Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Journal Article · Sat Jan 01 00:00:00 EST 2011 · Journal of Environmental Radioactivity, 102(1):67-71

DOI:https://doi.org/10.1016/j.jenvrad.2010.09.005· OSTI ID:1001454

Webb-Robertson, Bobbie-Jo M; Bunn, Amoret L; Bailey, Vanessa L

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ~87.0%, ~71.4%, ~87.5%, and 100% for the four groups; Control (non-amended system), low-dose (amended at 10 µg U L-1), medium dose (amended at 100 µg U L-1), and high dose (500 µg U L-1). The SVM model achieved an overall cross-validated classification accuracy of ~87% in contrast to ~59% for the best linear classifier.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1001454
• Report Number(s): PNNL-SA-72816; JERAEE; TRN: US1100364
• Journal Information: Journal of Environmental Radioactivity, 102(1):67-71, Vol. 102, Issue 1; ISSN 0265-931X
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
ACCURACY
AUFWUCHS
CARBOXYLIC ACIDS
CLASSIFICATION
COMMUNITIES
FUNCTIONALS
LEARNING
LIPIDS
PHOSPHOLIPIDS
PROBABILITY
SPECIFICITY
URANIUM
URANYL NITRATES
VECTORS
Non-linear statistics
Periphyton
Phospholipid fatty acids
Uranium
Predictive
Model
MICROBIAL COMMUNITY
CHLOROFORM FUMIGATION
SALT-MARSH
SOIL
BIOMASS
BACTERIAL
REDUCTION
DIVERSITY
SEDIMENTS
PROFILES