A computational exploration of resilience and evolvability of protein–protein interaction networks

Klein, B, Holmér, L, Smith, KM ORCID logoORCID: https://orcid.org/0000-0002-4615-9020, Johnson, MM, Swain, A, Stolp, L, Teufel, AI and Kleppe, AS, 2021. A computational exploration of resilience and evolvability of protein–protein interaction networks. Communications Biology, 4: 1352. ISSN 2399-3642

[thumbnail of 1502606_Smith.pdf]
Preview
Text
1502606_Smith.pdf - Published version

Download (3MB) | Preview

Abstract

Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions , and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype's PPI network's resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks' resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms-random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.

Item Type: Journal article
Publication Title: Communications Biology
Creators: Klein, B., Holmér, L., Smith, K.M., Johnson, M.M., Swain, A., Stolp, L., Teufel, A.I. and Kleppe, A.S.
Publisher: Springer
Date: 2 December 2021
Volume: 4
ISSN: 2399-3642
Identifiers:
Number
Type
10.1038/s42003-021-02867-8
DOI
1502606
Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 10 Dec 2021 11:51
Last Modified: 10 Dec 2021 11:53
URI: https://irep.ntu.ac.uk/id/eprint/45103

Actions (login required)

Edit View Edit View

Statistics

Views

Views per month over past year

Downloads

Downloads per month over past year