The Sedoheptulose Kinase CARKL Directs Macrophage Polarization through Control of Glucose Metabolism

Summary Immune cells are somewhat unique in that activation responses can alter quantitative phenotypes upwards of 100,000-fold. To date little is known about the metabolic adaptations necessary to mount such dramatic phenotypic shifts. Screening for novel regulators of macrophage activation, we found nonprotein kinases of glucose metabolism among the most enriched classes of candidate immune modulators. We find that one of these, the carbohydrate kinase-like protein CARKL, is rapidly downregulated in vitro and in vivo upon LPS stimulation in both mice and humans. Interestingly, CARKL catalyzes an orphan reaction in the pentose phosphate pathway, refocusing cellular metabolism to a high-redox state upon physiological or artificial downregulation. We find that CARKL-dependent metabolic reprogramming is required for proper M1- and M2-like macrophage polarization and uncover a rate-limiting requirement for appropriate glucose flux in macrophage polarization.


Figure S1
Figure S1. Kinase Screen in Macrophages and Activation Induced Metabolism (A) RAW264.7 cells transfected with a human ORF kinase collection were stimulated with LPS. TNF secretion of stimulated macrophages was analyzed by ELISA.
Twenty-one kinases exceeded the screen cut-off of 4 standard deviations (~30% change in TNF production) to determine novel candidate immuno-regulatory kinases. Interestingly, substantial enrichment of non-protein kinases over protein kinases was observed in both the activating and suppressive pools of candidate genes.
(B) To gain deeper insight into this observation we performed a gene-ontology based pathway analysis (IPA, Ingenuity Systems) in two contexts. In keeping with the inflammatory nature of the screen the top enrichment scores within the global category Diseases and Disorders included "organismal injury and abnormalities", "genetic disorders" and "inflammatory response" (Table S2). Analysis under Cellular and Molecular Function, interestingly, revealed high scores for genes involved in "molecular transport" and pathways of cell signaling, and notably, carbohydrate and lipid metabolism (lower chart, Table S3). Color intensities of pie-charts correspond to enrichment factor which describes the order to robustness of enrichment.
(D) By comparing S7P isotope-distributions a decreased m+1 S7P and an increased m+2 S7P fraction were observed. Increased PPP-flux directly forms m+2 S7P but the origin of m+1 S7P remains elusive. (insert) S7P showed relatively high incorporation rates (compare to Figure 1H) but no significant increase in total flux one hour after LPS activation.
(E) PPP activity (by NADPH formation) contributes to reduction of oxidized redoxcouples. We expected reduced GSH and NADH regeneration during M1-activation by blocking glucose-flux either by DHEA or by Oxamate. Both GSH and NADH (see Figure 1H) were increased during LPS-induced activation (100 ng/ml) accompanied by a moderated increase of the oxidized forms. Glutathione response was measured 4 hrs after stimulation. IL-4 activation operated differently. M2-like activation by IL-4 (10 ng/ml) was not followed by increased GSH formation or NADH formation. During LPS stimulation, CARKL overexpression ( Figure 5D-5F) or direct PPP blocking by DHEA in BMDM, annulled the increase in reduced-factors and resulted in a dramatic redox-shift towards the oxidized state. This clearly indicated the increased turnover of redox-factors during LPS activation in both primary and RAW264.7 macrophages and displayed increased PPP activity as prerequisite to sustain consumption. Thereby we show that redox-regulation is distinctly regulated for either polarization state, correlates with PPP activation and is regulated by CARKL. Data represent mean ± SEM of two independent experiments; *p < 0.05, **p < 0.01. phosphates showed substantial decrease although only reduction of ADP was significant. GTP levels trended towards an increase, GDP was similarly regulated as ADP, and GMP remained unchanged. (B) NAD/NADH ratios were calculated by peak ratios for each individual experiment over time in fold change (0 hr = 1) and were statistically analyzed by paired t test. The substantial increase in NADH observed in (A) was associated with a rapid drop of the NAD/NADH ratio after macrophage stimulation. The metabolomic data represent the mean peak change in % (untreated cells labelled as 0 hr = 100 %) ± SEM of three independent experiments; to test for significant changes in response to LPS, every time point was analyzed against untreated control (0 hr) by Student's t test; *p < 0.05, **p < 0.01.
(C and D) As for RAW264.7 macrophages ( Figure 2D and 2E), we tested primary cells for the relevance of this metabolic reconfiguration during M1 polarization in the context of macrophage effector function. We used inhibitors to interfere with glucosemetabolism and measured cytokine production as a functional readout. Both treatments (DHEA and oxamate resulted in a substantial inhibition of M-1 cytokine production as already shown for RAW264.7 cell line. This finding confirmed metabolic-reprogramming (activation of glucose consumption by glycolysis and PPP) as crucial event for proper macrophage M1-polarization. Data represent mean ± SEM of three independent experiments; *p < 0.05, **p < 0.01. we observed a significant CARKL loss in peripheral blood nucleated cells (PBNCs) after in vivo stimulation with LPS for two hours (upper left). As a control we also measured TNF mRNA expression (upper right). In murine bone marrow derived macrophages treated with LPS (100 ng/ml) we observed a very similar and significant down-regulation of CARKL mRNA as seen in the RAW264.7 cell line ( Figure 3B). To show whether cultured human cells show CARKL regulation comparable to murine cells, we also incubated primary human monocytes with LPS (100 ng/ml) and measured CARKL expression. We observed again a significant loss of CARKL transcript, matching our findings in murine cells. Data represent means ± SEM; *p < 0.05, **p < 0.01, ***p < 0.001.
(B) 1 H/ 13 C HSQC spectrum of purified reaction product generated by CARKL ( 31 P-NMR is shown in inset). Assignments are given for the major -furanose form, signals labeled with x correspond to residual HEPES buffer. Milligram amounts of phosphorylated Sedoheptulose were subjected it to 31 P-, 1 H-, and 13 C-NMR analysis.
The assignment of C-7 as the phosphorylation site was deduced from the low-field shifted 13 C-signals of C-7 ( 66.67 and 66.62) and the heteronuclear correlation of the geminal H-7 protons to a single 31 P NMR signal at 1.34, whereas both geminal protons at C-1 (identified via their HMBC-correlation to the anomeric carbon C-2) were observed at chemical shifts similar to Sedoheptulose. Furthermore, NMR data are in full agreement with recently published data of S-7P generated by a transketolase-catalyzed reaction (Charmantray et al., 2009).
(C) We also determined the Michaelis constant K m for CARKL protein. K m values were experimentally defined by incubation of recombinant CARKL with various doses of respective substrates. We could ascertain a K m of 134 ± 9 µM for sedoheptulose (upper graph) and for ATP a K m of 180 ± 8 µM (lower graph) using an ADP accumulation assay.
(D) We evaluated CARKL protein distribution and co-localization in RAW264.7 cells stably expressing CARKL_eGFP in very low quantities. We have shown that CARKL co-localize with G6PD ( Figure 3F). As many metabolic enzymes, including G6PD, CARKL co-localized with -tublin. Cellular distribution of CARKL could be disrupted by nocodazol (20 µM) treatment for 30 min, indicating that CARKL was attached to microtubule filaments. Scale bar equals 5 µm.
(E) We generated a structural 3D homology model of CARKL to gain detailed insight into its mechanistic action. Immersed CARKL 3D model in an artificial water bath of   Figure 4B and 6C. Data represent mean % ± SEM of three independent experiments and one sample t-test was used to calculate for significant changes by CARKL perturbation; *p < 0.05.

(B) We present Oxygen Consumption Rates (OCR) and Extracellular Acidification
Rates (ECAR) as metabolic-measure to assess changes in the cellular bioenergeticprofile (see also Figure 6D). By CARKL overexpression Oxygen Consumption Rate (OCR) dropped whereas Extracellular Acidification Rate (ECAR) was not significantly changed. In miCARKL cells we observed also a decrease in OCR but linked with an increase in ECAR, indicating that upon CARKL loss, cells re-route their glucose flux towards glycolysis. To address possible changes in metabolic function (mitochondrial respiration, non-mitochondrial respiration, ATP turnover, H + leak and the respiratory capacity) we performed an analysis of OCR after sequential injections of oligomycin (0.8 µg/ml), FCCP (0.4 µM) and rotenone (1 µM) (Nicholls et al., 2010). The pCARKL cell line (upper graph, blue bars) responded to hyperpolarization (oligomycin) and subsequent un-coupling (FCCP) as control cells (black bars). Upon inhibition of mitochondrial respiration (by additional application of rotenone), CARKL overexpression revealed reduced non-mitochondrial (rotenone-resistant) respiration.
Plasma membrane based oxygen-consumption is known to account for up to 80% of the entire cellular respiration in certain cell types (Herst and Berridge, 2007). Several oxidases, including NOX isofroms, were identified as part of a respiratory system located at the plasma-membrane dependent on reducing factors produced by the PPP and glycolysis (Piccoli et al., 2005). This revealed a possible link between CARKL and superoxide (O 2

•-
) formation (see below). An apparent reduction of PPP flux and thereby less potential to reduce oxygen might explain the decrease in nonmitochondrial respiration observed upon CARKL overexpression. In contrast to CARKL overexpression, loss of CARKL caused reduced mitochondrial respiratory capacity suggested by lower FCCP-induced OCR (lower graph, white bars). Further addition of rotenone resulted in the very same rotenone-resistant OCR as observed in control cells (black bars). Thereby, we identified a key difference in regulation of oxygen consumption by either enhanced or reduced CARKL levels. To conclude, reduced CARKL induced ECAR and reduced mitochondrial respiration whereas overexpression blocked non-mitochondrial respiration. Data represent mean % change ± SEM of three independent experiments; *p < 0.05, **p < 0.01.

•-
production. The resulting nitroxyl radical is resistant to reduction by Vitamin C and thiols. The half-life time of nitroxyl radical in biological environment is about 4 hrs (Fink and Dikalov, 2002). A typical ESR spectrum of oxidized CMH is presented below. To ensure that the increase in O 2 •production during macrophage activation is an intracellular event, we tested the cellular O 2 •response in the presence of extracellular superoxide dismutase (SOD). Increase in O 2 •production by LPS was insensitive to extracellular SOD indicating specificity for the intracellular detection.
(G) The total O 2 •production of macrophages before and after activation with LPS.
Control cells (pCtrl) or cells overexpressing either wild-type CARKL (pCARKL) or the catalytic inactive form W125D (pCARKL W125D) were stimulated for 2 hrs with 100 ng/ml LPS and then analyzed by ESR for O 2 •production. In pCtrl cells we observed increased O 2 •production after LPS activation. This was blocked in pCARKL cells.
Overexpression of the catalytic-inactive kinase (CARKL_W125D) showed same increase in O 2 •as control cell line. This finding validated our hypothesis that preserving CARKL-derived-S7P formation during LPS-polarization resulted in a block of intracellular O 2 •formation. This finding directly confirmed the association of CARKL's kinase function (which regulates PPP-flux) with O 2 •production. Data represent means ± SEM of three to four independent experiments; ns = not significant, **p < 0.01.

Figure S5. Metabolomic-Time-Course and Redox-Adaptation in pCARKL Cells
In addition to intermediate metabolites of glucose metabolism depicted in Figure  CARKL up-regulation resulted in higher basal GSH levels but also in increased GSSG levels. GSSG did not further increase upon IL-4 activation. Of note, IL-4 resulted in up-regulation of CARKL whereas LPS activation in CARKL loss. Data represents means ± SEM; ns = not significant, *p < 0.05, **p < 0.01, ***p < 0.001. This artificial metabolic-reprogramming was sufficient to induce IL-6 in resting primary macrophages but had no effect on TNF-α expression (bar graphs). In RAW264.7 cells, enforcing metabolic-reprogramming by CARKL knock-down was sufficient to induce TNFα (Figure 6G and 6I).
(B) In Figure 6 we showed that LPS-induced cytokine secretion is significantly affected in pCARKL (blocked) and miCARKL (enhanced) cells. For causality testing, we transiently overexpressed transaldolase1 (TALDO1) in pCARKL cells but that did not rescue inhibition of those cytokines.
(C) Substitution of glucose (4.5g/L) with galactose (4.5g/L) as the primary carbon source partly rescued TNF-α and IL-6 production in pCARKL cells. This directly implicated metabolic substrate flux as the primary determinant of CARKL's immunomodulatory effects. This was further demonstrated by comparison of cells overexpressing catalytic-inactive or catalytic-active CARKL ( Figure 6A).
(E) We tested miCARKL cells for IL-10 secretion before and after LPS-activation (100 ng/ml). In the resting state, we did not detect any IL-10. However, LPS-induced IL-10 secretion was enhanced in miCARKL cells 24 hrs after activation. CARKL loss sensitized macrophage M1 polarization not only regarding the pro-inflammatory cytokines TNFα and IL-6, but also affects the late-phase anti-inflammatory cytokine IL-10.
(G) We tested if pharmacologic activation of glucose consumption, using metformin or rotenone, would alter M2-like polarization by IL-4. Indeed, activation of glucose consumption during IL-4 stimulation resulted in an ablation of mannose receptor 1 (Mrc1) expression, an important marker of M2 polarization. Data in (G) represent mean ± SEM of two independent experiments; *p < 0.05, **p < 0.01, ***p < 0.001.
Further, we observed increased Mrc-1 expression in pCARKL cells and reduced levels in miCARKL cells (Figure 6M and 6J). These data based on Mrc-1 expression as readout and metformin or rotenone as tools suggest that elevated glycolysis is disruptive to M2 polarization in primary macrophages.

Figure S7. CARKL Is a Metabolic Kinase that Integrates Glycolysis and PPP
Simplified schematic illustration of intracellular carbon flux originating from glucose breakdown (indicated by arrows). Inter-conversions of the glycolysis/PPP carbohydrate-phosphate intermediates dihydroxyacetone phosphate (DHAP), G3P, S7P, erythrose-4P, F6P, F-1-6bp and sedoheptulose-1-7-bisphosphate (S1-7bp) are necessary to distribute glucose flux appropriately towards respiration (for energy) and anabolic reactions (nucleotide synthesis and amino acid synthesis) while providing sufficient redox potential to drive numerous cellular processes. Interestingly, in addition to our report on CARKL, a novel sedhoheptulose-1-7-bisphosphatase, which forms S7P from S1-7bp, was very recently reported as a crucial enzyme in yeast ribosome biogenesis with obvious consequences (Clasquin et al., 2011). One outstanding question which remains elusive for the field is how free sedoheptulose is actually formed.
Phosphorylation events (indicated by a red star) in glucose metabolism are rare and primarily used to direct flux orientation by introducing thermodynamically irreversible reactions. In glycolysis this is executed by HK driven phosphorylation of glucose and PFK catalyzed fructose-bisphosphate formation (both enzymes promote glucose consumption and in accordance to our kinase screen enhance also TNF production). CARKL is the first reported kinase to share a similar role located at the interface of glycolysis and the PPPthe non-oxidative arm of PPP. An important and still partly unresolved issue is the interdependence of CARKL, transketolase and transaldolase in carbon-scrambling events to direct glycolytic and PPP flux.
Knockdown of CARKL increased intracellular G3P, X5P and R5P steady-state levels, in agreement the converse findings in pCARKL overexpressors ( Figure 6C). In addition, S7P levels were significantly reduced in miCARKL cells whereas the substrate sedoheptulose remained unaffected. Together, these findings fit with the idea that CARKL directly controls flux through the PPP and glycolysis through a simple mass-action process -the constant S7P-feed.
Our data clearly show that even moderate rerouting of glycolytic intermediates towards or away from the PPP is sufficient to skew cell fate of RAW264.7 and primary macrophages. One argument for why enhanced glycolytic/PPP flux could be critical for M1-like polarization is the requirement of NADPH. The oxidative arm of the PPP is a major generator of NADPH, and we demonstrated a dramatic drop in X5P and R5P metabolite levels following LPS stimulation in RAW264.7 cells (which may reflect enhanced flux through the PPP as seen for flux-analysis in BMDM, see below). Thus, CARKL may block or slow NADPH production through a mass-action process, through the accumulation of S7P. This is supported by the accumulation of X5P and R5P in LPS activated CARKL over-expressing cells (Figure 5C). Under these conditions the NAD/NADH ratio increases 10-fold, presumably starving the cell of functionality. The same is true for GSH/GSSG, another redox-couple linked to PPP activity. By CARKL down-regulation we examined a M1-like state in metabolicparameters (ECAR/OCR, NAD/NADH) as well as in cytokine production. This supports our interpretation of simple mass-action processes regulated by CARKL's S7P contribution to the non-oxidative arm of PPP. During M1 activation loss of CARKL-derived S7P may drive a metabolic-imbalance to enable glycolytic intermediates to fuel PPP. In addition to redox-tuning, this activated PPP generates plenty of C5 and C6 bodies which are also likely demanded for proper M1-activation or for replenishing the carbon-cycle.
Taking a detailed snap-shot of intracellular glucose-flux during LPS-induced activation of bone marrow derived macrophages clearly indicated that M1-like activation increases glycolysis and PPP flux (Figure 1H and 1I). We used dynamicmetabolic-flux measurements taking advantage of asymmetrically labeled 13 C-1-2glucose to allow monitoring not only of pathway flux, but also of origin of the labeled metabolites and thus flux-directionality. To minimize noise from potential carbonreshuffling under these conditions we used short labeling periods (10min). Using this setup we now directly show that M1-like activated primary macrophages increase glycolytic flux and route a substantial portion into the PPP as indicated by the doubly labeled X5P/R5P (see insert). In our flux analysis we observed high labeling rates for glycolysis/PPP-but very low for TCA-intermediates due to short labeling times. Of note, monitoring IL-4 activation revealed relatively minimal metabolic reprogramming, identifying a key difference between classical and alternative activation modes.

Supplemental Experimental Procedures Kinase Screen
The human kinase cDNA library was previously generated (Park et al., 2005) (Dalpke et al., 2001). All other primers used are listed in Supplementary Table 5.

Sedoheptulose Isolation from Sedum Spec.
Sehoheptulose was isolated according to a modified protocol of Schmidt et al (Schmidt et al., 1998). Briefly, Leaves of Sedum Spec. were grinded and mixed with an equal volume of water. Crude leave mix was pressed and the liquid passed through a 0.45 µm filter. Pre-cleared extract was incubated for 10 min at 37 °C with activated carbon. After removal of carbon the extract was concentrated by vacuum centrifugation. The concentrate was deproteinized by mixing with 50 °C pre-heated absolute EtOH. The resulting solution was cleared by centrifugation and again concentrated by vacuum centrifugation. For further removal of contaminants the extracts were passed over a Dowex AG1X8 (HCO 3 form) column and concentrated.
The final Sedoheptulose preparation was ~90% pure as measured by NMR analysis (data not shown).

Purification and Characterization of Sedoheptulose-7P
For preparative generation of S7P we incubated 10 mM sedoheptulose with 8 µg/ml recombinant CARKL in a kinase reaction buffer pH 7.6 containing 25 mM HEPES, 20 mM KCl, 10 mM MgCl 2 and 10 mM ATP overnight at 30°C. The reaction mixture was applied on a Bio-Gel P2-column (Bio-Rad; 40cm length, 1.6cm in diameter), flushed with water (LiChrosolv Merck) and the flow-through was fractionated in 0.5 ml intervals. Each fraction was tested for the presence of S7P by thin layer chromatography in junction with anisaldehyde/H 2 SO 4 stain. S7P containing fractions were pooled and lyophilized for further NMR analysis.

Nuclear Magnetic Resonance (NMR)
NMR spectra were recorded at 297 K on a Bruker DPX 400 instrument at 400.13 MHz for 1 H, 100.62 MHz for 13 C and 161.97 MHz for 31 P using a 5 mm broad band probe with z-gradients. The sample contained freeze dried material dissolved in 600 l of D 2 O in a 5 mm NMR tube. The ppm scales were calibrated to 2,2-dimethyl-2silapentane-5-sulfonic acid for 1 H (0.00 ppm), external 1,4-dioxane for 13 C (67.40 ppm) and H 3 PO 4 for 31 P (0.00 ppm). NMR spectra were recorded using Bruker standard homo-nuclear pulse programs, such as COSY and mlevph. For heteronuclear experiments, Bruker standard pulse programs were used, such as HSQC for one bond 1 H/ 13 C and 1 H/ 31 P correlations and HMBC for multiple bond proton-carbon correlations. All homo-nuclear and hetero-nuclear spectra were recorded with 1k x 1k data points and zero filled in both dimensions.

3D-Modelling and Docking Experiments of CARKL
The model of CARKL was built based on the 3D structure of Xylulose Kinase (PDB code: 2ITM) by using MODWEB for homology and comparative modeling of protein three-dimensional structures (Eswar et al., 2003;Pieper et al., 2009). The generated model was further optimized and validated by employing a Molecular Dynamics simulation using Gromacs (Lindahl et al., 2001) by applying the following procedure: We immersed the generated model into an artificial water bath of 120 Å side length allowing for a minimum distance of 20 Å (Omasits et al., 2008) between box boundary and Sedoheptulose and applied periodic boundary conditions.
Subsequently, we performed an energy minimization of the system using a steepest decent method as implemented in Gromacs and then increased the system temperature up to 310 °K. Finally, we carried out a Molecular Dynamics simulation for a real-time of 25 ns and performed the RMSD calculations using the built-in analyses tools of Gromacs ( Figure S3E) or UCSF Chimera (Pettersen et al., 2004).

Silver Stain
Recombinant CARKL protein was separated on 4-12% polyacrylamide gels (Invitrogen) followed by over night fixation in 50% MeOH / 10% acetic acid. Gel were washed two times for 10min in 50% MeOH and subsequently sensitized with a incubation in 0.02% Sodium thiosulphate for 30 s and two times shortly rinsed with H 2 O. Staining was performed in the dark for 20min with a 0.1% silver nitrate solution which was freshly prepared. After a short wash with H 2 O gels were developed in a 3% sodium carbonate solution containing 0.05% formaldehyde. Reaction was stopped by incubation with 1% acetic acid.

Cloning and Generation of Stable Cell Lines
To generate a construct for overexpression of CARKL in mammalian cells we cloned a sequence verified murine CARKL cDNA (clone MMM1013 OpenBiosystems) lacking 5' and 3' UTRs into pcDNA6 (Invitrogen). Transfection of RAW264.7 cell with empty pcDNA6 or pcDNA6_CARKL was achieved by Superfect reagent (Qiagen).

Confocal Laser Scanning Microscopy
Stable CARKL_eGFP macrophages were cultured in tissue culture treated glass slides (BD Falcon). Briefly, for immunofluorescence microscopy, cells were washed twice in PBS and exposed to pre-chilled methanol at -20 °C for 45 seconds. Methanol was removed quickly and the coverslips were washed three times with PBS. Fixed cells were blocked overnight at 4 °C or 2 hrs at RT with blocking solution (2% BSA in PBS). Incubation with rabbit polyclonal anti-G6PD (ab993, AbCam), -tubulin and ß-Actin (T5168 and A5316 Sigma-Aldrich) was performed at RT for 2 hrs followed by four washing steps with PBS 0.05% Tween. Alexa-594 conjugated goat anti-rabbit or anti-mouse antibody (Molecular Probes) was added for 2 hrs at RT in the dark. Nuclei were visualized with DAPI (Sigma-Aldrich). Slides were mounted with moviol and dried overnight at RT in the dark. Specimens were then examined using a Zeiss LSM5 laser scanning Microscope (Carl Zeiss Optics).

Electron Spin Resonance
We employed a CMH (1-Hydroxy-2,2,5,5-tetramethyl-pyrrolidine-3-carboxylic acid methyl ester) spin probe (Noxygen) to measure intracellular and absolute superoxide generation rates of macrophages after activation ( Figure S4F). Cells (4x 10 6 /ml) were incubated with or without LPS (100 ng/ml) in ESR-Krebs HEPES Buffer (Noxygen). After two hours of incubation DTPA (0.2 mM) and CMH (2 mM) were added to cells. Twenty microliters of the incubated cell suspension were aspirated into a Teflon tube (0.9 mm ID) and transferred to a flexline dielectric resonator ER4118X-MD5 (Bruker). Electron spin resonance measurements were started 2 min after mixing at room temperature using a Bruker EMX spectrometer with the following parameters: microwave frequency 9.685 GHz, modulation frequency 100 kHz, modulation amplitude 1 G, time constant 0.082 sec, center field 3446 G, scan rate 71 G/min, sweep 100 G, sweep time 84 s, receiver gain 2 10 4 . Always five consecutive scans were recorded and from the increase in the peak-to-peak intensity of the middle line from the resulting nitroxyl radical CM the CHM oxidation rates were calculated. Absolute CM concentrations were obtained by comparison with a calibration curve constructed from different CP (3-carboxy-proxyl) concentrations.

Metabolomic Analysis
Cells were grown in 150 mm dishes and harvested after three PBS washes by centrifugation. The pellet was then frozen in liquid nitrogen and thawed in ice water to support cell lysis. Extraction solvent, which consisted of 100 µl of ice-cold 80/20 methanol/water containing 10 µM 13 C 6 -citric acid and 13 C 2 -succinic acid as internal standards, was added to the cell pellet, and the pellet was disrupted by probe sonication using a Branson Sonifier 450 (Danbury, CT) set at 20% duty cycle and 40% output power. The sample was sonicated for 20 seconds, followed by a 30 second rest period and then 20 additional seconds of sonication. The sample was then centrifuged at 14000 g at 4°C for 10 min, and the supernatant was transferred to an autosampler vial for analysis by LC-MS.
Samples prepared as described above were separated via hydrophilic interaction liquid chromatography (HILIC) and detected online using tandem mass spectrometry (MS/MS). The HILIC separation was carried out using an Agilent 1200 Rapid Resolution LC system (Agilent, Santa Clara, CA) and a Phenomenex Luna NH 2 (3 µm, 150 mm x 2.1 mm i.d.) column (Phenomenex, Torrance, CA). Mobile phase A was acetonitrile, and mobile phase B was 5 mM ammonium acetate in water, adjusted to pH 9.9 with ammonium hydroxide solution. The gradient was 60%/40% (A/B) to 100% B over 18 min, followed by a 18 sec hold at 100% B. The mobile phase was returned to 60%/40% (A/B) over 0.2 min and was held for 17.5 min for reequilibration. The flow rate was 0.25 ml/min and the column temperature was held at 25 °C. 8 µl of sample were injected for each analysis.
The LC system was coupled on-line to an Agilent 6410 Triple Quadrupole mass spectrometer with electrospray ionization (ESI) source. The spray voltage was set to -4.0 kV in negative ion mode. The desolvation gas flow rate was 10 L/min, the desolvation gas temperature was 350 °C, and the nebulizer pressure was 40 psi. The LC-MS system was controlled using the Agilent MassHunter Data Acquisition software. Compounds were detected using multiple reactions monitoring (MRM) mode with a 50 ms dwell time per transition. Prior to performing LC-MS analyses, the MS/MS transitions were optimized for detection of metabolite intermediates by flow injection analysis of authentic standard compounds.

Non-Stationary Isotopic Flux Analysis
Cells were grown in 100 mm dishes and at day of experiment stimulated for indicated times. After cell stimulation normal growth media (DMEM high glucose) was removed and replaced with media containing 100% 13 C-1-2-glucose instead of unlabeled glucose. Primary macrophages were placed back to incubator for 10 min to reach non-stationary labeling. For quenching, we exactly timed media removal, ddH 2 O wash and snap-freezing by pouring liquid nitrogen into the cell plate. Dishes were stored at -80 °C for one week. Carbon-13 mass isotopomer analysis of glycolysis, pentose phosphate pathway, and nucleotide metabolites in cultured cells was carried out using liquid chromatography-mass spectrometry (LC-MS) according to the protocol of (Lorenz et al., 2011). Briefly, metabolites were extracted by adding 1.5 mL of cold 8:1:1 methanol:chloroform:water to the quenched (frozen) cell culture plates and scraping with a cell scraper to release the cells. Cell debris and precipitated proteins were pelleted by centrifugation and the supernatant was directly analyzed by mixed-mode anion exchangehydrophilic interaction chromatography using a Phenomenex Luna NH2 3µ column, 15 cm x 1 mm ID. Mobile phase A for the separation was acetonitrile and mobile phase B was 5mM ammonium acetate in water (adjusted to pH 9.9 with ammonium hydroxide). The gradient consisted of a 15 min linear ramp from 15% to 100% B, followed by a 2-min hold at 100% B and a subsequent 17-min re-equilibration period at 15% B. The sample injection volume was 20 µL and the flow rate was 0.07 mL/min. Detection was performed by electrospray ionization mass spectrometry in negative ion mode using an Agilent 6220 time-of-flight mass spectrometer. MS parameters were as follows: gas temp 350 °C, drying gas 10 L/min, nebulizer 20 psig, capillary voltage 3500V, scan range 50-1200 m/z. Metabolites were identified in the LC-MS data by comparing accurate mass and retention time of peaks with those of authentic standards. Relative quantitation of each metabolite and all of its isotopes was performed by measurement of peak area from extracted ion chromatograms. Mass isotopomer distributions were calculated by dividing the peak area of each isotope by the sum of the peak area for all detected isotopes.