Multisegment Injection-capillary Electrophoresis-mass Spectrometry Research Articles

Metabolic Signatures of Cystic Fibrosis Identified in Dried Blood Spots For Newborn Screening Without Carrier Identification.

Cystic fibrosis (CF) is a complex multiorgan disorder that is among the most common fatal genetic diseases benefiting from therapeutic interventions early in life. Newborn screening (NBS) for presymptomatic detection of CF currently relies on a two-stage immunoreactive trypsinogen (IRT) and cystic fibrosis transmembrane conductance regulator (CFTR) mutation panel algorithm that is sensitive but not specific for identifying affected neonates with a low positive predictive value. For the first time, we report the discovery of a panel of CF-specific metabolites from a single 3.2 mm diameter dried blood spot (DBS) punch when using multisegment injection-capillary electrophoresis-mass spectrometry (MS) as a high-throughput platform for nontargeted metabolite profiling from volume-restricted/biobanked specimens with quality control. This retrospective case-control study design identified 32 metabolites, including a series of N-glycated amino acids, oxidized glutathione disulfide, and nicotinamide that were differentially expressed in normal birth weight CF neonates without meconium ileus ( n = 36) as compared to gestational age/sex-matched screen-negative controls ( n = 44) after a false discovery rate adjustment ( q < 0.05). Also, 16 metabolites from DBS extracts allowed for discrimination of true CF cases from presumptive screen-positive carriers with one identified CFTR mutation and transient neonatal hypertrypsinogenemic neonates ( n = 72), who were later confirmed as unaffected due to a low sweat chloride (<29 mM) test result. Importantly, six CF-specific biomarker candidates satisfying a Bonferroni adjustment ( p < 7.25 × 10-5) from three independent batches of DBS specimens included several amino acids depleted in circulation (Tyr, Ser, Thr, Pro, Gly) likely reflecting protein maldigestion/malabsorption. Additionally, CF neonates had lower ophthalmic acid as an indicator of oxidative stress due to impaired glutathione efflux from exocrine/epithelial tissue and elevation of an unknown trivalent peptide that was directly correlated with IRT (ρ = 0.332, p = 4.55 × 10-4). Structural elucidation of unknown metabolites was performed by high-resolution MS/MS, whereas biomarker validation was realized when comparing a subset of metabolites from matching neonatal DBS specimens independently analyzed by direct infusion-MS/MS at an accredited NBS facility. This work sheds new light into the metabolic phenotype of CF early in life, which is required for better functional understanding of CFTR mutations of unknown clinical consequence and the development of more accurate yet cost-effective strategies for CF screening.

High Throughput Screening Method for Systematic Surveillance of Drugs of Abuse by Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry.

New technologies are urgently required for reliable drug screening given a worldwide epidemic of prescription drug abuse and its devastating socioeconomic impacts on public health. Primary screening of drugs of abuse (DoA) currently relies on immunoassays that are prone to bias and are not applicable to detect an alarming array of psychoactive stimulants, tranquilizers, and synthetic opioids. These limitations impact patient safety when monitoring for medication compliance, drug substitution, or misuse/abuse and require follow-up confirmatory testing by more specific yet lower throughput instrumental methods. Herein, we introduce a high throughput platform for nontargeted screening of a broad spectrum of DoA and their metabolites based on multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). We demonstrate that MSI-CE-MS enables serial injections of 10 samples within a single run (<3 min/sample) where multiplexed electrophoretic separations are coupled to high resolution MS with full-scan data acquisition. Unambiguous drug identification was achieved by four or more independent parameters, including comigration with a deuterated internal standard or in silico prediction of electromigration behavior together with accurate mass, most likely molecular formula, as well as MS/MS as required for confirmation testing. Acceptable precision was demonstrated for over 50 DoA at 3 concentration levels over 4 days (median coefficient of variance = 13%, n = 117) with minimal ion suppression, isobaric interferences, and sample carry-over (<1%). This approach offers a rapid yet accurate method for simultaneous detection and identification of DoA at their recommended screening cutoff levels in human urine while allowing for systematic surveillance, specimen verification, and retrospective testing of designer drugs that elude conventional drug tests.

The Sweat Metabolome of Screen-Positive Cystic Fibrosis Infants: Revealing Mechanisms beyond Impaired Chloride Transport.

The sweat chloride test remains the gold standard for confirmatory diagnosis of cystic fibrosis (CF) in support of universal newborn screening programs. However, it provides ambiguous results for intermediate sweat chloride cases while not reflecting disease progression when classifying the complex CF disease spectrum given the pleiotropic effects of gene modifiers and environment. Herein we report the first characterization of the sweat metabolome from screen-positive CF infants and identify metabolites associated with disease status that complement sweat chloride testing. Pilocarpine-stimulated sweat specimens were collected independently from two CF clinics, including 50 unaffected infants (e.g., carriers) and 18 confirmed CF cases. Nontargeted metabolite profiling was performed using multisegment injection–capillary electrophoresis–mass spectrometry as a high throughput platform for analysis of polar/ionic metabolites in volume-restricted sweat samples. Amino acids, organic acids, amino acid derivatives, dipeptides, purine derivatives, and unknown exogenous compounds were identified in sweat when using high resolution tandem mass spectrometry, including metabolites associated with affected yet asymptomatic CF infants, such as asparagine and glutamine. Unexpectedly, a metabolite of pilocarpine, used to stimulate sweat secretion, pilocarpic acid, and a plasticizer metabolite from environmental exposure, mono(2-ethylhexyl)phthalic acid, were secreted in the sweat of CF infants at significantly lower concentrations relative to unaffected CF screen-positive controls. These results indicated a deficiency in human paraoxonase, an enzyme unrelated to mutations to the cystic fibrosis transmembrane conductance regulator (CFTR) and impaired chloride transport, which is a nonspecific arylesterase/lactonase known to mediate inflammation, bacterial biofilm formation, and recurrent lung infections in affected CF children later in life. This work sheds new light into the underlying mechanisms of CF pathophysiology as required for new advances in precision medicine of orphan diseases that benefit from early detection and intervention, including new molecular targets for therapeutic intervention.

Temporal Signal Pattern Recognition in Mass Spectrometry: A Method for Rapid Identification and Accurate Quantification of Biomarkers for Inborn Errors of Metabolism with Quality Assurance.

Mass spectrometry (MS)-based metabolomic initiatives that use conventional separation techniques are limited by low sample throughput and complicated data processing that contribute to false discoveries. Herein, we introduce a new strategy for unambiguous identification and accurate quantification of biomarkers for inborn errors of metabolism (IEM) from dried blood spots (DBS) with quality assurance. A multiplexed separation platform based on multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) was developed to provide comparable sample throughput to flow injection analysis-tandem MS (FIA-MS/MS) but with greater selectivity as required for confirmatory testing and discovery-based metabolite profiling of volume-restricted biospecimens. Mass spectral information is encoded temporally within a separation by serial injection of three or more sample pairs, each having a unique dilution pattern, alongside a quality control (QC) that serves as a reference in every run to facilitate between-sample comparisons and/or batch correction due to system drift. Optimization of whole blood extraction conditions on DBS filter paper cut-outs was first achieved to maximize recovery of a wide range of polar metabolites from DBS extracts. An interlaboratory comparison study was also conducted using a proficiency test and retrospective neonatal DBS that demonstrated good agreement between MSI-CE-MS and validated FIA-MS/MS methods within an accredited facility. Our work demonstrated accurate identification of various IEM based on reliable measurement of a panel of primary or secondary biomarkers above an upper cutoff concentration limit for presumptive screen-positive cases without stable isotope-labeled reagents. Additionally, nontargeted metabolite profiling by MSI-CE-MS with temporal signal pattern recognition revealed new biomarkers for early detection of galactosemia, such as N-galactated amino acids, that are a novel class of pathognomonic marker due to galactose stress in affected neonates.

Multiplexed separations for biomarker discovery in metabolomics: Elucidating adaptive responses to exercise training.

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.

Personalized metabolomics for predicting glucose tolerance changes in sedentary women after high-intensity interval training.

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.

Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry: A High-Throughput Platform for Metabolomics with High Data Fidelity

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.