Glyphosate Quantified in Black Tea by Automatically Optimized LC-FAIMS MS/MSRae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark HardmanThermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

Po

ster No

te 64

749

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

2 Glyphosate Quantified in Black Tea by Automatically Optimized LC-FAIMS MS/MS

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

Part # PO72083-EN 0616S

Rae Ana Snyder, Bennett S. Kalafut, Claudia Martins, Satendra Prasad, Manish Doshi, and Mark Hardman, Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, USA 95134

RESULTSTable 1. Signal to noise ratios for chromatograms with and without FAIMS

Signal to noise ratios (S/N) are estimated by taking the baseline subtracted signal height and dividing by the standard deviation of the noise.

Figure 8. Chromatograms of glyphosate spiked tea samples taken with FAIMS onABSTRACTThe organophosphate herbicide glyphosate is a common residual contaminant of produce. Quantitation by LC-MS/MS is typically highly noise-limited in complex phytochemical matrices due to the presence of isobaric interfering MS2 peaks. Since glyphosate has a narrow and distinct compensation voltage (CV) tuning in FAIMS, FAIMS presents itself as an ideal orthogonal separation technique for reduction of noise. We automatically optimize CV for glyphosate in an integrated compound optimization workflow, and use the optimally tuned FAIMS to analyze the nano LC chromatography of glyphosate in black tea samples andcompare signal response to data obtained without the use of FAIMS. We observe that FAIMS allows for the detection of lower levels of glyphosate concentration (by more than a factor of 10).

INTRODUCTIONBy volume, glyphosate (N-(phosphonomethyl)glycine, Figure 1) is one of the most globally used herbicides.1,2 Commonly found in agricultural and garden products worldwide, its use as a broad spectrum systemic herbicide has become increasingly popular due to the availability of genetically modified glyphosate-resistant crops. The herbicidal activity of glyphosate is owed to its inhibition of the shikimic acid pathway, the metabolic route for aromatic amino acid biosynthesis found in many bacteria, fungi, and plants.1 Although used ubiquitously in industrial agriculture, health studies indicate that glyphosate is correlated to increased cancer risk, particularly for non-Hodgkin lymphoma.1,2 In vitro studies show that glyphosate induces DNA and chromosomal damage in mammalian cells (including human cells). 2

The possible health effects and wide spread use of glyphosate have sparked public concern over its concentration levels in food and water. Quantitation of glyphosate by LC-MS/MS has been hindered by the presence of isobaric interfering MS2 peaks from complicated food matrices. Orthogonal to both chromatographic and mass spectrometric separation, field asymmetric ion mobility spectrometry (FAIMS) utilizes differences in the mobility of ions in a high electric field to separate them at ambient conditions.3 We present the use of FAIMS to increase the selectivity of the precursor ion of glyphosate and diminish the contributing effects of complex food matrices that complicate glyphosate quantitation. An SRM acquisition method is automatically optimized with optimum collision energy, collision cell RF amplitudes and compensation voltage (CV) for glyphosate. The SRM method is then used to assess glyphosate signal in tea.

MATERIALS AND METHODSInstrumentation: Mass spectrometry data were collected on a Thermo Scientific™ TSQ Quantiva™ triple quadrupole mass spectrometer. Liquid chromatography was conducted on a Thermo Scientific™ EASY-Spray™ system with a nanospray ion source (NSI). The NSI source needle was coupled directly to the inlet of a prototype of FAIMS spectrometer4 (Figure 2). A syringe pump was used for direct infusion during the automatic optimizations.

Compound optimization: A continuous flow of glyphosate standard (325 µg/µL) was directly infused into a nano-source/FAIMS-mass spectrometer at a rate of 0.5-1 µL/min until compound optimization completed. While monitoring the SIM signal of 170 m/z (glyphosate + H+) in positive mode, a scan of CV across the operating range of our FAIMS instrument is used to locate the optimum CV tuning. Following this, collision energy and S-lens RF amplitudes are tuned to generate an optimum SRM acquisition.

Liquid Chromatography: A mobile phase of water + 0.1% formic acid and acetonitrile + 0.1% formic acid was used with a flow rate of 200 nL/min. The 23 min. gradient shown in Figure 3 and a Thermo Scientific™ EASY-Spray™ LC column (Thermo Scientifc™ PepMap™ RSLC column, C18, 2 μm, 50 μm i.d. x 150 mm) were employed. Ion source parameters and FAIMS electrode temperature settings are shown in Figure 4. Dispersion voltage (DV) was set to a constant -4500 V and the CV was set to an optimized value for FAIMS “on” experiments. DV and CV were set to 0 for FAIMS “off” experiments. Sample injection volume was 2 µL.

Sample Preparation: A representative portion of black tea was weighed and water was added to obtain a 10 g sample. 10 mL of acidified methanol is added to the sample, shaken vigorously and centrifuged (5 min at 4000 rpm). Sample is then filtered through a filter syringe. Glyphosate was then spiked into aliquots of sample at 0, 10, 50, 100, and 500 pg/μL.

CONCLUSIONSOur comparison of optimized nano-LC-NSI MS/MS and nano-LC-NSI-FAIMS MS/MS shows a greater than tenfold (10X) decrease of the lower limit of detection of glyphosate in black tea, showing FAIMS to be a promising tool for greater selectivity and sensitivity in detection and quantification of this and other molecules with isobaric interferences in difficult matrices such as black tea. Future experiments should assess reproducibility of the designed method and determine the limit of quantiation (LOQ).

Limitations of the prototype FAIMS spectrometer not inherent to its design precluded the use of established LC protocols5 for separation of glyphosate from food matrices for MS/MS analysis. Our result was attained using a non-ideal column for separation of a highly polar molecule from matrix and also, due to fragmentation of the negative ion in the atmospheric pressure region of the NSI source, using the “wrong” ion polarity. We anticipate even greater sensitivity when the production version of the FAIMS apparatus is available as we will be able to increase the flow rate and switch to a Thermo Scientific™ Hypercarb™ column, H-ESI source, and negative ion mode.

Finally, we note the utility of automatic optimization of the FAIMS compensation voltage, which may be done alone to add FAIMS separation to existing SRM methods or as part of an integrated optimization workflow (Figure 5.)

REFERENCES1. Thongprakaisang, S., et al. Food and Chemical Toxicology 59 (2013): 129-136.2. Guyton, K. Z et al.,The Lancet Oncology 16.5 (2015): 490 – 491.3. Kolakowski, B. M., & Mester, Z., Analyst 132.9 (2007): 842-864.4. Prasad, S., Belford, M., Dunyach, J.-J., and Purves, R.. J. Am. Soc. Mass. Spectrom. 25

(2014):2143-21535. Anastaassides, M. et al. “Quick method for the analysis of numerous highly polar pesticides in

foods of plant origin via LC-MS/MS involving simultaneous extraction withm methanol.” Version 8.1 EU Reference Laboratories for Residues of Pesticides, Fellbach, Germany.

ACKNOWLEDGEMENTSThe authors thank Thermo Fisher Scientific colleagues Ann Yadlowsky for support of the FAIMS apparatus, Uma Kota for discussions of nano-LC method development, and Mike Belford and Jean-Jacques Dunyach for access to the FAIMS spectrometer during the prototype phase of development..

TRADEMARKS/LICENSING© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of ThermoFisher 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.

Glyphosate quantified in black tea by automatically optimized LC-FAIMS MS/MS

An SRM acquisition method was developed by directly infusing glyphosate standard into the NSI-FAIMS-MS system. Positive mode had the most intense precursor signal (glyphosate + H+) for the nanospray-FAIMS experimental design while the glyphosate – H+ (168 m/z) was barely detectable. Compensation voltage optimized to -14 V for glyphosate + H+ precursor (170 m/z) using a grid search (Figure 6). Further compound optimization included using the optimization routine provided in TSQ Quantiva 2.0 to obtain optimal values for RF lens, collision energy, and precursor to product ion transitions (Figure 7) while infusing directly with a nanospray ion source.

LC conditions for glyphosate using NSI-MS/MS were first developed on a TSQ Quantivasystem without FAIMS using only standards and negative mode SRM transitions. The developed LC method for NSI-MS/MS was then applied to the nano LC-NSI-FAIMS-MS/MS method using the optimized CV value and SRM method (vide supra) from compound optimization done by direct infusion. LC data were then collected for black tea samples at 0, 10, 50, 100 and 500 pg/µL. Presented chromatograms (Figures 8 and 9) are constructed from the SRM of the most intense product ion (124 m/z, Figure 7).

Visual inspection of the chromatograms collected with (Figure 8) and without (Figure 9) separation by FAIMS for the 170 to 124 m/z SRM transition indicates a clear difference in signal quality. Signal intensity is barely visible for high concentrations ( > 100 pg/μL) without FAIMS due to high baseline and noise whereas signal is readily apparent in the lowest concentration tested (10 pg/μL) with FAIMS, representing a more than 10 fold difference in the limit of detection. For the lower concentrations ( < 500 pg/μL, below response saturation), a response curve may be constructed with the area of the chromatograms from the data with FAIMS (Figure 8, embedded) plotted against concentration. A linear fit (shown in the graph of response curve) can be used to calculate an initial estimate of the concentration of glyphosate in the black tea matrix (~ 5 ppb).

These data show the clear advantage of using FAIMS for complex food matrices, such as black tea. Further experiments with more concentrations and better statistics are necessary to accurately quantify the advantage.

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to -4500 V and the CV set to -14 V.

Figure 9. Chromatograms of glyphosate spiked tea samples taken with FAIMS off

Chromatograms of glyphosate spiked tea samples at 0, 10, 50, 100 and 500 pg/µL from the 170 to 124 m/z SRM transition taken with the DV set to 0 V and the CV set to 0 V.

The signal to noise ratio (S/N) can be estimated by using the reciprocal of the coefficient of variation (i.e. 𝜇𝜇

𝜎𝜎, 𝜇𝜇 is the expected value and 𝜎𝜎 is the standard deviation), which can be calculated by dividing the

baseline subtracted signal height with the standard deviation of the noise. The presented chromatographic data show no discernable LC peaks in the 1-2 min. range for the black tea matrix samples in both experiments (with and without FAIMS). Using the data from this time region for the non-spiked black tea matrix, the average response and its standard deviation were used as estimates of the baseline and standard deviation of the noise. Signal height was then calculated by subtracting the baseline from the apex for each chromatographic peak. S/N estimates are tabulated in Table 1 for the varying concentrations.

For the above definition of S/N, the Rose Criterion states that an S/N > 5 is necessary to discern signal from noise. Using this criterion for the limit of detection and the values from Table 1, we see that the native concentration of glyphosate in the black tea matrix, which was estimated to be ~5 ppb, is near the limit of detection (S/N is 17) for the nano LC-NSI-FAIMS MS/MS experiment. By contrast, an added glyphosate concentration > 50 ppb is necessary to obtain an S/N value > 5 when not using FAIMS, representing a greater than 10 fold difference in detectable glyphosate concentration between FAIMS and non-FAIMS experiments.

Figure 2. FAIMS Hardware Assembly

Top frame shows a section of the new FAIMS electrode assembly where the original assembly was cut along a y-z plane at midway along the x dimension and along the x-z plane midway along the y dimension. Middle and bottom frame show sectioned view of the outer electrode inlet along the y-z and x-z plane, respectively.

Entrance PlateMain Gas Feed

Inner RF Electrode

Gas Expansion Chamber

Outer Electrode Inlet

Entrance Plate Inlet

FAIMS separation gap

Outer Electrode Outlet

r2r1

xy

z

Outer Electrode

xz

3.34

yz

2.35

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

Outer Electrode Inlet

“O” ring seal

De-solvationChamber

Inner Cylinder Center Line

Concentraiton (pg/µL) S/N for FAIMS on S/N for FAIMS off0 16.60 0.5710 42.22 2.2950 381.60 3.28

100 529.30 13.14500 768.58 10.81

Figure 3. The gradient used in the nano LC of glyphosate

Figure 4. Nanospray ion source and FAIMS electrode temperature parameters

Gradient and flow rate for the Nano LC of glyphosate. Mobile phase includes (A) water + 0.1% formic acid and (B) acetonitrile + 0.1 % formic acid.

Nanospray ion source parameters and FAIMS inner and outer electrode temperature settings.

Figure 7. Compound optimization results for glyphosate

Product ion spectrum (top) and optimized SRM parameters (bottom) provided by the compound optimization results from the routine optimization method provided in the TSQ Quantiva 2.0 software with direct infusion of sample.

Figure 6. Compensation voltage tuning curve for glyphosate

The compensation voltage tuning curve for glyphosate obtained through grid search of directly infused sample.

Figure 1. Glyphosate

Figure 5. Optimization workflow

Integrated optimization utility, for upcoming release of Thermo Scientific™ TSQ Endura ™ Triple Quadrupole Mass Spectrometer and TSQ Quantiva Mass Spectrometer

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