It is well established that the epigenetic interplay between Epstein–Barr Virus (EBV)
and the host contributes to the pathogenesis of EBV-related diseases 1], 2]. Previous studies have revealed that EBV latency in B-cells leads to the epigenetic
silencing of the BCL2-Like 11 apoptosis facilitator (BIM) 3], 4]. This study presents a bioinformatic analysis towards the identification and functional
prediction of BIM interacting partners so as to indicate new, potential host targets
of EBV. The gene network of BIM was constructed by interrogating the following three
databases: Biogrid (http://thebiogrid.org), String (http://string-db.org) and GeneMania (http://www.genemania.org). The Biogrid database is a repository of genetic and protein–protein interactions
that are curated from the primary biomedical literature for all major model organism
species 5]. String is a database of known and predicted protein interactions including both
direct (physical), and indirect (functional) associations 6]. GeneMania is a prediction server that generates hypotheses about gene function,
analyzes gene lists and prioritizes genes for functional assays 7]. Subsequently, the Human Gene Compendium-GeneCards (http://www.genecards.org) was used in order to assess the description of the retrieved genes. GeneCards is
an integrated database of human genes that provides concise genomic related information,
on all known and predicted human genes 8]. BIM interactors that were found in all three databases were then entered as a list
in the GeneCodis3 database (http://genecodis.cnb.csic.es/) for functional enrichment analysis of Gene Ontology (GO) annotations relative to
cellular pathways. GeneCodis is a tool for modular and singular enrichment analysis
oriented to integrate information from different sources 9]. Annotations selected were KEGG and PANTHER pathways. The p values were obtained through Hypergeometric analysis corrected by the False Discovery
Ratio (FDR) method. The option of high confidence/no more than ten interactors was
selected in the String database so as to increase the level of certainty.
Fifty-nine unique BIM interactors were identified. Seven of these interactors (MCL1:
myeloid cell leukemia 1; BCL2L1: BCL2-like 1; BCL2: B cell CLL/lymphoma 2; DYNLL1:
dynein, light chain, LC8-type 1; BCL2L2: BCL2-like 2; MAPK8: mitogen-activated protein
kinase 8; BAX: BCL2-associated X protein) appeared in all three databases and were
further subjected to functional analysis as the level of confidence for the common
genes is much more significant. The modular enrichment analysis identified: (1) pathways
related to cancer including apoptosis, (2) pathways related to Amyotrophic Lateral
Sclerosis (ALS), and (3) pathways related to other infectious diseases like tuberculosis
and toxoplasmosis (Table 1). The singular enrichment analysis of KEGG and PANTHER pathways highlighted: (1)
pathways involved in cancer as JAK-STAT and Wnt signalling pathways, (2) pathways
related to neurodegenerative disorders [like Huntington’s disease (HD) Parkinson disease
(PD), Alzheimer disease (AD) and ALS], (3) pathways involved in infectious diseases
like epithelial cell signalling in Escherichia coli infection, Chagas disease, Hepatitis C and prion diseases (results not shown).
Table 1. Results of the modular enrichment analysis in the GeneCodis3 database
EBV is a known oncogenic virus associated with 1Â % of cancers worldwide 10]. The interactions of EBV with members of the Bcl-2 family like BAX, BCL2, BCL2L1,
BCL2L2 and MCL1 in human tumor cells, have been extensively reviewed in Fu et al.
11]. Thus, the prediction that the BIM interactome is involved in cancer pathways was
not surprising. The main finding of this study is the indication that several BIM
interactors participate in pathways related to neurodegenerative disorders. In such
diseases, like AD, PD, ALS and—to a less extent—HD, many studies have highlighted
the importance of the immune system and the involvement of neuroinflammation 12]. It has been suggested that the adaptive immune response to EBV represents the key
initiating event in PD 13]. Recently, a study has reported on a high level of octapeptide matching between 7
viruses (including EBV), and human brain antigens that, when altered, have been specifically
associated with neuropathologies such as ALS, HD and PD 14]. Another important finding arising from the ontological analysis is the prediction
that the BIM interactome participates in pathways associated with other infectious
agents. The cooperative contribution of HIV, malaria and EBV in lymphomagenesis has
long been established while the possibility of synergy between EBV and Helicobacter pylori in the pathogenesis of gastric carcinomas has recently begun to unfold 15]. Any possible association of EBV with other infectious diseases revealed by the functional
analysis remains to be studied.
Cumulatively, by using contemporary bioinformatic tools this study has demonstrated
that the BIM regulatory network consists of 59 unique genes that could be targeted
by EBV. Furthermore, it has predicted that several BIM interactors have a central
role in pathways associated with neurodegenerative disorders and infectious diseases.
The BIM interactome warrants further study, in terms of clinical research, with respect
to its interplay with EBV.