No abstract

A major constraint in large-scale mass spectrometry (MS)-based metabolomic initiatives is the low sample throughput associated with chromatographic or electrophoretic separations. Herein, we introduce multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) as a multiplexed separation platform for metabolomics that increases sample throughput up to one order of magnitude while improving overall data fidelity. We demonstrate that serial injection of seven or more discrete sample segments can be performed within a single capillary while maintaining isomeric resolution without ion suppression when using a high mass resolution time-of-flight-MS. Customized injection sequences can be devised to encode information temporally within a separation based on signal pattern recognition, which enables unambiguous identification and accurate quantification (mean bias <10%) of polar metabolites in human plasma with good reproducibility (CV ≈ 10%, n = 70). False discoveries are avoided when using a rigorous dilution trend filter to reject spurious signals and background peaks that comprise the majority (≈65%) of total detectable features. MSI-CE-MS offers an unprecedented approach to enhance sample throughput analogous to direct infusion-MS (≈3 min/sample) while delivering far greater selectivity, quantitative performance, and data quality since the same ion from different samples migrates into the ion source within a short time interval (≈2-6 min). These distinct analytical and bioinformatic merits are achieved without column switching, isotopic labeling, hardware modifications, or costly infrastructure investments.

High-intensity interval training (HIIT) offers a practical approach for enhancing cardiorespiratory fitness, however its role in improving glucose regulation among sedentary yet normoglycemic women remains unclear. Herein, multi-segment injection capillary electrophoresis-mass spectrometry is used as a high-throughput platform in metabolomics to assess dynamic responses of overweight/obese women (BMI > 25, n = 11) to standardized oral glucose tolerance tests (OGTTs) performed before and after a 6-week HIIT intervention. Various statistical methods were used to classify plasma metabolic signatures associated with post-prandial glucose and/or training status when using a repeated measures/cross-over study design. Branched-chain/aromatic amino acids and other intermediates of urea cycle and carnitine metabolism decreased over time in plasma after oral glucose loading. Adaptive exercise-induced changes to plasma thiol redox and orthinine status were measured for trained subjects while at rest in a fasting state. A multi-linear regression model was developed to predict changes in glucose tolerance based on a panel of plasma metabolites measured for naïve subjects in their untrained state. Since treatment outcomes to physical activity are variable between-subjects, prognostic markers offer a novel approach to screen for potential negative responders while designing lifestyle modifications that maximize the salutary benefits of exercise for diabetes prevention on an individual level.

High efficiency separations are needed to enhance selectivity, mass spectral quality, and quantitative performance in metabolomic studies. However, low sample throughput and complicated data preprocessing remain major bottlenecks to biomarker discovery. We introduce an accelerated data workflow to identify plasma metabolite signatures of exercise responsiveness when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). This multiplexed separation platform takes advantage of customizable serial injections to enhance sample throughput and data fidelity based on temporally resolved ion signals derived from seven different sample segments analyzed within a single run. MSI-CE-MS was applied to explore the adaptive metabolic responses of a cohort of overweight/obese women (BMI > 25, n = 9) performing a 6-wk high-intensity interval training intervention using a repeated measures/cross-over study design. Venous blood samples were collected from each subject at three time intervals (baseline, postexercise, recovery) in their naïve and trained states while completing standardized cycling trials at the same absolute workload. Complementary statistical methods were used to classify dynamic changes in plasma metabolism associated with strenuous exercise and training status. Positive adaptations to exercise were associated with training-induced upregulation in plasma l-carnitine at rest due to improved muscle oxidative capacity, and greater antioxidant capacity as reflected by lower circulating glutathionyl-l-cysteine mixed disulfide. Attenuation in plasma hypoxanthine and higher O-acetyl-l-carnitine levels postexercise also indicated lower energetic stress for trained women.

The biological activity of estrogens is tightly regulated by regioselective phase I/II metabolic transformations that are critical to human health. Current methods for analysis of urinary estrogens are limited by complicated sample pretreatment and/or inadequate specificity for free estrogens and their glucuronide/sulfate conjugates that vary widely in their intrinsic polarity. In this work, direct speciation of intact estrogen conjugates and their regioisomers is demonstrated using capillary electrophoresis-time-of-flight/mass spectrometry (CE-TOF/MS) when using an alkaline buffer system with negative ion mode detection. This method allows for resolution of weakly acidic native estrogens, anionic estrogen conjugates and their positional isomers without significant matrix-induced ion suppression effects in human urine. Identification of unknown estrogen metabolites using CE-TOF/MS is supported by accurate mass together with their characteristic relative migration times, which can be predicted based on two intrinsic physicochemical properties of an ion. CE-TOF/MS offers a promising strategy for comprehensive profiling of estrogens and other classes of steroid conjugates that is needed for deeper insight into the etiology and treatment of chronic disorders associated with impaired estrogen metabolism.