Wine avonoids identi ed and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer Thermo Fisher Scienti c, Inc., 355 River Oaks Parkway, San Jose, CA

Po

ster No

te 64

743

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid. methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

2 Wine avonoids identi ed and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

skewing and averaged.

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

Bennett S. Kalafut, Rae Ana Snyder and Mark Dreyer, Thermo Fisher Scientific, Inc., 355 River Oaks Parkway, San Jose, CA 95134

The LC peak associated with Alprazolam SIM (309 m/z) data fit with a Gaussian.

ABSTRACT

The intensity of collision-induced dissociation (CID) transitions varies strongly with collision energy across the operating range of a triple quadrupole mass spectrometer, and the relationship between intensity and collision energy (tuning or breakdown curve) is highly compound- and transition- specific and cannot practically be determined a priori. Therefore, when using neutral loss or precursor ion MS/MS scans for metabolomics discovery or product ion scans for characterization of a metabolite or conjugate of interest, it is typically necessary to repeat the (LC-)MS/MS experiment multiple times using different collision energies. In order to increase the coverage of a single LC-MS/MS experiment for metabolomics discovery, we present: 1. A method for rapid on-instrument composition of neutral loss, precursor ion, and product

ion scans acquired at multiple collision energies; and 2. Data-dependent scans combining neutral loss or precursor ion survey scans with

composite multiple collision energy product ion scans and fiducial scans for correction of spectral skewing in the space of a single LC peak.

The utility of this method is demonstrated by analysis of glycosylated flavonoid compounds present in wine.

INTRODUCTION

Mass spectrometry is among the most utilized analytical techniques in metabolomics research, providing both qualitative and quantitative assessments.1 Triple quadrupole mass spectrometers, in particular, are valuable tools for metabolomics discovery due to the ability to operate in precursor ion scan or neutral loss scan modes, operating both mass analyzers at once to detect unknown conjugated biomolecules, in addition to the ability to use selected reaction monitoring (SRM) scans for quantitation of known metabolites. Since collision energies that optimize or even produce MS/MS signals reasonably more intense than background noise are compound- and transition- specific and cannot be known a priori in a discovery experiment, when using neutral loss or precursor ion scans for discovery it is necessary to repeat the experiment several times with different collision energies. Once precursor ions of interest are found it is again necessary to run multiple product ion scan experiments to characterize or identify them. To reduce the time and sample costs necessary in the discovery phase, we present a novel methodology that includes rapid acquisition of product ion scans at multiple collision energies across an LC peak triggered by multiple collision energy neutral loss scans, with fiducial scans taken to correct the product ion scans for spectral skewing The study of wine flavonoids is of ongoing interest.2 Flavonoids affect the color, taste and constitution of red wine, and are derived from the skin and seeds of red grapes. They are associated with some of the health benefits of red wine in lowering cardiovascular risk since they can cause vasorelaxation.3 Their concentration in wine is dependent upon a variety of factors, including genetic and environmental factors of the grapes and viticultural practices.2 Common wine flavonoids are illustrated in Figure 1. We have selected wine flavonoids to illustrate the utility of our novel data-dependent method for metabolite discovery. Results are compared to compound optimization by direct injection of flavonoid standard.

CONCLUSIONS

Our methodology for collecting and processing product ion scans at multiple collision energies across an LC was demonstrated with Alprazolam in a simple loop injection and isocratic flow method. Processing of the data accounted for spectral skewing. The final product ion spectrum was obtained from the composition of spectra at multiple collision energies across the LC peak. This approach was then successfully applied to wine flavonoids (standard and wine product samples) where product ion scans were triggered by a glycosyl neutral loss (146 m/z), confirming the presence of the glycosylated flavonoid Quercetrin in the wine sample without searching for it directly. The composite product ion scans (precursor 471 m/z, M+Na+) of the flavonoid standard mixture and wine products were comparable to the compound optimization results obtained through direct infusion. Weighted averaging of multiple product ion spectra per collision energy per LC peak or verification of correlation of change in intensity of product ion spectrum peaks with that of the SIM scans across an LC peak will likely eliminate the need to construct a two-experiment consensus scan. The data-dependent approach for obtaining product ion spectra at multiple collision energies, demonstrated here on a single glycosylated biomolecule, may be more broadly useful in the discovery phase of metabolite analysis, increasing coverage of single LC-MS/MS experiments and reducing cost of time, sample, and consumables.. The neutral loss triggering allows for selectivity of ions in complex matrices, such as those encountered in metabolomics. Precursor ion scans may be substituted for the neutral loss scans (here, searching for Quercetin or flavin) without additional modification.

REFERENCES

1. Dettmer, K. et. al., Mass Spectrom Rev. 2007; 26(1): 5178. 2. Roullier-Gall, C. et. al., Food Chemistry 152 (2014) 100107 3. Hodgson, J. M., Nutrition and Aging 2 (2014) 139144.

ACKNOWLEDGEMENTS We would like to acknowledge Wei Wei for thoughtful conversations on liquid chromatography.

TRADEMARKS/LICENSING

2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manner that might infringe the intellectual property rights of others.

Wine flavonoids identified and analyzed by composite neutral loss scan and novel data-dependent scans for metabolomics discovery by LC/MS/MS

MATERIALS AND METHODS

Mass spectrometry: All mass spectral data were acquired on a Thermo Scientific TSQ Quantiva triple quadrupole mass spectrometer in standard production hardware configuration using custom instrument control software to collect mixed-mode scan data and trigger change of scan mode on detection of a neutral loss of interest. Heated electrospray ionization (H-ESI) was used for sample ionization. At the beginning of acquisition, the mass spectrometer is set to acquire neutral loss scans, iterating repeatedly in sequence through a set of different collision energies. On detection of the neutral loss of interest (glycosyl loss, 146 amu) the instrument switches into a mixed scan mode, alternating between Q1 SIM scans and product ion scans of the discovered precursor ion, again acquired at multiple collision energies. After a predetermined amount of time has elapsed, the instrument switches back to the neutral loss scan for discovery of further molecules of interest during the same LC run. Loop injection: To generate mass spectra to test and refine the data analysis method presented here, 5 L of a solution of alprazolam (300 ppb) was injected into a 5 L loop on a divert valve. A syringe with a 100 L/min flow rate was used to provide an isocratic flow of 75% acetonitrile and 25% water. SIM (308.45-309.95 m/z) and product ion (10-307.2 m/z) scans with multiple collision energies were collected across the sample injection. Direct injection: A 10 g/mL solution of Quercetrin was directly infused into the mass spectrometer at a flow rate of 5 L/min. Compound optimization on the sodium adduct (471 m/z) was performed using the compound optimization routine provided by the standard TSQ Quantiva instrument control software, version 2.0. Liquid Chromatography: LC experiments were conducted on wine products and flavonoid standards (10 g/mL). Liquid chromatography was conducted with a Thermo Scientific UltiMate 3000 LC system with an LPG-3400SD pump, WPS-3000TXRS autosampler, and a TCC-3000RS column compartment. Ion source conditions are provided in Figure 2. A 5 min. LC gradient with a mobile phase of water + 0.1 % formic acid (A) and methanol + 0.1 % Formic acid (B) and a 300 L/min. flow rate was employed (Figure 3). A Hypersil gold column (50 mm x 2.1 mm, 1.9 um) held at 35 deg C provided flavonoid separation. Sample injection volume was 2 L.

Figure 4. Uncorrected and corrected product ion spectra for Alprazolam loop injection.

Product ion spectra for Alprazolam is shown with correction (right panel) and without correction (left panel).

Figure 1: Wine Flavinoids

Quercetin Quercetrin Rutin

Common flavonoids found in red wine.1

Figure 2: HESI source conditions for analysis of flavonoids in wine. Figure 3: LC gradient for flavonoid separation in wine.

Mobile phase: (A) water + 0.1 % formic acid and (B) methanol + 0.1 % formic acid.

Figure 5. Relative correction of spectral skewing at multiple collision energies.

Figure 6. Absolute correction for product ion spectra at multiple collision energies.

The relative correction for spectral skewing of product ion scans at collision energies 15, 25, 35, 45, and 55 eV.

Product ion spectra are corrected for spectral skewing and averaged.

Figure 7. Composite product ion spectrum

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 3. Guassian fitted LC peak

RESULTS

The data analysis approach described above is applied to wine flavonoid standards with an LC gradient and column and where product ion scan acquisition is triggered by detection of a neutral loss (glycosyl loss, 146 m/z) LC peak. Figure 8 and 9 shows the Gaussian fitted LC peaks for flavonoid standard mixture and wine product.

Figure 11. Composite product ion spectra for wine products.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 12. Compound Optimization results for quercetrin.

Product ion spectrum obtained from direct infusion of Quercetrin.

Figure 10. Composite product ion spectra for flavonoid standard mixture.

Product ion spectrum obtained from the composition of spectra at multiple collision energies.

Figure 9. Fitted LC peak of wine.

LC SIM peak triggered by neutral loss for wine products.

Figure 8. Fitted LC peak for standard mix.

LC SIM peak triggered by neutral loss for flavonoid standard mixture (Quercetrin, Quercetin, and Rutin) .

The composite product ion spectra (precursor 471 m/z, M+Na+) obtained by the method previously described are shown in Figure 10 for the standard mixture and Figure 11 for the wine products. Two single runs are in light yellow and light blue and overlapping (reproducible) features between the two runs are in dark blue. (Variability in the wine data is likely due to an SRM interference in the more complicated matrix). The composite product ion spectra for both wine and flavonoid mixture triggered by glycosyl neutral loss are comparable to the compound optimization results for directly infused Quercetrin (Figure 12). A spectrum of the overlapping features in the product ion spectra of the standard mixture and wine sample data is provided in Figure 13.

Figure 13. Product ion spectrum of overlapping features for flavonoid standards and wine.

A product ion spectrum of the overlapping features between flavonoid standard mixture and wine samples.

www.thermofisher.com2016 Thermo Fisher Scienti c Inc. All rights reserved. All other trademarks are the property of Thermo Fisher Scienti c and its subsidiaries. This information is presented as an example of the capabilities of Thermo Fisher Scienti c products. It is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others. Speci cations, terms and pricing are subject to change. Not all products are available in all countries. Please consult your local sales representative for details.

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