For research use only. Not for use in diagnostic procedures.
A rapid UPLC-MS/MS methodology has been developed for the research analysis of derivatized amino acids. This method has been demonstrated to be suitable for the analysis of physiologically relevant levels of these analytes in human serum. This method utilizes a generic LC-MS platform that can be used for various compound classes (including metabolomics, lipidomics, and proteomics), meaning it can be applied as part of a suite of analyses that are part of a targeted multi-omics workflow.
Amino acids are the constituent building blocks of proteins, and as such are extremely important molecules in human biochemistry. The analysis of these compounds is generally performed using derivatization, followed by flow injection analysis – tandem mass spectrometry (FIA-MS/MS). This method however cannot distinguish isobaric species resulting in limited information acquired from these types of analyses. Here we demonstrate a high-throughput UPLC-MS/MS research method for the semi-quantitative analysis of derivatized amino acids in human serum samples. This application note is also part of a MetaboQuan-R method package.
Human serum samples were prepared using the Waters AccQTag Ultra “3X” Derivatization Kit (p/n 186004535). Samples were crashed using sulfosalicylic acid and then derivatized as follows:
Step 1 Add 50 μL of sample to 1.5 mL eppendorf
Step 2 Add 50 μL of 10% sulfosalicylic acid
Step 3 Vortex mix for five seconds
Step 4 Add 50 μL of water
Step 5 Vortex mix for five seconds
Step 6 Centrifuge for 10 minutes at 10,000 rpm @ 5 °C
Step 7 Add 70 μL of Borate buffer (from AccQTag Kit) to a maximum recovery vial
Step 8 Transfer 10 uL of supernatant to the maximum recovery vial
Step 9 Vortex mix for five seconds
Step 10 Add 20 μL of AccQTag reagent (from AccQTag Kit)
Step 11 Vortex for five seconds after addition to each sample, allow sample to stand at ambient for one minute
Step 12 Heat for 10 minutes at 55 ÅãC
Step 13 Perform a 1 in 10 dilution in 80:20 (water:acetonitrile) (90 μL plus 10 μL sample) in a max recovery vial
Step 14 Inject 2 μL
UPLC separation was performed with an ACQUITY UPLC I-Class System (fixed loop), equipped with a CORTECS T3 2.7 µm (2.1 × 30 mm) analytical column. A sample of 2 µL was injected at a flow rate of 1.3 mL/min. Mobile phase A was 0.01% formic acid (aq) containing 0.2 mM Ammonium Formate and mobile phase B was 50% isopropanol in acetonitrile containing 0.01% formic acid and 0.2 mM Ammonium Formate. The derivatized amino acids were eluted from the column and separated with a gradient of 1–8% Mobile phase B over 2.4 minutes, followed by a 0.9 minute column wash at 98% Mobile phase B. The column was then re-equilibrated to initial conditions. The analytical column temperature was maintained at 60 °C.
Multiple Reaction Monitoring (MRM) analyses were performed using a Xevo TQ-S micro mass spectrometer. All experiments were performed in positive electrospray ionization (ESI+) mode. The ion source temperature and capillary voltage were kept constant and set to 150 °C and 2.0 kV respectively. The cone gas flow rate was 50 L/hr and desolvation temperature was 650 °C.
Method information was imported onto the LC-MS system using the Quanpedia functionality within MassLynx. This extendable and searchable database produces LC and MS methods as well as processing methods for use in TargetLynx for compound quantification.
The 29 amino acids detailed in Table 1 were separated and detected using the LC-MS platform and extraction protocol described herein. Figure 1 shows example chromatograms for the separation of key isobaric compounds achieved using the UPLC method detailed above.
A rapid UPLC-MS/MS methodology has been developed for the research analysis of derivatized amino acids. This method has been demonstrated to be suitable for the analysis of physiologically relevant levels of these analytes in human serum. This method utilizes a generic LC-MS platform that can be used for various compound classes (including metabolomics, lipidomics, and proteomics), meaning it can be applied as part of a suite of analyses that are part of a targeted multi-omics workflow.
720006271, February 2019