Liquid-scintillation-spectrometer data processing by desk-top computer

A desk-top computing system has been programmed to store accurately the quench curves necessary for the calculation of total disintegrations/minute (d.p.m.) of samples containing either one or two radioactive isotopes. In producing d.p.m. values background counts are subtracted, and in binary-labelled samples the counts attributable to each radioactive isotope are separated. The programme also relates d.p.m. to the weight, volume and density of the sample. Each variable is easily recalled and adjustments can be made for different batches of samples without reprogramming. Equally easily changes of radioactive isotope, quenching agent, scintillator or window setting can be accommodated. Quadratic equations are used to express the quench curves. Counting efficiencies obtained when the coefficients in the quadratic equations are derived from three carefully chosen points on a quench curve are compared with those obtained when the coefficients are derived by the method of least squares. The results of both mathematical approximations are compared with the efficiencies read by the eye from graphs.     

Regression analysis for comparing protein samples with 16O/18O stable-isotope labeled mass spectrometry

MOTIVATION: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for (16)O/(18)O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of (16)O/(18)O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies.     

A method for automatically interpreting mass spectra of 18O-labeled isotopic clusters

16O/18O labeling is one differential proteomics technology among many that promises diagnostic and prognostic biomarkers of disease. Although the incorporation of 18O in the C-terminal carboxyl group during endoproteinase digestion in the presence of H2 18O makes the process of labeling facile, the ease and effectiveness of label incorporation have in some regards been outweighed by the difficulties in interpreting the resulting spectra. Complex isotope patterns result from the composition of unlabeled (18O(0)), singly labeled (18O(1)), and doubly labeled species (18O(2)) as well as contributions from the naturally occurring isotopes (e.g. 13C and 15N). Moreover because labeling is enzymatic, the number of 18O atoms incorporated can vary from peptide to peptide. Finally it is difficult to distinguish highly up-regulated from highly down-regulated or C-terminal peptides. We have developed an algorithm entitled regression analysis applied to mass spectrometry (RAAMS) that automatically, rapidly, and confidently interprets spectra of 18O-labeled peptides without requiring chemical composition information derived from product ion spectra. The algorithm is able to measure the effective 18O incorporation rate due to variable enzyme substrate specificity of the pseudosubstrate during the isotope exchange reaction and corrects for the 18O(0) abundance that remains in the labeled sample when using a two-step digestion/labeling procedure. We have also incorporated a method for distinguishing pure 18O(0) from pure 18O(2) peptides utilizing impure H2 18O. The algorithm operates on centroided peak lists and is therefore very fast: nine chromatograms of, on average, 1,168 spectra and containing, on average, 6,761 isotopic clusters were interpreted in, on average, 45 s per chromatogram. RAAMS is fast enough (average, 38 ms/spectrum) to allow the possibility of performing information-dependent MS/MS on a chromatographic time scale on species exceeding predetermined ratio thresholds. We describe in detail the operation of the algorithm and demonstrate its use on datasets with known and unknown ratios.     

青海喇家遗址人类遗骸的锶同位素比值分析

喇家遗址位于青海省民和县,主体为齐家文化的遗存,距今大约3900~4300年。喇家遗址古代人类迁移活动的研究,对于探索黄河上游古代文明,推动该地区齐家文化研究,有着积极的学术意义。本文首先采用电感耦合等离子体质谱技术对喇家遗址出土的22个个体的44份牙釉质和骨骼样品进行了元素分析,根据检测结果排除了受到污染的2份骨骼样品。其次,通过热电离质谱分析方法对喇家遗址出土22个个体的42份牙釉质和骨骼样品及8个猪牙釉质样品的锶同位素比值进行了测定。检测数据表明,猪牙釉质的锶同位素比值的标准偏差远小于其他动物,可以推断猪由当地饲养的可能性是最大的,因此其牙釉质锶同位素比值可以代表当地的锶同位素水平。经过计算得到8个猪牙釉质的锶同位素比值的平均值为0.710930,将该平均值加或减2倍标准偏差可以得到喇家遗址当地的锶同位素比值范围在0.711058~0.710802之间。以此为前提可以推测,本次检测的22个个体中,有17个个体牙釉质的锶同位素比值在遗址当地的锶同位素比值范围内,可能为本地出生。还有2个个体牙釉质在当地的锶同位素比值范围上下限附近,姑且存疑;仅有3个个体牙釉质的锶同位素比值在遗址当地的锶同位素比值范围以外,表明这些个体可能在其他地区出生,去世后埋葬在遗址中。此外,数据分析还显示,本地出生人群牙釉质的锶同位素比值平均值与骨骼的锶同位素比值平均值比较接近,暗示喇家遗址当地古人类生活方式可能比较统一。     

Estimation of doubly labeled water energy expenditure with confidence intervals

Bivariate regression is used to estimate energy expenditure from doubly labeled water data. Two straight lines are fitted to the logarithms of the enrichments of oxygen-18 and deuterium simultaneously as a bivariate regression, so that the correlations between the oxygen and deuterium regression coefficients can be estimated. Maximum likelihood methods are used to extend bivariate regression to unbalanced situations caused by missing observations and to include replicate laboratory determination from the same urine samples, even if one of the replicates is missing. Use of maximum likelihood allows the determination of a confidence interval for the energy expenditure based on the log likelihood surface rather than use of the propagation of variance methods for nonlinear transformations. The model is extended to include the subject's deviations from the two lines as a bivariate continuous-time first-order autoregression to allow for serial correlation in the observations. The analysis of data from two subjects, one without apparent serial correlation and one with serial correlation, is presented.     

DeltaMS: a tool to track isotopologues in GC- and LC-MS data

Introduction

Stable isotopic labeling experiments are powerful tools to study metabolic pathways, to follow tracers and fluxes in biotic and abiotic transformations and to elucidate molecules involved in metal complexing.

Objective

To introduce a software tool for the identification of isotopologues from mass spectrometry data.

Methods

DeltaMS relies on XCMS peak detection and X¹³CMS isotopologue grouping and then analyses data for specific isotope ratios and the relative error of these ratios. It provides pipelines for recognition of isotope patterns in three experiment types commonly used in isotopic labeling studies: (1) search for isotope signatures with a specific mass shift and intensity ratio in one sample set, (2) analyze two sample sets for a specific mass shift and, optionally, the isotope ratio, whereby one sample set is isotope-labeled, and one is not, (3) analyze isotope-guided perturbation experiments with a setup described in X¹³CMS.

Results

To illustrate the versatility of DeltaMS, we analyze data sets from case-studies that commonly pose challenges in evaluation of natural isotopes or isotopic signatures in labeling experiment. In these examples, the untargeted detection of sulfur, bromine and artificial metal isotopic patterns is enabled by the automated search for specific isotopes or isotope signatures.

Conclusion

DeltaMS provides a platform for the identification of (pre-defined) isotopologues in MS data from single samples or comparative metabolomics data sets.

Graphical Abstract

Open image in new window

     

Biological Fractionation of Lead Isotopes in Sprague-Dawley Rats Lead Poisoned via the Respiratory Tract

Objectives

It was considered that lead isotope ratios did not change during physical, chemical, or biological processes. Thus, lead isotope ratios have been used as fingerprints to identify possible lead sources. However, recent evidence has shown that the lead isotope ratios among different biological samples in human are not always identical from its lead origins in vitro. An animal experiment was conducted to explore the biological fractionation of lead isotopes in biological systems.

Methods

24 male Sprague-Dawley (SD) rats were divided into groups that received acute lead exposure (0, 0.02, 0.2, or 2 mg/kg body weight of lead acetate) via the respiratory route every day for 5 days. Biological samples (i.e., blood, urine, and feces) were collected for comparison with the lead acetate (test substance) and the low-lead animal feed (diet) administered to the rats. The lead isotope ratios were determined by inductively coupled plasma mass spectrometry (ICP-MS).

Results

There are significant differences (p<0.05) in lead isotope ratios between blood, urine, and feces. Moreover, a nonlinear relationship between the blood lead concentration and the blood lead isotope ratios was observed. There is also a threshold effect to the fractionation function. Only the blood isotope ratio of ²⁰⁴Pb/²⁰⁶Pb matches the test substance well. As for feces, when ²⁰⁴Pb/²⁰⁶Pb ratio is considered, there is no significant difference between feces-test substance pairs in medium and high dose group.

Conclusions

The biological fractionation of lead isotopes in SD rats was observed. Moreover, there might be a threshold for the biological fractionation of lead isotopes which is depending on whole blood lead level. It is considered to be more reliable that we compared the isotope ratios of potential lead hazards with both blood and feces lead fingerprints especially for ²⁰⁴Pb/²⁰⁶Pb ratio under high-dose exposure.     

Determination of selenium stable isotopes by gas chromatography–mass spectrometry with negative chemical ionisation

A gas chromatography mass spectrometric method using negative chemical ionisation was developed for the determination of stable isotopes of selenium for evaluation of selenium absorption and retention from foods in humans. The method involves an acid digestion to convert all selenium into selenite, which subsequently reacts with 4-nitro-o-phenylene-diamine to form a volatile piazselenole. The piazselenole, after extraction into an organic solvent, was analysed for its isotopic selenium composition by gas chromatography mass spectrometry. Negative chemical ionisation is reported for the first time for the determination of selenium stable isotopes and its analytical characteristics were compared to those of electron impact mass spectrometric ionisation, classically used for the determination of selenium. The negative chemical ionisation technique allowed accurate determination of total selenium by isotope dilution and of selenium isotope ratios in biological samples. The repeatability for total selenium and for stable isotope ratios was good (R.S.D.≤10%) within the range of 50 to 250 ng selenium. The detection limit for the investigated selenium isotopes was approximately 1 pg (signal to noise ratio at 3). The applicability of the developed stable isotope methodology was demonstrated by the determination of the selenium absorption and retention from foods in a pilot study using one human adult.     

Source/Sink relations of abscising and nonabscising soybean flowers

The partitioning of recently fixed ¹⁴C to setting and abscising flowers within the axillary raceme of `Clark' isoline E1t soybeans (Glycine max L. Merr) was examined as a function of time after anthesis of individual flowers. In such racemes, the first four flowers showed a 17% abscission while the next four flowers showed 47% abscission.

Source/sink relations of flowers I-IV (normally setting) were compared to those of flowers V-VIII (normally abscising) by pulse labeling source leaves with ¹⁴CO₂ and determining the radioactivity of individual flowers after a 4-hour chase period. The relative specific activity (RSA;% disintegrations per minute per% dry weight), sink strength (% disintegrations per minute), and its components, sink size (milligrams dry weight) and sink intensity (% disintegrations per milligram dry weight) were then calculated as a function of days after anthesis.

Sink intensity (i.e. the competitive ability to accumulate photoassimilate per unit mass) was very high prior to anthesis of both setting and abscising flowers. Sink intensity then became very low for the first 3 days following anthesis after which it recovered in normally setting flowers, but failed to recover in normally abscising flowers. It is concluded that soybean reproductive abscission is determined at or very near the day of anthesis.

     

A rapid method for repeated collection of blood from the tail vein of rats

A method was developed for obtaining serial blood samples from the tail vein of rats. Seventy microliters of blood were collected at the rate of approximately one sample per minute for the quantitative determination of whole blood clearance of radiolabeled compounds. The technique was rapid, reproducible, and kept stress to the test animals at a minimum.     

Equations for Lipid Normalization of Carbon Stable Isotope Ratios in Aquatic Bird Eggs

Stable isotope ratios are biogeochemical tracers that can be used to determine the source of nutrients and contaminants in avian eggs. However, the interpretation of stable carbon ratios in lipid-rich eggs is complicated because ¹³C is depleted in lipids. Variation in ¹³C abundance can therefore be obscured by variation in percent lipids. Past attempts to establish an algebraic equation to correct carbon isotope ratios for lipid content in eggs have been unsuccessful, possibly because they relied partly on data from coastal or migratory species that may obtain egg lipids from different habitats than egg protein. We measured carbon, nitrogen and sulphur stable isotope ratios in 175 eggs from eight species of aquatic birds. Carbon, nitrogen and sulphur isotopes were enriched in lipid-extracted egg samples compared with non extracted egg samples. A logarithmic equation using the C∶N ratio and carbon isotope ratio from the non extracted egg tissue calculated 90% of the lipid-extracted carbon isotope ratios within ±0.5‰. Calculating separate equations for eggs laid by species in different habitats (pelagic, offshore and terrestrial-influenced) improved the fit. A logarithmic equation, rather than a linear equation as often used for muscle, was necessary to accurately correct for lipid content because the relatively high lipid content of eggs compared with muscle meant that a linear relationship did not accurately approximate the relationship between percent lipids and the C∶N ratio. Because lipid extraction alters sulphur and nitrogen isotope ratios (and cannot be corrected algebraically), we suggest that isotopic measurement on bulk tissue followed by algebraic lipid normalization of carbon stable isotope ratio is often a good solution for homogenated eggs, at least when it is not possible to complete separate chemical analyses for each isotope.     

Combination of online enzyme digestion with stable isotope labeling for high‐throughput quantitative proteome analysis

Various enzyme reactors and online enzyme digestion strategies have been developed in recent years. These reactors greatly enhanced the detection sensitivity and proteome coverage in qualitative proteomics. However, these devices have higher rates of miscleavage in protein digestion. Therefore, we investigated the effect of online enzyme digestion on the quantification accuracy of quantitative proteomics using chemical or metabolic isotope labeling approaches. The incomplete digestion would introduce some unexpected variations in comparative quantification when the samples are digested and then chemically isotope labeled in different aliquots. Even when identical protein aliquots are processed on these devices using post‐digestion chemical isotope labeling and the CVs of the ratios controlled to less than 50% in replicate analyses, about 10% of the quantified proteins have a ratio greater than two‐fold, whereas in theory the ratio is 1:1. Interestingly, the incomplete digestion with enzyme reactor is not a problem when metabolic isotope labeling samples were processed because the proteins are isotopically labeled in vivo prior to their simultaneous digestion within the reactor. Our results also demonstrated that both high quantification accuracy and high proteome coverage can be achieved in comparative proteome quantification using online enzyme digestion even when a limited amount of metabolic isotope labeling samples is used (1683 proteins comparatively quantified from 10⁵ Hela cells).     

Novel approach for peptide quantitation and sequencing based on 15N and 13C metabolic labeling

Here we describe a method for protein identification and quantification using stable isotopes via in vivo metabolic labeling of the hyperthermophilic crenarchaeon Sulfolobus solfataricus. Stable isotope labeling for quantitative proteomics is becoming increasingly popular; however, its usefulness in protein identification has not been fully exploited. We use both 15N and 13C labeling to create three different versions of the same peptide, corresponding to the unlabeled, 15N and 13C labeled versions. The peptide then appears as three different peaks in a TOF-MS scan and three corresponding sets of MS/MS spectra are obtained. With this information, the elemental carbon and nitrogen compositions for each peptide and each fragment can be calculated. When this is used as a constraint in database searching and/or de novo sequencing, the confidence of a match is increased (for an example intact peptide from 34 choices to 1). This makes the method a useful proteomic tool for both sequenced and unsequenced organisms. Furthermore, it allows for accurate protein quantitation (standard deviations over >4 peptides per protein were within 10%) of three phenotypes in one MS experiment. Abundances for each peptide are calculated by determining the relative areas of each of the three peaks in the TOF-MS spectrum.     

Comparison of Zinc Reduction with Platinum Reduction for Analysis of Deuterium‐Enriched Water Samples for the Doubly Labeled Water Technique

Objective: Isotope ratio mass spectrometry of hydrogen and oxygen is frequently used to determine total energy expenditure (TEE) using doubly labeled water. Conventionally, hydrogen isotope ratio is determined in hydrogen gas generated from water samples using zinc reduction. We compare this with a new automated platinum method to determine the ratios of hydrogen isotopes in deuterium‐enriched water samples. Research Methods and Procedures: The platinum method of sample preparation was compared with the zinc method in three ways: analytical variation in deuterium enrichment (within sample; n = 51), analytical variation in TEE estimates (within sample set; n = 10), and level of agreement of TEE estimates between both methods (n = 14). Results: For the zinc method, the standard deviation for multiple sets of triplicate ²H₂O sample analysis was ±4.36‰ and ±2.07‰ for platinum. The correlation between TEE estimates when sample sets were analyzed in duplicate was r = 0.89 for zinc and r = 0.83 for platinum. The intercept and slope of the regression line were significantly different from the line of identity for duplicate TEE estimates by zinc but were not different from the line of identity for platinum. After correction for the intra‐assay variation of each method, the correlation between zinc and platinum for TEE was 0.77, and the intercept, but not the slope, of the regression was significantly different from the line of identity. The mean difference between the zinc method and the platinum method was 56 kcal/day, and the 95% confidence interval was ?438 to 550 kcal/day. Discussion: These data suggest that the platinum method is at least as reliable as the zinc method as a sample preparation technique for isotope ratio mass spectrometry of deuterium‐enriched water samples. The platinum method is also less costly and less labor‐intensive than the zinc method.     

Otolith oxygen and carbon stable isotopes in wild and laboratory-reared plaice (Pleuronectes platessa)

The relationship between water temperature, growth rate, and otolith isotopic ratios was measured for juvenile plaice (Pleuronectes platessa) reared at two temperatures (11 and 17°C) and two feeding regimes (1 and 3 prey items·ml^?1). The otolith isotope ratios in individual fish ranged from ?2 to ?4 for carbon isotope ratios (δ¹³C) and from 0.2 to 1.9 for oxygen isotope ratios (δ¹⁸O). The otolith oxygen isotope ratios were significantly affected by water temperature, but not by feeding level, and there were no significant synergistic effects. The fractionation of oxygen isotopes during otolith growth was independent of individual growth rate. Carbon isotope ratios were not significantly affected by food ration or water temperature, but were related to fish growth rate. The carbon isotope ratios were negatively correlated with fish length in the colder water treatments, and tended to increase with fish length in the warm water treatments. The laboratory-determined relationship between otolith oxygen isotope ratio and water temperature was applied to individuals of five species (plaice, cod, whiting, haddock, gurnard) collected in a single trawl sample. The otolith derived temperatures often overestimated measured water temperatures. The difference between real and estimated water temperatures varied between species, and the closest fit was for field-caught plaice.     

Variance matters: The shape of a datum

In the quantitative analysis of behaviour, choice data are most often plotted and analyzed as logarithmic transforms of ratios of responses and of ratios of reinforcers according to the generalized-matching relation, or its derivatives such as conditional-discrimination models. The relation between log choice ratios and log reinforcer ratios has normally been found using ordinary linear regression, which minimizes the sums of the squares of the y deviations from the fitted line. However, linear regression of this type requires that the log choice data be normally distributed, of equal variance for each log reinforcer ratio, and that the x (log reinforcer ratio) measures be fixed with no variance. We argue that, while log transformed choice data may be normally distributed, log reinforcer ratios do have variance, and because these measures derive from a binomial process, log reinforcer ratio distributions will be non-normal and skewed to more extreme values. These effects result in ordinary linear regression systematically underestimating generalized-matching sensitivity values, and in faulty parameter estimates from non-linear regression to assume hyperbolic and exponential decay processes. They also lead to model comparisons, which assume equal normally distributed error around every data point, being incorrect. We describe an alternative approach that can be used if the variance in choice is measured.     

Quantitative analysis of SILAC data sets using spectral counting

We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.edu/visualize ) method relies on MS² spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high‐throughput analysis of complex biological samples.     

SVM model for quality assessment of medium resolution mass spectra from 18O-water labeling experiments

We describe a method for assessing the quality of mass spectra and improving reliability of relative ratio estimations from (18)O-water labeling experiments acquired from low resolution mass spectrometers. The mass profiles of heavy and light peptide pairs are often affected by artifacts, including coeluting contaminant species, noise signal, instrumental fluctuations in measuring ion position and abundance levels. Such artifacts distort the profiles, leading to erroneous ratio estimations, thus reducing the reliability of ratio estimations in high throughput quantification experiments. We used support vector machines (SVMs) to filter out mass spectra that deviated significantly from expected theoretical isotope distributions. We built an SVM classifier with a decision function that assigns a score to every mass profile based on such spectral features as mass accuracy, signal-to-noise ratio, and differences between experimental and theoretical isotopic distributions. The classifier was trained using a data set obtained from samples of mouse renal cortex. We then tested it on protein samples (bovine serum albumin) mixed in five different ratios of labeled and unlabeled species. We demonstrated that filtering the data using our SVM classifier results in as much as a 9-fold reduction in the coefficient of variance of peptide ratios, thus significantly improving the reliability of ratio estimations.     

Comparison of whole wood and cellulose carbon and oxygen isotope series from Pinus nigra ssp. laricio (Corsica/France)

Stable isotopes in tree rings have widely been used for palaeoclimate reconstructions since tree rings record climatic information at annual resolution. However, various wood components or different parts of an annual tree-ring may differ in their isotopic compositions. Thus, sample preparation and subsequent laboratory analysis are crucial for the isotopic signal retained in the final tree-ring isotope series used for climate reconstruction and must therefore be considered for the interpretation of isotope–climate relationships. This study focuses on wood of Corsican Pine trees (Pinus nigra ssp. laricio) as this tree species allows to reconstruct the long-term climate evolution in the western Mediterranean. In a pilot study, we concentrated on methodological issues of sample preparation techniques in order to evaluate isotope records measured on pooled whole tree-ring cellulose and whole tree-ring bulk wood samples. We analysed 80-year long carbon and oxygen chronologies of Corsican Pine trees growing near the upper tree line on Corsica. Carbon and oxygen isotope records of whole tree-ring bulk wood and whole tree-ring cellulose from a pooled sample of 5 trees were correlated with the climate parameters monthly precipitation, temperature and the self-calibrating Palmer Drought Severity Index (sc-PDSI). Results show that the offsets in carbon and oxygen isotopes of bulk wood and cellulose are not constant over time. Both isotopes correlate with climate parameters from late winter and summer. The carbon and oxygen isotope ratios of cellulose are more sensitive to climatic variables than those of bulk wood. The results of this study imply that extraction of cellulose is a pre-requisite for the reconstruction of high-resolution climate records from stable isotope series of P. nigra ssp. laricio.