecting the normal growth of A.fangsiao,egg protection has rarely been considered in previous behavioral studies.In this research,we analyzed the transcriptome profile of gene expression in A.fangsiao egg-unprotected larvae and egg-protected larvae,and identified 818 differentially expressed genes(DEGs).We used GO and KEGG enrichment analyses to search for metabolism-related DEGs.Protein-protein interaction networks were constructed to examine the interactions between metabolism-related genes.Twenty hub genes with multiple protein-protein interaction relationships or that were involved in multiple KEGG signaling pathways were obtained and verified by quantitative RT-PCR.We first studied the effects of egg protection on the metabolism of A.fangsiao larvae by means of protein-protein interaction networks,and the results provide va-luable gene resources for understanding the metabolism of invertebrate larvae.The data serve as a foundation for further research on the egg-protecting behavior of invertebrates.

Yeast protein-protein interaction network model based on biological experimental data

Duplication and divergence have been widely recognized as the two domi- nant evolutionary forces in shaping biological networks, e.g., gene regulatory networks and protein-protein interaction （PPI） networks. It has been shown that the network growth models constructed on the principle of duplication and divergence can recapture the topo- logical properties of real PPI networks. However, such network models only consider the evolution processes. How to select the model parameters with the real biological experi- mental data has not been presented. Therefore, based on the real PPI network statistical data, a yeast PPI network model is constructed. The simulation results indicate that the topological characteristics of the constructed network model are well consistent with those of real PPI networks, especially on sparseness, scale-free, small-world, hierarchical modularity, and disassortativity.

Searching maximum quasi-bicliques from protein-protein interaction network

Searching the maximum bicliques or bipartite subgraphs in a graph is a tough question. We proposed a new and efficient method, Searching Quasi-Bicliques (SQB) algorithm, to detect maximum quasi-bicliques from protein-protein interaction network. As a Divide-and-Conquer method, SQB consists of three steps: first, it divides the protein-protein interaction network into a number of Distance-2-Subgraphs;second, by combining top-down and branch-and-bound methods, SQB seeks quasi-bicliques from every Distance-2-Subgraph;third, all the redundant results are removed. We successfully applied our method on the Saccharomyces cerevisiae dataset and obtained 2754 distinct quasi-bicliques.

Protein-protein interactions: Methods, databases, and applications in virus-host study

Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

基于边权重信息深度网络嵌入的PPIN功能模块检测

现有基于网络嵌入的蛋白质相互作用网络(PPIN)功能模块检测方法通常仅对蛋白质节点信息进行网络嵌入,并未对蛋白质间的边权重信息进行网络嵌入,导致蛋白质功能模块检测质量不理想。针对该问题,提出一种基于边权重信息深度网络嵌入的PPIN功能模块检测方法。结合PPIN的拓扑结构以及基因本体的属性信息,通过图注意力网络的注意力系数来衡量蛋白质间的一阶边权重信息,基于邻域聚合对蛋白质的一阶边权重信息进行嵌入。利用长短期记忆网络的遗忘门和输入门来衡量蛋白质间的高阶边权重信息,并对蛋白质的高阶边权重信息进行嵌入。根据网络嵌入得到的低维向量,通过核心附属聚类算法挖掘出核心团并添加附属蛋白质,从而获得最终的蛋白质功能模块。在Collins、Gavin和Krogan蛋白质数据集上的实验结果表明,该方法相较于基于核心附属聚类的蛋白质功能模块检测等方法在准确率和F1值上最高提升了18.1和12.9个百分点。

RNA sequencing of exosomes secreted by fibroblast and Schwann cells elucidates mechanisms underlying peripheral nerve regeneration

Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported to play a crucial role in axonal regeneration.Howeve r,the role of the IncRNA-microRNAmessenger RNA(mRNA)-competitive endogenous RNA(ceRNA)network in exosome-mediated axonal regeneration remains unclear.In this study,we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts(FC-EXOs)and Schwann cells(SCEXOs).Diffe rential gene expression analysis,Gene Ontology analysis,Kyoto Encyclopedia of Genes and Genomes analysis,and protein-protein intera ction network analysis were used to explo re the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs.We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs,which suggests that it may promote axonal regeneration.In addition,using the miRWalk and Starbase prediction databases,we constructed a regulatory network of ceRNAs targeting Rps5,including 27 microRNAs and five IncRNAs.The ceRNA regulatory network,which included Ftx and Miat,revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury.Our findings suggest that exosomes derived from fibro blast and Schwann cells could be used to treat injuries of peripheral nervous system.

Investigating the Impact of Ocean Acidification on Anti-Stress Mechanisms in Sepia esculenta Larvae Based on Transcriptome Profiling

With the rapid development of oil,energy,power and other industries,CO_(2) emissions rise sharply,which will cause a large amount of CO_(2) in the air be absorbed by the ocean and lead to ocean acidification.The growth and development of organisms can be seriously affected by acidified seawater.Sepia esculenta is a mollusk with high nutritional and economic value and is widely cultured in offshore waters of China.Larvae are the early life forms of the organism and are more vulnerable to changes in the external environment.Too low pH will lead to some adverse reactions in larvae,which will affect metabolism,immune response and other life activities.In this study,we sequenced the transcriptome of S.esculenta subjected to acidified seawater stress and identified 1072differentially expressed genes(DEGs).The detected atypical expression of DEGs substantiates cellular malformation and translocation in S.esculenta under low pH stimulation.Simultaneously,this also substantiates the notable impact of ocean acidification on mollusks.These DEGs were used for functional enrichment analysis of GO and KEGG,and the top twenty items of the biological process classification in GO terms and 11 KEGG signaling pathways were significantly enriched.Finally,the constructed proteinprotein interaction network(PPI)was used to analyze protein-protein interactions,and 12 key DEGs and 3 hub genes were identified.The reliability of 12 genes was verified by quantitative RT-PCR.A comprehensive analysis of the KEGG signaling pathway and PPI revealed that ocean acidification leads to abnormalities in lipid metabolism in S.esculenta larvae,which can lead to cancer development and metastasis,accompanied by some degree of inflammation.The results of the study will help to further investigate the physiological processes of S.esculenta when stimulated by ocean acidification,and provide a reference to cope with the captive breeding of S.esculenta affected by acidification.

Computational and bioinformatics tools for understanding disease mechanisms

Computational methods have significantly transformed biomedical research,offering a comprehensive exploration of disease mechanisms and molecular protein functions.This article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease states.The utilization of protein/gene interaction and genetic variation databases,coupled with pathway analysis can facilitate the identification of potential drug targets.By bridging the gap between molecular-level information and disease understanding,this review contributes insights into the impactful utilization of computational methods,paving the way for targeted interventions and therapeutic advancements in biomedical research.

Structure-based protein-protein interaction networks and drug design

Proteins carry out their functions by interacting with other proteins and small molecules, forming a complex interaction network. In this review, we briefly introduce classical graph theory based protein-protein interaction networks. We also describe the commonly used experimental methods to construct these networks, and the insights that can be gained from these networks. We then discuss the recent transition from graph theory based networks to structure based protein-protein interaction networks and the advantages of the latter over the former, using two networks as examples. We further discuss the usefulness of structure based protein-protein interaction networks for drug discovery, with a special emphasis on drug repositioning.

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.

The USP7 protein interaction network and its roles in tumorigenesis

Ubiquitin-specific protease(USP7),also known as Herpesvirus-associated ubiquitin-specific protease(HAUSP),is a deubiquitinase.There has been significant recent attention on USP7 following the discovery that USP7 is a key regulator of the p53-MDM2 pathway.The USP7 protein is 130 kDa in size and has multiple domains which bind to a diverse set of proteins.These interactions mediate key developmental and homeostatic processes including the cell cycle,immune response,and modulation of transcription factor and epigenetic regulator activity and localization.USP7 also promotes carcinogenesis through aberrant activation of the Wnt signalling pathway and stabilization of HIF-1α.These findings have shown that USP7 may induce tumour progression and be a therapeutic target.Together with interest in developing USP7 as a target,several studies have defined new protein interactions and the regulatory networks within which USP7 functions.In this review,we focus on the protein interactions of USP7 that are most important for its cancer-associated roles.

Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis

BACKGROUND Gastric cancer(GC)is one of the most common cancers and has a poor prognosis.Treatment of GC has remained unchanged over the past few years.AIM To investigate the potential therapeutic targets and related regulatory biomarkers of GC.METHODS We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database.The datasets contained 348 GC tissues and 141 healthy tissues.In total,251 differentially expressed genes(DEGs)were identified,including 187 down-regulated genes and 64 up-regulated genes.The DEGs’enriched functions and pathways include Progesterone-mediated oocyte maturation,cell cycle,and oocyte meiosis,Hepatitis B,and the Hippo signaling pathway.Survival analysis showed that BUB1,MAD2L1,CCNA2,CCNB1,and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway.We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection.RESULTS We focused on three critical genes,which were highly expressed in GC,but negatively related to patient survival.Furthermore,we found that knockdown of Yu K et al.Biochemical analysis in GC WJCC https://www.wjgnet.com 5024 July 26,2023 Volume 11 Issue 21 BIRC5,TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis.In addition,knockdown of BIRC5,TRIP13 or UBE2C increased cellular sensitivity to cisplatin.CONCLUSION Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods.

Identification of host proteins that interact with African swine fever virus pE301R

African swine fever virus(ASFV)infection poses enormous threats and challenges to the global pig industry;however,no effective vaccine is available against ASFV,attributing to the huge viral genome(approximately189 kb)and numerous encoding products(>150 genes)due to the limited understanding on the molecular mechanisms of viral pathogenesis.Elucidating the host-factor/viral-protein interaction network will reveal new targets for developing novel antiviral therapies.Using proteomic analysis,we identified 255 cellular proteins that interact with the ASFV-encoded pE301R protein when transiently expressed in HEK293T cells.Gene ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)database enrichment,and protein-protein interaction(PPI)network analyses revealed that pE301R-interacting host proteins are potentially involved in various biological processes,including protein translation and folding,response to stimulation,and mitochondrial transmembrane transport.The interactions of two putative cellular proteins(apoptosis inducing factor mitochondria associated 1(AIFM1)and vimentin(VIM))with pE301R-apoptosis inducing factor have been verified by co-immunoprecipitation.Our study revealed the inhibitory role of pE301R in interferon(IFN)induction that involves VIM sequestration by pE301R,identified interactions between ASFV pE301R and cellular proteins,and predicted the potential function of pE301R and its associated biological processes,providing valuable information to enhance our understanding of viral protein function,pathogenesis,and potential candidates for the prevention and control of ASFV infection.

Identification of pathogenic genes of pterygium based on the Gene Expression Omnibus database

AIM: To identify the pathogenic genes in pterygium.METHODS: We obtained m RNA expression profiles from the Gene Expression Omnibus database(GEO) to identify differentially expressed genes(DEGs) between pterygium tissues and normal conjunctiva tissues. The Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction(PPI) network and transcription factors(TFs)-target gene regulatory network was performed to understand the function of DEGs. The expression of selected DEGs were validated by the quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS: A total of 557 DEGs were identified between pterygium and normal individual. In PPI network, several genes were with high degrees such as FN1, KPNB1, DDB1, NF2 and BUB3. SSH1, PRSS23, LRP5L, MEOX1, RBM14, ABCA1, JOSD1, KRT6 A and UPK1B were the most downstream genes regulated by TFs. q RT-PCR results showed that FN1, PRSS23, ABCA1, KRT6A, ECT2 and SPARC were significantly up-regulated in pterygium and MEOX1 and MMP3 were also up-regulated with no significance, which was consistent with the our integrated analysis. CONCLUSION: The deregulated genes might be involved in the pathology of pterygium and could be used as treatment targets for pterygium.

Bioinformatics analysis of microarray data to explore the key genes involved in HSF4 mutation-induced cataract

AIM： To reveal the mechanisms of heat-shock transcription factor 4 （HSF4） mutation-induced cataract.METHODS： GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes （DEGs） were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery （DAVID） tool, functional and pathway enrichment analyses were performed for the DEGs. Followed by protein-protein interaction （PPI） network was constructed using STRING database and Cytoscape software. Furthermore, the validated microRNA （miRNA）-DEG pairs were obtained from miRWalk2.0 database, and then miRNA-DEG regulatory network was visualized by Cytoscape software. RESULTS： A total of 176 DEGs were identified in HSF4-null lens compared with wild-type lens. In the PPI network, FBJ osteosarcoma oncogene （FOS）, early growth response 1 （EGR1） and heme oxygenase （decycling） 1 （HMOX1） had higher degrees and could interact with each other. Besides, mmu-miR-15a-5p and mmu-miR-26a-5p were among the top 10 miRNAs in the miRNA-DEG regulatory network. Additionally, mmu-miR-26a-5p could target EGR1 in the regulatory network. CONCLUSION： FOS, EGR1, HMOX1, mmu-miR-26a-5p and mmu-miR-15a-5p might function in the pathogenesis of HSF4 mutation-induced cataract.

Cell cycle and complement inhibitors may be specific for treatment of spinal cord injury in aged and young mice: transcriptomic analyses

Previous studies have reported age-specific pathological and functional outcomes in young and aged patients suffering spinal cord injury,but the mechanisms remain poorly understood. In this study, we examined mice with spinal cord injury. Gene expression profiles from the Gene Expression Omnibus database （accession number GSE93561） were used, including spinal cord samples from 3 young injured mice （2–3-months old, induced by Impactor at Th9 level） and 3 control mice （2–3-months old, no treatment）, as well as 2 aged injured mice （15–18-months old, induced by Impactor at Th9 level） and 2 control mice （15–18-months old, no treatment）. Differentially expressed genes （DEGs） in spinal cord tissue from injured and control mice were identified using the Linear Models for Microarray data method,with a threshold of adjusted P 〈 0.05 and ｜logFC（fold change）｜ 〉 1.5. Protein–protein interaction networks were constructed using data from the STRING database, followed by module analysis by Cytoscape software to screen crucial genes. Kyoto encyclopedia of genes and genomes pathway and Gene Ontology enrichment analyses were performed to investigate the underlying functions of DEGs using Database for Annotation, Visualization and Integrated Discovery. Consequently, 1,604 and 1,153 DEGs were identified between injured and normal control mice in spinal cord tissue of aged and young mice, respectively. Furthermore, a Venn diagram showed that 960 DEGs were shared among aged and young mice, while 644 and 193 DEGs were specific to aged and young mice, respectively. Functional enrichment indicates that shared DEGs are involved in osteoclast differentiation, extracellular matrix–receptor interaction, nuclear factor-kappa B signaling pathway, and focal adhesion. Unique genes for aged and young injured groups were involved in the cell cycle （upregulation of PLK1） and complement （upregulation of C3） activation, respectively. These findings were confirmed by functional analysis of genes in modules （common, 4; aged, 2; young, 1） screened from protein–protein interaction networks. Accordingly, cell cycle and complement inhibitors may be specific treatments for spinal cord injury in aged and young mice, respectively.

Identification of microRNAs and messenger RNAs involved in human umbilical cord mesenchymal stem cell treatment of ischemic cerebral infarction using integrated bioinformatics analysis

In recent years,a large number of differentially expressed genes have been identified in human umbilical cord mesenchymal stem cell(hUMSC)transplants for the treatment of ischemic cerebral infarction.These genes are involved in various biochemical processes,but the role of microRNAs(miRNAs)in this process is still unclear.From the Gene Expression Omnibus(GEO)database,we downloaded two microarray datasets for GSE78731(messenger RNA(mRNA)profile)and GSE97532(miRNA profile).The differentially expressed genes screened were compared between the hUMSC group and the middle cerebral artery occlusion group.Gene ontology enrichment and pathway enrichment analyses were subsequently conducted using the online Database for Annotation,Visualization,and Integrated Discovery.Identified genes were applied to perform weighted gene co-suppression analyses,to establish a weighted co-expression network model.Furthermore,the protein-protein interaction network for differentially expressed genes from turquoise modules was built using Cytoscape(version 3.40)and the most highly correlated subnetwork was extracted from the protein-protein interaction network using the MCODE plugin.The predicted target genes for differentially expressed miRNAs were also identified using the online database starBase v3.0.A total of 3698 differentially expressed genes were identified.Gene ontology analysis demonstrated that differentially expressed genes that are related to hUMSC treatment of ischemic cerebral infarction are involved in endocytosis and inflammatory responses.We identified 12 differentially expressed miRNAs in middle cerebral artery occlusion rats after hUMSC treatment,and these differentially expressed miRNAs were mainly involved in signaling in inflammatory pathways,such as in the regulation of neutrophil migration.In conclusion,we have identified a number of differentially expressed genes and differentially expressed mRNAs,miRNA-mRNAs,and signaling pathways involved in the hUMSC treatment of ischemic cerebral infarction.Bioinformatics and interaction analyses can provide novel clues for further research into hUMSC treatment of ischemic cerebral infarction.

Protein microarray analysis of cytokine expression changes in distal stumps after sciatic nerve transection

A large number of chemokines,cytokines,other trophic factors and the extracellular matrix molecules form a favorable microenvironment for peripheral nerve regeneration.This microenvironment is one of the major factors for regenerative success.Therefore,it is important to investigate the key molecules and regulators affecting nerve regeneration after peripheral nerve injury.However,the identities of specific cytokines at various time points after sciatic nerve injury have not been determined.The study was performed by transecting the sciatic nerve to establish a model of peripheral nerve injury and to analyze,by protein microarray,the expression of different cytokines in the distal nerve after injury.Results showed a large number of cytokines were up-regulated at different time points post injury and several cytokines,e.g.,ciliary neurotrophic factor,were downregulated.The construction of a protein-protein interaction network was used to screen how the proteins interacted with differentially expressed cytokines.Kyoto Encyclopedia of Genes and Genomes pathway and Gene ontology analyses indicated that the differentially expressed cytokines were significantly associated with chemokine signaling pathways,Janus kinase/signal transducers and activators of transcription,phosphoinositide 3-kinase/protein kinase B,and notch signaling pathway.The cytokines involved in inflammation,immune response and cell chemotaxis were up-regulated initially and the cytokines involved in neuronal apoptotic processes,cell-cell adhesion,and cell proliferation were up-regulated at 28 days after injury.Western blot analysis showed that the expression and changes of hepatocyte growth factor,glial cell line-derived neurotrophic factor and ciliary neurotrophic factor were consistent with the results of protein microarray analysis.The results provide a comprehensive understanding of changes in cytokine expression and changes in these cytokines and classical signaling pathways and biological functions during Wallerian degeneration,as well as a basis for potential treatments of peripheral nerve injury.The study was approved by the Institutional Animal Care and Use Committee of the Chinese PLA General Hospital,China(approval number:2016-x9-07)in September 2016.