Research Article - (2015) Volume 4, Issue 2
Systems biology is concerned with the study of biological systems, by investigating the components of cellular networks and their interactions. The objective of present study is to build gene-gene interaction network of human cytomegalovirus genes with human genes and other influenza causing genes which helps to identify pathways, recognize gene function and find potential drug targets for cytomegalovirus visualized through cytoscape and its plugin. So, genetic interaction is logical interaction between two genes and more than that affects any organism phenotypically. Human cytomegalovirus has many strategies to survive the attack of the host. Human cytomegalovirus infection of host cells induces cellular activation and disturbance of the cell cycle. Further functional analysis was done to know functionally active genes to cause infection and also these genes will be used as targets to prevent infection spread through virus and then ontology analysis was performed to those functionally active genes describes gene products in terms of their associated biological processes, cellular components and molecular functions by using clueGO Plugin.
Keywords: System biology; Functional analysis; Ontology analysis
Systems biology underpinning inter and intra-cellular dynamical networks, by means of signal and system-oriented approaches, applying experimental high throughput and whole genome techniques, integrating computational methods with experimental efforts. Emergence, robustness and modularity are the three basic concepts that are crucial to understanding complex biological system [1]. The main aspect of system biology is translating the biological information into models [2]. Drug discovery and the design of multiple drug therapies and therapeutic gene circuits and complex engineering product are the applications of systems biology to medical practice [3]. Human cytomegalovirus (HCMV) is an enveloped DNA virus that, like other members of the herpes virus family, establishes lifelong latency following primary infection Cytomegalovirus. Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and integrating with gene profiles and other state data. Cytoscape is most commonly used for biological research applications. The tool is best used in conjunction with large databases of gene expression data, proteinprotein interaction, protein-DNA interaction, and genetic interactions that are increasingly available for humans and model organisms [4]. Several useful plugins are available for Cytoscape to extend its capabilities for example network analyzer plug-in. The study of gene - gene interaction play an important role in the search for the cause of human disease and the main aim of establishment of this study is To Build and Analyse Gene-Gene Interaction Network of HCMV genes. The network of hcmv genes are used for further studies such as Functional and Ontology Analysis of HCMV genes.
Materials
Data source
Gene card is a database of human genes that provide information about their functions, genomic views, proteins and protein domains, transcripts, orthology, paralogs, their expression localization, interaction and involvement in pathway, disease and disorders on all known human genes. Total 129 genes (Table 1) have been extracted from gene card to build a network.
Gene name | GCID from gene cards | PMID |
---|---|---|
RAB6A | GC11MO73386 | 7798313 |
ENSG00000183214 | GC06Pn31357 | 19793804 |
ENSG00000235233 | GC06P131410 | Not found |
RSAD2 | GC02P007005 | Not found |
ENSG00000206206 | GC06MK33264 | 20444888 |
ENSG00000206279 | GC06Mn3215 | 20444888 |
ENSG00000227046 | GC06Mj33207 | 20444888 |
ENSG00000231617 | GC06Mm33456 | 20444888 |
MIR20A | GC13P092001 | 23768492 |
DAXX | GC06MO33286 | 17942542 |
ENSG00000206235 | GC06MI32943 | 9175839 |
ENSG00000206297 | GC06Mn32741 | 9175839 |
ENSG00000206299 | GC06Mn32718 | 9175839 |
ENSG00000223481 | GC06Mk32767 | 9175839 |
ENSG00000224212 | GC06Mk32790 | 9175839 |
ENSG00000225967 | GC06Mi32773 | 9175839 |
ENSG00000226173 | GC06MI32966 | 9175839 |
ENSG00000227816 | GC06Mi32796 | 9175839 |
ENSG00000228582 | GC06Mj32703 | 9175839 |
ENSG00000230705 | GC06Mm32846 | 9175839 |
ENSG00000232326 | GC06Mo32879 | 9175839 |
ENSG00000232367 | GC06Mj32735 | 9175839 |
ENSG00000237599 | GC06Mm23815 | 9175839 |
MIR17 | GC13P092002 | 23768492 |
TMEM147 | GC19P036038 | 17188320 |
GGH | GC08M063928 | 1328481 |
LINC01194 | GC05P012578 | 17400331 |
MRGPRXI | GC11M018955 | 16352349 |
MPZ | GC01M161274 | 17765268 |
HNRNPH3 | GC10P070090 | 21320693 |
MICA | GC06P031373 | 16951502 |
RAB11FIP4 | GC17P029718 | 19761540 |
CBR1 | GC21P037442 | 21320693 |
FKBP10 | GC17P039968 | 21320693 |
IL32 | GC16P003153 | 23402302 |
TMEM43 | GC03P014142 | 21320693 |
TRIM23 | GC05M064885 | 19176615 |
CX3CL1 | GC16P057406 | 19605482 |
DDX39A | GC19M014521 | 20610707 |
LBR | GC01M2255899 | 15018860 |
CAMKK1 | GC17M003763 | Not found |
CD69 | GC12M010498 | 19152985 |
CHAF1A | GC19P004402 | 21445097 |
LILRB1 | GC19P055085 | 23348966 |
MICB | GC06P031465 | 23625227 |
PDIA4 | GC07M148700 | 21320693 |
TAPT1 | GC04M016162 | 10640539 |
WDR26 | GC01M224573 | 21320693 |
ANXA2 | GC15M060639 | 12456502 |
CFLAR | GC02P201980 | 17056549 |
ACLY | GC17M040023 | 21320693 |
ACTL6A | GC03P179280 | 21320693 |
AGTR2 | GC0XP115216 | 18534055 |
ANAPC10 | GC04M145916 | 22792066 |
ANAPC7 | GC12M110810 | 22792066 |
ANAPC5 | GC12M121746 | 22792066 |
CEBPA | GC19M033790 | 19631360 |
EEF2K | GC16P022217 | Not found |
EIF2AK3 | GC02M088857 | 23592989 |
IFI16 | GC01P0158969 | 22291595 |
KAT5 | GC11P065479 | 21320693 |
NUDT21 | GC16M056463 | 21320693 |
RAB11A | GC15P066018 | 19761540 |
RAB1A | GC02M065297 | 21320693 |
SPI1 | GC11M049902 | 18308397 |
TAP1 | GC06M032812 | 9175839 |
TAP2 | GC06M032789 | 9175839 |
THBS2 | GC06M169615 | 11563036 |
TLR3 | GC04P186990 | 19914718 |
DDX39B | GC06M031522 | 20610707 |
ANPEP | GC15M090328 | Not found |
CAMKK2 | GC12M121675 | Not found |
CD59 | GC11M03721 | 7594597 |
CDC23 | GC05M137552 | 22792066 |
DDB1 | GC11M061066 | 21320693 |
EGR1 | GC05P137801 | 10623574 |
EP400 | GC12P132434 | 21320693 |
HFE | GC06P026087 | 12456502 |
HLA-G | GC06P029794 | 9687527 |
MSR1 | GC08M016009 | 19914718 |
PSMB6 | GC17P004699 | 21320693 |
PSMB4 | GC01P151372 | 21320693 |
PSME3 | GC17P040985 | 21320693 |
RUVBL2 | GC19P049497 | 21320693 |
RUVBL1 | GC03M127783 | 21320693 |
TLR9 | GC03M052255 | 19914718 |
UBR5 | GC08M103265 | 21320693 |
CAMK2B | GC07M044225 | Not found |
CAMK2A | GC05M149579 | Not found |
CDC27 | GC17M045195 | 22792066 |
E2F1 | GC20M032263 | 14695446 |
EIF4A1 | GC17P007476 | 23747307 |
HSPA5 | GC09M127997 | 21221131 |
KPNA1 | GC03M122140 | 12610148 |
PML | GC15P074287 | Not found |
PSMA3 | GC14P058711 | 21320693 |
PSMC6 | GC14P053173 | 21320693 |
PSMD3 | GC17P038137 | 21320693 |
RAN | GC12P131356 | 21320693 |
SUMO1 | GC02M203070 | 21816224 |
THBS1 | GC15P039873 | 11563036 |
TRRAP | GC07P098475 | 21320693 |
WT1 | GC11M032365 | 10623574 |
AGTR1 | GC03P148415 | 18534055 |
CAMK2G | GC10M075572 | Not found |
CDK2 | GC12P056360 | 14695446 |
FLNB | GC03P057969 | 12559625 |
GPT | GC08P145728 | 15797363 |
HLA-C | GC06M031236 | 9687527 |
HLA-DQA1 | GC06P032595 | 12443029 |
PSMD2 | CG03P184016 | 21320693 |
PSMC4 | GC19P040477 | 21320693 |
TLR2 | GC04P154612 | 18053251 |
IL10 | GC01M206940 | 15018860 |
IL4 | GC05P132009 | 15018860 |
STAT3 | GC17M040465 | 21320693 |
CAMK2D | GC04M114372 | NOT FOUND |
HLA-A | GC06P030186 | 12443029 |
HLA-DQB1 | GC06M032629 | 12443029 |
ICAM1 | GC19P010381 | 9154389 |
PIK3CG | GC07P106505 | 19427341 |
IL6 | GC07P022765 | 23555719 |
MAPK1 | GC22M022108 | 16650413 |
CASP3 | GC04M185548 | 14695446 |
HLA-DRB1 | GC06M032546 | 12443029 |
NFKB1 | GC04P103422 | 19427341 |
CD55 | GC01P207494 | 7594597 |
MAPK14 | GC06P035995 | 17229385 |
TNF | GC06P031543 | 22486303 |
TP53 | GC17M007565 | 17400331 |
Table 1: The table shows genes of HCMV with their respective GCID.
Tool
Cytoscape is an open source bioinformatics software platform and it provides basic functionality to layout and queries the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations [4,5]. Cytoscape has been used to construct HCMV network for Analysis of HCMV gene.
ClueGO is a cytoscape plug-in that enhances biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. CluePedia provides a comprehensive view on a pathway or process by investigating experimental [5].
Method
The genes involved in infection spread through cytomegalo virus find through GeneCards database and various publish literature. Hence, gene-gene interaction network was built. The interaction network is imported through Cytoscape’s web services option. However the study was aimed to find out the genes involved in cytomegalic infection in humans hence, genes from other species was removed but genes of influenza virus is in the network because patient’s infected with influenza have elevated level of genes which are found to be causative agents of cytomegalovirus. Network containing self-loops, duplicate edges were removed and gene-gene interaction network contains 13923 genes and 35714 interactions (Figure 2).
The main objective behind genetic interaction network is to understand the relationship between the genotypes and phenotypes of individuals which could be important key for identifying genetic variants responsible for disease. Generally, unexpected phenotypic changes will occurred when two or more genetic variants will interact with each other. Hence, genetic interaction network will help to map affected gene and their related biological process or pathways to develop successful therapeutic strategies further.
Analysis using CluePedia plugin
Although it was large gene interaction network and the research aimed to do functional analysis of gene dataset and this analysis was done through CluePedia plugin. Functional analysis helps to determine which gene is functional modules form list of genes of interest. CluePedia plugin helps to identify functionally participating group of genes in cytomegalic infection with their interaction type like expression, binding etc (Figure 3).
Analysis through ClueGO Plugin
47 genes found functionally enriched among 129 genes and with the help of ClueGO plugin further analysis was done. Go term analysis was performed through ClueGo plugin and for categorizing 47 genes into GO term parameters taken as defaulted.
Go term analysis was performed through ClueGO plugin and for categorizing 47 genes into GO term, some parameter was set. Kappa (ะบ) Statistics is used to examine interrater and intrarater reliability of data in relation to clinical diagnosis or classification and assessment finding. These data require to access specific reliability that’s why kappa statistics used. The range of possible values of kappa is from –1 to 1, though it usually falls between 0 and 1. Unity represents perfect agreement, indicating that the raters agree in their classification of every case. Zero indicates agreement no better than that expected by chance. A negative kappa would indicate agreement worse than that expected by chance [6].
The main aim of ontology analysis of functionally enriched genes is to know which gene upregulates and down regulates in certain biological process. ClueGO analysis performs automatically the calculation of the terms and groups significance. P-Value correction method is selected in ClueGO selection panel, then on the network and on the charts the corrected P-Value will be represented.
The terms and groups significance can be found in the ClueGo browser.
The chart showed in Figure 4; mark the level of the significance for terms and groups using:
1. **: if the term/group is over significant, P-Value <0.001.
2. *: if the term/group is significant, 0.001
3. . (Dot): 0.05
The below table shows biological process and name of genes involved in those biological process (Table 2).
Function | Groups | Group Genes |
---|---|---|
Cellular Senescence** | Group 1 | CDK2|CDK4|CDK6|E2F1|EP400|IL6|MAPK14|NFKB1|STAT3|TP53 |
Cellular responses to stress** | Group 6 | CDK2|CDK4|CDK6|E2F1|EP400|IL6|MAPK14|NFKB1|STAT3|TP53 |
Complement cascade** | Group 3 | CD55|CD59 |
ER-Phagosome pathway | Group 5 | HLA-G|TAP1 |
Extrinsic Pathway for Apoptosis** | Group 0 | CFLAR|TNF |
Immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell* | Group 2 | CAMK2B|HLA-G|ICAM1|LILRB1 |
Integrin cell surface interactions | None 0 | ICAM1|THBS1 |
Interferon alpha/beta signaling | None 1 | ADAR|EGR1|HLA-G |
Toll-Like Receptors Cascades** | Group 4 | IFI16|MAPK14|NFKB1|TLR2|TLR3|TLR9 |
Transcriptional Regulation of White Adipocyte Differentiation | None 2 | CDK4|NFKB1|TNF |
Table 2: The above table shows significant biological process founded for 47 genes.
According to previous studies HCMV infection could disrupt mucosal surfaces, predisposing the patient to superinfection, or it could cause alterations in humoral and cell-mediated immunity [7]. In ontology analysis the over-significant pathways were found are Cellular Senescence is a process in which aging is occurred in single cell at individual level and there is an arrest of cell cycle to encounter oncogenic stress and infected cell will eliminated. Cellular stress response is a reaction in which structure and function of macromolecules is changed due to fluctuations in extracellular conditions of cells. In Extrinsic Pathway for Apoptosis the extrinsic ligand which can cause harm is leads to death by binding to TNF receptor and
Toll-Like Receptors Cascades belong to a family of transmembrane proteins that can recognize and discriminate a diverse array of microbial antigens and also it plays important role in innate immunity system.
Somewhere these all over-significant process leads towards destruction of cell which can be oncogenic further and but in HCMV infection normal functions of all these pathways is disrupt primarily and afterwards infection can lead to chronic condition. Effective vaccines or drugs are not available for cytomegalo virus so by triggering these pathways and genes and their products which were affects the pathways successful therapeutic strategies will be developed.
The genetic interaction study of human cytomegalovirus was done using Cytoscape tool and its various plugins. This study focuses on building and analyzing the gene-gene interaction network for cytomegalovirus. Gene-gene interaction network was retrieve from Cytoscape web services and network contains 13923 nodes and 35714 edges of human gene and genes causing influenza infection. Functional analysis of HCMV genes found to spread disease was performed with the help of CluePedia plugin, a total of 47 genes were predicted in functional analysis. Ontology analysis of those 47 genes was performed through ClueGO plugin to predict significant biological processes.
I like to put my sincere acknowledgements to DBT for providing us such platform and financial assistance. And my sincere thanks to BIF Center at D.G.P.G. College, Kanpur and all staff members there.