Abstract
A rapid and selective method for the quantitation of neurotransmitters, l-Glutamic acid (GA) and γ–Aminobutyric acid (GABA), was developed and validated using gas chromatography-tandem mass spectrometry (GC–MS/MS). The novel method utilized a rapid online hot GC inlet gas phase sample derivatization and fast GC low thermal mass technology. The method calibration was linear from 0.5 to 100 μg/mL, with limits of detections of 100 ng/mL and 250 ng/mL for GA and GABA, respectively. The method was used to investigate the effects of deletion of organic anion transporter 1 (Oat1) or Oat3 on murine CNS levels of GA and GABA at 3 and 18 mo of age, as compared to age matched wild-type (WT) animals. Whole brain concentrations of GA were comparable between WT, Oat1−/−, and Oat3−/− 18 mo at both 3 and 18 mo of age. Similarly, whole brain concentrations of GABA were not significantly altered in either knockout mouse strain at 3 or 18 mo of age, as compared to WT. These results indicate that the developed GC–MS/MS method provides sufficient sensitivity and selectivity for the quantitation of these neurotransmitters in mouse brain tissue. Furthermore, these results suggest that loss of Oat1 or Oat3 function in isolation does not result in significant alterations in brain tissue levels of GA or GABA.
1. Introduction
l-Glutamic acid (GA) and γ-aminobutyric acid (GABA) are neurotransmitters found in the brains of mammals (Fig. 1). GABA is synthesized from GA by glutamate decarboxylase, yet the functions of these two neurotransmitters have opposing effects. GA is considered a major excitatory neurotransmitter in the CNS, while GABA is considered a major inhibitory neurotransmitter. Quantitation of these two neurotransmitters is important to the field of neuropharmacology, as they have been associated with learning and memory, the sleep cycle, and clinical conditions including schizophrenia, Alzheimer’s disease, Parkinson’s disease, depression, anxiety and obsessive-compulsive disorder [1–9].
Fig. 1.
Structures depicting the methylation sites (i.e., labile hydrogens) for l-Glutamic Acid and γ-Aminobutyric Acid. The MethElute derivatization occurs rapidly in a deactivated GC liner located in the heated GC inlet.
High performance liquid chromatography with electrochemical detection (HPLC-ECD) techniques have previously been used to study amino acid concentrations in the brain [10–13]. Since the amino acids are not naturally electroactive, these methods typically require a derivatization step (usually using o-phthalaldehyde in the presence of a thiol, e.g., β-mercaptoethanol, or a sulfite group). However, despite the sensitivity that can be achieved using HPLC-ECD, the electroactive derivatives are often unstable, and it has been reported that resolution may be problematic due to unknown peaks of biological origin that elute closely to GABA [14–16].
In addition, there have been several publications using liquid chromatography-tandem mass spectrometry (LC–MS/MS) for the analysis of GA and GABA in biological samples [17–19]. However, to our knowledge, there are no currently published methods utilizing gas chromatography-tandem mass spectrometry (GC–MS/MS) offering quantitation of both GA and GABA in brain tissue. In this article, we describe a rapid and selective GC–MS/MS method for the detection and quantitation of GA and GABA in mouse brain homogenate. Stable isotopes of each compound were used as internal standards. The use of MethElute™ reagent (as described in [20]) rapidly derivatized GA and GABA and their isotopologues in the heated GC injection port, which required less than 20 s for completion and utilization of the low thermal mass (LTM) technology provided high resolution and fast chromatography (Fig. 1). The method demonstrated excellent linearity from 0.5 to 100 μg/mL, with limits of detections of 100 ng/mL and 250 ng/mL for GA and GABA, respectively. The method was successfully used to assess the effects of deletion of the Solute Carrier 22 family members organic anion transporter 1 (Oat1) or Oat3 on mouse brain tissue concentrations of GA and GABA.
2. Materials and methods
2.1. Chemicals, reagents, and gases
Standard material of L-Glutamic acid and γ-aminobutyric acid were purchased from Sigma Aldrich (St. Louis, MO). The 13C5-l-Glutamic acid (M + 5 stable isotope, purity 99%) and U-13C4-4-aminobutyric acid (M + 4 stable isotope, purity 98%) internal standards were purchased from Cambridge Isotopes (Andover, MA).
MethElute™ derivatization reagent (0.2 M trimethylanilinium hydroxide in methanol, pH ≥ 10) was purchased from Thermo Scientific (Waltham, MA). Methanol (MeOH) (HPLC grade, 99.9% purity) was purchased from Acros Organics (Fair Lawn, NJ). Ultrapure deionized water (18 Ωohm-cm) was prepared daily using a Milli-Q Integral Water Purification system from EMD Millipore (Billerica, MA).
Gases used for GC–MS/MS analyses were helium (grade 5.5 purity), nitrogen (ultra high purity), isobutane (Matheson 99.99% purity) and methane (research grade purity) and were all purchased from Roberts Oxygen Company (Rockville, MD). Gas purifiers used to remove hydrocarbons and moisture from the gases were purchased from Agilent Technologies (Santa Clara, CA).
2.2. Equipment and software
The Agilent 7890 GC, LTM series II fast GC module, 7000A GC–MS triple quadrupole, and 7693 autosampler were purchased from Agilent Technologies (Santa Clara, CA). The Agilent MassHunter software was used for GC–MS/MS data collection and processing including GC–MS/MS Acquisition (version B.07.00), Qualitative Analysis (version B.04.00), and Quantitative Analysis (version B.05.00).
An Eppendorf Model 5417R centrifuge was used to centrifuge down any particulate in the tissue homogenate prior to the derivatization step (Hauppauge, NY). The Savant DNA110 SpeedVac® used for evaporating and concentrating samples was purchased from Thermo Fisher Scientific (Waltham, MA).
2.3. GC–MS/MS instrument conditions
The final GC–MS instrumental parameters used for sample analysis are listed in Tables 1 and 2, respectively.
Table 1.
Agilent 7890A GC and Autosampler Parameters.
| GC Inlet | |
| Mode | Pulsed Splitless |
| Temperature (°C) | 235 |
| Total Flow (mL/min Helium) | 54 |
| Septum Purge Flow (mL/min Helium) | 3 |
| Injection Pulse Pressure (psi until 1 min) | 25 |
| Purge flow to split vent (mL/min Helium at 1.1 min) | 50 |
| Gas saver (mL/min Helium after 3 min) | 15 |
| GC Program | |
| Initial GC Oven Temperature (°C) | 30 |
| Initial Oven Hold Time (min) | 1 |
| Rate (°C/min) | 75 |
| Final GC Oven Temperature (°C) | 300 |
| Final Over Hold Time (min) | 1.4 |
| Run Time (min) | 6 |
| Equilibration Time (min) | 0.1 |
| GC Transfer Line (°C) | 300 |
| Oven Max Temperature (°C) | 340 |
| GC Column | |
| LTM Column | DB–5 ms, 15 m × 250 μm × 0.25 μm |
| Head Pressure (psi) | 2.14 |
| Flow (mL/min Helium) | 1 |
| Average Velocity (cm/sec) | 47 |
| Holdup Time (min) | 0.5 |
| GC Autosampler | |
| Syringe Size (μL) | 10 |
| Injection Volume (μL) | 1 |
| Post Washes A | 3 with ethanol |
| Post Washes B | 3 with acetone |
| Samples Washes | 1 |
| Sample Wash Volume (μL) | 4 |
| Samples Pumps | 3 |
| Viscosity Delay (sec) | 3 |
| Air Gap (μL) | 0.2 |
| GC Autosampler Barcode Mixer | |
| Mixer | Enabled |
| Mixer Cycle | 1 |
| Mixer Time (sec) | 10 |
| Mixer Speed (rpm) | 2000 |
Table 2.
Agilent 7000A MS Parameters.
| Helium Quench Gas (mL/min) | 2.25 |
| Nitrogen Collision Gas (mL/min) | 1.5 |
| Isobutane Reagent Gas (mL/min) | 2 |
| Ion Source Temp (°C) | 350 |
| Quad 1 Temperature (°C) | 150 |
| Quad 3 Temperature (°C) | 150 |
| Ion Source | Chemical Ionization (CI) |
| Mode | Positive Ion (PCI) |
| Electron Energy Mode | Use tune settings |
| Solvent Delay (min) | 1.0 |
| Run Time (min) | 6.0 |
| Time Filter Enabled | |
| Peak Width | 0.7 |
| MS1 Resolution | Unit |
| MS2 Resolution | Unit |
| Dwell Time (msec) | 50 |
| Scan Rate (cycles/sec) | 5 |
| Collision Energy-GA (V) | 15 |
| Collision Energy-GABA (V) | 20 |
| Electron Multiplier (V) | 1600 |
| Delta EMV (V) | 400 |
| HED (kV) | −10 |
| Instrument Tuning (Mass Calibration) | |
| Tune MS weekly or as necessary | |
| MRM Transitions | |
| GA derivative (precursor ion/product ion) | m/z 204/144 |
| d5-GA derivative (precursor ion/product ion) | m/z 209/148 |
| GABA derivative (precursor ion/product ion) | m/z 146/101 |
| D4-GABA derivative (precursor ion/product ion) | m/z 150/105 |
2.4. GC–MS/MS calibration standards and internal standards
Stock standard solutions of GA and GABA (1 mg/mL) were prepared in deionized water and deionized water:MeOH (50:50 (v/v)), respectively, and stored at −20 °C until analysis. GA was found to be insoluble in aqueous solutions with varying percentages of organic modifiers (e.g. 70/30 v/v; 80/20 v/v; 90/10 v/v deionized water:MeOH). Working calibration standards (0.5, 2.5, 5, 10, 25, 50 and 100 μg/mL) were prepared containing GA and GABA, and their stable isotopes GA M + 5 and GABA M + 4 (internal standards) and stored at −20 °C until analysis. The calibration standards were prepared by adding 50 μL of standard to the microvial insert (Agilent, Santa Clara, CA) and evaporated to dryness (~45 min at 45 °C) using the Savant DNA SpeedVAC. For reconstitution, 50 μL of the MethElute™ derivatizing reagent was added to the autosampler microvial containing the sample residue, capped, and vortexed for 15 s prior to placement on the autosampler. The internal standard (I.S.) working solution was prepared by appropriate dilutions of the stock solution with deionized water. The I.S. working solution contained 10 μg/mL GA M + 5 and GABA M + 4.
2.5. Brain sample preparation
As per our established protocol, wild-type C57BL/6J mice (males 10–13 weeks) were sacrificed and whole brains were removed (average processing time ≤60 s minimizing any potential changes) [21]. Whole brains were immediately homogenized on ice using a PowerGen 125 homogenizer (Thermo Fisher Scientific, Fair Lawn, NJ, USA) and stored at −80 °C until subsequent analysis. For sample analysis, brain homogenates were thawed, vortexed for 30 s, and centrifuged at 2500 rpm for 5 min. Following centrifugation, 50 μL of brain homogenate and 50 μL of internal standard were added to the microvial insert (Agilent, Santa Clara, CA) and evaporated to dryness (~45 min at 45 °C) using the Savant DNA SpeedVAC. For reconstitution, 50 μL of the MethElute™ derivatizing reagent was added to the autosampler microvial containing the sample residue, capped, and vortexed for 15 s prior to placement on the autosampler.
2.6. Method validation
The method was validated in terms of linearity, sensitivity, selectivity, intra- and inter-day accuracy and precision, and stability. The linearity was evaluated using a weighted (1/x) quadratic analysis of calibration standards from 0.5–100 μg/mL (n = 3). The sensitivity was established by determining the lower limit of quantitation (LLOQ) and the limit of detection (LOD) for each component. The combined inter-day and intra-day accuracy and precision of the method was evaluated using calibrators from the standard curves (n = 3). Instrument injector precision and derivatization reproducibility were evaluated by using replicate injections of the 25 μg/mL calibration standard (n = 6). The stability of GA and GABA were evaluated using the mid calibration standard (10 μg/mL) at 0, 3, 5, 7 and 18 h at room temperature on the autosampler. Freeze/thaw stability was evaluated using wild-type control brains prepared and injected following one freeze thaw cycle.
2.7. Computations
Component computations were performed using MS multiple reaction monitoring (MRM) mode and peak height response with MassHunter quantitation software (Agilent Technologies, Santa Clara, CA). The seven point calibration curve was a plot of the standard concentrations versus the ratio of the peak height of the component and its internal standard. Calibration curves were constructed for each analytical run.
3. Results and discussion
3.1. GC–MS/MS method development and optimization
DB–17 ms and DB–5 ms columns were evaluated for this method. The DB–5 ms column provided better peak shape of GABA, as compared to the moderately polar DB–17 ms column, most likely due to the non-polar nature of the GABA derivative.
MS/MS optimizations were performed for both GA and GABA. Samples were injected in chemical ionization mode (positive ion mode) with data collected at unit mass resolution in MRM mode. The precursor ions were isolated in the first quadruple and further fragmented with different collision energies (15, 20 V) with optimal collision energies of 15 V for GA and 20 V for GABA. The third quadruple then sorted these fragments for detection. The main characteristic ions of GA and GABA produced major product ions at m/z 144 and m/z 101, respectively. Therefore, the precursor/product ion pairs of m/z 204 → m/z 144 and m/z 146 → m/z 101 were chosen as MRM transitions of GA and GABA, respectively. Fig. 2 shows chromatogram overlays representing MRM of the 25 μg/mL standards and representative brain samples.
Fig. 2.
Chromatographic overlays representing typical multiple reaction monitoring (MRM) of the 25 μg/mL standard (A) GA Internal Standard (209 → 148 m/z), (B) GA (204 → 144 m/z), (C) GABA Internal Standard (150 → 105 m/z), (D) GABA (146 → 101 m/z), and a representative mouse brain sample (E) GA Internal Standard, (F) GA, (G) GABA Internal Standard, (H) GABA.
The method could be made more sensitive by altering the sample preparation. For the current purpose, a 1:1 ratio (50 μL sample: reconstituted in 50 μL derivatizing agent) was used for reconstitution; however, by changing the ratio (v/v) (e.g. 150 μL sample: reconstituted in 25 μL derivatizing agent) sensitivity was increased 5 fold (data not shown).
3.2. GC–MS/MS method validation
The calibration curve (peak height ratio of analyte to internal standard vs. concentration) for both GA and GABA was evaluated using a 1/x weighted quadratic analysis and was linear over the range of 0.5–100 μg/mL (n = 3) with a correlation coefficient value ≥ 0.998. A typical calibration plot for each component is shown in Fig. 3. The lower limit of quantitation (LLOQ) for both components was defined as the lowest calibration standard (0.5 μg/mL), which could be accurately and precisely determined with less than 20% total error. The limit of detection (LOD) was determined by conducting dilutions of each component’s lowest calibration standard until the MS signal approached background noise. The LOD was determined to be 100 ng/mL and 250 ng/mL for GA and GABA derivatives, respectively (Fig. 4).
Fig. 3.
MassHunter quantitative analysis software generated calibration curves (peak height ratio of analyte to internal standard vs. concentration) for (A) GA and (B) GABA using a 1/x weighted quadratic analysis. The standards used for calibration were prepared at concentrations of 0.5, 2.5, 5, 10, 25, 50 and 100 μg/mL. The use of weighted calibration curves provided good correlation (R > 0.999) of the sample concentration to MS response for each component.
Fig. 4.
Chromatogram overlays (normalized) representing multiple reaction monitoring (MRM) of the limit of detection (LOD) for GA (panel B: (204 → 144 m/z), 100 ng/mL at RT = 3.16 min) and GABA (panel D: (146 → 101 m/z), 250 ng/mL at RT = 2.49 min) relative to MethElute™ derivatizing agent only (panels A and C, respectively).
The combined intra-day and inter-day accuracy and precision were evaluated using standard curves (Table 3). Accuracy (% error) was determined by the difference between ((measured concentration-nominal concentration)/(nominal concentration))*100. Precision (%CV) was determined by dividing the standard deviation by the mean (SD/mean)*100. Intra-day instrument injector precision and online heated GC inlet derivatization reproducibility were evaluated by using repetitive injections of the 25 μg/mL calibration standard (Table 3). The instrument injector precision was less than 7% C.V. and online heated derivatization procedure was very reproducible.
Table 3.
Intra-day and Inter-day accuracy and precisions of GA and GABA calibration standards.
| Combined Intra-Day and Inter-Day Accuracy and Precision | |||||||||
| GA |
GABA |
||||||||
| Conc. | Measured Conc. | SD | % Error | % CV | Conc. | Measured Conc. | SD | % Error | % CV |
| 0.5 | 0.5 | 0.02 | −3.3 | 3.2 | 0.5 | 0.5 | 0.02 | 0.0 | 3.5 |
| 2.5 | 2.5 | 0.18 | −1.6 | 7.4 | 2.5 | 2.5 | 0.03 | 1.2 | 1.2 |
| 5 | 4.8 | 0.22 | −3.3 | 4.6 | 5 | 4.9 | 0.03 | −1.8 | 0.7 |
| 10 | 10.8 | 0.21 | 7.8 | 2.0 | 10 | 10.4 | 0.33 | 4.2 | 3.1 |
| 25 | 25.9 | 1.07 | 3.9 | 4.1 | 25 | 23.7 | 0.20 | −5.2 | 0.8 |
| 50 | 47.4 | 1.51 | −5.2 | 3.2 | 50 | 51.3 | 0.36 | 2.7 | 0.7 |
| 100 | 101.1 | 0.59 | 1.1 | 0.6 | 100 | 97.9 | 2.69 | −2.1 | 2.7 |
| Instrument Precision and Derivatization Reproducibility | |||||||||
| GA |
GABA |
||||||||
| Conc. | Measured Conc. | SD | % Error | % CV | Conc. | Measured Conc. | SD | % Error | % CV |
| 25 | 25.4 | 1.59 | 1.4 | 6.3 | 25 | 24.1 | 0.3 | −3.7 | 1.4 |
A stability study was performed to evaluate the component’s stability in the MethElute™ derivatizing reagent. The stability of GA and GABA were evaluated using the mid calibration standard (10 μg/mL) at 3, 5, 7 and 18 h at ambient room temperature on the autosampler, as compared to freshly prepared and analyzed 10 μg/mL calibration standard. The results of the stability study indicate that GA and GABA are stable in the MethElute™ derivatizing agent for at least 7 h (typical run length), but are not stable at 18 h (< 10% degradation of GA, and ~30–40% degradation of GABA). Freeze/thaw stability was also evaluated using wild-type control brains (n = 4) prepared and injected following one freeze thaw cycle. Both components were stable through one freeze thaw cycle.
3.3. Method application
The validated method has successfully been applied for the quantitative detection of GA and GABA in mouse brain tissue of organic anion transporter (OAT) knockout mice. Mice (C57Bl/6J background) of three genotypes: wild-type (WT), Oat1 transporter knockout (Oat1−/−), and Oat3−/− at two ages (3 mo vs. 18 mo of age) were used for initial assessment (n = 4 in each group). Preliminary behavioral assessments (Farthing and Sweet, unpublished observations) indicated that the GA/GABA system may be altered over age from the loss of OAT transporter function in the brain. Brain tissue samples were previously collected following completion of the behavioral assessments, and homogenates were aliquoted and stored at −80 °C until analysis. The concentrations of GA and GABA in brain homogenates for each group are shown in Fig. 5A. As can be seen from Fig. 5B, GABA remained relatively unchanged across and within genotype. GA concentrations also remained unchanged within all three genotypes; however, a trend was observed with lower concentrations of GA in both of the aged OAT knockout genotypes compared to age matched WT mice. While these data rule out large changes in total brain content for GA and GABA after loss of OAT1 or OAT3 function, it is possible that local changes in distribution of these molecules does occur.
Fig. 5.
The concentrations of GA and GABA in brain homogenates for each group are shown. GA concentrations remained unchanged within all three genotypes (panel A); however, a trend was observed with lower concentrations of GA in both of the aged (18 mo) OAT knockout genotypes, as compared to age matched WT mice. As can be seen in panel B, GABA concentrations remained relatively unchanged across and within genotype. There were n = 4 mice in each of the groups (e.g. WT 3 mo, WT 18 mo, Oat1−/− 3 mo, etc.).
4. Conclusions
In order to achieve enhanced analytical sensitivity and selectivity for GA and GABA in mouse brain homogenate we developed a rapid GC–MS/MS (triple quadrupole) method employing positive chemical ionization and multiple reaction monitoring. The method incorporated both online hot inlet gas phase derivatization, which required less than 20 s for completion, and fast chromatography by utilization of LTM technology, allowing for shorter reaction cycle times. As conducted, the technique demonstrated excellent linearity from 0.5 to 100 μg/mL, with limits of detections of 100 ng/mL and 250 ng/mL for GA and GABA, respectively. The method was used to investigate the role of organic anion transporter deletion on concentrations of GA and GABA in the mouse brain.
Acknowledgements
This work was supported by funding from the Altria Regulatory Science Fellowship (grant number 646441) and the Virginia Commonwealth University Presidential Research Quest Fund (grant number 292991).
Footnotes
Conflict of interest
The authors declare that they have no conflict of interest.
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