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Open Access Methodology

Fluorescence resonance energy transfer sensors for quantitative monitoring of pentose and disaccharide accumulation in bacteria

Thijs Kaper12, Ida Lager13, Loren L Looger14, Diane Chermak1 and Wolf B Frommer1*

Author Affiliations

1 Department of Plant Biology, Carnegie Institution of Washington, Panama Street, Stanford, CA 94305, USA

2 Danisco US Inc., Genencor Division, Page Mill Road, Palo Alto, CA 94304, USA

3 Department of Cell and Organism Biology, Lund University, Sölvegatan 35, 223 62 Lund, Sweden

4 Janelia Farm, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA

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Biotechnology for Biofuels 2008, 1:11  doi:10.1186/1754-6834-1-11

Published: 3 June 2008

Abstract

Background

Engineering microorganisms to improve metabolite flux requires detailed knowledge of the concentrations and flux rates of metabolites and metabolic intermediates in vivo. Fluorescence resonance energy transfer sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. These sensors have been applied successfully in mammalian and plant cells but potentially could also be used to monitor steady-state levels of metabolites in microorganisms using fluorimetric assays. Sensors for hexose and pentose carbohydrates could help in the development of fermentative microorganisms, for example, for biofuels applications. Arabinose is one of the carbohydrates to be monitored during biofuels production from lignocellulose, while maltose is an important degradation product of starch that is relevant for starch-derived biofuels production.

Results

An Escherichia coli expression vector compatible with phage λ recombination technology was constructed to facilitate sensor construction and was used to generate a novel fluorescence resonance energy transfer sensor for arabinose. In parallel, a strategy for improving the sensor signal was applied to construct an improved maltose sensor. Both sensors were expressed in the cytosol of E. coli and sugar accumulation was monitored using a simple fluorimetric assay of E. coli cultures in microtiter plates. In the case of both nanosensors, the addition of the respective ligand led to concentration-dependent fluorescence resonance energy transfer responses allowing quantitative analysis of the intracellular sugar levels at given extracellular supply levels as well as accumulation rates.

Conclusion

The nanosensor destination vector combined with the optimization strategy for sensor responses should help to accelerate the development of metabolite sensors. The new carbohydrate fluorescence resonance energy transfer sensors can be used for in vivo monitoring of sugar levels in prokaryotes, demonstrating the potential of such sensors as reporter tools in the development of metabolically engineered microbial strains or for real-time monitoring of intracellular metabolite during fermentation.