Search

"Omics" revolution during the last few decades has vastly increased the understanding of the biological processes that remained obscure in part due to the lack of quality data. Genomics, transcriptomics, epigenomics, proteomics, lipidomics, metabolomics, and microbiomics form an invaluable array of fields that contribute holistically to a global understanding of the intertwined roles of the basic constituents of life and how they comprehensively paint a picture of disease. Metabolomics, in particular, is the study of metabolites, which are the products of cellular metabolic processes (small molecules, i.e., fatty acids, amino acids, or carbohydrates, are part of metabolomics). In this chapter, it is explained how to achieve a metabolomics profiling of aqueous humor using a special isotopic carbon labeling, a novel technique that combines a tremendous effectiveness with simplicity. The very nature of this technique guarantees the exclusion of false positives, since the algorithms are based on the recognition of unique isotopic patterns.

There is always a tension within the omics sciences between trying to measure biological molecules rapidly and measuring accurately. Metabolomics as an omics science tries to measure the small biochemicals rapidly, in a single pass, but the current state of the art cannot provide the reproducibility or accuracy needed for clinical use or even daily reproducibility for larger experiments. The IROA TruQuant measurement system uses a daily "Long-Term Reference Standard (LTRS)" and a chemically identical Internal Standard (IS) to provide validated chemical identity, daily QA/QC on instrument and sample preparation, and accurate reproducible quantitation that is comparable across days, instruments, and even, for most compounds, chromatographic methods. The LTRS is, as the name implies, a Long-Term Reference Standard that is always the same and should therefore provide very similar results on a large but finite collection of compounds. All of the compounds in the LTRS are isotopically signed with formula indicating IROA patterns so they cannot be mistaken for one another. Because of the precise IROA patterns, a software-driven analysis of the compounds seen daily can determine the performance of the instrument in terms of sensitivity, in-source fragmentation, and chromatographic and injection stability and provide completely reproducible quantitation.

Lead (Pb) isotope has been extensively used to identify sources of Pb and apportion their contributions in the environment. Conventionally, isotope ratios are used to express Pb isotopic composition. However, the linear combination of Pb isotope ratios is not consistent with mass balance. Moreover, the graphical presentations based on Pb isotope ratios are always inconsistent when different Pb isotope ratios are used. In this study, we proposed to use fractional abundance to express Pb isotopic composition to achieve more accurate and reliable source apportionment. A new method (rotation-projection method) based on fractional abundance was developed in this research. The new method compared favorably to the isotopic ratio-based method and to another fractional abundance based method using default 204 Pb value (0) (Walraven’s method). It allows to present four-dimensional (4-D) Pb isotope fractional abundance data in a 3-D plot. In the meantime, due to the low variation of the fractional abundance of 204 Pb in the terrestrial ecosystem, the terrestrial Pb isotope fractional abundance data fell nearly on a plane, which further allows to plot the Pb isotope fractional abundance data on a two-dimensional diagram. Proper presentation of the isotopic composition data helps to achieve more accurate and reliable source identification and apportionment.

Identifying non-annotated peaks may have a significant impact on the understanding of biological systems. In silico methodologies have focused on ESI LC/MS/MS for identifying non-annotated MS peaks. In this study, we employed in silico methodology to develop an Isotopic Ratio Outlier Analysis (IROA) workflow using enhanced mass spectrometric data acquired with the ultra-high resolution GC-Orbitrap/MS to determine the identity of non-annotated metabolites. The higher resolution of the GC-Orbitrap/MS, together with its wide dynamic range, resulted in more IROA peak pairs detected, and increased reliability of chemical formulae generation (CFG). IROA uses two different 13C-enriched carbon sources (randomized 95% 12C and 95% 13C) to produce mirror image isotopologue pairs, whose mass difference reveals the carbon chain length (n), which aids in the identification of endogenous metabolites. Accurate m/z, n, and derivatization information are obtained from our GC/MS workflow for unknown metabolite identification, and aids in silico methodologies for identifying isomeric and non-annotated metabolites. We were able to mine more mass spectral information using the same Saccharomyces cerevisiae growth protocol (Qiu et al. Anal. Chem 2016) with the ultra-high resolution GC-Orbitrap/MS, using 10% ammonia in methane as the CI reagent gas. We identified 244 IROA peaks pairs, which significantly increased IROA detection capability compared with our previous report (126 IROA peak pairs using a GC-TOF/MS machine). For 55 selected metabolites identified from matched IROA CI and EI spectra, using the GC-Orbitrap/MS vs. GC-TOF/MS, the average mass deviation for GC-Orbitrap/MS was 1.48 ppm, however, the average mass deviation was 32.2 ppm for the GC-TOF/MS machine. In summary, the higher resolution and wider dynamic range of the GC-Orbitrap/MS enabled more accurate CFG, and the coupling of accurate mass GC/MS IROA methodology with in silico fragmentation has great potential in unknown metabolite identification, with applications for characterizing model organism networks.

A new approach to isotopic purification has been developed and applied to the production of a small quantity of 244Pu with an isotopic purity >99.996 %, as compared against the standard 244Pu available that displays an isotopic purity of 97.87 %. The presence of Pu isotopes 239Pu, 240Pu, 241Pu and 242Pu have been greatly reduced, allowing for higher spiking levels of the isotopically purified 244Pu tracer to be used in environmental level sample analysis. Details of the isotopic purification process will be described along with the effect this improved Pu tracer could have on analytical Pu mass spectrometry measurements.

This review provides an overview of two complementary approaches to identify biologically active compounds for studies in chemical ecology. The first is activity-guided fractionation and the second is metabolomics, particularly focusing on a new liquid chromatography–mass spectrometry-based method called isotopic ratio outlier analysis. To illustrate examples using these approaches, we review recent experiments using Caenorhabditis elegans and related free-living nematodes.

Actinomycetes are powerhouses of natural product biosynthesis. Full realization of this biosynthetic potential requires approaches for recognizing novel metabolites and determining mediators of metabolite production. Herein, we develop an isotopic ratio outlier analysis (IROA) ultra-high performance liquid chromatography-mass spectrometry (UHPLC/MS) global metabolomics strategy for actinomycetes that facilitates recognition of novel metabolites and evaluation of production mediators. We demonstrate this approach by determining impacts of the iron chelator 2,2&prime, bipyridyl on the Nocardiopsis dassonvillei metabolome. Experimental and control cultures produced metabolites with isotopic carbon signatures that were distinct from corresponding &ldquo, standard&rdquo, culture metabolites, which were used as internal standards for LC/MS. This provided an isotopic MS peak pair for each metabolite, which revealed the number of carbon atoms and relative concentrations of metabolites and distinguished biosynthetic products from artifacts. Principal component analysis (PCA) and random forest (RF) differentiated bipyridyl-treated samples from controls. RF mean decrease accuracy (MDA) values supported perturbation of metabolites from multiple amino acid pathways and novel natural products. Evaluation of bipyridyl impacts on the nocazine/XR334 diketopiperazine (DKP) pathway revealed upregulation of amino acid precursors and downregulation of late stage intermediates and products. These results establish IROA as a tool in the actinomycete natural product chemistry arsenal and support broad metabolic consequences of bipyridyl.

We report a case of seized methamphetamine (MA) samples showing unique profiles of stable isotopic compositions. Three packages of MA-HCl samples seized simultaneously from one suspect were subjected to gas chromatographic impurity profiling and stable isotope ratio mass spectrometry (IRMS). The samples showed similar impurity profiles by gas chromatography, but their stable isotopic compositions were complicated. The δ15N values of the samples from each package varied widely when the crystals were analyzed separately; we could differentiate two major groups labeled I and II, and also their subgroups. Each of the three packages contained MA-HCl crystals belonging to multiple groups and subgroups. It was considered that several batches of MA-HCl with starting materials from different sources were mixed together after a similar or the same synthesis procedure and then divided into the packages. This is the first report to show that stable IRMS is useful for differentiating seized MA using small crystals from different sources.

Isotope variability due to natural processes provides important information for studying a variety of complex natural phenomena from the origins of a particular sample to the traces of biochemical reaction mechanisms. These measurements require high-precision determination of isotope ratios of a particular element involved. Isotope Ratio Mass Spectrometers (IRMS) are widely employed tools for such a high-precision analysis, which have some limitations. This work aims at overcoming the limitations inherent to IRMS by estimating the elemental isotopic abundance from the experimental isotopic distribution. In particular, a computational method has been derived which allows the calculation of 13C/12C ratios from the whole isotopic distributions, given certain caveats, and these calculations are applied to several cases to demonstrate their utility. The limitations of the method in terms of the required number of ions and S/N ratio are discussed. For high-precision estimates of the isotope ratios, this method requires very precise measurement of the experimental isotopic distribution abundances, free from any artifacts introduced by noise, sample heterogeneity, or other experimental sources.

Mass spectrometry (MS) is widely used for isotopic studies of metabolism in which detailed information about biochemical processes is obtained from the analysis of isotope incorporation into metabolites. The biological value of such experiments is dependent on the accuracy of the isotopic measurements. Using MS, isotopologue distributions are measured from the quantitative analysis of isotopic clusters. These measurements are prone to various biases, which can occur during the experimental workflow and/or MS analysis. The lack of relevant standards limits investigations of the quality of the measured isotopologue distributions. To meet that need, we developed a complete theoretical and experimental framework for the biological production of metabolites with fully controlled and predictable labeling patterns. This strategy is valid for different isotopes and different types of metabolisms and organisms, and was applied to two model microorganisms, Pichia augusta and Escherichia coli, cultivated on (13)C-labeled methanol and acetate as sole carbon source, respectively. The isotopic composition of the substrates was designed to obtain samples in which the isotopologue distribution of all the metabolites should give the binomial coefficients found in Pascal's triangle. The strategy was validated on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform by quantifying the complete isotopologue distributions of different intracellular metabolites, which were in close agreement with predictions. This strategy can be used to evaluate entire experimental workflows (from sampling to data processing) or different analytical platforms in the context of isotope labeling experiments.

This article examines the feasibility of source identification of seized street drug samples by exploiting differences in isotopic composition at natural abundance level by gc/ms as compared to isotope ratio mass spectrometry. This is a letter to the Editor.

We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass spectrometry-based technique called Isotopic Ratio Outlier Analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95% and 5% 13C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: 1) compounds arising from biosynthesis are easily distinguished from artifacts, 2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, 3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulae, and 4) relative concentrations of all metabolites are easily determined. A heat shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway, which we use to demonstrate the approach. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans. Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline.

Mass spectrometry (MS) analysis of peptides and proteins has evolved dramatically over the last 20 years. Improvement of MS instrumentation, computational data analysis, and the availability of complete sequence databases for many species have made large-scale proteomics analyses possible. The measurement of global protein abundance by quantitative mass spectrometry has the potential to increase both speed and impact of biological and clinical research. However, to be able to detect and identify potential biomarkers, reproducible and accurate quantification is essential. The following chapter describes how to perform quantitative protein profiling using stable isotope labeling methods. Throughout, there is a focus on guidance in selection of an appropriate labeling strategy. With that in mind, we have included a section on acquisition and understanding of the liquid chromatography-mass spectrometry (LC-MS) data format. Further, we describe the different stable isotope labeling methods and their pros and cons. We start by giving an overview of the overall quantitative proteomics workflow in which extracting relevant biological information from the acquired data is the ultimate goal.

>Metabolomics or biochemical profiling is a fast emerging science; however, there are still many associated bottlenecks to overcome before measurements will be considered robust. Advances in MS resolution and sensitivity, ultra pressure LC–MS, ESI, and isotopic approaches such as flux analysis and stable-isotope dilution, have made it easier to quantitate biochemicals. The digitization of mass spectrometers has simplified informatic aspects. However, issues of analytical variability, ion suppression and metabolite identification still plague metabolomics investigators. These hurdles need to be overcome for accurate metabolite quantitation not only for in vitro systems, but for complex matrices such as biofluids and tissues, before it is possible to routinely identify biomarkers that are associated with the early prediction and diagnosis of diseases. In this report, we describe a novel isotopic-labeling method that uses the creation of distinct biochemical signatures to eliminate current bottlenecks and enable accurate metabolic profiling

Mass spectrometry (MS) is widely used for isotopic labeling studies of metabolism and other biological processes. Quantitative applications—e.g. metabolic flux analysis—require tools to correct the raw MS data for the contribution of all naturally abundant isotopes. IsoCor is a software that allows such correction to be applied to any chemical species. Hence it can be used to exploit any isotopic tracer, from well-known (13C, 15N, 18O, etc) to unusual (57Fe, 77Se, etc) isotopes. It also provides new features—e.g. correction for the isotopic purity of the tracer—to improve the accuracy of quantitative isotopic studies, and implements an efficient algorithm to process large datasets. Its user-friendly interface makes isotope labeling experiments more accessible to a wider biological community. Availability: IsoCor is distributed under OpenSource license at http://metasys.insa-toulouse.fr/software/isocor/ Contact: jean-charles.portais@insa-toulouse.fr

Isotopic composition of elements and their effect on mass spectra Translation of isotopic abundances into mass spectral patterns Analytical information from isotopic patterns Nominal and accurate mass of molecules and ions Mass resolution and its effects on isotopic patterns and mass accuracy Accurate mass as a tool for determining molecular formulas Ultrahigh resolution – aspects and applications Relevance of these topics for all types of mass spectral analyses

Besides the well-established (13)C-metabolic flux analysis ((13)C-MFA) which characterizes a cell's fluxome in a metabolic and isotopic stationary state a current area of research is isotopically non-stationary MFA. Non-stationary (13)C-MFA uses short-time isotopic transient data instead of long-time isotopic equilibrium data and thus is capable to resolve fluxes within much shorter labeling experiments. However, a comparison of both methods with data from one single experiment has not been made so far. In order to create a consistent database for directly comparing both methods a (13)C-labeling experiment in a fed-batch cultivation with a Corynebacterium glutamicum lysine producer was carried out. During the experiment the substrate glucose was switched from unlabeled to a specifically labeled glucose mixture which was immediately traced by fast sampling and metabolite quenching. The time course of labeling enrichments in intracellular metabolites until isotopic stationarity was monitored by LC-MS/MS. The resulting dataset was evaluated using the classical as well as the isotopic non-stationary MFA approach. The results show that not only the obtained relative data, i.e. intracellular flux distributions, but also the more informative quantitative fluxome data significantly depend on the combination of the measurements and the underlying modeling approach used for data integration. Taking further criteria on the experimental and computational part into consideration, the current limitations of both methods are demonstrated and possible pitfalls are concluded.

Isotopically enriched CF235Cl37Cl (∼94% isotopic purity) has been synthesised by a three-step reaction. CHF2CO2H, 35Cl2 (99% isotopic purity) and 37Cl2 (95% isotopic purity) have been used as reactants. Intermediate products CF235ClCO2H and CF235ClCO2Ag have been obtained. The yield of spectroscopically pure CF235Cl37Cl, with respect to CHF2CO2H, is ca. 18%. Isotopic enrichment of CF235Cl37Cl has been checked employing the splitting of chlorine isotopes observed in the gas-phase infrared spectrum for the ν6 band region. The preparation has been improved to 1 mmol scale, obtaining a sample suitable for infrared measurements. The selective process is a general method to synthesise alternatively the three isotopic species CF235Cl37Cl, CF235Cl2 and CF237Cl2.

[1] NASA’s latest plans for Mars sample returns [Lawler, 2000] mean that pristine rocks from carefully selected sites on the Red Planet could be back in the Houston Space Center as early as 2014. With a mission price tag of over $2 billion, the scientists bidding for the right to analyze these samples will need to be able to offer the most powerful, sensitive, and precise techniques known, just as was done in 1969 with the lunar returned samples [e.g., Lunar Sample Analysis Planning Team, 1970]. Whether or not it turns out that Mars has, or had, living organisms on or beneath its surface, we will want to know everything we can about its G Geochemistry Geophysics Geosystems

The recently proposed average mass approach to isotopic analysis is extended to the analyses of materials for which the molecular ion groups are distorted by the presence of one or more overlapping species. The method is simple and direct and could prove to be more general and accurate than conventional approaches to these problems.

In 1890, the geologist G. R. Lepsius identified as Lakonian the marble used to sculpt a small, fragmentary, battered lion (Fig.l) found at Olympia (1). In the century that has since elapsed, the little marble lion from Olympia has been recognized as part of a perirrhanterion, or marble cult basin. As many as seventeen perirrhanteria are now known from the seventh century B.C.; they form an important and still-growing group among the earliest examples of Greek marble sculpture.