TY - JOUR
AU - Hua,, Xiangdong
AB - Abstract PTEN loss-of-function mutations frequently occur in gliomas and lead to poor overall survival. PTEN deficiency induces metabolic reprogramming, which may provide therapeutic targets. PTEN is known to impact the Warburg effect and glutaminolysis. To uncover essential glutamine-related metabolic changes specific in PTEN-deficient cells and thus provide potential therapeutic targets, we performed capillary electrophoresis–mass spectrometry-based metabolomics analysis and metabolic flux analysis under different glutamine culture conditions and PTEN alteration status. Glu, Asn, Gly, Ala, and 1-methylnicotinamide were decreased in PTEN-deficient cells under normal culture conditions. Meanwhile, under Gln-deprived culture conditions, Glu, citrate, and UTP synthesis were reduced and acetyl carnitine was increased in PTEN-deficient cells. The reliance on Gln was increased for metabolic intermediates synthesis but decreased for energy production in PTEN-deficient cells. However, the reliance on Gln for UTP synthesis cannot be targeted due to anaplerotic synthesis of UTP from other sources. How to target these metabolic addictions needs further research. metabolomics, metabolic flux analysis, CE-MS, PTEN, Gln addiction Introduction Loss-of-function mutations in PTEN frequently occur in cancers [1], especially in gliomas [2]. About 75% of gliomas have monoallelic loss of PTEN [3], and glioma patients with PTEN mutation usually have shorter survival time [4]. How to target PTEN-deficient cancer cells for therapy has been seriously investigated [1,5,6]. Activation of oncogenes and loss function of suppressor genes are main drivers for the metabolic reprogramming [7]. Targeting metabolism vulnerabilities has been shown as an effective way for precision cancer therapy, which generates less side effects [8,9]. PTEN influences cell metabolism by multiple metabolism pathways [10–12]. Therefore, metabolic vulnerabilities induced by PTEN deficiency have been extensively studied. Mathur et al. [13] found that PTEN-deficient cells were sensitive to inhibition of dihydroorotate dehydrogenase (DHODH) due to reliance on de novo pyrimidine synthesis, thus uncovering the therapeutic potential of DHODH inhibitor. However, PTEN induces huge metabolic changes, and the function of PTEN varies with cancer microenvironment. Consequently, it is necessary to find PTEN-relevant metabolic pathways that are essential for cell survival in specific cancer microenvironment. The Warburg effect, glutaminolysis, as well as glucose and glutamine metabolism play key roles in cancer metabolism [14–16]. PTEN upregulation negatively impacts the Warburg effect and glutaminolysis [17]. However, these pathways are not directly targetable. Therefore, a further investigation on how PTEN regulates the metabolic network involved in Gln and glucose addiction will provide clues of metabolic pathways suitable for targeted cancer therapy. Due to its high coverage, precision, and sensitivity, chromatography coupled with mass spectrometry (MS) has become a robust tool for metabolomics analysis [18]. Capillary electrophoresis–mass spectrometry (CE-MS) has been applied to polar metabolites analysis [19,20]. However, static metabolomics analysis cannot elucidate the intracellular dynamic metabolic flux. Untargeted metabolomics analysis with stable isotope labeling can show the network flux of the labeled precursor. Thus, metabolic flux analysis (MFA) has been widely used for uncovering cancer metabolic vulnerabilities and therapeutic targets [21,22]. In the present study, to elucidate Gln-related metabolic vulnerabilities induced by PTEN deficiency, we established both PTEN-deficient and PTEN-overexpressing cells. Then the cells were cultured under Gln-deprived culture conditions to explore the metabolic changes by both CE-MS-based metabolomics analysis and [U-13C6]-glucose labeling MFA. We found that PTEN-deficient cells depend more on Gln for TCA cycle and UTP synthesis, but less on Gln for energy production, which provide possible clinical targets for precision therapy of PTEN-deficient patients. Materials and Methods Materials and chemicals Ultrapure water was made from Millipore Milli-Q system (Bedford, USA). HPLC grade methanol and acetonitrile were bought from Merck (Darmstadt, Germany). Chloroform was bought from Duksan (Seoul, Korea). Ammonium hydroxide, formic acid, and ammonium acetate were bought from Sigma (St Louis, USA). 13C6-glucose was purchased from Cambridge Isotope Laboratories (Andover, USA). Internal standards IS1 (L-methionine sulfone, D-camphor-10-sulfonic acid sodium salt) and IS3 (3-aminopyrrolidine dihydrochloride, N, N-diethyl-2-phenylacetamide, trimesic acid, and disodium 3-hydroxynaphthalene-2, 7-disulfonate) for CE-MS-based metabolomics analysis were bought from Human Metabolome Technologies (HMT) (Tsuruoka, Japan). Cell culture and transfection and validation The human glioblastoma cell lines LN-229 and U87 were purchased from the American Type Culture Collection (ATCC; Manassas, USA). LN-229 and U87 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM; GIBCO, Carlsbad, USA) supplemented with 10% fetal bovine serum (FBS). All cells were cultured in cell-culture flasks or Petri dishes in a humidified incubator at 37°C in an atmosphere of 5% CO2. shRNA with pLKO.1 vector for PTEN silencing were bought from Sigma. The sequences of shControl, shPTEN1, and shPTEN2 were as follows: 5′-CCGGCAACAAGATGAAGAGCACCAACTCGAGTTGGTGCTCTTCATCTTGTTGTTTTT-3′ (SHC002), 5′-CCGGAGGCGCTATGTGTATTATTATCTCGAGATAATAATACACATAGCGCCTTTTTT-3′ (TRCN0000002745), and 5′-CCGGACATTATGACACCGCCAAATTCTCGAGAATTTGGCGGTGTCATAATGTTTTTTG-3′ (TRCN0000355946), respectively. PTEN-overexpressing plasmid (HG10421-UT) was bought from Sino Biological (Beijing, China). LN-229 was transfected with PTEN shRNA using Lipofectamine 3000 (Life Technologies, Waltham, USA) for 6 h and selected with 0.5 μg/ml puromycin after transfection. U87 was transfected with the PTEN-overexpressing plasmid using lipofectamine 3000 (Life Technologies) lipofectamine 3000 (Life Technologies) and selected with 800 μg/ml hygromycin after transfection. CE-MS-based cell metabolomics Sample preparation Cells were used for metabolomics analysis after being grown to 80% confluence. Cells were washed with 10 ml of 5% mannitol in water for three times when the cells were harvested. Then they were quenched with liquid nitrogen immediately. After addition of 1 ml methanol with 1:200 (v/v) HMT CE-MS IS1 to each plate, the cells were scraped off and transferred to a 5-ml tube. After 30 s of vortexing, 1 ml chloroform was added to the tube and vortexed for another 30 s. Then 400 μl of water was added and vortexed for 60 s. The mixtures were placed on ice for 10 min and centrifuged at 15,000 g for 15 min at 4°C. Then, 450 μl of upper-layer solution for each sample was transferred to a filter (5 kDa cutoff; Millipore, Billerica, USA) and centrifuged at 12,000 g at 4°C until all the solution passed through the filter. The filtrate was dried and stored at −80°C. Data acquisition Before CE-MS analysis, the dried sample was dissolved in ultrapure water containing 50 μM IS3. Non-target metabolomics analyses were performed with the CE-TOF/MS system (Agilent, Santa Clara, USA) equipped with a CE-electrospray ionization-MS sprayer kit (G1607A; Agilent). The detailed parameters were the same as those described before [28]. Metabolomics data processing A database provided by Human Metabolome Technologies, Inc. (Tsuruoka, Japan), which contains 1000 metabolites with migration time and precision m/z, was used for metabolites qualitative analysis. L-methionine sulfone in IS1 and 3-aminopyrrolidine dihydrochloride, N, N-diethyl-2-phenylacetamide in IS3 were used for migration time correction in cation mode. D-camphor-10-sulfonic acid in IS1 and trimesic acid, disodium 3-hydroxynaphthalene-2, 7-disulfonate in IS3 were used for migration time correction in cation mode. The migration time of each metabolite was corrected with the real migration time of the metabolite, the three internal standards, and the theoretical migration time of the three internal standards by the software MethodMaker (HMT). The difference of the corrected and theoretical migration time of the metabolite was set at ±0.1 min. Mass tolerance was set at ±20 ppm. The Agilent Quantitative Analysis software was used for the qualitative analysis based on the above parameters and origin intensities of the metabolites were exported. Data normalization was performed by dividing each metabolite response with total metabolites area of each sample. Metabolic flux analysis Cell culture Cells were cultured in glucose-free DMEM medium supplemented with 10% dialyzed FBS (Gemini, Woodland, USA) and 25 mM 13C6-Glucose (Invitrogen, Carlsbad, USA) for glucose labeling MFA. Metabolomics data processing Precision m/z of each isotopologue were calculated based on (m/z)M + i = (m/z)M + 0 + 1.00335i (i means the number of 13C in isotopologue M + i, 1.00335 is the mass difference between 13C and 12C). All the isotopologues of each metabolite share the same migration time. Each isotopologue was treated as independent metabolite. Thus, the database provided by HMT was extended and contained all the isotopologues of the metabolites. The subsequent qualitative and quantitative analyses were the same as what was mentioned above, and the origin intensities of all the isotopologues were exported. Natural isotope peak correction and filter were performed with an in-house software ‘Stable Isotope-Assisted Metabolomics Analyzer’ (SIAM Analyzer) (Under preparing for publishing). Mass isotopomer distribution (MID) was also calculated with SIAM. Data normalization was performed by dividing each metabolite response with total metabolites area of each sample after the filter. Metabolic changes induced by PTEN deficiency (A) Heatmaps of significantly changed metabolites in LN-229 cells transfected with two independent PTEN shRNAs or in PTEN-transfected U87 cells. (B) Carbon transition map from glucose. Red and black balls mean carbon atoms derived from glucose and other sources respectively. MID of Ala (C), Gly (D), Asn (E), and Glu (F) in PTEN-silenced LN-229. Cells were labeled with 13C6-glucose for 24 h. Relative intensity was calculated by dividing normalized peak intensity by average normalized peak intensity of the control. **P < 0.01, and ****P < 0.0001; n = 4. Figure 1 Open in new tabDownload slide Figure 1 Open in new tabDownload slide Western blot analysis Cell lines were validated by western blot analysis. Protein extraction and western blot analysis were performed as described before [30]. Briefly, proteins were extracted using radioimmunoprecipitation assay buffer containing protease inhibitors (Sigma), separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and then transferred to polyvinylidene fluoride (PVDF) membranes. After being blocked, the membranes were incubated with corresponding primary antibodies and peroxidase-conjugated secondary antibodies successively. The bands were visualized with Chemiluminescence (Fusion FX5 820, Vilber, France). Primary antibodies against PTEN (11,000; Cell Signaling, Beverly, USA) and actin (11,000; Proteintech, Chicago, USA) were used. Statistical analysis Two-way ANOVA was performed with SPSS 20 (IBM, Armonk, USA), and the significance level was set at P < 0.05. Heatmaps were constructed with metaboanalyst (http://www.metaboanalyst.ca/) [29]. T-test for each metabolite was performed with GraphPad Prism 7 (GraphPad, San Diego, USA). Results CE-MS-based MFA of PTEN-deficient cells To elucidate the function of PTEN on metabolism, we silenced PTEN in PTEN-normal LN-229 cells and overexpressed PTEN in PTEN-deficient U87 cells (Supplementary Figure S1), and then performed CE-MS-based 13C6-glucose labeling MFA. There were 99 and 35 differential metabolites in U87 and LN-229 cells, respectively, compared with control cells, while 5 metabolites showed common changes. Notably, Glu was increased, while Asn, Gly, Ala, and 1-methylnicotinamide were decreased in the PTEN-deficient cells (Fig. 1A). The synthesis of four differential metabolites from glucose was shown in Fig. 1B. Ala M + 3, Gly M + 2, Glu M + 2, M + 3, M + 4, M + 5, Asn M + 2, M + 3, and M + 4 are synthesized from 13C6-glucose. Intracellular Ala was mainly synthesized from glucose (Ala M + 3) in all the three LN-229 cell lines (Fig. 1C), while little Gly was synthesized from glucose (Gly M + 2; Fig. 1D). PTEN deficiency decreased the contributions of glucose for Ala, Gly, and Glu synthesis (Fig. 1C–E), but did not affect the contribution of glucose for Asn synthesis (Fig. 1F). 1-Methylnicotinamide was not synthesized from glucose. However, even though glucose contributed little to Glu synthesis, the total amount of Glu was increased in PTEN-deficiency cells (Fig. 1E). These results indicated that Ala, Gly, and Asn are mainly synthesized from glucose, but Glu synthesis may have other synthetic sources in PTEN-deficiency cells. CE-MS-based MFA of PTEN-deficient cells under Gln-deprived culture conditions Since differential metabolites induced by PTEN deficiency were discovered, metabolic reliance in PTEN-deficient cells, which can provide potential targets, is of concern. To find the essential metabolic pathways related to Gln, we cultured the cell lines with different PTEN status under Gln-deprived culture conditions for 24 h. Cell viabilities under different culture conditions were detected (Supplementary Fig. S2). Cell growth was slightly decreased in U87 control cells and LN-229 shPTEN1 cells after Gln deprivation compared with normal culture conditions, and did not change in LN-229 control cells and shPTEN2 cells. All types of cells were almost doubled after 24 h of treatment. Then CE-MS-based metabolomics analyses and MFA were performed. As expected, intracellular Gln was significantly decreased in all cell lines, regardless of the PTEN status (Fig. 2A,B). Metabolic changes specific in PTEN-deficient cells after Gln restriction Gln changes in U87 cells with overexpression of PTEN (A) or LN-229 cells transfected with two independent PTEN shRNAs (B). Metabolic changes of U87 (C) or LN-229 (D) specific in PTEN-deficient cells under Gln-deprived culture conditions. The metabolic changes in two cell lines were calculated by two-way ANOVA. **P < 0.01; ns means no significant difference; n = 4. Figure 2 Open in new tabDownload slide Figure 2 Open in new tabDownload slide Furthermore, we analyzed the metabolic changes specific in PTEN-deficient cells under Gln-deprived culture conditions to find Gln-related therapeutic targets for PTEN-deficient cells. Metabolites, including Asn, Citrate, Glu, GDP-glucose, Ile, Val, acetyl carnitine (C2 CN), Phe, His, Tyr, FBP, UDP-glucose, and UTP, showed remarkable changes in both U87 and LN-229 cells (Fig. 2C,D). Essential amino acids Ile, His, Phe, Val, and Tyr, which are synthesized from Phe were increased under Gln-deprivation conditions, while the incremental trends were more significant in PTEN-deficient cells compared with PTEN-normal cells (Fig. 2C,D). Essential amino acids are very important for cellular signaling transduction and survival, and further mechanism needs to be explored in PTEN-mutated cells. PTEN-deficient cells are dependent more on Gln anaplerosis for TCA cycle Compared with PTEN-normal cells, citrate, which can represent TCA cycle flux, was not changed under normal culture condition in PTEN-deficient cells, but was decreased under Gln-deprived culture condition (Fig. 3A,B), indicating that PTEN-deficient cells were dependent more on Gln for maintaining TCA cycle. Furthermore, we investigated how Gln influences TCA cycle by analyzing the citrate flux with 13C6-glucose labeling MFA. Under Gln-deprived culture conditions, quantities of nearly all isotopologues (except M + 0 citrate isotopologue) of citrate were decreased in PTEN-deficient cells compared with normal cells, while the decreases of M + 5 and M + 6 citrate isotopologues were more obvious than others (Fig. 3B). Citrate isotopologues from M + 2 to M + 4 are derived from 13C6-glucose in the first cycle of TCA cycle, and isotopologues from M + 4 to M + 6 are synthesized from the second and latter cycle. We hypothesized that due to more reliance on Gln, PTEN-deficient cells consumed more intermediates in TCA cycle for other metabolites synthesis under Gln-deprived conditions, so the remaining intermediates would not circulate efficiently to produce M + 5 and M + 6 citrate isotopologues. Increased anaplerosis of Gln to TCA cycle in PTEN-deficient cells and the ratio of C2 CN to CN under different culture conditions (A) Relative intensity of citrate in U87 with different PTEN status and culture conditions. (B) MID of citrate in LN-229 with different PTEN status and culture conditions. (C) Relative intensity of Glu in U87 with different PTEN status and culture conditions. (D) MID of Glu in LN-229 with different PTEN status and culture conditions. (E) Ratio of C2 CN to CN in U87 under different culture conditions. (F) MID of C2 CN to CN ratio in LN-229 under different culture conditions. Data were expressed as the mean ± standard error of the mean (SEM) or as bar graphs with mean values. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns means no significant difference; n = 4. All assays were performed at least in triplicate. Figure 3 Open in new tabDownload slide Figure 3 Open in new tabDownload slide Reliance on Gln for UTP synthesis in PTEN-deficient cells Relative intensity of UTP in U87 cells (A) or LN-229 cells (B) with different PTEN and Gln conditions. (C) MID of UTP in LN-229 cells with different PTEN status under different conditions. Relative intensities of anaplerosis synthesis (D) or de novo synthesis (E) of UTP in LN-229 cells under different culture conditions. Relative intensities of anaplerosis and de novo synthesis of UTP were represented by relative intensity of M + 0 isotopologue and the M + 5 to M + 8 isotopologues, respectively. Data were expressed as the mean ± SEM or as bar graphs with mean values. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns means no significant difference; n = 4. All assays were performed at least in triplicate. Figure 4 Open in new tabDownload slide Figure 4 Open in new tabDownload slide Glu presented similar variation trends to that of citrate in all types of cells, and it was significantly decreased under Gln-deprived conditions (Fig. 3C,D). Meanwhile, the quantities of Glu were higher in PTEN-deficient cells compared with that in normal cells under normal culture conditions, while reverse trends were observed under Gln-deprived conditions (Fig. 3C,D). Glu M + 0 in PTEN-deficient cells was increased when compared with control cells under normal culture conditions, but not changed under Gln restriction (Fig. 3D). These results indicated that PTEN-deficiency might promote Glu synthesis from Gln. Taken together, PTEN-deficient cells were dependent more on Gln for TCA cycle flux and Glu synthesis, even under Gln-deprived conditions. PTEN-deficient cells are dependent more on glucose for energy production C2 CN can be produced from acetyl CoA, which is catalyzed by carnitine acetyltransferase (CrAT) when acetyl CoA production exceeds TCA cycle flux [23]. C2 CN storages excess acetyl CoA and transits to acetyl CoA when acetyl CoA is desired [24]. Here, C2 CN/CN was found to be increased in all cells under Gln-deprived conditions (Fig. 3E,F), suggesting that Gln deprivation induced inhibition on TCA cycle flux was more obvious than that on acetyl CoA production. Under Gln-deprived culture conditions, C2 CN/CN in PTEN-deficient cells was more significantly increased than PTEN-normal cells (Fig. 3E,F), which implied more remarkable imbalance between acetyl CoA production and TCA cycle flux. We further analyzed the distribution of 13C and 12C atom in the acetyl of C2 CN. No significant difference was observed under normal culture conditions between PTEN-deficient and PTEN-normal cells (Fig. 3F). However, under Gln-deprived conditions, both ratios of 12C C2 CN to C0 CN and 13C C2 CN to C0 CN were remarkably increased in PTEN-deficient cells compared with those in PTEN-normal cells (Fig. 3F), indicating that the increase of C2 CN to C0 CN ratio was largely due to the increased production of C2 CN from sources other than glucose, e.g. fatty acids. Considering the more obvious imbalance between TCA cycle flux and acetyl CoA production and the decrease of M + 2 citrate isotopologue in PTEN-deficient cells compared with PTEN-normal cells (Fig. 3B), the results indicated that under Gln-deprived conditions, the flux inhibition of TCA cycle was severer and the fatty acid oxidation might be more active in the PTEN-deficient cells than in the PTEN normal cells. UTP synthesis was inhibited in PTEN-deficient cells under Gln-deprived culture conditions Compared with PTEN-normal cells, UTP was respectively increased and decreased under normal and Gln-deprived culture conditions in PTEN-deficient cells (Fig. 4A,B). The carbons for de novo UTP synthesis were from one PRPP, one orotate, and one CO2, where both PRPP and orotate can be produced by glucose. Almost all the PRPP was produced by glucose, so M + 5, M + 6, M + 7, and M + 8 UTP isotopologues represent de novo synthesis, while M + 0 UTP isotopologue represent anaplerosis synthesis. As indicated by proportions of M + 0 UTP isotopologue, nearly 10% and 34% of the UTP was from anaplerosis synthesis under normal culture conditions and Gln-deprived culture conditions, respectively (Fig. 4C). Moreover, anaplerosis synthesis of UTP was increased under Gln-deprived culture condition and anaplerosis synthesis of UTP in PTEN-deficient cells was increased compared with PTEN-normal cells under both culture conditions (Fig. 4D). In addition, de novo synthesis of UTP (represented by the sum of M + 5, M + 6, M + 7, and M + 8 isotopologues) was increased slightly or even not changed under normal culture conditions, but was decreased significantly under Gln-deprived conditions in PTEN-deficient cells compared with PTEN-normal cells (Fig. 4E). This indicated that PTEN-deficient cells were dependent more on Gln for de novo synthesis of UTP. In conclusion, with increased anaplerosis synthesis of UTP, quantities of UTP were increased in both types of cells when Gln was deprived. Then, due to decreased de novo synthesis of UTP in PTEN-deficient cells, the increase of UTP in PTEN-deficient cells were less than that in PTEN-normal cells. Consequently, inhibition of de novo UTP synthesis could not decrease intracellular UTP. Furthermore, we explored how Gln deprivation affected de novo synthesis of UTP. M + 5, M + 6, M + 7, and M + 8 UTP isotopologues contained five 13C atoms from PRPP and one 13C atom from orotate. The proportion of M + 5 isotopologue was not changed and the proportions of M + 6, M + 7, and M + 8 isotopologues were decreased (Fig. 4C). This indicated that the lack of orotate rather than PRPP induced the decrease of de novo UTP synthesis. Discussion Differential metabolites can be functional but may not be targetable due to anaplerosis synthesis. In this study, a few differential metabolites were observed in PTEN-deficient cells under normal culture conditions. To further explore potential therapeutic targets, we investigated the function of PTEN on Gln-related metabolic pathways by Gln restriction and 13C6-glucose labeling MFA, and many differential metabolites were discovered. Specific reliance on Gln in PTEN-deficient cells was elucidated. Although Gln restriction is unpractical in cancer therapy, we found that UTP synthesis and energy production may be targetable. Consistent with the conclusion of a previous research that PTEN-deficient cells were sensitive to the inhibition of DHODH due to reliance on de novo pyrimidine synthesis from Gln [13], we found that PTEN-deficient cells were dependent more on Gln for orotate synthesis and the subsequent de novo UTP synthesis. However, our results indicated that due to the existence of anaplerosis synthesis of UTP, targeting only de novo pyrimidine synthesis may be not effective in specific cancer microenvironment. Microenvironment substantially regulates cancer cell metabolism [25]. So microenvironment should also be considered for UTP synthesis-targeted cancer therapy. PTEN-deficient cells were also dependent more on Gln for TCA cycle. C2 CN is positively correlated with acetyl CoA [26]. Under Gln-deprived culture conditions, PTEN-deficient cells were dependent more on glucose and other sources, but not Gln, for energy production, so the production of acetyl CoA exceeded the TCA cycle flux and resulted in C2 CN accumulation. Consequently, PTEN-deficient cells maintained a high energy level under Gln-deprived culture conditions. Energy supplementation is crucial for cell survival and provides potential therapeutic targets [27]. Intervention of energy production in PTEN-deficient cells would be meaningful. The metabolic synthesis reliance induced by PTEN deficiency may be taken as a therapeutic target, but further consideration of microenvironment is essential. However, PTEN deficiency can also promote energy production independent of Gln, which needs further research. Acknowledgement We would like to thank the members of the Dr Piao’s laboratory and Dr Hua for their helpful discussion. 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TI - PTEN-deficient cells prefer glutamine for metabolic synthesis
JF - Acta Biochimica et Biophysica Sinica
DO - 10.1093/abbs/gmz163
DA - 2020-03-18
UR - https://www.deepdyve.com/lp/oxford-university-press/pten-deficient-cells-prefer-glutamine-for-metabolic-synthesis-bFZFSy044p
SP - 251
VL - 52
IS - 3
DP - DeepDyve
ER -