A compositional data model to predict the isotope distribution for average peptides using a compositional spline model.

We propose an updated approach for approximating the isotope distribution of average peptides given their monoisotopic mass. Our methodology involves in-silico cleavage of the entire UNIPROT database of human-reviewed proteins using Trypsin, generating a theoretical peptide dataset. The isotope distribution is computed using BRAIN. We apply a compositional data modelling strategy that utilizes an additive log-ratio transformation for the isotope probabilities followed by a penalized spline regression. Furthermore, due to the impact of the number of sulphur atoms on the course of the isotope distribution, we develop separate models for peptides containing zero up to five sulphur atoms. Additionally, we propose three methods to estimate the number of sulphur atoms based on an observed isotope distribution. The performance of the spline models and the sulphur prediction approaches is evaluated using a mean squared error and a modified Pearson's χ2 goodness-of-fit measure on an experimental UPS2 data set. Our analysis reveals that the variability in spectral accuracy, that is, the variability between MS1 scans, contributes more to the errors than the approximation of the theoretical isotope distribution by our proposed average peptide model. Moreover, we find that the accuracy of predicting the number of sulphur atoms based on the observed isotope distribution is limited by measurement accuracy.

Lithium isotopes differentially modify mitochondrial amorphous calcium phosphate cluster size distribution and calcium capacity.

Lithium is commonly prescribed as a mood stabilizer in a variety of mental health conditions, yet its molecular mode of action is incompletely understood. Many cellular events associated with lithium appear tied to mitochondrial function. Further, recent evidence suggests that lithium bioactivities are isotope specific. Here we focus on lithium effects related to mitochondrial calcium handling. Lithium protected against calcium-induced permeability transition and decreased the calcium capacity of liver mitochondria at a clinically relevant concentration. In contrast, brain mitochondrial calcium capacity was increased by lithium. Surprisingly, 7Li acted more potently than 6Li on calcium capacity, yet 6Li was more effective at delaying permeability transition. The size distribution of amorphous calcium phosphate colloids formed in vitro was differentially affected by lithium isotopes, providing a mechanistic basis for the observed isotope specific effects on mitochondrial calcium handling. This work highlights a need to better understand how mitochondrial calcium stores are structurally regulated and provides key considerations for future formulations of lithium-based therapeutics.

Nanoscale Clustering in an Additively Manufactured Zr-Based Metallic Glass Evaluated by Atom Probe Tomography.

Composition analysis at the nm-scale, marking the onset of clustering in bulk metallic glasses, can aid the understanding and further optimization of additive manufacturing processes. By atom probe tomography, it is challenging to differentiate nm-scale segregations from random fluctuations. This ambiguity is due to the limited spatial resolution and detection efficiency. Cu and Zr were selected as model systems since the spatial distributions of the isotopes therein constitute ideal solid solutions, as the mixing enthalpy is, by definition, zero. Close agreement is observed between the simulated and measured spatial distributions of the isotopes. Having established the signature of a random distribution of atoms, the elemental distribution in amorphous Zr59.3Cu28.8Al10.4Nb1.5 samples fabricated by laser powder bed fusion is analyzed. By comparison with the length scales of spatial isotope distributions, the probed volume of the bulk metallic glass shows a random distribution of all constitutional elements, and no evidence for clustering is observed. However, heat-treated metallic glass samples clearly exhibit elemental segregation which increases in size with annealing time. Segregations in Zr59.3Cu28.8Al10.4Nb1.5 > 1 nm can be observed and separated from random fluctuations, while accurate determination of segregations < 1 nm in size are limited by spatial resolution and detection efficiency.

The isotope distribution: A rose with thorns.

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Determination of deuterium incorporation of new drug donafenib tosilate by two methods of LC-MS with natural isotope abundance correction and 1H NMR relative quantitative method / 药学学报

An LC-MS method with natural isotope abundance correction and a 1H NMR relative quantitative method were established to determine the deuterium incorporation of donafenib tosilate, a new deuterated drug molecule. First, the peak areas of isotopic impurities (non-deuterated and incompletely deuterated impurities) and deuterated drug were recorded through the single ion monitoring (SIM) mode of the established LC-MS method and then corrected in terms of the natural isotope abundance offered by ChemDraw soft, removing the nature isotope interference from 13C, 37Cl, etc. The corrected areas were subsequently used to calculate mol% of isotopologues (D0, D1, D2, D3) and Atom% D, namely, deuterium incorporation. In addition, a 1H qNMR experiment was conducted with the aromatic proton at δ 8.63 and the residual proton of isotopic impurities at δ 2.79 as quantitative peaks. The mixture of DMSO-d6 and D2O (10∶1) was employed as the solvent to change the spin-coupling between the residual proton and active hydrogen so that the residual proton could be measured as the single peak, and the sensitivity was greatly improved. The acquisition parameters were also optimized, and Atom% 1H and the deuterium incorporation were then calculated. The two methods were applied to samples of three commercial batches, and the testing results were almost consistent. Both methods proved accurate, sensitive, fast and independent of standard substances and accurate weighing, which could be applied to the determination of the deuterium incorporation of donafenib tosilate and provide a reference for other deuterated drugs.

Software Tool for Visualization and Validation of Protein Turnover Rates Using Heavy Water Metabolic Labeling and LC-MS.

Metabolic stable isotope labeling followed by liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful tool for in vivo protein turnover studies of individual proteins on a large scale and with high throughput. Turnover rates of thousands of proteins from dozens of time course experiments are determined by data processing tools, which are essential components of the workflows for automated extraction of turnover rates. The development of sophisticated algorithms for estimating protein turnover has been emphasized. However, the visualization and annotation of the time series data are no less important. The visualization tools help to validate the quality of the model fits, their goodness-of-fit characteristics, mass spectral features of peptides, and consistency of peptide identifications, among others. Here, we describe a graphical user interface (GUI) to visualize the results from the protein turnover analysis tool, d2ome, which determines protein turnover rates from metabolic D2O labeling followed by LC-MS. We emphasize the specific features of the time series data and their visualization in the GUI. The time series data visualized by the GUI can be saved in JPEG format for storage and further dissemination.

A novel calibration strategy based on isotopic distribution for high-throughput quantitative analysis of pesticides and veterinary drugs using LC-HRMS.

Preparation of calibration curves is a critical step for large-scale quantification. However, this procedure is time-consuming, labor intensive. Herein, a novel isotopologue multipoint calibration (IMC) strategy, was proposed and demonstrated for the simultaneous quantitation of 120 pesticides and 83 veterinary drugs in surface water samples using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS). In this strategy, the natural isotopic distribution was used to generate external calibration curves, eliminating the need of analyst's adjustment and many sets of chemical standard solutions required in external calibration curves. Additionally, this strategy was comprehensively validated, and the results indicated this strategy had better performance in both accuracy and precision, fully meeting the requirements for the quantitative analysis. Interestingly, for the samples with high concentration beyond the upper limit of quantitation, the IMC strategy could avoid samples dilution by monitoring the less abundant isotopic channels. Furthermore, the IMC method was successfully applied in the surface water samples collected from Anhui province, China. Among which, sulfamethoxazole and imidacoprid were the main contributors. In conclusion, we present a promising LC-HRMS strategy for the accurate quantitation of small molecules, which has a potential application in food and environmental analysis.

A Compositional Model to Predict the Aggregated Isotope Distribution for Average DNA and RNA Oligonucleotides.

Structural modifications of DNA and RNA molecules play a pivotal role in epigenetic and posttranscriptional regulation. To characterise these modifications, more and more MS and MS/MS- based tools for the analysis of nucleic acids are being developed. To identify an oligonucleotide in a mass spectrum, it is useful to compare the obtained isotope pattern of the molecule of interest to the one that is theoretically expected based on its elemental composition. However, this is not straightforward when the identity of the molecule under investigation is unknown. Here, we present a modelling approach for the prediction of the aggregated isotope distribution of an average DNA or RNA molecule when a particular (monoisotopic) mass is available. For this purpose, a theoretical database of all possible DNA/RNA oligonucleotides up to a mass of 25 kDa is created, and the aggregated isotope distribution for the entire database of oligonucleotides is generated using the BRAIN algorithm. Since this isotope information is compositional in nature, the modelling method is based on the additive log-ratio analysis of Aitchison. As a result, a univariate weighted polynomial regression model of order 10 is fitted to predict the first 20 isotope peaks for DNA and RNA molecules. The performance of the prediction model is assessed by using a mean squared error approach and a modified Pearson's χ2 goodness-of-fit measure on experimental data. Our analysis has indicated that the variability in spectral accuracy contributed more to the errors than the approximation of the theoretical isotope distribution by our proposed average DNA/RNA model. The prediction model is implemented as an online tool. An R function can be downloaded to incorporate the method in custom analysis workflows to process mass spectral data.

Distribution of hydrogen and oxygen stable isotopes and pollution indicators in water during a monsoon transitional period in Min River Basin.

Based on 197 monthly river water and groundwater samples and 30 event-scale precipitation samples, our study reports the distribution of hydrogen and oxygen isotopes and pollution indicators in Min River Basin. The variation of δ18O and d-excess indicate that the water source in the upper main course water is more variable and that in the middle-lower part is relatively stable. Comparison between plots of δ2H versus δ18O in the river water and precipitation reflect the dominant water source is different between river water in the upper and middle-lower parts. The electrical conductivity (EC) shows a similar spatial variation trend for main course water collected in four campaigns. The pollutant concentration change at the confluences of main tributaries shows that the inflow of Heishui River and Dadu River leads to decreased NO3- and Cl-, while that of Xi River, Pu River and Fuhe River leads to a leap in NO3- and Cl-. A significant positive correlation is observed between EC and δ18O, indicating the consistent control of water sources on isotope distribution and water quality. The relationship between elevation and δ18O in the main course river water suggests that the factors affecting isotope distribution vary spatially. "Altitude effect" can only be observed in October and November for the upper steepest plateau zone due to the spatial variation in the precipitation stored during the wet season. The "inverse altitude effect" is observed for the upper part during the wet season and for the middle-lower part during the whole study period, which can be explained by the contribution of tributaries with different discharge regimes. Our findings show that water source with different discharge regimes can serve as the leading factor controlling the stream component in multi-tributary river basins with large spatial span and may mask the influence of spatial distribution of precipitation.

Insights Into the Known 13C Depletion of Methane-Contribution of the Kinetic Isotope Effects on the Serine Hydroxymethyltransferase Reaction.

We determined the kinetic isotope effect on the serine hydroxymethyltransferase reaction (SHMT), which provides important C1 metabolites that are essential for the biosynthesis of DNA bases, O-methyl groups of lignin and methane. An isotope effect on the SHMT reaction was suggested being responsible for the well-known isotopic depletion of methane. Using the cytosolic SHMT from pig liver, we measured the natural carbon isotope ratios of both atoms involved in the bond splitting by chemical degradation of the remaining serine before and after partial turnover. The kinetic isotope effect 13(VMax/Km) was 0.994 0.006 and 0.995 0.007 on position C-3 and C-2, respectively. The results indicated that the SHMT reaction does not contribute to the 13C depletion observed for methyl groups in natural products and methane. However, from the isotopic pattern of caffeine, isotope effects on the methionine synthetase reaction and on reactions forming Grignard compounds, the involved formation and fission of metal organic bonds are likely responsible for the observed general depletion of "activated" methyl groups. As metal organic bond formations in methyl transferases are also rate limiting in the formation of methane, they may likely be the origin of the known 13C depletion in methane.

Evaluation of on-line pyrolysis coupled to isotope ratio mass spectrometry for the determination of position-specific (13)C isotope composition of short chain n-alkanes (C6-C12).

We measured (13)C intramolecular isotopic composition of commercially available short-chain hydrocarbons (n-C6-n-C12) using (13)C-NMR. Results show that the main variation is between the terminal and the sub-terminal C-atom positions. Site-preference (difference in δ(13)C values between terminal and sub-terminal C-atom positions) among all the samples varies between -12.2‰ and +8.4‰. Comparison of these results with those obtained using on-line pyrolysis coupled with GC-C-IRMS show that the thermal cracking of hydrocarbons occurs with a good isotopic fidelity between terminal and sub-terminal C-atom positions of the starting material and the related pyrolysis products (methane and ethylene). On-line pyrolysis coupled with GC-C-IRMS can thus be used for tracing hydrocarbons biogeochemical processes.

Determination of the enrichment of isotopically labelled molecules by mass spectrometry.

A general method for the determination of the enrichment of isotopically labelled molecules by mass spectrometry (MS) is described. In contrast to other published procedures, the method described here takes into account and corrects for measurement errors such as the contribution at M - 1 due to loss of hydrogen or lack of spectral resolution and provides an uncertainty value for the determined enrichment. The general procedure requires the following steps: (1) evaluation of linearity in the mass spectrometer by injecting the natural abundance compound at different concentration levels, (2) determination of the purity of the mass cluster using the natural abundance analogue, (3) calculation of the theoretical isotope composition of the labelled compound using different tentative isotope enrichments, (4) calculation of 'convoluted' isotope distributions for the labelled compound taking into account the purity of the mass cluster determined with the natural abundance analogue and (5) comparison of the isotope distributions measured for the labelled compound with those calculated for different isotope enrichments using linear regression. The method was applied to a series of commercially available (13)C- and (2)H-labelled compounds and to a suite of singly (13)C-labelled ß2-agonist prepared in-house both by gas chromatography (GC)-MS, GC-tandem MS (MS/MS) and liquid chromatography-MS/MS with satisfactory results. It was observed that the main uncertainty source for the isotope enrichment was the uncertainty in the purity of the measured cluster as determined with the natural abundance compound.

Site-specific 13C content by quantitative isotopic 13C nuclear magnetic resonance spectrometry: a pilot inter-laboratory study.

Isotopic (13)C NMR spectrometry, which is able to measure intra-molecular (13)C composition, is of emerging demand because of the new information provided by the (13)C site-specific content of a given molecule. A systematic evaluation of instrumental behaviour is of importance to envisage isotopic (13)C NMR as a routine tool. This paper describes the first collaborative study of intra-molecular (13)C composition by NMR. The main goals of the ring test were to establish intra- and inter-variability of the spectrometer response. Eight instruments with different configuration were retained for the exercise on the basis of a qualification test. Reproducibility at the natural abundance of isotopic (13)C NMR was then assessed on vanillin from three different origins associated with specific δ (13)Ci profiles. The standard deviation was, on average, between 0.9 and 1.2‰ for intra-variability. The highest standard deviation for inter-variability was 2.1‰. This is significantly higher than the internal precision but could be considered good in respect of a first ring test on a new analytical method. The standard deviation of δ (13)Ci in vanillin was not homogeneous over the eight carbons, with no trend either for the carbon position or for the configuration of the spectrometer. However, since the repeatability for each instrument was satisfactory, correction factors for each carbon in vanillin could be calculated to harmonize the results.

Understanding the characteristics of mass spectrometry data through the use of simulation.

BACKGROUND: Mass spectrometry is actively being used to discover disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids. The potential importance of these clinical applications has made the development of better methods for processing and analyzing the data an active area of research. It is, however, difficult to determine which methods are better without knowing the true biochemical composition of the samples used in the experiments. METHODS: We developed a mathematical model based on the physics of a simple MALDI-TOF mass spectrometer with time-lag focusing. Using this model, we implemented a statistical simulation of mass spectra. We used the simulation to explore some of the basicoperating characteristics of MALDI or SELDI instruments. RESULTS: The simulation reproduced several characteristics of actual instruments. We found that the relative mass error is affected by the time discretization of the detector (about 0.01%) and the spread of initial velocities (about 0.1%). The accuracy of calibration based on external standards decays rapidly outside the range spanned by the calibrants. Natural isotope distributions play a major role inbroadening peaks associated with individual proteins. The area of a peak is a more accurate measure of its size than the height. CONCLUSIONS: The model described here is capable of simulating realistic mass spectra. The simulation should become a useful tool forgenerating spectra where the true inputs are known, allowing researchers to evaluate the performance of new methods for processing and analyzing mass spectra. AVAILABILITY: http://bioinformatics.mdanderson.org/cromwell.html.