U.S. Department of Energy

Pacific Northwest National Laboratory

Automated Solid Phase Extractions Coupled with Ion Mobility-Mass Spectrometry for Rapid Metabolomic Screening


Metabolomic analyses of complex plasma and urine samples present numerous analytical challenges, such as isomeric indistinguishability and inadequate measurement throughput. Ion mobility separations (IMS) minimize these limitations by providing high throughput structurally informative analyses, and when combined with mass spectrometry (MS) measurements, the multidimensional IMS-MS analyses provide in depth metabolite characterization. However, ionization suppression is typically observed in ESI-IMS-MS direct injection studies of plasma and urine due to the numerous components and their concentrations. Rapid separations and sample cleanup prior to IMS-MS analyses can avoid suppression and enable broader molecular coverage. In this study, we explored the use of automated solid phase extractions (SPE) coupled with IMS-MS to rapidly analyze plasma and urine samples.    



Metabolite standards and complex extracts were analyzed using a Rapidfire 365 automated SPE system and an Agilent 6560 IMS-QTOF MS platform resulting in a 10-s sample-sample analysis cycle. An assortment of SPE cartridges were utilized in the Rapidfire system to optimize the metabolites detected. The SPE bound species were then eluted into a Jetstream ESI source, and ions were efficiently transmitted through a two stage electrodynamic ion funnel interface where they were accumulated in a lower pressure ion funnel trap and then pulsed into the IMS drift cell prior to QTOF MS detection. The data was analyzed using the IMS Browser and identifications were made using a database populated with mass, IMS cross section and MS/MS spectra.


Preliminary Data 

IMS coupled with MS provides many advantages for evaluating metabolites since many have identical masses but distinct structures. To understand how well the IMS structural separation distinguishes isomeric endogenous metabolites, fructose-6-phosphate, glucose-6-phosphate, and glucose-1-phosphate, all important in glucose metabolism, were analyzed by IMS-MS. The IMS spectra clearly separated each with fructose-6-phosphate having the smallest structure and glucose-1-phosphate having the largest structure. To further characterize the IMS-MS technique for metabolomics in complex biological matrixes, exogenous parent metabolite standards were spiked into water and then into urine and plasma to determine their limits of detection (LODs) and calibration curve linearity. The analysis of each metabolite individually dissolved in water showed a limit of detection around 10 pM and linear calibration curves from 10 pM to 1 µM (R2 values ≥ 0.99). While this data looked very promising, problems occurred when the exogenous metabolites were spiked into urine and plasma extracts as the LODs increased to high nM levels, indicating ionization suppression occurred due to the higher overall concentration of species potentially ionized.  Automated SPE-IMS-MS analyses were then performed using the Rapidfire 365 to enable rapid cleanup of the samples and a sample-to-sample analysis cycle of 10-s. The 20 exogenous metabolites spiked into human plasma and urine extracts were again studied. This time, all 20 were detected with LODs ≤ 10 nM, with six having LODs at 500 pM. The R2 values were mostly > 98%, indicating linear response, and instrument reproducibility using triplicate analyses illustrated average intensity coefficient of variance (CV) values of ≤ 8% for all concentrations detected and < 3% for the metabolites not at their LOD. The automated SPE-IMS-MS method was then utilized to study different diseases such as diabetes type 1 and 2. The presentation will illustrate results from these studies.


Novel Aspect 

Automated SPE-IMS-MS analyses allow rapid and more effective metabolomic screening of complex plasma and urine samples

| Pacific Northwest National Laboratory