Carl Jenkinson (Presenter)
Metabolism and Systems Research, University of Birmingham
Bio: Post-Doctoral Research Fellow within the Institute of Metabolism and Systems Research at the University of Birmingham. PhD undertaken in the monitoring of anabolic steroid metabolism.
Authorship: Carl Jenkinson (1), James Bradbury (2), Angela Taylor (1), Shan He (2), Mark Viant (3), Martin Hewison (1)
(1) Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK, B15 2TT, (2) School of Computer Science, University of Birmingham (3) School of Biosiences University of Bir
| Short Abstract Increased demand has been placed on clinical laboratories to develop and run rapid liquid chromatography-tandem mass-spectrometry (LC-MS/MS) methods to accurately quantify multiple analytes of interest. Manual method development can be time consuming and challenging, particularly with multiple metabolites. This study utilises a software platform, MUSCLE, for automated method development of multiple vitamin D metabolites, comparing the optimised parameters with a manually developed method. The optimised MUSCLE method reduced the overall method run time from 9 minutes to 6.5 minutes although mass spectrometry transitions did not alter significantly with either method. This study illustrates the use of MUSCLE for clinical laboratories for reducing labour and time for developing LC-MS/MS methods. |
Long Abstract
Increased demand has been placed on clinical laboratories to provide rapid analytical methods to accurately quantify multiple analytes of interest. To meet this demand, methods are developed on high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) platforms with the aim of analysing multiple metabolites in a single run. However, manually developing LC-MS/MS methods can prove challenging and time consuming. An experienced analyst is required to overcome challenges of separating multiple metabolites whilst minimising run time. These issues are commonly encountered when developing LC-MS/MS methods for measuring multiple vitamin D metabolites as several compounds have equal multiple reaction monitoring (MRM) transitions that require baseline separation for accurate quantitation. Active forms have low endogenous concentration ranges requiring optimal MS conditions by manual tuning. This study aimed to utilise a software application, MUSCLE, to automate the LC-MS/MS method development for measuring vitamin D analogues. Comparing the use of MUSCLE with a method developed manually will inform the effectiveness of automated development in optimising method parameters and labour time.
Multi-objective Unbiased Spectroscopy via Closed-Loop experimentation (MUSCLE) is a software platform developed within Computer Science. MUSCLE is designed to automate method development through identifying optimal liquid chromatography (LC) and mass spectrometry (MS) parameters for each analyte. An algorithm script is applied by MUSCLE to alter the LC gradient, collision energies, cone voltages and desolvation temperature after each run, utilising the results from previous samples in the sequence to further optimise these conditions on a run to run basis. Results are grouped into sample generations, displaying the sample runs considered to have optimum method parameters based on the number of compounds quantified and peak areas.
MUSCLE was applied on a Waters AQUITY UPLC coupled to a Xevo TQ-D mass spectrometer for the development of a vitamin D method. A 1 µL sample stock solution was injected 200 times. A Phenomenex Lux cellulose-3 chiral column (100 mm, 2 mm, 3µm) was used for separation with a mobile phase of water/methanol 0.1% formic acid. Each sample was monitored in MRM mode over a 9 minute period.
An optimised LC-MS/MS method that separated 12 vitamin D metabolites, along with an isobar 7áC4, was achieved by MUSCLE. The run time of the method was 6.5 minutes, which was shorter than the current 9 minute run time from a manually optimised method with the same compounds. The retention time window was between 1.74-3.83 minutes for the MUSCLE software method and 2.70-5.46 minutes for the manually optimised method. These shorter retention times were gained by an increase in initial organic mobile phase composition at the start of the run and increasing the in run gradient for a 100% organic mobile phase at an earlier timepoint, without compromising resolution. Baseline separation of analytes with the same MRM transitions was achieved, apart from 24’ and 25’-hydroxyvitamin D2, which could not be completely separated manually or by MUSCLE. Overall the optimal MS conditions determined manually by infusion did not alter or were not improved when compared with the MS conditions and compound intensities from the MUSCLE sequence.
Accurate 25-hydroxyvitamin D3 (25OHD3) and D2 measurements can be performed by applying both manual and MUSCLE optimised methods as both methods ensure separation of isobars and inactive forms. Both 7áC4 and the respective C3 epimers of 25OHD, which have the same MRM transitions, were separated at baseline by liquid chromatography.
A novel aspect to LC-MS/MS method development has been applied by MUSCLE using an automated approach for improving resolution and run time over a manually developed vitamin D method, along with improving labour time for developing the method. This software could be applied for developing other clinical related LC-MS/MS methods, particularly involving high throughput analysis of multiple endocrine and pharmaceutical compounds.
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