High-Throughput Measurement of Lipid Turnover Rates Using Partial Metabolic Heavy Water Labeling

Dynamics of mature myelin

Myelin, which is produced by oligodendrocytes, insulates axons to facilitate rapid and efficient action potential propagation in the central nervous system. Traditionally viewed as a stable structure, myelin is now known to undergo dynamic modulation throughout life. This Review examines these dynamics, focusing on two key aspects: (1) the turnover of myelin, involving not only the renewal of constituents but the continuous wholesale replacement of myelin membranes; and (2) the structural remodeling of pre-existing, mature myelin, a newly discovered form of neural plasticity that can be stimulated by external factors, including neuronal activity, behavioral experience and injury. We explore the mechanisms regulating these dynamics and speculate that myelin remodeling could be driven by an asymmetry in myelin turnover or reactivation of pathways involved in myelin formation. Finally, we outline how myelin remodeling could have profound impacts on neural function, serving as an integral component of behavioral adaptation.

Hydrogen/deuterium exchange mass spectrometry in the world of small molecules

The combined use of hydrogen/deuterium exchange (HDX) and mass spectrometry (MS), referred to as HDX-MS, is a powerful tool for exploring molecular edifices and has been used for over 60 years. Initially for structural and mechanistic investigation of low-molecular weight organic compounds, then to study protein structure and dynamics, then, the craze to study small molecules by HDX-MS accelerated and has not stopped yet. The purpose of this review is to present its different facets with particular emphasis on recent developments and applications. Reversible H/D exchanges of mobilizable protons as well as stable exchanges of non-labile hydrogen are considered whether they are taking place in solution or in the gas phase, or enzymatically in a biological media. Some fundamental principles are restated, especially for gas-phase processes, and an overview of recent applications, ranging from identification to quantification through the study of metabolic pathways, is given.

Metabolic deuterium oxide (D2O) labeling in quantitative omics studies: A tutorial review

Mass spectrometry (MS) is an invaluable tool for sensitive detection and characterization of individual biomolecules in omics studies. MS combined with stable isotope labeling enables the accurate and precise determination of quantitative changes occurring in biological samples. Metabolic isotope labeling, wherein isotopes are introduced into biomolecules through biosynthetic metabolism, is one of the main labeling strategies. Among the precursors employed in metabolic isotope labeling, deuterium oxide (D₂O) is cost-effective and easy to implement in any biological systems. This tutorial review aims to explain the basic principle of D₂O labeling and its applications in omics research. D₂O labeling incorporates D into stable C-H bonds in various biomolecules, including nucleotides, proteins, lipids, and carbohydrates. Typically, D₂O labeling is performed at low enrichment of 1%-10% D₂O, which causes subtle changes in the isotopic distribution of a biomolecule, instead of the complete separation between labeled and unlabeled samples in a mass spectrum. D₂O labeling has been employed in various omics studies to determine the metabolic flux, turnover rate, and relative quantification. Moreover, the advantages and challenges of D₂O labeling and its future prospects in quantitative omics are discussed. The economy, versatility, and convenience of D₂O labeling will be beneficial for the long-term omics studies for higher organisms.

Metabolically-incorporated deuterium in myelin localized by neutron diffraction and identified by mass spectrometry

Myelin is a natural and dynamic multilamellar membrane structure that continues to be of significant biological and neurological interest, especially with respect to its biosynthesis and assembly during its normal formation, maintenance, and pathological breakdown. To explore the usefulness of neutron diffraction in the structural analysis of myelin, we investigated the use of in vivo labeling by metabolically incorporating non-toxic levels of deuterium (²H; D) via drinking water into a pregnant dam (D-dam) and her developing embryos. All of the mice were sacrificed when the pups (D-pups) were 55 days old. Myelinated sciatic nerves were dissected, fixed in glutaraldehyde and examined by neutron diffraction. Parallel samples that were unfixed (trigeminal nerves) were frozen for mass spectrometry (MS). The diffraction patterns of the nerves from deuterium-fed mice (D-mice) vs. the controls (H-mice) had major differences in the intensities of the Bragg peaks but no appreciable differences in myelin periodicity. Neutron scattering density profiles showed an appreciable increase in density at the center of the lipid-rich membrane bilayer. This increase was greater in D-pups than in D-dam, and its localization was consistent with deuteration of lipid hydrocarbon, which predominates over transmembrane protein in myelin. MS analysis of the lipids isolated from the trigeminal nerves demonstrated that in the pups the percentage of lipids that had one or more deuterium atoms was uniformly high across lipid species (97.6% ​± ​2.0%), whereas in the mother the lipids were substantially less deuterated (60.6% ​± ​26.4%) with levels varying among lipid species and subspecies. The mass distribution pattern of deuterium-containing isotopologues indicated the fraction (in %) of each lipid (sub-)species having one or more deuteriums incorporated: in the D-pups, the pattern was always bell-shaped, and the average number of D atoms ranged from a low of ∼4 in fatty acid to a high of ∼9 in cerebroside. By contrast, in D-dam most lipids had more complex, overlapping distributions that were weighted toward a lower average number of deuteriums, which ranged from a low of ∼3–4 in fatty acid and in one species of sulfatide to a high of 6–7 in cerebroside and sphingomyelin. The consistently high level of deuteration in D-pups can be attributed to their de novo lipogenesis during gestation and rapid, postnatal myelination. The widely varying levels of deuteration in D-dam, by contrast, likely depends on the relative metabolic stability of the particular lipid species during myelin maintenance. Our current findings demonstrate that stably-incorporated D label can be detected and localized using neutron diffraction in a complex tissue such as myelin; and moreover, that MS can be used to screen a broad range of deuterated lipid species to monitor differential rates of lipid turnover. In addition to helping to develop a comprehensive understanding of the de novo synthesis and turnover of specific lipids in normal and abnormal myelin, our results also suggest application to studies on myelin proteins (which constitute only 20–30% by dry mass of the myelin, vs. 70–80% for lipid), as well as more broadly to the molecular constituents of other biological tissues.

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Deuterium metabolically assimilated into gestating mouse pups via drinking water.

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Neutron diffraction localized deuterium to middle of myelin membrane bilayers.

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Mass spectrometry identified 26 deuterated lipid species as myelinic.

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Myelin of pups substantially more deuterated than that of their dam.

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Deuterium differentially distributed among lipid species and subspecies.

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De novo lipid biogenesis vs. steady-state maintenance readily distinguished.

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Novel paradigm suggests application to animal models of human myelinopathies.

High-Resolution Mass Spectrometry for In Vivo Proteome Dynamics using Heavy Water Metabolic Labeling

Cellular proteins are continuously degraded and synthesized. The turnover of proteins is essential to many cellular functions. Combined with metabolic labeling using stable isotopes, LC-MS estimates proteome dynamics in high-throughput and on a large scale. Modern mass spectrometers allow a range of instrumental settings to optimize experimental output for specific research goals. One such setting which affects the results for dynamic proteome studies is the mass resolution. The resolution is vital for distinguishing target species from co-eluting contaminants with close mass-to-charge ratios. However, for estimations of proteome dynamics from metabolic labeling with stable isotopes, the spectral accuracy is highly important. Studies examining the effects of increased mass resolutions (in modern mass spectrometers) on the proteome turnover output and accuracy have been lacking. Here, we use a publicly available heavy water labeling and mass spectral data sets of murine serum proteome (acquired on Orbitrap Fusion and Agilent 6530 QToF) to analyze the effect of mass resolution of the Orbitrap mass analyzer on the proteome dynamics estimation. Increased mass resolution affected the spectral accuracy and the number acquired tandem mass spectra.

Partial Isotope Profiles Are Sufficient for Protein Turnover Analysis Using Closed-Form Equations of Mass Isotopomer Dynamics

Metabolic labeling with atom-based heavy isotopes, followed by liquid chromatography coupled with mass spectrometry (LC-MS), has been a powerful technique for studies of proteome and metabolome. In proteomics, the protein turnover of thousands of proteins can be estimated from the gradual incorporation of ²H or ¹⁵N in the diet. Software tools have been developed to automate the estimation of protein turnover. Traditionally, the turnover has been estimated using the time course of the depletion of the normalized abundance of monoisotopes. While the bioinformatic aspects of peak detection and integration, time course modeling, and uncertainty estimation have progressed, mass isotopomer dynamics during label incorporation has only been modeled from approximate approaches or numerical simulations. We derive closed-form equations that describe the dynamics of mass isotopomers during metabolic labeling with an atom-based stable isotope. The derived equations create an alternative method for estimating label incorporation. They also provide opportunities for estimation of precursor-product relationships in species or systems where they are unknown. The equations are useful in bioinformatic tools for analyzing mass spectral data from metabolic labeling.

Ultrahigh-Resolution Mass Spectrometry Method for Resolving 13C-Enrichment Patterns in a Microalgal Lipidome

The analysis of 13C-labeled lipids by mass spectrometry is challenging due to the complexity from labeling the large number of carbon atoms in lipids. To further add to the complexity, different adducts can be produced during electrospray ionization and in-source fragmentation, which can create complex overlapping isotope patterns that can only be resolved using high-resolution mass spectrometry. Co-elution of lipids even after chromatographic separation also adds to the potential for overlapping mass spectra. Here, we describe a procedure that enables full 13C-labeled patterns to be resolved in complex microalgal lipid extracts as well a procedure that provides structural labeling information. Mass resolving powers of 240000 full width half-maximum (fwhm) and fast targeted MS/MS allowed the differentiation of isotopologues, adducts, and unresolved lipid species after chromatographic separation. This enabled the percentage of 13C enrichment to be calculated for each individual lipid species over a time series in the microalgal lipidome. The application of tandem mass spectrometry (MS/MS) also allowed the degree of labeling within the headgroup vs acyl chains to be determined, further adding to the detail of information collected. This information is particularly useful for studying lipid synthesis and remodeling processes and can be extended to other biological systems.

Timepoint Selection Strategy for In Vivo Proteome Dynamics from Heavy Water Metabolic Labeling and LC-MS

Protein homeostasis, proteostasis, is essential for healthy cell functioning and is dysregulated in many diseases. Metabolic labeling with heavy water followed by liquid chromatography coupled online to mass spectrometry (LC-MS) is a powerful high-throughput technique to study proteome dynamics in vivo. Longer labeling duration and dense timepoint sampling (TPS) of tissues provide accurate proteome dynamics estimations. However, the experiments are expensive, and they require animal housing and care, as well as labeling with stable isotopes. Often, the animals are sacrificed at selected timepoints to collect tissues. Therefore, it is necessary to optimize TPS for a given number of sampling points and labeling duration and target a specific tissue of study. Currently, such techniques are missing in proteomics. Here, we report on a formula-based stochastic simulation strategy for TPS for in vivo studies with heavy water metabolic labeling and LC-MS. We model the rate constant (lognormal), measurement error (Laplace), peptide length (gamma), relative abundance of the monoisotopic peak (beta regression), and the number of exchangeable hydrogens (gamma regression). The parameters of the distributions are determined using the corresponding empirical probability density functions from a large-scale dataset of murine heart proteome. The models are used in the simulations of the rate constant to minimize the root-mean-square error (rmse). The rmse for different TPSs shows structured patterns. They are analyzed to elucidate common features in the patterns.

Analysis of the Physiological and Metabolic State of Leishmania Using Heavy Water Labeling

This protocol describes the use of heavy water (²H₂O) labeling to determine the growth rate and metabolic state of Leishmania parasites in culture and in infected animals. In vitro labeling studies are undertaken by cultivating defined parasite developmental stages in standard medium supplemented with 5% ²H₂O, resulting in the incorporation of deuterium (²H) into a range of metabolic precursors used in macromolecule (DNA, RNA, protein, lipid, and glycan) synthesis. The rate of turnover of different parasite macromolecules can subsequently be determined by analysis of deuterium enrichment in the different constituents of these macromolecules by gas chromatography-mass spectrometry (GC-MS). To measure the growth rate and physiological state of parasite stages in lesion tissue, infected mice were provided with 9% ²H₂O in their drinking water for various periods of time and ²H-enrichment in the macromolecular constituents of isolated lesion-derived parasite stages determined by GC-MS. This protocol provides quantitative information on key cellular processes, such as replication (DNA turnover), transcription (RNA turnover), translation (protein turnover), membrane biogenesis (lipid turnover), and central carbon metabolism (glycan turnover) that define the growth state and phenome of different parasite stages in vitro and in vivo. This approach can be used to assess the impact of host immune responses on parasite growth and physiology (using different Leishmania strains/species, mouse lines), characterize different parasite populations during chronic and acute infections, and assess parasite responses to drug treatments. It is also broadly applicable to other microbial pathogens.