Columba livia as a sentinel species for the assessment of urban air genotoxicity.

This study explored the comet assay as a possible tool to assess genotoxicity in erythrocytes of Columba livia to detect genotoxic effects induced by exposure to urban air pollution. Fieldwork was conducted between June 2004 and June 2005 in the city of Milan, Italy, by sampling pigeons in different areas almost twice a week. Six air contaminants-CO, PM10, NO(2), O(3) (ozone), SO(2), and C6H6-plus polycyclic aromatic hydrocarbons (PAHs) in fine particles, temperature, and ultraviolet index, were considered. Genotoxicity levels, expressed as %DNA migrated, tail moment, and damage index (DI), were always higher in wild pigeons than in pigeons living indoors (controls). Animals exposed to urban air showed significant differences from season to season, and the genotoxic parameters presented the highest values in summer (45.30% +/- 1.40% %DNA migrated, 12.73 +/- 0.80 tail moment, and 22.30 +/- 0.15 x DI x 10(-1)); regression analyses showed a positive relation between DI and O(3) concentrations (P < 0.001). The use of the comet assay DI parameter as a rapid assessment of incipient genotoxic risk by pollution, as measured in C. livia living in urban areas, is also discussed.

Soil genotoxicity assessment: a new stategy based on biomolecular tools and plant bioindicators.

The setting up of efficient early warning systems is a challenge to research for preventing environmental alteration and human disease. In this paper, we report the development and the field application of a new biomonitoring methodology for assessing soil genotoxicity. In the first part, the use of amplified fragment length polymorphism and flow cytometry techniques to detect DNA damage induced by soils artificially contaminated with heavy metals as potentially genotoxic compounds is explained. Results show that the combination of the two techniques leads to efficient detection of the sublethal genotoxic effect induced in the plant bioindicator by contaminated soil. By contrast, the classic mortality, root, and shoot growth vegetative endpoints prove inappropriate for assessing soil genotoxicity because, although they cause genotoxic damage, some heavy metals do not affect sentinel plant development negatively. The statistical elaboration of the data obtained led to the development of a statistical predictive model which differentiates four different levels of soil genotoxic pollution and can be used everywhere. The second part deals with the application of the biomonitoring protocol in the genotoxic assessment of two areas surrounding a steelworks in northern Italy and the effectiveness of this methodology. In this particular case, in these areas, the predictive model reveals a pollution level strictly correlated to the heavy metal concentrations revealed by traditional chemical analysis.