Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data

The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h(-1). Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass.     

Dynamic flux responses in riboflavin overproducing Bacillus subtilis to increasing glucose limitation in fed‐batch culture

How do intracellular fluxes respond to dynamically increasing glucose limitation when the physiology changes from strong overflow metabolism near to exclusively maintenance metabolism? Here we investigate this question in a typical industrial, glucose‐limited fed‐batch cultivation with a riboflavin overproducing Bacillus subtilis strain. To resolve dynamic flux changes, a novel approach to ¹³C flux analysis was developed that is based on recording ¹³C labeling patterns in free intracellular amino acids. Fluxes are then estimated with stationary flux ratio and iterative isotopomer balancing methods, for which a decomposition of the process into quasi‐steady states and estimation of isotopic steady state ¹³C labeling patterns was necessary. By this approach, we achieve a temporal resolution of 30–60 min that allows us to resolve the slow metabolic transients that typically occur in such cultivations. In the late process phase we found, most prominently, almost exclusive respiratory metabolism, significantly increased pentose phosphate pathway contribution and a strongly decreased futile cycle through the PEP carboxykinase. As a consequence, higher catabolic NADPH formation occurred than was necessary to satisfy the anabolic demands, suggesting a transhydrogenase‐like mechanism to close the balance of reducing equivalents. Biotechnol. Bioeng. 2010. 105: 795–804. © 2009 Wiley Periodicals, Inc.     

Fate of xylem‐transported 11C‐ and 13C‐labeled CO2 in leaves of poplar

In recent studies, assimilation of xylem‐transported CO₂ has gained considerable attention as a means of recycling respired CO₂ in trees. However, we still lack a clear and detailed picture on the magnitude of xylem‐transported CO₂ assimilation, in particular within leaf tissues. To this end, detached poplar leaves (Populus × canadensis Moench ‘Robusta’) were allowed to take up a dissolved ¹³CO₂ label serving as a proxy of xylem‐transported CO₂ entering the leaf from the branch. The uptake rate of the ¹³C was manipulated by altering the vapor pressure deficit (VPD) (0.84, 1.29 and 1.83 kPa). Highest tissue enrichments were observed under the highest VPD. Among tissues, highest enrichment was observed in the petiole and the veins, regardless of the VPD treatment. Analysis of non‐labeled leaves showed that some ¹³C diffused from the labeled leaves and was fixed in the mesophyll of the non‐labeled leaves. However, ¹³C leaf tissue enrichment analysis with elemental analysis coupled to isotope ratio mass spectrometry was limited in spatial resolution at the leaf tissue level. Therefore, ¹¹C‐based CO₂ labeling combined with positron autoradiography was used and showed a more detailed spatial distribution within a single tissue, in particular in secondary veins. Therefore, in addition to ¹³C, ¹¹C‐based autoradiography can be used to study the fate of xylem‐transported CO₂ at leaf level, allowing the acquisition of data at a yet unprecedented resolution.     

Kinetic isotope effects significantly influence intracellular metabolite 13C labeling patterns and flux determination

Rigorous mathematical modeling of carbon-labeling experiments allows estimation of fluxes through the pathways of central carbon metabolism, yielding powerful information for basic scientific studies as well as for a wide range of applications. However, the mathematical models that have been developed for flux determination from ¹³C labeling data have commonly neglected the influence of kinetic isotope effects on the distribution of ¹³C label in intracellular metabolites, as these effects have often been assumed to be inconsequential. We have used measurements of the ¹³C isotope effects on the pyruvate dehydrogenase enzyme from the literature to model isotopic fractionation at the pyruvate node and quantify the modeling errors expected to result from the assumption that isotope effects are negligible. We show that under some conditions kinetic isotope effects have a significant impact on the ¹³C labeling patterns of intracellular metabolites, and the errors associated with neglecting isotope effects in ¹³C-metabolic flux analysis models can be comparable in size to measurement errors associated with GC–MS. Thus, kinetic isotope effects must be considered in any rigorous assessment of errors in ¹³C labeling data, goodness-of-fit between model and data, confidence intervals of estimated metabolic fluxes, and statistical significance of differences between estimated metabolic flux distributions.     

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system

¹³C-Metabolic flux analysis (¹³C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by ¹³C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for ¹³C-MFA. The best single tracers were doubly ¹³C-labeled glucose tracers, including [1,6-¹³C]glucose, [5,6-¹³C]glucose and [1,2-¹³C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-¹³C]glucose and [1,2-¹³C]glucose. Combined analysis of [1,6-¹³C]glucose and [1,2-¹³C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-¹³C]glucose +20% [U-¹³C]glucose.     

Metabolic flux analysis using 13C peptide label measurements

¹³C metabolic flux analysis (MFA) has become the experimental method of choice to investigate the cellular metabolism of microbes, cell cultures and plant seeds. Conventional steady‐state MFA utilizes isotopic labeling measurements of amino acids obtained from protein hydrolysates. To retain spatial information in conventional steady‐state MFA, tissues or subcellular fractions must be dissected or biochemically purified. In contrast, peptides retain their identity in complex protein extracts, and may therefore be associated with a specific time of expression, tissue type and subcellular compartment. To enable ‘single‐sample’ spatially and temporally resolved steady‐state flux analysis, we investigated the suitability of peptide mass distributions (PMDs) as an alternative to amino acid label measurements. PMDs are the discrete convolution of the mass distributions of the constituent amino acids of a peptide. We investigated the requirements for the unique deconvolution of PMDs into amino acid mass distributions (AAMDs), the influence of peptide sequence length on parameter sensitivity, and how AAMD and flux estimates that are determined through deconvolution compare to estimates from a conventional GC–MS measurement‐based approach. Deconvolution of PMDs of the storage protein β–conglycinin of soybean (Glycine max) resulted in good AAMD and flux estimates if fluxes were directly fitted to PMDs. Unconstrained deconvolution resulted in inferior AAMD and flux estimates. PMD measurements do not include amino acid backbone fragments, which increase the information content in GC–MS‐derived analyses. Nonetheless, the resulting flux maps were of comparable quality due to the precision of Orbitrap quantification and the larger number of peptide measurements.     

COMPLETE-MFA: Complementary parallel labeling experiments technique for metabolic flux analysis

We have developed a novel approach for measuring highly accurate and precise metabolic fluxes in living cells, termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. The COMPLETE-MFA method is based on combined analysis of multiple isotopic labeling experiments, where the synergy of using complementary tracers greatly improves the precision of estimated fluxes. In this work, we demonstrate the COMPLETE-MFA approach using all singly labeled glucose tracers, [1-¹³C], [2-¹³C], [3-¹³C], [4-¹³C], [5-¹³C], and [6-¹³C]glucose to determine precise metabolic fluxes for wild-type Escherichia coli. Cells were grown in six parallel cultures on defined medium with glucose as the only carbon source. Mass isotopomers of biomass amino acids were measured by gas chromatography–mass spectrometry (GC–MS). The data from all six experiments were then fitted simultaneously to a single flux model to determine accurate intracellular fluxes. We obtained a statistically acceptable fit with more than 300 redundant measurements. The estimated flux map is the most precise flux result obtained thus far for E. coli cells. To our knowledge, this is the first time that six isotopic labeling experiments have been successfully integrated for high-resolution ¹³C-flux analysis.     

Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for ¹³C metabolic flux analysis (¹³C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-¹³C]glucose and mixtures of [1-¹³C]glucose and [U-¹³C]glucose, four novel tracers were applied in this study: [2,3-¹³C]glucose, [4,5,6-¹³C]glucose, [2,3,4,5,6-¹³C]glucose and a mixture of [1-¹³C]glucose and [4,5,6-¹³C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-¹³C]glucose+20% [U-¹³C]glucose, while [4,5,6-¹³C]glucose and [5-¹³C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.     

13C标记代谢流分析中天然稳定性同位素修正矩阵构建方法及应用

稳定性同位素¹³C标记实验是分析细胞代谢流的一种重要手段,主要通过质谱检测胞内代谢物中¹³C标记的同位素分布,并作为胞内代谢流计算时的约束条件,进而通过代谢流分析算法得到相应代谢网络中的通量分布。然而在自然界中,并非只有C元素存在天然稳定性同位素¹³C,其他元素如O元素也有其天然稳定性同位素¹⁷O、¹⁸O等,这使得质谱方法所测得的同位素分布中会夹杂除¹³C标记之外的其他元素的同位素信息,特别是分子中含有较多其他元素的分子,这将导致很大的实验误差,因此需要在进行代谢流计算前进行质谱数据的矫正。本研究提出了一种基于Python语言的天然同位素修正矩阵的构建方法,用于修正同位素分布测量值中由于天然同位素分布引起的测定误差。文中提出的基本修正矩阵幂方法用于构建各元素修正矩阵,结构简单、易于编码实现,可直接应用于¹³C代谢流分析软件数据前处理。将该修正方法应用于¹³C标记的黑曲霉（Aspergillus niger）胞内代谢流分析,结果表明本研究提出的方法准确有效,为准确获取微生物胞内代谢流分析提供了可靠的数据修正方法。     

Tracing metabolic pathways of lipid biosynthesis in ectomycorrhizal fungi from position‐specific 13C‐labelling in glucose

Six position‐specific ¹³C‐labelled isotopomers of glucose were supplied to the ectomycorrhizal fungi Suillus pungens and Tricholoma flavovirens. From the resulting distribution of ¹³C among fungal PLFAs, the overall order and contribution of each glucose atom to fatty acid ¹³C enrichment was: C6 (～31%) > C5 (～25%) > C1 (～18%) > C2 (～18%) > C3 (～8%) > C4 (～1%). These data were used to parameterize a metabolic model of the relative fluxes from glucose degradation to lipid synthesis. Our data revealed that a higher amount of carbon is directed to glycolysis than to the oxidative pentose phosphate pathway (60% and 40% respectively) and that a significant part flows through these pathways more than once (73%) due to the reversibility of some glycolysis reactions. Surprisingly, 95% of carbon cycled through glyoxylate prior to incorporation into lipids, possibly to consume the excess of acetyl‐CoA produced during fatty acid turnover. Our approach provides a rigorous framework for analysing lipid biosynthesis in fungi. In addition, this approach could ultimately improve the interpretation of isotopic patterns at natural abundance in field studies.     

13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling

¹³C metabolic flux analysis (¹³C-MFA) is a widely used tool for quantitative analysis of microbial and mammalian metabolism. Until now, ¹³C-MFA was based mainly on measurements of isotopic labeling of amino acids derived from hydrolyzed biomass proteins and isotopic labeling of extracted intracellular metabolites. Here, we demonstrate that isotopic labeling of glycogen and RNA, measured with gas chromatography-mass spectrometry (GC-MS), provides valuable additional information for ¹³C-MFA. Specifically, we demonstrate that isotopic labeling of glucose moiety of glycogen and ribose moiety of RNA greatly enhances resolution of metabolic fluxes in the upper part of metabolism; importantly, these measurements allow precise quantification of net and exchange fluxes in the pentose phosphate pathway. To demonstrate the practical importance of these measurements for ¹³C-MFA, we have used Escherichia coli as a model microbial system and CHO cells as a model mammalian system. Additionally, we have applied this approach to determine metabolic fluxes of glucose and xylose co-utilization in the E. coli ΔptsG mutant. The convenience of measuring glycogen and RNA, which are stable and abundant in microbial and mammalian cells, offers the following key advantages: reduced sample size, no quenching required, no extractions required, and GC-MS can be used instead of more costly LC-MS/MS techniques. Overall, the presented approach for ¹³C-MFA will have widespread applicability in metabolic engineering and biomedical research.     

Elucidating the role of copper in CHO cell energy metabolism using 13C metabolic flux analysis

¹³C‐metabolic flux analysis was used to understand copper deficiency‐related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein‐producing CHO cells. Stationary‐phase labeling experiments with U‐¹³C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed‐batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC‐MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux. Fluxes were evaluated 300 times from stoichiometrically feasible random guess values and their confidence intervals calculated by Monte Carlo simulations. Results from metabolic flux analysis exhibited significant carbon redistribution throughout the metabolic network in cells under Cu deficiency. Specifically, glycolytic fluxes increased (25%–79% relative to glucose uptake) whereas fluxes through the TCA and pentose phosphate pathway (PPP) were lower (15%–23% and 74%, respectively) compared with the Cu‐containing condition. Furthermore, under Cu deficiency, 33% of the flux entering TCA via the pyruvate node was redirected to lactate and malate production. Based on these results, we hypothesize that Cu deficiency disrupts the electron transport chain causing ATP deficiency, redox imbalance, and oxidative stress, which in turn drive copper‐deficient CHO cells to produce energy via aerobic glycolysis, which is associated with excessive lactate production, rather than the more efficient route of oxidative phosphorylation. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1179–1186, 2015     

New tools for mass isotopomer data evaluation in (13)C flux analysis: mass isotope correction, data consistency checking, and precursor relationships

13C metabolic flux analysis (MFA) is based on carbon-labeling experiments where a specifically (13)C labeled substrate is fed. The labeled carbon atoms distribute over the metabolic network and the label enrichment of certain metabolic pools is measured by using different methods. Recently, MS methods have been dramatically improved-large and precise datasets are now available. MS data has to be preprocessed and corrected for natural stable mass isotopes. In this article we present (1). a new elegant method to correct MS measurement data for natural stable mass isotopes by infinite dimensional matrix calculus and (2). we statistically analyze and discuss a reconstruction of labeling pattern in metabolic precursors from biosynthesis molecules. Moreover, we establish a new method for consistency checking of MS spectra that can be applied for automatic error recognition in high-throughput flux analysis procedures. Preprocessing the measurement data changes their statistical properties which have to be considered in the subsequent parameter fitting process for (13)C MFA. We show that correcting for stable mass isotopes leads to rather small correlations. On the other hand, a direct reconstruction of a precursor labeling pattern from an aromatic amino acid measurement turns out to be critical. Reasonable results are only obtained if additional, independent information about the labeling of at least one precursor is available. A versatile MatLab tool for the rapid correction and consistency checking of MS spectra is presented. Practical examples for the described methods are also given.     

Metabolic flux analysis in biotechnology processes

Metabolic flux analysis (MFA) has become a fundamental tool of metabolic engineering to elucidate the metabolic state of the cell and has been applied to various biotechnological processes. In recent years, considerable technical advances have been made. Developments of analytical instruments allow us to determine ¹³C labeling distribution of intracellular metabolites with high accuracy and sensitivity. Moreover, kinetic information of intracellular label distribution during isotopic instationary enables us to calculate metabolic fluxes with shortened experimental time and decreased amount of labeled substrate. The ¹³C MFA may be one of the most promising approaches for the target estimation to improve strain performances and production processes.     

Mass Spectrometric Identification of 13C‐Labeled Metabolites During Anaerobic Propanoic Acid Oxidation

Biowaste digestion is a possibility to gain biogas as a renewable fuel source. However, the anaerobic food chain may be disrupted by, e.g., substrate overload or by inhibitors, leading to the accumulation of volatile fatty acids (VFAs), predominantly of propanoic acid (PA). VFA Accumulation may cause a rapid pH decrease, less biogas production, or even a total inhibition. To maintain high biogas productivity or to prevent a collapse of methanogenesis, metabolic properties of the degrading microorganisms must be elucidated, e.g., by investigation of the established pathways for degradation of VFAs. A Dani 3950 headspace system (HS), a Varian 431 gas chromatograph (GC), and a Varian 210 mass spectrometer (MS) have been combined to quantify and specifically identify metabolites of PA oxidation. The use of [1‐¹³C]‐labeled PA as a carbon source for microorganisms allows differentiation between the methyl‐malonyl‐CoA or the C(6)‐dismutation pathway, both resulting in AcOH production. Appearance of the ¹³C‐moiety either in the COO or Me group of AcO can easily be detected by MS. The methyl‐malonyl‐CoA pathway was successfully identified as the only pathway of PA degradation by organisms in a lab‐scale anaerobic digester. A similar approach can be applied to any degradation pathway involving VFAs.     

Dual‐tracer‐based isotope turnover rates in a highly invasive mysid Limnomysis benedeni from Lake Constance

Understanding the ecological patterns of invasive species and their habitats require an understanding of the species’ foraging ecology. Stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope values provide useful information into the study of animal ecology and evolution, since the isotope ratios of consumers reflect consumer's dietary patterns. Nevertheless, the lack of species‐ and element‐specific laboratory‐derived turnover rates could limit their application. Using a laboratory‐based dual stable isotope tracer approach (Na¹⁵NO₃ and NaH¹³CO₃), we evaluated the δ¹⁵N and δ¹³C isotope turnover rates in full‐grown adult invasive Limnomysis benedeni from Lake Constance. We provide δ¹⁵N and δ¹³C turnover rates based on nonlinear least‐squares regression and posterior linear regression models. Model precisions and fit were evaluated using Akaike's information criterion. Within a couple of days, the δ¹⁵N and δ¹³C of mysids began to change. Nevertheless, after about 14 days, L. benedeni did not reach equilibrium with their new isotope values. Since the experiment was conducted on adult subjects, it is evident that turnover was mainly influenced by metabolism (in contrast to growth). Unlike traditional dietary shifts, our laboratory‐based dual stable isotope tracer approach does not shift the experimental organisms into a new diet and avoids dietary effects on isotope values. Results confirm the application of isotopic tracers to label mysid subpopulations and could be used to reflect assimilation and turnover from the labeled dietary sources. Field‐based stable isotope studies often use isotopic mixing models commonly assuming diet‐tissue steady state. Unfortunately, in cases where the isotopic composition of the animal is not in equilibrium with its diet, this can lead to highly misleading conclusions. Thus, our laboratory‐based isotopic incorporation rates assist interpretation of the isotopic values from the field and provide a foundation for future research into using isotopic tracers to investigate invasion ecology.     

Re-examination of metabolic fluxes in <Emphasis Type="Italic">Escherichia coli</Emphasis> during anaerobic fermentation of glucose using <Superscript>13</Superscript>C labeling experiments and 2-dimensional nuclear magnetic resonance (NMR) spectroscopy

Improved design of metabolic flux estimation using mixed label ¹³C labeling experiments and identifiability analysis motivated re-examination of metabolic fluxes during anaerobic fermentation in the Escherichia coli. Comprehensive metabolic flux maps were determined by using a mixture of differently labeled glucose and compared to conventional flux maps obtained using extracellular measurements and comprehensive metabolic flux maps obtained using only U-¹³C glucose as the substrate. As expected, conventional flux analysis performs poorly in comparison to ¹³C-MFA, especially in the Embden-Meyerhof-Parnas (EMP) and pentose phosphate (PP) pathways. Identifiability analysis indicated and experiments confirmed that a mixture of 10% U-^l3C glucose, 25% 1-¹³C glucose, and 65% naturally labeled glucose significantly improved the statistical quality of all calculated fluxes in the PP pathway, the EMP pathway, the anaplerotic reactions, and the tricarboxylic acid cycle. Modifying the network topology for the presence and absence of the Entner-Doudoroff pathway and the glyoxylate shunt did not affect the value or quality of estimated fluxes significantly. Extracellular measurement of formate production was necessary for the accurate estimation of the fluxes around the formate node.     

Life‐style changes of a halophilic archaeon analyzed by quantitative proteomics

Quantitative proteomics based on isotopic labeling has become the method of choice to accurately determine changes in protein abundance in highly complex mixtures. Isotope‐coded protein labeling (ICPL), which is based on the nicotinoylation of proteins at lysine residues and free N‐termini was used as a simple, reliable and fast method for the comparative analysis of three different cellular states of the halophilic archaeon Halobacterium salinarum through pairwise comparison. The labeled proteins were subjected to SDS‐PAGE, in‐gel digested and the proteolytic peptides were separated by LC and analyzed by MALDI‐TOF/TOF MS. Automated quantitation was performed by comparing the MS peptide signals of ¹²C and ¹³C nicotinoylated isotopic peptide pairs. The transitions between (i) aerobic growth in complex versus synthetic medium and (ii) aerobic versus anaerobic/phototrophic growth, both in complex medium, provide a wide span in nutrient and energy supply for the cell and thus allowed optimal studies of proteome changes. In these two studies, 559 and 643 proteins, respectively, could be quantified allowing a detailed analysis of the adaptation of H. salinarum to changes of its living conditions. The subtle cellular response to a wide variation of nutrient and energy supply demonstrates a fine tuning of the cellular protein inventory.     

The effect of cold-induced increased metabolic rate on the rate of <Superscript>13</Superscript>C and <Superscript>15</Superscript>N incorporation in house sparrows (<Emphasis Type="Italic">Passer domesticus</Emphasis>)

Animals with high metabolic rates are believed to have high rates of carbon and nitrogen isotopic incorporation. We hypothesized that (1) chronic exposure to cold, and hence an increase in metabolic rate, would increase the rate of isotopic incorporation of both ¹³C and ¹⁵N into red blood cells; and (2) that the rate of isotopic incorporation into red blood cells would be allometrically related to body mass. Two groups of sparrows were chronically exposed to either 5 or 22°C and switched from a ¹³C-depleted C₃-plant diet to a more ¹³C-enriched C₄-plant one. We used respirometry to estimate the resting metabolic rate of birds exposed chronically to our two experimental temperatures. The allometric relationship between the rate of ¹³C incorporation into blood and body mass was determined from published data. The of birds at 5°C was 1.9 times higher than that of birds at 22°C. Chronic exposure to a low temperature did not have an effect on the rate of isotopic incorporation of ¹⁵N save for a very small effect on the incorporation of ¹³C. The isotopic incorporation rate of ¹³C was 1.5 times faster than that of ¹⁵N. The fractional rate of ¹³C incorporation into avian blood was allometrically related to body mass with an exponent similar to −1/4. We conclude that the relationship between metabolic rate and the rate of isotopic incorporation into an animal’s tissues is indirect. It is probably mediated by protein turnover and thus more complex than previous studies have assumed.     

Stable isotopic labeling‐based quantitative targeted glycomics (i‐QTaG)

Mass spectrometry (MS) analysis combined with stable isotopic labeling is a promising method for the relative quantification of aberrant glycosylation in diseases and disorders. We developed a stable isotopic labeling‐based quantitative targeted glycomics (i‐QTaG) technique for the comparative and quantitative analysis of total N‐glycans using matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS). We established the analytical procedure with the chemical derivatizations (i.e., sialic acid neutralization and stable isotopic labeling) of N‐glycans using a model glycoprotein (bovine fetuin). Moreover, the i‐QTaG using MALDI‐TOF MS was evaluated with various molar ratios (1:1, 1:2, 1:5) of ¹³C₆/¹²C₆‐2‐aminobenzoic acid‐labeled glycans from normal human serum. Finally, this method was applied to direct comparison of the total N‐glycan profiles between normal human sera (n = 8) and prostate cancer patient sera (n = 17). The intensities of the N‐glycan peaks from i‐QTaG method showed a good linearity (R² > 0.99) with the amount of the bovine fetuin glycoproteins. The ratios of relative intensity between the isotopically 2‐AA labeled N‐glycans were close to the theoretical molar ratios (1:1, 1:2, 1:5). We also demonstrated that the up‐regulation of the Lewis antigen (～82%) in sera from prostate cancer patients. In this proof‐of‐concept study, we demonstrated that the i‐QTaG method, which enables to achieve a reliable comparative quantitation of total N‐glycans via MALDI‐TOF MS analysis, has the potential to diagnose and monitor alterations in glycosylation associated with disease states or biotherapeutics. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:840–848, 2015