Analytical and Bioanalytical Chemistry (v.405, #15)
Ji-Xin Cheng and Xiaoliang Sunney Xie (Eds.): Coherent Raman scattering microscopy by David S. Moore (5001-5002).
Metabolomics and metabolite profiling by Rainer Schuhmacher; Rudolf Krska; Wolfram Weckwerth; Royston Goodacre (5003-5004).
is Associate Professor in the Department for Agrobiotechnology (IFA-Tulln) of the University of Natural Resources and Life Sciences, Vienna (BOKU). He currently heads the Metabolomics and Bioactive Compounds working group at BOKU, IFA-Tulln, and in the last few years he has shifted his research focus towards LC–MS- and GC–MS-based metabolomics of microbes and plants. In 2012 he received the Fritz Feigl Award of the Austrian Society of Analytical Chemistry and he is the author or coauthor of more than 80 publications. is Professor of (Bio-)analytics and Organic Trace Analysis and is head of the Department for Agrobiotechnology (IFA-Tulln) at the University of Natural Resources and Life Sciences, Vienna (BOKU). In 2009–2010 he worked for 1 year as A/Chief of Health Canada’s Food Research Division in Ottawa. He is an expert in food analysis by chromatographic and mass spectrometric techniques. In the last few years his research focus has been on metabolomics and metabolite profiling to study plant–fungi interactions, an area which has been funded by the Austrian Science Fund within a Special Research Programme. He has received six scientific awards and is the author or coauthor of more than 180 publications. is Professor and Chair of the Department of Molecular Systems Biology at the University of Vienna (Austria). Prior to this, he was at the Max Planck Institute of Molecular Plant Physiology in Potsdam (Germany), where he established metabolomic methods and integrated proteomic and metabolic modelling approaches into a systems biology framework. He became the head of a research laboratory in the German FORSYS systems biology initiative before founding the Department of Molecular Systems Biology at the University of Vienna in 2008. is currently Professor of Biological Chemistry at the University of Manchester (UK). His group’s main areas of research ( http://www.biospec.net/ ) are broadly within analytical biotechnology, metabolomics and systems biology. His expertise involves MS, Fourier transform IR spectroscopy and Raman spectroscopy, as well as advanced chemometrics, machine learning and evolutionary computational methods. He is Editor-in-Chief of the journal Metabolomics, a founding director of the Metabolomics Society and one of the directors of the Metabolic Profiling Forum.
Metabolomics for unknown plant metabolites by Ryo Nakabayashi; Kazuki Saito (5005-5011).
In this article we discuss current trends in the techniques available for plant metabolomics. Chemical assignment of unknown metabolites leads to understanding of biosynthetic mechanisms at the gene level for genome-sequenced plants. Metabolomics using mass spectrometry has achieved innovative results in phytochemical genomics for primary and secondary metabolism in the model plant Arabidopsis thaliana by using publicly and commercially available information and standard compounds. However, finding a consolidated analytical technique for elucidation of structural information (e.g., elemental composition and structure) remains challenging. Recently, hyphenated analytical techniques and computer-assisted structural analysis with high-throughput and high-accuracy have been developing. Metabolite-driven approaches using such technology will be of central importance in phytochemical genomics.
Keywords: Metabolomics; Unknown secondary metabolites; LC–MS; LC–SPE–NMR–MS; Computer-assisted structure elucidation
Metabolomics of colorectal cancer: past and current analytical platforms by Michael D. Williams; Raymond Reeves; Linda S. Resar; Herbert H. Hill Jr. (5013-5030).
Metabolomics is coming of age as an important area of investigation which may help reveal answers to questions left unanswered or only partially understood from proteomic or genomic approaches. Increased knowledge of the relationship of genes and proteins to smaller biomolecules (metabolites) will advance our ability to diagnose, treat, and perhaps prevent cancer and other diseases that have eluded scientists for generations. Colorectal tumors are the second leading cause of cancer mortality in the USA, and the incidence is rising. Many patients present late, after the onset of symptoms, when the tumor has spread from the primary site. Once metastases have occurred, the prognosis is significantly worse. Understanding alterations in metabolic profiles that occur with tumor onset and progression could lead to better diagnostic tests as well as uncover new approaches to treat or even prevent colorectal cancer (CRC). In this review, we explore the various analytical technologies that have been applied in CRC metabolomics research and summarize all metabolites measured in CRC and integrate them into metabolic pathways. Early studies with nuclear magnetic resonance and gas-chromatographic mass spectrometry suggest that tumor cells are characterized by aerobic glycolysis, increased purine metabolism for DNA synthesis, and protein synthesis. Liquid chromatography, capillary electrophoresis, and ion mobility, each coupled with mass spectrometry, promise to advance the field and provide new insight into metabolic pathways used by cancer cells. Studies with improved technology are needed to identify better biomarkers and targets for treatment or prevention of CRC. Abstract Figure 2D IMMS spectra of Tumor and normal matched tissues. Several metabolites are detected within the bracketed area in only the Tumor sample.
Keywords: Bioanalytical methods; Mass spectrometry/inductively coupled plasma mass spectrometry; Nuclear magnetic resonance/electron spin resonance; High-performance liquid chromatography; Gas chromatography; Capillary electrophoresis/electrophoresis
Stable isotopic labelling-assisted untargeted metabolic profiling reveals novel conjugates of the mycotoxin deoxynivalenol in wheat by Bernhard Kluger; Christoph Bueschl; Marc Lemmens; Franz Berthiller; Georg Häubl; Günther Jaunecker; Gerhard Adam; Rudolf Krska; Rainer Schuhmacher (5031-5036).
An untargeted screening strategy for the detection of biotransformation products of xenobiotics using stable isotopic labelling (SIL) and liquid chromatography–high resolution mass spectrometry (LC-HRMS) is reported. The organism of interest is treated with a mixture of labelled and non-labelled precursor and samples are analysed by LC-HRMS. Raw data are processed with the recently developed MetExtract software for the automated extraction of corresponding peak pairs. The SIL-assisted approach is exemplified by the metabolisation of the Fusarium mycotoxin deoxynivalenol (DON) in planta. Flowering ears were inoculated with 100 μg of a 1 + 1 (v/v) mixture of non-labelled and fully labelled DON. Subsequent sample preparation, LC-HRMS measurements and data processing revealed a total of 57 corresponding peak pairs, which originated from ten metabolites. Besides the known DON and DON-3-glucoside, which were confirmed by measurement of authentic standards, eight further DON-biotransformation products were found by the untargeted screening approach. Based on a mass deviation of less than ±5 ppm and MS/MS measurements, one of these products was annotated as DON-glutathione (GSH) conjugate, which is described here for the first time for wheat. Our data further suggest that two DON-GSH-related metabolites, the processing products DON-S-cysteine and DON-S-cysteinyl-glycine and five unknown DON conjugates were formed in planta. Future MS/MS measurements shall reveal the molecular structures of the detected conjugates in more detail.
Keywords: Metabolisation; Xenobiotics; Stable isotopic labelling; Deoxynivalenol; Liquid chromatography–high resolution mass spectrometry; Mycotoxin conjugate
Metabolite profiling and beyond: approaches for the rapid processing and annotation of human blood serum mass spectrometry data by Jan Stanstrup; Michael Gerlich; Lars Ove Dragsted; Steffen Neumann (5037-5048).
In this paper, we describe data processing and metabolite identification approaches which lead to a rapid and semi-automated interpretation of metabolomics experiments. Data from metabolite fingerprinting using LC-ESI-Q-TOF/MS were processed with several open-source software packages, including XCMS and CAMERA to detect features and group features into compound spectra. Next, we describe the automatic scheduling of tandem mass spectrometry (MS) acquisitions to acquire a large number of MS/MS spectra, and the subsequent processing and computer-assisted annotation towards identification using the R packages MetShot, Rdisop, and the MetFusion application. We also implement a simple retention time prediction model using predicted lipophilicity logD, which predicts retention times within 42 s (6 min gradient) for most compounds in our setup. We putatively identified 44 common metabolites including several amino acids and phospholipids at metabolomics standards initiative (MSI) levels two and three and confirmed the majority of them by comparison with authentic standards at MSI level one. To aid both data integration within and data sharing between laboratories, we integrated data from two labs and mapped retention times between the chromatographic systems. Despite the different MS instrumentation and different chromatographic gradient programs, the mapped retention times agree within 26 s (20 min gradient) for 90 % of the mapped features. Figure Workflow for the rapid processing and annotation of untargeted mass spectrometry data
Keywords: Human metabolome; Metabolite fingerprinting; Mass spectrometry; Metabolite identification; Retention time prediction; Isotope pattern scoring
An efficient spectra processing method for metabolite identification from 1H-NMR metabolomics data by Daniel Jacob; Catherine Deborde; Annick Moing (5049-5061).
The spectra processing step is crucial in metabolomics approaches, especially for proton NMR metabolomics profiling. During this step, noise reduction, baseline correction, peak alignment and reduction of the 1D 1H-NMR spectral data are required in order to allow biological information to be highlighted through further statistical analyses. Above all, data reduction (binning or bucketing) strongly impacts subsequent statistical data analysis and potential biomarker discovery. Here, we propose an efficient spectra processing method which also provides helpful support for compound identification using a new data reduction algorithm that produces relevant variables, called buckets. These buckets are the result of the extraction of all relevant peaks contained in the complex mixture spectra, rid of any non-significant signal. Taking advantage of the concentration variability of each compound in a series of samples and based on significant correlations that link these buckets together into clusters, the method further proposes automatic assignment of metabolites by matching these clusters with the spectra of reference compounds from the Human Metabolome Database or a home-made database. This new method is applied to a set of simulated 1H-NMR spectra to determine the effect of some processing parameters and, as a proof of concept, to a tomato 1H-NMR dataset to test its ability to recover the fruit extract compositions. The implementation code for both clustering and matching steps is available upon request to the corresponding author. Figure Illustration of the processing approach from spectra bucketing to the proposal of candidate compounds, using a set of six simulated NMR spectra. First, the ERVA method of data reduction is applied to the spectra after noise processing, generating buckets as shown for two spectra regions. Second, the correlation matrix between bucket intensities is computed and a correlation threshold is applied for bucket clustering. The cluster shown gathers two sub-clusters (A and B), each being intra-connected with higher correlations (r > 0.996) than the interconnections (r < 0.994). Third, matching of the cluster with using a reference compound library provides a list of candidate compounds. Last, for validation, the reference spectrum of proline is shown with the corresponding matched regions highlighted.
Keywords: 1H-NMR spectroscopy; Spectra processing; Metabolite identification; Metabolomics
Integrating multiple analytical platforms and chemometrics for comprehensive metabolic profiling: application to meat spoilage detection by Yun Xu; Elon Correa; Royston Goodacre (5063-5074).
Untargeted metabolic profiling has become a common approach to attempt to understand biological systems. However, due to the large chemical diversity in the metabolites it is generally necessary to employ multiple analytical platforms so as to encompass a wide range of metabolites. Thus it is beneficial to find chemometrics approaches which can effectively integrate data generated from multiple platforms and ideally combine the strength of each platform and overcome their inherent weaknesses; most pertinent is with respect to limited chemistries. We have reported a few studies using untargeted metabolic profiling techniques to monitor the natural spoilage process in pork and also to detect specific metabolites associated with contaminations with the pathogen Salmonella typhimurium. One method used was to analyse the volatile organic compounds (VoCs) generated throughout the spoilage process while the other was to analyse the soluble small molecule metabolites (SMM) extracted from the microbial community, as well as from the surface of the spoiled/contaminated meat. In this study, we exploit multi-block principal component analysis (MB-PCA) and multi-block partial least squares (MB-PLS) to combine the VoCs and SMM data together and compare the results obtained by analysing each data set individually. We show that by combining the two data sets and applying appropriate chemometrics, a model with much better prediction and importantly with improved interpretability was obtained. The MB-PCA model was able to combine the strength of both platforms together and generated a model with high consistency with the biological expectations, despite its unsupervised nature. MB-PLS models also achieved the best over-all performance in modelling the spoilage progression and discriminating the naturally spoiled samples and the pathogen contaminated samples. Correlation analysis and Bayesian network analysis were also performed to elucidate which metabolites were correlated strongly in the two data sets and such information could add additional information in understanding the meat spoilage process.
Keywords: Multi-block principal component analysis; Multi-block partial least squares; Data fusion; Correlation analysis; Bayesian network; Pork spoilage; Salmonella typhimurium
High-throughput carotenoid profiling using multivariate curve resolution by Ron Wehrens; Elisabete Carvalho; Domenico Masuero; Anna de Juan; Stefan Martens (5075-5086).
We present automated data analysis of high-throughput high-performance liquid chromatography with diode array detection (HPLC-DAD) data using multivariate curve resolution. This technique provides spectra and elution profiles of all UV-Vis active compounds present in the mixture. The specifics of using this method in noninteractive fashion are discussed. A case study on the stability of isoprenoids in grape extracts under two different experimental regimes serves to illustrate the potential of the method: quantitative results clearly show that the addition of triethylamine is beneficial in that carotenoid, chlorophyll, and tocopherol compounds are much more stable and in this way can be kept up to at least 30 days without any sign of degradation.
Keywords: Multivariate data analysis; HPLC-DAD; Metabolomics; Grapes; Isoprenoids
Development and validation of a (semi-)quantitative UHPLC-MS/MS method for the determination of 191 mycotoxins and other fungal metabolites in almonds, hazelnuts, peanuts and pistachios by Elisabeth Varga; Thomas Glauner; Franz Berthiller; Rudolf Krska; Rainer Schuhmacher; Michael Sulyok (5087-5104).
A multi-target method for the determination of 191 fungal metabolites in almonds, hazelnuts, peanuts and pistachios was developed. The method includes all mycotoxins regulated in the European Union and mycotoxins regularly found in food. After extraction with an acidified acetonitrile water mixture, the raw extract was diluted and injected directly into the UHPLC-MS/MS system. In two chromatographic runs, analysis was performed in positive and in negative ionisation mode. The method was in-house validated for the most important 65 analytes in these four commodities. Apparent recoveries between 80 and 120 % were obtained for about half of the analyte–matrix combinations. Good repeatabilities (standard deviations < 10 %) were achieved for the vast majority (83 %) of all cases. Only in 6 % of all combinations did the standard deviations exceed 15 %. Matrix effects, arising during electrospray ionisation, significantly influenced the determination. For instance, signal suppression was observed for several early-eluting analytes and also signal enhancement up to 295 % for physcion in peanuts was determined. Concerning extraction recovery, 94 % of the analyte–matrix combinations showed values higher than 50 %. Lower limits of quantification ranged between 0.04 μg kg−1 for enniatin B3 in peanuts and 500 μg kg−1 for HC toxin in hazelnuts. Additionally, the applicability of the developed method was demonstrated through the analysis of 53 naturally contaminated nut samples from Austria and Turkey. Overall, 40 toxins were quantified; the most frequently found mycotoxins were beauvericin (79 %), enniatin B (62 %) and macrosporin (57 %). In the most contaminated hazelnut sample, 26 different fungal metabolites were detected.
Keywords: Multi-target analysis; Tandem mass spectrometry; Ultra-high-performance liquid chromatography; Nuts
Hippocampal metabolomics using ultrahigh-resolution mass spectrometry reveals neuroinflammation from Alzheimer’s disease in CRND8 mice by Shuhai Lin; Hongde Liu; Basem Kanawati; Liangfeng Liu; Jiyang Dong; Min Li; Jiandong Huang; Philippe Schmitt-Kopplin; Zongwei Cai (5105-5117).
In the wake of genomics, metabolomics characterizes the small molecular metabolites revealing the phenotypes induced by gene mutants. To address the metabolic signatures in the hippocampus of the amyloid-beta (Aβ) peptides produced in transgenic (Tg) CRND8 mice, high-field ion cyclotron resonance–Fourier transform mass spectrometry supported by LC-LTQ-Orbitrap was introduced to profile the extracted metabolites. More than 10,000 ions were detected in the mass profile for each sample. Subsequently, peak alignment and the 80 % rule followed by feature selection based on T score computation were performed. The putative identification was also conducted using the highly accurate masses with isotopic distribution by interfacing the MassTRIX database as well as MS/MS fragmentation generated in the LTQ-Orbitrap after chromatographic separation. Consequently, 58 differentiating masses were tentatively identified while up to 44 differentiating elemental compositions could not be biologically annotated in the databases. Nonetheless, of the putatively annotated masses, eicosanoids in arachidonic acid metabolism, fatty acid beta-oxidation disorders as well as disturbed glucose metabolism were highlighted as metabolic traits of Aβ toxicity in Tg CRND8 mice. Furthermore, a web-based bioinformatic tool was used for simulation of the metabolic pathways. As a result of the obtained metabolic signatures, the arachidonic acid metabolism dominates the metabolic perturbation in hippocampal tissues of Tg CRND8 mice compared to non-Tg littermates, indicating that Aβ toxicity functions neuroinflammation in hippocampal tissue and new theranostic opportunities might be offered by characterization of altered arachidonic acid metabolism for Alzheimer’s disease.
Keywords: Metabolomics; FTMS; Arachidonic acid metabolism; Hippocampus; Alzheimer’s disease
Molecular cartography in acute Chlamydia pneumoniae infections—a non-targeted metabolomics approach by Constanze Müller; Inga Dietz; Dimitrios Tziotis; Franco Moritz; Jan Rupp; Philippe Schmitt-Kopplin (5119-5131).
Infections with Chlamydia pneumoniae cause several respiratory diseases, such as community-acquired pneumonia, bronchitis or sinusitis. Here, we present an integrated non-targeted metabolomics analysis applying ultra-high-resolution mass spectrometry and ultra-performance liquid chromatography mass spectrometry to determine metabolite alterations in C. pneumoniae-infected HEp-2 cells. Most important permutations are elaborated using uni- and multivariate statistical analysis, logD retention time regression and mass defect-based network analysis. Classes of metabolites showing high variations upon infection are lipids, carbohydrates and amino acids. Moreover, we observed several non-annotated compounds as predominantly abundant after infection, which are promising biomarker candidates for drug-target and diagnostic research.
Keywords: Mass spectrometry; Host–pathogen interactions; Liquid chromatography
Measurement uncertainty of isotopologue fractions in fluxomics determined via mass spectrometry by R. Guerrasio; C. Haberhauer-Troyer; M. Steiger; M. Sauer; D. Mattanovich; G. Koellensperger; S. Hann (5133-5146).
Metabolic flux analysis implies mass isotopomer distribution analysis and determination of mass isotopologue fractions (IFs) of proteinogenic amino acids of cell cultures. In this work, for the first time, this type of analysis is comprehensively investigated in terms of measurement uncertainty by calculating and comparing budgets for different mass spectrometric techniques. The calculations addressed amino acids of Pichia pastoris grown on 10 % uniformly 13C labeled glucose. Typically, such experiments revealed an enrichment of 13C by at least one order of magnitude in all proteinogenic amino acids. Liquid chromatography–time-of-flight mass spectrometry (LC-TOFMS), liquid chromatography–tandem mass spectrometry (LC-MS/MS) and gas chromatography–mass spectrometry (GC-MS) analyses were performed. The samples were diluted to fit the linear dynamic range of the mass spectrometers used (10 μM amino acid concentration). The total combined uncertainties of IFs as well as the major uncertainty contributions affecting the IFs were determined for phenylalanine, which was selected as exemplary model compound. A bottom-up uncertainty propagation was performed according to Quantifying Uncertainty in Analytical Measurement and using the Monte Carlo method by considering all factors leading to an IF, i.e., the process of measurement and the addition of 13C-glucose. Excellent relative expanded uncertainties (k = 1) of 0.32, 0.75, and 0.96 % were obtained for an IF value of 0.7 by LC-MS/MS, GC-MS, and LC-TOFMS, respectively. The major source of uncertainty, with a relative contribution of 20–80 % of the total uncertainty, was attributed to the signal intensity (absolute counts) uncertainty calculated according to Poisson counting statistics, regardless which of the mass spectrometry platforms was used. Uncertainty due to measurement repeatability was of importance in LC-MS/MS, showing a relative contribution up to 47 % of the total uncertainty, whereas for GC-MS and LC-TOFMS the average contribution was lower (30 and 15 %, respectively). Moreover, the IF actually present also depends on the isotopic purity of the carbon sources. Therefore, in the uncertainty calculation a carbon source purity factor was introduced and a minor contribution to the total uncertainty was observed. The results obtained by uncertainty calculation performed according to the Monte Carlo method were in agreement with the uncertainty value of the Kragten approach and showed a Gaussian distribution.
Keywords: Measurement uncertainty; Monte Carlo method; Fluxomics; Isotopologue fraction; Mass isotopomer distribution; Mass spectrometry
Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow by J. A. Kirwan; D. I. Broadhurst; R. L. Davidson; M. R. Viant (5147-5157).
Direct infusion mass spectrometry (DIMS)-based untargeted metabolomics measures many hundreds of metabolites in a single experiment. While every effort is made to reduce within-experiment analytical variation in untargeted metabolomics, unavoidable sources of measurement error are introduced. This is particularly true for large-scale multi-batch experiments, necessitating the development of robust workflows that minimise batch-to-batch variation. Here, we conducted a purpose-designed, eight-batch DIMS metabolomics study using nanoelectrospray (nESI) Fourier transform ion cyclotron resonance mass spectrometric analyses of mammalian heart extracts. First, we characterised the intrinsic analytical variation of this approach to determine whether our existing workflows are fit for purpose when applied to a multi-batch investigation. Batch-to-batch variation was readily observed across the 7-day experiment, both in terms of its absolute measurement using quality control (QC) and biological replicate samples, as well as its adverse impact on our ability to discover significant metabolic information within the data. Subsequently, we developed and implemented a computational workflow that includes total-ion-current filtering, QC-robust spline batch correction and spectral cleaning, and provide conclusive evidence that this workflow reduces analytical variation and increases the proportion of significant peaks. We report an overall analytical precision of 15.9 %, measured as the median relative standard deviation (RSD) for the technical replicates of the biological samples, across eight batches and 7 days of measurements. When compared against the FDA guidelines for biomarker studies, which specify an RSD of <20 % as an acceptable level of precision, we conclude that our new workflows are fit for purpose for large-scale, high-throughput nESI DIMS metabolomics studies.
Keywords: Batch effect; Block effects; QC-RSC; Relative standard deviation; Reproducibility
Interlaboratory comparison for quantitative primary metabolite profiling in Pichia pastoris by Kristaps Klavins; Stefan Neubauer; Ali Al Chalabi; Denise Sonntag; Christina Haberhauer-Troyer; Hannes Russmayer; Michael Sauer; Diethard Mattanovich; Stephan Hann; Gunda Koellensperger (5159-5169).
For the first time, an interlaboratory comparison was performed in the field of quantitative metabolite profiling in Pichia pastoris. The study was designed for the evaluation of different measurement platforms integrating different quantification strategies using internal standardization. Nineteen primary metabolites including amino acids and organic acids were selected for the study. Homogenous samples were obtained from chemostat fermentations after rapid sampling, quenching and filtration, and hot ethanol extraction. Laboratory 1 (BOKU) employed an in vivo-synthesized fully labeled U13C cell extracts of P. pastoris for immediate internal standardization upon cell extraction. Quantification was carried out using orthogonal reversed-phase (RP-LC) and hydrophilic interaction chromatography (HILIC) in combination with tandem mass spectrometry. Laboratory 2 (Biocrates) applied a metabolomics kit allowing fully automated, rapid derivatization, solid phase extraction and internal standardization in 96-well plates with immobilized isotopically enriched internal standards in combination with HILIC-MS-MS and RP-LC-MS-MS for organic acids and derivatized amino acids, respectively. In this study, the obtained intracellular concentrations ranged from 0.2 to 108 μmol g−1 cell dry weight. The total combined uncertainty was estimated including uncertainty contributions from the corresponding MS-based measurement and sample preparation for each metabolite. Evidently, the uncertainty contribution of sample preparation was lower for the values obtained by laboratory 1, implementing isotope dilution upon extraction. Total combined uncertainties (K = 2) ranging from 21 to 48 % and from 30 to 57 % were assessed for the quantitative results obtained in laboratories 1 and 2, respectively. The major contribution arose from sample preparation, hence from repeatability precision of the extraction procedure. Finally, the laboratory intercomparison was successful as most of the investigated metabolites showed concentration levels agreeing within their total combined uncertainty, implying that accurate quantification was given. The application of isotope dilution upon extraction was an absolute prerequisite for the quantification of the redox-sensitive amino acid methionine, where no agreement between the two laboratories could be achieved.
Keywords: Metabolomics; Interlaboratory comparison; LC-MS/MS; Pichia pastoris
REMUS100 AUV with an integrated microfluidic system for explosives detection by André A. Adams; Paul T. Charles; Scott P. Veitch; Alfred Hanson; Jeffrey R. Deschamps; Anne W. Kusterbeck (5171-5178).
Quantitating explosive materials at trace concentrations in real-time on-site within the marine environment may prove critical to protecting civilians, waterways, and military personnel during this era of increased threat of widespread terroristic activity. Presented herein are results from recent field trials that demonstrate detection and quantitation of small nitroaromatic molecules using novel high-throughput microfluidic immunosensors (HTMI) to perform displacement-based immunoassays onboard a HYDROID REMUS100 autonomous underwater vehicle. Missions were conducted 2–3 m above the sea floor, and no HTMI failures were observed due to clogging from biomass infiltration. Additionally, no device leaks were observed during the trials. HTMIs maintained immunoassay functionality during 2 h deployments, while continuously sampling seawater absent without any pretreatment at a flow rate of 2 mL/min. This 20-fold increase in the nominal flow rate of the assay resulted in an order of magnitude reduction in both lag and assay times. Contaminated seawater that contained 20–175 ppb trinitrotoluene was analyzed. Figure Displacement-based immunoassay targeting trinitrotoluene is shown
Keywords: Remote sensing; Explosives; Microfluidics; Autonomous underwater vehicles; Displacement-based immunoassay
Detection of arsenic-containing hydrocarbons in a range of commercial fish oils by GC-ICPMS analysis by Veronika Sele; Heidi Amlund; Marc H. G. Berntssen; Jannicke A. Berntsen; Kasper Skov; Jens J. Sloth (5179-5190).
The present study describes the use of a simple solid-phase extraction procedure for the extraction of arsenic-containing hydrocarbons from fish oil followed by analysis using gas chromatography (GC) coupled to inductively coupled plasma mass spectrometry (ICPMS). The procedure permitted the analysis of a small sample amount, and the method was applied on a range of different commercial fish oils, including oils of anchovy (Engraulis ringens), Atlantic herring (Clupea harengus), sand eel (Ammodytes marinus), blue whiting (Micromesistius poutassou) and a commercial mixed fish oil (mix of oils of Atlantic herring, Atlantic cod (Gadus morhua) and saithe (Pollachius virens)). Total arsenic concentrations in the fish oils and in the extracts of the fish oils were determined by microwave-assisted acid digestion and ICPMS. The arsenic concentrations in the fish oils ranged from 5.9 to 8.7 mg kg−1. Three dominant arsenic-containing hydrocarbons in addition to one minor unidentified compound were detected in all the oils using GC-ICPMS. The molecular structures of the arsenic-containing hydrocarbons, dimethylarsinoyl hydrocarbons (C17H38AsO, C19H42AsO, C23H38AsO), were verified using GC coupled to tandem mass spectrometry (MS/MS), and the accurate masses of the compounds were verified using quadrupole time-of-flight mass spectrometry (qTOF-MS). Additionally, total arsenic and the arsenic-containing hydrocarbons were studied in decontaminated and in non-decontaminated fish oils, where a reduced arsenic concentration was seen in the decontaminated fish oils. This provided an insight to how a decontamination procedure originally ascribed for the removal of persistent organic pollutants affects the level of arsenolipids present in fish oils.
Keywords: Arsenic; Arsenolipids; ICPMS; Decontamination; Speciation; GC-MS/MS; qTOF-MS
A high-throughput method for the quantification of iron saturation in lactoferrin preparations by Grzegorz Majka; Klaudyna Śpiewak; Katarzyna Kurpiewska; Piotr Heczko; Grażyna Stochel; Magdalena Strus; Małgorzata Brindell (5191-5200).
Lactoferrin is considered as a part of the innate immune system that plays a crucial role in preventing bacterial growth, mostly via an iron sequestration mechanism. Recent data show that bovine lactoferrin prevents late-onset sepsis in preterm very low birth weight neonates by serving as an iron chelator for some bacterial strains; thus, it is very important to control the iron saturation level during diet supplementation. An accurate estimation of lactoferrin iron saturation is essential not only because of its clinical applications but also for a wide range of biochemical experiments. A comprehensive method for the quantification of iron saturation in lactoferrin preparations was developed to obtain a calibration curve enabling the determination of iron saturation levels relying exclusively on the defined ratio of absorbances at 280 and 466 nm (A 280/466). To achieve this goal, selected techniques such as spectrophotometry, ELISA, and ICP-MS were combined. The ability to obtain samples of lactoferrin with determination of its iron content in a simple and fast way has been proven to be very useful. Furthermore, a similar approach could easily be implemented to facilitate the determination of iron saturation level for other metalloproteins in which metal binding results in the appearance of a distinct band in the visible part of the spectrum.
Keywords: Lactoferrin; Iron saturation; Absorption ratio; ICP-MS
Unexpectedly high levels of antimony (III) in the pentavalent antimonial drug Glucantime: insights from a new voltammetric approach by Pascal Salaün; Frédéric Frézard (5201-5214).
Glucantime, a pentavalent antimonial drug, is commonly used for the treatment of leishmaniasis but the presence of residual trivalent antimony, Sb(III), is thought to be responsible for toxic side-effects observed in patients. Numerous analytical studies have focused on determining Sb(III) concentrations in Glucantime but without reaching a consensus: results span over 3 orders of magnitude. In this study, we present a detailed new analytical approach showing that: (1) Sb(III) levels are much higher than previously reported and represent more than 30 % of total Sb; (2) determination of Sb(III) concentrations in acidic conditions is hampered by fast oxidation rates. This latter point explains the large variations in previously reported results of Sb(III) concentrations in Glucantime. Measurements were made here at a vibrated gold microwire electrode by stripping voltammetry enabling measurement of Sb(III) in acidic, neutral or alkaline conditions. The developed methods are sensitive (e.g., detection limits of 19 pM for 120 s deposition at pH 4.5), stable (<6 %, N = 100), precise (5 %, N = 5) and robust (same electrode used for weeks) at all pH values. In diluted solutions of Glucantime, Sb(III) levels were strongly dependent both on pH and ionic strength. At pH < 3, Sb(III) is oxidized with oxidation rates that increase as pH is decreased. At high pH, Sb(III) forms electro-inactive complexes. Highest Sb(III) levels were detected at pH ∼3 and at low ionic strength. The presence of several Sb(III) and Sb(V) species was demonstrated by different reduction waves obtained by stripping scanned voltammetry. As an implication of these unexpectedly high Sb(III) concentrations, an alternative model can be proposed for the mode of action of pentavalent antimonials against leishmaniasis, in which antimony complexes may act as molecular carrier of Sb(III) and release it specifically in the acidic intracellular compartment where the Leishmania parasites reside.
Keywords: Electrochemical sensors; Electroanalytical methods; Inorganic compounds/trace inorganic compounds; Speciation; Stripping analysis; Solid electrodes
Determination of organic priority pollutants in the low nanogram-per-litre range in water by solid-phase extraction disk combined with large-volume injection/gas chromatography–mass spectrometry by Christine Erger; Peter Balsaa; Friedrich Werres; Torsten C. Schmidt (5215-5223).
Polybrominated diphenyl ethers, polychlorinated biphenyls, polycyclic aromatic hydrocarbons and organochlorine pesticides in the low nanogram-per-litre range in water were enriched by solid-phase extraction (SPE) disks and their concentration determined by large-volume injection/gas chromatography–mass spectrometry (LVI/GC-MS). One advantage of using SPE disks in comparison with SPE cartridges is that suspended particulate matter (SPM) does not have to be separated prior to the enrichment step, which saves time and effort. To increase the sensitivity of the method, the SPE disk procedure was combined with LVI/GC-MS, which has not been reported so far for water analysis. The method was calibrated in ranges from 0.25 to 2.5 ng/L and from 2.5 to 25 ng/L. The average recovery was 76 % at an analyte concentration of 2.5 ng/L. The limits of quantification, defined at a signal-to-noise ratio of 6:1, reach from 0.1 to 24.0 ng/L and are up to 400 times lower than previously reported in water analysis. By the developed SPE/LVI/GC-MS method, it is possible to investigate the whole water sample without prior separation of the SPM within 2 h including GC-MS analysis.
Keywords: Solid-phase extraction disk (SPE disk); Low nanogram-per-litre range; Organic compounds; Large-volume injection (LVI); Water; GC-MS
Uptake and release kinetics of 22 polar organic chemicals in the Chemcatcher passive sampler by Etiënne L. M. Vermeirssen; Conrad Dietschweiler; Beate I. Escher; Jürgen van der Voet; Juliane Hollender (5225-5236).
The Chemcatcher passive sampler, which uses Empore™ disks as sampling phase, is frequently used to monitor polar organic chemicals in river water and effluents. Uptake kinetics need to be quantified to calculate time-weighted average concentrations from Chemcatcher field deployments. Information on release kinetics is needed if performance reference compounds (PRCs) are used to quantify the influence of environmental conditions on the uptake. In a series of uptake and elimination experiments, we used Empore™ SDB disks (poly(styrenedivinylbenzene) copolymer modified with sulfonic acid groups) as a sampling phase and 22 compounds with a logK ow (octanol–water partitioning coefficient) range from −2.6 to 3.8. Uptake experiments were conducted in river water or tap water and lasted up to 25 days. Only 1 of 22 compounds (sulfamethoxazole) approached equilibrium in the uptake trials. Other compounds showed continuing non-linear uptake, even after 25 days. All compounds could be released from SDB disks, and desorption was proportionally higher in disks loaded for shorter periods. Desorption showed two-phase characteristics, and desorption was proportionally higher for passively sorbed compounds compared to actively loaded compounds (active loading was performed by pulling spiked river water over SDB disks using vacuum). We hypothesise that the two-phase kinetics and better retention of actively loaded compounds—and compounds loaded for a longer period—may be caused by slow diffusion of chemicals within the polymer. As sorption and desorption did not show isotropic kinetics, it is not possible to develop robust PRCs for adsorbent material like SDB disks.
Keywords: Passive sampling; Chemcatcher; POCIS; Pharmaceuticals; Biocides
Identification of the nitroaromatic explosives in post-blast samples by online solid phase extraction using molecularly imprinted silica sorbent coupled with reversed-phase chromatography by Sonia Lordel-Madeleine; Véronique Eudes; Valérie Pichon (5237-5247).
In a previous work, a molecularly imprinted silica (MIS) sorbent was synthesized for the selective extraction of nitroaromatic explosives from real samples. This MIS packed in a cartridge was used for an off-line solid phase extraction procedure mainly based on hydrophobic and π–π interactions. In this work, the MIS was packed in a precolumn to be connected online with a reversed-phase LC system and a diode array detector. For this, the chromatographic conditions were first studied to obtain the separation of 1,3-dinitrobenzene, 1,3,5-trinitrobenzene, 2,4-dinitrotoluene, 2,6-dinitrotoluene, 2,4,6-trinitrotoluene, and tetryl. An optimized procedure dedicated to the selective treatment of aqueous samples was then developed with the MIS for the simultaneous extraction of the nitroaromatic compounds commonly used as explosives. Finally, the four nitrotoluenes were selectively extracted and determined simultaneously with extraction recoveries higher than 90 % using the online device composed of the MIS coupled with a diphenyl chromatographic column. The potential of this sorbent was highlighted by its use for the cleanup of simulated post-blast samples.
Keywords: Nitroaromatic explosives; Molecularly imprinted silica; Online solid phase extraction; Selective extraction procedure; Post-blast samples
Investigation of the biotransformation of melarsoprol by electrochemistry coupled to complementary LC/ESI–MS and LC/ICP–MS analysis by Anne Baumann; Thorben Pfeifer; Daniel Melles; Uwe Karst (5249-5258).
Melarsoprol is the only currently available drug for treatment of the late stage of African trypanosomiasis (sleeping sickness). Unfortunately, the arsenic-containing drug causes serious side effects, for which the mechanisms have not been elucidated so far. This investigation describes the study of the melarsoprol biotransformation processes by electrochemical (EC) techniques. Based on EC, potential oxidation reactions of melarsoprol are examined. Moreover, the reactivity of melarsoprol, its metabolite melarsen oxide, and their oxidation products toward the tripeptide glutathione and the proteins hemoglobin and human serum albumin is evaluated. The combination of different analytical techniques allows the identification as well as the quantification of the biotransformation products. The hyphenation of liquid chromatography (LC) and electrospray ionization mass spectrometry (ESI–MS) is applied for identification and structure elucidation, which implies the determination of exact masses and fragmentation patterns. For the selective detection of arsenic containing metabolites, LC coupled to inductively coupled plasma mass spectrometry is utilized. Based on the obtained data, the oxidative biotransformation of melarsoprol can be predicted, revealing novel species which have been suspected, but not been identified up to now. The results of the protein studies prove that melarsen oxide, the active derivative of melarsoprol, strongly binds to human hemoglobin and forms different adducts via the free cysteinyl groups of the hemoglobin α- and β-chain.
Keywords: Electrochemistry; Mass spectrometry; Phase-I metabolism; Sleeping sickness
MALDI-TOF MS applied to indirect carbapenemase detection: a validated procedure to clearly distinguish between carbapenemase-positive and carbapenemase-negative bacterial strains by Lijun Wang; Chao Han; Wenjun Sui; Mei Wang; Xinxin Lu (5259-5266).
Laboratory identification of carbapenemase-producing clinical isolates is crucial to limit the spread of the bacteria. In this study, we shall first develop the matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF MS) assay in automatic identification of carbapenemase producers. A total of 143 well-characterized isolates were studied. After an incubation of bacteria with meropenem trihydrate, the mixture was centrifuged and the supernatant analyzed by MALDI-TOF MS. A genetic algorithm model with ClinProTools software was built using spectra of 43 carbapenemase-positive isolates and 40 carbapenemase-negative isolates after 2 h of incubation. This model was externally validated using 60 test isolates. All spectra of supernatants of the carbapenemase-negative isolates showed peak profiles comparable to that of pure meropenem (m/z 384.159, 406.140, and 428.122 of its two sodium salt variants) regardless of the incubation time tested. For the carbapenemase-positive isolates, the specific peak for meropenem at m/z 384.159 disappeared during the incubation time, two products of meropenem degradation were identified with m/z 358.18 (the decarboxylated product) and 380.161 (sodium salt of the decarboxylated product), and other degradation products were observed (native molecule with disrupted amide bond with m/z 402.169, three sodium salt variants with m/z 424.151, 446.133, and 468.115). Sixty test isolates were 100 % correctly classified as carbapenemase positive and carbapenemase negative with the genetic algorithm model. MALDI-TOF MS coupled with ClinProTools is capable of rapidly, accurately, and automatically identifying carbapenemase producers. Figure The average spectra of the carbapenemase-positive (red) and carbapenemasenegative isolates (green) were shown. Nine peaks differentiating the two classes are highlighted by arrows. x axis, mass per charge [m/z (in daltons)]; y axis, intensity(arbitrary units [arb.u.]).
Keywords: MALDI; Carbapenem; Carbapenemases; Resistance; Classification
Mass spectrometry based phospholipidomics of mammalian thymus and leukemia patients: implication for function of iNKT cells by Xiukun Xu; Yunhui Yu; Zheng Wang; Tingting Zhu; Yanping Wang; Jian Zhu; Zijun Chen; Yun He; Linling Ju; Yunsen Li (5267-5278).
In previous studies phospholipids have been proved to be involved in biochemical, physiological, and pathological processes. As a special class of phospholipids, peroxisome-derived lipids (PDLs) have been proved to be potential ligands of invariant natural killer T (iNKT) cells in recent studies. Here, on the basis of phospholipidomics, we focused on the relative quantity of PDLs extracted from mammalian thymus or bone marrow using electrospray ionization mass spectrometry (MS). In phospholipid analysis, we identified 12 classes of phospholipids and accounted for their relative quantities by comparing their relative abundances in the MS1 map. Our results show that PDLs are present in mammalian thymus as well as mouse spleen and liver. Interestingly, the relative quantity of PDLs extracted from human acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) bone marrows is higher than that extracted from bone marrow of healthy donors. Our results may help to explain the close correlation between PDLs and iNKT cell function in thymus, spleen, liver, and especially in leukemia patients. We think that our phospholipidomics work may reveal a function of iNKT cells.
Keywords: Phospholipids; Natural killer T cells; Lipidomics; Peroxisome-derived lipids; Function
Optimization of harvesting, extraction, and analytical protocols for UPLC-ESI-MS-based metabolomic analysis of adherent mammalian cancer cells by Huichang Bi; Kristopher W. Krausz; Soumen K. Manna; Fei Li; Caroline H. Johnson; Frank J. Gonzalez (5279-5289).
In this study, a liquid chromatography mass spectrometry (LC/MS)-based metabolomics protocol was optimized for quenching, harvesting, and extraction of metabolites from the human pancreatic cancer cell line Panc-1. Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in water were compared for sample harvesting. Four different extraction methods were compared to investigate the efficiency of intracellular metabolite extraction, including pure acetonitrile, methanol, methanol/chloroform/H2O, and methanol/chloroform/acetonitrile. The separation efficiencies of hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) with UPLC-QTOF-MS were also evaluated. Global metabolomics profiles were compared; the number of total detected features and the recovery and relative extraction efficiencies of target metabolites were assessed. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Direct scraping after flash quenching with liquid nitrogen was chosen to harvest Panc-1 cells which allowed for samples to be stored before extraction. Methanol/chloroform/H2O was chosen as the optimal extraction solvent to recover the highest number of intracellular features with the best reproducibility. HILIC had better resolution for intracellular metabolites of Panc-1 cells. This optimized method therefore provides high sensitivity and reproducibility for a variety of cellular metabolites and can be applicable to further LC/MS-based global metabolomics study on Panc-1 cell lines and possibly other cancer cell lines with similar chemical and physical properties. Figure Optimized harvesting, extraction and analytical protocols for cell metabolomics analysis.
Keywords: Metabolomics; Sample preparation; Metabolite extraction; Panc-1 cell line; HILIC
GC-MS-based urine metabolic profiling of autism spectrum disorders by Patrick Emond; Sylvie Mavel; Nacima Aïdoud; Lydie Nadal-Desbarats; Frédéric Montigny; Frédérique Bonnet-Brilhault; Catherine Barthélémy; Marc Merten; Pierre Sarda; Frédéric Laumonnier; Patrick Vourc’h; Hélène Blasco; Christian R. Andres (5291-5300).
Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders resulting from multiple factors. Diagnosis is based on behavioural and developmental signs detected before 3 years of age, and there is no reliable biological marker. The purpose of this study was to evaluate the value of gas chromatography combined with mass spectroscopy (GC-MS) associated with multivariate statistical modeling to capture the global biochemical signature of autistic individuals. GC-MS urinary metabolic profiles of 26 autistic and 24 healthy children were obtained by liq/liq extraction, and were or were not subjected to an oximation step, and then were subjected to a persilylation step. These metabolic profiles were then processed by multivariate analysis, in particular orthogonal partial least-squares discriminant analysis (OPLS-DA, R 2Y(cum) = 0.97, Q 2(cum) = 0.88). Discriminating metabolites were identified. The relative concentrations of the succinate and glycolate were higher for autistic than healthy children, whereas those of hippurate, 3-hydroxyphenylacetate, vanillylhydracrylate, 3-hydroxyhippurate, 4-hydroxyphenyl-2-hydroxyacetate, 1H-indole-3-acetate, phosphate, palmitate, stearate, and 3-methyladipate were lower. Eight other metabolites, which were not identified but characterized by a retention time plus a quantifier and its qualifier ion masses, were found to differ between the two groups. Comparison of statistical models leads to the conclusion that the combination of data obtained from both derivatization techniques leads to the model best discriminating between autistic and healthy groups of children.
Keywords: Metabolomics; Gas chromatography-mass spectrometry; Trimethylsilyl oximes; Orthogonal partial least-squares discriminant analysis (OPLS-DA)
A fast method for the quantitation of key metabolites of the methionine pathway in liver tissue by high-resolution mass spectrometry and hydrophilic interaction ultra-performance liquid chromatography by S. van Liempd; D. Cabrera; J. M. Mato; J. M. Falcon-Perez (5301-5310).
We developed an assay for the extraction and simultaneous quantitation of five key metabolites of the methionine metabolic pathway in liver tissue. The metabolites included were 5′-methylthioadenosine, methionine, homocysteine, S-adenosyl-l-homocysteine, and S-adenosyl-l-methionine. The metabolites were extracted using a bead-based homogenization method, and quantitation was carried out using hydrophilic interaction chromatography and time-of-flight mass spectrometry. The extraction procedure was optimized by testing the effect of various solvent combinations. The chromatographic method was optimized for peak shape, signal intensity, and carry-over. With a total chromatographic run time of 5 min, this assay is suitable for the analysis of large sample sets. Time-of-flight mass spectrometry provided high mass accuracy which, combined with isotope pattern matching and use of chemical standards, guarantees high specificity. Moreover, by operating the mass spectrometer in enhanced duty cycle mode the signal strength for the analytes increased three- to tenfold in comparison with the generic full-scan mode. For quantitation, a matrix-spiked calibration method was used. The lowest analyte levels detected and quantified using our method were within the range of concentrations found in the liver. The inter-day coefficients of variance for the analytes were between 5 and 15 % in pooled tissue samples. Interestingly, the CVs between individual liver tissue aliquots were about twice as high. Additional experiments suggested that this higher variability was caused by uneven distribution of the analytes within the liver. In conclusion, an optimized and robust assay is now available for the extraction and quantification of key metabolites in the methionine metabolic pathway.
Keywords: Quantitation; HILIC; Time-of-flight mass spectrometry; Liver; Methionine; S-Adenosyl-l-methionine
Analysis of nucleosides and nucleotides in infant formula by liquid chromatography–tandem mass spectrometry by Brendon D. Gill; Harvey E. Indyk; Merilyn Manley-Harris (5311-5319).
A method for the simultaneous analysis of nucleosides and nucleotides in infant formula using reversed-phase liquid chromatography–tandem mass spectrometry is described. This approach is advantageous for compliance testing of infant formula over other LC-MS methods in which only nucleotides or nucleosides are measured. Following sample dissolution, protein was removed by centrifugal ultrafiltration. Chromatographic analyses were performed using a C18 stationary phase and gradient elution of an ammonium acetate/bicarbonate buffer, mass spectrometric detection and quantitation by a stable isotope-labelled internal standard technique. A single laboratory validation was performed, with spike recoveries of 80.1–112.9 % and repeatability relative standard deviations of 1.9–7.2 %. Accuracy as bias was demonstrated against reference values for NIST1849a certified reference material. The method has been validated for the analysis of bovine milk-based, soy-based, caprine milk-based and hydrolysed milk protein-based infant formulae. Figure LC-MS/MS MRM chromatogram of mixed nucleoside and nucleotide standard
Keywords: Nucleotides; Nucleosides; Infant formula; LC-MS
Preparation of a boronate-functionalized affinity hybrid monolith for specific capture of glycoproteins by F. Yang; J. Mao; X. W. He; L. X. Chen; Y. K. Zhang (5321-5331).
A novel strategy for preparation of a boronate affinity hybrid monolith was developed using a Cu(I)-catalyzed 1,3-dipolar azide–alkyne cycloaddition (CuAAC) reaction of an alkyne–boronate ligand with an azide-functionalized monolithic intermediate. An azide-functionalized hybrid monolith was first synthesized via a single-step procedure to provide reactive sites for click chemistry; then the alkyne–boronate ligands were covalently immobilized on the azide-functionalized hybrid monolith via an in-column CuAAC reaction to form a boronate affinity hybrid monolith under mild conditions. The boronate affinity monolith was characterized and evaluated by means of elemental analysis, Fourier transform infrared spectroscopy, and scanning electron microscopy. The boronate affinity hybrid monolith exhibited excellent specificity toward nucleosides and glycoproteins, which were chosen as test cis-diol-containing compounds under neutral conditions. The binding capacity of the monolith for the glycoprotein ovalbumin was 2.36 mg · g-1 at pH 7.0. The practicability of the boronate affinity hybrid monolithic material was demonstrated by specific capture of the glycoproteins ovalbumin and ovotransferrin from an egg sample. Figure A novel strategy for preparation of boronate affinity hybrid monolith was developed by utilizing Cu(I)-catalyzed 1,3-dipolar azide-alkyne cycloaddition reaction (CuAAC). The obtained boronate affinity hybrid monolith exhibited excellent performance for isolation and enrichment of nucleosides and glycoproteins and was successfully employed to specific capture of glycoproteins from the egg sample
Keywords: Click chemistry; Boronate affinity hybrid monolith; Glycoproteins; Enrichment; Egg sample
Determining urea levels in dialysis human serum by means of headspace solid phase microextraction coupled with ion mobility spectrometry and on the basis of nanostructured polypyrrole film by Hamideh Kalhor; Naader Alizadeh (5333-5339).
A simple and sensitive headspace (HS) solid phase microextraction (SPME) coupled with ion mobility spectrometry (IMS) method is presented for analysis of urea in dialysis human serum samples. A dodecylbenzenesulfonate-doped polypyrrole coating was used as a fiber for SPME. The HS-SPME–IMS method exhibits good repeatability (relative standard deviation of 3 % or less), simplicity, and good sensitivity. The influence of various analytical parameters such as pH, ionic strength, extraction time and temperature was investigated and the parameters were optimized. The calibration graph was linear in the range from 5 to 50 μg mL−1, and the detection limit was 2 μg mL−1. The method was applied successfully for determination of urea in human serum and with acceptable recovery (more than 98 %). Finally, a standard addition calibration method was applied to the HS-SPME-IMS method for the analysis of human serum samples before and at the end of dialysis. The proposed method appears to be suitable for the analysis of urea in serum samples as it is not time-consuming and requires only small quantities of the sample without any derivatization process. Figure The ion mobility spectrum obtained by HS-SPME–IMS using a PPy fiber under optimum conditions from headspace of 5 mL (A): 2 µg mL-1 of urea solution, (B): non-spiked control serum sample, (C): non-spiked patient 1 serum sample before dialysis, (D) non-spiked patient 1 serum sample at the end of dialysis, (E) spiked patient 1 serum sample at the end of dialysis with 10 µg mL−1 of urea, (F): non-spiked patient 2 serum sample before dialysis, (G): non-spiked patient 2 serum sample at the end of dialysis, (H): spiked patient 2 serum sample at the end of dialysis with 10 µg mL−1 of urea
Keywords: Biological samples; Extraction; Solid phase extraction; Solid phase microextraction; Sampling; Thin films
Identification and functional characterization of a novel α-conotoxin (EIIA) from Conus ermineus by Loïc Quinton; Denis Servent; Emmanuelle Girard; Jordi Molgó; Jean-Pierre Le Caer; Christian Malosse; El Ali Haidar; Alain Lecoq; Nicolas Gilles; Julia Chamot-Rooke (5341-5351).
Nicotinic acetylcholine receptors (nAChRs) are one of the most important families in the ligand-gated ion channel superfamily due to their involvement in primordial brain functions and in several neurodegenerative pathologies. The discovery of new ligands which can bind with high affinity and selectivity to nAChR subtypes is of prime interest in order to study these receptors and to potentially discover new drugs for treating various pathologies. Predatory cone snails of the genus Conus hunt their prey using venoms containing a large number of small, highly structured peptides called conotoxins. Conotoxins are classified in different structural families and target a large panel of receptors and ion channels. Interestingly, nAChRs represent the only subgroup for which Conus has developed seven distinct families of conotoxins. Conus venoms have thus received much attention as they could represent a potential source of selective ligands of nAChR subtypes. We describe the mass spectrometric-based approaches which led to the discovery of a novel α-conotoxin targeting muscular nAChR from the venom of Conus ermineus. The presence of several posttranslational modifications complicated the N-terminal sequencing. To discriminate between the different possible sequences, analogs with variable N-terminus were synthesized and fragmented by MS/MS. Understanding the fragmentation pathways in the low m/z range appeared crucial to determine the right sequence. The biological activity of this novel α-conotoxin (α-EIIA) that belongs to the unusual α4/4 subfamily was determined by binding experiments. The results revealed not only its selectivity for the muscular nAChR, but also a clear discrimination between the two binding sites described for this receptor.
Keywords: Conus venom; Mass spectrometry; α-Conotoxin; De novo sequencing; Nicotinic acetylcholine receptors; Binding experiments
Selective isolation of hemoglobin by use of imidazolium-modified polystyrene as extractant by Gang Zhao; Shuai Chen; Xu-Wei Chen; Rong-Huan He (5353-5358).
Ionic liquids have attracted much attention in the analysis of a variety of species. The functional groups in ionic liquids can result in highly efficient separation and enrichment and, because of their typical lack of volatility, they are environmentally benign. We grafted imidazole cations onto the surface of chloromethyl polystyrene, denoted PS-CH2-[MIM]+Cl−, and this modified polymer was used to selectively extract the protein hemoglobin (Hb). The prepared extractant PS-CH2-[MIM]+Cl−, containing 2 mmol immobilized imidazole groups per gram polymer, was characterized by FT-IR, surface charge analysis, and elemental analysis. The adsorption efficiency was 91 %. The adsorption capacity of the PS-CH2-[MIM]+Cl− for Hb was 23.6 μg mg−1, and 80 % of the retained Hb could be readily recovered by use of 0.5 % (m/v) aqueous sodium dodecyl sulfate (SDS) solution as eluate. The activity of the eluted Hb was approximately 90 %. The prepared imidazole-containing solid phase polymer was used for direct adsorption of Hb without use of any other solid matrix as support of the ionic liquid. The material was used in practice to isolate Hb from human whole blood. Figure Coordination interaction between heme of hemoglobin and imidazolium-modified chloromethyl polystyrene.
Keywords: Ionic liquid immobilization; Protein; Adsorption; Hemoglobin; Biocompatibility; Solid-phase extraction