Transport-exclusion pharmacology to localize lactate dehydrogenase activity within cells.

BACKGROUND: Recent in vitro and in vivo work has shown that lactate provides an important source of carbon for metabolic reactions in cancer cell mitochondria. An interesting question is whether lactate is oxidized by lactate dehydrogenase (LDH) in the cytosol and/or in mitochondria. Since metabolic processes in the cytosol and mitochondria are affected by redox balance, the location of LDH may have important regulatory implications in cancer metabolism. METHODS: Within most mammalian cells, metabolic processes are physically separated by membrane-bound compartments. Our general understanding of this spatial organization and its role in cellular function, however, suffers from the limited number of techniques to localize enzymatic activities within a cell. Here, we describe an approach to assess metabolic compartmentalization by monitoring the activity of pharmacological inhibitors that cannot be transported into specific cellular compartments. RESULTS: Oxamate, which chemically resembles pyruvate, is transported into mitochondria and inhibits LDH activity in purified mitochondria. GSK-2837808A, in contrast, is a competitive inhibitor of NAD, which cannot cross the inner mitochondrial membrane. GSK-2837808A did not inhibit the LDH activity of intact mitochondria, but GSK-2837808A did inhibit LDH activity after the inner mitochondrial membrane was disrupted. CONCLUSIONS: Our results are consistent with some mitochondrial LDH that is accessible to oxamate, but inaccessible to GSK-2837808A until mitochondria are homogenized. This strategy of using inhibitors with selective access to subcellular compartments, which we refer to as transport-exclusion pharmacology, is broadly applicable to localize other metabolic reactions within cells.

Lactate metabolism is associated with mammalian mitochondria.

It is well established that lactate secreted by fermenting cells can be oxidized or used as a gluconeogenic substrate by other cells and tissues. It is generally assumed, however, that within the fermenting cell itself, lactate is produced to replenish NAD+ and then is secreted. Here we explore the possibility that cytosolic lactate is metabolized by the mitochondria of fermenting mammalian cells. We found that fermenting HeLa and H460 cells utilize exogenous lactate carbon to synthesize a large percentage of their lipids. Using high-resolution mass spectrometry, we found that both 13C and 2-2H labels from enriched lactate enter the mitochondria. The lactate dehydrogenase (LDH) inhibitor oxamate decreased respiration of isolated mitochondria incubated in lactate, but not of isolated mitochondria incubated in pyruvate. Additionally, transmission electron microscopy (TEM) showed that LDHB localizes to the mitochondria. Taken together, our results demonstrate a link between lactate metabolism and the mitochondria of fermenting mammalian cells.

Exogenous Fatty Acids Are the Preferred Source of Membrane Lipids in Proliferating Fibroblasts.

Cellular proliferation requires the formation of new membranes. It is often assumed that the lipids needed for these membranes are synthesized mostly de novo. Here, we show that proliferating fibroblasts prefer to take up palmitate from the extracellular environment over synthesizing it de novo. Relative to quiescent fibroblasts, proliferating fibroblasts increase their uptake of palmitate, decrease fatty acid degradation, and instead direct more palmitate to membrane lipids. When exogenous palmitate is provided in the culture media at physiological concentrations, de novo synthesis accounts for only a minor fraction of intracellular palmitate in proliferating fibroblasts as well as proliferating HeLa and H460 cells. Blocking fatty acid uptake decreased the proliferation rate of fibroblasts, HeLa, and H460 cells, while supplementing media with exogenous palmitate resulted in decreased glucose uptake and rendered cells less sensitive to glycolytic inhibition. Our results suggest that cells scavenging exogenous lipids may be less susceptible to drugs targeting glycolysis and de novo lipid synthesis.

Metabolic regulator LKB1 is crucial for Schwann cell-mediated axon maintenance.

Schwann cells (SCs) promote axonal integrity independently of myelination by poorly understood mechanisms. Current models suggest that SC metabolism is critical for this support function and that SC metabolic deficits may lead to axonal demise. The LKB1-AMP-activated protein kinase (AMPK) kinase pathway targets several downstream effectors, including mammalian target of rapamycin (mTOR), and is a key metabolic regulator implicated in metabolic diseases. We found through molecular, structural and behavioral characterization of SC-specific mutant mice that LKB1 activity is central to axon stability, whereas AMPK and mTOR in SCs are largely dispensable. The degeneration of axons in LKB1 mutants was most dramatic in unmyelinated small sensory fibers, whereas motor axons were comparatively spared. LKB1 deletion in SCs led to abnormalities in nerve energy and lipid homeostasis and to increased lactate release. The latter acts in a compensatory manner to support distressed axons. LKB1 signaling is essential for SC-mediated axon support, a function that may be dysregulated in diabetic neuropathy.

isoMETLIN: a database for isotope-based metabolomics.

The METLIN metabolite database has become one of the most widely used resources in metabolomics for making metabolite identifications. However, METLIN is not designed to identify metabolites that have been isotopically labeled. As a result, unbiasedly tracking the transformation of labeled metabolites with isotope-based metabolomics is a challenge. Here, we introduce a new database, called isoMETLIN (http://isometlin.scripps.edu/), that has been developed specifically to identify metabolites incorporating isotopic labels. isoMETLIN enables users to search all computed isotopologues derived from METLIN on the basis of mass-to-charge values and specified isotopes of interest, such as (13)C or (15)N. Additionally, isoMETLIN contains experimental MS/MS data on hundreds of isotopomers. These data assist in localizing the position of isotopic labels within a metabolite. From these experimental MS/MS isotopomer spectra, precursor atoms can be mapped to fragments. The MS/MS spectra of additional isotopomers can then be computationally generated and included within isoMETLIN. Given that isobaric isotopomers cannot be separated chromatographically or by mass but are likely to occur simultaneously in a biological system, we have also implemented a spectral-mixing function in isoMETLIN. This functionality allows users to combine MS/MS spectra from various isotopomers in different ratios to obtain a theoretical MS/MS spectrum that matches the MS/MS spectrum from a biological sample. Thus, by searching MS and MS/MS experimental data, isoMETLIN facilitates the identification of isotopologues as well as isotopomers from biological samples and provides a platform to drive the next generation of isotope-based metabolomic studies.

Phase-aligned multiple spin-echo averaging: a simple way to improve signal-to-noise ratio of in vivo mouse spinal cord diffusion tensor image.

PURPOSE: To improve signal-noise-ratio of in vivo mouse spinal cord diffusion tensor imaging using-phase aligned multiple spin-echo technique. MATERIAL AND METHODS: In vivo mouse spinal cord diffusion tensor imaging maps generated by multiple spin-echo and conventional spin-echo diffusion weighting were examined to demonstrate the efficacy of multiple spin-echo diffusion sequence to improve image quality and throughput. Effects of signal averaging using complex, magnitude and phased images from multiple spin-echo diffusion weighting were also assessed. Bayesian probability theory was used to generate phased images by moving the coherent signals to the real channel to eliminate the effect of phase variation between echoes while preserving the Gaussian noise distribution. Signal averaging of phased multiple spin-echo images potentially solves both the phase incoherence problem and the bias of the elevated Rician noise distribution in magnitude image. The proposed signal averaging with Bayesian phase-aligned multiple spin-echo images approach was compared to the conventional spin-echo data acquired with doubling the scan time. The diffusion tensor imaging parameters were compared in the mouse contusion spinal cord injury. Significance level (p-value) and effect size (Cohen's d) were reported between the control and contused spinal cord to inspect the sensitivity of each approach in detecting white matter pathology. RESULTS: Compared to the spin-echo image, the signal-noise-ratio increased to 1.84-fold using the phased image averaging and to 1.30-fold using magnitude image averaging in the spinal cord white matter. Multiple spin-echo phased image averaging showed improved image quality of the mouse spinal cord among the tested methods. Diffusion tensor imaging metrics obtained from multiple spin-echo phased images using three echoes and two averages closely agreed with those derived by spin-echo magnitude data with four averages (two times more in acquisition time). The phased image averaging correctly reflected pathological features in contusion spinal cord injury. CONCLUSION: Our in vivo imaging results indicate that averaging the phased multiple spin-echo images yields an 84% signal-noise-ratio increase over the spin-echo images and a 41% gain over the magnitude averaged multiple spin-echo images with equal acquisition time. Current results from the animal model of spinal cord injury suggest that the phased multiple spin-echo images could be used to improve signal-noise-ratio.

Credentialing features: a platform to benchmark and optimize untargeted metabolomic methods.

The aim of untargeted metabolomics is to profile as many metabolites as possible, yet a major challenge is comparing experimental method performance on the basis of metabolome coverage. To date, most published approaches have compared experimental methods by counting the total number of features detected. Due to artifactual interference, however, this number is highly variable and therefore is a poor metric for comparing metabolomic methods. Here we introduce an alternative approach to benchmarking metabolome coverage which relies on mixed Escherichia coli extracts from cells cultured in regular and (13)C-enriched media. After mass spectrometry-based metabolomic analysis of these extracts, we "credential" features arising from E. coli metabolites on the basis of isotope spacing and intensity. This credentialing platform enables us to accurately compare the number of nonartifactual features yielded by different experimental approaches. We highlight the value of our platform by reoptimizing a published untargeted metabolomic method for XCMS data processing. Compared to the published parameters, the new XCMS parameters decrease the total number of features by 15% (a reduction in noise features) while increasing the number of true metabolites detected and grouped by 20%. Our credentialing platform relies on easily generated E. coli samples and a simple software algorithm that is freely available on our laboratory Web site (http://pattilab.wustl.edu/software/credential/). We have validated the credentialing platform with reversed-phase and hydrophilic interaction liquid chromatography as well as Agilent, Thermo Scientific, AB SCIEX, and LECO mass spectrometers. Thus, the credentialing platform can readily be applied by any laboratory to optimize their untargeted metabolomic pipeline for metabolite extraction, chromatographic separation, mass spectrometric detection, and bioinformatic processing.

Differential incorporation of glucose into biomass during Warburg metabolism.

It is well established that most cancer cells take up an increased amount of glucose relative to that taken up by normal differentiated cells. The majority of this glucose carbon is secreted from the cell as lactate. The fate of the remaining glucose carbon, however, has not been well-characterized. Here we apply a novel combination of metabolomic technologies to track uniformly labeled glucose in HeLa cancer cells. We provide a list of specific intracellular metabolites that become enriched after being labeled for 48 h and quantitate the fraction of consumed glucose that ends up in proteins, peptides, sugars/glycerol, and lipids.

X13CMS: global tracking of isotopic labels in untargeted metabolomics.

Studies of isotopically labeled compounds have been fundamental to understanding metabolic pathways and fluxes. They have traditionally, however, been used in conjunction with targeted analyses that identify and quantify a limited number of labeled downstream metabolites. Here we describe an alternative workflow that leverages recent advances in untargeted metabolomic technologies to track the fates of isotopically labeled metabolites in a global, unbiased manner. This untargeted approach can be applied to discover novel biochemical pathways and characterize changes in the fates of labeled metabolites as a function of altered biological conditions such as disease. To facilitate the data analysis, we introduce X(13)CMS, an extension of the widely used mass spectrometry-based metabolomic software package XCMS. X(13)CMS uses the XCMS platform to detect metabolite peaks and perform retention-time alignment in liquid chromatography/mass spectrometry (LC/MS) data. With the use of the XCMS output, the program then identifies isotopologue groups that correspond to isotopically labeled compounds. The retrieval of these groups is done without any a priori knowledge besides the following input parameters: (i) the mass difference between the unlabeled and labeled isotopes, (ii) the mass accuracy of the instrument used in the analysis, and (iii) the estimated retention-time reproducibility of the chromatographic method. Despite its name, X(13)CMS can be used to track any isotopic label. Additionally, it detects differential labeling patterns in biological samples collected from parallel control and experimental conditions. We validated the ability of X(13)CMS to accurately retrieve labeled metabolites from complex biological matrices both with targeted LC/MS/MS analysis of a subset of the hits identified by the program and with labeled standards spiked into cell extracts. We demonstrate the full functionality of X(13)CMS with an analysis of cultured rat astrocytes treated with uniformly labeled (U-)(13)C-glucose during lipopolysaccharide (LPS) challenge. Our results show that out of 223 isotopologue groups enriched from U-(13)C-glucose, 95 have statistically significant differential labeling patterns in astrocytes challenged with LPS compared to unchallenged control cells. Only two of these groups overlap with the 32 differentially regulated peaks identified by XCMS, indicating that X(13)CMS uncovers different and complementary information from untargeted metabolomic studies. Like XCMS, X(13)CMS is implemented in R. It is available from our laboratory website at http://pattilab.wustl.edu/x13cms.php .

Diffusion tensor imaging detects treatment effects of FTY720 in experimental autoimmune encephalomyelitis mice.

Fingolimod (FTY720) is an orally available sphingosine-1-phosphate (S1P) receptor modulator reducing relapse frequency in patients with relapsing-remitting multiple sclerosis (RRMS). In addition to immunosuppression, neuronal protection by FTY720 has also been suggested, but remains controversial. Axial and radial diffusivities derived from in vivo diffusion tensor imaging (DTI) were employed as noninvasive biomarkers of axonal injury and demyelination to assess axonal protection by FTY720 in experimental autoimmune encephalomyelitis (EAE) mice. EAE was induced through active immunization of C57BL/6 mice using myelin oligodendrocyte glycoprotein peptide 35-55 (MOG(35-55)). We evaluated both the prophylactic and therapeutic treatment effect of FTY720 at doses of 3 and 10 mg/kg on EAE mice by daily clinical scoring and end-point in vivo DTI. Prophylactic administration of FTY720 suppressed the disease onset and prevented axon and myelin damage when compared with EAE mice without treatment. Therapeutic treatment by FTY720 did not prevent EAE onset, but reduced disease severity, improving axial and radial diffusivity towards the control values without statistical significance. Consistent with previous findings, in vivo DTI-derived axial and radial diffusivity correlated with clinical scores in EAE mice. The results support the use of in vivo DTI as an effective outcome measure for preclinical drug development.

An untargeted metabolomic workflow to improve structural characterization of metabolites.

Mass spectrometry-based metabolomics relies on MS(2) data for structural characterization of metabolites. To obtain the high-quality MS(2) data necessary to support metabolite identifications, ions of interest must be purely isolated for fragmentation. Here, we show that metabolomic MS(2) data are frequently characterized by contaminating ions that prevent structural identification. Although using narrow-isolation windows can minimize contaminating MS(2) fragments, even narrow windows are not always selective enough, and they can complicate data analysis by removing isotopic patterns from MS(2) spectra. Moreover, narrow windows can significantly reduce sensitivity. In this work, we introduce a novel, two-part approach for performing metabolomic identifications that addresses these issues. First, we collect MS(2) scans with less stringent isolation settings to obtain improved sensitivity at the expense of specificity. Then, by evaluating MS(2) fragment intensities as a function of retention time and precursor mass targeted for MS(2) analysis, we obtain deconvolved MS(2) spectra that are consistent with pure standards and can therefore be used for metabolite identification. The value of our approach is highlighted with metabolic extracts from brain, liver, astrocytes, as well as nerve tissue, and performance is evaluated by using pure metabolite standards in combination with simulations based on raw MS(2) data from the METLIN metabolite database. A R package implementing the algorithms used in our workflow is available on our laboratory website ( http://pattilab.wustl.edu/decoms2.php ).

CXCR7 antagonism prevents axonal injury during experimental autoimmune encephalomyelitis as revealed by in vivo axial diffusivity.

BACKGROUND: Multiple Sclerosis (MS) is characterized by the pathological trafficking of leukocytes into the central nervous system (CNS). Using the murine MS model, experimental autoimmune encephalomyelitis (EAE), we previously demonstrated that antagonism of the chemokine receptor CXCR7 blocks endothelial cell sequestration of CXCL12, thereby enhancing the abluminal localization of CXCR4-expressing leukocytes. CXCR7 antagonism led to decreased parenchymal entry of leukocytes and amelioration of ongoing disease during EAE. Of note, animals that received high doses of CXCR7 antagonist recovered to baseline function, as assessed by standard clinical scoring. Because functional recovery reflects axonal integrity, we utilized diffusion tensor imaging (DTI) to evaluate axonal injury in CXCR7 antagonist- versus vehicle-treated mice after recovery from EAE. METHODS: C57BL6/J mice underwent adoptive transfer of MOG-reactive Th1 cells and were treated daily with either CXCR7 antagonist or vehicle for 28 days; and then evaluated by DTI to assess for axonal injury. After imaging, spinal cords underwent histological analysis of myelin and oligodendrocytes via staining with luxol fast blue (LFB), and immunofluorescence for myelin basic protein (MBP) and glutathione S-transferase-π (GST-π). Detection of non-phosphorylated neurofilament H (NH-F) was also performed to detect injured axons. Statistical analysis for EAE scores, DTI parameters and non-phosphorylated NH-F immunofluorescence were done by ANOVA followed by Bonferroni post-hoc test. For all statistical analysis a p < 0.05 was considered significant. RESULTS: In vivo DTI maps of spinal cord ventrolateral white matter (VLWM) axial diffusivities of naïve and CXCR7 antagonist-treated mice were indistinguishable, while vehicle-treated animals exhibited decreased axial diffusivities. Quantitative differences in injured axons, as assessed via detection of non-phosphorylated NH-F, were consistent with axial diffusivity measurements. Overall, qualitative myelin content and presence of oligodendrocytes were similar in all treatment groups, as expected by their radial diffusivity values. Quantitative assessment of persistent inflammatory infiltrates revealed significant decreases within the parenchyma of CXCR7 antagonist-treated mice versus controls. CONCLUSIONS: These data suggest that CXCR7 antagonism not only prevents persistent inflammation but also preserves axonal integrity. Thus, targeting CXCR7 modifies both disease severity and recovery during EAE, suggesting a role for this molecule in both phases of disease.