A computational exploration of resilience and evolvability of protein–protein interaction networks
Klein, Brennan and Holmér, Ludvig and Smith, Keith M. and Johnson, Mackenzie M. and Swain, Anshuman and Stolp, Laura and Teufel, Ashley I. and Kleppe, April S. (2021) A computational exploration of resilience and evolvability of protein–protein interaction networks. Communications Biology, 4. 1352. ISSN 2399-3642 (https://doi.org/10.1038/s42003-021-02867-8)
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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.
ORCID iDs
Klein, Brennan, Holmér, Ludvig, Smith, Keith M. ORCID: https://orcid.org/0000-0002-4615-9020, Johnson, Mackenzie M., Swain, Anshuman, Stolp, Laura, Teufel, Ashley I. and Kleppe, April S.;-
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Science > Natural history > GeneticsDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 15 Nov 2023 13:15 Last modified: 12 Dec 2024 15:07 URI: https://strathprints.strath.ac.uk/id/eprint/87331