Mixtures of environmental pollutants: effects on microorganisms and their activities in soils.

Soil is the ultimate sink for most contaminants and rarely has only a single contaminant. More than is generally acknowledge, environmental pollutants exist as mixtures (organic-organic, inorganic-inorganic, and organic-inorganic). It is much more difficult to study chemical mixtures than individual chemicals, especially in the complex soil environment. Similarly, understanding the toxicity of a chemical mixture on different microbial species is much more complex, time consuming and expensive, because multiple testing designs are needed for an increased array of variables. Therefore, until now, scientific enquiries worldwide have extensively addressed the effects of only individual pollutants toward nontarget microorganisms. In this review, we emphasize the present status of research on (i) the environmental occurrence of pollutant mixtures; (ii) the interactions between pollutant mixtures and ecologically beneficial microorganisms; and (iii) the impact of such interactions on environmental quality. We also address the limitations of traditional cultivation based methods for monitoring the effects of pollutant mixtures on microorganisms. Long-term monitoring of the effects of pollutant mixtures on microorganisms, particularly in soil and aquatic ecosystems, has received little attention. Microbial communities that can degrade or can degrade or can develop tolerance to, or are inhibited by chemical mixtures greatly contribute to resilience and resistance in soil environments. We also stress in this review the important emerging trend associated with the employment of molecular methods for establishing the effects of pollutant mixtures on microbial communities. There is currently a lack of sufficient cogent toxicological data on chemical mixtures for making informed decision making in risk assessment by regulators. Therefore, not only more toxicology information on mixtures is needed but also there is an urgent need to generate sufficient, suitable, and long-term modeling data that have higher predictability when assessing pollutant mixture effects on microorganisms. Such data would improve risk assessment at contaminated sites and would help devise more effective bioremediation strategies.