Biomarkers in aquatic plants: selection and utility.
This review emphasizes the predictive ability, sensitivity and specificity of aquatic plant biomarkers as biomonitoring agents of exposure and effect. Biomarkers of exposure are those that provide functional measures of exposure that are characterized at a sub-organism level. Biomarkers of effect require causal linkages between the biomarker and effects, measured at higher levels of biological organization. With the exception of pathway specific metabolites, the biomarkers assessed in this review show variable sensitivity and predictive ability that is often confounded by variations in growth conditions, rendering them unsuitable as stand alone indicators of environmental stress. The use of gene expression for detecting pollution has been, and remains immature; this immaturity derives from inadequate knowledge on predictive ability, sensitivity and specificity. Moreover, the ability to the detect mode of action of unknown toxicants using gene expression is not as clear-cut as initially hypothesized. The principal patterns in gene expression is not as clear-cut as initially hypothesized. The principal patterns in gene expression are generally derived from stress induced genes, rather than on ones that respond to substances with known modes of action (Baerson et al. 2005). Future developments in multivariate statistics and chemometric methods that enhance pattern analyses in ways that could produce a "fingerprint", may improve methods for discovering modes of action of unknown toxicants. Pathway specific metabolites are unambiguous, sensitive, correlate well to growth effects, and are relatively unaffected by growth conditions. These traits make them excellent biomarkers under both field and laboratory conditions. Changes in metabolites precede visible growth effects; therefore, measuring changes in metabolite concentrations (Harring et al. 1998; Shaner et al. 2005). The metabolic phase I enzymes (primarily associated with P-450 activity) are non-specific biomarkers, and few studies relate them to growth parameters. P-450 activity both increases and decreases in response to chemical stress, often confounding interpretation of experimental results. Alternatively, phase II metabolic enzymes (e.g., glutathione S-transferases; GST's) appear to be sensitive biomarkers of exposure, and potentially effect. Some GST's are affected by growth factors, but others may only be induced by xenobiotics. Measuring xenobiotic-induced GST's, or their gene expression patterns, are good candidates for future biomarkers of the cumulative load of chemical stress, both in the laboratory and under field conditions. Phytochelatins respond to some but not all metal ions, and may therefore be used as biomarkers of exposure to identify the presence and bioavailability of ions to which they respond. However, more data on their specificity to, and interactions with growth factors, in more species are needed. The flavenoids are only represented by one heavy metal exposure study; therefore their use as biomarkers is currently difficult to judge. Stress proteins tend to be specific for toxicants that affect protein function. Growth factors are known to affect the level of stress proteins; hence, the use of stress proteins as biomarkers will be confined to experiments performed under controlled growth conditions, where they can be excellent indicators of proteotoxicity. Reactive oxygen species (ROS), ROS scavenging enzymes, changes in pigment content, photosynthesis and chlorophyll fluorescence are all affected by growth factors, particularly light and nutrient availability. Therefore, these biomarkers are best suited to investigate the mode of action of toxicants under controlled growth conditions. These biomarkers are sensitive to xenobiotic stressors that affect various processes in the photosynthetic apparatus, and can be used to diagnose which photosynthetic process or processes are primarily affected. Chlorophyll fluorescence is a non-destructive measure, and is thereby well suited for repeated measures of effect and recovery (Abbaspoor and Streibig 2005; Abbaspoor et al. 2006; Cedergreen et al. 2004). Bi-phasic responses (over time and with dose) are probably major sources of variation in sensitivity for many biomarkers. Metabolic enzymes, stress proteins, ROS and their corresponding scavenging enzymes increase in a time-frame and at doses in which plant cell damage is still repairable. However, when toxicity progresses to the point of cell damage, the concentration/activity of the biomarker either stabilizes or decreases. Examples of this response pattern are given in Lei et al. (2006); Pflugmacher et al. (2000b); Teisseire et al. (1998); and Teisseire and Guy (2000). Gene expression is also a time-dependent phenomenon varying several fold within a few hour. Therefore, bi-phasic response patterns make timing and dose-range, within which the biomarkers can be used as measures of both exposure and effect, extremely important. As a result, most biomarkers are best suited for situations in which the time and dose dependence of the biomarker, in the investigated species, are established. Notwithstanding the previously mentioned limitations, all assessed biomarkers provide valuable information on the physiological effects of specific stressors, and are valuable tools in the search for understanding xenobiotic modes of action. However, the future use of aquatic plant biomarkers will probably be confined to laboratory studies designed to assess toxicant modes of action, until further knowledge is gained regarding the time, dose and growth-factor dependence of biomarkers, in different species. No single biomarker is viable in gaining a comprehensive understanding of xenobiotic stress. Only through the concomitant measurement of a suite of appropriate biomarkers will our diagnostic capacity be enhanced and the field of ecotoxicology, as it relates to aquatic plants, advanced.
Brain
Richard A
RA
Center for Reservoir and Aquatic Systems Research, Department of Environmental Science, Baylor University, Waco, Texas 76798, USA.
Cedergreen
Nina
N
D000975:Antioxidants / Q000378:metabolism; D015415:Biomarkers / Q000032:analysis*; D004785:Environmental Pollutants / Q000633:toxicity*; D015870:Gene Expression / Q000187:drug effects; D018384:Oxidative Stress / Q000187:drug effects* / Q000235:genetics; D063245:Plant Development; D010944:Plants / Q000187:drug effects* / Q000235:genetics / Q000378:metabolism; D015262:Xenobiotics / Q000633:toxicity*
D000975:Antioxidants; D015415:Biomarkers; D004785:Environmental Pollutants; D015262:Xenobiotics