<<

ABSTRACT

GANAWI, AMEL AHMED.A. Extraction and Direct Quantification of in Arabidopsis Using Matrix-Assisted Laser Desorption Ionization . (Under the direction of Assistant professor Lin He).

Systemic acquire resistant (SAR) is enhanced resistance created by the plant after infection, in which the plant becomes resistant to a second pathogen infection. This resistant can last for weeks preventing the plant from being infected. In addition the plant becomes resistant not only to the pathogen that causes the infection but also to a wide range of pathogens. Knowing how to activate this resistant in the plant is critical to increase crop production. Salicylic Acid has been suggested as one of the main signaling compounds to activate SAR after plant infection. I describe here the development of a matrix assisted laser desorption ionization mass spectrometry (MALDI-MS)-based approach to monitor SA in Arabidopsis thaliana. Sinapic acid was identified as the preferred choice in SA detection because minimal interference was observed between the matrix and analyte peaks. The use of Isotopic labeled Salicylic Acid (SA-d6) as a suitable internal standard for SA quantification was also demonstrated. SA spiked in plant extract at known concentrations was used as the model system to evaluate quantification and reproducibility of this newly developed MALDI-MS method. A comparison in detection feasibility between MALDI-MS and DIOS-MS was also conducted and reported in this thesis.

In addition, a Liquid-phase extraction method is optimized to yield maximal extraction efficiency. I have quantified extraction efficiency and method reproducibility to extract SA in Arabidopsis leaves, and demonstrated its applicability for quantitation of endogenous SA in different plant samples. Extraction and Direct Quantification of Salicylic Acid in Arabidopsis Using Matrix- Assisted Laser Desorption Ionization Mass Spectrometry

By

AMEL AHMED A.GANAWI

A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Master of Science

CHEMISTRY Raleigh, NC 2007

APPROVED BY:

______

Assistant Professor Lin He Chair of Advisory Committee

______

Professor David C. Muddiman Professor Wendy F. Boss Chemistry Plant

DEDICATION

This thesis is dedicated to my parents, who were always there for me, for their continuous encouragement for highest levels of education, and for teaching me to use education as a measure of success. I also dedicated it to my husband for his continuous and endless support and patience. I also dedicated it to my two little sons, Ahmed and Mazin, for their time I spent away from them working on my project.

ii BIOGRAPHY

The author was born in Dongola, Sudan in 1970. She attended her elementary, intermediate and high school in her city of birth. After finishing her high school, her family moved to Khartoum, where she attended her undergraduate education in the

Department of Chemistry at University of Khartoum. During her college life, she became more interested in pursuing higher education in chemistry. She was graduated in 1995 with Bachelor Degree in Chemistry first class honor and joined the Department of

Chemistry as part timer teaching assistant. She was also nominated as a full time research assistant at The Sudan Atomic Energy Commission (SAEC), from 1995 to 1999. She was married in 1998. She moved to Saudi with her husband before she finally moved to the

United States in 2002 to continue her educational journey. She joined the Department of

Chemistry at North Carolina State University in the summer of 2004, where she for studied her Masters of Chemistry under supervision of Professor Lin He.

iii TABLE OF CONTENTS

LIST OF TABLES ...... vi LIST OF FIGURES ...... vii LIST OF SCHEMES ...... x

CHAPTER 1: GENERAL LITERATURE OVERVIEW

1.1. Importance of Salicylic Acid (SA) as Signaling Compound...... 1 1.2. Current Analytical Methods for SA Detection ...... 3 1.3. Overview of MALDI-MS in Small Detection ...... 4 1.4. References...... 6

CHAPTER 2: DETECTION OF SALICYLIC ACID (SA) AS AN ESSENTIAL COMPOUND IN REGULATING SYSTEMIC DEFENSE RESPONSE IN ARABIDOPSIS

2.1. Introduction...... 14 2.2. Experimental Section...... 15 2.2.1. Material...... 15 2.2.2. Standard Solution Preparation ...... 16 2.2.3. Extraction Procedure...... 16 2.2.4. MS Analysis...... 17 2.3. Results and Discussion ...... 18 2.4. Conclusion ...... 22 2.5. References...... 23

CHAPTER 3: OPTIMIZATION OF SALICYLIC ACID EXTRACTION

3.1. Introduction...... 37 3.2. Experimental Section...... 38 3.2.1. Materials ...... 38 3.2.2. Extraction procedure...... 39 3.2.3. Instrument and Data Analysis...... 39 3.3. Results and Discussion ...... 40 3.4. Conclusion ...... 43 3.6. References...... 44

CHAPTER 4: AN SYSTEMATIC INVESTIGATION OF THERMAL CONTRIBUTION INSURFACE-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY (SALDI- MS) USING ORDERED NANOCAVITY ARRAYS

4.1 Introduction...... 52

iv 4.2 Experimental...... 54 4.2.1 Materials ...... 54 4.2.2 preparation ...... 55 4.2.3 Field-Emission Scanning Electron Microscope (FE-SEM) Imaging...... 56 4.2.4 Thermal Measurements...... 56 4.2.5 Mass Spectrometry Measurements ...... 57 4.3 Results and discussion ...... 57 4.3.1Substrate Fabrication ...... 57 4.3.2 Surface Temperature Measurements...... 59 4.3.3 Substrate Mass Spectrometry Measurements ...... 62 4.4 Conclusion ...... 63 4.5 References...... 65

v LIST OF TABLES

CHAPTER 2: DETECTION OF SALICYLIC ACID (SA) AS AN Page ESSENTIAL COMPOUND IN REGULATING SYSTEMIC DEFENSE RESPONSE IN ARABIDOPISIS.

Table 2.1. The combinatorial list of different matrices screen in SA detection 26

Table 2.2. Sample preparation of SA 27 Table 2.3. Sample preparation table of standard SA spiked in the plant 28 extract. Table 2.4. The calculated extraction efficiency for each amount of SA added 29 to the plant tissue before the extraction. Three different independent assays were generated for each concentration to determine the inter-day precisions.

CHAPTER 3: OPTIMIZATION OF SALICYLIC ACID EXTRACTION

Table 3.1. Sample preparation table of standard calibration curve used to 46 calculate the amount of SA recovered after the extraction Table 3.2. Shows the change in the extraction efficiencies with respect to the 47 extraction volume.

CHAPTER 4: A SYSTEMATIC INVESTIGATION OF THERMAL CONTRIBUTION IN SURFACE-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY (SALDI-MS) USING ORDERED NANOCAVITY ARRAYS.

Table 4.1. Shows etching time and the calculated volume porosity for each 68 substrate. The particle size used in the mask was 170 nm

vi LIST OF FIGURES

CHAPTER 1: GENERAL LITERATURE OVERVIEW Page

Fig 1.1. The proposal pathway (PAL) in which 12 endogenous SA is synthesized. Fig 1.2. The proposed alternative pathway in which endogenous SA is 13 synthesized.

CHAPTER 2: DETECTION OF SALICYLIC ACID (SA) AS ESSENTIAL COMPOUND IN REGULATING SYSTEMIC DEFENSE RESPONSE IN ARABIDOPSIS.

Fig 2.1. (A) DIOS spectrum of the control where only the solvent was 30 deposited on a DIOS substrate. The background peak at where SA was expected was labeled with asterisk. The inset shows the zoom-in of the region. (B) A DIOS spectrum of 500 µM SA. The SA peak was labeled with asterisk.

Fig 2.2. (A) A MALDI –MS spectrum of 250 pmol SA with sinapic acid 31 as a matrix. The SA peak is labeled by an asterisk. (B) A MALDI-MS spectrum of sinapic acid as the control. Note that the asterisk in the zoom-in inset shows the relatively clean background in the area where SA will be expected Fig 2.3. (A)The chemical structure of the internal standard SA-d6 and its 32 proton exchange equilibrium with SA-d4. (B)The MALDI-MS spectrum of 20 pmol SA and 20 pmol SA-d6 using sinapic acid as the matrix Fig 2.4. The MALDI-MS spectra of 20 pmol SA and 20 pmol IS added 33 in a wt uninfected plant extract inset show clear detection of both peaks Fig 2.5. Linear calibration curves of standard SA detected (A) in water 34 and (B) spiked in a wt uninfected plant extract. Fig 2.6. Standard curve shows the MS measurement reproducibility. The 35 standard error generated from three different acquisition dates for the standard SA spiked in the same wt uninfected plant extract.

Fig 2.7. Linear correlation of the amount of SA added before the 36 extraction and the corresponding MS response.

CHAPTER 3: OPTIMIZATION OF SALICYLIC ACID EXTRACTION.

vii

Fig 3.1. MALDI-MS spectrum of wt infected plant extract. The 48 highlighted region shows the region where the natural occurring SA in the plant spectrum. The zoom in, shows the natural occurring SA peak and SA-d4 peak Fig 3.2. The calibration curves used to calculate the amounts of SA 49 recovered after the extraction. One calibration curve was generated for each extract volume used in the extraction procedure; during the quantitative study to determine the extract volume which provides higher extraction recovery.

Fig 3.3. Concentration dependant extraction efficiency. The extraction 50 efficiency increases with the extract volume increases.

Fig 3.4. The calculated natural occurring SA in wt uninfected, wt 51 infected, PBS3 uninfected and PBS3 infected

CHAPTER 4: AN SYSTEMATIC INVESTIGATION OF THERMAL CONTRIBUTION IN SURFACE- ASSISTED LASER DESORPTION /IONIZATION MASS SPECTROMETRY (SALDI-MS) USING ORDERED NANOCAVITY ARRAYS.

Fig 4.1. Representative FE-SEM images of Si substrates of different 69 nanocavity arrays. The substrates were prepared using 170 nm polystyrene beads as the mask and RIE for 1 min (A, B), 2 min (C, D), 5 min (E) and 20 min (F). Both the top-view (A, C, E, and F) and the cross-section (B and D) were shown Fig 4.2. Semi-linear correlation of porosity and etching time. Different 70 volume porosity profiles were obtained for the two mask size used. For each mask size the volume porosity increases as an etching time increases linearly.

Fig 4.3. (A) A schematic drawing of the infrared thermography setup to 71 measure temperature changes on the surface of the Si substrate upon laser irradiation. (B) Five representative temperature profiles plotted as a function of time. The laser irradiation started at 5 sec time point and was blocked after 5-sec irradiation. The five profiles were recorded from center and four corners of the same substrate.

Fig 4.4. A plot of the surface temp changes as a function of calculated 72 volume porosity Fig 4.5. MS intensity of DPPC as a function of irradiation laser intensity 73 for different substrates. 100 pmol DPPC was used as the

viii standard. The laser intensity was tuned using a neutral density filter, and the numbers recorded were arbitrarily assigned by the manufacturer. (B) A close-to-linear relationship between the MS response (S/N) and the substrate volume porosity. (C) The SALDI laser threshold value decreases with increasing porosity. The laser threshold was defined as the laser energy needed to reach a signal-to-noise ration of 50:1 in DPPC detection Fig 4.6. The signal to noise ratio of DPPC as a function of temperature 74 change. The etching time for the ordered surface structure is 0.5,1,1.5 and 2 min starting from the lowest temperature change. The etching time for the non-ordered structure is 20 and 5 min starting from the lowest temperature change. 1.5 and 5 min etching time has the same temperature change and completely different MS performance. Which suggest that the surface geometry has a big impact in the MS performance.

ix LIST OF SCHEMES

CHAPTER 1: GENERAL LITERATURE OVERVIEW Page

Scheme 1.1. SA, as a central signal component, in 11 plant resistance net work.

x CHAPTER 1

GENERAL LITERATURE OVERVIEW

1.1 Importance of Salicylic Acid (SA) as Signaling Compound

It is known that upon infection a plant can undergo certain actions to eliminate the

spread of the pathogen in the entire plant as a part of hypersensitive response (HR) by

confining the viral effect in the local tissue area, strengthening walls by oxidative cross-

linking, or inducing local cell death. Meanwhile, the uninfected section of the plant activates

certain defense responses that make the plant become resistant to later pathogen infections, a

process known as Systemic Acquire Resistant (SAR). The importance of SAR goes beyond

an improved resistance to the same pathogen strain, enabling a plant to develop broad

resistance to different pathogens and protecting the plant from various infections. Giving the

importance of improved plant resistance to viral, viroid, fungal, and bacterial pathogen infection, which is vital to increase plant production quantity and quality, understanding the signaling pathways associated with plant self-defense against various infections is critical and thus has attracted a great deal of interest. 1-3

A small , salicylic acid (SA), has been suggested to function as a

natural transduction signal mediator to activate HR and SAR inside plants: the level of

endogenous SA is found to increase after infection and applications of exogenous SA to the

plant in the absence of pathogens increase the expression level of pathogen-related genes, which subsequently enhances pathogen resistance. Furthermore, when SA synthesis is purposely blocked or degraded after formation in a transgenic plant, SAR and HR do not

1 occur. 1, 4-8 Additional evidence of the important roles played by SA include observations of an enhanced production of H2O2 in oxidative cross-linking cell walls and of an that

participates in cell protection 9, 10 An incubation of plant tissues in SA has also been found to inhibit the spread of viruses in the plant tissue.11

A simplified SAR pathway is shown in Scheme 1.1 where SA serves as the critical

network signaling compound in Arabidopsis thaliana: an enhanced SA production upon

pathogen infection leads to an increased expression of the resistant gene NPR1 which

triggers local cell death to prevent virus spreading to healthy plant tissues. SA also serves as

the central signaling compound to induce the expression of PR genes in the resistance

network. The production of PR can be enhanced by two suggested pathways in

parallel where one requires NPR1 genes and the other pathway is independent of NPR1

genes.2,5.12-15 despite the improved understanding on the SAR mechanism from recent

studies, biosynthetic pathways of SA in the plant are yet to be understood. Two possible SA

synthetic routes have been suggested: one starting from phenylalanine (PAL) in the plant

(Fig 1.1),16 and the other an isochorismate synthase (ICS)-assisted path from chorismate (Fig

1.2).17 The presence of ICS pathway was discovered in a study in which the blocking of the

PAL pathway didn’t completely prevent SA formation. It has also been suggested that the

PAL pathway works immediately after the infection and the second one becomes active later.

However additional studies are needed to verify these hypotheses by monitoring SA at

different time points of infection and with/without blocking one or more genes in the

network. To obtain statistically significant results, a large biological sample population is

preferred therefore the development of a simple and fast method to quantitate the expression

and distribution of SA is imperative.

2

1.2 Current Analytical Methods for SA Detection

Most methods used for SA detection are based on fluorometry, colorimetry,

gas/liquid (G/LC) and high performance liquid chromatography (HPLC).

Among them HPLC coupled with fluormetric detection offers the best sensitivity (0.01 mg/L), which makes it highly favorable and has been widely used in SA detection.18 One of

the limitations of using HPLC/Fluorescence based method to detect SA, however, is the

interference introduced by the presence of various unidentified fluorescent compounds in

relatively high concentrations.19 The long elution time (approx. 30 min/run) also limits assay

throughput. The use of high performance anion exchange chromatography by forming a Fe3+

complex with SA has reportedly decreased the total analysis time to 15 min with a limit of

detection (LOD) of 5 ng/g fresh weight. 20

Gas Chromatography/Mass Spectrometry (GC-MS) is another technique that has been

routinely used to quantitate SA in plant samples. It is highly sensitive, robust, and

automatable. In 1994 Yamamoto et al. was able to detect and quantitate the natural occurring

SA in rice by derivatizing SA to methylated SA.21 The limitation of GC-MS, however, lies

in the need for an additional sample purification step, using anion exchange or reverse phase

exchange, to reduce sample complexity and remove and chlorophyll.22 This necessary

extra step increases the total analysis time and reduces sample recovery. Other methods,

such as solid phase extraction (SFE) coupled with direct spectrofluorimetric23 and Capillary

electrophoresis (CE), have also been used to detect SA and phenolic compounds in

3 Arabidopsis.24 DIOS-MS coupled with SPE has also been used successfully in direct

detection of SA in plasma samples.25

Regardless the method chosen for SA detection, three major drawbacks have limited

their applications (1) Most of the methods reported to date consume large amounts of plant

tissues as the starting materials to ensure acceptable detection sensitivity downstream. For

example, to achieve detection of 10 ng/g fresh weight SA in an Arum Lily plant sample using

HPLC, 1 g of the plant tissue was used.26 (2) Complex sample preparation procedures are often required as well. Meuwly and Metraux have improved the method by adding ortho- anisic acid as an internal standard. The of SA was reduced to 4 ng/g fresh weights, though ortho-anisic acid had to be detected separately 27 The use of a SPE cartridge

containing Fe3+ to form a complex with SA has also been used to concentrate SA prior to

chromatographic detection.20 Yet, the necessary purification steps extended the analysis

time and increases the chances of sample losses. The derivitization step can add additional

strain in the applicability of the method uses. (3) Last but not least, most separation-based

methods are sequential methods that can only handle one sample per injection. .

1.3 Overview of MALDI-MS in Small Molecule Detection

MALDI is a soft ionization technique that is relatively simple and high throughput. It utilizes small organic compounds (matrix) to absorb and transfer laser energy to the analytes,

and facilitates the desorption of the analytes from a surface. A complete understanding of

analyte ionization is not yet available; but it is generally accepted that matrix play

a critical role in the process, 28-30 especially in analysis of high molecular weight

4 biomolecules.31-33 Despite of the fact that ionization of the matrix itself often generates

peaks in the low mass region to interfere with analyte peaks, MALDI has been proven for its

ability in targeted small molecule detection for the analytes such as amino acids and small

drugs molecules in pharmaceuticals applications. 34

Although a typical >30% standard variation in MALDI peak intensities is expected,

mainly due to shot-to-shot laser energy variation and -dependent analyte

distribution, the quantitative performance of MALDI-MS has been significantly improved in

recent years through the use of internal standards. Several sample preparation approaches,

such as faster solvent evaporation and electrospray-assisted analyte deposition, have also

been developed to minimize quantification variations. 35-38

In this research, I have studied the feasibility of using Matrix–Assisted Laser

Desorption/Ionization Mass Spectrometry (MALDI-MS) to quantify endogenous level of SA in the plants and subsequently monitor concentration variations of SA in the plant at different

infection stages. Direct profiling without column-based separation has been demonstrated with simplified sample preparation that does not require additional purification or

derivitization after SA extraction. The total analysis time is significantly shortened, which

allows high-throughput sample profiling of multiple samples to ensure statistic collection of

biologically significant information.

5 1.4 References

(1) Malamy, J.; Carr, J. P.; Klessig, D. F.; Raskin, I., Salicylic-Acid - a Likely

Endogenous Signal in the Resistance Response of Tobacco to Viral-Infection. Science

1990, 250, (4983), 1002-1004.

(2) Shah, J., The salicylic acid loop in plant defense. Current Opinion in Plant Biology

2003, 6, (4), 365-371.

(3) Sticher, L.; MauchMani, B.; Metraux, J. P., Systemic acquired resistance. Annual

Review of Phytopathology 1997, 35, 235-270.

(4) Delaney, T. P.; Uknes, S.; Vernooij, B.; Friedrich, L.; Weymann, K.; Negrotto, D.;

Gaffney, T.; Gutrella, M.; Kessmann, H.; Ward, E.; Ryals, J., A Central Role of

Salicylic-Acid in Plant-Disease Resistance. Science 1994, 266, (5188), 1247-1250.

(5) Gaffney, T.; Friedrich, L.; Vernooij, B.; Negrotto, D.; Nye, G.; Uknes, S.; Ward, E.;

Kessmann, H.; Ryals, J., Requirement of Salicylic-Acid for the Induction of Systemic

Acquired-Resistance. Science 1993, 261, (5122), 754-756.

(6) Ward, E. R.; Uknes, S. J.; Williams, S. C.; Dincher, S. S.; Wiederhold, D. L.;

Alexander, D. C.; Ahlgoy, P.; Metraux, J. P.; Ryals, J. A., Coordinate Gene Activity

in Response to Agents That Induce Systemic Acquired-Resistance. Plant Cell 1991,

3, (10), 1085-1094.

(7) Raskin, I., Role of Salicylic-Acid in Plants. Annual Review of Plant Physiology and

Plant 1992, 43, 439-463.

(8) Malamy, J.; Klessig, D. F., Salicylic-Acid and Plant-Disease Resistance. Plant

Journal 1992, 2, (5), 643-654.

6 (9) Shirasu, K.; Nakajima, H.; Rajasekhar, V. K.; Dixon, R. A.; Lamb, C., Salicylic acid

potentiates an agonist-dependent gain control that amplifies pathogen signals in the

activation of defense mechanisms. Plant Cell 1997, 9, (2), 261-270.

(10) Dempsey, D. A.; Shah, J.; Klessig, D. F., Salicylic acid and disease resistance in

plants. Critical Reviews in Plant Sciences 1999, 18, (4), 547-575.

(11) Chivasa, S.; Murphy, A. M.; Naylor, M.; Carr, J. P., Salicylic acid interferes with

tobacco mosaic virus replication via a novel salicylhydroxamic acid-sensitive

mechanism. Plant Cell 1997, 9, (4), 547-557.

(12) Durrant, W. E.; Dong, X., Systemic acquired resistance. Annual Review of

Phytopathology 2004, 42, 185-209.

(13) Durrant, W. E.; Wang, S.; Dong, X. N., Arabidopsis SNI1 and RAD51D regulate

both gene and DNA recombination during the defense response.

Proceedings of the National Academy of Sciences of the United States of America

2007, 104, (10), 4223-4227.

(14) Heidel, A. J.; Dong, X. N., Fitness benefits of systemic acquired resistance during

Hyaloperonospora parasitica infection in Arabidopsis thaliana. Genetics 2006, 173,

(3), 1621-1628.

(15) Wang, D.; Amornsiripanitch, N.; Dong, X. N., A genomic approach to identify

regulatory nodes in the transcriptional network of systemic acquired resistance in

plants. Plos Pathogens 2006, 2, (11), 1042-1050.

(16) Ribnicky, D. M.; Shulaev, V.; Raskin, I., Intermediates of salicylic acid

in tobacco. Plant Physiology 1998, 118, (2), 565-572.

7 (17) Wildermuth, M. C.; Dewdney, J.; Wu, G.; Ausubel, F. M., Isochorismate synthase is

required to synthesize salicylic acid for plant defence. Nature 2001, 414, (6863), 562-

565.

(18) Kwong, T. C., Analysis of Acetylsalicylic-Acid and Its Metabolites by Liquid-

Chromatography. Journal of Liquid Chromatography 1987, 10, (2-3), 305-321.

(19) Bowling, S. A.; Guo, A.; Cao, H.; Gordon, A. S.; Klessig, D. F.; Dong, X. I., A

Mutation in Arabidopsis That Leads to Constitutive Expression of Systemic

Acquired-Resistance. Plant Cell 1994, 6, (12), 1845-1857.

(20) Rozhon, W.; Petutschnig, E.; Wrzaczek, M.; Jonak, C., Quantification of free and

total salicylic acid in plants by solid-phase extraction and isocratic high-performance

anion-exchange chromatography. Analytical and Bioanalytical Chemistry 2005, 382,

(7), 1620-1627.

(21) Scott, I. M.; Yamamoto, H., Mass-Spectrometric Quantification of Salicylic-Acid in

Plant-Tissues. 1994, 37, (2), 335-336.

(22) Engelberth, J.; Schmelz, E. A.; Alborn, H. T.; Cardoza, Y. J.; Huang, J.; Tumlinson,

J. H., Simultaneous quantification of jasmonic acid and salicylic acid in plants by

vapor-phase extraction and -chemical ionization-mass

spectrometry. Analytical 2003, 312, (2), 242-250.

(23) Lianidou, E. S.; Ioannou, P. C.; Polydorou, C. K.; Efstathiou, C. E., Synchronous

scanning second derivative spectrofluorimetry for the simultaneous determination of

diflunisal and salicylic acid added to serum and urine as ternary complexes with

terbium and EDTA. Analytica Chimica Acta 1996, 320, (1), 107-114.

8 (24) Shapiro, A. D.; Gutsche, A. T., Capillary electrophoresis-based profiling and

quantitation of total salicylic acid and related phenolics for analysis of early signaling

in Arabidopsis disease resistance. Analytical Biochemistry 2003, 320, (2), 223-233.

(25) Okuno, S.; Wada, Y., Measurement of serum salicylate levels by solid-phase

extraction and desorption/ionization on silicon mass spectrometry. Journal of Mass

Spectrometry 2005, 40, (8), 1000-1004.

(26) Raskin, I.; Turner, I. M.; Melander, W. R., Regulation of Heat-Production in the

Inflorescences of an Arum Lily by Endogenous Salicyclic Acid. Proceedings of the

National Academy of Sciences of the United States of America 1989, 86, (7), 2214-

2218.

(27) Meuwly, P.; Metraux, J. P., Ortho-Anisic Acid as Internal Standard for the

Simultaneous Quantitation of Salicylic-Acid and Its Putative Biosynthetic Precursors

in Cucumber Leaves. Analytical Biochemistry 1993, 214, (2), 500-505.

(28) Karas, M.; Bachmann, D.; Bahr, U.; Hillenkamp, F., Matrix-Assisted Ultraviolet-

Laser Desorption of Nonvolatile Compounds. International Journal of Mass

Spectrometry and Processes 1987, 78, 53-68.

(29) Karas, M.; Bachmann, D.; Hillenkamp, F., Influence of the Wavelength in High-

Irradiance Ultraviolet-Laser Desorption Mass-Spectrometry of Organic-Molecules.

Analytical Chemistry 1985, 57, (14), 2935-2939.

(30) Karas, M.; Hillenkamp, F., Laser Desorption Ionization of Proteins with Molecular

Masses Exceeding 10000 Daltons. 1988, 60, (20), 2299-2301.

(31) Zenobi, R.; Knochenmuss, R., Ion formation in MALDI mass spectrometry. Mass

Spectrometry Reviews 1998, 17, (5), 337-366.

9 (32) Dreisewerd, K., The desorption process in MALDI. Chemical Reviews 2003, 103, (2),

395-425.

(33) Karas, M.; Gluckmann, M.; Schafer, J., Ionization in matrix-assisted laser

desorption/ionization: singly charged molecular are the lucky survivors. Journal

of Mass Spectrometry 2000, 35, (1), 1-12.

(34) Lidgard, R.; Duncan, M. W., Utility of Matrix-Assisted Laser-Desorption Ionization

Time-of-Flight Mass-Spectrometry for the Analysis of Low-Molecular-Weight

Compounds. Rapid Communications in Mass Spectrometry 1995, 9, (2), 128-132.

(35) Muddiman, D. C.; Gusev, A. I.; Hercules, D. M., Application of secondary ion and

matrix-assisted laser desorption-ionization time-of-flight mass spectrometry for the

quantitative analysis of biological molecules. Mass Spectrometry Reviews 1995, 14,

(6), 383-429.

(36) Xiang, F.; Beavis, R. C., A Method to Increase Contaminant Tolerance in

Matrix-Assisted Laser-Desorption Ionization by the Fabrication of Thin Protein-

Doped Polycrystalline Films. Rapid Communications in Mass Spectrometry 1994, 8,

(2), 199-204.

(37) Cohen, L. H.; Gusev, A. I., Small molecule analysis by MALDI mass spectrometry.

Analytical and Bioanalytical Chemistry 2002, 373, (7), 571-586.

(38) Vorm, O.; Roepstorff, P.; Mann, M., Improved Resolution and Very High-Sensitivity

in Maldi Tof of Matrix Surfaces Made by Fast Evaporation. Analytical Chemistry

1994, 66, (19), 3281-3287.

10

Scheme 1.1 SA, as a central signal component, in plant resistance net work.

11

Fig 1.1 The proposal Phenylalanine pathway (PAL) in which endogenous SA is synthesized (Plant Physiol 1998).

12

Fig 1.2 The proposed alternative pathway in which endogenous SA is synthesized (Nature 2001).

13 CHAPTER 2

DETECTION OF SALICYLIC ACID (SA) AS AN ESSENTIAL COMPOUND IN REGULATING SYSTEMIC DEFENSE RESPONSE IN ARABIDOPSIS

2.1 Introduction

Salicylic Acid (SA) is known to be an important signaling compound in the plant defense response during Hypersensitive Response (HR) and Systemic Acquire Resistant

(SAR).1, 2 In particular, HR and SAR, a part of plant self-defense mechanism, are often

accompanied by elevation of the endogenous SA level in the infected plant.2 It has been

suggested that the amount of SA formed after infection depends on the type of the pathogen

used and the time allowed for SA to accumulate. Therefore, a comprehensive understanding

of SAR and HR calls for an ability to detect and quantify SA across a broad selection of plant

samples in a timely manner. Effective SA quantification methods may also shed light on the

possible SA synthetic pathways in vivo, which is yet to be fully understood.3, 4 Traditional

analytical methods, such as HPLC and GC-MS, have been utilized over years to detect SA in

the plant samples. 5-9 Though highly sensitive, they are limited by the needs for frequent method optimization, highly trained staff to operate and slow throughput; thereby a combinatorial screening of large numbers of samples and pathogens at different infection

points could be laborious and time consuming. A simpler and faster method is desired.

Since its introduction MALDI has been widely used in qualitative analysis.10-13 In

addition to good sensitivity and high salt tolerance MALDI has been valuable for its easy

sample preparation and the ability to profile several samples in a short time, which makes it a

method of choice for high throughput. Surface-based method such as Desorption ionization

on porous silicon (DIOS) is another alternative for SA quantification with the benefits of

easy sample preparation and high throughput.14 While the use of MALDI-MS in small

14 molecule quantification has been reported,15 the employment of MALDI-MS in SA detection has yet to be demonstrated.

In this chapter, I demonstrated the development of a MALDI-MS based method to quickly determine the amount of SA in the plants before and after the infection. Several traditional MALDI matrices were screened and sinapic acid was identified as the preferred choice in SA detection because minimal interference was observed between the matrix and analyte peaks. The use of SA-d6 as a suitable internal standard for SA quantification was also demonstrated. SA spiked in plant extract at known concentrations was used as the model system to evaluate quantification and reproducibility of this newly developed

MALDI-MS method. A comparison in detection feasibility between MALDI-MS and DIOS-

MS was also conducted and reported in this chapter.

2.2 Experimental Section

2.2.1. Material

Salicylic acid (SA, C6H4(OH)CO2H, 99.0%), trifluoroacetic acid (TFA), sinapic acid,

9-aminoacridine (9AA), 6-aza-2-thiothymine, 2, 4, 6-trihydroxyacetophenone (THAP), α- cyano-4-hydroxy cinnamic acid (CHCA) were purchased from Sigma-Aldrich (St.Louis,

MO). SA-d6 was obtained from C/D/N Isotopes (Quebec, Canada). CH3OH, hydrofluoric acid (HF, 49%), H2O2 (30%), cyclohexane (99%) and ethyl were purchased from

Fisher Scientific (Pittsburgh, PA). CD3OD was purchased from Cambridge Isotope

Laboratories (Andover, MA). Trichloroacetic acid was purchased from Ricca chemical company (Arlington. TX). CH3CH2OH was purchased from Aaper Alcohol (Shelbyvill,

KY). Antimony–doped (100) single–crystalline silicon wafer at 0.002-0.05 Ω/cm was

15 purchased from Silicon Sense Inc. (Nashua, NH). The wafers were stored under vacuum

until needed. Lyophilized plant samples were received from the Biology Department at

Duke University. The samples were stored at -80 ◦C till the analysis time.

2.2.2. Standard Solution Preparation

A stock solution of SA (1 M) was prepared by dissolving 0.279 g SA in 2 mL

. A stock solution of SA-d6 (0.7 M) was prepared by dissolving 0.1 g SA-d6 in 1 mL

CD3OD to eliminate hydrogen exchange. Both standard stock solutions were sealed and kept in a refrigerator. Fresh solutions of standards were prepared every week to ensure minimal

solvent losses. Successive dilutions were made daily to obtain desired concentrations, as

specified in the Result and Discussion section.

2.2.3 Extraction Procedure

Lyophilized wild type (wt) uninfected plant tissue (0.013 g) was added to 3 mL of

90% methanol, followed by vortexing for 1 min and sonicating for 5 min. After centrifuging

the mixture for 5 min, the supernatant was transferred to a 5-mL tube. The pellet left was

resuspended in 3 mL 100% methanol. Same steps were repeated. Both sets of supernatant

solutions were combined and centrifuged again to remove any particulates. Methanol in the

mixture was then vaporized using N2, till only 2 mL solution was left in the tube. Following the addition of 2.5 mL TFA (5% solution in water), two consecutive phase extraction was conducted by adding two portions of a 2.5-mL solvent mixture of ethyl acetate: cyclohexane

(1:1) to the above solution. The organic layers containing SA were separated from the aqueous layers and were combined in a 5-mL tube. 100 µL of 8 M HCl was added to the aqueous layer and the sample was heated in a water bath for 5 min. Again, 2.5 mL of ethyl

16 acetate: cyclohexane (1:1) was added to the aqueous layer for the third time and the organic

layer was combined with the first two organic layers. The sample was concentrated by

16 removing the solvent using N2 till it reached a final volume of 100 µL.

2.2.4 MS Analysis

During MALDI matrix selection, 10 mg of each matrix was dissolved in a 1-mL

solvent mixture (acetonitrile:water:TFA=50:49.9:0.1), except for sinapic acid where 20 mg

of the materials was dissolved in 1 mL solvent (acetonitrile:water:TFA=70:29.9:0.1). A

binary matrix mixture was also prepared by mixing two matrices at 1:1 (v/v).17 The matrix solution was prepared fresh before each experiment Table 2.1.

During MS detection, 5 nmol SA was mixed with 10 µL matrix and diluted to a total volume of 20 µL. Similarly, 7.5 nmol SA-d6 was mixed with 10 µL matrix and was diluted

to a total volume of 15 µL. Detailed sample preparation for the SA standard calibration

curve in water was described in Table 2.2, and the calibration curve spiked in plant extracts

was described in Table 2.3. 1 µL of the mixture was spotted on the MALDI plate in a

layered fashion to reduce surface heterogeneity and subsequently reduce the standard deviations of the MS measurements.

DIOS substrate was prepared by anodic etching. In particular, the oxide layer on

silicon was removed by soaking the substrate in 5% HF/ethanol for 1 min, followed by

rinsing with ethanol and drying by nitrogen. The silicon substrate was mounted in a Teflon

coated cell with one Au and two Platinum wires as the working counter and reference

electrodes respectively. A white light source was used as the illumination source and was

well focused. The etching solution contained 1.5 mL of 25% HF in ethanol. The etching

17 time was 2 min with a current density of 5 mA/cm2. After etching the substrate was soaked in a 15% H2O2/ethanol solution for 1 min, then cleaned with 5% HF in ethanol. The DIOS

substrate was stored in ethanol until needed. A drop of 1µL of 500 µM SA standard was spotted on the DIOS substrate, whereas 1 µL of water:acetonitrile solution was spotted on the side as the control.

The MALDI-MS and DIOS-MS measurements were performed with an Applied

Biosystem Voyager DE-STR TOF mass spectrometer. The samples were analyzed using an accelerating voltage of 20 kV and a delay time of 150 nsec. The ions were monitored in the linear negative ion mode. The mass window was from 65 to 150 m/z was monitored, where the molecular ion peak of SA, [SA-H]-, was located (m/z =137.13). The laser intensity was adjusted using a manufactory-provided neutral density filter. Ten spectra were accumulated per sample spot. Five replicates were measured at each SA concentration to calculate signal averages and standard deviations.

A linear regression analysis was conducted to fit standard curves. The limit of detection (LOD) of SA was calculated as MSLOD= Sbl+3×σbl and the limit of quantification

(LOQ) as MSLOQ= Sbl+10×σbl .

2.3 Results and Discussion

Two MS methods were tested in SA detection. Desorption Ionization on Porous

Silicon (DIOS), a surface based method to enhance the ionization, was evaluated first. The

absence of matrix molecules allows for small molecule detection with little background

noise, which simplifies spectrum interpretation. The elimination of MALDI matrices could

also simplify sample preparation. The DIOS substrate was prepared by anodic etching of

low resistivity Si, following the literature protocol.18 A mesoporous surface was formed after

18 2-min etching in a 25% HF/CH3CH2OH solution. Fig 2.1A shows a typical mass spectrum

collected from a DIOS surface with only solvent (water:acetonitrile) deposited. It was noted

that background peaks were observed at the same location where SA was expected to appear, as indicated by the asterisk label. The intensities of this peak were also found to vary from substrate to substrate and from detection to detection. It’s known that adsorb

on DIOS as impurities, that could cause higher backgrounds in the absence of analytes.18 In

the presence of the analyte, however, this noise level significantly decreases through

competitive detection. For example, SA was detected with a reasonable S/N ratio (Fig 2.1B).

Regardless, the presence of this background peak makes reliable quantification of SA in plant at a low concentration in plants challenging

MALDI-MS has been demonstrated capable of detecting low-mass molecules, if a matrix system was carefully chosen. For example, it has been reported that a binary matrix system, a mixture of matrices of different acidities, effectively reduced background signals.17

In addition, with knowing prior information on the analyte to be studied, a proper MALDI matrix can be selected to avoid overlapping with the detection of low-mass analytes. A combinatorial screening was designed in my study to identify suitable MALDI matrices

(Table 2.1). Three combinations (sinapic acid alone, 6-aza+sinapic acid and CHCA+sinapic acid) were identified to be suitable in SA detection (Figure 2.3). Among these options, the use of sinapic acid alone provided the best detection sensitivity with the lower energy input; thus was chosen as the matrix to be used in my further studies.

After optimizing the MALDI-MS matrix to be used, choosing an appropriate internal standard (IS) was the next factor studied for reliable SA quantification. The basic criteria for the successful IS require the compound exhibit a spectrometrically distinguishable MS peak

19 from that of the analyte; have similar ionization efficiency as the analyte to avoid biased

signal suppression when the sample background changes; and exhibit no chemical

19 interference to the analyte. An isotopic-labeled salicylic acid (DOC6D4COOD, MW

144.15, SA-d6) is used as the IS in my study for its chemically similar structure. It is

important to note that during sample preparation, two deuteria in the hydroxyl and carboxylic

groups were easily replaceable by the hydrogens in the matrix or the solvent that were

present in high concentrations.14 Consequently, under the negative-ion mode an IS peak of

HOC6D4COOH was expected at m/z=141.1, whereas the un-deuterated SA appeared at

m/z=137.1. No background peaks were observed at either peak positions (Figure 2.3).

Similar peak intensities observed for SA and SA-d4 at the same concentration confirmed the

use of SA-d4 as the proper quantification standard. Figure 2.4 shows that both SA and its IS

at the 20-pmol level were easily detectable when they were spiked in plant extracts,

suggesting negligible impact from the presence of complex biological samples.

To quantify the amount of SA in an unknown sample, a series of SA standard

solutions were prepared in water/ACN or in the plant extracts to construct standard

calibration curves (Table 2.2 and 2.3). The normalized MS responses (MSSA/MSSA-d4) were plotted as a function of the SA concentrations. Good linearity was obtained in both cases

2 with a correlation coefficient (R ) of 0.996 for SA in water/ACN (Fig 2.5A) and 0.985 in the

plant extracts (Fig 2.5 B). In both cases, a linear MS response was observed for the

concentrations between 0-40 µM. A slow level-off was observed at higher concentrations

due to saturation of MS detection. The (LOD) of SA in water was 0.73 µg/mL and the

calculated limit of quantification was 2.44 µg/mL. The LOD for SA spiked in the plant

extract was 1.4 µg/mL, LOQ was 4.7 µg/mL.

20 Method reproducibility is vital in analyte quantification since both DOL and DOQ are partially decided by the variation of measurements. In this study, two factors are primarily responsible for detection reproducibility: the consistency of mass spectrometric measurements of the same sample and that of the SA extraction process. To study the MS measurement reproducibility, SA was spiked to the same plant extract on separate days but same sample preparation was followed to obtain separate calibration curves for comparison.

Linear fitting of each calibration curve yielded following equations:

1- Y=0.268+ 0.0279X, R2= 0.982.

2- Y=0.359+ 0.023X, R2= 0.924.

3- Y= 0.246+ 0.083X, R2=0.970.

All three slopes and intercept values were in the 95% confident interval of each other. The calibration curve generated from the mean of these three different calibrations curves shows small standard deviations (Figure 2.6), suggesting that the MS response at each concentration in the three curves was sufficiently close and the MS measurement was reproducible.

To investigate the method precision a series of working samples with different amounts of standard SA added to the plant tissue before the extraction were used (Table 2.4).

The amount of the standard SA added covered a broad range of analyte concentrations to illustrate the dynamic range of the method. A fixed amount of Internal Standard (i.e. deuterated SA) was added before extraction to reduce the errors introduced during extraction.

The established extraction procedure was conducted as described in the experimental section.

A standard calibration curve was generated by plotting the MS signals as a function of SA added. The precision of the extraction was tested by repeating the exact assay on different

21 days (inter-day measurement). Table 2.4 shows the amount of SA added and the corresponding mass spectrometric response for each amount of SA added each day as well as the RSD% of the measurements. Figure 2.7 shows a linear correlation of the mass spectrometric response with the amount of standard SA added to 0.013 g plant tissue in the presence of SA IS. This data shows the reproducibility of the extraction method over a wide dynamic range that could be very beneficial in comparing different plant samples which contains different SA concentration. The standard error calculated from three independent runs in three different days which represent the inter-day precision the RSD% was ranged between (5-15%).

2.4 Conclusion

Here I have shown here that MALDI-MS is a viable method in SA detection. Sinapic acid is found to be a suitable matrix for both SA and its isotopic internal standard detection.

No chemical interference was observed from the matrix. The complexity of the plant extract does not affect the detection or quantification of SA using MALDI-MS. The MS detection takes 1 min per sample, much faster than the reported column-based separation methods. A detection limit of 1.4 µg/mL was demonstrated, sufficient to examine endogenous SA in plants. A good MS and extraction reproducibility for samples prepared on separate days was established.

22 2.5 References

(1) Malamy, J.; Carr, J. P.; Klessig, D. F.; Raskin, I., Salicylic-Acid - a Likely

Endogenous Signal in the Resistance Response of Tobacco to Viral-Infection. Science

1990, 250, (4983), 1002-1004.

(2) Shah, J., The salicylic acid loop in plant defense. Current Opinion in Plant Biology

2003, 6, (4), 365-371.

(3) Ribnicky, D. M.; Shulaev, V.; Raskin, I., Intermediates of salicylic acid biosynthesis

in tobacco. Plant Physiology 1998, 118, (2), 565-572.

(4) Wildermuth, M. C.; Dewdney, J.; Wu, G.; Ausubel, F. M., Isochorismate synthase is

required to synthesize salicylic acid for plant defence. Nature 2001, 414, (6863), 562-

565.

(5) Raskin, I.; Turner, I. M.; Melander, W. R., Regulation of Heat-Production in the

Inflorescences of an Arum Lily by Endogenous Salicyclic Acid. Proceedings of the

National Academy of Sciences of the United States of America 1989, 86, (7), 2214-

2218.

(6) Verberne, M. C.; Brouwer, N.; Delbianco, F.; Linthorst, H. J. M.; Bol, J. F.;

Verpoorte, R., Method for the extraction of the volatile compound salicylic acid from

tobacco leaf material. Phytochemical Analysis 2002, 13, (1), 45-50.

(7) Scott, I. M.; Yamamoto, H., Mass-Spectrometric Quantification of Salicylic-Acid in

Plant-Tissues. Phytochemistry 1994, 37, (2), 335-336.

23 (8) Yalpani, N.; Silverman, P.; Wilson, T. M. A.; Kleier, D. A.; Raskin, I., Salicylic-Acid

Is a Systemic Signal and an Inducer of Pathogenesis-Related Proteins in Virus-

Infected Tobacco. Plant Cell 1991, 3, (8), 809-818.

(9) Engelberth, J.; Schmelz, E. A.; Alborn, H. T.; Cardoza, Y. J.; Huang, J.; Tumlinson,

J. H., Simultaneous quantification of jasmonic acid and salicylic acid in plants by

vapor-phase extraction and gas chromatography-chemical ionization-mass

spectrometry. Analytical Biochemistry 2003, 312, (2), 242-250.

(10) Karas, M.; Bachmann, D.; Bahr, U.; Hillenkamp, F., Matrix-Assisted Ultraviolet-

Laser Desorption of Nonvolatile Compounds. International Journal of Mass

Spectrometry and Ion Processes 1987, 78, 53-68.

(11) Karas, M.; Bachmann, D.; Hillenkamp, F., Influence of the Wavelength in High-

Irradiance Ultraviolet-Laser Desorption Mass-Spectrometry of Organic-Molecules.

Analytical Chemistry 1985, 57, (14), 2935-2939.

(12) Karas, M.; Bahr, U.; Ingendoh, A.; Nordhoff, E.; Stahl, B.; Strupat, K.; Hillenkamp,

F., Principles and Applications of Matrix-Assisted Uv Laser Desorption Ionization

Mass-Spectrometry. Analytica Chimica Acta 1990, 241, (2), 175-185.

(13) Karas, M.; Hillenkamp, F., Laser Desorption Ionization of Proteins with Molecular

Masses Exceeding 10000 Daltons. Analytical Chemistry 1988, 60, (20), 2299-2301.

(14) Okuno, S.; Wada, Y., Measurement of serum salicylate levels by solid-phase

extraction and desorption/ionization on silicon mass spectrometry. Journal of Mass

Spectrometry 2005, 40, (8), 1000-1004.

24 (15) Muddiman, D. C.; Gusev, A. I.; Proctor, A.; Hercules, D. M.; Venkataramanan, R.;

Diven, W., Quantitative Measurement of Cyclosporine-a in Blood by Time-of-Flight

Mass-Spectrometry. Analytical Chemistry 1994, 66, (14), 2362-2368.

(16) Nandi, A.; Welti, R.; Shah, J., The Arabidopsis thaliana dihydroxyacetone

reductase gene SUPPRESSOR OF DESATURASE DEFICIENCY1 is

required for glycerolipid and for the activation of systemic acquired

resistance. Plant Cell 2004, 16, (2), 465-477.

(17) Zhong, G.; Lin, H., A binary matrix for background suppression in MALDI-MS of

small molecules. Analytical and Bioanalytical Chemistry 2007, 387, (5), 1939-1944.

(18) Wei, J.; Buriak, J. M.; Siuzdak, G., Desorption-ionization mass spectrometry on

porous silicon. Nature 1999, 399, (6733), 243-246.

(19) Muddiman, D. C.; Gusev, A. I.; Hercules, D. M., Application of secondary ion and

matrix-assisted laser desorption-ionization time-of-flight mass spectrometry for the

quantitative analysis of biological molecules. Mass Spectrometry Reviews 1995, 14,

(6), 383-429.

25 Table 2.1 The combinatorial list of different matrices screen in SA detection.

Matrix Used in Matrix Peaks at 250 pmol SA Laser Intensity

MALDI-MS m/z=137.13 detectable used to detect SA

6-aza Clean Yes 2116

THAP Clean Yes 3100

Sinapic Clean Yes 1716

CHCA Clean NO N/A

6-aza +THAP Clean NO N/A

6-aza +9AA Not clean N/A N/A

6-aza +CHCA Clean NO N/A

9AA+Sinapic Not clean N/A N/A

9AA +THAP Clean NO N/A

6-aza+sinapic Clean Yes 1575

CHCA +Sinapic Clean Yes 1575

26

Table 2.2: Sample preparation of SA calibration curve.

Volume of SA Volume of Solvent Matrix Final SA final

added (500 SA-d4 added (W:ACN) volume Volume Concentration µM) (250 µM) Volume(µL) (µL) (µL) ( µM)

(µL) (µL)

0 1.2 3.8 10 15 0

0.6 1.2 3.2 10 15 20

1.2 1.2 2.6 10 15 40

1.8 1.2 2.0 10 15 60

27

Table 2.3 Sample preparation table of standard SA spiked in the plant extract.

Volume of Volume of Solvent Plant Extract Matrix Final SA final

SA added SA-d4 (W:ACN) volume(µL) volume Volume Concentration

(500 µM) added (250 Volume(µL) (µL) (µL) (µM)

(µL) µM)

(µL)

0 1.2 2.8 1 10 15 0

0.6 1.2 2.2 1 10 15 20

1.2 1.2 1.6 1 10 15 40

1.8 1.2 1 1 10 15 60

28

Table 2.4 The calculated extraction efficiency for each amount of SA added to the plant tissue before the extraction. Three different independent assays were generated for each concentration to determine the inter-day precisions.

Amount of Relative MS Intensities

SA added

Mean SD RSD% µg/g Day1 Day2 Day 3

61.57 0.523 0.396 0.500 0.473 0.06 14.3

79.69 0.405 0.539 0.494 0.479 0.06 14.0

122.72 0.500 0.459 0.511 0.490 0.02 5.00

956.28 1.533 1.137 1.236 1.302 0.20 15.8

29

15,000 2000 * A

1000 10,000

0

135 140 145

5,000

MS Intensity

0 100 150 m/z

15,000 B

10,000 *

5,000

MS Intensity

0 100 150 m/z

Fig 2.1 (A) DIOS spectrum of the control where only the solvent was

deposited on a DIOS substrate. The background peak at where SA was expected was labeled with asterisk. The inset shows the zoom-in of the

region. (B) A DIOS spectrum of 500 µM SA. The SA peak was labeled with an asterisk.

30

15,000 A

10,000 *

5,000

MS Intensity

0 100 150 m/z

15,000 3000 2000 B 1000 * 0 10,000 135 140

5,000

MS Intensity 0 100 150 m/z

Fig 2.2 (A) A MALDI –MS spectrum of 250 pmol SA with sinapic acid as a matrix. The SA peak is labeled by an asterisk. (B) A MALDI-MS spectrum of sinapic acid as the control. Note that the asterisk in the zoom- in inset shows the relatively clean background in the area where SA will be expected.

31

COOD COOH

O D D D OH

D D D D

D D

SA -d6 SA-d4

6000 SA B 4000 SA-d4 12,000 2000 0 135 140 145 8,000

SA

SA-d4 4,000

MS Intensity

0 105 120 135 150 m/z

Fig 2.3 (A) The chemical structure of the internal standard SA-d6

and its proton exchange equilibrium with SA-d4. (B)The MALDI-MS spectrum of 20 pmol SA and 20 pmol SA-d6 using

sinapic acid as the matrix.

32

6000 25,000 SA SA-d4 3000 20,000 0 135 140 145 15,000

10,000

MS Intensity 5,000

0

100 150 m/z

Fig 2.4 The MALDI-MS spectra of 20 pmol SA and 20 pmol IS added in a wt uninfected plant extract. The inset show clear detection of both peaks.

33

2.4 Y=0.488X+0.0353 A 2.0 R2=0.996

1.6

1.2

0.8

0.4 MS RI(SA/SA-d4)

0.0 0 10203040

SA Concentration(µM)

2.4 2.2 Y=0.0302 X+0.232 B 2 2.0 R =0.985 1.8 1.6 1.4 1.2

1.0 0.8 0.6

MS RI(SA/SA/SA-d4) MS 0.4 0.2 0.0 0 10203040 SA Concentration(µM)

Fig 2.5 Linear calibration curves of standard SA detected (A) in water and

(B) spiked in a wt uninfected plant extract.

34

2.0 Y=0.0267x +0.2916 1.8 R2=0.970 1.6

1.4 1.2 1.0

0.8 0.6

MS RI(SA/SA-d4) 0.4 0.2

0.0 0 102030405060 SA concentration uM

Fig 2.6 Standard curve shows the MS measurement reproducibility. The standard error generated from three different acquisition dates for the standard SA spiked in the same wt uninfected plant extract.

35

1.6 Y= 0.001x +0.3835 2 1.4 R =0.995

1.2

1.0

0.8

0.6

MS RI(SA/SA-d4) MS 0.4

0.2 0 200 400 600 800 1000 Amount of SA added µg/g

Fig 2.7 Linear correlation of the amount of SA added before the extraction and the corresponding MS response.

36 CHAPTER 3

OPTIMIZATION OF SALICYLIC ACID EXTRACTION

3.1 Introduction

Various extraction protocols have been developed over the years to detect SA in

plants. The general scheme of these extraction methods is to grind plant tissue in the

presence/absence of liquid nitrogen, dissolve the mulch in 90% methanol, followed by

extraction of SA from the aqueous phase to the organic layer using an organic solvent. The

most commonly used method was developed by Raskin et al in 1989 to detect SA in Arum

lily . In their method, 1 g of the plant tissue was dissolved in 90% methanol, followed by

centrifuging. The pellet was resuspended in 100% methanol. Methanol was removed under

N2. Followed by phase separation using ethyl acetate /cyclopentane as the organic phase.

The organic solvent was dried completely using N2 gas. The sample was cleaned using a diol solid phase extraction (SPE) column. After collecting the elute, the cartridge was washed using ethyl acetate /cyclopentane. Two elutes were combined and dried using N2. The lyophilized analytes were resuspended in a HPLC mobile phase and then detected. The extraction recovery was 55% and detection limit of 10 ng/g fresh weight. 1 Similar extraction

method was conducted by Nasser in 1991 to detect SA in Tobacco using vacuum-assisted

solvent removal. The purification step was eliminated. The extraction efficiency was 45%

and the detection limit was 10 ng/g fresh weight. 2 Additional optimizations have been

reported by different groups with various successes.3,4 To date, the extraction efficiency of

SA from tobacco has been improved to 71-91%, mainly through the elimination of the

solvent removal step.5 A salt-free extraction method was also developed to be compatible to downstream mass spectrometric detection using acidified methanol.

37 In this chapter I report an optimized extraction method based on the one used by

Raskin et al. The amount of the plant tissue was significantly reduced and the volume of the

organic phase was significantly increased to exemplify tissue interactions with the solvent

and to allow maximum recovery of the analyte. Solvent evaporation was controlled to avoid

the losses occurred from the sublimation of the analyte. No column purification was needed

prior to MALDI detection to simplify the process and reduce analyte loss. 6 As a result the

extraction efficiency was improved to a 100% to ensure best detection sensitivity. The application of the developed method to quantify natural occurring SA in different plant samples was also demonstrated.

3.2 Experimental Section

3.2.1 Materials

Salicylic acid (SA, C6H4 (OH) CO2H, 99.0%) and sinapic acid were purchased from

Sigma-Aldrich (St.Louis, MO). SA-d6 was obtained from C/D/N isotopes (Quebec, Canada).

Methanol (CH3OH), ethyl acetate (CH3CH2OC(O)CH3 ) and Cyclohexane (99%) were

purchased from Fisher Scientific (Pittsburgh, PA). Deuterated methanol (CD3OD) was

purchased from Cambridge Isotope Laboratories (Andover, MA). Trichloroacetic acid was

purchased from Ricca Co. (Arlington, TX).

Lyophilized Arabidopsis leaves (wild type infected, wild type uninfected, PBS3 mutant infected and PBS3 mutant uninfected) were received from the Biology Department at

Duke University. The samples were stored at -80 ◦C till the analysis time.

38 3.2.2 Extraction procedure

Methanol of 3 mL (90%) was added to 0.013 g lyophilized plant tissue. The mixture

was mixed using a vortexer for 1 min, followed by 5-min sonication and 5-min

centrifugation. The supernatant was collected in a 5-mL tube. The pellet was resuspended in

3 mL of 100% methanol. The same steps described previously were followed and the

supernatants from both cycles were combined. The solution was centrifuged to remove

particulates. Methanol in the sample was evaporated to a final volume of 2 mL under a

nitrogen stream. Followed by addition of 2.5 mL trichloroacetic acid (5% solution in water),

liquid-liquid phase extraction was conducting by adding two portion of 2.5 mL ethyl acetate:

cyclohexane (1:1) to the above solution. The organic layers, which contained SA were

separated from the aqueous layer, and combined in a 5 mL tube. A solution of 8M HCl (100

µL) was added to the aqueous layer and the sample was heated into a water bath for 5 min.

2.5 mL of ethyl acetate: cyclohexane (1:1) was added again to the aqueous layer for extraction. The organic layer was separated and added to previous organic extracts. All the three organic layers were combined and the sample was concentrated by solvent removal under nitrogen gas. The final volume was adjusted to 20-100 µL.

In some cases 50 µL of the internal standard, SA-d6 (1 mM), was added to the lyophilized plant tissue a day before extraction, as specified in the text.

3.2.3 Instrument and Data Analysis

An Applied Biosystem Voyager DE-STR TOF mass spectrometer was used in

MALDI-MS measurements. Most measurements were carried out at 20 KV with a delayed

39 extraction of 150 nsec. The SA molecular ions were detected in a negative ion linear mode.

A mass window of m/z = 65-150 was monitored where the molecular ion peak of SA,

[SA-H] - was expected (m/z = 137.13). Laser intensity was adjusted using a manufacturer provided neutral density filter. Ten MS spectra were accumulated as one final spectrum from each spot. Five replicates from different spots were averaged for each tissue sample. Sinapic acid and SA standard solutions were prepared prior to MS measurements, as described in chapter 2. A standard calibration curve was obtained by spiking SA of known concentrations to the plant extract (Table 3.1). The mixtures of 1 µL each were spotted atop a thin layer of sinapic acid on the MALDI target plate. Linear regression was used to fit the standard curves. The amount of SA recovered was calculated using the regression equation generated from the standard curve.

3.3 Results and Discussion

Figure 3.1 shows a MALDI MS spectrum of wt infected plant sample prepared using the Raskin method. Wt infected plant was chosen here to insure sufficient amount of SA accumulate after infection. To allow MALDI-MS detection. It is important to note that although the plant extract was very complex, the natural occurring SA was directly detectable without prior sample clean up. This observation suggests that a liquid-liquid extraction method is sufficient to isolate SA and that few background species in MS were most likely suppressed in the negative-mode MS detection. The classic Raskin method calls for 1 g of starting plant materials for a final plant extract volume of 5.5 mL to be concentrated for

HPLC detection. Given the fact that as low as 1 µL plant extract was sufficient for MALDI detection, an improved method was needed to reduce the amount of plant tissue used in a single experiment. In addition to reduce the amount of solvent to be used, the use of a

40 smaller scale of starting material also reduced sample preparation time and allow the use of

fewer plant samples that eliminated biological variations during method development.

Methanol has been selected as the ideal solvent that effectively breaks the and exhibit good solubility for SA in the plant tissue. The amount of Ethyl acetate: cyclohexane to be used to extract the analyte from the aqueous phase was decided by balancing between achieving maximum extraction efficiency of an often unknown amount of

SA and minimizing unnecessary loss when too much solvent was used. Quantitative study was conducted to determine the suitable extraction volume which provides higher recovery.

Series of experiments was conducted to establish a SA calibration standard curve by spiking different amounts of SA into the plant extracts collected at different conditions (Fig 3.2) in which different volumes of organic solvents were used. The curves allowed later retro- calculation of the amount of SA recovered. Linear plots with R2 0.9895, 0.9924 and 0.9936

were obtained in the range of 0 to 60 µM for each plant extraction conditions. Known

amounts of SA were then added to the ground plant tissues before extraction. That covered

a wide dynamic range of the expected concentration of SA in the plant sample (table 3.2).

The internal standard was added after the extraction. The extraction efficiency at each

spiked SA concentration was calculated as a percentage of the recovered SA, calculated from

the regression equation of the standard calibration curve, to the original amount added to the

sample. Concentration-depended extraction efficiency was observed when an extraction

volume of 0.75 mL was used, the same volume ratio as in the Raskin method. An increase

in SA concentration was not accompanied by an increase in Mass spectrometric response as

it was expected, due to saturation of the organic solvent. An increase in solvent volume significantly improved. The extraction efficiencies reached ~100% for the range of spiked

41 SA examined when 6 mL methanol was used. Figure 3.3 shows the summarized data when

different extraction volumes were used. Given the anticipated SA concentrations in infected

plant to be <22.1 µg/g fresh weight.7 The use of 6 mL extraction volume should be sufficient to effectively extract endogenous SA in the plant samples.

3.3.2 Applications:

The method applicability of SA quantification was tested in Figure 3.5, in which the

endogenous SA in wt uninfected, wt infected, PBS3 mutant uninfected and PBS3 infected

were measured. Separate calibration curves were generated for each plant sample. Here the

method applicability of detecting and quantitation the natural occurring SA in four different

plant samples was proved. Differences were observed for the calculated amounts of SA

present in different samples, the significant increases in SA present in wt plant after the

infection fit well with the reported results. A reduction in SA expression in the transmutant

plant PBS3 was also consistent with the literature report of the defected processing of SA in

PBS3.8 The drastic concentrations difference between wt uninfected and PBS3 uninfected

however is not understood. It is important to note that to reach an ambiguous conclusion of

biological significant, more replicates from plants of the same growth conditions need to be

studied to take in account of biological fluctuations.

Nevertheless, the developed method has proven to be sensitive, reproducible, and

fast. Employment of such a method to address biological problems is feasible when more

plant samples are available.

42 3.4 Conclusion

The data show that the extraction efficiency is a concentration dependant.

Phenomena that can be improved by optimize solvent volume. A quantitative study was conducted to determine the suitable extract volume that achieved better extraction recovery.

In addition the amount of plant tissue used per experiment was reduced by a factor of

8 without comprising the detection sensitivity.

The applicability of the method in detecting the endogenous level of SA in four different plant samples was also demonstrated.

43 3.6 References

(1) Raskin, I.; Turner, I. M.; Melander, W. R., Regulation of Heat-Production in the

Inflorescences of an Arum Lily by Endogenous Salicyclic Acid. Proceedings of the

National Academy of Sciences of the United States of America 1989, 86, (7), 2214-

2218.

(2) Yalpani, N.; Silverman, P.; Wilson, T. M. A.; Kleier, D. A.; Raskin, I., Salicylic-Acid

Is a Systemic Signal and an Inducer of Pathogenesis-Related Proteins in Virus-

Infected Tobacco. Plant Cell 1991, 3, (8), 809-818.

(3) Enyedi, A. J.; Yalpani, N.; Silverman, P.; Raskin, I., Localization, Conjugation, and

Function of Salicylic-Acid in Tobacco During the Hypersensitive Reaction to

Tobacco Mosaic-Virus. Proceedings of the National Academy of Sciences of the

United States of America 1992, 89, (6), 2480-2484.

(4) Gaffney, T.; Friedrich, L.; Vernooij, B.; Negrotto, D.; Nye, G.; Uknes, S.; Ward, E.;

Kessmann, H.; Ryals, J., Requirement of Salicylic-Acid for the Induction of Systemic

Acquired-Resistance. Science 1993, 261, (5122), 754-756.

(5) Verberne, M. C.; Brouwer, N.; Delbianco, F.; Linthorst, H. J. M.; Bol, J. F.;

Verpoorte, R., Method for the extraction of the volatile compound salicylic acid from

tobacco leaf material. Phytochemical Analysis 2002, 13, (1), 45-50.

(6) Nandi, A.; Welti, R.; Shah, J., The Arabidopsis thaliana dihydroxyacetone phosphate

reductase gene SUPPRESSOR OF FATTY ACID DESATURASE DEFICIENCY1 is

required for glycerolipid metabolism and for the activation of systemic acquired

resistance. Plant Cell 2004, 16, (2), 465-477.

44 (7) Freeman, J. L.; Garcia, D.; Kim, D. G.; Hopf, A.; Salt, D. E., Constitutively elevated

salicylic acid signals glutathione-mediated nickel tolerance in Thlaspi nickel

hyperaccumulators. Plant Physiology 2005, 137, (3), 1082-1091.

(8) Nobuta, K.; Okrent, R.A.; Stoutemyer.M.; Rodibaugh, N.; Kempema,M.C.;

Wildermuth, M.C.;

Innes, R.W., The GH3 Acyl Adenylase family member PBS3 regulates Salicylic acid-

dependent

defense responses in Arabidopisi.Plant Physiology 2007, 144, 1144-1156.

45

Table 3.1 Sample preparation table of standard calibration curve used to calculate the amount of SA recovered after the extraction.

Volume of Volume of Solvent Plant Matrix SA final SA added SA-d4 added Volume Extract Final volume Concentration (500 µM) (250 µM ) ( µL ) volume Volume(µL) ( µL) ( µM ) (µL) ( µL ) (W:ACN) ( µL )

0 1.2 2.8 1 10 15 0

0.6 1.2 2.2 1 10 15 20

1.2 1.2 1.6 1 10 15 40

1.8 1.2 1 1 10 15 60

46 Table (3.2) shows the change in the extraction efficiencies with respect to the extraction volume.

The calculated Extraction Efficiency % when the extraction No of µL of amounts of volume(mL) is standard SA standard SA added added to the plant (500 µM) tissue( µg /g) 0.75 1.5 6.0

11.59 32 NA 80.0 90.7

23.18 64 69.7 73.6 104.0

30.00 82 32.2 51.2 113.9 46.20 128 28.4 37.8 N/A

47

20000 SA-d4 60,000 15000

10000 SA 5000 0 45,000 135 140 145

30,000

15,000 MS Intensity * 0 100 150 m/z

Figure 3.1 MALDI-MS spectrum of wt infected plant extract. The highlighted region shows the region where the natural occurring SA in the plant spectrum. The zoom in, shows the natural occurring SA peak and SA-d4 peak.

48

2.8 0.75mL 1.50mL 2.4 6.00mL 2.0

1.6

1.2

0.8

RI (SA/SA-d4)MS 0.4

0.0 0 102030405060 SA concentration µM

Fig 3.2 The calibration curves used to calculate the amounts of SA recovered after the extraction. One calibration curve was generated for each extract volume used in the extraction procedure; during the quantitative study to determine the extract volume which provides higher extraction recovery.

49

120 64 (µg SA/g DW) 110 82 (µg SA/g DW) 100 128(µg SA/g DW)

90 80

70 60 50

efficiency Extraction 40 30

20 0123456 Volume added(mL)

Figure 3.3 Concentration dependant extraction efficiency. The extraction efficiency increases with the extract volume increases.

50

70

60

50

40

30

20 Endogenous SA (µg/g DW) Endogenous 10

0 wt uninfected wt infected PBS3 uninfected PBS3 infected

Fig 3.4 The calculated natural occurring SA in wt uninfected, wt infected, PBS3 uninfected and PBS3 infected.

51 CHAPTER 4

AN SYSTEMATIC INVESTIGATION OF THERMAL CONTRIBUTION INSURFACE-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY (SALDI-MS) USING ORDERED NANOCAVITY ARRAYS

4.1 Introduction

Surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) has been

demonstrated for small molecule detection.1-5 The technique is based on the use of UV- absorbing materials to facilitate desorption and ionization of small molecules under laser irradiation without introducing background peaks in the low mass region. Inorganic media, such as Au nanoparticles, ZnO, TiO2, Si, SiO2 nanoparticles, active carbon, and carbon

nanotubes, have all been evaluated as effective SALDI-MS substrates in promoting desorption and ionization of analytes of interest. Among the materials tested, porous silicon-based surface, as in Desorption/ Ionization on Silicon (DIOS), has been the most popular choice by far because of its ease of preparation, good sensitivity, and flexible surface chemistry to be derivitized to allow subsequent sample clean-up via solid phase extraction.4-8

Small pharmaceutical drugs, , and polymers have been successfully detected with adequate sensitivity; thus allow universal detection of low mass species that are not always accessible using the conventional MALDI technique.6

It is commonly agreed that the presence of a roughened surface is a prerequisite to the

observed desorption efficiency in SALDI-MS (including DIOS).9, 10 How the roughed

surface participates in surface energy transfer to promote analyte desorption in MS

measurements, however, is still under discussion. Giving there is a plethora of information

52 available in the literature on how the thermal and electronic properties of a Si wafer change when its porosity increases.11 it is speculated that the surface feature-dependent electronic

and thermal properties to be the main attributors to the observed non-ablative laser

desorption ionization-MS. For example, in a photo-thermal model the transformation of

photon energy to thermal energy was suggested to result in the abrupt increase of local

temperatures, then the subsequent thermal excitation leads to surface-absorbed analyte

desorption. Multiple groups have qualitatively disscussed the correlation between the local

temperature increase and the observed MS performances, and have estimated the importance

of thermal excitation based on the thermal parameters of corresponding bulk materials. 12, 13

Conversely, different opinion has been expressed by Paltauf et al, in which the importance of thermal contribution was considerably smaller due to the fact that little thermally induced fragmentation was observed in SALDI-MS. This notion is supported by the findings that in matrix-assisted laser desorption/ionization (MALDI)-MS thermal excitation is fundamentally constrained by the matrix properties, such as matrix crystal size, matrix energy coupling efficiency, matrix-analyte incorporation, etc, and only plays minor roles.14

In this work, I have continued a previous group member 15(Nancy Finkel’s ) study on

the measurements of the substrate temperature changes as a function of surface porosity to qualitatively address the involvement of thermal excitement in SALDI-MS. To systematically varying surface features, I used nanosphere-based lithographic method to reproducibly generate porous Si substrates with tunable pore geometries and densities. 15 In

particular, a close-packed nanoparticle array was formed on a low resistance Si wafer via

evaporation-induced self assembly, i.e. convective assembly. The highly packed

nanoparticle monolayer was then used as a mask to selectively protect portions of the Si

53 surface underneath whereas a mixture of SF6/O2 plasma was used to remove the exposed region in reactive ion etching (RIE). Following RIE, the nanoparticle mask was removed by vigorous sonication, leaving ordered triangle-shaped nanocavities on the surface with pre- determined pore sizes and inter-feature spacing. The temperature increases upon laser irradiation was measured using an infrared CCD camera in a thermographic imaging mode.

The MS measurements of various analytes from the same set of substrates were recorded.

The correlations between MS responses, the degree of surface temperature changes, and substrate porosities were examined

4.2 Experimental

4.2.1 Materials

The COOH-derivatized polystyrene (PS) beads of 170 and 300-nm diameters were purchased from Bangs Lab (Fisher, IN) and used as received. Antimony-doped (100) single- crystalline silicon wafer at 0.002-0.005 Ω/cm were purchased from Silicon Sense, Inc.

(Nashua, NH). The wafers were stored under vacuum until needed. Hydrofluoric acid (HF,

49%), H2SO4, H2O2 (30%), and CH3OH (HPLC grade) were purchased from Fisher

Scientific (Pittsburgh, PA). CH3CH2OH was purchased from Aaper Alcohol (Shelbyville,

KY). Trifluoroacetic acid (TFA) were purchased from Sigma Aldrich (St. Louis, MO). 1,2-

Dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) was purchased from Avanti Polar Lipids,

Inc.(Alabaster, AL). DI H2O of 18 MΩ (Millipore, PO) was used throughout the experiments.

54 4.2.2 Substrate preparation

The ordered nanocavity arrays were prepared following the protocol reported

previously. Briefly, a silicon wafer was cut into several 1”× 1” squares, followed by removal

of the oxide layer by soaking the silicon wafer in 5% HF/CH3CH2OH solution for 1 min.

The silicon wafer was then soaked in a piranha solution (H2SO4:H2O2= 3:1, hazard solution!)

for 2 hr to remove any organic residuals and yield a thin layer of freshly oxided surface.

After rinsing the substrates in copious amounts of water, the substrates were dried in an oven

at 70◦ Cfor 1 hr. One of the Si wafers was then placed on a linear stage controlled

by a syringe pump and a cleaned microscope glass slide was leaned on the wafer at a 30-

degree angle. The nanoparticle solution of the original concentration (10% by weight, 10-15

µL) was deposited under the microscope slide and the particles were spread on the wafer at a constant rate, controlled by movement of the syringe pump. The typical spreading rate was

10-45 µL/s, depending on the size of the nanoparticles used. Reactive ion etching (RIE,

Semi Group system 1000 TP) was used to transfer the mask feature to the silicon wafer surface. The rf power to generate the plasma was set at 100 W. The chamber pressure was at 50 mTorr. The etching gases SF6 and O2 were set at flow rates of 15 and 5 standard

centimeters cubed per min (SCCM). The etching time varied between 0.5 to 20 mins,

depending on the final features desired. After etching, the nanoparticle mask was removed

by sonicating the substrate in EtOH for 30 min. The substrates were stored in ethanol until

SALDI-MS analysis.

55 4.2.3 Field-Emission Scanning Electron Microscope (FE-SEM) Imaging

A FEI XL30 SEM-FEG FE-SEM was used to examine substrate features. The

working voltage was set at 5 kV with a working distance of ~5 mm. Different imaging

magnification was achieved by varying the working distance. To image the cross-section of

the etched features, the Si wafer was broken in the middle and placed on an Al block.

Approximately 20-80 pores from each surface were randomly selected to measure the size

distribution of surface features.

4.2.4 Thermal Measurements

A ThermaCAM SC3000 instrument (FLIR Systems, North Billerica, MA) was used

to measure the surface temperatures of substrates. An Ar laser of 514 nm was used as the

irradiation source for surface heating. The continuous wave laser was used in place of a

2 typical MALDI laser (N2 laser, 5-ns pulse, 337 nm, and laser fluence of 10-30 mJ/cm )

because of the low frame rate of the ThermaCAM SC3000 camera. The laser power was

measured at 1 W, and the incident beam was set at a 45-degree angle. The infrared camera

was oriented orthogonal to the substrate to reduce possible surface reflection. The camera

was stabilized on a x-z translational stage to optimize camera-surface distance. The substrate

was placed approximately 10 cm from the infrared camera. The substrates were heated by

laser irradiation for 5 sec, followed by manual blocking of the laser beam. The temperature changes as a function of time were recorded by a computer. The temperature changes were calculated as the difference between the baseline of the temperature profile and the maximum

56 temperature reached after 5-sec heating. The temperature changes at five different positions

on each substrate were averaged.

4.2.5 Mass Spectrometry Measurements

SALDI-MS analysis was conducted using an Applied Biosystem Voyager DE-STR

Time-of-Flight (TOF) Mass Spectrometer (Foster City, CA). DPPC was deposited on the

SALDI surface at 1 uL each as triplicates and dried in air before MS analysis. The samples

were analyzed in a linear mode and the spectra were collected for the 50-500 m/z range. The

MS conditions were optimized with an extraction voltage of 20 kV, the grid voltage of 96%, and a delay time of 150 ns. An average of 10 shots/spectrum for DPPC was used. The signal-to-background ratio (S/N) of each analyte was calculated using Data ExplorerTM, the

data processing software provided by the instrument manufacturer. A S/N value >50 was

used as the criterion for MS performance comparison, unless otherwise stated. The laser

fluence was measured using a FieldMax-P laser power meter (FieldMax, Coherent, Inc)

outside of the sample chamber to avoid disruption of the chamber vacuum.

4.3 Results and Discussion

4.3.1 Substrate Fabrication

Nanosphere lithography in combination with reactive ion etching is a relatively

simple and inexpensive method to generate ordered features in the sub-micrometer scale.

Carboxyl-coated polystyrene beads of 170 and 300 nm in diameters were used as the masks

57 to prepare the nanocavity arrays for its narrower size distribution and better resistant to plasma etching. As previously described, negatively charged nanoparticles were self- assembled into a highly ordered and closely packed monolayer in a convective assembly setup under the optimal solution concentration and the spreading rate. The substrates were placed in a RIE chamber where the exposed Si surface in-between the beads was selectively etched by a combination of SF6 and O2 gas. The later removal of the particle mask revealed the cavity arrays underneath. Figure 4.1 shows a few representative field-emission scanning electron microscopic (FE-SEM) images of the nanocavity arrays of different pore size and inter-pore spacing. The hexagonal surface patterns in Figure 4.1 A and 4.1C correlated well to that of close-packed spherical beads. Because the plasmon ions that bombarded on the mask particles were scattered to random directions, an isotropic etching of surface features was observed and the feature width changed over time (Figure 4.1B). Furthermore, extensive etching slowly eroded away the Si materials under the masking particles and the residual surface became isolated posts and then pointy needles (Figure 4.1D). Eventually, the ordered surface features disappeared, and the remaining surface was left with randomly roughed features (Figure 4.1E &F).

After measuring the pore sizes, depths, and pore densities of the features on each substrate from their FE-SEM images, Table 4.1 shows the calculated mass change for the obtained substrates based on theoretical geometric equations. In particular, approximately 80 pores were counted from SEM images in a 1 × 106 nm2 area when the 170-nm beads were used as the mask and approximately 25 pores with the 300-nm beads. An invert pyramidal model was used to proximate the pores for the substrates etched for less than 1 min and a cylindrical one for those etched for more than 1 min.15 The total pore volume was calculated

58 from the measured pore depth and width and the volume porosity was calculated as a

percentage of the total pore volume against the original substrate volume. A linear

relationship was observed when the volume porosity was plotted as a function of etching

time at the early stage of RIE (Fig 4.2). The slope of the linear fitting was the actual etching

rate on the substrate, and a 2.7:1 ratio was obtained for the substrates prepared using a 170- nm bead mask (porosity%=-5.4+17×time (min)) vs. those using a 300-nm bead mask

(porosity%=-0.48+6.4×time (min)). Although larger particles were used as the mask in the latter case where a bigger surface area was exposed, the total number of pores is less than that of using 170-nm beads by a factor of 3.2.

4.3.2 Surface Temperature Measurements

The amount of energy emitted by an object is related to its thermal emissivity and the blackbody temperature, as described in the Planck’s law. A simplified version as described in the Stefan-Boltzmann’s law shows that a direct correlation exists between the measured energy and the substance temperature : J = ε·σ·T4, where J is the total energy radiated per

unit area in a time unit, ε the emissivity of the blackbody which equals to 1 in a perfect

blackbody, σ the Stefan’s constant, and T the absolute temperature. 16 Based on this

equation, an infrared detector is commonly used to monitor thermal radiation emitted from a

heated item in a non-invasive fashion to estimate the corresponding surface temperature, a

technology termed as thermography. Under the Stefan-Boltzmann’s law the blackbody can not transmit or reflect the light, it absorbs all the light that causes thermal excitation. The amount of energy emitted from any object depends on its surface temperature that caused by thermal excitation. Regular objects can absorb, transmit and reflect the incident light, and the amount of energy emitted depends on its emissivity. In my study the total amount of

59 laser irradiation energy reached the substrates was exculpated to be constant during a given

period of time. The different surface geometries of substrates of (different porosities) were

expected to have different emissivities that led to different thermal excitation, observed as different temperatures according to Stefan-Boltzmann’s law. 16

Figure 4.3A shows the instrument setup used in our study: a thermaCAM SC 3000

camera that collected the thermal images at a rate of 900 Hz was used to capture the

temperature changes in real time. This response rate ( ms) did not allow ns fast image

capturing; therefore a continuous-wave (CW) Ar laser with a 514-nm beam wavelength was

used in place of the typical ns-pulsed N2 laser used in MALDI to slow down the heating

process. The laser incident angle was set at 45 degree and was reflected into a beam block.

The camera was placed 10 cm away from the surface at a 90-degree angle and the measured

infrared emission was automatically converted to the surface temperature by the instrument

software. A typical temperature profile from a bare silicon surface was shown in Figure

4.3B: The recording of the substrate temperature started before laser irradiation to obtain a

steady baseline. The substrate was then exposed to the laser beam for 5 sec, followed by the

blockage of the laser beam to allow the substrate equilibrate back to the room temperature.

The surface temperature change was calculated as the difference between the peak temperature after 5-sec heating and the initial substrate temperature. A 5-point measurement across the substrate (one from the center location, one from each corner at 1-cm away from the center) showed that the temperature differences were well within a 95% confidence interval, which suggested a negligible temperature gradient present across the substrate. The temperature changes at these five points were therefore averaged and used in further discussions. It is important to note that the temperature changes from the instrument setup

60 described here were much lower than what were expected during actual SALDI-MS

experiments due to following reasons: (1) the use of the CW Ar laser provided ~1.5 x 105

J/cm2 energy from the photons during 5-sec irradiation with an average power of 104 W/cm2.

On the other hand, during SALDI-MS measurements, 10 shots of ns-sec pulse laser firing although only led to ~300 mJ/cm2 energy transferring; a peak power of more than 106 W/cm2 was introduced at each pulse. Consequently, a much higher local temperature is expected during SALDI measurements. (2) Second, Si surfaces had lower absorption coefficient at the visible range, whereas a more efficient energy transfer was expected when the 337-nm N2 laser was used in SALDI-MS measurements. (3) Additional environmental factors, such as the surrounding temperature and the pressure in the sample chamber, differed from those during thermographic measurements and subsequently affected the absolute temperature readouts. Nevertheless, the substrate temperature changes were expected to qualitatively correlate to the substrate behavior during SALDI-MS measurements, therefore were adequate to address the impact of the thermal effect on MS.

Figure 4.4 shows a semi-linear correlation was obtained after plotting the changes in

temperature as a function of the volume porosity for 170-nm bead-coated substrates, with

higher surface temperatures accompanied with increased surface porosities. This observation

was in agreement to the reported study where a decrease in Si thermal conductivity was

measured with increasing surface defects.17 Shen et. al suggested that the pores in Si

substrates acted as insulating air pockets between the continuous Si crystals as well as the

local traps that confined the movement of conducting electrons. For example, they have

measured a thermal conductivity of Si drop from 150 W/m.K of a smooth Si surface to 1.2-2

W/m.K for the same substrate but with 2-5-nm pores. This change in thermal conductivity

61 would corresponded to a ~10-fold increase in the local surface temperature change upon

heating.10 Similar monotonic increase in surface temperatures was observed for the surfaces prepared using 300-nm bead-coated mask, but a significantly deviation from the linear increase was observed.

4.3.3 Substrate Mass Spectrometry Measurements

Three MS spectral characteristics were used to evaluate the substrate MS performance: the absolute ion current of the MS peak of interest, its signal-to-background ratios (S/B), and the laser fluence threshold in which the minimal laser energy was needed to reach a calculated S/B=50. DPPC was used as the standard molecule to evaluate the MS performance of the nanocavity Si arrays. DPPC at 100 pmol was directly spotted on the

SALDI substrates, and the MS spectra were collected under different laser intensities at 200 step, adjusted by a neutral density filter. The ion intensity of the major DPPC fragment

(m/z=184.1) was plotted as a function of the irradiation laser intensities in Figure 4.5 A, where an increase in laser energy input led to an increase in MS ion currents. The more porous the substrate was, the stronger MS signal was, until all MS responses disappeared when the laser intensity was raised beyond 2,500 (a.b.). This was because of sever fragmentation of the analyte under the high laser intensity. Under the same irradiation energy, the substrate of higher volume porosity was more effective in analyte ionization and a lower laser threshold was needed. All findings were in a good agreement with the reported notion that lower excitation energy was needed for substrates of higher porosities. Giving the previous observation that the surface temperatures also correlated with the substrate porosity linearly, it is not surprising to see that for the ordered surfaces, an increase in surface

62 temperature accompanied monotonically with the improved MS detection (Figure 4.6). A question then arises: were the changes in the substrate temperature the determining factor for the observed MS responses; or the temperature changes simply concurred with the improved

MS performance, but in no direct relationship, i.e. other substrate porosity-dependent factors were more crucial during the SALDI measurements?

I suspect the temperature change is less important than what has been postulated to date. In particular a set of experiments where, the over-etched substrates were used for

DPPC detection under the same ms conditions similar macroscopic temperature changes as the ordered nanocavity surface upon laser irradiation, the measured MS S/B ratio however was much lower than that from an ordered nanocavity arrayed surface was observed, mainly due to an elevated noise level in the background (Figure 4.6). The presence of this temperature-independent MS response suggested the co-existence of different mechanisms in analyte ionization; and the thermal property of the substrates could be a but can not be a major one for analyte ionization. Two surface shared same surface temperature, same laser excitation, yet exhibited different MS responses suggest that the surface geometry it self has more influence on the MS response. In addition, the amount of analyte molecules presented under the laser beam was proportional to the increased total surface area, whereas the temperature increases were expected to be proportional to a quarter root of the surface area. The data presented here suggest that the MS signal was directly related to the amount of analytes under the laser beam, i.e. direct correlation to the total surface area.

4.4 Conclusion

We report here a systematic approach to studying the influence of the surface thermal property on the observed SALDI-MS responses. The results have suggested that the surface

63 porosity of Si is the key factor in desorption/ionization efficiency in SALDI-MS analysis.

MS signals could only be collected when the laser fluence exceeds certain threshold, which is

in direct correlation with the surface porosity. But the change in surface temperature did not

direct correlate with the observed MS responses.

Additional factors to be considered include the electronic structure of the surface. A

detailed examination of the FE-SEM images of the SALDI substrates of ordered arrays vs.

random features shows the presence of sharper edges for the latter. These sharp edges

experienced much intense electromagnetic field. In addition, the change of work function of

Si substrates at these defect sites inevitably affects surface electron affinity, as well as the electronic state of the analytes adsorbed on the surface. As a result, both field desorption efficiency and electron emission efficiency of a roughed surface are expected to vary as a function of surface protruding features’ curvatures. While no direct evidence is shown in this study, a field desorption-like SALDI phenomenon has been discussed previously; the emission of photoelectrons that neutralize preformed ions before desorption has been suggested; and the formation of the positively charged surface layer from the loss of electrons has also been suspected to stabilize preformed analyte ions and facilitate ion ejections. Together, more electronic structure-dependent and less thermal dependent MS responses were not unexpected for the substrates of random roughness.

64

4.5 References

(1) Xu, S. Y.; Li, Y. F.; Zou, H. F.; Qiu, J. S.; Guo, Z.; Guo, B. C., Carbon nanotubes as

assisted matrix for laser desorption/ionization time-of-flight mass spectrometry.

Analytical Chemistry 2003, 75, (22), 6191-6195.

(2) Michalak, L.; Fisher, K. J.; Alderdice, D. S.; Jardine, D. R.; Willett, G. D., C60-

Assisted Laser Desorption-Ionization Mass-Spectrometry. Organic Mass

Spectrometry 1994, 29, (9), 512-515.

(3) Hopwood, F. G.; Michalak, L.; Alderdice, D. S.; Fisher, K. J.; Willett, G. D., C-60-

Assisted Laser Desorption/Ionization Mass-Spectrometry in the Analysis of

Phosphotungstic Acid. Rapid Communications in Mass Spectrometry 1994, 8, (11),

881-885.

(4) Go, E. P.; Shen, Z. X.; Harris, K.; Siuzdak, G., Quantitative analysis with

desorption/ionization on silicon mass spectrometry using electrospray deposition.

Analytical Chemistry 2003, 75, (20), 5475-5479.

(5) Lewis, W. G.; Shen, Z. X.; Finn, M. G.; Siuzdak, G., Desorption/ionization on silicon

(DIOS) mass spectrometry: background and applications. International Journal of

Mass Spectrometry 2003, 226, (1), 107-116.

(6) Shen, Z. X.; Thomas, J. J.; Averbuj, C.; Broo, K. M.; Engelhard, M.; Crowell, J. E.;

Finn, M. G.; Siuzdak, G., Porous silicon as a versatile platform for laser

desorption/ionization mass spectrometry. Analytical Chemistry 2001, 73, (3), 612-

619.

65 (7) Wei, J.; Buriak, J. M.; Siuzdak, G., Desorption-ionization mass spectrometry on

porous silicon. Nature 1999, 399, (6733), 243-246.

(8) Go, E. P.; Prenni, J. E.; Wei, J.; Jones, A.; Hall, S. C.; Witkowska, H. E.; Shen, Z. X.;

Siuzdak, G., Desorption/ionization on silicon time-of-flight/time-of-flight mass

spectrometry. Analytical Chemistry 2003, 75, (10), 2504-2506.

(9) Kruse, R. A.; Li, X. L.; Bohn, P. W.; Sweedler, J. V., Experimental factors

controlling analyte ion generation in laser desorption/ionization mass spectrometry on

porous silicon. Analytical Chemistry 2001, 73, (15), 3639-3645.

(10) Alimpiev, S.; Nikiforov, S.; Karavanskii, V.; Minton, T.; Sunner, J., On the

mechanism of laser-induced desorption-ionization of organic compounds from etched

silicon and carbon surfaces. Journal of 2001, 115, (4), 1891-1901.

(11) Lu, X.; Shen, W. Z.; Chu, J. H., Size effect on the thermal conductivity of nanowires.

Journal of Applied Physics 2002, 91, (3), 1542-1552.

(12) Sunner, J.; Dratz, E.; Chen, Y. C., Graphite Surface Assisted Laser

Desorption/Ionization Time-of-Flight Mass-Spectrometry of Peptides and Proteins

from Liquid Solutions. Analytical Chemistry 1995, 67, (23), 4335-4342.

(13) Dale, M. J.; Knochenmuss, R.; Zenobi, R., Graphite/liquid mixed matrices for laser

desorption/ionization mass spectrometry. Analytical Chemistry 1996, 68, (19), 3321-

3329.

(14) Paltauf, G.; Dyer, P. E., Photomechanical processes and effects in ablation. Chemical

Reviews 2003, 103, (2), 487-518.

66 (15) Finkel, N. H.; Prevo, B. G.; Velev, O. D.; He, L., Ordered silicon nanocavity arrays in

surface-assisted desorption/ionization mass spectrometry. Analytical Chemistry 2005,

77, (4), 1088-1095.

(16) Cerruti, M. G.; Sauthier, M.; Leonard, D.; Liu, D.; Duscher, G.; Feldheim, D. L.;

Franzen, S., Gold and silica-coated gold nanoparticles as thermographic labels for

DNA detection. Analytical Chemistry 2006, 78, (10), 3282-3288.

(17) Shen, Q.; Takahashi, T.; Toyoda, T., Characterization of optical and thermal

properties of porous silicon using photoacoustic technique. Analytical Sciences 2001,

17, S281-S283.

67

Table 4.1 shows etching time and the calculated volume porosity for each substrate. The particle size used in the mask was 170 nm

Etching time Pore area Pore depth Number of volume

(min) (nm2) (nm) pores porosity%

0.5 1160 39 80 3.89

1.0 3753 89 80 10.00

1.5 7910 39 80 21.23

2.0 11680 318 80 28.48

68

A B

C D

E F

Fig 4.1 Representative FE-SEM images of Si substrates of different nanocavity arrays. The substrates were prepared using 170 nm polystyrene beads as the mask and RIE for 1 min (A, B), 2 min (C, D), 5 min (E) and 20 min (F). Both the top-view (A, C, E, and F) and the cross-section (B and D) were shown.

69

30 170-nm mask 300-nm mask 25

20

15

10

Volume porosity% 5

0 0.4 0.8 1.2 1.6 2.0 Etching time(min)

Fig 4.2 Semi-linear correlation of porosity and etching time. Different volume porosity profiles were obtained for the two mask size used. For each mask size the volume porosity increases as an etching time increases linearly.

70 A IR Camera

Beam Block Argon Laser 514 nm Substrate

310 B Center Edge1 308 Edge2 Edge3 Edge4 306

304

302

Surface Temp. 300

0 5 10 15 20 25 30 35

Time (s)

Fig 4.3 (A) A schematic drawing of the infrared thermography setup to measure temperature changes on the surface of the Si substrate upon laser irradiation. 15 (B) Five representative temperature profiles plotted as a function of time. The laser irradiation started at 5 sec time point and was blocked after 5-sec irradiation. The five profiles were recorded from center and four corners of the same substrate.

71

60 55 170-nm mask 300-nm mask 50 45 40 35 30 25 20 15 Temp Change (delta K) 10 5 0 5 10 15 20 25 30 Volume porosity%

Fig 4.4 A plot of the surface temp changes as a function of calculated volume porosity.

72

A B 20000 3.89 % 16000 10.00% 16000 21.23% 28.48% 12000 12000

8000 8000 S/N 4000

Peak Intensity 4000

0 0 1200 1800 2400 0 5 10 15 20 25 30 Laser Intensity Volume porosity %

50 )

2 C 45

40

35

30 25

20

Laser threshold(mJ/cm 0 5 10 15 20 25 30 Volume Porosity%

Fig 4.5 MS intensity of DPPC as a function of irradiation laser

intensity for different substrates. 100 pmol DPPC was used as the standard. The laser intensity was tuned using a neutral density filter,

and the numbers recorded were arbitrarily assigned by the manufacturer. (B) A close-to-linear relationship between the MS

response (S/N) and the substrate volume porosity. (C) The SALDI laser threshold value decreases with increasing porosity. The laser

threshold was defined as the laser energy needed to reach a signal-to- noise ration of 50:1 in DPPC detection.

73

20000 Ordered structure Non-ordered structure 16000

12000

S/N 8000

4000

0 10 15 20 25 30 35 40 45 Temp Change (K)

Fig 4.6 The signal to noise ratio of DPPC as a function of temperature change. The etching time for the ordered surface structure is 0.5,1,1.5 and 2 min starting from the lowest temperature change. The etching time for the non-ordered structure is 20 and 5 min starting from the lowest temperature change. 1.5 and 5 min etching time has the same temperature change and completely different MS performance. Which suggest that the surface geometry has a big impact in the MS performance.

74