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

Defraia CT, Schmelz EA, Mou Z - Plant Methods (2008)

Bottom Line: ADPWH_lux.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Microbiology and Cell Science, University of Florida, P,O, Box 110700, Gainesville, FL, 32611, USA. zhlmou@ufl.edu.

ABSTRACT

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 mug 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.

No MeSH data available.


Related in: MedlinePlus

Standard curve optimization. (A) Effect of plant extract on SA-induced luminescence. SA standards were made with either LB or sid2-2 plant extract as the solvent. (B) Non-linearity of the SA-response curve. Data points were fitted with linear (blue) and third order polynomial (orange) best-fit lines. Note the lower R-squared value of the linear best-fit line. (C) A typical set of best-fit standard curves based on SA standards. The low SA concentration curve (orange) was fitted to standards of 0.8, 1.6, and 3.2 ng SA. The medium SA concentration curve (blue) was fitted to standards of 8, 16, 24, and 32 ng SA. The high SA concentration curve (green) was fitted to standards of 40, 48, 56, and 64 ng SA. (D) Diminishing response of the biosensor to increasing SA concentrations. (E) Effect of biosensor culture density on SA-induced luminescence. Biosensor cultures of OD600 = 0.6–0.8 were also tested and exhibited lower response to SA than OD600 = 0.4, but were omitted for clarity, as were error bars. Values indicate the average of three replicates with standard deviation (A-D only). Experiments were done three times with similar results.
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Figure 1: Standard curve optimization. (A) Effect of plant extract on SA-induced luminescence. SA standards were made with either LB or sid2-2 plant extract as the solvent. (B) Non-linearity of the SA-response curve. Data points were fitted with linear (blue) and third order polynomial (orange) best-fit lines. Note the lower R-squared value of the linear best-fit line. (C) A typical set of best-fit standard curves based on SA standards. The low SA concentration curve (orange) was fitted to standards of 0.8, 1.6, and 3.2 ng SA. The medium SA concentration curve (blue) was fitted to standards of 8, 16, 24, and 32 ng SA. The high SA concentration curve (green) was fitted to standards of 40, 48, 56, and 64 ng SA. (D) Diminishing response of the biosensor to increasing SA concentrations. (E) Effect of biosensor culture density on SA-induced luminescence. Biosensor cultures of OD600 = 0.6–0.8 were also tested and exhibited lower response to SA than OD600 = 0.4, but were omitted for clarity, as were error bars. Values indicate the average of three replicates with standard deviation (A-D only). Experiments were done three times with similar results.

Mentions: Briefly, the method described by Huang et al. comprises tissue grinding, extraction in LB, sonication, and centrifugation, resulting in a crude plant extract containing SA. The crude extract is then mixed with a culture of the biosensor in a 96-well cell culture plate, and incubated at 37°C for one hour. The luminescence is then determined. In order to convert SA-induced luminescence into units of SA concentration, several standards with known amounts of SA are included to generate a standard curve [28]. We found that standards made with crude extract had significantly lower luminescence than those made with LB (Figure 1A), suggesting that the plant extract decreases induction of the biosensor by SA. Since our aim was to determine SA concentrations in plant extract, the standards must also have plant extract as a solvent. The ideal plant extract for making SA standards would initially contain no SA. In order to minimize the SA content of the extract used to make the standards, we used extract from sid2-2 plants, which fail to accumulate significant amounts of SA during pathogen infection. However, we and others [24] were unable to consistently detect a difference in constitutive SA levels between sid2-2 and wild type (data not shown). Therefore, untreated wild type plants may also be used for making the SA standards. Lack of a standard with no SA precludes the determination of absolute SA concentrations from plant extracts. Thus, the biosensor may only be used to determine relative SA levels between samples rather than absolute concentrations. When SA standards were made with plant extract, the relationship between luminescence and SA concentration was non-linear (Figure 1B). To simplify data analysis, instead of using all standards to construct the standard curve, only the standards with luminescence similar to that of the experimental sample were used. A best-fit linear line with a high R-squared value could then be derived and used as the standard curve (Figure 1C). Alternatively, a non-linear best-fit line can be used, although we found higher R-squared values for standards with low SA content, using the former method. Conversion from luminescence to SA concentration was carried out using the following equation:


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

Defraia CT, Schmelz EA, Mou Z - Plant Methods (2008)

Standard curve optimization. (A) Effect of plant extract on SA-induced luminescence. SA standards were made with either LB or sid2-2 plant extract as the solvent. (B) Non-linearity of the SA-response curve. Data points were fitted with linear (blue) and third order polynomial (orange) best-fit lines. Note the lower R-squared value of the linear best-fit line. (C) A typical set of best-fit standard curves based on SA standards. The low SA concentration curve (orange) was fitted to standards of 0.8, 1.6, and 3.2 ng SA. The medium SA concentration curve (blue) was fitted to standards of 8, 16, 24, and 32 ng SA. The high SA concentration curve (green) was fitted to standards of 40, 48, 56, and 64 ng SA. (D) Diminishing response of the biosensor to increasing SA concentrations. (E) Effect of biosensor culture density on SA-induced luminescence. Biosensor cultures of OD600 = 0.6–0.8 were also tested and exhibited lower response to SA than OD600 = 0.4, but were omitted for clarity, as were error bars. Values indicate the average of three replicates with standard deviation (A-D only). Experiments were done three times with similar results.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2654556&req=5

Figure 1: Standard curve optimization. (A) Effect of plant extract on SA-induced luminescence. SA standards were made with either LB or sid2-2 plant extract as the solvent. (B) Non-linearity of the SA-response curve. Data points were fitted with linear (blue) and third order polynomial (orange) best-fit lines. Note the lower R-squared value of the linear best-fit line. (C) A typical set of best-fit standard curves based on SA standards. The low SA concentration curve (orange) was fitted to standards of 0.8, 1.6, and 3.2 ng SA. The medium SA concentration curve (blue) was fitted to standards of 8, 16, 24, and 32 ng SA. The high SA concentration curve (green) was fitted to standards of 40, 48, 56, and 64 ng SA. (D) Diminishing response of the biosensor to increasing SA concentrations. (E) Effect of biosensor culture density on SA-induced luminescence. Biosensor cultures of OD600 = 0.6–0.8 were also tested and exhibited lower response to SA than OD600 = 0.4, but were omitted for clarity, as were error bars. Values indicate the average of three replicates with standard deviation (A-D only). Experiments were done three times with similar results.
Mentions: Briefly, the method described by Huang et al. comprises tissue grinding, extraction in LB, sonication, and centrifugation, resulting in a crude plant extract containing SA. The crude extract is then mixed with a culture of the biosensor in a 96-well cell culture plate, and incubated at 37°C for one hour. The luminescence is then determined. In order to convert SA-induced luminescence into units of SA concentration, several standards with known amounts of SA are included to generate a standard curve [28]. We found that standards made with crude extract had significantly lower luminescence than those made with LB (Figure 1A), suggesting that the plant extract decreases induction of the biosensor by SA. Since our aim was to determine SA concentrations in plant extract, the standards must also have plant extract as a solvent. The ideal plant extract for making SA standards would initially contain no SA. In order to minimize the SA content of the extract used to make the standards, we used extract from sid2-2 plants, which fail to accumulate significant amounts of SA during pathogen infection. However, we and others [24] were unable to consistently detect a difference in constitutive SA levels between sid2-2 and wild type (data not shown). Therefore, untreated wild type plants may also be used for making the SA standards. Lack of a standard with no SA precludes the determination of absolute SA concentrations from plant extracts. Thus, the biosensor may only be used to determine relative SA levels between samples rather than absolute concentrations. When SA standards were made with plant extract, the relationship between luminescence and SA concentration was non-linear (Figure 1B). To simplify data analysis, instead of using all standards to construct the standard curve, only the standards with luminescence similar to that of the experimental sample were used. A best-fit linear line with a high R-squared value could then be derived and used as the standard curve (Figure 1C). Alternatively, a non-linear best-fit line can be used, although we found higher R-squared values for standards with low SA content, using the former method. Conversion from luminescence to SA concentration was carried out using the following equation:

Bottom Line: ADPWH_lux.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Microbiology and Cell Science, University of Florida, P,O, Box 110700, Gainesville, FL, 32611, USA. zhlmou@ufl.edu.

ABSTRACT

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 mug 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.

No MeSH data available.


Related in: MedlinePlus