The Potential of Ecotoxicoproteomics in Environmental Monitoring: Biomarker Profiling in Mussel Plasma Using Proteinchip Array Technology

• Published in: Journal of Toxicology and Environmental Health, Part A Vol. 69; no. 1-2; pp. 77 - 96
• Main Authors: Bjørnstad, A., Larsen, B. K., Skadsheim, A., Jones, M. B., Andersen, O. K.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01.01.2006
• Subjects: Animals; Biomarkers - blood; ecotoxicology; Environmental Monitoring; Female; Male; Mytilus edulis; Mytilus edulis - drug effects; Mytilus edulis - metabolism; oil; Petroleum - toxicity; Phenols - toxicity; Polycyclic Aromatic Hydrocarbons - toxicity; produced water; Protein Array Analysis; Proteins - analysis; Proteomics; SELDI TOF MS; Toxicogenetics; Water Pollutants, Chemical - toxicity
• ISSN: 1528-7394; 1087-2620
• DOI: 10.1080/15287390500259277

New global technologies, allowing simultaneous analysis of thousands of genes, proteins, and metabolites (so-called "omics" technologies), are being adopted rapidly by industry, academia, and regulatory agencies. This study evaluated the potential of proteomics in ecotoxicological research (i.e., ecotoxicoproteomics). Filter-feeding mussels (Mytilus edulis) were exposed continuously for 3 wk to oil, or oil spiked with alkylphenols and extra polycyclic aromatic hydrocarbons. The influence of chronic exposure on mussel plasma protein expression was investigated utilizing ProteinChip array technology in combination with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF MS). Results indicated that exposure to spiked oil had a more significant effect on protein expression in mussels than oil alone. In total, 83 mass peaks (intact or modified proteins/peptides) were significantly altered by spiked oil, while 49 were altered by oil. In exposed organisms, the majority of peaks were upregulated compared to controls (i.e., 69% in oil and 71% in spiked oil). Some peaks (32 in total) were affected by both treatments; however, the degree of response was higher in the spiked oil group for 25 of the 32 commonly affected features. Additionally, certain peaks revealed exposure- or gender-specific responses. Multivariate analysis with regression tree-based methods detected protein patterns associated with exposure that correctly classified masked samples with 90-95% accuracy. Similarly, 92% of females and 85% of males were correctly classified (independent of exposure). Results indicate that proteomics have the potential to make a valuable contribution to environmental monitoring and risk assessment.