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Systematic Analysis of Protein Interaction Network Associated with Azoospermia.

ABSTRACT: Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Using Online Mendelian Inheritance in Man, the Human Protein Reference Database and Cytoscape, we created a novel network consisting of 209 protein nodes and 737 interactions. Mathematical analysis identified three proteins, ar, dazap2, and esr1, as hub nodes and a bottleneck protein within the network. We also identified new candidate genes, CREBBP and BCAR1, which may play a role in azoospermia. The gene ontology analysis suggests a genetic link between azoospermia and liver disease. The KEGG analysis also showed 45 statistically important pathways with 31 proteins associated with colorectal, pancreatic, chronic myeloid leukemia and prostate cancer. Two new genes and associated diseases are promising for further experimental validation.

SUBMITTER: Sabetian S

PROVIDER: S-EPMC5133857 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Systematic Analysis of Protein Interaction Network Associated with Azoospermia.

Sabetian Soudabeh S Shamsir Mohd Shahir MS

International journal of molecular sciences 20161110 11

Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Usin ...[more]

PMID: 27834916

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Project description:BackgroundInfectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.ResultsAs host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins' marker.ConclusionsDifferent centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens' favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.

Dataset Information

Systematic Analysis of Protein Interaction Network Associated with Azoospermia.

Publications

Systematic Analysis of Protein Interaction Network Associated with Azoospermia.

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