A Network-Based Analysis of Proteins Involved In Hypoxia Stress and Identification of Leader Proteins

Hypoxia arises in many pathophysiological conditions like hypertension, cancers, pre-natal birth and environmental conditions like high altitude, deep sea diving etc. The multivariate nature of this stress makes to it difficult to predict accurately susceptibility and adaptability to hypoxia. A large amount of expression data under hypoxic stress is generated and available in the public domain. However, there have been no systematic efforts to identify the key proteins and their molecular connectivity. In the present study, the proteins whose expressions are regulated under hypoxic-stress were identified and an interaction network was built. The interactions were given a significance score using the STRING database. For each protein, the scores were added up to obtain a weighted number of links (WNL) and thereafter the proteins were clustered using k-means according to this parameter. The highest scoring proteins were termed as “leader proteins”. 43 leader proteins were identified which may play a critical role in pathophysiology and prognosis of hypoxic-stress response. These 43 leader proteins were enriched in four biological pathways namely Transcription factors and Cell cycle control; Proteasomal machinery; Signalling pathways and Ribosomal machinery. The enriched pathways shed light on the molecular response to hypoxia response and knowledge of the key regulatory interactions and further planning for targeted experimentations. Gene ontology analysis was also carried out using Webgalst software which identified various biological pathways modulated under hypoxic stress. In principle, the methodology described here may be implemented to understand the molecular mechanisms in other multivariate disorders also.