A rapid biosensor-based method for quantification of free and glucose-conjugated salicylic acid

Background: Salicylic acid (SA) is an important signalling molecule in plant defenses against biotrophic pathogens. It is also involved in several other processes such as heat production, flowering, and germination. SA exists in the plant as free SA and as an inert glucose conjugate (salicylic acid 2-O-beta-D-glucoside or SAG). Recently, Huang et al. developed a bacterial biosensor that responds to free SA but not SAG, designated as Acinetobacter sp. ADPWH_lux. In this paper we describe an improved methodology for Acinetobacter sp. ADPWH_lux-based free SA quantification, enabling high-throughput analysis, and present an approach for the quantification of SAG from crude plant extracts. Results: On the basis of the original biosensor-based method, we optimized extraction and quantification. SAG content was determined by treating crude extracts with beta-glucosidase, then measuring the released free SA with the biosensor. beta-glucosidase treatment released more SA in acetate buffer extract than in Luria-Bertani (LB) extract, while enzymatic hydrolysis in either solution released more free SA than acid hydrolysis. The biosensor-based method detected higher amounts of SA in pathogen-infected plants than did a GC/MS-based method. SA quantification of control and pathogen-treated wild-type and sid2 (SA induction-deficient) plants demonstrated the efficacy of the method described. Using the methods detailed here, we were able to detect as little as 0.28 mu g SA/g FW. Samples typically had a standard deviation of up to 25% of the mean. Conclusion: The ability of Acinetobacter sp. ADPWH_lux to detect SA in a complex mixture, combined with the enzymatic hydrolysis of SAG in crude extract, allowed the development of a simple, rapid, and inexpensive method to simultaneously measure free and glucose-conjugated SA. This approach is amenable to a high-throughput format, which would further reduce the cost and time required for biosensor-based SA quantification. Possible applications of this approach include characterization of enzymes involved in SA metabolism, analysis of temporal changes in SA levels, and isolation of mutants with aberrant SA accumulation.