Multibiomarker interactions to diagnose and follow-up chronic exposure of a marine crustacean to Hazardous and Noxious Substances (HNS)

Integrated compensatory responses of physiological systems towards homeostasis are generally overlooked when it comes to analysing alterations in biochemical parameters indicative of such processes. Here an hypothesis-driven multivariate analysis accounting for interactive multibiomarker responses was used to investigate effects of long-term exposure of Carcinus maenas to Hazardous and Noxious Substances (HNS). Adult male crabs were exposed to low and high post-spill levels of acrylonitrile (ACN) or aniline (ANL) for 21d. Bioaccumulation, feeding behaviour, and biomarkers related to mode-of-action (MoA) (detoxification, neurotransmission and energy production) were evaluated over time. Distinct temporal patterns of response to low and high exposure concentrations were depicted, with a main set of interactive multibiomarker predictors identified for each HNS (five for ACN and three for ANL), useful to follow coupled evolvement of biomarker responses. ACN caused peripheral neurotoxic effects coupled with enhanced biotransformation and significant oxidative damage particularly relevant in gills. ANL elicited alterations in central neurotransmission affecting ventilation coupled with very low levels of oxidative damage in gills. Results indicate chronic toxicity data are determinant to improve HNS hazard assessment if the aim is to obtain reliable risk calculations, and develop effective predictive models avoiding overestimation but sufficiently protective. Accounting for multibiomarker interactions brought otherwise overlooked information about C. maenas responses and MoA of ACN and ANL. Accounting for biomarker interactions drastically improves the quality of the model to diagnose toxic effects. © 2018 Elsevier

This article is a result of INNOVMAR - Innovation and Sustainability in the Management and Exploitation of Marine Resources (reference NORTE-01-0145-FEDER-000035), ECOSERVICES, supported by NORTE2020, PORTUGAL2020 Partnership Agreement, through ERDF . This work was partially funded by Strategic Funding UID/Multi/04423/2013 through FCT and ERDF .