Citation

Moore MN. Mar. Environ. Res. 2010; 69(Suppl): S37-S41.

Affiliation

Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL1 3DH, UK.

Copyright

(Copyright © 2010, Elsevier Publishing)

DOI

10.1016/j.marenvres.2009.11.006

PMID

20005567

Abstract

Physiological function emerges from complex biomolecular interactions (e.g., protein-protein) and control mechanisms that enable animals to respond and adapt to changes in their environment. Cell injury and pathology induced by pollutants and other stressors appears to involve the gradual and progressive dysfunction of complex biomolecular interactions, resulting in loss of integrated physiological interactions and homeostasis leading to a reduced capacity to respond effectively to stress. In order to determine whether complexity can be used as an indicator of health, the hypothesis that pathology involves a loss of biological complexity has been tested using a generic physiological interaction network. System complexity was evaluated using Eulerian cycles and connectedness (connectance%) for estimating topological complexity and application of network theory (i.e., analysis of scale-free networks and network diameter). The complexity of the whole system increases when sub-systems, such as detoxication and anti-oxidant protective processes, augmented autophagy, protein degradation and induction of stress proteins, are up-regulated and start to interact significantly as part of a response to low-level stress (i.e., biphasic or hormetic response). However, with increasing severity of stress, cell injury and higher-level functional impairment lead to physiological dysfunction and breakdown of the whole interaction network with consequent loss of complexity. In summary for the model described here, network and graph theory appear to provide a mathematical formalism that can facilitate the system-level interpretation of health and dysfunction in living cells.

Language: en