Supplemental Figure Legends

Figure S1. Hierarchical clustering and principle component analysis (PCA) for RNAseq samples. A) Heat map showing hierarchical clustering of expression data for individual RNAseq samples, based on Pearson correlation with complete linkage clustering of all differentially expressed between the T-ALL cell lines. Clusters are marked by blue triangles. Scale bar represents log2 FPKM values. B) 3D scatter plot depicting the PCA of the eight independent RNAseq samples. The replicates for each cell line cluster closely together and SIL TAL cell lines cluster closer together than the ARR cell line.

Figure S2. enrichment analysis was performed for C8 and C11 of the hierarchical clustering of RNAseq data, as shown in Figure 1A. Terms are ordered based on Modified Fisher Extract P-value and shown as percentage of input genes (% genes).

Figure S3. levels and phosphorylation status of mTOR regulators (A) and mTOR effectors (B). Western blot analysis of 150µg cell extract. Treatment was DMSO (-,Ctrl) or 10nM rapamycin (+,Rap) for 24h. PonceauS staining was used to confirm equal loading. Each experiment was performed at least three times and representative results are shown. C-E) TSC1 expression is lost in ARR due to alternative splicing. C) UCSC genome browser screenshot showing the distribution of reads across TSC1 from a representative set of RNAseq tracks. D) Expression level for TSC1 gene and identified transcripts based on the RNA-seq data, presented as FPKM values. E) qPCR data showing relative TSC1 mRNA level using primer pairs recognising exon 18-19 and the 5’UTR. Data points are the mean of at least three independent samples measured in duplicate ± StDev.

Figure S4. T-ALL metabolite levels measured by nuclear magnetic resonance (NMR) spectrometry. A) Bar graphs showing the relative abundance of intracellular metabolite levels after culturing T-ALL cells for 24h. Two metabolites from each of the metabolic clusters as indicated in figure 4C are presented. Data are the average of at least three independent experimental measurements ± StDev. Only metabolites with significantly different levels between at least two of the cell lines are shown. B) Bar graphs showing relative metabolite levels from the T-ALL cells cultured for 24h in the presence of 10nM rapamycin or vehicle (DMSO). Data are the average of at least three independent experimental measurements ± StDev. Only metabolites with significantly different levels between the rapamycin and the control in all four cell lines are shown. Significance was based on the two-tailed t-test with p<0.05.

Figure S5. Glutamine deprivation induces apoptosis in T-ALL cell lines. Scatter plots show flow-cytometry Annexin V and propidium iodide staining by flow-cytometry of cells grown in RPMI media without glutamine but supplemented with 10% FCS. Gating was determined based on the staining of T-ALL cells grown in the RPMI media supplemented with 2mM glutamine. Cells were grown for the indicated number of days (D0-8) prior to staining and analyses. Similar was observed in three independent experiments and a representative experiment is shown.

Figure S6. Metabolite tracing experiments using [2,5-15 N] Glutamine and [3-13 C] Glutamine. T-ALL cell lines were grown in the presence of 2mM [2,5-15 N] Glutamine) (A) or [3-13 C] Glutamine) (B-D). A) Overlay of 1D 1H-NMR spectra showing the H β-alanine resonance after 0, 8 and 24h and schematic representations of [2,5-15 N] Glutamine and the observed [2-15 N] Alanine. 15 N are in red and shading indicates the observed 3J scalar couplings between the alanine Hβs and glutamine-derived 15 N. The X-axis shows the chemical shift relative to TMSP in ppm and the Y-axis indicates TSA scaled intensity. B-D) Resonances observed in 1H-13 C-HSQC for T-ALL cells grown in the presence of [3-13C] Glutamine for 24h. Resonances are marked by letters a-b. Schematics on the right show malate, proline and arginine with colour-coded atoms based on the substrate of their origin. Blue shaded lines indicate observed couplings. E) Quantification of the glutamine-derived aspartate and UDP. Bar graphs show 13 C signal intensity acquired from the cells grown in the presence of [3-13 C] Glutamine for 24h, relative to the signal acquired from the naturally occurring 13 C cells observed in the cell extracts grown without the label. Data are the average of at least three independent experimental measurements ± StDev. Figure S7. UCPH102 induced changes in metabolite uptake and release. Bar graph showing metabolite levels from the T-ALL cells cultured for 48h in the presence of 25µM UCPH102 or vehicle (DMSO) from four independent samples and relative to the media control. Data are the average ± StDev. Metabolites with significantly different levels between the UCPH102 and the control are indicated with (*). Significance was based on a two-tailed t-test with p<0.05.

Supplemental Results for profiling mTOR signalling in T-ALL

Our results imply restricted amino acid availability in all T-ALL cell lines and this would suggest reduced mTOR signalling. In order to gain better understanding of mTOR signalling in the T-ALL cell lines, we assayed the endogenous levels and phosphorylation status of constituting the PI3K-AKT-mTOR signalling cascade under normal growth conditions and in rapamycin treated cells. Binding of growth factors to G-protein coupled receptors results in PI3K activation and generation of PI3P that further activates PDK1 to phosphorylate itself (S241) and AKT1 (T308) [1-3]. Opposing this is the phosphatase PTEN, which dephosphorylates PI3P and inhibits AKT1 signalling [4-6]. Western blot analyses revealed that T-ALL cells had active PDK-1 (p-PDK1 S241 ), only CCRF-CEM, which harbours a PTEN deletion, contained active AKT1 (p-AKT1 T308 ) (Figure S2A) [7]. In CCRF-CEM, AKT1 was additionally phosphorylated at the mTORC1 target site S473 and this activating mark was absent in the rapamycin treated cells, showing that mTOR has intact kinase activity in this cell line (Figure S2A) [8, 9]. The presence of inactive AKT1 in ARR, DU.528 and HSB2 and constitutively active AKT1 in CCRF-CEM cells implies that mTOR signalling is uncoupled from growth factor-AKT stimulation in all four T-ALL cell lines. Next, we examined the AKT substrates c-RAF S259 and AKT1S1/PRAS40 T246 [10-12]. As expected, both sites were phosphorylated in CCRF-CEM cells, but also in ARR (Figure S2A). Since PRAS40 is an inhibitor of the mTOR signalling cascade and the phosphorylation of PRAS40 by AKT1, at T246, relieves mTORC1 from PRAS40 inhibition, our results imply that the mTORC1 signalling is not suppressed by PRAS40 in ARR cells. RHEB is a small GTPase required for mTOR lysosomal activation, which is negatively regulated by the tuberous sclerosis complex (TSC) complex [13-16]. AKT inhibits the TSC complex and allows RHEB to stimulate mTOR signalling [15, 17-20]. The loss of any of the members of the TSC-complex renders mTOR insensitive to regulation through amino acid availability and growth factors [21-23]. Examination of the gene expression data for the genes encoding the proteins of the mTOR signalling pathway revealed defective TSC1 gene expression in ARR cells. Due to alternative splicing, TSC1 transcripts lack four exons (exons 3-7) including the translation start site (Figure S3C-E) and consequently ARR fails to generate TSC1 protein (Figure S2B). The lack of TSC1 implies that mTOR signalling in ARR cells cannot be inhibited by the TSC complex. Additionally, rapamycin failed to supress mTOR and 4E-BP phosphorylation (mTOR S2448 , mTOR S2481 , 4E-BP1 T37/46 , 4E-BP1 T70 and 4E- BP1 S65 ) but did reduce the phosphorylation of p70S6K T389 and S6 ribosomal protein (rpS6 S235 ) (Figure S2A,B). Taken together, ARR cells are characterised by PRAS40 and TSC-independent mTOR signalling with rapamycin-insensitive phosphorylation of 4E-BP. Based on this we conclude that in ARR cells mTOR and protein synthesis regulated by 4E- BP is independent of growth factor and amino acid signalling. Another regulator of the mTOR signalling is the binding partner Raptor, which mediates mTOR interaction with 4E-BP1 and p70S6K [24-27]. As a result of low cellular energy status, AMP kinase (AMPK) phosphorylates S792 on Raptor leading to mTORC1 inhibition and cell cycle arrest [28]. Surprisingly, p-Raptor S792 was observed in all cell lines implying active AMPK and reduced energy availability. In SIL-TAL cells p-Raptor S792 occurred together with reduced RHEB-driven mTOR auto-phosphorylation (S2481) and mTOR phosphorylation by AKT1 at S2448 (Figure S2B) [29, 30]. The commonalities found between the T-ALL cells suggest that T-ALL cells have low energy status that activates AMPK to phosphorylate Raptor and suppress mTOR signalling. Active AMPK and p-Raptor S792 had limited effect on mTOR activity in ARR cells showing that mTOR is constitutively active. The result of supressed mTOR signalling in SIL-TAL was reduced p-4E-BP1 T37/46 in comparison to ARR. Additionally, SIL-TAL cells had reduced phosphorylation on S65 or T70, with DU.528 exhibiting low phosphorylation on both residues. Since the function of 4E-BP is to inhibit cap- dependent translation by binding to the translation initiation factor eIF4E, hyper- phosphorylation of 4E-BP1 by AKT and mTOR disrupts the interaction with eIF4E resulting in activation of cap-dependent mRNA translation [31-34]. 4E-BP phosphorylation at T37 and T46 is required for subsequent S65 and T70 phosphorylation and the release of eIF4E [33, 35, 36]. Therefore, we conclude that the SIL-TAL 4E-BP phosphorylation status is not optimal for supporting mRNA translation and it corroborates our observation that SIL-TALs have reduced de novo protein synthesis. The consequence of supressed mTOR signalling on p70S6K in SIL-TAL cells was only observed is HSB2 cells, where p-p70S6K T389 was the lowest. Despite this, phosphorylation of the p70S6K target rpS6 was observed and remained sensitive to rapamycin showing that AMPK-mediated mTOR suppression does not affect rpS6 phosphorylation in SIL-TALs.

Experimental Procedures Cell Culture T-ALL cell lines ARR, DU.528, HSB2 and CCRF-CEM were grown in RPMI 1640 medium (Sigma Aldrich) supplemented with 10% FCS, 5 U/ml Pen/Strep, 20 mM HEPES, 2mM Glutamine or GlutaMax (LifeTechnologies) and 0.075 mM 1-Thyoglycerol (Sigma). Rapamycin (Sigma), Dorsomorphin (Tocris), UCPH-101 and UCPH-102 (Abcam) were added to a final concentration of 10 nM, 5 µM and 25 µM. For the labelling experiments glutamine-free RPMI was supplemented with 2 mM [1,5-15 N]-L-Glutamine or [3-13 C]-L-

Glutamine (Sigma). Cell lines were grown in a humidified incubator at 37°C and 5% CO 2, at a density between 0.2 – 1.5 10 6/ml.

RNA isolation and cDNA synthesis Total DNA-free RNA was isolated from 5x10 6 cells using Mini Nucleospin RNA kit (Macherey Nagel), according to the manufacturer’s protocol. The RNA concentration and quality was determined using a Nanodrop2000 UV-Vis Spectrophotometer (Thermo Scientific). To synthesize the cDNA, 1µg RNA was denatured at 70°C for 10 minutes in the presence of 0.1 mM oligo(dT) 20 and the cDNA was synthesized using 200 U SuperScript II Reverse Transcriptase, 1 mM dNTPs and 1X First-Strand (LifeTech) at 37°C for 60 minutes. Specific cDNAs were quantifies by quantitative PCR (qPCR) using SYBR Green master mix (Life Tech) and measured on an ABI 7500 Real-Time PCR System. Quantitation was carried out using a standard curve of serial dilutions and relative to rDNA. Primers used for quantification: TAL1F_5’GTTCTTTGGGGAGCCGGATG, TAL1R 5’TGAAGATACGCCGCACAACT, LYL1F 5’CATCTTCCCTAGCAGCCGGTTG, LYL1R 5’GTTGGTGAACACGCGCCG, GATA2F 5’ACTCATCAAGCCCAAGCGAA, GATA2R 5’AAGGTGGTGGTTGTCGTCTG, LMO2F 5’GAAGAGCCTGGACCCTTCAG, LMO2F 5’TCGATGGCCTTCAGGAAGTA, GAPDH 5’CCTGGCCAAGGTCATCCAT, GAPDHR 5’AGGGGCCATCCACAGTCTT, ASS1F 5’GCCCGCAAACAAGTGGAAAT, ASS1R 5’GTGTTGCTTTGCGTACTCCA, ACSS1F 5’GGCTTCAGTGCAGAGTCCTT, ACSS1R 5’CAGTGCTTCACAGCCTCATC, SLC1A3F 5’AAGAGAACAATGGCGTGGAC, TSC15’UTRF 5’AGGTGCTGTACGTCCAAGATG, TSC15’UTRR 5’CTCCAGGACGTGTGCTACAG, TSC1F 5’GAGCAGCGTGACACTATGGT, TSC1R 5’GGAAACCTGACTGAGCAGCA SLC1A3R 5’ATTCCAGCTGCCCCAATACT, 18SrRNAF 5’GGCCCGAAGCGTTTACTTTGA, 18SrRNAR 5’GAACCGCGGTCCTATTCCATTA.

Protein extract preparation Nuclear extracts were prepared by lysing 10 7 cells in hypotonic cell lysis buffer (10 mM

HEPES pH7.6, 10 mM KCl, 1.5 mM MgCl 2) on ice for 15 minutes. Nuclei were pelleted by centrifuging at 500 g for 10 minutes and lysed in 50 µl hypertonic buffer (20 mM HEPES pH

7.6, 420 mM NaCl, 1.5 mM MgCl 2, 0.2 mM EDTA, 0.5 % NP40, 20 % Glycerol) for 20 minutes on ice. The insoluble fraction was precipitated by centrifugation at 20 Kg for 10 minutes. Salt concentrations were adjusted to 150mM NaCl by diluting the supernatants with 1.8 volumes no-salt buffer (20 mM HEPES pH7.6, 1.5 mM MgCl2, 0.2 mM EDTA, 0.5 % NP40, 20 % Glycerol). Protease inhibitor cocktail (Roche) and PMSF were used in all the steps. Total cell extracts were prepared by lysing 10 7 cells in 50 µl cell lysis buffer (20 mM TRIS pH8, 150 mM NaCl, 2 mM EDTA, 0.5 % NP40) or RIPA buffer (50 mM TRIS pH8, 150 mM NaCl, 0.5 % deoxycholic acid, 1 % NP40, 0.1 % SDS) on ice for 20 minutes. The insoluble fraction was precipitated by centrifuging at 20 Kg for 10 min. Protease inhibitor mini tablets and PhosSTOP tablets (Roche) were used 1:100. Concentrations of the protein extracts were assayed using a BCA Protein Assay Kit (Pierce Biotechnology).

Western blot analysis Protein extracts were denatured at 95 °C for 5 minutes in 1X LDS sample loading buffer and 1X DTT (Life Technologies). Proteins were separated on a 4-12 % gradient Bis-Tris Plus Bolt Mini Gels (Life Technologies) at 165 V for 45 minutes, alongside a Page Ruler prestained protein ladder (Thermo Scientific) and transferred to nitrocellulose membranes using Protean Dry-blot transfer stacks on an iBlot blotting system (Life technologies) or using wet transfer in 25 mM Tris, 192 mM Glycine, 20% (v/v) methanol. Every gel was stained with PonceauS to confirm equal loading and only gels satisfying the equal loading criteria were incubated with antibodies. Westerns were blocked in 5 % skimmed milk powder (Marvel) in PBS and incubated overnight with primary antibody, followed by 1 hour incubation with the appropriate secondary antibody. PBS was used for all in between washes. Primary antibodies raised against TAL1 (sc-12984X), GATA2 (sc-9008), Lyl1 (sc-374164) from Santa Cruz Biotechnology; β-actin (a1978) from Sigma-Aldrich; LMO2 (AF2726) from R&D Systems; Phospho-PDK1 (Ser241)(3438), Phospho-Akt (Ser473)(4060), Phospho-Akt (Thr308)(13038), Akt (9916), Phospho-c-Raf (Ser259)(9421), Phospho-PTEN (Ser380)(9551) mTOR (2983), Phospho-mTOR (Ser2448)(5536), Phospho-mTOR (Ser2481)(2974), Raptor (2280), Rictor (2114), G βL (3274), Phospho-Raptor (Ser792)(2083), PRAS40 (2691), Phospho-PRAS40 (Thr246)(2997), RagC (5466), TSC1 (6935), TSC2 (4308), S6 ribosomal protein (2217), Phospho-S6 ribosomal protein (Ser235)(2211), p70 S6 Kinase (9202), Phospho-p70 S6 Kinase (Thr389)(9234), Phospho- 4E-BP1 (Thr37/46)(2855), Non-phospho-4E-BP1 (Thr46)(4923), Phospho-4E-BP1 (Ser65)(9451), 4E-BP1 (9644), 4E-BP2 (2845), Phospho-4E-BP1 (Thr70)(9455), Phospho- AMPK α (Thr172)(50081), AMPK α (5831), Phospho-ULK1 (Ser555)(5869), Phospho-ULK1 (Ser757)(6888), ULK1 (8054), Phospho-Beclin-1 (Ser93)(14717), Beclin-1 (3495), LAMP1 (15665) and EAAT1 (D4166) from Cell Signalling; LAMP1 (ab2417) from Abcam; p62 (610832) from BD Biosciences; LC3 from NovusBiological; LC3II from nanoTools. All antibodies were used at a final concentration of 1 µg/ml. Secondary antibodies, IRDye 680RD or 800RD (Li-Cor) were used at a 0.5 µg/ml. Westerns were visualised using an Odyssey CLx Imager (Li-Cor).

Immunofluorescent Staining Cells were washed in PBS, fixed with 2 % formaldehyde for 10 min and washed twice in PBS containing 0.05% Tween, 2% FCS. Immunostaining was performed using 1 µg/ml primary antibody in PBS/0.05 % Tween/2 % FCS overnight, followed by three washes and a 30 minutes incubation with 1 µg/ml secondary antibody conjugated to Alexa dyes (LifeTech). Immuno-stained cells were deposited onto the glass slides by centrifugation at 500 rpm for 2 minutes in a Cytospin III centrifuge (Shandon). LysoTracker Red and MitoTracker Red CMXRos (Invitrogen) were used for lysosome and mitochondria staining as per manufacturer’s instruction. Slides were dried for 30 minutes and covered in Prolong Gold Anti-Fade reagent with DAPI (LifeTech). Imaging was performed using a Carl Zeiss LSM880 Confocal microscope.

Quantification of de novo protein synthesis Click-iT™ Plus OPP Alexa Fluor™ 488 Protein Synthesis Assay Kit (Invitrogen) was used as according to the manufacturer’s manual. Cells were prepared and the staining was visualised as describe for immunofluorescent stainings. Experiments were performed in triplicate and from each experiment 5 images were recorded per cell line. Staining was quantified using CellProfiler software [37].

Cloning SLC1A3 was amplified by PCR from pcDNA3-EAAT1 using primers SLC1A3_Bgl II_F1 AGATCTATGACTAAAAGCAATGGAGA and SLC1A3_ Xho I_R1 CTCGAGCTACATCTTGGTTTCACTGT [38]. The PCR product was digested with Bgl II and Xho I (Thermo) and SLC1A3 cDNA was cloned into a MigR1 backbone in front of IRES-GFP generating MigR1-SLC1A3 [39]. Short hairpin sequences targeting SLC1A3 were designed using the SLC1A3 cDNA sequence and the http://cancan.cshl.edu/RNAi_central/RNAi.cgi?type=shRNA website [40]. Designed shRNA (shSLC1A3_1 ACCATATCAACTGATTGCACAG, shSLC1A3_2 GGGTAACTCAGTGATTGAAGAG, shSLC1A3_3 GTGGCACACAATCCTATAAATG ,shSLC1A3_4 AGGCCTCAGTGTCCTCATCTAT and shSLC1A3_5 CACTCCTCAACTGATGATAGAC) were embedded into mir30, cloned into pMSCVhygro and tested as described previously [41]. The PlatE mouse fibroblast cell line was transfected using Trans IT-LT1 (Mirusbio) with MigRI-SLC1A3 and MSCVhyg_shSLC1A3 as well as with MSCVhyg_shGFP and MSCVhyg_shFF3 [42]. Effectiveness of shRNA was monitored by flow cytometry, measuring GFP level and comparing to the positive control shGFP and the negative control shFF3 [40]. shSLC1A3_1 and shSLC1A3_2 had an effect similar to shGFP. Protein extracts were prepared and EAAT1 and GFP levels were determined by western blotting using rabbit anti-human EAAT1 (D4166)(CellSignalling) and rabbit anti-GFP (GF28R)(eBiosciences). Identified shRNA were cloned into piggybac transposon inducible expression vector PB_tet- on_Apple_shGFP using Hind III and Kpn 2L (ThermoFisher) generating pBshSLC1A3_1 and _2 [43]. T-ALL cell lines (4x10 6 cells) were electroporated with 4 µg pB and 1 µg pCAGG- PBase in 400 µL Optimem medium (Invitrogen) using 4 mm cuvettes, 300 V, 1000 µF in a GenePulser Xcell (BioRad) [44]. Cells were expanded and selected with puromycine (ThermoFisher): 1 µg/ml for ARR, HSB2 and CCRF-CEM; 5 µg/ml for DU.528.

Screening the effect on shSLC1A3 on T-ALL growth T-ALL cell lines with integrated pBshSLC1A3_1, pBshSLC1A3_2 or pBshSLC1A3_shFF3 had shRNA expression induced with doxycycline (Sigma-Aldrich) at a final concentration of 0.1 µg/ml. Every second day, sells were counted, medium was changed and the cell concentration was adjusted to 0.4x10 6/ml.

Patient Samples Samples used in this study are surplus diagnostic samples from presentation cases before treatment obtained from the Queen Elizabeth Hospital Birmingham, Birmingham, UK. Cytogenetic abnormalities and sample immunophenotype were also determined at the time of disease diagnosis at the West Midlands Regional Genetics Laboratory, Birmingham Women’s NHS Foundation Trust, Birmingham, UK. Samples were obtained with the required ethical approval from the NHS National Research Ethics Committee (Reg:10/H1206/58). Samples were processed on the same day that they were taken from the patient. Mononuclear cells were purified from peripheral blood by differential centrifugation (20 mins, 1000 g) using Lymphoprep (Axis-Shield UK, Cambridgeshire, UK). Undifferentiated blast cells were then isolated using anti-human CD34- (T-ALL_1 and _2) or CD7- (T-ALL_3) coupled MACS Micro Beads (Miltenyi Biotec) and column separation on magnets (Miltenyi Biotec), according to the manufacturer’s guidelines. For T-ALL_1 and _3, sample purity was confirmed by flow cytometry and cells were used in downstream application. T-ALL_2, CD34 + cells were further sorted by FACS for CD7 + using anti-human CD7-FITC antibody (CD6-6B7)(BioLegend). After the purification, cells were grown in co-culture with OP-9DL4 stromal cells in αMEM medium containing 10% FCS, 5 U/ml Pen/Strep, 2 mM GlutaMAX, 5 ng/ml rhIL7 (R&D Systems), 5 ng/ml rhFLT3L (R&D Systems).

RNASeq library preparation For each cell line, RNASeq libraries were prepared from biological triplicates or duplicates (fig legends) and indexed using the TruSeq Stranded mRNA Sample Preparation Kit LH (Illumina), starting with 4 µg total RNA per sample according to manufacturer’s protocol. Quality control of the libraries was carried out by Agilent Bioanalyzer using the High Sensitivity DNA analysis kit, and quantitation of the libraries was carried out using the Kapa Biosystems Illumina library Quantitation kit. Libraries were pooled and sequenced as 100 nt paired-end on Illumina HiSeq 2500 sequencer at a depth of approximately 30 million reads per library.

RNA-seq data analysis Reads acquired from RNASeq were mapped as stranded libraries to the hg38 (GRCh38), using TopHat 2.2 using the public server at usegalaxy.org [45, 46] . Transcripts were assembled using Cufflinks 2.2.1 and GENCODE gene annotation with quartile normalisation and effective length correction [46]. Assembled transcripts were merged and normalised before differential gene expression was determined. Gene differential expression and FPKM gene expression files were used to select the gene IDs that were significantly differential expressed. Pearson complete linkage hierarchical clustering and heat maps were computed by Multi Experiment Viewer software [47]. Gene ontology enrichment was performed using DAVID 6.8 beta [48, 49]. GO terms for biological processes with Modified Fisher Extract P-value <0.05 were considered significant, categories with redundant terms were filtered out, and the top 10 are presented. To visualize the distribution of transcripts across the reference genome, the DNA strand specific bam files were transformed to bigwig files and uploaded as composite tracks to the UCSC browser.

NMR spectroscopy of cell extracts Methanol/chloroform extraction was used to prepare polar extracts from 5x10 7 cells for NMR spectroscopy analysis. Cells were washed twice with PBS, pelleted by centrifuging for 5 min at 300 g and resuspended in 400 µl ice cold methanol. After adding 100 µl water, cell extracts were transferred to glass vials and 400 µl chloroform was added. Extracts were vortexed for 30 s and incubated on ice for 10 min. Next, samples were centrifuged at 1500 g for 10 min at 4 °C and 400 µl of the polar, upper phase was transferred to low-binding tubes (Axygen) and dried in a vacuum concentrator (SpeedVac) for 3-6 hours. Dry pellets were stored at -80 °C until required, after which they were resuspended in 50 µl NMR buffer (100 mM sodium phosphate, 500 µM Sodium 3-(trimethylsilyl)propionate (TMSP)(Sigma-Aldrich),

10% D 2O, pH7.0) by vortexing and sonication. For NMR spectroscopy, 35 µl of sample was transferred to 1.7mm NMR tubes and stored at 4 °C prior to measurements. NOESY 1D spectra with water pre-saturation were acquired using the standard Bruker pulse sequence noesygppr1d on a Bruker 600 MHz spectrometer with a TCI 1.7 mm z-PFG CryoProbe™ using a Bruker SampleJet autosampler. The sample temperature was set to 300 K. The 1H carrier was on the water frequency and the 1H 90° pulse was calibrated at a power of 0.326 W. Key parameters were as follows: spectral width 12.15 ppm/7288.6 Hz; complex data points, 16384; interscan relaxation delay, 4 s; acquisition time, 2.25 s; short NOE mixing time, 10 ms; number of transients, 256; steady state scans, 4. Total experimental time was approximately 28 min per sample.

Growth-media metabolite uptake and release Cells were grown under normal conditions where 10 6 or 4x10 5 cells/ml media were grown up to 16 h or 48 h, respectively. Cells and media were collected, centrifuged for 5 min at 300 g and supernatant was collected. NMR samples (650 µl) consisted of collected media with 10

% D 2O and 1 mM TMSP was transferred to 5mm glass NMR tubes prior to measurements. NMR spectra were acquired at 300 K using a Bruker 500 MHz spectrometer equipped with a TXI probe. The 1H carrier was on the water frequency and the 1H 90° pulse was calibrated at a power of 12.9 W. Measurements were carried out after locking on deuterium frequency and shimming. The standard Bruker 1D NOESY pulse sequence (noesygppr1d) with water saturation was used. Spectra were acquired with 64 transients and 4 steady state scans. NMR spectroscopy data was processed in Topspin (Bruker Ltd, UK) and MetaboLab within the MATLAB environment (MathWorks, USA)[50]. Spectral assignments were made using Chenomx software.

Live-cell real-time NMR spectroscopy Patient-derived T-ALL cells were collected from the over-night co-culture. ARR and DU.528 cells cultures concentration was set up to 0.3x10 6 cells/ml and cells were grown overnight before 10 6 cells were collected. Cells were resuspended in 1 ml growth media containing 0.1

% low melting agarose (Sigma) with 1 mM TMSP and 10 % D2O. Samples were loaded into 5 mm NMR tubes and measurements were collected every 8.4 minutes, for the total of 100 time points (about 14 h). Specifically, CPMG (Carr-Purcell-Meiboom-Gill) 1D spectra with water pre-saturation were acquired using the standard Bruker pulse sequence cpmgpr1d on a Bruker 500 MHz spectrometer with a TXI 1H/D-13 C/ 15 N probe at 310K. The 1H carrier was on the water frequency and the 1H 90° pulse was calibrated at a power of 12.9 W. For the

CPMG T 2 filter, a T 2 filter time of 68 ms arose from 100 loops over a 680 µs echo time between 180 pulses. Other key parameters were as follows: spectral width 12.02 ppm/6009.6 Hz; complex data points, 16384; interscan relaxation delay, 4s; acquisition time, 2.73 s; short NOE mixing time, 10 ms; number of transients, 64; steady state scans, 4. This resulted in an experiment time for each individual data point of about 7.6 min. With shimming between spectra, the time between measurements was approximately 8.4 min and 100 spectra required a total time of circa 14 h.

NMR spectroscopy data processing and analysis Spectra were processed using MetaboLab (version 20910688) in MATLAB (version R2015b). All spectra were re-phased manually after initial automated phase correction. Before analysis of the spectra, all spectra were aligned to TMSP, a spline baseline correction was applied, the water and TMSP regions were excluded, and the total spectral area (TSA) of each spectrum was scaled to 1. To compare metabolite concentrations, a well- resolved peak was picked for each metabolite in the first spectrum and peaks were picked in the other spectra in an automated manner using in-house subroutines of MetaboLab (version 20910688) [2]. Spectral assignments were made using Chenomx software and acquired chemical standards. For live-cell real-time NMR experiments, spectra were scaled to give constant TMSP area under the curve to equalise differences due to shimming.

Drug Screen In silico drug screen was performed by Domainex Ltd. based on the published EAAT1 crystal structures [51]. Chemical compounds that are predicted to inhibit EAAT1 allosterically were curated based on the following criteria: LogP <4.3; LogD (pH7.4) -2.05-4.13; MW 270- 385 g/mol; H + Acceptors <7; H + Donors <4; TPSA 40-135 A2; Number of Atoms 20-28; CNS MPO 2.87-5; LogD -0.77-4.02.

Based on this screen and availability, compounds were purchased from MolPort and prepared as 25mM solutions in DMSO. All compounds were screened at 25 µM concentration with CCRF_CEM cells over 9 days. Cells were grown and treated in 96-well Black Flat Bottom TC-treated Microplates (Falcon). Cells were split every other day. Counts were acquired on a CellInsight CX5 High-Content Screening Platform on day 0, 1, 3, 5, 7 and 9. Compounds that inhibited cell growth were screened in Kasumi-1 cells for cytotoxicity. Non-cytotoxic compounds were tested in all four T-ALL cell lines and screened at a range of concentrations from 0.15 to 25 µM.

1. Casamayor, A., N.A. Morrice, and D.R. Alessi, Phosphorylation of Ser-241 is essential for the activity of 3-phosphoinositide-dependent protein kinase-1: identification of five sites of phosphorylation in vivo. Biochem J, 1999. 342 ( Pt 2) : p. 287-92. 2. Alessi, D.R., et al., Characterization of a 3-phosphoinositide-dependent protein kinase which phosphorylates and activates protein kinase Balpha. Curr Biol, 1997. 7(4): p. 261-9. 3. Cheng, X., et al., Phosphorylation and activation of cAMP-dependent protein kinase by phosphoinositide-dependent protein kinase. Proc Natl Acad Sci U S A, 1998. 95 (17): p. 9849- 54. 4. Myers, M.P., et al., P-TEN, the tumor suppressor from human 10q23, is a dual- specificity phosphatase. Proc Natl Acad Sci U S A, 1997. 94 (17): p. 9052-7. 5. Myers, M.P., et al., The lipid phosphatase activity of PTEN is critical for its tumor supressor function. Proc Natl Acad Sci U S A, 1998. 95 (23): p. 13513-8. 6. Wu, X., et al., The PTEN/MMAC1 tumor suppressor phosphatase functions as a negative regulator of the phosphoinositide 3-kinase/Akt pathway. Proc Natl Acad Sci U S A, 1998. 95 (26): p. 15587-91. 7. Sakai, A., et al., PTEN gene alterations in lymphoid neoplasms. Blood, 1998. 92 (9): p. 3410-5. 8. Sarbassov, D.D., et al., Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex. Science, 2005. 307 (5712): p. 1098-101. 9. Bayascas, J.R. and D.R. Alessi, Regulation of Akt/PKB Ser473 phosphorylation. Mol Cell, 2005. 18 (2): p. 143-5. 10. Sprenkle, A.B., et al., Identification of Raf-1 Ser621 kinase activity from NIH 3T3 cells as AMP- activated protein kinase. FEBS Lett, 1997. 403 (3): p. 254-8. 11. Kovacina, K.S., et al., Identification of a proline-rich Akt substrate as a 14-3-3 binding partner. J Biol Chem, 2003. 278 (12): p. 10189-94. 12. Sancak, Y., et al., PRAS40 is an insulin-regulated inhibitor of the mTORC1 protein kinase. Mol Cell, 2007. 25 (6): p. 903-15. 13. Sancak, Y., et al., Ragulator-Rag complex targets mTORC1 to the lysosomal surface and is necessary for its activation by amino acids. Cell, 2010. 141 (2): p. 290-303. 14. Castro, A.F., et al., Rheb binds tuberous sclerosis complex 2 (TSC2) and promotes S6 kinase activation in a rapamycin- and farnesylation-dependent manner. J Biol Chem, 2003. 278 (35): p. 32493-6. 15. Inoki, K., et al., Rheb GTPase is a direct target of TSC2 GAP activity and regulates mTOR signaling. Genes Dev, 2003. 17 (15): p. 1829-34. 16. Zhang, Y., et al., Rheb is a direct target of the tuberous sclerosis tumour suppressor proteins. Nat Cell Biol, 2003. 5(6): p. 578-81. 17. Stocker, H., et al., Rheb is an essential regulator of S6K in controlling cell growth in Drosophila. Nat Cell Biol, 2003. 5(6): p. 559-65. 18. Saucedo, L.J., et al., Rheb promotes cell growth as a component of the insulin/TOR signalling network. Nat Cell Biol, 2003. 5(6): p. 566-71. 19. Fonseca, B.D., et al., PRAS40 is a target for mammalian target of rapamycin complex 1 and is required for signaling downstream of this complex. J Biol Chem, 2007. 282 (34): p. 24514-24. 20. Menon, S., et al., Spatial control of the TSC complex integrates insulin and nutrient regulation of mTORC1 at the lysosome. Cell, 2014. 156 (4): p. 771-85. 21. Zhang, H., et al., Loss of Tsc1/Tsc2 activates mTOR and disrupts PI3K-Akt signaling through downregulation of PDGFR. J Clin Invest, 2003. 112 (8): p. 1223-33. 22. Kwiatkowski, D.J., et al., A mouse model of TSC1 reveals sex-dependent lethality from liver hemangiomas, and up-regulation of p70S6 kinase activity in Tsc1 null cells. Hum Mol Genet, 2002. 11 (5): p. 525-34. 23. Manning, B.D., et al., Identification of the tuberous sclerosis complex-2 tumor suppressor gene product tuberin as a target of the phosphoinositide 3-kinase/akt pathway. Mol Cell, 2002. 10 (1): p. 151-62. 24. Hara, K., et al., Raptor, a binding partner of target of rapamycin (TOR), mediates TOR action. Cell, 2002. 110 (2): p. 177-89. 25. Kim, D.H., et al., mTOR interacts with raptor to form a nutrient-sensitive complex that signals to the cell growth machinery. Cell, 2002. 110 (2): p. 163-75. 26. Beugnet, A., X. Wang, and C.G. Proud, Target of rapamycin (TOR)-signaling and RAIP motifs play distinct roles in the mammalian TOR-dependent phosphorylation of initiation factor 4E- binding protein 1. J Biol Chem, 2003. 278 (42): p. 40717-22. 27. Nojima, H., et al., The mammalian target of rapamycin (mTOR) partner, raptor, binds the mTOR substrates p70 S6 kinase and 4E-BP1 through their TOR signaling (TOS) motif. J Biol Chem, 2003. 278 (18): p. 15461-4. 28. Gwinn, D.M., et al., AMPK phosphorylation of raptor mediates a metabolic checkpoint. Mol Cell, 2008. 30 (2): p. 214-26. 29. Peterson, R.T., et al., FKBP12-rapamycin-associated protein (FRAP) autophosphorylates at serine 2481 under translationally repressive conditions. J Biol Chem, 2000. 275 (10): p. 7416- 23. 30. Nave, B.T., et al., Mammalian target of rapamycin is a direct target for protein kinase B: identification of a convergence point for opposing effects of insulin and amino-acid deficiency on protein translation. Biochem J, 1999. 344 Pt 2 : p. 427-31. 31. Brown, E.J., et al., Control of p70 s6 kinase by kinase activity of FRAP in vivo. Nature, 1995. 377 (6548): p. 441-6. 32. Brunn, G.J., et al., Phosphorylation of the translational repressor PHAS-I by the mammalian target of rapamycin. Science, 1997. 277 (5322): p. 99-101. 33. Peter, D., et al., Molecular architecture of 4E-BP translational inhibitors bound to eIF4E. Mol Cell, 2015. 57 (6): p. 1074-1087. 34. Marcotrigiano, J., et al., Cap-dependent translation initiation in eukaryotes is regulated by a molecular mimic of eIF4G. Mol Cell, 1999. 3(6): p. 707-16. 35. Gingras, A.C., et al., Regulation of 4E-BP1 phosphorylation: a novel two-step mechanism. Genes Dev, 1999. 13 (11): p. 1422-37. 36. Gingras, A.C., B. Raught, and N. Sonenberg, Regulation of translation initiation by FRAP/mTOR. Genes Dev, 2001. 15 (7): p. 807-26. 37. Kamentsky, L., et al., Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. Bioinformatics, 2011. 27 (8): p. 1179-80. 38. Jensen, A.A. and H. Brauner-Osborne, Pharmacological characterization of human excitatory amino acid transporters EAAT1, EAAT2 and EAAT3 in a fluorescence-based membrane potential assay. Biochem Pharmacol, 2004. 67 (11): p. 2115-27. 39. Pear, W.S., et al., Efficient and rapid induction of a chronic myelogenous leukemia-like myeloproliferative disease in mice receiving P210 bcr/abl-transduced bone marrow. Blood, 1998. 92 (10): p. 3780-92. 40. Paddison, P.J., et al., Cloning of short hairpin RNAs for gene knockdown in mammalian cells. Nat Methods, 2004. 1(2): p. 163-7. 41. Dow, L.E., et al., A pipeline for the generation of shRNA transgenic mice. Nat Protoc, 2012. 7(2): p. 374-93. 42. Morita, S., T. Kojima, and T. Kitamura, Plat-E: an efficient and stable system for transient packaging of retroviruses. Gene Ther, 2000. 7(12): p. 1063-6. 43. Glover, J.D., et al., A novel piggyBac transposon inducible expression system identifies a role for AKT signalling in primordial germ cell migration. PLoS One, 2013. 8(11): p. e77222. 44. Wang, W., et al., Chromosomal transposition of PiggyBac in mouse embryonic stem cells. Proc Natl Acad Sci U S A, 2008. 105 (27): p. 9290-5. 45. Afgan, E., et al., The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res, 2018. 46 (W1): p. W537-W544. 46. Trapnell, C., et al., Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc, 2012. 7(3): p. 562-78. 47. Howe, E.A., et al., RNA-Seq analysis in MeV. Bioinformatics, 2011. 27 (22): p. 3209-10. 48. Huang da, W., B.T. Sherman, and R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009. 4(1): p. 44-57. 49. Huang da, W., B.T. Sherman, and R.A. Lempicki, Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res, 2009. 37 (1): p. 1-13. 50. Ludwig, C. and U.L. Gunther, MetaboLab--advanced NMR data processing and analysis for metabolomics. BMC Bioinformatics, 2011. 12 : p. 366. 51. Canul-Tec, J.C., et al., Structure and allosteric inhibition of excitatory amino acid transporter 1. Nature, 2017. 544 (7651): p. 446-451.