Version 1
: Received: 14 May 2021 / Approved: 17 May 2021 / Online: 17 May 2021 (16:56:57 CEST)
How to cite:
Swain, A.; Milzman, J.; Fagan, W.F. Exploring patterns in modularity of protein interaction networks across the tree of life using Spectral Entropy. Preprints2021, 2021050394. https://doi.org/10.20944/preprints202105.0394.v1
Swain, A.; Milzman, J.; Fagan, W.F. Exploring patterns in modularity of protein interaction networks across the tree of life using Spectral Entropy. Preprints 2021, 2021050394. https://doi.org/10.20944/preprints202105.0394.v1
Swain, A.; Milzman, J.; Fagan, W.F. Exploring patterns in modularity of protein interaction networks across the tree of life using Spectral Entropy. Preprints2021, 2021050394. https://doi.org/10.20944/preprints202105.0394.v1
APA Style
Swain, A., Milzman, J., & Fagan, W.F. (2021). Exploring patterns in modularity of protein interaction networks across the tree of life using Spectral Entropy. Preprints. https://doi.org/10.20944/preprints202105.0394.v1
Chicago/Turabian Style
Swain, A., Jesse Milzman and William F Fagan. 2021 "Exploring patterns in modularity of protein interaction networks across the tree of life using Spectral Entropy" Preprints. https://doi.org/10.20944/preprints202105.0394.v1
Abstract
Modularity and organizational hierarchy are important concepts in understanding the structure and evolution of interactions in complex biological systems. In this work, we introduce and use a spectral characterization measure (Spectral Entropy) to quantify modularity in protein-to-protein interaction (PPI) networks in species across the tree of life. We evaluated the relation between the size of a PPI network and its (Spectral Entropy-based) modularity, and found a sigmoidal response between the two. We also found significant differences in the distribution of Spectral Entropy values among the three domains of life (Bacteria, Archaea, Eukaryotes). To explore further correlations with biological traits, we focused solely on bacterial PPI networks, which are the most numerous among the three domains and had associated trait metadata, and investigated how modularity impacts or is impacted by growth, aerobicity, selection and location on the tree of life. We found no relation between maximal growth rate and Spectral Entropy, but a strong dependence between G-C content (a proxy for selection) and Spectral Entropy. We also discovered that Spectral Entropy is negatively affected by phylogenetic placement (evolutionary distance from the last universal common ancestor). The general nature of the Spectral Entropy measure of hierarchical modularity in networks suggests that it will be useful in other settings where structural properties of real-world networks are being compared.
Keywords
Modularity; Protein-to-protein interaction networks; Spectral characterization; Tree of life
Subject
Biology and Life Sciences, Biophysics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
