MEPS 156:141-150 (1997)  -  doi:10.3354/meps156141

Metal bioavailability assessment in 'mussel-watch' programmes by automated image analysis of autometallographical black silver deposits (BSD) in digestive cell lysosomes

Manu Soto*, Ionan Marigómez

Biologia Zelularra Atala, Zoologi eta Animali Zelulen Dinamika Saila, Zientzi Fakultatea, Euskal Herriko Unibertsitatea, 644 P.K., E-48080 Bilbo, Basque Country, Spain

The extent of autometallographical black silver deposits (BSD) was quantified by automated image analysis in digestive lysosomes of the digestive gland of mussels collected from 2 estuaries of the coast of Biscay for 1 yr. Additionally, metal composition of digestive lysosomes was characterised by X-ray microprobe analysis. Zn levels were the most variable among the metals analysed by AAS (Cd, Cr, Cu, Ni, Zn, Pb, Fe). A logarithmic regression model explained the changes in volume density (VD) of BSD by changes in the Zn/shell-wt index recorded in mussels from different sites of the coast. Similar regression models were obtained between the VD of BSD and metal/shell-wt indices resulting from pooling the 7 metals (umol metal g-1 dry shell weight). In conclusion, metal bioavailability can be estimated by analysing the VD of BSD in the digestive lysosomes of sentinel mussels. This index may allow workers to discard chemical analysis of biological samples when low traces of metals are present in the tissues, since the method proposed herein provides a quick and cost-effective alternative to routine chemical analyses in biomonitoring programmes. Only when values of VD of BSD reach the plateau of the function would a more accurate chemical analysis be required. This approach does not require special facilities or specialised technicians and would reduce the time and cost of routine metal determination in water pollution monitoring programmes.


Field validation · Autometallography · Digestive lysosomes · Automated image analysis · AAS · Metal content · Correlation analysis · X-ray microanalysis · Metal pollution monitoring


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