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Mar Environ Res. 2006 Apr;61(3):278-304. Epub 2005 Dec 15.

Environmental prognostics: an integrated model supporting lysosomal stress responses as predictive biomarkers of animal health status.

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


The potential prognostic use of lysosomal reactions to environmental pollutants is explored in relation to predicting animal health in marine mussels, based on diagnostic biomarker data. Cellular lysosomes are already known to accumulate many metals and organic xenobiotics and the lysosomal accumulation of the carcinogenic polycyclic aromatic hydrocarbon 3-methylcholanthrene (3-MC) is demonstrated here in the hepatopancreatic digestive cells and ovarian oocytes of the blue mussel. Lysosomal membrane integrity or stability appears to be a generic indicator of cellular well-being in eukaryotes; and in bivalve molluscs it is correlated with total oxygen and nitrogen radical scavenging capacity (TOSC), protein synthesis, scope for growth and larval viability; and inversely correlated with DNA damage (micronuclei), as well as lysosomal swelling (volume density), lipidosis and lipofuscinosis, which are all characteristic of failed or incomplete autophagy. Integration of multiple biomarker data is achieved using multivariate statistics and then mapped onto "health status space" by using lysosomal membrane stability as a measure of cellular well-being. This is viewed as a crucial step towards the derivation of explanatory frameworks for prediction of pollutant impact on animal health; and has facilitated the development of a conceptual mechanistic model linking lysosomal damage and autophagic dysfunction with injury to cells, tissues and the whole animal. This model has also complemented the creation and use of a cell-based bioenergetic computational model of molluscan hepatopancreatic cells that simulates lysosomal and cellular reactions to pollutants. More speculatively, the use of coupled empirical measurements of biomarker reactions and modelling is proposed as a practical approach to the development of an operational toolbox for predicting the health of the environment.

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