Protein targets of contemporary research are often membrane proteins, multiprotein complexes, secreted proteins, or other proteins of human origin. These are difficult to express in the standard expression host used for most nuclear magnetic resonance (NMR) studies, Escherichia coli. Insect cells represent an attractive alternative, since they have become a well-established expression system and simple solutions have been developed for generation of viruses to efficiently introduce the target protein DNA into cells. Insect cells enable production of a larger fraction of the human proteome in a properly folded way than bacteria, as insect cells have a very similar set of cytosolic chaperones and a closely related secretory pathway. Here, the limited and defined glycosylation pattern that insect cells produce is an advantage for structural biology studies. For these reasons, insect cells have been established as the most widely used eukaryotic expression host for crystallographic studies. In the past decade, significant advancements have enabled amino acid type-specific as well as uniform isotope labeling of proteins in insect cells, turning them into an attractive expression host for NMR studies.

The genome of the predatory bacterium Herpetosiphon aurantiacus 114-95T harbors a number of biosynthesis genes, including four terpene cyclase genes. To identify the terpenes biosynthesized from H. aurantiacus 114-95T, we fed the strain with 13C-labeled glucose and, subsequently, searched for characteristic mass shifts in its metabolome. This approach led to the discovery of a new natural product, of which the isotope pattern is indicative for a diterpene originating from the methylerythritol phosphate pathway. After large-scale fermentation of H. aurantiacus 114-95T, the putative diterpene was isolated in sufficient quantity to enable NMR-based structure elucidation. The compound, for which the name herpetopanone is proposed, features a rare octahydro-1H-indenyl skeleton. Herpetopanone bears resemblance to cadinane-type sesquiterpenes from plants, but is structurally entirely unprecedented in bacteria. Based on its molecular architecture, a possible biosynthetic pathway is postulated.

Stable isotope labeling is the state of the art technique for in vivo quantification of lymphocyte kinetics in humans. It has been central to a number of seminal studies, particularly in the context of HIV-1 and leukemia. However, there is a significant discrepancy between lymphocyte proliferation rates estimated in different studies. Notably, deuterated (2)H2-glucose (D2-glucose) labeling studies consistently yield higher estimates of proliferation than deuterated water (D2O) labeling studies. This hampers our understanding of immune function and undermines our confidence in this important technique. Whether these differences are caused by fundamental biochemical differences between the two compounds and/or by methodological differences in the studies is unknown. D2-glucose and D2O labeling experiments have never been performed by the same group under the same experimental conditions; consequently a direct comparison of these two techniques has not been possible. We sought to address this problem. We performed both in vitro and murine in vivo labeling experiments using identical protocols with both D2-glucose and D2O. This showed that intrinsic differences between the two compounds do not cause differences in the proliferation rate estimates, but that estimates made using D2-glucose in vivo were susceptible to difficulties in normalization due to highly variable blood glucose enrichment. Analysis of three published human studies made using D2-glucose and D2O confirmed this problem, particularly in the case of short term D2-glucose labeling. Correcting for these inaccuracies in normalization decreased proliferation rate estimates made using D2-glucose and slightly increased estimates made using D2O; thus bringing the estimates from the two methods significantly closer and highlighting the importance of reliable normalization when using this technique.

Stable isotope labeling is widely used to encode and quantify proteins in mass-spectrometry-based proteomics. We compared metabolic labeling with stable isotope labeling by amino acids in cell culture (SILAC) and chemical labeling by stable isotope dimethyl labeling and find that they have comparable accuracy and quantitative dynamic range in unfractionated proteome analyses and affinity pull-down experiments. Analyzing SILAC- and dimethyl-labeled samples together in single liquid chromatography-mass spectrometric analyses minimizes differences under analytical conditions, allowing comparisons of quantitative errors introduced during sample processing. We find that SILAC is more reproducible than dimethyl labeling. Because proteins from metabolically labeled populations can be combined before proteolytic digestion, SILAC is particularly suited to studies with extensive sample processing, such as fractionation and enrichment of peptides with post-translational modifications. We compared both methods in pull-down experiments using a kinase inhibitor, dasatinib, and tagged GRB2-SH2 protein as affinity baits. We describe a StageTip dimethyl-labeling protocol that we applied to in-solution and in-gel protein digests. Comparing the impact of post-digest isotopic labeling on quantitative accuracy, we demonstrate how specific experimental designs can benefit most from metabolic labeling approaches like SILAC and situations where chemical labeling by stable isotope-dimethyl labeling can be a practical alternative.

Among the inheritance of cellular components during cell division, deoxyribonucleic acid (DNA) and its condensate (chromosome) are conventionally visualized using chemical tag-labeled nucleotide analogs. However, associated mutagenesis with nucleotide analogs in the visualization of chromosomes is cause for concern. This study investigated the efficiency of using stable isotope labels in visualizing the replicating cultured human cell-chromosomes, in the absence of analog labels, at a high spatial resolution of 100 nm. The distinct carbon isotope ratio between sister chromatids reflected the semi-conservative replication of individual DNA strands through cell cycles and suggested the renewal of histone molecules in daughter chromosomes. Thus, this study provides a new, powerful approach to trace and visualize cellular components with stable isotope labeling.Key words: stable isotope, chromosome replication, semi-conservative replication, imaging, mass spectrometry.

Soil microbial diversity represents the largest global reservoir of novel microorganisms and enzymes. In this study, we coupled functional metagenomics and DNA stable-isotope probing (DNA-SIP) using multiple plant-derived carbon substrates and diverse soils to characterize active soil bacterial communities and their glycoside hydrolase genes, which have value for industrial applications. We incubated samples from three disparate Canadian soils (tundra, temperate rainforest, and agricultural) with five native carbon ((12)C) or stable-isotope-labeled ((13)C) carbohydrates (glucose, cellobiose, xylose, arabinose, and cellulose). Indicator species analysis revealed high specificity and fidelity for many uncultured and unclassified bacterial taxa in the heavy DNA for all soils and substrates. Among characterized taxa, Actinomycetales (Salinibacterium), Rhizobiales (Devosia), Rhodospirillales (Telmatospirillum), and Caulobacterales (Phenylobacterium and Asticcacaulis) were bacterial indicator species for the heavy substrates and soils tested. Both Actinomycetales and Caulobacterales (Phenylobacterium) were associated with metabolism of cellulose, and Alphaproteobacteria were associated with the metabolism of arabinose; members of the order Rhizobiales were strongly associated with the metabolism of xylose. Annotated metagenomic data suggested diverse glycoside hydrolase gene representation within the pooled heavy DNA. By screening 2,876 cloned fragments derived from the (13)C-labeled DNA isolated from soils incubated with cellulose, we demonstrate the power of combining DNA-SIP, multiple-displacement amplification (MDA), and functional metagenomics by efficiently isolating multiple clones with activity on carboxymethyl cellulose and fluorogenic proxy substrates for carbohydrate-active enzymes. Importance: The ability to identify genes based on function, instead of sequence homology, allows the discovery of genes that would not be identified through sequence alone. This is arguably the most powerful application of metagenomics for the recovery of novel genes and a natural partner of the stable-isotope-probing approach for targeting active-yet-uncultured microorganisms. We expanded on previous efforts to combine stable-isotope probing and metagenomics, enriching microorganisms from multiple soils that were active in degrading plant-derived carbohydrates, followed by construction of a cellulose-based metagenomic library and recovery of glycoside hydrolases through functional metagenomics. The major advance of our study was the discovery of active-yet-uncultivated soil microorganisms and enrichment of their glycoside hydrolases. We recovered positive cosmid clones in a higher frequency than would be expected with direct metagenomic analysis of soil DNA. This study has generated an invaluable metagenomic resource that future research will exploit for genetic and enzymatic potential.

Amino-acid selective isotope labeling of proteins offers numerous advantages in mechanistic studies by revealing structural and functional information unattainable from a crystallographic approach. However, efficient labeling of proteins with selected amino acids necessitates auxotrophic hosts, which are often not available. We have constructed a set of auxotrophs in a commonly used Escherichia coli expression strain C43(DE3), a derivative of E. coli BL21(DE3), which can be used for isotopic labeling of individual amino acids or sets of amino acids. These strains have general applicability to either soluble or membrane proteins that can be expressed in E. coli. We present examples in which proteins are selectively labeled with (13)C- and (15)N-amino acids and studied using magic-angle spinning solid-state NMR and pulsed EPR, demonstrating the utility of these strains for biophysical characterization of membrane proteins, radical-generating enzymes and metalloproteins.

The transportome of Saccharomyces cerevisiae comprises approximately 340 membrane-bound proteins, of which very few are well-characterized. Elucidating transporter proteins' function is essential not only for understanding central cellular processes in metabolite exchange with the external milieu but also for optimizing the production of value-added compounds in microbial cell factories. Here, we describe the application of 13C-labeled stable isotopes and detection by targeted LC-MS/MS as a screening tool for identifying Saccharomyces cerevisiae metabolite transporters. We compare the transport assay's sensitivity, reproducibility, and accuracy in yeast transporter mutant cell lines and Xenopus oocytes. As proof of principle, we analyzed the transport profiles of five yeast amino acid transporters. We first cultured yeast transporter deletion or overexpression mutants on uniformly labeled 13C-glucose and then screened their ability to facilitate the uptake or export of an unlabeled pool of amino acids. Individual transporters were further studied by heterologous expression in Xenopus oocytes, followed by an uptake assay with 13C labeled yeast extract. Uptake assays in Xenopus oocytes showed higher reproducibility and accuracy. Although having lower accuracy, the results from S. cerevisiae indicated the system's potential for initial high-throughput screening for native metabolite transporters. We partially confirmed previously reported substrates for all five amino acid transporters. In addition, we propose broader substrate specificity for two of the transporter proteins. The method presented here demonstrates the application of a comprehensive screening platform for the knowledge expansion of the transporter-substrate relationship for native metabolites in S. cerevisiae.

Fluxomics offers a direct readout of metabolic state but relies on indirect measurement. Stable isotope tracers imprint flux-dependent isotope labeling patterns on metabolites we measure; however, the relationship between labeling patterns and fluxes remains elusive. Here we innovate a two-stage machine learning framework termed ML-Flux that streamlines metabolic flux quantitation from isotope tracing. We train machine learning models by simulating atom transitions across five universal metabolic models starting from 26 13C-glucose, 2H-glucose, and 13C-glutamine tracers within feasible flux space. ML-Flux employs deep-learning-based imputation to take variable measurements of labeling patterns as input and successive neural networks to convert the ensuing comprehensive labeling information into metabolic fluxes. Using ML-Flux with multi-isotope tracing, we obtain fluxes through central carbon metabolism that are comparable to those from a least-squares method but orders-of-magnitude faster. ML-Flux is deployed as a webtool to expand the accessibility of metabolic flux quantitation and afford actionable information on metabolism.

Stable Isotope Labeling by Amino Acids (SILAC) is a commonly used method in quantitative proteomics. Because of compatibility with trypsin digestion, arginine and lysine are the most widely used amino acids for SILAC labeling. We observed that Schizosaccharomyces pombe (fission yeast) cannot be labeled with a specific form of arginine, (13)C(6) (15)N(4)-arginine (Arg-10), which limits the exploitation of SILAC technology in this model organism. We hypothesized that in the fission yeast the guanidinium group of (13)C(6) (15)N(4)-arginine is catabolized by arginase and urease activity to (15)N1-labeled ammonia that is used as a precursor for general amino acid biosynthesis. We show that disruption of Ni(2+)-dependent urease activity, through deletion of the sole Ni(2+) transporter Nic1, blocks this recycling in ammonium-supplemented EMMG medium to enable (13)C(6) (15)N(4)-arginine labeling for SILAC strategies in S. pombe. Finally, we employed Arg-10 in a triple-SILAC experiment to perform quantitative comparison of G1 + S, M, and G2 cell cycle phases in S. pombe.

Solid-state NMR (ssNMR) is a rapidly developing technique for exploring structure and dynamics of membrane proteins, but its progress is hampered by its low sensitivity. Despite the latest technological advances, routine ssNMR experiments still require several milligrams of isotopically labeled protein. While production of bacterial membrane proteins on this scale is usually feasible, obtaining such quantities of eukaryotic membrane proteins is often impossible or extremely costly. We have demonstrated that, by using isotopic labeling in yeast Pichia pastoris, one can inexpensively produce milligram quantities of doubly labeled functional samples, which yield multidimensional ssNMR spectra of high resolution suitable for detailed structural investigation. This was achieved by combining protocols of economical isotope labeling of soluble proteins previously used for solution NMR with protocols of expression of eukaryotic membrane proteins successfully employed for other methods. We review two cases of such isotope labeling, of fungal rhodopsin from Leptosphaeria maculans and human aquaporin-1.

Metabolomics has been used in unraveling metabolites that play essential roles in plant-microbe (including pathogen) interactions. However, the problem of profiling a plant metabolome with potential contaminating metabolites from the coexisting microbes has been largely ignored. To address this problem, we implemented an effective stable isotope labeling approach, where the metabolome of a plant bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 was labeled with heavy isotopes. The labeled bacterial cells were incubated with Arabidopsis thaliana epidermal peels (EPs) with guard cells, and excessive bacterial cells were subsequently removed from the plant tissues by washing. The plant metabolites were characterized by liquid chromatography mass spectrometry using multiple reactions monitoring, which can differentiate plant and bacterial metabolites. Targeted metabolomic analysis suggested that Pst DC3000 infection may modulate stomatal movement by reprograming plant signaling and primary metabolic pathways. This proof-of-concept study demonstrates the utility of this strategy in differentiation of the plant and microbe metabolomes, and it has broad applications in studying metabolic interactions between microbes and other organisms.

Cancer detection relying on the release of volatile biomarkers has been extensively studied, but the individual biochemical processes of the cells from which biogenic volatiles originate have not been thoroughly elucidated to date. Inadequate determination of the metabolic origin of the volatile biomarkers has limited the progress of the scientific and practical applications of volatile biomarkers. To overcome the current limitations, we developed a metabolism tracking approach combining stable isotope labeling and flux analysis of volatiles to trace the intracellular metabolism-derived volatiles and to reveal their relation to cancer metabolic pathways. Specifically, after the 13C labeling of lung cancer cell, the isotopic ratio of whole cellular carbon was measured by nanoscale secondary ion mass spectrometry-based imaging. The kinetic modeling with the time-dependent isotopic ratio determined the period during which cancer cells reach the metabolic steady state, at which time all of the potential volatiles derived from intracellular metabolism were fully enriched isotopically. By measuring the isotopic enrichment of volatiles at the end-stage of isotopic flux, we found that 2-pentadecanone appeared to be derived from the metabolic cascade starting from glucose to fatty acid synthesis. Furthermore, this biosynthetic pathway was determined to be distinct in cancer, as it was upregulated in colon, breast, and pancreatic cancer cells but not in normal cells. The investigation of the metabolic footprint of 2-pentadecanone demonstrates that our novel approach could be applied to trace the metabolic origin of biogenic volatile organic compounds. This analytical strategy represents a potential cutting-edge tool in elucidating the biochemical authenticity of cancer volatiles and further expanding our understanding of the metabolic network of airborne metabolites in vitro.

Post-transcriptional RNA modifications that are introduced during the multistep ribosome biogenesis process are essential for protein synthesis. The current lack of a comprehensive method for a fast quantitative analysis of rRNA modifications significantly limits our understanding of how individual modification steps are coordinated during biogenesis inside the cell. Here, an LC-MS approach has been developed and successfully applied for quantitative monitoring of 29 out of 36 modified residues in the 16S and 23S rRNA from Escherichia coli . An isotope labeling strategy is described for efficient identification of ribose and base methylations, and a novel metabolic labeling approach is presented to allow identification of MS-silent pseudouridine modifications. The method was used to measure relative abundances of modified residues in incomplete ribosomal subunits compared to a mature (15)N-labeled rRNA standard, and a number of modifications in both 16S and 23S rRNA were present in substoichiometric amounts in the preribosomal particles. The RNA modification levels correlate well with previously obtained profiles for the ribosomal proteins, suggesting that RNA is modified in a schedule comparable to the association of the ribosomal proteins. Importantly, this study establishes an efficient workflow for a global monitoring of ribosomal modifications that will contribute to a better understanding of mechanisms of RNA modifications and their impact on intracellular processes in the future.

Phosphatidylethanolamine metabolism plays essential roles in eukaryotic cells but has not been completely investigated due to its complexity. This is because lipid species, unlike proteins or nucleic acids, cannot be easily manipulated at the single molecule level or controlled with subcellular resolution, two of the key factors toward understanding their functions. Here, we use the organelle-targeting photoactivation method to study PE metabolism in living cells with a high spatiotemporal resolution. Containing predefined PE structures, probes which can be selectively introduced into the ER or mitochondria were designed to compare their metabolic products according to their subcellular localization. We combined photo-uncaging with dual stable isotopic labeling to track PE metabolism in living cells by mass spectrometry analysis. Our results reveal that both mitochondria- and ER-released PE participate in phospholipid remodeling, and that PE methylation can be detected only under particular conditions. Thus, our method provides a framework to study phospholipid metabolism at subcellular resolution.

Baculovirus-infected silkworms are promising bioreactors for producing recombinant glycoproteins, including antibodies. Previously, we developed a method for isotope labeling of glycoproteins for nuclear magnetic resonance (NMR) studies using silkworm larvae reared on an artificial diet containing 15N-labeled yeast crude protein extract. Here, we further develop this method by introducing a technique for the expression of isotope-labeled glycoproteins by silkworm pupae, which has several potential advantages relative to larvae-based techniques in terms of production yield, ease of handling, and storage. Here, we fed fifth instar larvae an artificial diet with an optimized composition containing [methyl-13C]methionine, leading to pupation. Nine-day-old pupae were then injected with recombinant Bombyx mori nucleopolyhedrovirus (BmNPV) bacmid for expression of recombinant human immunoglobulin G (IgG). From the whole-body homogenates of pupae, 0.35 mg/pupa of IgG was harvested, which is a yield that is five times higher than can be obtained from larvae. Recombinant IgG, thus prepared, exhibited mainly three kinds of pauci-mannose-type oligosaccharides and had a 13C-enrichment ratio of approximately 80%. This enabled selective observation of NMR signals originating from the methionyl methyl group of IgG, confirming its conformational integrity. These data demonstrate the utility of silkworm pupae as factories for producing recombinant glycoproteins with amino-acid-selective isotope labeling.

Metabolism gained increasing interest for the understanding of diseases and to pinpoint therapeutic intervention points. However, classical metabolomics techniques only provide a very static view on metabolism. Metabolic flux analysis methods, on the other hand, are highly targeted and require detailed knowledge on metabolism beforehand.

Multiple segmental and selective isotope labeling of RNA with three segments has been demonstrated by introducing an RNA segment, selectively labeled with (13)C(9)/(15)N(2)/(2)H((1', 3', 4', 5', 5''))-labeled uridine residues, into the central position of the 20 kDa epsilon-RNA of Duck Hepatitis B Virus. The RNA molecules were produced via two efficient protocols: a two-step protocol, which uses T4 DNA ligase and T4 RNA ligase 1, and a one-pot protocol, which uses T4 RNA ligase 1 alone. With T4 RNA ligase 1 all not-to-be-ligated termini are usually protected to prevent formation of side products. We show that such labor-intensive protection of termini is not required, provided segmentation sites can be chosen such that the segments fold into the target structure or target-like structures and thus are not trapped into stable alternate structures. These sites can be reliably predicted via DINAMelt. The simplified NMR spectrum provided evidence for the presence of a U28 H(3)-imino resonance, previously obscured in the fully labeled sample, and thus of the non-canonical base pair U28:C37. The demonstrated multiple segmental labeling protocols are generally applicable to large RNA molecules and can be extended to more than three segments.

The ocean is a net source of the greenhouse gas and ozone-depleting substance, nitrous oxide (N2O), to the atmosphere. Most of that N2O is produced as a trace side product during ammonia oxidation, primarily by ammonia-oxidizing archaea (AOA), which numerically dominate the ammonia-oxidizing community in most marine environments. The pathways to N2O production and their kinetics, however, are not completely understood. Here, we use 15N and 18O isotopes to determine the kinetics of N2O production and trace the source of nitrogen (N) and oxygen (O) atoms in N2O produced by a model marine AOA species, Nitrosopumilus maritimus. We find that during ammonia oxidation, the apparent half saturation constants of nitrite and N2O production are comparable, suggesting that both processes are enzymatically controlled and tightly coupled at low ammonia concentrations. The constituent atoms in N2O are derived from ammonia, nitrite, O2, and H2O via multiple pathways. Ammonia is the primary source of N atoms in N2O, but its contribution varies with ammonia to nitrite ratio. The ratio of 45N2O to 46N2O (i.e., single or double labeled N) varies with substrate ratio, leading to widely varying isotopic signatures in the N2O pool. O2 is the primary source for O atoms. In addition to the previously demonstrated hybrid formation pathway, we found a substantial contribution by hydroxylamine oxidation, while nitrite reduction is an insignificant source of N2O. Our study highlights the power of dual 15N-18O isotope labeling to disentangle N2O production pathways in microbes, with implications for interpretation of pathways and regulation of marine N2O sources.

miRNAs are small noncoding RNAs that regulate gene expression. We have used stable isotope labeling by amino acids in cell culture (SILAC) to investigate the effect of miRNA-1 on the HeLa cell proteome. Expression of 12 out of 504 investigated proteins was repressed by miRNA-1 transfection. This repressed set of genes significantly overlaps with miRNA-1 regulated genes that have been identified with DNA array technology and are predicted by computational methods. Moreover, we find that the 3'-untranslated region for the repressed set are enriched in miRNA-1 complementary sites. Our findings demonstrate that SILAC can be used for miRNA target identification and that one highly expressed miRNA can regulate the levels of many different proteins.