Quantitative gas chromatography/time-of-flight mass spectrometry: a review

Development of stability-indicating method for separation and characterization of benidipine forced degradation products using LC-MS/MS

The present study describes forced degradation of benidipine (BEN) as per  Q1A (R2) and Q1B guidelines of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. BEN degraded under hydrolysis (neutral, acidic, and alkaline), hydrogen peroxide induced oxidation, and UV light mediated photolytic degradation. A total of 14 degradation products (DPs) were found in all degradation studies, comprising 4 hydrolytic DPs, 8 oxidative DPs, and 4 photolytic DPs. A selective stability-indicating method was developed using an XBridge BEH C18 column with gradient elution program consisting of ammonium acetate (10 mM, 4.8 pH, acetic acid) and acetonitrile. The flow rate was maintained at 1 ml min^-1 . All DPs were separated well using the developed HPLC method and were characterized using LC-MS/MS data. As this method is effective in identifying and separating BEN and its DPs with sufficient resolution, it can be used in laboratories for quality control of drugs in daily routine analysis and stability studies.

Simulating comprehensive two-dimensional gas chromatography mass spectrometry data with realistic run-to-run shifting to evaluate the robustness of tile-based Fisher ratio analysis

Untargeted analysis of comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data has the potential to be hindered by run-to-run retention time shifting. To address this challenge, tile-based Fisher ratio (F-ratio) analysis (FRA) has been developed, which utilizes a supervised, untargeted approach involving a chromatographic segmentation routine termed "tiling" combined with the ANOVA F-ratio statistic to discover class-distinguishing analytes while minimizing false positives arising from shifting. The tiling algorithm is designed to account for retention shifting in both separation dimensions. Although applications of FRA have been reported, there remains a need to thoroughly evaluate the robustness of FRA for different levels of run-to-run retention shifting in order to broaden the scope of its application. To this end, a novel method of simulating GC×GC-TOFMS chromatograms with realistic run-to-run shifting is presented by random generation of low-frequency "shift functions". The dimensionless retention-time precision, <δ_r>, which is four times the standard deviation in retention time normalized to the peak width-at-base is used as a key modeling variable along with the 2D chromatographic saturation, α_e,2D, and within-class relative standard deviation in peak area, RSD_wc. We demonstrate that all three of these variables operate together to impact true positive discovery. To quantify the "success" of true positive discovery, GC×GC-TOFMS datasets for various combinations of <δ_r>, α_e,2D, and RSD_wc were simulated and then analyzed by FRA using a wide range of relative tile areas (RTA), which is a dimensionless measure of tile size. Since each hit in the FRA hit list was known a priori as either a true or false positive based on the simulation inputs, receiver operating characteristic (ROC) curves were readily constructed. Then, the area under the ROC curve (AUROC) was used as a metric for discovery "success" for various combinations of the modeling variables. Based on the results of this study, recommendations for tile size selection and experimental design are provided, and further supported by comparison to previous tile-based FRA applications. For instance, values for <δ_r>, α_e,2D, and RSD_wc obtained from a GC×GC-TOFMS dataset of yeast metabolites suggested an optimum RTA of 6.25, corresponding closely to the RTA of 4.00 employed in the study, implying the simulation results obtained here can be generalized to real datasets.

Breath-Based Diagnosis of Infectious Diseases: A Review of the Current Landscape

Various analytical methods can be applied to concentrate, separate, and examine trace volatile organic metabolites in the breath, with the potential for noninvasive, rapid, real-time identification of various disease processes, including an array of microbial infections. Although biomarker discovery and validation in microbial infections can be technically challenging, it is an approach that has shown great promise, especially for infections that are particularly difficult to identify with standard culture and molecular amplification-based approaches. This article discusses the current state of breath analysis for the diagnosis of infectious diseases.

Hepcidin quantification: methods and utility in diagnosis

Hepcidin is a 25-amino acid peptide hormone that is produced and secreted predominantly by hepatocytes, circulates in the bloodstream, and is excreted by the kidneys. Since the discovery of hepcidin and the elucidation of its important role in iron homeostasis, hepcidin has been suggested as a promising diagnostic marker for iron-related disorders. In this regard, a number of analytical methods have been developed in order to assess hepcidin concentration in different biological fluids, particularly serum and urine. In this critical review we have tried to address the issues still pending in accurate determination of this peptide by evaluating the available analytical methodologies. Among them, the use of ELISA strategies (in competitive or sandwich formats) and molecular mass spectrometry (MS) including MALDI and/or LC-MS has been critically compared. The use of elemental mass spectrometry (ICP-MS) has also been included as a possible complementary tool to the previous ones. In addition, this manuscript has revised the existing and potentially emerging clinical applications of hepcidin testing for diagnosis. These include the iron disorders such as iron deficiency anemia (IDA, low hepcidin), anemia of chronic disease (ACD, high hepcidin) and the combined state of ACD and IDA or hemochromatosis. Other applications such as using hepcidin in assessing the response to existing therapies in cancer have also been revised in the manuscript.

Current use of high-resolution mass spectrometry in the environmental sciences

During the last two decades, mass spectrometry (MS) has been increasingly used in the environmental sciences with the objective of investigating the presence of organic pollutants. MS has been widely coupled with chromatographic techniques, both gas chromatography (GC) and liquid chromatography (LC), because of their complementary nature when facing a broad range of organic pollutants of different polarity and volatility. A clear trend has been observed, from the very popular GC-MS with a single quadrupole mass analyser, to tandem mass spectrometry (MS-MS) and, more recently, high-resolution mass spectrometry (HRMS). For years GC has been coupled to HR magnetic sector instruments, mostly for dioxin analysis, although in the last ten years there has been growing interest in HRMS with time-of-flight (TOF) and Orbitrap mass analyzers, especially in LC-MS analysis. The increasing interest in the use of HRMS in the environmental sciences is because of its suitability for both targeted and untargeted analysis, owing to its sensitivity in full-scan acquisition mode and high mass accuracy. With the same instrument one can perform a variety of tasks: pre- and post-target analysis, retrospective analysis, discovery of metabolite and transformation products, and non-target analysis. All these functions are relevant to the environmental sciences, in which the analyst encounters thousands of different organic contaminants. Thus, wide-scope screening of environmental samples is one of the main applications of HRMS. This paper is a critical review of current use of HRMS in the environmental sciences. Needless to say, it is not the intention of the authors to summarise all contributions of HRMS in this field, as in classic descriptive reviews, but to give an overview of the main characteristics of HRMS, its strong potential in environmental mass spectrometry and the trends observed over the last few years. Most of the literature has been acquired since 2005, coinciding with the growth and popularity of HRMS in this field, with a few exceptions that deserve to be mentioned because of their relevance.

Current mass spectrometry strategies for the analysis of pesticides and their metabolites in food and water matrices

Analysis of pesticides and their metabolites in food and water matrices continues to be an active research area closely related to food safety and environmental issues. This review discusses the most widely applied mass spectrometric (MS) approaches to pesticide residues analysis over the last few years. The main techniques for sample preparation remain solvent extraction and solid-phase extraction. The QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) approach is being increasingly used for the development of multi-class pesticide residues methods in various sample matrices. MS detectors-triple quadrupole (QqQ), ion-trap (IT), quadrupole linear ion trap (QqLIT), time-of-flight (TOF), and quadrupole time-of-flight (QqTOF)-have been established as powerful analytical tools sharing a primary role in the detection/quantification and/or identification/confirmation of pesticides and their metabolites. Recent developments in analytical instrumentation have enabled coupling of ultra-performance liquid chromatography (UPLC) and fast gas chromatography (GC) with MS detectors, and faster analysis for a greater number of pesticides. The newly developed "ambient-ionization" MS techniques (e.g., desorption electrospray ionization, DESI, and direct analysis in real time, DART) hyphenated with high-resolution MS platforms without liquid chromatography separation, and sometimes with minimum pre-treatment, have shown potential for pesticide residue screening. The recently introduced Orbitrap mass spectrometers can provide high resolving power and mass accuracy, to tackle complex analytical problems involved in pesticide residue analysis.

Fast, low-pressure gas chromatography triple quadrupole tandem mass spectrometry for analysis of 150 pesticide residues in fruits and vegetables

We developed and evaluated a new method of low-pressure gas chromatography-tandem mass spectrometry (LP-GC/MS-MS) using a triple quadrupole instrument for fast analysis of 150 relevant pesticides in four representative fruits and vegetables. This LP-GC (vacuum outlet) approach entails coupling a 10 m, 0.53 mm i.d., 1 μm film analytical column between the MS transfer line and a 3 m, 0.15 mm i.d. capillary at the inlet. The MS creates a vacuum in the 10 m analytical column, which reduces the viscosity of the He carrier gas and thereby shifts the optimal flow rate to greater velocity. By taking advantage of the H(2)-like properties of He under vacuum, the short analytical column, a rapid oven temperature ramp rate, and the high selectivity and sensitivity of MS/MS, 150 pesticides were separated in <6.5 min. The 2.5 ms dwell time and 1 ms interscan delay of the MS/MS instrument were critical for achieving >8 data points across the 2-3 s wide peaks. To keep dwell and cycle times constant across all peaks, each segment consisted of 30 analytes (60 transitions). For assessment, we injected extracts of spiked broccoli, cantaloupe, lemon, and sweet potato from the updated QuEChERS sample preparation method. Average recoveries (n=72) were 70-120% for 144 of the pesticides, and reproducibilities were <20% RSD for all but 4 analytes. Also, detection limits were <5 ng/g for all but a few pesticides, depending on the matrix. In addition to high quality performance, the method gave excellent reliability and high sample throughput, including easy peak integration to obtain rapid results.

Volatile compound fingerprinting of mixed-culture fermentations

With the advent of the -omics era, classical technology platforms, such as hyphenated mass spectrometry, are currently undergoing a transformation toward high-throughput application. These novel platforms yield highly detailed metabolite profiles in large numbers of samples. Such profiles can be used as fingerprints for the accurate identification and classification of samples as well as for the study of effects of experimental conditions on the concentrations of specific metabolites. Challenges for the application of these methods lie in the acquisition of high-quality data, data normalization, and data mining. Here, a high-throughput fingerprinting approach based on analysis of headspace volatiles using ultrafast gas chromatography coupled to time of flight mass spectrometry (ultrafast GC/TOF-MS) was developed and evaluated for classification and screening purposes in food fermentation. GC-MS mass spectra of headspace samples of milk fermented by different mixed cultures of lactic acid bacteria (LAB) were collected and preprocessed in MetAlign, a dedicated software package for the preprocessing and comparison of liquid chromatography (LC)-MS and GC-MS data. The Random Forest algorithm was used to detect mass peaks that discriminated combinations of species or strains used in fermentations. Many of these mass peaks originated from key flavor compounds, indicating that the presence or absence of individual strains or combinations of strains significantly influenced the concentrations of these components. We demonstrate that the approach can be used for purposes like the selection of strains from collections based on flavor characteristics and the screening of (mixed) cultures for the presence or absence of strains. In addition, we show that strain-specific flavor characteristics can be traced back to genetic markers when comparative genome hybridization (CGH) data are available.

Accelerating analysis for metabolomics, drugs and their metabolites in biological samples using multidimensional gas chromatography

Gas chromatography (GC) with mass spectrometry (MS) is one of the great enabling analytical tools available to the chemical and biochemical analyst for the measurement of volatile and semi-volatile compounds. From the analysis result, it is possible to assess progress in chemical reactions, to monitor environmental pollutants in a wide range of soil, water or air samples, to determine if an athlete or horse trainer has contravened doping laws, or if crude oil has migrated through subsurface rock to a reservoir. Each of these scenarios and samples has an associated implementation method for GC-MS. However, few samples and the associated interpretation of data is as complex or important as biochemical sample analysis for trace drugs or metabolites. Improving the analysis in both the GC and MS domains is a continual search for better separation, selectivity and sensitivity. Multidimensional methods are playing important roles in providing quality data to address the needs of analysts.

Classification of jet fuels by fuzzy rule-building expert systems applied to three-way data by fast gas chromatography--fast scanning quadrupole ion trap mass spectrometry

A fast method that can be used to classify unknown jet fuel types or detect possible property changes in jet fuel physical properties is of paramount interest to national defense and the airline industries. While fast gas chromatography (GC) has been used with conventional mass spectrometry (MS) to study jet fuels, fast GC was combined with fast scanning MS and used to classify jet fuels into lot numbers or origin for the first time by using fuzzy rule-building expert system (FuRES) classifiers. In the process of building classifiers, the data were pretreated with and without wavelet transformation and evaluated with respect to performance. Principal component transformation was used to compress the two-way data images prior to classification. Jet fuel samples were successfully classified with 99.8 ± 0.5% accuracy for both with and without wavelet compression. Ten bootstrapped Latin partitions were used to validate the generalized prediction accuracy. Optimized partial least squares (o-PLS) regression results were used as positively biased references for comparing the FuRES prediction results. The prediction results for the jet fuel samples obtained with these two methods were compared statistically. The projected difference resolution (PDR) method was also used to evaluate the fast GC and fast MS data. Two batches of aliquots of ten new samples were prepared and run independently 4 days apart to evaluate the robustness of the method. The only change in classification parameters was the use of polynomial retention time alignment to correct for drift that occurred during the 4-day span of the two collections. FuRES achieved perfect classifications for four models of uncompressed three-way data. This fast GC/fast MS method furnishes characteristics of high speed, accuracy, and robustness. This mode of measurement may be useful as a monitoring tool to track changes in the chemical composition of fuels that may also lead to property changes.