Cargando…

Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection

Complex protein networks underlie any cellular function. Certain proteins play a pivotal role in many network configurations, disruption of whose expression proves fatal to the cell. An efficient method to tease out such key proteins in a network is still unavailable. Here, we used graph-theoretic m...

Descripción completa

Detalles Bibliográficos
Autores principales: Ghosh, Sourish, Kumar, G. Vinodh, Basu, Anirban, Banerjee, Arpan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585883/
https://www.ncbi.nlm.nih.gov/pubmed/26404759
http://dx.doi.org/10.1038/srep14438
_version_ 1782392298268524544
author Ghosh, Sourish
Kumar, G. Vinodh
Basu, Anirban
Banerjee, Arpan
author_facet Ghosh, Sourish
Kumar, G. Vinodh
Basu, Anirban
Banerjee, Arpan
author_sort Ghosh, Sourish
collection PubMed
description Complex protein networks underlie any cellular function. Certain proteins play a pivotal role in many network configurations, disruption of whose expression proves fatal to the cell. An efficient method to tease out such key proteins in a network is still unavailable. Here, we used graph-theoretic measures on protein-protein interaction data (interactome) to extract biophysically relevant information about individual protein regulation and network properties such as formation of function specific modules (sub-networks) of proteins. We took 5 major proteins that are involved in neuronal apoptosis post Chandipura Virus (CHPV) infection as seed proteins in a database to create a meta-network of immediately interacting proteins (1(st) order network). Graph theoretic measures were employed to rank the proteins in terms of their connectivity and the degree upto which they can be organized into smaller modules (hubs). We repeated the analysis on 2(nd) order interactome that includes proteins connected directly with proteins of 1(st) order. FADD and Casp-3 were connected maximally to other proteins in both analyses, thus indicating their importance in neuronal apoptosis. Thus, our analysis provides a blueprint for the detection and validation of protein networks disrupted by viral infections.
format Online
Article
Text
id pubmed-4585883
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-45858832015-09-30 Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection Ghosh, Sourish Kumar, G. Vinodh Basu, Anirban Banerjee, Arpan Sci Rep Article Complex protein networks underlie any cellular function. Certain proteins play a pivotal role in many network configurations, disruption of whose expression proves fatal to the cell. An efficient method to tease out such key proteins in a network is still unavailable. Here, we used graph-theoretic measures on protein-protein interaction data (interactome) to extract biophysically relevant information about individual protein regulation and network properties such as formation of function specific modules (sub-networks) of proteins. We took 5 major proteins that are involved in neuronal apoptosis post Chandipura Virus (CHPV) infection as seed proteins in a database to create a meta-network of immediately interacting proteins (1(st) order network). Graph theoretic measures were employed to rank the proteins in terms of their connectivity and the degree upto which they can be organized into smaller modules (hubs). We repeated the analysis on 2(nd) order interactome that includes proteins connected directly with proteins of 1(st) order. FADD and Casp-3 were connected maximally to other proteins in both analyses, thus indicating their importance in neuronal apoptosis. Thus, our analysis provides a blueprint for the detection and validation of protein networks disrupted by viral infections. Nature Publishing Group 2015-09-25 /pmc/articles/PMC4585883/ /pubmed/26404759 http://dx.doi.org/10.1038/srep14438 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Ghosh, Sourish
Kumar, G. Vinodh
Basu, Anirban
Banerjee, Arpan
Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title_full Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title_fullStr Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title_full_unstemmed Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title_short Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
title_sort graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585883/
https://www.ncbi.nlm.nih.gov/pubmed/26404759
http://dx.doi.org/10.1038/srep14438
work_keys_str_mv AT ghoshsourish graphtheoreticnetworkanalysisrevealsproteinpathwaysunderlyingcelldeathfollowingneurotropicviralinfection
AT kumargvinodh graphtheoreticnetworkanalysisrevealsproteinpathwaysunderlyingcelldeathfollowingneurotropicviralinfection
AT basuanirban graphtheoreticnetworkanalysisrevealsproteinpathwaysunderlyingcelldeathfollowingneurotropicviralinfection
AT banerjeearpan graphtheoreticnetworkanalysisrevealsproteinpathwaysunderlyingcelldeathfollowingneurotropicviralinfection