Protein-protein interaction network of E. coli K-12 has significant high-dimensional cavities: new insights from algebraic topological studies.
FEBS Open Bio
; 12(7): 1406-1418, 2022 07.
Article
em En
| MEDLINE
| ID: mdl-35560988
ABSTRACT
As a model system, Escherichia coli has been used to study various life processes. A dramatic paradigm shift has occurred in recent years, with the study of single proteins moving toward the study of dynamically interacting proteins, especially protein-protein interaction (PPI) networks. However, despite the importance of PPI networks, little is known about the intrinsic nature of the network structure, especially high-dimensional topological properties. By introducing general hypergeometric distribution, we reconstruct a statistically reliable combined PPI network of E. coli (E. coli-PPI-Network) from several datasets. Unlike traditional graph analysis, algebraic topology was introduced to analyze the topological structures of the E. coli-PPI-Network, including high-dimensional cavities and cycles. Random networks with the same node and edge number (RandomNet) or scale-free networks with the same degree distribution (RandomNet-SameDD) were produced as controls. We discovered that the E. coli-PPI-Network had special algebraic typological structures, exhibiting more high-dimensional cavities and cycles, compared to RandomNets or, importantly, RandomNet-SameDD. Based on these results, we defined degree of involved q-dimensional cycles of proteins (q-DCprotein ) in the network, a novel concept that relies on the integral structure of the network and is different from traditional node degree or hubs. Finally, top proteins ranked by their 1-DCprotein were identified (such as gmhB, rpoA, rplB, rpsF and yfgB). In conclusion, by introducing mathematical and computer technologies, we discovered novel algebraic topological properties of the E. coli-PPI-Network, which has special high-dimensional cavities and cycles, and thereby revealed certain intrinsic rules of information flow underlining bacteria biology.
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Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
3_ND
Base de dados:
MEDLINE
Assunto principal:
Mapeamento de Interação de Proteínas
/
Mapas de Interação de Proteínas
Idioma:
En
Revista:
FEBS Open Bio
Ano de publicação:
2022
Tipo de documento:
Article