The March of the Masses

Isotope dilution with isotopically labeled biomass: An effective alternative for quantitative metabolomics

BACKGROUND

State-of-the-art quantitative metabolomics relies on isotope dilution using internal standards (IS) derived from fully 13C labeled biomass. By spiking samples and external standards with known amounts of IS, the spike characterization demands are kept to a minimum. In fact, it is sufficient to experimentally assess the isotopic enrichment of the IS. This study develops the yeast derived IS toolbox further, (1) by characterizing the concentration levels of hydrophilic metabolites in a yeast fermentation batch and (2) by exploring the analytical figures of merit of one-point IS versus multipoint external calibration using IS, the established gold-standard for quantitative metabolomics.

RESULTS

Independent reverse isotope dilution experiments using different chromatographic methods over a period of several months, delivered a list of 83 13C-labeled metabolites with fully characterized concentration and their uncertainty, covering 5 orders of magnitude, from the nanomolar to the low millimolar range. The 13C-labeled yeast-derived IS showed excellent intermediate stability with 92 % of molecules showing inter-method RSDs ≤30 % (75 % of molecules showed RSDs ≤15 %) over a timeframe of five months. One-point internal standardization with the characterized labeled biomass achieved figures of merit equivalent to multipoint calibrations for the majority of metabolites.

SIGNIFICANCE

The proposed calibration workflow rationalizes time and standard expenditure and is particularly beneficial for laboratories dealing with wide-target assays and small analysis batches. The present assessment serves as a seminal study for further developments of the concept towards absolute quantification from archive high-resolution MS data of U13C-biomass-spiked samples and the implementation of quick biomass recalibration with each experiment, promising seamless transition between internal standards derived from different fermentation batches.

System Performance Monitoring in Clinical Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)

Quality assurance (QA) activities enable continuous improvement through ongoing post-implementation monitoring to identify, evaluate, and correct problems. QA for clinical liquid chromatography tandem mass spectrometry (LC-MS/MS) assays should include specific components that address the unique aspects of these methods. This chapter briefly describes approaches for clinical LC-MS/MS system performance monitoring using batch and peak review metrics, largely following CLSI-C62A guidance. Though routine checks ensure the quality of results reported for each run, there is also a need to evaluate metrics between runs over time. Post-implementation performance monitoring of LC-MS/MS methods is typically focused on calibration curves, retention times, peak intensities, and ion ratios.

Quantitative NMR (qNMR) spectroscopy based investigation of the absolute content, stability and isomerization of 25-hydroxyvitamin D2/D3 and 24(R),25-dihydroxyvitamin D2 in solution phase

Vitamin D is an important parameter, in serum/plasma based diagnostic analysis, for the determination of optimal regulation of calcium and phosphate homeostases in the human body, vital for the monitoring/progression of osteomalacia and rickets. Particularly, the quantification of 25-hydroxyvitamin D2, 25-hydroxyvitamin D3 and 24R,25-dihydroxyvitamin D in blood is an excellent indicator for the vitamin D status of a patient. For this purpose, LC–MS/MS methods, based on appropriate vitamin D reference standards, are considered to be ‘gold standard’ for such measurements. We have utilized quantitative NMR spectroscopy to determine the absolute content of these molecules, available as non-certified chemicals, and have determined the stability of these callibrators in borderline polar solvents at room temperature. We have observed significant isomerization of the analytes, which can play a big role in quantification of these analytes by hyphenated LC and GC analytical techniques. Appropriate explanations are given for the observation of new impurities with time in solution phase. The spin system selected for quantitation was determined using relevant 1D and 2D NMR pulse sequences. The advantage of the qNMR approach is that it is based on the quantification of atoms rather than molecular properties (e.g., quantitation by LC/UV, GC, etc.). Since the signals in an NMR spectrum are different nuclear spin-systems dispersed precisely in a magnetic environment, with the intensity being directly proportional to the amount of a particular type of nuclear spin, this technique delivers unparalleled information about the chemical structure and the absolute content.

Isotopic Distribution Calibration for Mass Spectrometry

Mass spectrometry (MS) is widely used in science and industry. It allows accurate, specific, sensitive, and reproducible detection and quantification of a huge range of analytes. Across MS applications, quantification by MS has grown most dramatically, with >50 million experiments/year in the USA alone. However, quantification performance varies between instruments, compounds, different samples, and within- and across runs, necessitating normalization with analyte-similar internal standards (IS) and use of IS-corrected multipoint external calibration curves for each analyte, a complicated and resource-intensive approach, which is particularly ill-suited for multi-analyte measurements. We have developed an internal calibration method that utilizes the natural isotope distribution of an IS for a given analyte to provide internal multipoint calibration. Multiple isotope distribution calibrators for different targets in the same sample facilitate multiplex quantification, while the emerging random-access automated MS platforms should also greatly benefit from this approach. Finally, isotope distribution calibration allows mathematical correction for suboptimal experimental conditions. This might also enable quantification of hitherto difficult, or impossible to quantify, targets, if the distribution is adjusted in silico to mimic the analyte. The approach works well for high resolution, accurate mass MS for analytes with at least a modest-sized isotopic envelope. As shown herein, the approach can also be applied to lower molecular weight analytes, but the reduction in calibration points does reduce quantification performance.

Machine Learning Identifies Metabolic Signatures that Predict the Risk of Recurrent Angina in Remitted Patients after Percutaneous Coronary Intervention: A Multicenter Prospective Cohort Study

Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations. In this multicenter study, plasma samples are collected from patients with stable angina after PCI, and these patients are followed-up for 9 months for angina recurrence. Broad-spectrum metabolomic profiling with LC-MS/MS followed by multiple machine learning algorithms is conducted to identify the metabolic signatures associated with future risk of angina recurrence in two large cohorts (n = 750 for discovery set, and n = 775 for additional independent discovery cohort). The metabolic predictors are further validated in a third cohort from another center (n = 130) using a clinically-sound quantitative approach. Compared to angina-free patients, the remitted patients with future RA demonstrates a unique chemical endophenotype dominated by abnormalities in chemical communication across lipid membranes and mitochondrial function. A novel multi-metabolite predictive model constructed from these latent signatures can stratify remitted patients at high-risk for angina recurrence with over 89% accuracy, sensitivity, and specificity across three independent cohorts. Our findings revealed reproducible plasma metabolic signatures to predict patients with a latent future risk of RA during post-PCI remission, allowing them to be treated in advance before an event.

Calibrating from Within: Multipoint Internal Calibration of a Quantitative Mass Spectrometric Assay of Serum Methotrexate

BACKGROUND

Clinical LC-MS/MS assays traditionally require that samples be run in batches with calibration curves in each batch. This approach is inefficient and presents a barrier to random access analysis. We developed an alternative approach called multipoint internal calibration (MPIC) that eliminated the need for batch-mode analysis.

METHODS

The new approach used 4 variants of 13C-labeled methotrexate (0.026-10.3 µM) as an internal calibration curve within each sample. One site carried out a comprehensive validation, which included an evaluation of interferences and matrix effects, lower limit of quantification (LLOQ), and 20-day precision. Three sites evaluated assay precision and linearity. MPIC was also compared with traditional LC-MS/MS and an immunoassay.

RESULTS

Recovery of spiked analyte was 93%-102%. The LLOQ was validated to be 0.017 µM. Total variability, determined in a 20-day experiment, was 11.5%CV. In a 5-day variability study performed at each site, total imprecision was 3.4 to 16.8%CV. Linearity was validated throughout the calibrator range (r2 > 0.995, slopes = 0.996-1.01). In comparing 40 samples run in each laboratory, the median interlaboratory imprecision was 6.55%CV. MPIC quantification was comparable to both traditional LC-MS/MS and immunoassay (r2 = 0.96-0.98, slopes = 1.04-1.06). Bland-Altman analysis of all comparisons showed biases rarely exceeding 20% when MTX concentrations were >0.4 µM.

CONCLUSION

The MPIC method for serum methotrexate quantification was validated in a multisite proof-of-concept study and represents a big step toward random-access LC-MS/MS analysis, which could change the paradigm of mass spectrometry in the clinical laboratory.

Recent developments in software tools for high-throughput in vitro ADME support with high-resolution MS

The last several years have seen the rapid adoption of the high-resolution MS (HRMS) for bioanalytical support of high throughput in vitro ADME profiling. Many capable software tools have been developed and refined to process quantitative HRMS bioanalysis data for ADME samples with excellent performance. Additionally, new software applications specifically designed for quan/qual soft spot identification workflows using HRMS have greatly enhanced the quality and efficiency of the structure elucidation process for high throughput metabolite ID in early in vitro ADME profiling. Finally, novel approaches in data acquisition and compression, as well as tools for transferring, archiving and retrieving HRMS data, are being continuously refined to tackle the issue of large data file size typical for HRMS analyses.

Deproteination of whole blood for LC-MS/MS using paramagnetic micro-particles

OBJECTIVES

Liquid chromatography tandem mass spectrometry has become increasingly popular in clinical laboratories over the last decade due to the inherent sensitivity and specificity of the technology. Nevertheless, full automation and hence application in routine laboratories is still hampered by laborious and difficult-to-automate sample pre-treatment protocols. Functionalized paramagnetic micro-particles could simplify sample pre-treatment and ease automation. We evaluated the applicability of a pre-commercial, straightforward paramagnetic micro-particle based kit for the lysis and deproteination of whole blood for the LC-MS/MS analysis of everolimus and compared the performance to our routine protein precipitation method.

DESIGN AND METHODS

Samples were prepared for LC-MS/MS everolimus analysis on an Acquity UPLC chromatographic system coupled to a TQD mass spectrometer (both Waters Ltd.) using a pre-commercial MagSi-TDMprep kit and a routine protein precipitation respectively. Both pre-treatment methods were validated for imprecision, accuracy, linearity, limit of quantification, matrix effect, recovery and process efficiency. A method comparison (n=63) between both pre-treatment methods was performed.

RESULTS

Imprecision and bias were within pre-defined criteria (15%) for both pre-treatment methods. Both methods were linear from 1.2 to 14.8μg/L with a limit of quantification of 0.6μg/L. Process efficiency was on average 65% for protein precipitation pre-treatment and was substantially higher for the MagSi-TDMprep method (85%). A Passing-Bablok regression showed no significant difference between the two pre-treatment methods.

CONCLUSION

For everolimus in whole blood, the MagSi-TDMprep sample pre-treatment was applicable and comparable to protein precipitation for LC-MS/MS with the possible advantage of easier automation.

A novel approach to quantitative LC-MS/MS: therapeutic drug monitoring of clozapine and norclozapine using isotopic internal calibration

Therapeutic drug monitoring (TDM) requires timely results in order to be clinically helpful. Such assays, when carried out using mass spectrometry-based methods, typically involve a batched sample approach with multipoint calibration. Isotopic internal calibration offers the possibility of open-access mass spectrometric analysis with consequent shortening of turnaround times. We measured plasma clozapine and N-desmethylclozapine (norclozapine) concentrations in (1) external quality assessment (EQA) samples (N = 22) and (2) patient samples (N = 100) using liquid chromatography-tandem mass spectrometry with isotopic internal calibration (ICAL-LC-MS/MS). Analyte concentrations were calculated from graphs of the response of three internal calibrators (clozapine-D4, norclozapine-D8, and clozapine-D8) against concentration. Precision (% RSD) and accuracy (% nominal concentrations) for the ICAL-LC-MS/MS method were <5 % and 104-112 %, respectively for both analytes. There was excellent agreement with consensus mean and with 'spiked' values on analysis of the EQA samples (R (2) = 0.98 and 0.97, respectively, inclusive of clozapine and norclozapine results). In the patient samples, comparison against traditionally calibrated HPLC-UV and LC-MS/MS methods showed excellent agreement (R (2) = 0.97 or better) with small albeit significant mean differences (<0.041 and <0.042 mg/L for clozapine and norclozapine, respectively). These differences probably reflect discrepancies in the in-house preparation of calibrators and/or interference in the UV method. Internal calibration offers a novel and attractive alternative to traditionally calibrated batch analysis in analytical toxicology. The method described has been validated for use in the high-throughput TDM of clozapine and norclozapine, and allows for (1) same-day reporting of results and (2) significant cost savings.