Heavy metals are commonly associated with the generation of reactive oxygen species (ROS), which may cause oxidative damage to several cellular macromolecules and organelles. In an attempt to correlate biomarker responses to oxidative stress, caged mussels (Mytilus galloprovincialis) were exposed for 30 days in a relatively clean site and two areas (Stations 1 and 2) unevenly polluted by heavy metals in Gulf of Patras (Greece). Three periods of caging were: one in winter, the second in spring, and the third in autumn. Heavy metal content was determined in digestive glands of the exposed mussels as a measure of metal pollution, metallothionein content as an adaptive and detoxifying index, lysosomal membrane stability as a biomarker of general stress, superoxide radical production and lipid peroxidation as indicators of oxidative stress, and micronucleus frequency in gill cells as an index of chromosomal damage. Considering that protein-synthesizing machinery is one of the candidate targets for ROS, the in vivo activity of ribosomes in digestive glands was also tested. Compared with the reference samples, mussels transplanted to Station 1 showed increased levels of heavy metals and metallothionein in digestive glands, lower lysosomal membrane stability, higher values in oxidative stress indices, reduced activity of ribosomes, and increased chromosomal damage in gill cells. In addition, run-off ribosomes isolated from mussels transplanted to Station 1 were less efficient at initiating protein synthesis in a cell-free system than those from mussels in the reference site. Mussels transplanted to Station 2 exhibited similar but less pronounced responses. Statistical analysis revealed a strong positive correlation of ribosomal activity with lysosomal membrane stability, as well as a significant negative correlation with the oxidative stress indices, metallothionein content, micronucleus frequency, and the digestive gland content in Cr, Cu and Mn. Integration of all the measured biomarker responses into one general "stress index" demonstrated a clear distinction between the sampling sites, allowing classification along a pollution gradient (reference site<Station 2<Station 1), independently from the season. Moreover, this analysis allowed us to compare responses between sampling campaigns and showed that the biomarker responses show best integration in winter. It was also evident that climatic or metabolic changes could modulate bioavailability of pollutants and priming of cellular defence processes.