Robustness and lethality in multilayer biological molecular networks
(2020) In Nature Communications 11(1).- Abstract
Robustness is a prominent feature of most biological systems. Most previous related studies have been focused on homogeneous molecular networks. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, a protein–protein interaction layer, and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall system’s robustness, and find that influential genes are enriched in essential and cancer genes. We show... (More)
Robustness is a prominent feature of most biological systems. Most previous related studies have been focused on homogeneous molecular networks. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, a protein–protein interaction layer, and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall system’s robustness, and find that influential genes are enriched in essential and cancer genes. We show that the proposed mechanism predicts a higher vulnerability of the metabolic layer to perturbations applied to genes associated with metabolic diseases. Furthermore, we find that the real network is comparably or more robust than expected in multiple random realizations. Finally, we analytically derive the expected robustness of multilayer biological networks starting from the degree distributions within and between layers. These results provide insights into the non-trivial dynamics occurring in the cell after a genetic perturbation is applied, confirming the importance of including the coupling between different layers of interaction in models of complex biological systems.
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- author
- Liu, Xueming ; Maiorino, Enrico ; Halu, Arda ; Glass, Kimberly ; Prasad, Rashmi B. LU ; Loscalzo, Joseph ; Gao, Jianxi and Sharma, Amitabh LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Communications
- volume
- 11
- issue
- 1
- article number
- 6043
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85096654044
- pmid:33247151
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-020-19841-3
- language
- English
- LU publication?
- yes
- id
- 93d4378c-3760-4278-bc2f-0911ea1e0da0
- date added to LUP
- 2020-12-03 12:51:01
- date last changed
- 2024-04-17 20:00:55
@article{93d4378c-3760-4278-bc2f-0911ea1e0da0,
abstract = {{<p>Robustness is a prominent feature of most biological systems. Most previous related studies have been focused on homogeneous molecular networks. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, a protein–protein interaction layer, and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall system’s robustness, and find that influential genes are enriched in essential and cancer genes. We show that the proposed mechanism predicts a higher vulnerability of the metabolic layer to perturbations applied to genes associated with metabolic diseases. Furthermore, we find that the real network is comparably or more robust than expected in multiple random realizations. Finally, we analytically derive the expected robustness of multilayer biological networks starting from the degree distributions within and between layers. These results provide insights into the non-trivial dynamics occurring in the cell after a genetic perturbation is applied, confirming the importance of including the coupling between different layers of interaction in models of complex biological systems.</p>}},
author = {{Liu, Xueming and Maiorino, Enrico and Halu, Arda and Glass, Kimberly and Prasad, Rashmi B. and Loscalzo, Joseph and Gao, Jianxi and Sharma, Amitabh}},
issn = {{2041-1723}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Nature Communications}},
title = {{Robustness and lethality in multilayer biological molecular networks}},
url = {{http://dx.doi.org/10.1038/s41467-020-19841-3}},
doi = {{10.1038/s41467-020-19841-3}},
volume = {{11}},
year = {{2020}},
}