Luke C. Marney

Simultaneous Quantification of Apolipoprotein A-I and Apolipoprotein B by Liquid-Chromatography–Multiple- Reaction–Monitoring Mass Spectrometry

BACKGROUND If liquid-chromatography-multiple-reaction-monitoring mass spectrometry (LC-MRM/MS) could be used in the large-scale preclinical verification of putative biomarkers, it would obviate the need for the development of expensive immunoassays. In addition, the translation of novel biomarkers to clinical use would be accelerated if the assays used in preclinical studies were the same as those used in the clinical laboratory. To validate this approach, we developed a multiplexed assay for the quantification of 2 clinically well-known biomarkers in human plasma, apolipoprotein A-I and apolipoprotein B (apoA-I and apoB). METHODS We used PeptideAtlas to identify candidate peptides. Human samples were denatured with urea or trifluoroethanol, reduced and alkylated, and digested with trypsin. We compared reversed-phase chromatographic separation of peptides with normal flow and microflow, and we normalized endogenous peptide peak areas to internal standard peptides. We evaluated different methods of calibration and compared the final method with a nephelometric immunoassay. RESULTS We developed a final method using trifluoroethanol denaturation, 21-h digestion, normal flow chromatography-electrospray ionization, and calibration with a single normal human plasma sample. For samples injected in duplicate, the method had intraassay CVs <6% and interassay CVs <12% for both proteins, and compared well with immunoassay (n = 47; Deming regression, LC-MRM/MS = 1.17 × immunoassay - 36.6; S(x|y) = 10.3 for apoA-I and LC-MRM/MS = 1.21 × immunoassay + 7.0; S(x|y) = 7.9 for apoB). CONCLUSIONS Multiplexed quantification of proteins in human plasma/serum by LC-MRM/MS is possible and compares well with clinically useful immunoassays. The potential application of single-point calibration to large clinical studies could simplify efforts to reduce day-to-day digestion variability.

Cardiac-Specific Deletion of Acetyl CoA Carboxylase 2 Prevents Metabolic Remodeling During Pressure-Overload Hypertrophy

Rationale: Decreased fatty acid oxidation (FAO) with increased reliance on glucose are hallmarks of metabolic remodeling that occurs in pathological cardiac hypertrophy and is associated with decreased myocardial energetics and impaired cardiac function. To date, it has not been tested whether prevention of the metabolic switch that occurs during the development of cardiac hypertrophy has unequivocal benefits on cardiac function and energetics. Objective: Because malonyl CoA production via acetyl CoA carboxylase 2 (ACC2) inhibits the entry of long chain fatty acids into the mitochondria, we hypothesized that mice with a cardiac-specific deletion of ACC2 (ACC2H−/−) would maintain cardiac FAO and improve function and energetics during the development of pressure-overload hypertrophy. Methods and Results: ACC2 deletion led to a significant reduction in cardiac malonyl CoA levels. In isolated perfused heart experiments, left ventricular function and oxygen consumption were similar in ACC2H−/− mice despite an ≈60% increase in FAO compared with controls (CON). After 8 weeks of pressure overload via transverse aortic constriction (TAC), ACC2H−/− mice exhibited a substrate utilization profile similar to sham animals, whereas CON-TAC hearts had decreased FAO with increased glycolysis and anaplerosis. Myocardial energetics, assessed by 31P nuclear magnetic resonance spectroscopy, and cardiac function were maintained in ACC2H−/− after 8 weeks of TAC. Furthermore, ACC2H−/−-TAC demonstrated an attenuation of cardiac hypertrophy with a significant reduction in fibrosis relative to CON-TAC. Conclusions: These data suggest that reversion to the fetal metabolic profile in chronic pathological hypertrophy is associated with impaired myocardial function and energetics and maintenance of the inherent cardiac metabolic profile and mitochondrial oxidative capacity is a viable therapeutic strategy.

Review of chemometric analysis techniques for comprehensive two dimensional separations data

Comprehensive two-dimensional (2D) separations, such as comprehensive 2D gas chromatography (GC×GC), liquid chromatography (LC×LC), and related instrumental techniques, provide very large and complex data sets. It is often up to the software to assist the analyst in transforming these complex data sets into useful information, and that is precisely where the field of chemometric data analysis plays a pivotal role. Chemometric tools for comprehensive 2D separations are continually being developed and applied as researchers make significant advances in novel state-of-the-art algorithms and software, and as the commercial sector continues to provide user friendly chemometric software. In this review, we build upon previous reviews of this topic, by focusing primarily on advances that have been reported in the past five years. Most of the reports focus on instrumental platforms using GC×GC with either flame ionization detection (FID) or time-of-flight mass spectrometry (TOFMS) detection, or LC×LC with diode array absorbance detection (DAD). The review covers the following general topics: data preprocessing techniques, target analyte techniques, comprehensive nontarget analysis techniques, and software for chemometrics in multidimensional separations.

Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma

A critical question facing the field of metabolomics is whether data obtained from different centers can be effectively compared and combined. An important aspect of this is the interlaboratory precision (reproducibility) of the analytical protocols used. We analyzed human samples in six laboratories using different instrumentation but a common protocol (the AbsoluteIDQ p180 kit) for the measurement of 189 metabolites via liquid chromatography (LC) or flow injection analysis (FIA) coupled to tandem mass spectrometry (MS/MS). In spiked quality control (QC) samples 82% of metabolite measurements had an interlaboratory precision of <20%, while 83% of averaged individual laboratory measurements were accurate to within 20%. For 20 typical biological samples (serum and plasma from healthy individuals) the median interlaboratory coefficient of variation (CV) was 7.6%, with 85% of metabolites exhibiting a median interlaboratory CV of <20%. Precision was largely independent of the type of sample (serum or plasma) or the anticoagulant used but was reduced in a sample from a patient with dyslipidaemia. The median interlaboratory accuracy and precision of the assay for standard reference plasma (NIST SRM 1950) were 107% and 6.7%, respectively. Likely sources of irreproducibility were the near limit of detection (LOD) typical abundance of some metabolites and the degree of manual review and optimization of peak integration in the LC-MS/MS data after acquisition. Normalization to a reference material was crucial for the semi-quantitative FIA measurements. This is the first interlaboratory assessment of a widely used, targeted metabolomics assay illustrating the reproducibility of the protocol and how data generated on different instruments could be directly integrated in large-scale epidemiological studies.

Isopropanol Protein Precipitation for the Analysis of Plasma Free Metanephrines by Liquid Chromatography–Tandem Mass Spectrometry

BACKGROUND High-performance liquid chromatography-tandem mass spectrometric (LC-MS/MS)1 analysis of plasma free metanephrines is the most diagnostically sensitive and specific screening test for the diagnosis of pheochromocytoma. We sought to develop an in-house method for this expensive test METHODS We used off-line isopropanol protein precipitation of plasma to remove interfering substances before LC-MS/MS analysis. We compared the extraction efficiency and limits of quantification of protein precipitation to those of previously reported solid-phase techniques. RESULTS The new method had limits of quantification of 0.09 nmol/L and 0.17 nmol/L for metanephrine and normetanephrine, respectively. Method comparison with a previously described solid-phase extraction method revealed Deming regression slopes of 0.904 and 0.994, intercepts of 0.007 and 0.023, and SEs of the residuals (S(y/x)) of 0.071 and 0.284 for metanephrine and normetanephrine, respectively. Extraction efficiency of isopropanol protein precipitation was 66% for metanephrine and 35% for normetanephrine, results that were superior to the efficiencies of 4% and 1% for our adapted solid-phase extraction method. No ion suppression was observed at the retention times for metanephrine and normetanephrine. CONCLUSIONS Isopropanol protein precipitation is a novel and effective off-line sample preparation method for metanephrines that offers a less expensive alternative to on-line solid-phase extraction for low-volume testing and requires a sample volume of only 200 microL. The mass spectrometric analysis time is equivalent to that of solid-phase techniques.

Tile-based Fisher ratio analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) data using a null distribution approach.

Comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) is a versatile instrumental platform capable of collecting highly informative, yet highly complex, chemical data for a variety of samples. Fisher-ratio (F-ratio) analysis applied to the supervised comparison of sample classes algorithmically reduces complex GC × GC-TOFMS data sets to find class distinguishing chemical features. F-ratio analysis, using a tile-based algorithm, significantly reduces the adverse effects of chromatographic misalignment and spurious covariance of the detected signal, enhancing the discovery of true positives while simultaneously reducing the likelihood of detecting false positives. Herein, we report a study using tile-based F-ratio analysis whereby four non-native analytes were spiked into diesel fuel at several concentrations ranging from 0 to 100 ppm. Spike level comparisons were performed in two regimes: comparing the spiked samples to the nonspiked fuel matrix and to each other at relative concentration factors of two. Redundant hits were algorithmically removed by refocusing the tiled results onto the original high resolution pixel level data. To objectively limit the tile-based F-ratio results to only features which are statistically likely to be true positives, we developed a combinatorial technique using null class comparisons, called null distribution analysis, by which we determined a statistically defensible F-ratio cutoff for the analysis of the hit list. After applying null distribution analysis, spiked analytes were reliably discovered at ∼1 to ∼10 ppm (∼5 to ∼50 pg using a 200:1 split), depending upon the degree of mass spectral selectivity and 2D chromatographic resolution, with minimal occurrence of false positives. To place the relevance of this work among other methods in this field, results are compared to those for pixel and peak table-based approaches.

Serial Plasma Metabolites Following Hypoxic-Ischemic Encephalopathy in a Nonhuman Primate Model

Biomarkers that indicate the severity of hypoxic-ischemic brain injury and response to treatment and that predict neurodevelopmental outcomes are urgently needed to improve the care of affected neonates. We hypothesize that sequentially obtained plasma metabolomes will provide indicators of brain injury and repair, allowing for the prediction of neurodevelopmental outcomes. A total of 33 Macaca nemestrina underwent 0, 15 or 18 min of in utero umbilical cord occlusion (UCO) to induce hypoxic-ischemic encephalopathy and were then delivered by hysterotomy, resuscitated and stabilized. Serial blood samples were obtained at baseline (cord blood) and at 0.1, 24, 48, and 72 h of age. Treatment groups included nonasphyxiated controls (n = 7), untreated UCO (n = 11), UCO + hypothermia (HT; n = 6), and UCO + HT + erythropoietin (n = 9). Metabolites were extracted and analyzed using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and quantified by PARAFAC (parallel factor analysis). Using nontargeted discovery-based methods, we identified 63 metabolites as potential biomarkers. The changes in metabolite concentrations were characterized and compared between treatment groups. Further comparison determined that 8 metabolites (arachidonic acid, butanoic acid, citric acid, fumaric acid, lactate, malate, propanoic acid, and succinic acid) correlated with early and/or long-term neurodevelopmental outcomes. The combined outcomes of death or cerebral palsy correlated with citric acid, fumaric acid, lactate, and propanoic acid. This change in circulating metabolome after UCO may reflect cellular metabolism and biochemical changes in response to the severity of brain injury and have potential to predict neurodevelopmental outcomes.

Sample preparation methodology for mouse heart metabolomics using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

The investigation of naturally volatile and derivatized metabolites in mammalian tissues by comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) can provide the data for a comprehensive analysis of the pathophysiology of disease processes. When relative quantification is needed for hypothesis testing, the preparation of sample tissue must provide clear evidence that a quantitative relationship exists between the final detected signal and the amount of metabolite in the tissue. Herein, we report the optimization of a metabolite extraction method for mouse heart tissue for GC × GC-TOFMS analysis. A recursive extraction experiment was initially performed to measure the extraction efficiency of representative target metabolites (sugars, tricarboxylic acid cycle metabolites, amino acids, lipid and signaling molecules) in the aqueous fraction of a three-phase extraction system involving tissue, methanol:water, and chloroform. Some metabolites suffered from incomplete extraction with a single extraction of ≈ 40 mg in 600 μl organic and 400 μl aqueous phases, possibly caused by saturation effects. Subsequent experiments, calibrating resulting metabolite signal to the mass of heart tissue extracted, demonstrated that doubling the solvent volumes and a lower tissue mass was needed to provide accurate relative quantification of the derivatized mouse heart metabolome. We demonstrate quantitative extraction of metabolites from ≈ 20 mg of heart tissue using 1200 μl organic phase (chloroform) and 800 μl aqueous phase (methanol:water in equal parts by volume).

Methods of Discovery-Based and Targeted Metabolite Analysis by Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometry Detection

The investigation of naturally volatile and derivatized metabolites in biological tissues by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) can provide highly complex and information-rich data for comprehensive metabolomics analysis. The addition of the second separation dimension with GC × GC provides additional chemical selectivity, and the fast scanning time of TOFMS offers benefits in chemical selectivity and overall peak capacity compared to traditional one-dimensional (1D) GC. Furthermore, methods of derivatization to facilitate volatility and thermal stability, the most prominent being the silylation of organic compounds, have extended the use of GC as an important metabolomics tool. The highly information-rich data from GC × GC-TOFMS benefits from sophisticated comprehensive targeted and nontargeted algorithmic software methods. Herein, we detail a robust derivatization and instrumental method for metabolomics analysis and provide a brief overview of possible methods for data analysis.