Characterization of microbial communities from coastal waters using microarrays

Molecular methods, including DNA probes, were used to identify and enumerate pathogenic Vibrio species in the Chesapeake Bay; our data indicated that Vibrio vulnificus exhibits seasonal fluctuations in number. Our work included a characterization of total microbial communities from the Bay; development of microarrays that identify and quantify the diversity of those communities; and observation of temporal changes in those communities. To identify members of the microbial community, we amplified the 16S rDNA gene from community DNA isolated from a biofilm sample collected from the Chesapeake Bay in February, 2000. The resultant 75 sequences were 95% or more similar to 7 species including two recently described Shewanella species, baltica and frigidimarina, that have not been previously isolated from the Chesapeake. When the genera of bacteria from biofilm after culturing are compared to those detected by subcloning amplified 16S fragments from community DNA, the cultured sample exhibited a strong bias. In oysters collected in February, the most common bacteria were previously unknown. Based on our 16S findings, we are developing microarrays to detect these and other microbial species in these estuarine communities. The microarrays will detect each species using four distinct loci, with the multiple loci serving as an internal control. The accuracy of the microarray will be measured using sentinel species such as Aeromonas species, Escherichia coli, and Vibrio vulnificus. Using microarrays, it should be possible to determine the annual fluctuations of bacterial species (culturable and non-culturable, pathogenic and non-pathogenic). The data may be applied to understanding patterns of environmental change; assessing the health of the Bay; and evaluating the risk of human illness associated with exposure to and ingestion of water and shellfish.     

Modification of the biochemical pathways of plants induced by ozone: what are the varied routes to change?

When plants are observed under a low dose of ozone, some physiological and metabolic shifts occur. Barring extreme injury such as tissue damage or stomata closure, most of these disruptive changes are likely to have been initiated at the level of gene expression. The belief is oxidative products formed in ozone exposed leaves, e.g. hydrogen peroxide, are responsible for much of the biochemical adjustments. The first line of defense is a range of antioxidants, such as ascorbate and glutathione, but if this defense is overwhelmed, subsequent actions occur, similar to systemic acquired resistance or general wounding. Yet there are seemingly unrelated metabolic responses which are also triggered, such as early senescence. We discuss here the current understanding of gene control and signal transduction/control in order to increase our comprehension of how ozone alters the basic metabolism of plants and how plants counteract or cope with ozone.     

Effluent impact assessment using microarray-based analysis in common carp: a systems toxicology approach

Effluents are a main source of direct and continuous input of pollutants to the aquatic environment, and can cause ecotoxicological effects at different levels of biological organization. Since gene expression responses represent the primary interaction site between environmental contaminants and biota, they provide essential clues to understand how chemical exposure can affect organismal health. The aim of the present study was to investigate the applicability of a microarray approach for unraveling modes of action of whole effluent toxicity and impact assessment. A chronic toxicity test with common carp (Cyprinus carpio) was conducted where fish were exposed to a control and 100% effluent for 21 days under flow-through conditions. Microarray analysis revealed that effluent treatment mainly affected molecular pathways associated with the energy balance of the fish, including changes in carbohydrate and lipid metabolism, as well as digestive enzyme activity. These gene expression responses were in clear agreement with, and provided additional mechanistic information on various cellular and higher level effects observed for the same effluent. Our results demonstrate the benefit of toxicogenomic tools in a “systems toxicology” approach, involving the integration of adverse effects of chemicals and stressors across multiple levels of biological complexity.