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Sensors 2007, 7(1), 38-51; doi:10.3390/s7010038

Improvement of Bioactive Compound Classification through Integration of Orthogonal Cell-Based Biosensing Methods

Department of Biological and Ecological Engineering, Oregon State University, 116 Gilmore Hall, Corvallis, OR 97331, USA
Department of Chemical Engineering, Oregon State University, 103 Gleeson Hall, Corvallis, OR 97331, USA
Department of Botany and Plant Pathology, Oregon State University, 2082 Cordley Hall, Corvallis, OR 97331, USA
Author to whom correspondence should be addressed.
Received: 14 December 2006 / Accepted: 18 January 2007 / Published: 21 January 2007
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Lack of specificity for different classes of chemical and biological agents, and false positives and negatives, can limit the range of applications for cell-based biosensors. This study suggests that the integration of results from algal cells (Mesotaenium caldariorum) and fish chromatophores (Betta splendens) improves classification efficiency and detection reliability. Cells were challenged with paraquat, mercuric chloride, sodium arsenite and clonidine. The two detection systems were independently investigated for classification of the toxin set by performing discriminant analysis. The algal system correctly classified 72% of the bioactive compounds, whereas the fish chromatophore system correctly classified 68%. The combined classification efficiency was 95%. The algal sensor readout is based on fluorescence measurements of changes in the energy producing pathways of photosynthetic cells, whereas the response from fish chromatophores was quantified using optical density. Change in optical density reflects interference with the functioning of cellular signal transduction networks. Thus, algal cells and fish chromatophores respond to the challenge agents through sufficiently different mechanisms of action to be considered orthogonal.
Keywords: Fish chromatophore; algae; orthogonal; sensor system. Fish chromatophore; algae; orthogonal; sensor system.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Chaplen, F.W.R.; Vissvesvaran, G.; Henry, E.C.; Jovanovic, G.N. Improvement of Bioactive Compound Classification through Integration of Orthogonal Cell-Based Biosensing Methods. Sensors 2007, 7, 38-51.

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