Summary Durable antibody production after vaccination or infection is mediated by long-lived plasma cells (LLPCs). Pathways that specifically allow LLPCs to persist remain unknown. Through bioenergetic profiling, we found that human and mouse LLPCs could robustly engage pyruvate-dependent respiration whereas their short-lived counterparts could not. LLPCs took up more glucose than did short-lived plasma cells (SLPCs) in vivo, and this glucose was essential for the generation of pyruvate. Glucose was primarily used to glycosylate antibodies, but glycolysis could be promoted by stimuli such as low ATP levels and the resultant pyruvate used for respiration by LLPCs. Deletion of Mpc2, which encodes an essential component of the mitochondrial pyruvate carrier, led to a progressive loss of LLPCs and of vaccine-specific antibodies in vivo. Thus, glucose uptake and mitochondrial pyruvate import prevent bioenergetic crises and allow LLPCs to persist. Immunizations which maximize these plasma cell metabolic properties may thus provide enduring antibody-mediated immunity.

A growing appreciation of the metabolic artifacts of cell culture has generated heightened enthusiasm for performing metabolomics on populations of cells purified from tissues and biofluids. Fluorescence activated cell sorting, or FACS, is a widely used experimental approach to purify specific cell types from complex heterogeneous samples. Here we show that FACS introduces oxidative stress and alters the metabolic state of cells. Compared to unsorted controls, astrocytes subjected to FACS prior to metabolomic analysis showed altered ratios of GSSG to GSH, NADPH to NADP+, and NAD+ to NADH. Additionally, a 50% increase in reactive oxygen species was observed in astrocytes subjected to FACS relative to unsorted controls. At a more comprehensive scale, nearly half of the metabolomic features that we profiled by liquid chromatography/mass spectrometry were changed by at least 1.5-fold in intensity due to cell sorting. Some specific metabolites identified to have significantly altered levels as a result of cell sorting included glycogen, nucleosides, amino acids, central carbon metabolites, and acylcarnitines. Although the addition of fetal bovine serum to the cell-sorting buffer decreased oxidative stress and attenuated changes in metabolite concentrations, fetal bovine serum did not preserve the metabolic state of the cells during FACS. We conclude that, irrespective of buffer components and data-normalization strategies we examined, metabolomic results from sorted cells do not accurately reflect physiological conditions prior to sorting.

Identification of previously unreported metabolites (so-called 'unknowns') in untargeted metabolomic data has become an increasingly active area of research. Considerably less attention, however, has been dedicated to identifying unknown metabolic pathways. Yet, for each unknown metabolite structure, there is potentially a yet-to-be-discovered chemical transformation. Elucidating these biochemical connections is essential to advancing our knowledge of cellular metabolism and can be achieved by tracking an isotopically labeled precursor to an unexpected product. In addition to their role in mapping metabolic fates, isotopic labels also provide critical insight into pathway dynamics (i.e., metabolic fluxes) that cannot be obtained from conventional label-free metabolomic analyses. When labeling is compared quantitatively between conditions, for example, isotopic tracers can enable relative pathway activities to be inferred. To discover unexpected chemical transformations or unanticipated differences in metabolic pathway activities, we have developed X 13 CMS, a platform for analyzing liquid chromatography/mass spectrometry (LC/MS) data at the systems level. After providing cells, animals, or patients with an isotopically enriched metabolite (e.g., 13 C, 15 N, or 2 H), X 13 CMS identifies compounds that have incorporated the isotopic tracer and reports the extent of labeling for each. The analysis can be performed with a single condition, or isotopic fates can be compared between multiple conditions. The choice of which metabolite to enrich and which isotopic label to use is highly context dependent, but 13 Cglucose and 13 C-glutamine are often applied because they feed a large number of metabolic pathways. X 13 CMS is freely available.

BackgroundTwo-hydroxyglutarate (2HG) is present at low concentrations in healthy mammalian cells as both an L and D enantiomer. Both the L and D enantiomers have been implicated in regulating cellular physiology by mechanisms that are only partially characterized. In multiple human cancers, the D enantiomer accumulates due to gain-of-function mutations in the enzyme isocitrate dehydrogenase (IDH) and has been hypothesized to drive malignancy through mechanisms that remain incompletely understood. While much attention has been dedicated to identifying the route of 2HG synthesis, the metabolic fate of 2HG has not been studied in detail. Yet the metabolism of 2HG may have important mechanistic consequences influencing cell function and cancer pathogenesis, such as modulating redox potential or producing unknown products with unique modes of action.ResultsBy applying our isotope-based metabolomic platform, we unbiasedly and comprehensively screened for products of L- and D-2HG in HCT116 colorectal carcinoma cells harboring a mutation in IDH1. After incubating HCT116 cells in uniformly 13C-labeled 2HG for 24 h, we used liquid chromatography/mass spectrometry to track the labeled carbons in small molecules. Strikingly, we did not identify any products of 2HG metabolism from the thousands of metabolomic features that we screened. Consistent with these results, we did not detect any significant changes in the labeling patterns of tricarboxylic acid cycle metabolites from wild type or IDH1 mutant cells cultured in 13C-labeled glucose upon the addition of L, D, or racemic mixtures of 2HG. A more sensitive, targeted analysis revealed trace levels of isotopic enrichment (<1 %) in some central carbon metabolites from 13C-labeled 2HG. However, we found that cells do not deplete 2HG from the media at levels above our detection limit over a 48 h time period.ConclusionsTaken together, we conclude that 2HG carbon is not readily transformed in the HCT116 cell line. These data indicate that the phenotypic alterations induced by 2HG are not a result of its metabolic products.

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for the treatment of type 2 diabetes; however, the enzyme has been classified by some as an "undruggable target". Here we describe studies directed toward the development of agents that covalently capture the sulfenyl amide "oxoform" of PTP1B generated during insulin signaling events. The sulfenyl amide residue found in oxidized PTP1B presents a unique electrophilic sulfur center that may be exploited in drug and probe design. Covalent capture of oxidized PTP1B could permanently disable the intracellular pool of enzyme involved in regulation of insulin signaling. Here, we employed a dipeptide model of oxidized PTP1B to investigate the nucleophilic capture of the sulfenyl amide residue by structurally diverse 1,3-diketones. All of the 1,3-diketones examined here reacted readily with the electrophilic sulfur center in the sulfenyl amide residue to generate stable covalent attachments. Several different types of products were observed, depending upon the substituents present on the 1,3-diketone. The results provide a chemical foundation for the development of agents that covalently capture the oxidized form of PTP1B generated in cells during insulin signaling events.

Metabolite identifications are most frequently achieved in untargeted metabolomics by matching precursor mass and full, high-resolution MS2 spectra to metabolite databases and standards. Here we considered an alternative approach for establishing metabolite identifications that does not rely on full, high-resolution MS2 spectra. First, we select mass-to-charge regions containing the most informative metabolite fragments and designate them as bins. We then translate each metabolite fragmentation pattern into a binary code by assigning 1’s to bins containing fragments and 0’s to bins without fragments. With 20 bins, this binary-code system is capable of distinguishing 96% of the compounds in the METLIN MS2 library. A major advantage of the approach is that it extends untargeted metabolomics to low-resolution triple quadrupole (QqQ) instruments, which are typically less expensive and more robust than other types of mass spectrometers. We demonstrate a method of acquiring MS2 data in which the third quadrupole of a QqQ instrument cycles over 20 wide isolation windows (coinciding with the location and width of our bins) for each precursor mass selected by the first quadrupole. Operating the QqQ instrument in this mode yields diagnostic bar codes for each precursor mass that can be matched to the bar codes of metabolite standards. Furthermore, our data suggest that using low-resolution bar codes enables QqQ instruments to make MS2-based identifications in untargeted metabolomics with a specificity and sensitivity that is competitive to high-resolution time-of-flight technologies.

Model dipeptide (I) is prepared for a detailed title study.

There is increasing interest in the application of metabolomics to animal models. When performing metabolomics with animal models, however, often researchers are focused on only one specific cell lineage. A common approach for purifying one cell type from a multicellular sample is fluorescent‐activated cell sorting (FACS). Cells can be sorted according to morphology or fluorescent markers, such as GFP. Although necessary to purify cell populations, FACS is a timely process that could potentially influence metabolism. In this study, we examined whether the process of cell sorting causes changes in metabolism, which may complicate interpretation in metabolic studies employing FACS. We used a simplified model in which astrocytes grown in a mono‐culture were either metabolically quenched with methanol immediately after harvesting or metabolically quenched after cell sorting. Samples were analyzed using tandem liquid chromatography/mass spectrometry (LC/MS) with both targeted and untargeted methods. We found that many metabolite concentrations, including central carbon metabolites, amino acids, and nucleotides, were altered after cell sorting. Some structural lipid pool sizes were unchanged. We conclude that cell sorting is not compatible with measuring metabolite concentrations by conventional metabolomics, and we explore several alternative metabolomics strategies that may provide more robust results.Support or Funding InformationGJP received financial support for this work from the National Institutes of Health Grants R21 CA191097 and R35 ES028365, the Alfred P. Sloan Foundation, the Pew Scholars Program in the Biomedical Sciences, the Camille Dreyfus Foundation, and the Edward Mallinckrodt, Jr Foundation.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.