bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Inosine is an alternative carbon supply that supports effector T cell proliferation and anti- tumor function under glucose restriction

Tingting Wang1*, JN Rashida Gnanaprakasam1*, Xuyong Chen1, Siwen Kang1, Xuequn Xu1, Hua

Sun3, Lingling Liu1, Ethan Miller1, Teresa A. Cassel2, Qiushi Sun2, Sara Vicente-Muñoz2, Marc O.

Warmoes2, Andrew N. Lane2, Xiaotong Song3,4$, Teresa W.-M. Fan2$, and Ruoning Wang1$

1Center for Childhood Cancer & Blood Diseases, Hematology/Oncology & BMT, Abigail Wexner Research Institute at Nationwide Children's Hospital, The Ohio State University, Columbus, OH, USA

2Center for Environmental and Systems Biochemistry, Dept. of Toxicology and Cancer Biology,

Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA 3The Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX 77030 USA

4Icell Kealex Therapeutics, Houston, TX 77021

$Correspondence should be addressed to: Ruoning Wang, Phone: 614-335-2980; Fax: 614-722-5895. [email protected]; Teresa W.-M. Fan, Phone: 858-218-1028, Fax: 859-257-1307 [email protected]; Xiaotong Song; [email protected];

*Wang T and Gnanaprakasam J contributed equally to this paper

Short title: Modulation of metabolic plasticity to enhance T cell function

Key words: Metabolism, Glucose, Inosine, metabolic stress, metabolic plasticity, tumor immunity, stable isotope-resolved metabolomics bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Abstract T cells undergo a characteristic metabolic rewiring that fulfills the dramatically increased bioenergetic, biosynthetic, and redox demands following antigen stimulation. A robust adaptive immune system requires effector T cells to respond and adapt to fluctuations in environmental nutrient levels imposed by infectious and inflammatory sites in different tissues. Inevitably, such responsiveness and adaptation reflect metabolic plasticity, allowing T cells to elicit immune functions by using a wide range of nutrient substrates. Here, we show that effector T cells utilize inosine, as an alternative substrate, to support cell growth and function in the absence of glucose. T cells metabolize inosine into hypoxanthine and phosphorylated ribose by purine nucleoside phosphorylase (PNP). Using Stable Isotope-Resolved Metabolomics (SIRM), we demonstrated that ribose moiety of inosine can enter into central metabolic pathways to provide ATP and biosynthetic precursors. Accordingly, the dependence of T cells on extracellular glucose for growth and effector functions can be relieved by inosine. On the other hand, cancer cells display diverse capacity to utilize inosine as a carbon resource. Moreover, the supplement of inosine enhances the anti-tumor efficacy of immune-checkpoint blockade or adoptive T cell transfer, reflecting the capability of inosine in relieving tumor-imposed metabolic restrictions on T cells in vivo.

bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Introduction

A robust adaptive immune response relies on the ability of antigen-specific T cells to rapidly transform from a quiescent (naive) state to a proliferative (active) state, followed by sustained proliferation during the period of antigen presentation. An increasing body of evidence suggests that a coordinated rewiring of cellular metabolism, is required to fulfill the bioenergetic, biosynthetic and redox demands of T cells following activation [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11]. Naive T cells and memory T cells predominantly rely on fatty acid oxidation (FAO) and oxidative phosphorylation (OXPHOS) for their energy supply in the quiescent state. Following antigen

stimulation, effector T (Teff) cells rapidly upregulate other pathways including aerobic glycolysis, the pentose phosphate pathway (PPP) and glutaminolysis to drive clonal expansion and effector functions [12; 13; 14; 15; 16; 17; 18; 19; 20]. Such metabolic reprogramming induced by T cell activation relies on a hierarchical signaling cascade transcriptional networks [13; 16; 21; 22; 23; 24; 25; 26].

It is now commonly recognized that the immune system is intimately involved in tumor initiation,

progression, and responses to therapy [27; 28; 29; 30; 31; 32]. Teff cells are the major agents of anti- tumor immunity, and elicit anti-tumor activity through direct recognition and killing of antigen presenting tumor cells as well as orchestrating a plethora of adaptive and innate immune responses [31; 33; 34; 35]. However, tumors often co-opt a broad spectrum of mechanisms that foster an immune suppressive microenvironment, thereby escaping T cell-mediated anti-tumor immune response. Various intrinsic and extrinsic tumor factors favor the development of

immunosuppressive myeloid-derived suppressor cells (MDSC) and regulatory T (Treg) cells, increasing the expression of inhibitory checkpoint receptors, such as cytotoxic T-lymphocyte- associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and lymphocyte- activation gene 3 (LAG 3); while reducing the expression and presentation of tumor specific antigens [30; 36; 37; 38; 39; 40; 41]

Mounting evidence has shown that immunotherapies through strengthening the amplitude and quality of T cell-mediated adaptive response may mediate durable and even complete tumor regression in some cancer patients. Two of the most promising approaches to enhance therapeutic bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

anti-tumor immunity are immune checkpoint blockade using monoclonal antibodies against PD- 1/PDL1 and CTLA4, and adoptive cell transfer (ACT) of tumor infiltrating lymphocytes (TILs) or peripheral T cells that are genetically engineered with chimeric antigen receptors (CARs) [30; 42; 43; 44; 45; 46; 47; 48; 49]. Despite the clinical promise of CAR T-cell therapy in B cell leukemia and checkpoint blockade therapies in metastatic melanoma, non-small cell lung cancer (NSCLC), bladder cancer, and others, more than three-quarters of cancer patients overall remain refractory to the current immunotherapeutic regimen [49; 50; 51; 52; 53; 54].

To enhance immunotherapeutic efficacy, understanding the key immunosuppressive barriers in cancer tissues is critically important. A key but largely overlooked problem is nutrient competition between tumor cells and T cells in the nutrient poor tumor microenvironment (TME). Metabolic dysregulation is now recognized as one of the hallmarks of human cancer and the activation of oncogenic signaling pathways enabling tumor cells to reprogram pathways of nutrient acquisition and metabolism to meet the additional bioenergetic, biosynthetic and redox demands of cell transformation and proliferation. [55; 56; 57; 58; 59; 60; 61; 62; 63]. The TME of solid tumors represents a dramatic example of metabolic stress, where the high metabolic demands of cancer

cells can restrict the function of Teff cells by competing for nutrients including glucose and by producing immune suppressive metabolites [62; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74]. As

such, a better understanding of the metabolic modulation of Teff cells to relieve the immunosuppressive barriers in the TME will enable us to devise rational and effective approaches to enhance cancer immunotherapy via improving T cell metabolic fitness.

Here, we report that T cells can utilize few substrates, and that inosine is an alternative metabolic substrate that can support cell growth and crucial T-cell functions in the absence of glucose. The catabolism of the ribose subunit of inosine provides both metabolic energy in the form of ATP and biosynthetic precursors from glycolysis and the pentose phosphate pathway. Inosine supplementation promotes T cell-mediated tumor killing activity in vitro and enhances the anti- tumor efficacy of checkpoint blockade therapy or adoptive T cell therapy in mouse models, reflecting the capability of inosine in relieving tumor-imposed metabolic restrictions on T cells.

Results bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

A metabolic screen identifies inosine as an alternative fuel to support Teff cell survival and proliferation Solid tumors typically develop a hostile microenvironment characterized by an irregular vascular network and a correspondingly poor nutrient supply. Highly glycolytic cancer cells may deplete nutrients, particularly glucose, thereby restricting glucose availability to T cells [66; 67; 68; 72]. Previous studies have shown that murine T cells significantly enhanced glucose catabolic activity

following activation, and that glucose starvation compromises viability and proliferation of Teff

cells [13; 14; 16; 25; 75]. We asked whether Teff cells have the capability of taking up alternative carbon and energy sources to support their survival and proliferation in the absence of glucose. To

this end, we generated human Teff cells by stimulating human PBMCs with plate-bound anti-CD3

antibody in the presence of IL-2. After three days activation and expansion of human Teff cells, we plated cells in glucose-free media into 96 well plates (Biolog’s Phenotype MicroArray Mammalian plates PM-M1 and PM-M2) pre-loaded with an array of compounds that can serve as carbon and/or nitrogen sources for mammalian cells. Blank wells and wells pre-loaded with glucose were included as negative and positive controls, respectively. We then determined the substrate

utilization of Teff cells in each well through a colorimetric assay in which the formation of the reduced dye represents cells’ ability to catabolize these extracellular substrates and generate NADH [76]. The results were normalized to positive control (wells preloaded with glucose) and summarized in Figure 1A and Figure S1A. It was found that polysaccharides, six-carbon sugars and their derivatives including dextrin, glycogen, maltotriose, maltose, mannose and fructose-6-

phosphate were utilized by Teff cells in the absence of glucose (Figure 1A and Figure S1A).

Remarkably, inosine, a nucleoside, also supported Teff cells bioenergetic activity in the absence of glucose (Figure 1A). To eliminate the possibility that inosine was contaminated with glucose or glucose analogs, we obtained inosine from a different source and determined if inosine could

support mouse and human Teff cell proliferation and viability in the absence of glucose. Freshly isolated mouse and human CD8+ T cells were stained with carboxyfluorescein succinimidyl ester (CFSE) dye and stimulated with plate-bound anti-CD3 and anti-CD28 antibodies in conditional media supplied with interleukin 2 (IL-2). Glucose starvation significantly reduced cell proliferation and increased cell death (Figure 1B, 1C, S1B and S1C). However, Inosine supplemented at an equimolar amount of glucose markedly reduced cell death and restored cell

proliferation in mouse and human Teff cells following glucose starvation (Figure 1B, 1C, S1B and bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

S1C). This shows that inosine may offer bioenergetic support similar to as glucose to support Teff cell proliferation.

Inosine supports T effector cell function in the absence of glucose We next asked whether inosine could restore the cytotoxic activity and other effector functions of

Teff cells in the absence of glucose. We generated antigen specific mouse Teff cells by stimulating major histocompatibility complex (MHC) class I-restricted T cells, isolated from premelanosome protein (Pmel)-1 T cell receptor transgenic mice, with peptide antigen and interleukin 2 (IL-2) [77; 78; 79]. We also generated human GD2-specific chimeric antigen receptor (GD2-CAR) T cells by stimulating human PBMCs with plate-bound anti-CD3 antibody in the presence of IL-2, followed by retroviral transduction with GD2-CAR [80; 81]. It was found that Pmel+ cells recognized Pmel- 17 (mouse homologue of human SIVL/gp100) in mouse melanoma, while GD2-CAR T cells recognized GD2, a disialoganglioside expressed in tumors of neuroectodermal origin. We co-

cultured Pmel+ Teff cells with B16F10 mouse melanoma cells (Figure 1D), as well as GD2-CAR T cells with LAN-1 human neuroblastoma cells (Figure S1D), in conditional media, then assessed tumor cell apoptosis by real-time imaging analysis of caspase activity. We also cultured mouse

(Figure 1E) and human (Figure S1E) Teff cells in conditional media and assessed the expression of effector molecules including granzyme B, tumor necrosis factor alpha (TNF-α) and interferon

gamma (IFNγ), all of which are important in mediating tumor cell-killing activity of Teff cells. While glucose starvation significantly reduced the tumor-killing capacity and the expression of

granzyme B, TNF-α and IFNγ of Teff cells, both glucose and inosine supplementation restored these

properties in mouse and human Teff cells (Figure 1D, 1E, S1D and S1E). Taken together, our results

indicate that inosine has the capacity to replace glucose in supporting the effector function of Teff cells.

Adenosine, the metabolic precursor of inosine, cannot support the proliferation and function of T effector cells in the absence of glucose Adenosine, the metabolic precursor of inosine, has been reported as an immune suppressive metabolite and promotes the resolution of inflammation by targeting a range of immune cells, including T cells [82; 83; 84; 85]. Since adenosine and inosine have identical chemical properties,

we asked whether adenosine can support the proliferation of Teff cells in the absence of glucose. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Adenosine supplemented at an equimolar amount of glucose, failed to reduce cell death or restore

the proliferation of mouse and human Teff cells following glucose starvation (Figure S2A and S2B).

Next, we asked whether adenosine can support the effector functions of Teff cells in the absence of glucose. We found that, while adenosine had a marginal effect of enhancing the expression of granzyme B, it failed to restore the tumor-killing activity and the expression of other effector

molecules in mouse (Figure S2C and S2D) or human Teff cells (Figure S2E and S2F) in the absence of glucose. Collectively, our results indicate that inosine, but not its metabolic precursor adenosine,

has the capacity for replacing glucose in supporting the cytotoxic function of Teff cells.

Inosine does not support the proliferation of T effector cells by enhancing glutamine and fatty acid catabolism or through purine nucleotide salvage.

Glutamine is a key carbon and nitrogen donor for Teff cells, while fatty acids are also known carbon

donors for naive T (Tnai), regulatory T (Treg) and memory T (Tmem) cells [5; 6; 11; 86]. We next asked

whether inosine supports Teff cell proliferation by enhancing glutaminolysis and fatty acid β-

oxidation (FAO). Mouse Teff cells cultured in glucose or inosine conditional media displayed

14 14 comparable catabolic activities via glutaminolysis, as indicated by CO2 release from [ C5]-

glutamine, or via FAO, indicated by 3H-water release from [9,10-3H]-palmitic acid (Figure. S3A).

Moreover, an inhibitor of FAO (Etomoxir), failed to block Teff cell proliferation in inosine

conditional media (Figure. S3B). However, glutamine starvation blocks inosine-dependent Teff cell proliferation (Figure. S3B), supporting the indispensable role of glutamine as a key nitrogen donor

of Teff cells [5; 6]. Collectively, our results show that inosine does not enhance glutamine and fatty

acid catabolism in Teff cells. Inosine is a hypoxanthine nucleoside that can be broken down into ribose-1-phosphate and hypoxanthine, the latter of which can funnel into purine nucleotide salvage pathway (Figure S3C) [87; 88]. We next asked whether hypoxanthine or the purine nucleoside

guanosine can support the proliferation of Teff cells in the absence of glucose. Neither hypoxanthine nor guanosine supplemented at an equimolar amount of glucose can reduce cell death or restore

the proliferation of mouse Teff cells following glucose starvation (Figure S3D). Together with our adenosine data, we conclude that purine nucleotide salvage is not responsible for inosine-

dependent Teff cell proliferation.

Inosine-ribose fuels key metabolic pathways in T effector cells bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Next, we asked whether inosine-derived ribose (Figure S3C) could be a fuel for key metabolic pathways involved in cell proliferation and survival. To this end, we applied a stable isotope based metabolic flux approach to compare metabolic routes of glucose and the ribose moiety in inosine.

13 13 Specifically, we supplied [ C6]-Glucose (Glc) or [1',2',3',4',5'- C5]-Inosine (Ino), where only the

13 ribose contains carbon-13 ( C), as the metabolic tracer in human Teff cells cultured with glucose

free conditional media (Figure 2A). Then, we followed 13C incorporation into intermediate metabolites in the central carbon metabolic pathways including the pentose phosphate pathway (PPP), glycolysis and the Krebs cycle.

13 13 We first compared the metabolism of [ C6]-Glc versus [ C5]-Ino via the PPP (Figure 2B). As

13 expected, the C5 fractional enrichment of the parent tracer inosine were higher in the inosine

tracer-treated Teff cells than the glucose tracer-treated ones. Moreover, both tracers were extensively

metabolized via the PPP to produce 13C labeled intermediates, including ribose-5-phosphate (R1P), ribose-5-phosphate (R5P), sedoheptulose-7-phosphate (Sed7P), erythrose-4-phosphate (Ery4P),

fructose-6-phosphate (Fruc6P) and glucose-6-phosphate (Glc6P) (Figure 2B). The fraction of 13C

enrichment in the dominant fully 13C labeled isotopologues of R5P, Fruc6P and Glc6P were higher for the inosine tracer treatment than the glucose tracer treatment. This is consistent with the direct

13 and rapid metabolism of [ C5]-inosine via the non-oxidative branch of the PPP and the equilibration of Fruc6P with Glc6P via the action of phosphoglucose isomerase (PGI). We also observed the

13 13 13 presence of scrambled C products of Sed7P ([ C2]- and [ C5]-Sed7P in particular), Fruc6P, and Glc6P. These scrambled products were presumably derived from the reversible transketolase (TK)

13 13 and transaldolase (TA) activity. The dominant presence of [ C2]- and [ C5]-isotopologues among

the 13C scrambled products of Sed7P is again consistent with the flux through both branches of PPP for both inosine and glucose tracer treatments.

13 13 The C-Fruc6P and Glc6P products of [ C5]-inosine from PPP can be further metabolized via

13 13 glycolysis and the Krebs cycle, as in the case of [ C6]-Glc. We thus tracked the fate of [ C5]-inosine

13 and [ C6]-Glc in human Teff cells through these two key bioenergetic pathways via IC-UHR-FTMS

13 13 analysis (Figure 2C). [ C5]-inosine was metabolized as extensively as [ C6]-Glc via glycolysis to

produce fully 13C labeled isotopologues of intermediate metabolites including

13 phosphoenolpyruvate (PEP), pyruvate, and lactate. The presence of a significant fraction of [ C2]-

isotopologues among the 13C products of the Krebs cycle (citrate, a-ketoglutarate or aKG, bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

glutamate or Glu, glutathione or GSH, succinate, fumarate, malate, and aspartate or Asp) is consistent with flux through pyruvate dehydrogenase (PDH)-dependent reaction for both inosine and glucose tracer treatments (Figure 2C). Together, these data support an extensive capacity of

Teff cells to utilize inosine as an alternative fuel source to glucose in the central carbon metabolism.

The Inosine hydrolyzing enzyme, purine nucleoside phosphorylase, is required for inosine- dependent proliferation and effector functions in T effector cells Purine nucleoside phosphorylase (PNP) is responsible for hydrolyzing inosine into ribose-1- phosphate and is significantly induced following T cell activation (Figure 3A and 3B) [87; 88].

Given that the ribose moiety of inosine is extensively catabolized in Teff cells, we reasoned that PNP is required for inosine-mediated bioenergetic support. To test this idea, we assessed the

bioenergetic activity of Teff cells in the presence of a PNP inhibitor (forodesine (Foro); also referred as BCX-1777, Immucillin H) [89; 90]. As shown in Figure 3C and S4A, the PNP inhibitor Foro treatment led to a dosage-dependent attenuation of bioenergetic activity in both human and mouse

Teff cells cultured in inosine-containing but not glucose-containing media. We then assessed the

proliferation, viability and effector functions of Teff cells treated with Foro. Consistent with its effects on the bioenergetic activity, Foro significantly dampened proliferation, viability, tumor killing activity as well as the expression of granzyme B, TNF-α and IFNγ in mouse (Figure 3D-

3F) and human (Figure S4B-S4D) Teff cells cultured in inosine-containing media. Next, we sought

to validate the data of pharmacological inhibition of PNP by knocking down PNP in human Teff cells. As shown in Figure S4E and S4F, electroporation with PNP siRNA but not control scramble

siRNA partially reduced the level of PNP protein in Teff cells, and attenuated the bioenergetic

activity and number of human Teff cells cultured in inosine-containing but not glucose-containing media. Taken together, our results suggest that PNP-dependent inosine hydrolysis is required for inosine-mediated proliferation, bioenergetic support, tumor killing activity, and the expression of

Teff cell effector molecules.

The PNP inhibitor, Forodesine, suppresses inosine catabolism in T effector cells

Next, we assessed the effect of PNP inhibition on inosine catabolism by comparing the carbon flux

13 of [ C5]-Inosine in the presence or absence of the PNP inhibitor (Foro), in Teff cells (Figure 4A). bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Since Foro treatment significantly reduces T cell viability in inosine-containing media (Figure 3D and S4B), we chose to moderately suppress the PNP activity by applying a lower dose of Foro along with a shorter incubation time compared to the previous experiment. Treatment with Foro

13 led to the fractional enrichment of C5 inosine, the metabolic substrate of PNP, and a decrease in

the fractional enrichment of the fully 13C labeled species of PPP metabolites, which are indirect metabolic products of PNP (Figure 4B). These results suggested that the inhibition of PNP suppresses the catabolism of the ribose moiety of inosine via the PPP. Next, we tracked the fate of

13 [ C5]-inosine via glycolysis and the Krebs cycle in the context of suppressed PNP activity. As shown by IC-UHR-FTMS analysis (Figure 4C), the Foro treatment greatly reduced the fraction of

13 13 fully C labeled isotopologues of glycolysis metabolites and the fraction of [ C2]-isotopologues of the Krebs cycle metabolites. To further assess the effect of Foro in T cell metabolism in both

glucose- and inosine-containing media, we applied 1D HSQC NMR to quantify 13C labeled isotopologues of several representative metabolites in glycolysis, the Krebs cycle and nucleotide biosynthesis, including lactate (Lac), alanine (Ala), inosine (Ino), glutamine (Glu), GSH+GSSG (Gluta), adeninine nucleotides (AXP) and uracil nuecleotides (UXP) (Figure S5). Foro treatment

13 significantly altered the quantity of [ C5]-Ino-derived metabolites (Figure S5A). In contrast, Foro

13 had little effect on the quantity of [ C6]-Glc-derived metabolites (Figure S5B). Together, these data

support an extensive capacity of Teff cells for hydrolyzing inosine as an alternative fuel source to glucose in the central carbon metabolism.

Transformed cells display a diverse capacity for utilizing inosine as a carbon source

The nucleoside transporters and PNP are expressed in the majority of tissues and cell lines (data from The Human Protein Atlas). We therefore reasoned that cancer cells may also be able to take up and utilize inosine as an alternative carbon resource. To this end, we selected a panel of transformed cell lines and compared their growth rate in glucose- versus inosine-containing media. While most of the tested cell lines displayed some degree of inosine-dependent proliferation, several cell lines were unable to grow in inosine-containing media (Figure 5A, 5B and S6A). Next, we chose HeLa as a model cell line to study inosine catabolism and the role of PNP in inosine- dependent growth. We applied the same metabolic approach (Figure 2A) that was used to study T cells, to compare glucose and inosine catabolism in HeLa cells. HeLa cells displayed a similar bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

pattern of 13C incorporation into intermediate metabolites in the central carbon metabolic pathways

13 13 as in the T cells. Collectively, HeLa cells extensively catabolized [ C6]-Glc) and [ C5]-Ino, which

derived fully 13C labeled isotopologues of intermediate metabolites in the PPP and glycolysis, and

13 also a significant fraction of [ C2]-isotopologues in the Krebs cycle metabolites (Figure 5C and 5D). Consistent with the indispensable role of PNP in inosine catabolism in T cells, the pharmacological inhibition of PNP via Foro or genetic knockdown of PNP via siRNA significantly dampened inosine-dependent bioenergetics activity and cell growth in HeLa cells (Figure S6B and S6C). Together, these data suggest that some cancer cells are capable of utilizing inosine as an alternative fuel source to glucose in the central carbon metabolism.

Inosine enhances the efficacy of T cell based immunotherapy in solid tumors

Teff cells represent a key component of anti-tumor immunity. The checkpoint blockade approach that uses monoclonal antibodies targeting PD-1/PDL1 and CTLA4, and adoptive cell transfer (ACT) of tumor infiltrating lymphocytes (TILs) or CAR T cells are two front-line T cell-based immunotherapies [30; 42; 43; 44; 45; 46; 47; 48; 49]. Based on the in vitro findings described

above, we reasoned that inosine supplement may improve Teff cell-mediated anti-tumor activity, particularly toward tumor cells such as B16F10 or Lan-1 that are unable to utilize inosine to support cell growth (Figure S6A). PDL1 and PD-1 (PD) pathway blockade has been shown to elicit durable T cell-dependent anti-tumor responses. We thus assessed the anti-tumor effect of combining inosine and anti-PDL1 antibody in B16 melanoma bearing mice. While tumor growth, tumor-infiltrating T cells, and animal survival were comparable between vehicle (IgG control) and inosine treatment, the monotherapy of anti-PDL1 antibody clearly delayed tumor growth, prolonged animal survival time, and increased infiltrating T cells (Figure 6A and S7A). Importantly, mice treated with the combination of inosine and anti-PDL1 antibody displayed a better outcome (Figure 6A) and more tumor-infiltrating T cells than monotherapy group (Figure S7A). We also examined the ability of inosine to potentiate adoptive transfer based therapy which transfers Pmel+ T cells to mice bearing B16F10 xenografts (Figure 6B) or GD2-CAR T cells to immune-deficient mice bearing GD2 positive human neuroblastoma (LAN-1) xenografts (Figure 6C). While adoptively transferred T cells alone significantly delayed tumor growth and prolonged animal survival time, inosine plus T cells further potentiated these effects in the mouse xenograft models (Figure 6B, 6C and S7B). Taken together, our studies suggest that inosine supplementation bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

enhances the potency and durability of T cell-based cancer immunotherapy in mouse preclinical models.

Discussion

In addition to intrinsic cell signaling cascade, numerous extrinsic environmental factors including oxygen and tissue-specific nutrient supplies significantly influence T cell metabolic programming and thus activation. T cells are distributed throughout the body and thus encounter variable metabolic stresses depending on where tumors or infections occur. A key factor could be the competition for nutrients between infiltrating T cells and rapidly proliferating cells including cancer cells or pathogens. It is likely that a wide range of abundant bioenergetic carbohydrates in blood plasma could be a source of nutrients for proliferative T cells and cancer cells in vivo [91; 92; 93]. Mounting evidence suggests that cancer cells can also scavenge extracellular protein or utilize acetate and ketone bodies as alternative fuels [94; 95; 96]. Although glucose is considered as the primary fuel for proliferating T cells, galactose can replace glucose to support T cell survival and proliferation following activation [97]. Our studies suggest that T cells, to various extents, can metabolize other naturally occurring saccharides or their derivatives, such as D-fructose and D- mannose, as fuels for supporting survival and proliferation. Our studies also revealed T cell’s capacity to utilize inosine for energy and effector cell functions. Such metabolic plasticity is likely to be crucial to T cell’s ability to elicit robust immune responses in different tissue contexts. Although D-ribose produced via the ribose salvage pathway from nucleotide or nucleoside can serve as a carbon and bioenergetic source under nutrient starvation, proliferative normal or transformed cells are unable to catabolize free ribose due to the lack of functional ribose transporters or key enzymes [98; 99; 100; 101; 102]. In contrast, the expression of phosphorylase (PNP) that can convert inosine into ribose-1-phosphate and hypoxanthine is consistent with our finding on inosine’s capacity as a ribose donor in T cells. Such PNP-mediated breakdown of inosine is energetically more efficient than free ribose metabolism, as it only needs inorganic phosphate while the latter requires ATP. We found that the ribose derived from inosine was catabolized efficiently through the central carbon metabolic routes including the PPP, glycolysis,

and the Krebs cycle in place of glucose. This, together with inosine’s ability to support Teff cell growth and functions in the absence of glucose, suggests that inosine, as a ribose donor, may bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

replace glucose as a key fuel source for Teff cells under glucose deprivation, as is found in solid tumors.

The degradation of nucleotides and nucleosides is an evolutionarily conserved metabolic process, which can supply carbon and energy to support cell proliferation and functions [98; 99; 100; 101; 102; 103; 104; 105; 106; 107]. However, we found that inosine but no other nucleosides (adenosine and guanosine) supported T cell proliferation. This result suggests that inosine is a preferred substrate of nucleoside transporters and nucleoside phosphorylase that are predominantly expressed in T cells. Furthermore, PNP inhibitor abolished inosine uptake and metabolism as well

as its ability to support Teff cell proliferation and functions in vitro. Several previous studies also demonstrated the role of inosine in supporting bioenergetic and function in human red blood cells, swine and chicken erythrocytes, which lack glucose transporters, as well as enhancing the recovery of ischemic heart and kidney by preserving ATP [108; 109; 110; 111; 112; 113; 114; 115].

Inosine and adenosine can maintain ATP during hypoxia and nutrient restriction in the central nerve system (CNS) and the catabolism of the ribose moiety of inosine is necessary to provide the bioenergetic support for CNS cells [116]. The protective effect of adenosine depends on adenosine deaminase (ADA), which converts adenosine into inosine [117]. Although inosine and adenosine concentrations in blood plasma is in the low micromolar range, they can accumulate to hundreds of micromolar via catabolism of nucleotides and nucleosides in the necrotic, hypoxic, or inflammatory microenvironment, which is characteristic of solid tumors [118; 119; 120; 121; 122; 123]. T cells may utilize inosine and adenosine accumulated in the tumor microenvironment (TME) as an important carbon and energy source.

In response to tissue injury, stressed or damaged cells release ATP and its product, adenosine, into the extracellular space to elicit autocrine and paracrine signaling responses through cell-surface P2 purinergic receptors [85; 124; 125]. To terminate adenosine-mediated signaling, adenosine deaminase (ADA) converts adenosine to inosine, rendering inosine a weak agonist of adenosine receptor [126]. Consistent with these findings, we found that inosine but not adenosine enhances

Teff cell functions, which may be mediated via inosine catabolism, as the inhibitor of PNP abolished

both inosine catabolism and inosine-induced activation of Teff cell functions. However, it is still conceivable that some of the in vivo effects of inosine are mediated by purinergic signaling due to the concurrent depletion of immune suppressive adenosine. We therefore surmise that ADA bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

treatment may reduce immune suppressive adenosine in TME while increasing the levels of inosine to fuel tumor infiltrated T cells, thereby improving anti-tumor immunity. The genetic disorder leading to the loss of ADA enzymatic function can cause severe combined immunodeficiency (SCID) [127; 128]. As such, the polyethylene glycol–conjugated adenosine deaminase (PEG-ADA) and ADA gene therapy have been developed as the first enzyme replacement therapy (ERT) to treat ADA-SCID [129; 130]. Based on our findings, further research on the molecular action of PEG-ADA and its repurposing in cancer immunotherapy is warranted.

Anti-tumor immunotherapy not only offers the potential of high selectivity in targeting and killing tumor cells, but also represents an appealing addition to the current therapeutic regimens due to its potential to eradicate recurrent/metastatic disease following conventional therapies. However, the immunosuppressive microenvironment is a major barrier to the development of effective immunotherapy. It has been shown that metabolic modulation of T cells is a valid approach to alter T cell mediated immune responses in a variety of physio-pathological contexts [15; 16; 24; 67; 68; 69; 75; 131; 132; 133; 134; 135; 136; 137]. Clearly, nutrient restriction in solid tumor can play an important role in restraining anti-tumor activity of infiltrating T cells. We have shown that inosine

readily replaced glucose in supporting Teff cells growth and functions in vitro, and inosine

supplement improved Teff cell-mediated anti-tumor activities in animal models. Inosine supplementation via oral administration or intravenous infusion has been shown to be safe and tolerable in recent clinical trials of inosine supplementation in Multiple Sclerosis and Parkinson Disease [138; 139; 140; 141]. We therefore envision that metabolic modulation of T cells including inosine and PEG-ADA supplementation poses a new complementary strategy to optimize the potency and durability of cancer immunotherapy. Additional studies on the formulation of inosine supply or strategies that may enhance the local accumulation of inosine in the TME are warranted to facilitate future clinical development of metabolic modulation in cancer immunotherapy.

ACKNOWLEDGEMENTS This work was supported by 1R21CA227926-01A1, 1UO1CA232488-01 and 1R01AI114581 from National Institute of Health, V2014-001 from the V-Foundation and 128436-RSG-15-180- 01-LIB from the American Cancer Society (to RW); 1P01CA163223-01A1, 1U24DK097215- 01A1 (to TWMF, ANL); Redox Metabolism Shared Resource(s) of the University of Kentucky bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Markey Cancer Center (P30CA177558). 13C-enriched standards were obtained from NIH Common Fund Metabolite Standards Synthesis Core (http://www.metabolomicsworkbench.org/standards/index.php). We thank John Sherman for critically reading and editing the manuscript.

Material and Methods Mice C57BL/6 and NSG mice were purchased from Envigo (formly Harlan) and the Jackson Laboratory.

Pmel transgenic mice (B6.Cg-Thy1a/Cy Tg(TcraTcrb)8Rest) were purchased from the Jackson Laboratory [79]. Mice at 7–12 weeks of age were used. All mice were kept in specific pathogen– free conditions within the Animal Resource Center at the Research Institute at Nationwide Children’s Hospital and Baylor College of Medicine. Animal protocols were approved by the Institutional Animal Care and Use Committee of the Research Institute at Nationwide Children’s Hospital and Baylor College of Medicine.

Tumor cell culture and reagents LAN-1, a GD2-positive tumor cell line, and B16-F10 cell lines were purchased from ATCC and were grown in RPMI 1640 and DMEM media (Corning Cellgro, Thermo Fisher Scientific, Grand Island, NY) with 10% fetal calf serum (Gibco-Invitrogen, Carlsbad, CA) and 1% penicillin-

streptomycin (Corning) in a 37 ̊C humidified atmosphere of 95% air and 5% CO2, respectively.

HeLa (human cervical cancer cells, ATCC) cells were grown at 37 ̊C/5% CO2 in DMEM media supplemented with 10% fetal calf serum and 1% penicillin-streptomycin. Glucose-free DMEM was supplemented with 10% (v/v) heat-inactivated dialyzed fetal bovine serum, which was made

TM dialyzing against 100 volumes of distilled water (five changes in 3 days) using Slide-ALyzer G2 dialysis cassettes with cut-through MW size 2K (Thermo Fisher Scientific) at 4 °C. Forodesine Hydrocholoride was purchased from MedChem Express (Monmouth Junction, NJ). Anti-PNP and anti-actin antibodies were from Santa Cruz Biotechnology (Santa Cruz, CA, USA).

Human and mouse T cells isolation and culture PBMCs were collected from healthy donors, approved by Baylor College of Medicine review board. Mononuclear cells from peripheral blood (PBMCs) were isolated by Ficoll/Hypaque bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

density gradient centrifugation. In some experiment, human T cells were directly enriched from PBMC by negative selection using MojoSort™ Human CD3 T Cell Isolation Kit (Biolegend, CA) following the manufacturer’s instructions. Isolated human mononuclear cells or enriched human T cells were either maintained in culture media containing 10 ng/ml IL-7 or stimulated human IL- 2 (100 U/ml) and plate-bound anti-CD3 and anti CD28 antibody. Plates were pre-coated with 1 μg/ml antibodies overnight at 4 °C. To generate GD2-CAR T cells, activated human T cells were transduced with GD2-CAR retrovirus on retronectin-coated nontissue culture plates and cultured with IL-2 for one week [81]. Mouse total T and CD8+ native T cells were enriched from spleens

and lymph nodes by negative selection using MACS system (Miltenyi Biotec, Auburn, CA) following the manufacturer’s instructions. For total T cells culture, freshly isolated total T cells with 75-80% CD3 positivity were either maintained in culture media containing 5 ng/ml IL-7 or were stimulated with human IL-2 (100 U/ml) as well as plate-bound anti-mCD3 (clone 145- 2C11) and anti-mCD28 (clone 37.51) antibodies. Plates were pre-coated with 2 μg/mL antibodies

overnight at 4 °C. For mouse and human T cell CFSE dilution analysis, 10-20 x106 cells were pre- incubated for 10 min in 4 μM CFSE (Invitrogen) diluted in PBS plus 5% FBS before culture. For CD8+ T cells activation and culture, naive CD8 T cells were activated by plate-bound antibodies and incubated with recombinant mouse IL-2 (100 U/mL) and IL-12 5 ng/mL for 5 days. For Pmel+ CD8+ T cell activation and culture, splenocytes from Pmel were isolated and culture with 1µM human gp100 (hgp100) (Genscript) and 30 IU/mL recombinant human IL-2 (PeproTech Inc) in complete media for 5-7 days [142]. The cells were then cultured in RPMI 1640 media supplemented with 10% (v/v) heat-inactivated fetal bovine serum (FBS), 2 mM L-glutamine, 0.05

mM 2-mercaptoethanol, 100 units/mL penicillin and 100 μg/mL streptomycin at 37˚C in 5% CO2. Glucose free RPMI 1640 media that was supplemented with 10% (v/v) heat-inactivated dialyzed fetal bovine serum (DFBS) was used as basal conditional media for glucose and inosine reconstitution. DFBS was made dialyzing against 100 volumes of distilled water (five changes in

three days) using Slide-ALyzerTM G2 dialysis cassettes with cut-through MW size 2K (ThermoFisher Scientific) at 4˚C.

Flow cytometry For the analysis of surface markers, cells were stained in PBS containing 2% (w/v) BSA and the appropriate antibodies listed in table S1. For intracellular cytokine staining, T cells were stimulated bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

for 4-5 h with phorbol 12-myristate 13-acetate (PMA) and ionomycin in the presence of monensin before being stained according to the manufacturer's instructions (BD Bioscience). Flow cytometry data were acquired on Novocyte (ACEA Biosciences) or LSRII (Becton Dickinson) and were analyzed with FlowJo software (TreeStar). All the chemicals and antibodies used are listed in Table S1.

Metabolite screening and bioenergetics analysis Metabolite screening was performed using 96-well PM-M1 and PM-M2 phenotyping microarray for mammalian cells (BioLog Inc). Human or mouse activated T cells were washed twice with PBS, and resuspended in glucose and phenol red free DMEM media supplemented with 10%

dialyzed FBS and 100 U/mL IL-2 followed by immediate inoculation of 100 µL cells/well (1x106

cells/ml) into the Biolog plates. After 24 h incubation at 37˚C in a 5% CO2 incubator, 20 µL of Redox Dye Mix MB (Biolog Inc) was added to each well, and absorbance at 590 and 750 nm wavelengths were recorded at different time points.

CD8+ CTL tumor killing assay CTL tumor killing assay was performed using caspase-3/7 reagent (Essen BioScience, Ann Arbor, MI) and the IncuCyte ZOOM live-cell imaging system (Essen BioScience) which is placed in an

4 3 incubator at 37 °C and 5% CO2. LAN-1 cells, (1.5x10 cells /well) and B16F10 (1.5x10 cells/well) were plated in 96 well plates and allowed to grow until 20% confluence was achieved. The media was replaced and target cells were co-cultured with GD2-CAR T cells or hgp100 activated Pmel T cells respectively in 10:1 (effector: target) ratios in glucose free media or with 2 mM glucose or Inosine or adenosine, and caspase 3/7 reagent was added at 1:1000 dilution to each well. Dead cells, which are positive for Caspase-3/7, were monitored and quantified automatically acquired at regular intervals by the IncuCyte software.

Tumor xenograft and T cell in vivo imaging

For the LAN-1 xenograft, 1.5x106 LAN-1 tumor cells were mixed in 100 µl matrigel (Corning)

and were subcutaneously inoculated in the dorsal left and right flanks of NSG mice. 8 x106 GD2- CAR-T or GD2-CAR-T-Luciferase cells were intravenously injected into tumor-bearing mice when tumor grew to about 4-6 mm in diameter (around 6-8 days). For inosine treatments, inosine bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

(Sigma) was administered (300 mg/kg in PBS) by oral gavage daily after CAR-T cell administration and throughout the experiment. For T cell in vivo imaging, the images were captured using IVIS imaging system (Xenogen) after i.v injection of 150 mg/kg D-luciferin (Xenogen, Alameda, CA) at day 4 and day 7 after GD2-CAR-T-Luciferase cells administration. Photon emission was analyzed by constant region-of-interest (ROI) drawn over the tumor region and the signal measured as total photon/sec/cm2/steridian (p/s/cm2/sr).

For B16F10 melanoma model, female C57BL6 mice were inoculated with 1×105 cells in the flank subcutaneously at day 0 and treated on days 1 (200 μg), 4 and 7 (100 μg) with anti-PDL1 antibody. Inosine (300 mg/kg) was administered by oral gavage every day, until animals reach end point and

tumor volume (mm3) and overall survival were assessed throughout the experiment. To evaluate the tumor infiltrating immune cells, after 10 and 15 days of inosine treatment, tumors were dissected and dissociated using gentle MACS™ Dissociators according to manufacturer’s instructions. Cells were stained with surface antibodies and analyzed using flow cytometry. In

adoptive transfer experiments, C57BL/6 mice were injected (s.c.) with 1X105 B16F10 melanoma cells and animals were irradiated sublethaly (500cGy) after 6 days of tumor cell inoculation. On

day 7, 4X106 active Pmel T cells were injected (i.v.) and inosine (300 mg/kg oral gavage) was administered daily and tumor size was monitored until animals reach the endpoint.

Metabolite extraction and analysis by ion chromatography-ultra high resolution-Fourier transform mass spectrometry (IC-UHR-FTMS) and NMR

13 Cells were cultured in glucose-free media with 2 mM C6-glucose (Cambridge Isotope Laboratories)

13 or [ C5]-ribose-inosine (Omicron Biochemicals) for 24 h at 37 °C and were then washed 3 times in cold PBS before metabolic quenching in cold acetonitrile and harvested for metabolite extraction as described previously [143]. The polar extracts were reconstituted in nanopure water before analysis on a Dionex ICS-5000+ ion chromatography system interfaced with a Thermo Fusion Orbitrap Tribrid mass spectrometer (Thermo Fisher Scientific) as previously described [144] using a m/z scan range of 80-700. Peak areas were integrated and exported to Excel via the Thermo TraceFinder (version 3.3) software package before natural abundance correction [145]. The isotopologue distributions of metabolites were calculated as the mole fractions as previously described [146]. The number of moles of each metabolite was determined by calibrating the natural bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

abundance-corrected signal against that of authentic external standards. The amount was normalized to the amount of extracted protein, and is reported in nmol/mg protein.

Polar extracts reconstituted in D2O (> 99.9%, Cambridge Isotope Laboratories, MA) containing

0.5 mmole/L d6-2,2-dimethyl-2-silapentane-5-sulfonate (DSS) as internal standard were analyzed

by 1D 1H and 1H{13C}-HSQC NMR on a 14.1 T DD2 NMR spectrometer (Agilent Technologies,

CA). 1D 1H spectra were acquired using the standard PRESAT pulse sequence with 512 transients, 16384 data points, 12 ppm spectral width, an acquisition time of 2 s and a 6 s recycle time with weak irradiation on the residual HOD signal during the relaxation delay. The raw fids were zero filled to 131072 points and apodized with 1 Hz exponential line broadening prior to fourier transformation. 1D HSQC spectra were recorded with an acquisition time of 0.25 s with GARP decoupling, and recycle time of 2 s over a spectral width of 12 ppm, with, 1024 transients. The HSQC spectra were then apodized with unshifted Gaussian function and 4 Hz exponential line broadening and zero filled to 16k data points before Fourier transformation. Metabolites were

assigned by comparison with in-house [147] and public NMR databases. Metabolite and their 13C isotopomers were quantified using the MesReNova software (Mestrelab, Santiago de Compostela, Spain) by peak deconvolution. The peak intensities of metabolites obtained were converted into

nmoles by calibration against the peak intensity of DSS (27.5 nmoles) at 0 ppm for 1H spectra and

that of phosphocholine at 3.21 ppm (nmoles determined from 1D 1H spectra) for HSQC spectra before normalization with mg protein in each sample.

siRNA transfection in HeLa cells The siRNA oligonucleotides corresponding to human PNP (Purine nucleoside phosphorylase) were purchased from Fisher. siRNA oligonucleotides (20 nM) were transfected into HeLa cells using Lipofectamine RNAiMAX reagent (Invitrogen). After 72 h of transfection, immunoblots were carried out to examine the knockdown of targeted proteins.

Electroporation of human T cells PBMC cells were stimulated with plate-bound anti-CD3 and anti-CD28 antibodies for two days

before electroporation. Cells were centrifuged and washed once with PBS. 1×106 cells were resuspended in 100 μL electroporation buffer T (Thermo Fisher, Waltham, MA) and 100 nM bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

siRNA oligonucleotides corresponding to human PNP was added. Electroporation was performed at 2150 V 20 ms 1 pulses settings for stimulated PBMC cells using Neon electroporation device (Thermo Fisher, Waltham, MA). Immediately after electroporation, the cells were plated in 12- well plate with 100 IU/ml IL-2 and incubated at 37°C.

qPCR and western blot analysis.

Total RNA was isolated using the Quick-RNATM MiniPrep Kit (Zymo Research) and was reverse transcribed using random hexamer and M-MLV Reverse Transcriptase (Invitrogen). SYBR green-

based quantitative RT-PCR was performed using the BIO-RAD CFX96TMReal-Time System. The

−ΔΔC relative gene expression was determined by the comparative CT method also referred to as the 2 T method. The data were presented as the fold change in gene expression normalized to an internal reference gene (beta2-microglobulin) and relative to the control (the first sample in the group).

−ΔΔC Fold change=2 T=[( CTgene of interst- CTinternal reference)]sample A-=[( CTgene of interst- CTinternal reference)]sample B. Samples for each experimental condition were run in triplicate PCR reactions. Primer sequences were obtained from PrimerBank [148]. The following pair of primers were used for detecting mouse PNP (5’- ATCTGTGGTTCCGGCTTAGGA-3’ and 5’-TGGGGAAAGTTGGGTATCTCAT-3’). Cell extracts were prepared and immunoblotted as previously described [149].

Metabolic activity analysis.

Fatty acid β-oxidation flux was determined by measuring the detritiation of [9,10-3H]-palmitic acid [150; 151]. One million T cells were suspended in 0.5ml fresh media. The experiment was initiated

by adding 3 µCi [9,10-3H]-palmitic acid complexed to 5% BSA (lipids free; Sigma) and, 2 h later, media were transferred to 1.5 mL microcentrifuge tubes containing 50 μL 5 N HCL. The microcentrifuge tubes were then placed in 20 mL scintillation vials containing 0.5 mL water with

3 3 the vials capped and sealed. H2O was separated from unmetabolized [9,10- H]-palmitic acid by

evaporation diffusion for 24 h at room temperature. A cell-free sample containing 3 µCi [9,10-3H]- palmitic acid was included as a background control.

14 14 Gluamine oxidation activity was determined by the rate of CO2 released from [U- C]-glutamine [152]. In brief, one-five million T cells were suspended in 0.5 ml fresh media. To facilitate the

14 collection of CO2, cells were dispensed into 7ml glass vials (TS-13028, Thermo) with a PCR tube

containing 50μl 0.2M KOH glued on the sidewall. After adding 0.5 μci [U-14C]-glutamine, the vials bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

were capped using a screw cap with rubber septum (TS-12713, Thermo). The assay was stopped 2h later by injection of 100μl 5N HCL and the vials were kept at room temperate overnight to trap

14 the CO2. The 50μl KOH in the PCR tube was then transferred to scintillation vials containing 10ml

scintillation solution for counting. A cell-free sample containing 0.5μci [U-14C]-glutamine was included as a background control.

Statistical analysis. P values were calculated with Student's t-test. P values smaller than 0.05 were considered significant, with P-values<0.05, P-values<0.01, and P-values<0.001 indicated as *, **, and ***, respectively.

Figure legends Figure 1. Inosine can support T effector cells proliferation and function in the absence of glucose. (A) Metabolite array from the PM-M1 Microplate (Biolog). Activated human T cells were incubated with various energy sources in a PM-M1 Microplate for 24 h, followed by Biolog redox dye mix MB incubation and measured spectrophotometrically at 590 nm. (B-C) Naive CD8+ T cells from C57BL/6 mice were activated by plate-bound anti-CD3 and anti-CD28 antibodies in complete media for 24 h, then the cells were switched to indicated conditional media and were cultured for 48 h. Cell proliferation and cell death were determined by CFSE dilution and 7AAD uptake, respectively. Data are representative of three independent experiments. (D) B16F10 tumor cells were co-cultured with activated Pmel T cells in the indicated conditional media, and tumor cell death was evaluated using caspase 3/7 reagent by IncuCyte ZOOM™. Error bars represent

mean ± SD (n=4). **, P=0.0072 for glucose free versus 2 mM Inosine. (E) Naive CD8+ T cells from C57BL/6 mice were activated by plate bound anti-CD3 and anti-CD28 antibodies and differentiated in the indicated conditional media for 4 days. The indicated proteins were quantified by intracellular staining following PMA and ionomycin stimulation.

Figure S1. Inosine can support T effector cells proliferation and function in the absence of glucose. (A) Metabolite array from the PM-M2 Microplate (Biolog). Activated human T cells were incubated with various energy sources in a PM-M2 Microplate for 24 h, followed by Biolog redox dye mix MB incubation and measured spectrophotometrically at 590 nm. (B-C) Naive CD8+ T cells from human PBMC were activated by plate-bound anti-CD3 and anti-CD28 antibodies in the bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

indicated conditional media for 5 days. Cell proliferation and cell death of active CD8+ T cells were determined by CFSE dilution and 7AAD uptake, respectively. Data are representative of three independent experiments. (D) LAN-1 cells were co-cultured with GD2-CAR T cells in the indicated conditional media and cell death of LAN-1 was monitored using caspase 3/7 fluorescent substrate by live cell imaging and quantified using the IncuCyte ZOOM™ analyzer. Error bars represent standard deviation (n=4). ***, P<0.001 for glucose free versus 2 mM Inosine. (E) The indicated proteins in GD2-CAR T cells were quantified by intracellular staining following PMA and ionomycin stimulation.

Figure S2. Adenosine cannot support T effector cells proliferation and function in the absence of glucose. (A-B) Naive CD8+ T cells from C57BL/6 mice or from human PBMC were activated by plate-bound anti-CD3 and anti-CD28 antibodies in the indicated conditional media for 3-5 days. Cell proliferation and cell death of active CD8+ T cells were determined by CFSE dilution and 7AAD uptake, respectively. Data are representative of three independent experiments. (C) B16F10 melanoma cells were co-cultured with activated Pmel T cell in the indicated conditional media, and tumor cell death was evaluated using caspase 3/7 reagent by IncuCyte ZOOM™. Error bars represent standard deviation (n=4). **, P =0.007 for 2 mM glucose versus 2 mM Adenosine. Data are representative of two independent experiments. (D) Naive CD8+ T cells from C57BL/6 mice were activated by plate bound anti-CD3 and anti-CD28 antibodies and differentiated in the indicated conditional media for 4 days. The indicated proteins were quantified by intracellular staining following PMA and ionomycin stimulation. (E) LAN-1 cells were co- cultured with GD2-CAR T cells in the indicated conditional media and cell death of LAN-1 was monitored using caspase 3/7 fluorescent substrate by IncuCyte ZOOM™. Error bars represent standard deviation (n=4). ***, P<0.001 for 2 mM Glucose versus 2 mM Adenosine. Data are representative of two independent experiments. (F) The indicated effector molecules in GD2-CAR T cells were quantified by intracellular staining following PMA and ionomycin stimulation.

Figure 2. The ribose moiety of inosine can replace glucose and feed into the central carbon

13 13 metabolism in T effector cells. (A) Diagram of [ C5]-inosine or [ C6]-Glucose uptake and conversion to ribose-1-phosphate (R-1-P) or glucose-6-phosphate (G-6-P), respectively, which subsequently enters the downstream PPP, glycolysis and Krebs cycle metabolic pathways. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

¨denoted the uniformly 13C label positions of the ribose moiety of inosine and all carbons of

13 13 glucose. (B-C) Active human T cells were incubated in [ C6]-Glucose (Glc) or [ C5]-ribose-inosine (Ino) for 24 h, extracted as described in methods, and analyzed for PPP metabolites (B) and glycolytic/Krebs cycle metabolites (C) by IC-UHR-FTMS. Glc6P: glucose-6-phosphate; R1P: ribose-1-phosphate; R5P: ribose-5-phosphate; X5P: xylulose-5-phosphate; Sed7P: sedoheptulose- 7-phosphate; Gly3P: glyceraldehyde-3-phosphate; Ery4P: erythrose-4-phosphate; G6PDH: glucose-6-phosphate dehydrogenase; TK: transketolase; TA: transaldolase; Fruc6P: fructose-6- phosphate; aKG: a-ketoglutarate; Glu-GSH: glutamyl unit of glutathione; PDH: pyruvate

dehydrogenase; PCB: pyruvate carboxylase; ME: malic enzyme; ●: 12C; ●: 13C derived either from the PDH or PCB-initiated Krebs cycle reactions, or from the reverse ME reaction. Solid and dashed arrows represent single- and multi-step reactions, single and double-headed arrows refer to

irreversible and reversible reactions, respectively. Numbers in the X-axis represent those of 13C atoms in given metabolites.

Figure S3. Inosine does not support T effector cell proliferation by enhancing glutamine and fatty acids catabolism or through purine nucleotide salvage. (A) Naive CD8+ T cells from C57BL/6 mice were activated by plate-bound anti-CD3 and anti- CD28 antibodies in complete media for 24 h, then the cells were switched to indicated conditional media and were cultured for 24 h. Metabolic fluxes of glutaminolysis and fatty acid β-oxidation

14 14 3 (FAO) were measured by the generation of CO2 from [U- C]-glutamine and H2O from from [9,

10-3H]-palmitic acid, respectively. Error bars represent standard deviation from the mean of triplicate samples. Data are representative of two independent experiments. (B) Naive CD8+ T cells from C57BL/6 mice (upper) and human PBMC (lower) were activated by plate-bound anti- CD3 and anti-CD28 antibodies in complete media for 24 h, then cells were switched to indicated culture condition for 3-5 days. Cell proliferation of active CD8+ T cells was determined by CFSE dilution. Data are representative of two independent experiments. (C) Diagram of inosine uptake and breakdown into ribose-1-phosphate (Ribose-1-P) and hypoxanthine, entering central carbon catabolism and the purine nucleotide salvage pathway, respectively. (D) Naive CD8+ T cells from C57BL/6 mice were activated by plate-bound anti-CD3 and anti-CD28 antibodies for 24 h, then cells were switched to indicated conditional media for 72 h. Cell proliferation and cell death were bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

determined by CFSE dilution (upper) and 7AAD uptake (lower), respectively. Data are representative of three independent experiments.

Figure 3. The purine nucleoside phosphorylase (PNP) is required for inosine-dependent mouse T effector cell proliferation and effector functions. (A) Diagram of purine nucleoside phosphorylase (PNP) inhibitor Foroesine (Foro) in blocking the breakdown of inosine into hypoxanthine and R-1-P. (B) PNP protein and mRNA expression levels in mouse T cells at the indicated time points upon activation by plate-bound anti-CD3 and anti- CD28 antibodies were determined by immunoblot (upper) and qPCR (lower), respectively. * indicates a nonspecific band recognized by PNP antibody. Error bars represent standard deviation from the mean of triplicate samples. Data are representative of two independent experiments. (C) Activated mouse T cells were incubated without glucose (background), with glucose or with inosine, as well as in combination with increased concentrations of Foro (0.1 μM, 0.5 μM, and 2 μM) for 24 h, followed by Biolog redox dye mix MB incubation and measured spectrophotometrically at 590 nm. (D) Naive CD8+ cells from C57BL/6 mice were activated by plate-bound anti-CD3 and anti-CD28 antibodies in complete media for 24 h, then the cells were switched to the indicated conditional media in combination with 2 μM Foro for 72 h. Cell proliferation and cell death were determined by CFSE dilution (upper) and 7AAD uptake (lower), respectively. Data are representative of three independent experiments. (E) B16F10 tumor cells were co-cultured with activated Pmel T cells in the presence of inosine with or without Foro, and tumor cell death was evaluated using caspase 3/7 reagent by IncuCyte ZOOM™. Error bars represent mean ± SD (n=4). **, P<0.01 for 2 mM Inosine versus 2 mM Inosine + 2 μM Foro. Data are representative of two independent experiments. (F) Naive CD8+ T cells from C57BL/6 mice were activated by plate bound anti-CD3 and anti-CD28 antibodies and differentiated in the indicated conditional media with or without 2 μM Foro for 4 days. The indicated proteins were quantified by intracellular staining following PMA and ionomycin stimulation. Data are representative of three independent experiments.

Figure S4. The purine nucleoside phosphorylase (PNP) is required for inosine-dependent human T effector cell proliferation and effector functions. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

(A) Activated human T cells were incubated without glucose (background), with glucose or with inosine in combination with increased concentrations of Foro (0.1 μM, 0.5 μM, and 2 μM) for 24 h, followed by Biolog redox dye mix MB incubation and measured spectrophotometrically at 590 nm. (B) Naive CD8+ T cells from human PBMC were activated by plate-bound anti-CD3 and anti- CD28 antibodies in the indicated conditional media with or without 2 μM Foro for 5 days. Cell proliferation and cell death of active CD8+ T cells were determined by CFSE dilution (upper) and 7AAD uptake (lower), respectively. Data are representative of three independent experiments. (C) LAN-1 cells were co-cultured with GD2-CAR T cells in the presence of inosine with or without Foro and cell death of LAN-1 was determined by using caspase 3/7 fluorescent substrate with live cell imaging analysis (IncuCyte ZOOM™). Error bars represent standard deviation (n=4). ***, P<0.001 for 2 mM Inosine versus 2 mM Inosine + 2 μM Foro. (D) The indicated proteins were quantified by intracellular staining following PMA and ionomycin stimulation. Data are representative of three independent experiments. (E) Human T cells from human PBMC were activated by plate-bound anti-CD3 and anti-CD28 antibodies for 2 days. Activated human T cells were electroporated with scrambled siRNA or PNP siRNA using Neon system and cultured for 2 days. PNP protein expression levels were determined by immunoblot (left). Cells were then incubated without glucose (background), with glucose or with inosine for 24 h, followed by Biolog redox dye mix MB incubation for 2 h and measured spectrophotometrically at 590 nm (right). (F) Proliferation curves of human T cells transfected with scrambled siRNA (upper) or PNP siRNA (lower) cultured in the indicated conditional media were determined by counting cell number daily. Error bars represent standard deviation (n=3). **, P<0.01 for 2 mM Glucose versus 2 mM Inosine in PNP siRNA transfected cells (lower). Data are representative of three independent experiments.

Figure 4. PNP inhibitor forodesine suppresses inosine catabolism in T effector cells.

13 (A) Diagram of PNP inhibitor Forodesine (Foro) blocking the catabolism of [ C5]-inosine into R- 1-P and its subsequent entrance into the PPP, Glycolysis and Krebs cycle. ¨denoted the uniformly

13C label positions of the ribose moiety of inosine. (B-C) Active human T cells were incubated in

13 [ C5]-Ino with or without Foro for 24 h, extracted, and analyzed as described in methods for PPP metabolites (B) and glycolytic/Krebs cycle metabolites (C) by IC-UHR-FTMS and by 1D HSQC NMR for inosine. All symbols and abbreviations are as described in Figure 2. Numbers in the X- bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

axis represent those of 13C atoms in given metabolites. Values represent mean ± SEM (n=3). *, **, ***, and ***** denote p values ≤0.05, 0.01, 0.001, and 0.00001, respectively.

13 13 Figure S5. PNP inhibitor forodesine blocks C incorporation from [ C5]-ribose-inosine into

13 central metabolites but has little effect on [ C6]-glucose catabolism The same experiment as in Figure 4 was performed for active human T cells ± Foro in the presence

13 13 of [ C5]-inosine or [ C6]-Glc for 24 h. The polar extracts from both tracer experiments were

analyzed by 1D HSQC NMR for 13C abundance (spectra as shown). Selected metabolites were

quantified as 13C µmoles/g protein using the N-methyl resonance of phosphocholine (NMe-

13 PCholine) as an internal standard, which are shown as bar graphs for the [ C5]-inosine (A) and

13 [ C6]-glucose tracer (B) experiments. Values are average ± SEM (n=3). Dashed line denotes the expected peak position of the H1-glucose resonance of glycogen. The proton resonances used for

13 13 quantification were: C3-Lac/Ala – the H3 resonances of lactate/Ala; C-Gluta – the H4-Glu

resonance of GSH + GSSG with minor contribution of H2,5 resonance of citrate; 13C-Ino, 13C-Glu,

13C-Asp, 13C-AXP, and 13C-UXP – H1’, H4, H3, and H1’ resonances of inosine, Glutamate, Aspartate, and adenine/uracil nucleotides, respectively.

Figure 5. Transformed cells display diverse capacity to utilize inosine as a carbon source. (A) HeLa cell growth curves in the indicated conditional media were determined by live cell imaging analysis (IncuCyte ZOOM™). Error bars represent mean ± SD (n=4). ***, P<0.001 for 2 mM Inosine versus Glucose free. Data are representative of three independent experiments. (B) LAN-1 cells were cultured in the indicated conditional media and cell growth curves were monitored and analyzed by IncuCyte ZOOM™. Error bars represent mean ± SD (n=4). ***, P<0.001 for 2 mM Glucose versus 2 mM Inosine. Data are representative of three independent

13 13 experiments. (C-D) HeLa cells were incubated with [ C6]-Glc or [ C5]-Ino for 24 h, extracted as described in Methods, and analyzed for PPP metabolites (C) and glycolytic/Krebs cycle metabolites (D) by IC-UHR-FTMS, respectively. All symbols and abbreviations are as described

in Figure 2. Numbers in the X-axis represent those of 13C atoms in given metabolites. Values represent mean ± SEM (n=3).

Figure S6. Transformed cells display diverse capacity to utilize inosine as a carbon source. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

(A) The indicated cell lines were cultured without glucose (background), with glucose or with inosine, and cell growth curves were monitored by live cell imaging analysis (IncuCyte ZOOM™). Cell confluences of the indicated cell lines cultured with glucose at 72-96 h were set to 100%. Error bars represent mean ± SD (n=4). **, P<0.01 and ***, P<0.001 for Glucose versus Inosine, respectively. (B) HeLa cells were incubated without glucose (background), with glucose or with inosine, as well as in combination with increased concentrations of Foro (0.1 μM, 0.5 μM, and 2 μM), and cell growth was monitored by live cell imaging analysis (IncuCyte ZOOM™). The confluences of HeLa cells cultured with glucose at 60 h were set to 100%. Error bars represent mean ± SD (n=4). Data are representative of two independent experiments. (C) HeLa cells were transfected with scrambled siRNA or PNP siRNA for 3 days. Cells were then switched to media without glucose (background), with either glucose or inosine, and cell confluence was determined by live cell imaging analysis (IncuCyte ZOOM™). The confluences of HeLa cells in the presence of glucose at 96 h were set to 100%. Error bars represent standard deviation from mean of quadruplicate samples (left). PNP protein expression levels were determined by immunoblot (right). Data are representative of two independent experiments.

Figure 6. Inosine supplement enhances immunotherapy in targeting solid tumor. (A) Murine melanoma xenograft model was established in C57BL/6 mice by subcutaneously inoculation of B16F10 tumor cells. The indicated experimental mice were treated with IgG control (i.p at day 1, 4 and 7), inosine (oral gavage every day), anti-PDL1 antibody (i.p. at day 1, 4 and 7), and anti-PDL1 antibody (i.p. at day 1, 4 and 7) + inosine (oral gavage daily). Tumor size and mice survival were monitored. Error bars represent mean ± SEM (n=10). ***, P<0.001 for anti-PDL1 versus anti-PDL1+Inosine (left). **, P=0.0018 for anti-PDL1 versus anti-PDL1+Inosine (right). Data are representative of two independent experiments. (B) C57BL/6 mice were injected (s.c.) with B16F10 melanoma cells and sublethally irradiated (500cGy) at day 6 after tumor cell

inoculation. One day later, mice were i.v. injected with activated Pmel CD8+ T cells (4×106 cells/mouse). Mice were administered with Inosine 300 mg/kg/day by oral gavage from day 8 to 20. Tumor size and mice survival were monitored. Error bars represent mean ± SEM (n=10). **, P=0.0091 for Pmel versus Pmel+Inosine (left). ***, P<0.001 for Pmel versus Pmel+Inosine (right). Data are representative of two independent experiments. (C) Human neuroblastoma xenograft model was established in NSG mice by subcutaneously inoculation of LAN-1 neuroblastoma cells. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

The indicated experimental mice were treated with control (PBS i.v. at day 6 when tumors reach

100-150 mm3), inosine (300 mg/kg oral gavage daily starting from day 6), GD2-CAR-T cells

(8×106 cells/mouse i.v at day 6 when tumors grow to 100-150 mm3), and GD2-CAR-T cells (8×106

cells/mouse i.v at day 6 when tumors grow to 100-150 mm3) + inosine (300 mg/kg oral gavage daily starting from day 6), respectively. Tumor growth and mice survival were monitored. Error bars represent mean ± SEM (n=16). ***, P<0.001 for CAR-T versus CAR-T+Inosine (left). *, P<0.05 for CAR-T versus CAR-T+Inosine (right). Data are representative of two independent experiments.

Figure S7. Inosine supplement prolongs CAR-T cell proliferation and survival in tumor environment. (A) Murine melanoma xenograft model was established in C57BL/6 mice by subcutaneously inoculation of B16F10 tumor cells. T cell infiltration in tumor was monitored at indicated time by flow cytometry after surface staining of anti-CD45, anti-CD3 and anti-CD8 antibodies. Gating strategy for flow cytometry analysis of leucocytes (CD45+), T cells (CD3+), and effector T cells (CD3+CD8+) (top panel); Values represent mean ± SEM (n=3). *, P< 0.05 for anti-PDL1 versus anti-PDL1+ inosine and **, P< 0.001 for Control versus anti-PDL1. (B) Human neuroblastoma xenograft model was established in NSG mice by subcutaneously inoculation of LAN-1 neuroblastoma cells, followed by i.v. administration of GD2-CAR-T-Luciferase cells only or in combination with oral gavage of inosine (300 mg/kg/day) when tumor grow to 4-6 mm in diameter. T cell infiltration in tumor was monitored at indicated time by IVIS imaging. Error bars represent mean ± SEM (n=5). **, P< 0.01 for CAR-T only versus CAR-T + inosine at Day 7. Data are representative of two independent experiments.

bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

References [1] D. Finlay, and D.A. Cantrell, Metabolism, migration and memory in cytotoxic T cells. Nature reviews. Immunology 11 (2011) 109-17. [2] R. Wang, and D.R. Green, Metabolic checkpoints in activated T cells. Nature immunology 13 (2012) 907-15. [3] E.L. Pearce, and E.J. Pearce, Metabolic pathways in immune cell activation and quiescence. Immunity 38 (2013) 633-43. [4] S.E. Weinberg, L.A. Sena, and N.S. Chandel, Mitochondria in the regulation of innate and adaptive immunity. Immunity 42 (2015) 406-17. [5] L.A. O'Neill, R.J. Kishton, and J. Rathmell, A guide to immunometabolism for immunologists. Nature reviews. Immunology 16 (2016) 553-65. [6] M.D. Buck, R.T. Sowell, S.M. Kaech, and E.L. Pearce, Metabolic Instruction of Immunity. Cell 169 (2017) 570-586. [7] E.H. Ma, M.C. Poffenberger, A.H. Wong, and R.G. Jones, The role of AMPK in T cell metabolism and function. Current opinion in immunology 46 (2017) 45-52. [8] C.H. Patel, and J.D. Powell, Targeting T cell metabolism to regulate T cell activation, differentiation and function in disease. Current opinion in immunology 46 (2017) 82-88. [9] H. Zeng, and H. Chi, mTOR signaling in the differentiation and function of regulatory and effector T cells. Current opinion in immunology 46 (2017) 103-111. [10] G. Lian, J.R. Gnanaprakasam, T. Wang, R. Wu, X. Chen, L. Liu, Y. Shen, M. Yang, J. Yang, Y. Chen, V. Vasiliou, T.A. Cassel, D.R. Green, Y. Liu, T.W. Fan, and R. Wang, Glutathione de novo synthesis but not recycling process coordinates with glutamine catabolism to control redox homeostasis and directs murine T cell differentiation. eLife 7 (2018). [11] M. Slack, T. Wang, and R. Wang, T cell metabolic reprogramming and plasticity. Molecular immunology 68 (2015) 507-12. [12] J.C. Rathmell, E.A. Farkash, W. Gao, and C.B. Thompson, IL-7 enhances the survival and maintains the size of naive T cells. J Immunol 167 (2001) 6869-76. [13] K.A. Frauwirth, J.L. Riley, M.H. Harris, R.V. Parry, J.C. Rathmell, D.R. Plas, R.L. Elstrom, C.H. June, and C.B. Thompson, The CD28 signaling pathway regulates glucose metabolism. Immunity 16 (2002) 769-77. [14] S.R. Jacobs, C.E. Herman, N.J. Maciver, J.A. Wofford, H.L. Wieman, J.J. Hammen, and J.C. Rathmell, Glucose uptake is limiting in T cell activation and requires CD28- mediated Akt-dependent and independent pathways. J Immunol 180 (2008) 4476-86. [15] E.L. Pearce, M.C. Walsh, P.J. Cejas, G.M. Harms, H. Shen, L.S. Wang, R.G. Jones, and Y. Choi, Enhancing CD8 T-cell memory by modulating fatty acid metabolism. Nature 460 (2009) 103-7. [16] R. Wang, C.P. Dillon, L.Z. Shi, S. Milasta, R. Carter, D. Finkelstein, L.L. McCormick, P. Fitzgerald, H. Chi, J. Munger, and D.R. Green, The Transcription Factor Myc Controls Metabolic Reprogramming upon T Lymphocyte Activation. Immunity 35 (2011) 871-82. [17] V.A. Gerriets, and J.C. Rathmell, Metabolic pathways in T cell fate and function. Trends Immunol 33 (2012) 168-73. [18] G.J. van der Windt, B. Everts, C.H. Chang, J.D. Curtis, T.C. Freitas, E. Amiel, E.J. Pearce, and E.L. Pearce, Mitochondrial Respiratory Capacity Is a Critical Regulator of CD8(+) T Cell Memory Development. Immunity (2012). bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[19] M. Angela, Y. Endo, H.K. Asou, T. Yamamoto, D.J. Tumes, H. Tokuyama, K. Yokote, and T. Nakayama, Fatty acid metabolic reprogramming via mTOR-mediated inductions of PPARgamma directs early activation of T cells. Nature communications 7 (2016) 13683. [20] M.D. Buck, D. O'Sullivan, R.I. Klein Geltink, J.D. Curtis, C.H. Chang, D.E. Sanin, J. Qiu, O. Kretz, D. Braas, G.J. van der Windt, Q. Chen, S.C. Huang, C.M. O'Neill, B.T. Edelson, E.J. Pearce, H. Sesaki, T.B. Huber, A.S. Rambold, and E.L. Pearce, Mitochondrial Dynamics Controls T Cell Fate through Metabolic Programming. Cell 166 (2016) 63-76. [21] S.J. Bensinger, M.N. Bradley, S.B. Joseph, N. Zelcer, E.M. Janssen, M.A. Hausner, R. Shih, J.S. Parks, P.A. Edwards, B.D. Jamieson, and P. Tontonoz, LXR signaling couples sterol metabolism to proliferation in the acquired immune response. Cell 134 (2008) 97-111. [22] J.A. Wofford, H.L. Wieman, S.R. Jacobs, Y. Zhao, and J.C. Rathmell, IL-7 promotes Glut1 trafficking and glucose uptake via STAT5-mediated activation of Akt to support T-cell survival. Blood 111 (2008) 2101-11. [23] E.L. Carr, A. Kelman, G.S. Wu, R. Gopaul, E. Senkevitch, A. Aghvanyan, A.M. Turay, and K.A. Frauwirth, Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation. J Immunol 185 (2011) 1037-44. [24] R.D. Michalek, V.A. Gerriets, S.R. Jacobs, A.N. Macintyre, N.J. MacIver, E.F. Mason, S.A. Sullivan, A.G. Nichols, and J.C. Rathmell, Cutting edge: Distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets. J Immunol 186 (2011) 3299-303. [25] D.K. Finlay, E. Rosenzweig, L.V. Sinclair, C. Feijoo-Carnero, J.L. Hukelmann, J. Rolf, A.A. Panteleyev, K. Okkenhaug, and D.A. Cantrell, PDK1 regulation of mTOR and hypoxia-inducible factor 1 integrate metabolism and migration of CD8+ T cells. The Journal of experimental medicine 209 (2012) 2441-53. [26] Y. Kidani, H. Elsaesser, M.B. Hock, L. Vergnes, K.J. Williams, J.P. Argus, B.N. Marbois, E. Komisopoulou, E.B. Wilson, T.F. Osborne, T.G. Graeber, K. Reue, D.G. Brooks, and S.J. Bensinger, Sterol regulatory element-binding proteins are essential for the metabolic programming of effector T cells and adaptive immunity. Nature immunology 14 (2013) 489-99. [27] S.I. Grivennikov, F.R. Greten, and M. Karin, Immunity, inflammation, and cancer. Cell 140 (2010) 883-99. [28] R.D. Schreiber, L.J. Old, and M.J. Smyth, Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science 331 (2011) 1565-70. [29] W.H. Fridman, F. Pages, C. Sautes-Fridman, and J. Galon, The immune contexture in human tumours: impact on clinical outcome. Nature reviews. Cancer 12 (2012) 298-306. [30] N.P. Restifo, M.E. Dudley, and S.A. Rosenberg, Adoptive immunotherapy for cancer: harnessing the T cell response. Nature reviews. Immunology 12 (2012) 269-81. [31] T.F. Gajewski, H. Schreiber, and Y.X. Fu, Innate and adaptive immune cells in the tumor microenvironment. Nature immunology 14 (2013) 1014-22. [32] A.K. Palucka, and L.M. Coussens, The Basis of Oncoimmunology. Cell 164 (2016) 1233- 47. [33] D. Mittal, M.M. Gubin, R.D. Schreiber, and M.J. Smyth, New insights into cancer immunoediting and its three component phases--elimination, equilibrium and escape. Current opinion in immunology 27 (2014) 16-25. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[34] R. Roychoudhuri, R.L. Eil, and N.P. Restifo, The interplay of effector and regulatory T cells in cancer. Current opinion in immunology 33 (2015) 101-11. [35] D.E. Speiser, P.C. Ho, and G. Verdeil, Regulatory circuits of T cell function in cancer. Nature reviews. Immunology 16 (2016) 599-611. [36] H. Nishikawa, and S. Sakaguchi, Regulatory T cells in cancer immunotherapy. Current opinion in immunology 27 (2014) 1-7. [37] P. Sharma, and J.P. Allison, Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 161 (2015) 205-14. [38] C. Engblom, C. Pfirschke, and M.J. Pittet, The role of myeloid cells in cancer therapies. Nature reviews. Cancer 16 (2016) 447-62. [39] V. Kumar, S. Patel, E. Tcyganov, and D.I. Gabrilovich, The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment. Trends Immunol 37 (2016) 208-220. [40] W. Zou, J.D. Wolchok, and L. Chen, PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Science translational medicine 8 (2016) 328rv4. [41] L.P. Andrews, A.E. Marciscano, C.G. Drake, and D.A. Vignali, LAG3 (CD223) as a cancer immunotherapy target. Immunological reviews 276 (2017) 80-96. [42] D.M. Barrett, N. Singh, D.L. Porter, S.A. Grupp, and C.H. June, Chimeric antigen receptor therapy for cancer. Annual review of medicine 65 (2014) 333-47. [43] L. Chen, and X. Han, Anti-PD-1/PD-L1 therapy of human cancer: past, present, and future. The Journal of clinical investigation 125 (2015) 3384-91. [44] S.A. Rosenberg, and N.P. Restifo, Adoptive cell transfer as personalized immunotherapy for human cancer. Science 348 (2015) 62-8. [45] P. Sharma, and J.P. Allison, The future of immune checkpoint therapy. Science 348 (2015) 56-61. [46] A.D. Fesnak, C.H. June, and B.L. Levine, Engineered T cells: the promise and challenges of cancer immunotherapy. Nature reviews. Cancer 16 (2016) 566-81. [47] H.J. Jackson, S. Rafiq, and R.J. Brentjens, Driving CAR T-cells forward. Nature reviews. Clinical oncology 13 (2016) 370-83. [48] A.J. Minn, and E.J. Wherry, Combination Cancer Therapies with Immune Checkpoint Blockade: Convergence on Interferon Signaling. Cell 165 (2016) 272-5. [49] W.A. Lim, and C.H. June, The Principles of Engineering Immune Cells to Treat Cancer. Cell 168 (2017) 724-740. [50] D.E. Gilham, R. Debets, M. Pule, R.E. Hawkins, and H. Abken, CAR-T cells and solid tumors: tuning T cells to challenge an inveterate foe. Trends in molecular medicine 18 (2012) 377-84. [51] M. Sadelain, I. Riviere, and S. Riddell, Therapeutic T cell engineering. Nature 545 (2017) 423-431. [52] P. Sharma, S. Hu-Lieskovan, J.A. Wargo, and A. Ribas, Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell 168 (2017) 707-723. [53] J.J. Havel, D. Chowell, and T.A. Chan, The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nature reviews. Cancer 19 (2019) 133-150. [54] V.M. Konala, S. Adapa, and W.S. Aronow, Immunotherapy in Bladder Cancer. American journal of therapeutics (2019). [55] P.P. Hsu, and D.M. Sabatini, Cancer cell metabolism: Warburg and beyond. Cell 134 (2008) 703-7. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[56] M.G. Vander Heiden, L.C. Cantley, and C.B. Thompson, Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324 (2009) 1029-33. [57] R.A. Cairns, I.S. Harris, and T.W. Mak, Regulation of cancer cell metabolism. Nature reviews. Cancer 11 (2011) 85-95. [58] D. Hanahan, and R.A. Weinberg, Hallmarks of cancer: the next generation. Cell 144 (2011) 646-74. [59] P.S. Ward, and C.B. Thompson, Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer cell 21 (2012) 297-308. [60] C.V. Dang, MYC, metabolism, cell growth, and tumorigenesis. Cold Spring Harbor perspectives in medicine 3 (2013). [61] G.M. DeNicola, and L.C. Cantley, Cancer's Fuel Choice: New Flavors for a Picky Eater. Molecular cell 60 (2015) 514-23. [62] D. O'Sullivan, and E.L. Pearce, Targeting T cell metabolism for therapy. Trends Immunol 36 (2015) 71-80. [63] N.N. Pavlova, and C.B. Thompson, The Emerging Hallmarks of Cancer Metabolism. Cell metabolism 23 (2016) 27-47. [64] C.M. Cham, and T.F. Gajewski, Glucose availability regulates IFN-gamma production and p70S6 kinase activation in CD8+ effector T cells. Journal of immunology 174 (2005) 4670-7. [65] L. Antonioli, C. Blandizzi, P. Pacher, and G. Hasko, Immunity, inflammation and cancer: a leading role for adenosine. Nature reviews. Cancer 13 (2013) 842-57. [66] T. Wang, G. Liu, and R. Wang, The Intercellular Metabolic Interplay between Tumor and Immune Cells. Frontiers in immunology 5 (2014) 358. [67] C.H. Chang, J. Qiu, D. O'Sullivan, M.D. Buck, T. Noguchi, J.D. Curtis, Q. Chen, M. Gindin, M.M. Gubin, G.J. van der Windt, E. Tonc, R.D. Schreiber, E.J. Pearce, and E.L. Pearce, Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression. Cell 162 (2015) 1229-41. [68] P.C. Ho, J.D. Bihuniak, A.N. Macintyre, M. Staron, X. Liu, R. Amezquita, Y.C. Tsui, G. Cui, G. Micevic, J.C. Perales, S.H. Kleinstein, E.D. Abel, K.L. Insogna, S. Feske, J.W. Locasale, M.W. Bosenberg, J.C. Rathmell, and S.M. Kaech, Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses. Cell 162 (2015) 1217-28. [69] S. Kleffel, C. Posch, S.R. Barthel, H. Mueller, C. Schlapbach, E. Guenova, C.P. Elco, N. Lee, V.R. Juneja, Q. Zhan, C.G. Lian, R. Thomi, W. Hoetzenecker, A. Cozzio, R. Dummer, M.C. Mihm, Jr., K.T. Flaherty, M.H. Frank, G.F. Murphy, A.H. Sharpe, T.S. Kupper, and T. Schatton, Melanoma Cell-Intrinsic PD-1 Receptor Functions Promote Tumor Growth. Cell 162 (2015) 1242-56. [70] C. Herbel, N. Patsoukis, K. Bardhan, P. Seth, J.D. Weaver, and V.A. Boussiotis, Clinical significance of T cell metabolic reprogramming in cancer. Clinical and translational medicine 5 (2016) 29. [71] D.H. Munn, and A.L. Mellor, IDO in the Tumor Microenvironment: Inflammation, Counter-Regulation, and Tolerance. Trends Immunol 37 (2016) 193-207. [72] G. Andrejeva, and J.C. Rathmell, Similarities and Distinctions of Cancer and Immune Metabolism in Inflammation and Tumors. Cell metabolism 26 (2017) 49-70. [73] R.J. Kishton, M. Sukumar, and N.P. Restifo, Metabolic Regulation of T Cell Longevity and Function in Tumor Immunotherapy. Cell metabolism 26 (2017) 94-109. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[74] X. Xu, J.N.R. Gnanaprakasam, J. Sherman, and R. Wang, A Metabolism Toolbox for CAR T Therapy. Frontiers in oncology 9 (2019) 322. [75] L.Z. Shi, R. Wang, G. Huang, P. Vogel, G. Neale, D.R. Green, and H. Chi, HIF1alpha- dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. The Journal of experimental medicine 208 (2011) 1367-76. [76] B.R. Bochner, M. Siri, R.H. Huang, S. Noble, X.H. Lei, P.A. Clemons, and B.K. Wagner, Assay of the multiple energy-producing pathways of mammalian cells. PLoS One 6 (2011) e18147. [77] W.W. Overwijk, A. Tsung, K.R. Irvine, M.R. Parkhurst, T.J. Goletz, K. Tsung, M.W. Carroll, C. Liu, B. Moss, S.A. Rosenberg, and N.P. Restifo, gp100/pmel 17 is a murine tumor rejection antigen: induction of "self"-reactive, tumoricidal T cells using high- affinity, altered peptide ligand. The Journal of experimental medicine 188 (1998) 277-86. [78] W.W. Overwijk, D.S. Lee, D.R. Surman, K.R. Irvine, C.E. Touloukian, C.C. Chan, M.W. Carroll, B. Moss, S.A. Rosenberg, and N.P. Restifo, Vaccination with a recombinant vaccinia virus encoding a "self" antigen induces autoimmune vitiligo and tumor cell destruction in mice: requirement for CD4(+) T lymphocytes. Proceedings of the National Academy of Sciences of the United States of America 96 (1999) 2982-7. [79] W.W. Overwijk, M.R. Theoret, S.E. Finkelstein, D.R. Surman, L.A. de Jong, F.A. Vyth- Dreese, T.A. Dellemijn, P.A. Antony, P.J. Spiess, D.C. Palmer, D.M. Heimann, C.A. Klebanoff, Z. Yu, L.N. Hwang, L. Feigenbaum, A.M. Kruisbeek, S.A. Rosenberg, and N.P. Restifo, Tumor regression and autoimmunity after reversal of a functionally tolerant state of self-reactive CD8+ T cells. The Journal of experimental medicine 198 (2003) 569-80. [80] M.A. Pule, B. Savoldo, G.D. Myers, C. Rossig, H.V. Russell, G. Dotti, M.H. Huls, E. Liu, A.P. Gee, Z. Mei, E. Yvon, H.L. Weiss, H. Liu, C.M. Rooney, H.E. Heslop, and M.K. Brenner, Virus-specific T cells engineered to coexpress tumor-specific receptors: persistence and antitumor activity in individuals with neuroblastoma. Nature medicine 14 (2008) 1264-70. [81] J.A. Craddock, A. Lu, A. Bear, M. Pule, M.K. Brenner, C.M. Rooney, and A.E. Foster, Enhanced tumor trafficking of GD2 chimeric antigen receptor T cells by expression of the chemokine receptor CCR2b. Journal of immunotherapy 33 (2010) 780-8. [82] G. Burnstock, Purinergic signalling--an overview. Novartis Foundation symposium 276 (2006) 26-48; discussion 48-57, 275-81. [83] G. Burnstock, Purinergic signalling and disorders of the central nervous system. Nature reviews. Drug discovery 7 (2008) 575-90. [84] H.K. Eltzschig, M.V. Sitkovsky, and S.C. Robson, Purinergic signaling during inflammation. The New England journal of medicine 367 (2012) 2322-33. [85] C. Cekic, and J. Linden, Purinergic regulation of the immune system. Nature reviews. Immunology 16 (2016) 177-92. [86] J.N. Rashida Gnanaprakasam, R. Wu, and R. Wang, Metabolic Reprogramming in Modulating T Cell Reactive Oxygen Species Generation and Antioxidant Capacity. Frontiers in immunology 9 (2018) 1075. [87] A. Bzowska, E. Kulikowska, and D. Shugar, Purine nucleoside phosphorylases: properties, functions, and clinical aspects. Pharmacology & therapeutics 88 (2000) 349-425. [88] R.G. Silva, J.E. Nunes, F. Canduri, J.C. Borges, L.M. Gava, F.B. Moreno, L.A. Basso, and D.S. Santos, Purine nucleoside phosphorylase: a potential target for the development of bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

drugs to treat T-cell- and apicomplexan parasite-mediated diseases. Current drug targets 8 (2007) 413-22. [89] A. Korycka, J.Z. Blonski, and T. Robak, Forodesine (BCX-1777, Immucillin H)--a new purine nucleoside analogue: mechanism of action and potential clinical application. Mini reviews in medicinal chemistry 7 (2007) 976-83. [90] A. Al-Kali, V. Gandhi, M. Ayoubi, M. Keating, and F. Ravandi, Forodesine: review of preclinical and clinical data. Future oncology 6 (2010) 1211-7. [91] A. Kratz, M. Ferraro, P.M. Sluss, and K.B. Lewandrowski, Case records of the Massachusetts General Hospital. Weekly clinicopathological exercises. Laboratory reference values. The New England journal of medicine 351 (2004) 1548-63. [92] N. Psychogios, D.D. Hau, J. Peng, A.C. Guo, R. Mandal, S. Bouatra, I. Sinelnikov, R. Krishnamurthy, R. Eisner, B. Gautam, N. Young, J. Xia, C. Knox, E. Dong, P. Huang, Z. Hollander, T.L. Pedersen, S.R. Smith, F. Bamforth, R. Greiner, B. McManus, J.W. Newman, T. Goodfriend, and D.S. Wishart, The human serum metabolome. PLoS One 6 (2011) e16957. [93] J.R. Mayers, and M.G. Vander Heiden, Famine versus feast: understanding the metabolism of tumors in vivo. Trends in biochemical sciences 40 (2015) 130-40. [94] C. Commisso, S.M. Davidson, R.G. Soydaner-Azeloglu, S.J. Parker, J.J. Kamphorst, S. Hackett, E. Grabocka, M. Nofal, J.A. Drebin, C.B. Thompson, J.D. Rabinowitz, C.M. Metallo, M.G. Vander Heiden, and D. Bar-Sagi, Macropinocytosis of protein is an amino acid supply route in Ras-transformed cells. Nature 497 (2013) 633-7. [95] T. Mashimo, K. Pichumani, V. Vemireddy, K.J. Hatanpaa, D.K. Singh, S. Sirasanagandla, S. Nannepaga, S.G. Piccirillo, Z. Kovacs, C. Foong, Z. Huang, S. Barnett, B.E. Mickey, R.J. DeBerardinis, B.P. Tu, E.A. Maher, and R.M. Bachoo, Acetate is a bioenergetic substrate for human glioblastoma and brain metastases. Cell 159 (2014) 1603-14. [96] S.K. Shukla, T. Gebregiworgis, V. Purohit, N.V. Chaika, V. Gunda, P. Radhakrishnan, K. Mehla, Pipinos, II, R. Powers, F. Yu, and P.K. Singh, Metabolic reprogramming induced by ketone bodies diminishes pancreatic cancer cachexia. Cancer & metabolism 2 (2014) 18. [97] C.H. Chang, J.D. Curtis, L.B. Maggi, Jr., B. Faubert, A.V. Villarino, D. O'Sullivan, S.C. Huang, G.J. van der Windt, J. Blagih, J. Qiu, J.D. Weber, E.J. Pearce, R.G. Jones, and E.L. Pearce, Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 153 (2013) 1239-51. [98] E. Kun, P. Talalay, and H.G. Williams-Ashman, Studies on the Ehrlich ascites tumor. I. The enzymic and metabolic activities of the ascitic cells and the ascitic plasma. Cancer research 11 (1951) 855-63. [99] H. Harrington, Effect of glucose and various nucleosides on purine synthesis by Ehrlich ascites tumor cells in vitro. The Journal of biological chemistry 233 (1958) 1190-3. [100] M. Cappiello, D. Barsacchi, A. Del Corso, M.G. Tozzi, M. Camici, U. Mura, and P.L. Ipata, Purine salvage as a metabolite and energy saving mechanism in the ocular lens. Current eye research 11 (1992) 435-44. [101] Y.F. Xu, F. Letisse, F. Absalan, W. Lu, E. Kuznetsova, G. Brown, A.A. Caudy, A.F. Yakunin, J.R. Broach, and J.D. Rabinowitz, Nucleotide degradation and ribose salvage in yeast. Molecular systems biology 9 (2013) 665. [102] S. Tabata, M. Yamamoto, H. Goto, A. Hirayama, M. Ohishi, T. Kuramoto, A. Mitsuhashi, R. Ikeda, M. Haraguchi, K. Kawahara, Y. Shinsato, K. Minami, A. Saijo, M. Hanibuchi, bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

Y. Nishioka, S. Sone, H. Esumi, M. Tomita, T. Soga, T. Furukawa, and S.I. Akiyama, Thymidine Catabolism as a Metabolic Strategy for Cancer Survival. Cell reports 19 (2017) 1313-1321. [103] A.L. Koch, Some enzymes of nucleoside metabolism of Escherichia coli. The Journal of biological chemistry 223 (1956) 535-49. [104] K. Hammer-Jespersen, Nucleoside catabolism. In Metabolism of Nucleotides. in: A. Munch-Petersen, (Ed.), Nucleosides and Nucleobases in Microorganisms, Academic Press, New York, 1983, pp. 203-258. [105] R. Schuch, A. Garibian, H.H. Saxild, P.J. Piggot, and P. Nygaard, Nucleosides as a carbon source in Bacillus subtilis: characterization of the drm-pupG operon. Microbiology 145 ( Pt 10) (1999) 2957-66. [106] M.G. Tozzi, M. Camici, L. Mascia, F. Sgarrella, and P.L. Ipata, Pentose phosphates in nucleoside interconversion and catabolism. The FEBS journal 273 (2006) 1089-101. [107] T. Rimaux, G. Vrancken, B. Vuylsteke, L. De Vuyst, and F. Leroy, The pentose moiety of adenosine and inosine is an important energy source for the fermented-meat starter culture Lactobacillus sakei CTC 494. Applied and environmental microbiology 77 (2011) 6539-50. [108] R.D. Lange, W.H. Crosby, D.M. Donohue, C.A. Finch, J.G. Gibson, 2nd, M.T. Mc, and M.M. Strumia, Effect of inosine on red cell preservation. The Journal of clinical investigation 37 (1958) 1485-93. [109] A.W. Konings, Comparison of inosine and glucose as a substrate for energy metabolism in isolated rat-thymus nuclei. Biochimica et biophysica acta 189 (1969) 125-8. [110] M.M. Strumia, and P.V. Strumia, The preservation of blood for transfusion. IX. The effect of increased pH and addition of inosine only or adenine and inosine on the red cell function. The Journal of laboratory and clinical medicine 79 (1972) 863-72. [111] A.R. Fernando, D.M. Armstrong, J.R. Griffiths, W.F. Hendry, E.P. O'Donoghue, D. Perrett, J.P. Ward, and J.E. Wickham, Enhanced preservation of the ischaemic kidney with inosine. Lancet 1 (1976) 555-7. [112] S.M. Jarvis, J.D. Young, M. Ansay, A.L. Archibald, R.A. Harkness, and R.J. Simmonds, Is inosine the physiological energy source of pig erythrocytes? Biochimica et biophysica acta 597 (1980) 183-8. [113] R.B. Jennings, and C. Steenbergen, Jr., Nucleotide metabolism and cellular damage in myocardial ischemia. Annual review of physiology 47 (1985) 727-49. [114] M.D. Devous, Sr., and E.D. Lewandowski, Inosine preserves ATP during ischemia and enhances recovery during reperfusion. The American journal of physiology 253 (1987) H1224-33. [115] A. Mathew, M. Grdisa, and R.M. Johnstone, Nucleosides and glutamine are primary energy substrates for embryonic and adult chicken red cells. Biochemistry and cell biology = Biochimie et biologie cellulaire 71 (1993) 288-95. [116] M.S. Jurkowitz, M.L. Litsky, M.J. Browning, and C.M. Hohl, Adenosine, inosine, and guanosine protect glial cells during glucose deprivation and mitochondrial inhibition: correlation between protection and ATP preservation. Journal of neurochemistry 71 (1998) 535-48. [117] S.E. Haun, J.E. Segeleon, V.L. Trapp, M.A. Clotz, and L.A. Horrocks, Inosine mediates the protective effect of adenosine in rat astrocyte cultures subjected to combined glucose- oxygen deprivation. Journal of neurochemistry 67 (1996) 2051-9. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[118] T.W. Traut, Physiological concentrations of purines and pyrimidines. Molecular and cellular biochemistry 140 (1994) 1-22. [119] I. Kaufmann, A. Hoelzl, F. Schliephake, T. Hummel, A. Chouker, L. Lysenko, K. Peter, and M. Thiel, Effects of adenosine on functions of polymorphonuclear leukocytes from patients with septic shock. Shock (Augusta, Ga.) 27 (2007) 25-31. [120] P. Pellegatti, L. Raffaghello, G. Bianchi, F. Piccardi, V. Pistoia, and F. Di Virgilio, Increased level of extracellular ATP at tumor sites: in vivo imaging with plasma membrane luciferase. PLoS One 3 (2008) e2599. [121] J. Stagg, and M.J. Smyth, Extracellular adenosine triphosphate and adenosine in cancer. Oncogene 29 (2010) 5346-58. [122] P.L. Ipata, M. Camici, V. Micheli, and M.G. Tozz, Metabolic network of nucleosides in the brain. Current topics in medicinal chemistry 11 (2011) 909-22. [123] V. Kumar, Adenosine as an endogenous immunoregulator in cancer pathogenesis: where to go? Purinergic signalling 9 (2013) 145-65. [124] M.P. Abbracchio, G. Burnstock, A. Verkhratsky, and H. Zimmermann, Purinergic signalling in the nervous system: an overview. Trends in neurosciences 32 (2009) 19-29. [125] W.G. Junger, Immune cell regulation by autocrine purinergic signalling. Nature reviews. Immunology 11 (2011) 201-12. [126] X. Jin, R.K. Shepherd, B.R. Duling, and J. Linden, Inosine binds to A3 adenosine receptors and stimulates mast cell degranulation. The Journal of clinical investigation 100 (1997) 2849-57. [127] E.R. Giblett, J.E. Anderson, F. Cohen, B. Pollara, and H.J. Meuwissen, Adenosine- deaminase deficiency in two patients with severely impaired cellular immunity. Lancet 2 (1972) 1067-9. [128] R. Parkman, E.W. Gelfand, F.S. Rosen, A. Sanderson, and R. Hirschhorn, Severe combined immunodeficiency and adenosine deaminase deficiency. The New England journal of medicine 292 (1975) 714-9. [129] M.S. Hershfield, R.H. Buckley, M.L. Greenberg, A.L. Melton, R. Schiff, C. Hatem, J. Kurtzberg, M.L. Markert, R.H. Kobayashi, A.L. Kobayashi, and et al., Treatment of adenosine deaminase deficiency with polyethylene glycol-modified adenosine deaminase. The New England journal of medicine 316 (1987) 589-96. [130] A. Aiuti, F. Cattaneo, S. Galimberti, U. Benninghoff, B. Cassani, L. Callegaro, S. Scaramuzza, G. Andolfi, M. Mirolo, I. Brigida, A. Tabucchi, F. Carlucci, M. Eibl, M. Aker, S. Slavin, H. Al-Mousa, A. Al Ghonaium, A. Ferster, A. Duppenthaler, L. Notarangelo, U. Wintergerst, R.H. Buckley, M. Bregni, S. Marktel, M.G. Valsecchi, P. Rossi, F. Ciceri, R. Miniero, C. Bordignon, and M.G. Roncarolo, Gene therapy for immunodeficiency due to adenosine deaminase deficiency. The New England journal of medicine 360 (2009) 447-58. [131] M. Sukumar, J. Liu, Y. Ji, M. Subramanian, J.G. Crompton, Z. Yu, R. Roychoudhuri, D.C. Palmer, P. Muranski, E.D. Karoly, R.P. Mohney, C.A. Klebanoff, A. Lal, T. Finkel, N.P. Restifo, and L. Gattinoni, Inhibiting glycolytic metabolism enhances CD8+ T cell memory and antitumor function. The Journal of clinical investigation 123 (2013) 4479- 88. [132] A. Caro-Maldonado, R. Wang, A.G. Nichols, M. Kuraoka, S. Milasta, L.D. Sun, A.L. Gavin, E.D. Abel, G. Kelsoe, D.R. Green, and J.C. Rathmell, Metabolic reprogramming bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

is required for antibody production that is suppressed in anergic but exaggerated in chronically BAFF-exposed B cells. J Immunol 192 (2014) 3626-36. [133] V.A. Gerriets, R.J. Kishton, A.G. Nichols, A.N. Macintyre, M. Inoue, O. Ilkayeva, P.S. Winter, X. Liu, B. Priyadharshini, M.E. Slawinska, L. Haeberli, C. Huck, L.A. Turka, K.C. Wood, L.P. Hale, P.A. Smith, M.A. Schneider, N.J. MacIver, J.W. Locasale, C.B. Newgard, M.L. Shinohara, and J.C. Rathmell, Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation. The Journal of clinical investigation 125 (2015) 194-207. [134] G. Liu, Y. Bi, L. Xue, Y. Zhang, H. Yang, X. Chen, Y. Lu, Z. Zhang, H. Liu, X. Wang, R. Wang, Y. Chu, and R. Yang, Dendritic cell SIRT1-HIF1alpha axis programs the differentiation of CD4+ T cells through IL-12 and TGF-beta1. Proceedings of the National Academy of Sciences of the United States of America 112 (2015) E957-65. [135] O.U. Kawalekar, R.S. O'Connor, J.A. Fraietta, L. Guo, S.E. McGettigan, A.D. Posey, Jr., P.R. Patel, S. Guedan, J. Scholler, B. Keith, N.W. Snyder, I.A. Blair, M.C. Milone, and C.H. June, Distinct Signaling of Coreceptors Regulates Specific Metabolism Pathways and Impacts Memory Development in CAR T Cells. Immunity 44 (2016) 380-90. [136] L. Liu, Y. Lu, J. Martinez, Y. Bi, G. Lian, T. Wang, S. Milasta, J. Wang, M. Yang, G. Liu, D.R. Green, and R. Wang, Proinflammatory signal suppresses proliferation and shifts macrophage metabolism from Myc-dependent to HIF1alpha-dependent. Proceedings of the National Academy of Sciences of the United States of America 113 (2016) 1564-9. [137] M. Sukumar, J. Liu, G.U. Mehta, S.J. Patel, R. Roychoudhuri, J.G. Crompton, C.A. Klebanoff, Y. Ji, P. Li, Z. Yu, G.D. Whitehill, D. Clever, R.L. Eil, D.C. Palmer, S. Mitra, M. Rao, K. Keyvanfar, D.S. Schrump, E. Wang, F.M. Marincola, L. Gattinoni, W.J. Leonard, P. Muranski, T. Finkel, and N.P. Restifo, Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy. Cell metabolism 23 (2016) 63-76. [138] L. Fazekas, F. Horkay, V. Kekesi, E. Huszar, E. Barat, R. Fazekas, T. Szabo, A. Juhasz- Nagy, and A. Naszlady, Enhanced accumulation of pericardial fluid adenosine and inosine in patients with coronary artery disease. Life sciences 65 (1999) 1005-12. [139] C.E. Markowitz, S. Spitsin, V. Zimmerman, D. Jacobs, J.K. Udupa, D.C. Hooper, and H. Koprowski, The treatment of multiple sclerosis with inosine. Journal of alternative and complementary medicine 15 (2009) 619-25. [140] S. Spitsin, C.E. Markowitz, V. Zimmerman, H. Koprowski, and D.C. Hooper, Modulation of serum uric acid levels by inosine in patients with multiple sclerosis does not affect blood pressure. Journal of human hypertension 24 (2010) 359-62. [141] S.-P.D.I. Parkinson Study Group, M.A. Schwarzschild, A. Ascherio, M.F. Beal, M.E. Cudkowicz, G.C. Curhan, J.M. Hare, D.C. Hooper, K.D. Kieburtz, E.A. Macklin, D. Oakes, A. Rudolph, I. Shoulson, M.K. Tennis, A.J. Espay, M. Gartner, A. Hung, G. Bwala, R. Lenehan, E. Encarnacion, M. Ainslie, R. Castillo, D. Togasaki, G. Barles, J.H. Friedman, L. Niles, J.H. Carter, M. Murray, C.G. Goetz, J. Jaglin, A. Ahmed, D.S. Russell, C. Cotto, J.L. Goudreau, D. Russell, S.A. Parashos, P. Ede, M.H. Saint-Hilaire, C.A. Thomas, R. James, M.A. Stacy, J. Johnson, L. Gauger, J. Antonelle de Marcaida, S. Thurlow, S.H. Isaacson, L. Carvajal, J. Rao, M. Cook, C. Hope-Porche, L. McClurg, D.L. Grasso, R. Logan, C. Orme, T. Ross, A.F. Brocht, R. Constantinescu, S. Sharma, C. Venuto, J. Weber, and K. Eaton, Inosine to increase serum and cerebrospinal fluid urate in Parkinson disease: a randomized clinical trial. JAMA neurology 71 (2014) 141-50. bioRxiv preprint doi: https://doi.org/10.1101/766642; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.

[142] Y. Lou, G. Wang, G. Lizee, G.J. Kim, S.E. Finkelstein, C. Feng, N.P. Restifo, and P. Hwu, Dendritic cells strongly boost the antitumor activity of adoptively transferred T cells in vivo. Cancer research 64 (2004) 6783-90. [143] T.W.-M. Fan, Sample Preparation for Metabolomics Investigation. in: T.W.-M. Fan, A.N. Lane, and R.M. Higashi, (Eds.), The Handbook of Metabolomics: Pathway and Flux Analysis, Methods in Pharmacology and Toxicology. DOI 10.1007/978-1-61779-618- 0_11, Springer Science, New York, 2012, pp. 7-27. [144] T.W. Fan, M.O. Warmoes, Q. Sun, H. Song, J. Turchan-Cholewo, J.T. Martin, A. Mahan, R.M. Higashi, and A.N. Lane, Distinctly perturbed metabolic networks underlie differential tumor tissue damages induced by immune modulator beta-glucan in a two- case ex vivo non-small-cell lung cancer study. Cold Spring Harb Mol Case Stud 2 (2016) a000893. [145] H.N. Moseley, Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC bioinformatics 11 (2010) 139. [146] A.N. Lane, T.W. Fan, and R.M. Higashi, Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol 84 (2008) 541-88. [147] T.W.-M. Fan, and A.N. Lane, Structure-based profiling of Metabolites and Isotopomers by NMR. Progress in NMR Spectroscopy 52 (2008) 69-117. [148] A. Spandidos, X. Wang, H. Wang, and B. Seed, PrimerBank: a resource of human and mouse PCR primer pairs for gene expression detection and quantification. Nucleic Acids Res 38 (2010) D792-9. [149] R. Wang, G. He, M. Nelman-Gonzalez, C.L. Ashorn, G.E. Gallick, P.T. Stukenberg, M.W. Kirschner, and J. Kuang, Regulation of Cdc25C by ERK-MAP kinases during the G2/M transition. Cell 128 (2007) 1119-32. [150] A. Moon, and W.J. Rhead, Complementation analysis of fatty acid oxidation disorders. The Journal of clinical investigation 79 (1987) 59-64. [151] M. Buzzai, D.E. Bauer, R.G. Jones, R.J. Deberardinis, G. Hatzivassiliou, R.L. Elstrom, and C.B. Thompson, The glucose dependence of Akt-transformed cells can be reversed by pharmacologic activation of fatty acid beta-oxidation. Oncogene 24 (2005) 4165-73. [152] K. Brand, J.F. Williams, and M.J. Weidemann, Glucose and glutamine metabolism in rat thymocytes. Biochem J 221 (1984) 471-5.

A P - glucose 6 - - 9: 6: Glucose & - - E12: Inosine C5: Mannose A5 Polysaccharides D6: Fructose B1 Phospho PM-M1 100

80 60

40

20 0 % Relative Value to control Value Relative % -20 Metabolites

B Glucose free 2 mM Glucose 2 mM Inosine C Glucose free 2 mM Glucose 2 mM Inosine

31.7±1.4% 83.2±2.1% 80.2±1.9% 7AAD Count CD8+ CFSE CD8+ FSC-H

D E Glucose free 2 mM Glucose 2 mM Inosine

B 1.6% 21% 45.6% - Glucose free 2mM Glucose

2mM Inosine Granzyme

2.2% 25.9% 21.3% α ** - TNF

% tumor cell killing tumor% cell 1.2% 22% 35% γ - IFN Time (h) CD8+

Figure 1. Inosine can support T effector cells proliferation and function in the absence of glucose. A

PM-M2 100

80 Positive control

60

40

20 % Relative Value to control to Value Relative % 0 Metabolites

B C Glucose free 2 mM Glucose 2 mM Inosine Glucose free 2 mM Glucose 2 mM Inosine

33.5% 69.7% Count 68.4% 7AAD CD8+ CFSE CD8+ FSC-H

D E Glucose free 2 mM Glucose 2 mM Inosine

3.79% 31.2% Glucose free B 32.2% -

2mM Glucose

2mM Inosine Granzyme *** 23.2% 50.2% 60.1% α - TNF

% tumor cell killing tumor% cell 9.7% 23.8% 25.9% γ - IFN Time (h) CD8+

Figure S1. Inosine can support T effector cells proliferation and function in the absence of glucose. A B

Glucose free 2 mM Glucose 2 mM Adenosine Glucose free 2 mM Glucose 2 mM Adenosine Count Count CD8+ CFSE CD8+ CFSE

22.1% 66.9% 9.3% 39.3% 64.4% 27.4% 7AAD 7AAD CD8+ FSC-H CD8+ FSC-H C D Glucose free 2 mM Glucose 2 mM Adenosine B - 0.43% 20.2% 1.59% Glucose free 2mM Glucose 2mM Adenosine Granzyme ** 1.41% 15.5% 2.9% α - TNF

% tumor cell killing tumor% cell 0.27% 13.5% 1.08% γ - IFN

Time (h) CD8+

E F Glucose free 2 mM Glucose 2 mM Adenosine

B 5.4% 25.7% 13.4% Glucose free - 2mM Glucose 2mM Adenosine

** Granzyme

18.3% 49.2% 7.25% α - TNF % tumor cell killing tumor% cell

1.97% 23.9% 2.53% γ - IFN

Time (h) CD8+ Figure S2. Adenosine cannot support T effector cells proliferation and function in the absence of glucose. 250 250250 250Inosine InosineInosine 250 6 200 Inosine *** 6 6 200 200 *** *** 6 200 13C6Glc *** 13C6Glc13C6Glc Inosine 150 13C5Ino13C6Glc 6 200 O *** 1.0 150150 150 13C5Ino13C5Ino OO O 1.0 1.0 13C5Ino 13C6Glc1’ 1 1.0 R1P *** 0.8 R5P 100 150 N 13C5Ino1’ 1’ 1’ 1 1O 0.8 R1PR1P R1P****** ***0.80.8 1.00.8 R5P R5P****** *** 100100 100 NN NNH 1 0.80.8 0.8 ** R5P *** H NHNH NH PNP 1’ 13C6Glc **** ** R1P *** 0.8 50 A 100HH H PNPPNP N 13C6Glc13C6Glc13C6Glc 1 0.6 0.8 13C6Glc R5P *** Norm Inr/10 A A B 0.6 0.60.6 0.6 13C6Glc13C6Glc13C6Glc ** A NH 13C5Ino 5050 50 Norm Inr/10 Norm Inr/10 Norm Inr/10 N 0.60.6 0.6 NN NN H H PNP13C5Ino13C5Ino 13C5Ino 13C5Ino13C6Glc 50 NN AHH N H 0.4 13C5Ino13C5Ino13C5Ino 0.6 13C6Glc 0 5’ Norm Inr/10 0.6 00 0 5’ 5’ 5’ N 0.4 0.40.4 0.4 13C5Ino HO 5’ H Fraction 0.40.4 0.4 O 5’5’ 5’ 5 N Fraction PPP 13C5Ino Fraction Fraction Fraction Fraction HOHO HO Fraction Fraction Fraction Fraction Fraction 0 1 2 3 4 5 55 5 Fraction PPPPPPPPP 00 11 0 22 1 33 2 44 3 55 4 5 OO0 1’O 5’ P P C 0.2 0.4 * 1’1’ 1’ PP PP 0.2P5’ CC C 0.20.2 0.4 D HO Fraction 0.2 DD D ** * 13 O 0.20.2 0.2 5 Fraction PPP 0.8 Inosine * 250* * *0 1 13132 313 4 5 1’ P P C 0.80.8 0.8 InosineInosineInosine ****** ** OH ** **OH* *** * *C -Ino * 0.0 0.0 0.2 0.2 D *** *** OHOH OHOHOH InosineOH C555 -Ino-InoC5-Ino R1PR1P13R1P 0.00.0 0.0 0.00.0 0.0 13C6Glc 6 2000.8 *** * * * * 0 1 2 3 4 5 0 1 2 3 4 5 0.6 13C6Glc13C6Glc13C6Glc Inosine *** OH OH C -Ino00 11 02 2 13 3 24 4 35 5 4 5 0.000 11 02 2 13 3 24 4 35 5 4 5 0.0 0.60.6 0.6 13C5Ino 13C6Glc 5 R1P 13C5Ino13C5Ino13C5Ino 150 13C6Glc 0 1 2 3 0.74 5 0.4 0.6 13C5Ino O 1.0 0.70.7 0.7 0 1 2 3 4 5 0.40.4 0.4 1 13C5Ino1 13C6Glc0.8 Fraction Fraction 11 1 11 1 1’ 1 1 R1P 0.6*** 13C6Glc13C6Glc13C6GlcSed7P R5P *** PPP Fraction Fraction 13 0.6 0.7

Fraction Fraction 100 1 Fraction Fraction N PNP 0.811 1 0.6 0.6 Sed7PSed7PSed7P 0.213 BB 0.4 C CO-COInoNH2 11 1 ** 13C5Ino 0.20.2C 6-0.2Glucose B B G6PDH1 H 5 CO1CO2 2 2PNP 13C6Glc 0.50.5 13C5Ino13C5Ino13C5Ino 13C6Glc Fraction Fraction 0.6 13 50 A G6PDHG6PDH 1 0.5 0.50.6 1 13C6Glc Sed7P C5-Inosine Norm Inr/10 B PCO 0.6 0.0 0.2 N H 2 13C5Ino 0.40.4 0.5 13C5Ino 0.00.0 250 N G6PDH 0.4 0.4 13C5Ino 0.0 0 0.3 0.4 00 11 22 33 Inosine44 55 5’ 5’ R1P 0.4 0.30.3 0.3 E 0.4 HO Fraction E

Fraction Fraction 0 1 0 2 1 3 2 4 3 5 4 5 0.0 5 Fraction E E PPP

O 5 Fraction 6 200 *** 5 0 1 2 3 4 5 Fraction 66 66 1’ 5P P 5P P P P C 0.20.2 Fraction 0.3 13C6Glc 6 6 0 1 2 63P P 46 P5 NADPHNADPH* NADPH P PP P 0.2 0.2 0.20.2 D E 250 5 0.1 Fraction 150 13C5Ino 0.8 O * 6 13 6 1.0 77 P P 0.10.1 0.1 0.2 13 Inosine *** OH* *OH * CP-Ino NADPH 0.07 P P 7P P PP Inosine1313 13 1’ 5 X5PX5P R1P *** P0.8 P P 0.00.0P 0.0 6 1 CO 0.0 0.1 200100 CC***6-Glc-Glc Glc6PGlc6PN X5P0.8 X5P 2 TKTK R5P ***0.0 7 13C6GlcC 66-GlcC0.6 6-Glc 13C6Glc Glc6P NH13 TKTK ** 0 1 2 3 4 5 00 11 22 330 4P4 1 5 5 26 6P 737 4P 5 13 H PNP 13C6Glc Sed7PSed7PX5P 0 1 20 31 42 53 64 75 6 7 0.0 1.01.0 15050 13C5InoA 13C5Ino O C -Glc Glc6P 1.0 Sed7P0.6 Sed7P 13C6Glc TK 1.0 = 1.0Norm Inr/10 C 1.01.0 6 0.6 13C5Ino 0.70.7 0.7 0.4 1.0 1.0N N H G6PDH 0.8 13C5Ino0.7 0.7 0 1 2 3 4 5 6 7 Glc6PGlc6P **** 1’ 1 11 R1P *** R5P0.60.6 *** Ery4PEry4PSed7P 13C6Glc 0.80.8 1000 Glc6PGlc6P Fraction 1.0 N Glc1PGlc1P 0.8 0.4+ 1 0.6 Sed7P 0.8 0.8 ** ** 0.85’0.8 Glc1PNHGlc1P5’ 1.0 0.4 ** 1 ++ + 0.6 0.6 Ery4PEry4P 0.7 HO B Fraction CO 13C6Glc13C6Glc 0.2 0.8 HOGlc6P0.8 PNP 5 13C6Glc 2 Fraction 0.6 0.50.5 13C6Glc13C6GlcPPP 0.5 13C5Ino 0.60.6 50 13C6Glc0 113C6Glc A2 3 4 5 0.8 1’13C6Glc 13C6Glc** PGlc1P G6PDHP CP 13C6Glc0.5 0.5 13C6Glc 0.6 Ery4P Norm Inr/10 11 13C6Glc 0.6 13C6Glc 0.6 0.6 13C5Ino13C5Ino 1 1* N 13C6Glc P 0.8 11 0.2 13C5Ino 0.211 D + 13C5Ino13C5Ino PP 0.60.60.6 13C6Glc13C5Ino13C5InoN H 1 1 1 1 13C5Ino0.40.4 13C5Ino13C5Ino 0.4 0.8 0.0 *P * *0.6 * 13C5Ino13 13C5Ino 13C6Glc 0.4 0.4 0.4 13C5Ino13C5Ino 0.5 13C6Glc 0.40.4 0 Inosine *** 0.6 5’OH 13C5InoOH C -Ino1 NADPH 0.40.0 R5P 0.0 0.30.3 Fraction Fraction P Fraction Fraction 0.4 0.4 5’ 1 0.3 HO 5 Fraction 1 1300.4 0.4 1 2 3 4 5 **** P 0.6 5R1P Fraction 0.3 0.3 PPP 0.4 13C5InoE Fraction Fraction

Fraction Fraction O

13C5Ino 3 Fraction 0 1 2 3 4 5 ** 3 Fraction Fraction Fraction I 0.4 ** Fraction I 13C6Glc Fraction 0.4 P P 5 C -Glc1’ 0 1 C2 3 4 5 3 P0 1 2 Fraction 30.2 4 5 0.2 P 3 0.2 Fraction 0.2 0.6 I 0.4 Fraction 0.2 0.2 0.2 I * 6 Fraction J Glc6P6 6 0.2 P P PP D0.2 0.2 FF 0.3 0.2 Fraction J NADPH 13C5Ino 0.20.2 13J J 0.4 P ** Sed7P0.1 F F TK 0.1 3 Fraction 0.0 0.8 Inosine *** * 0.2* *0.2 I * Fraction 55 0.1 0.10.7 7 P 0.10.2 0.00.0 0.4 6 0.2 OH OH C5-Ino J 5P P0.0 5 PP 0.0 P P P F Hypoxanthine 0.0 66 0.00.01 131 0.2 R1P P PP P 0.00.0 13C6Glc 0.0 0 Fraction 1 2 3 4 5 6 6 Gly3PGly3PX5P 0.6 0 00.6 1 1 2 2 3 3 413C6Glc 4 5 5 6 6 0.0 0.0 C -Glc Glc6P 10 1 2 3 4 5 Gly3P5 Gly3P10 1 2 3 0.0TK 4 0.0 5 Sed7P0.1 0.2 0 1 2 B3 4 5 6 0.0 00 11 22 33 44 55 666 CO2 P P 00 11 22 13C5Ino 33 44 0 1 2 3 4 5 6 7 13C5Ino 0 1 02 13 24 35 G6PDH46 6 5 6 0.0 + 0 0.51 0 Sed7P2 1 3 2 4 3 4 0.0 Glc1PGlc1P1.0 0 1 2 3 4 5 6 R5PR5P 0.7 Gly3P 0.4 Glc1PGlc1P 1.0 R5PR5P 0.8 0.4 0.7 0 1 2 3 4 R-1-P G-6-P 0.0 1 1 0 1 2 3 4 5 6 0.80.8 13C6Glc Fraction Fraction Glc6P 1 0.8Fruc6P Fruc6P0.6 ****** Sed7P B 0.8 ** Glc1P Glc1PCO 1 R5P 0.3Fruc6P Fruc6P+ *** *** 0.6 Ery4P 0.2 0 1 2 3 4 5 0.8 2 TATA 0.6 0.5 13C5InoE 0.8 13C6Glc G6PDH0.10 5 TA 0.6 Fraction 13C6Glc13C6Glc 6 6 0.100.10 13C6Glc P P TAP 0.6 0.6 0.213C6Glc 13C6Glc 0.5 Fruc6P13C6Glc *** 4 0.6 13C5Ino P 1 NADPH0.10 Fruc6P P 0.413C5Ino13C5Ino 0.0 4 0.08P 0.6 Fruc6P ** 1 1 0.113C5Ino 1 TA 0.4 13C5Ino 4 4 0.08 Fruc6PFruc6P13C5Ino * * 0.101 7 0.40.4 13C5Ino 0.6 13C6Glc 0 1 2 3 4 135 0.4 0.08 0.08 13C6Glc 1 1 P P 0.4 P 0.4 0.3 E 6 13C6Glc Fraction 0.0 0.3 Fraction Fraction 13C5Ino

X5P Fraction 1 6C -Glc Glc6P4 0.06 0.4 13C6Glc13C6Glc **5 X5PFruc6PTK * Gly3P Fraction 6 Fraction 1 G 3 Fraction 1 66 6 0.06 0.08 1 0.2 Fraction 0.2 I Fraction 13C5Ino P P 1 1 0.2 6n P 0.06 NADPH0.06 13C5Ino 1 0.2 G0 1 2 P3 4 5 6 0.20.47 11 1 nn n 13C5Ino13C5InoJ 13C6Glc 1 Sed7P1 0.2 0.2 G G F 1.0 0.046 0.2 0.1 Fraction 1.0 1 0.04 0.06 5 7 0.7 0.1 130.01 4 1 0.04 0.04n 13C5Ino++ P P0.00.0 P 1 0.2 G Glc6P 1 4 6 H X5P + +P P 0.0 0.0 0.0 0.8 **C1 -Glc14 4 Glc6PGlc1P protein mole/g 0.02 0.0 H 6 TK 4 + 0 10.6 2 3 4 Ery4P5 6 0.0 6 protein mole/g 0.02 0.04 Gly3P 0 1 2 3 4 5 6 µ H 4 P 0 1 2 3 4 5 6 0.8 protein mole/g 0.02 H 6 P 0 1 2 3 4 5 6 7 1 4 protein mole/g 0.02 P P P 13C6Glc n µ 6 6 4P Sed7P 4P TA 0 1 02 +13 24 35 46 5 6 0.0 0 1 2 3 4 1 4 µ 1 4 P P P 0.5 n 13C6Glc0.00 µ 0 1 2 3 4 5 6 P P 13C6Glc 1.00.6 1 1 14 4 n n 0.00 P P HP P P P 0.7

13C5Ino protein mole/g 0.02 P 1.00.6 Glc1P0.00 0.00 1 R5P 16 0.4 4 0 1 2 3 4 5 6 PPP, Glycolysis and Krebs cycle 13C5Ino 0 1 2 3 4 5 6 µ 13C5InoP Glc6P13 ** 0 11 2 34 4 5 n6 P P 0.6P Ery4P P 0.8 0.80.4 13 Glc1P 0 1 02 13 24 35 46 5 6 0.00Fruc6P Ery4P+ 0.3 Fruc6P *** Fraction Fraction [ C-U]-Glycogen0.8 13C6Glc13 13 0.4 ** Fruc6PFruc6P Ery4PEry4P 0.5 [ C-U]-Glycogen Fruc6P Ery4P3 Fraction 13C6Glc I Fraction 13C6Glc TA 0.60.2 13C5Ino[ C [-U]-GlycogenC-U]-Glycogen1 0.10 0 1 2 3 4 5 6 P 0.2 F 0.6 13C6Glc P 0.6 13 J 1 1Fruc6P 0.4 Ery4P13C5Ino 0.2 [4 13C5InoC-U]-Glycogen 5 Fruc6P * 0.1 13C5Ino 0.40.0 Glycolysis 0.08 1 0.3 0.4 Fraction Fraction P P 6 0.40.0 Glycolysis** 0.0 13C6Glc Gly3P3 Fraction Fraction Fraction 0 1 2I 3 4 5 6 Glycolysis6 Fraction 0.2 1 Glycolysis 0.06 + P 0.2 F 0 11 2 J3 4 5 n6 13C5Ino P 0 11 2 3 40.2 G Glc1P0.2 Glycolysis5R5P 0.1 0.0 0.04P P P 6 0.0 0.80.0 + 0.0 0 1 2 3 4 5 6 1 4 H Gly3P Fruc6P *** 0 1 2 3 4 5 6 protein mole/g 0.02 6TA Ery4P 0 41 2 3 4 0 1 2 3 4 5 6 0.7Glc1P 10.10 4 n µ R5P P P 0.6P 13C6GlcP P 0.8 4 0.7 Fruc6P 0.00 Fruc6P 13C5Ino PEP 0.6 Glycolysis* 1 0.8 0.8 PEPPyruvate 0.08 0 1 2 3 4 5 6 0.4 Fruc6P *** 13 0.6 GlycolysisPyruvate13C6Glc 0.5 6 TA Fraction 0.6 13C6Glc 1 13C6Glc [ C-U]-Glycogen0.100.06 Glycolysis Fruc6P0.6 Ery4P13C6Glc 0.6 1 13C6Glcn 0.5 13C6Glc 13C5Ino 1 0.2 G 0.713C5Ino 0.44 13C5Ino Fruc6P0.8 * 13C5Ino C 0.4 13C5Ino 0.4 0.080.04 1 0.8 0.4 0.8 13C5Ino PEP 0.6 Pyruvate0.40.3 1 4 13C6Glc Lactate + 0.0 Fraction Fraction

6 Fraction Fraction Fraction 0.7 0.3 0.06 0.6HGlycolysis Lactate 1 0.7 Glycolysis protein mole/g 0.02 0.2 0.5 Fraction 0.2 13C5Ino 6 14 0.2 0 1 2 3G 4 5 6

µ 13C6Glc 0.6 113C6Glc 0.8 APEP 13C6Glc 1 n 1 4 0.7 Fraction n P P0.6 P P P PEP1 0.20.60.6 0.7 APyruvatePyruvateB 0.2 13C6Glc 13C5Ino 0.7 0.4 13C5Ino0.8 0.1 PEP Glycolysis0.8 0.040.00 13C5Ino 0.4 0.00.6 0.8 13C6GlcPEP 0.5 113C6Glc 4 0.60.1 GlycolysisPyruvateB 0.4 + 0.0 0.8 0.6 0.3 13C6Glc0.7 0.00.5 0.6 13C6GlcPyruvate Lactate0 1 2 H3 4 5 6 0.4 13C5Ino

PEP 0.0 protein mole/g 0.02 Glycolysis 13 Fraction 0.6 0 1 Pyruvate2 3 0.4 13 0.5 0.8 6 4 0 1 2 3 4 5 6 Fraction Fraction 13C5Ino 0.6 Fraction Fruc6P Ery4P 0.4 13C6Glc13C5Ino 0.00.6 Glycolysis13C6Glcµ 0.8 C6-Glc0.2 0.8 13 PEP0.40.6 0.2 13C5Ino13C6Glc0.70.6 [PyruvateC0.50 Glycolysis-U]-Glycogen0 1 113C5Ino 213C6Glc1 2 3 43 n 13C6Glc C P P P P P A 0.2 Fraction 0.61 13C6Glc0.8 C0.40.5 -Glc 13C6Glc 0.3 13C5Ino 0.4 0 0.001 2 3 Lactate 0.8 PEP Fraction 6 0.1 0.6 B Pyruvate0.3 0.4 Glycolysis13C5Ino 0.8 Lactate 0.2 C Fraction Fraction 0.6 Fraction 13C5Ino0.5 0.4 13C5Ino 0.8 1 13C5Ino0.6 13C6Glc0.4 1 0.2 Fraction 13C6Glc 1 0.4 0.0 13C5Ino6 1 0.20.4 0.7A13C5Ino 0.2 Glycolysis0.3 0 1 20.6 3 4 13C6Glc5 6 Lactate 0.4 0.6 1 13C6Glc0.2 0.0 A0.5 Fraction 13C6Glc13 0.31 1 0.0 1 13C6GlcLactate 13 0.8 0.4 B Fraction 0.8 Fruc6P0.6 Ery4P 0 1 2 13C5Ino Fraction 30.3 0.113C5Ino Glycolysis PEP 0.6 6 [ C-U]-Glycogen0.2 Fraction LactateLactate 13C5Ino PyruvatePyruvate Fraction B C -Glc Fraction 0.4 0.0 00.41 1 0.22 0.13 A 0.8 C 0.4 0.6 13C5Ino 0.0 13C6Glc 6 13C5Ino Fraction 0.2 0 1 2 3 13 1 0.00.2 3 A0.3 13C5Ino0.0 3 GlycolysisPyruvate0.6 30.2 B 0.4Lactate Lactate 13C6Glc 1 130.2 0.6 A0.4 Fraction 1’ 13C6Glc 0 1 0.5 2 3 0.0 0.1 13C6Glc 0 1 2 3 Fraction Fraction 13C6Glc Fraction 0.53 13C5Ino 13 C -GlcC 15- Ino 0.3 1 0.0 0.103 1 1 2 B 3 0.63 Lactate 0.4 Fraction Fraction 0 1 0.22 3 6 0.2 0.1 B1’ 0.2 Fraction 13C6Glc C 13C5Ino 6C 1-Glc 13C5InoA0.0 0.4CO Fraction 0 1 2 3 0.0 0.0 0.813C5Ino 0.6 0.4 C 0.5 0.0 6 0.2 13 0.2 2 13C5InoB0 0.0 1 CO2 3 0.4 Glycolysis0.213C6Glc Citrate 13 0.4 A 0.1 Lactate Fraction

13 1 C Pyruvate0.0-Glc 10 0.31 2 3 1CO 2 1 0 1 2 3 13C5Ino0.4 Fraction Fraction 13 C -Ino 0.03 6 6 PEP 3 B PDH 3 2 0 0.41 2 Lactate3 0.2 C Citrate 0 Fraction 1 2 313 0.1 1 1 CO

C5 -Glc 1 0 1 2 Fraction 3 0.0 13C5Ino 13C6Glc 0.4

C -Glc 1’ 6 6 0 Fraction 1 0.0 2 3 0.6 0.4 2 0.2 C 6 13 0.2 0.0 0 1C 2-Ino 3 0.2 PyruvatePEP 0.2 LactatePDH 0.5 C 0.0 0.3 E 13C6Glc C -Glc 1 A 5 3 0.0 1 3 3 Lactate1 Fraction 13C6Glc01 1 2 3 13C5Ino 13 6 5’0 CO1 2 3 1 6 Pyruvate0 1 2 3 1 1 1 0.2 CitrateC 0.3 E 13 1 1’ 2 3 0.1 1 CO BAcetyl 1 CoA3 3 Fraction 0.5 0 1 2 3 0.0

C6-Glc 6 5’ 0 2 1 2 3 0.40.4 13C5InoC0.2 0.0 Lactate 13C5Ino C -Ino6 0.0PEP 1’ PDH Pyruvate0.0 0.2 13C6Glc1 0.5 5 1 0.0CO 2 Pyruvate1 3 1 GlycolysisAcetylLactate3 CoA 3 Fraction Citrate 0 1 2 3

13 0.6 13 6 0 Pyruvate1 2 3PEP COPyruvate LactateCO 0.3 0.0E 0.4 0 1 2 3 0.2

3 1 21 3 3 Fraction 1 1’ 0 1 2 3 Citrate Fraction C -Glc 135’ C -Ino3 PEP 3 0 2 1 2 3PDH Lactate3 CO 13C5Ino0.1 0.5

6 65 1’0.6 Pyruvate 1 2 Lactate0.2 0.0 C 0.4 0.5 13C6Glc 1’ C -InoAspartate 3 PEPAcetyl CoA3 PDH CO3 Citrate0.5 0 1 2 E 3 0.5 5 5’13 Pyruvate 2 Lactate0.2CO 0.3 13C5Ino13C6Glc 0.1 Citrate

CO Fraction

1’ CO1 30.5 1 Aspartate 21 3 1 3 1 2 0.50 1Citrate 0.30.02 3E Citrate0.4

136 13C6Glc 2 C -Ino AcetylPEPCO 2 CoACO PDH Citrate 0.4 13C5Ino

13 0.6 0.4 1’ 5’ 5 CO2 2 1 0.4 0.10.0 0.5 0.2 0.0 13C6Glc C -Ino COPEP PDH 1 0 1 2 3 4 5 6 PEP PDH 1 Acetyl CoA Fraction

C -Ino13 5 Pyruvate2 13C6Glc PCB CO Lactate 13C6Glc Citrate 13C6Glc0.3 0.8 E

5 0.5 Aspartate0.3 0.6 J 13C5Ino 0.4 CO Citrate2 3 0 0.4 1 1 20.2 3 13C5Ino 3 5’ 3 Fraction E

C -Ino 13 PEP 2 PDH E 0.1 Citrate0.3 0 1 2 3 4 5 6 13 CO PCB 0.3 0.0 1 13C6Glc 13C5Ino

55’ 0.6 1’ 1 C6-Glc5’ JCO13C5Ino2 2 Acetyl4 CoA0.5 0.4 13C5Ino αKG 0.8 0.4 C -Ino13C6Glc0.5 AspartatePEP0.3 PDH 1 Citrate1 E0.1 0.2 5 Fraction 0.2 4 Acetyl CoA 1Acetyl CoA 0 1 0.32 3 4 5 6 13C6Glc 13C5Ino Fraction 0.6

13C5Ino0.5 5’ Aspartate CO1 PCB 2 1 Citrate0.2 0.3 0.0E4Citrate 0.20.8 13C6Glc αKG

13C6Glc Fraction

0.6 Fraction 0.313 J 0.4 0.2 AcetylCO4 CoA Fraction

0.1 5’ Acetyl2 CoA 1 6 0.4 0.2 0.00 113C5Ino 2 3 4 5 6 0.1 0.6 PDH PDH 1

0.6 C -Ino 0.6 PEP13C6GlcAsp 1 PCB 4 13C6Glc αKG0.8 13C5Ino 13C6Glc 5 0.4 13C5Ino AcetylOxaloacetate CoA 0.1 Fraction Isocitrate0.1

Fraction Fraction J 0.4

0.2 0.0 0.3 4 0.50.1 Aspartate 1 0.2 Citrate6 0 0.61 2 3 4 5 6 0.6 PCB 0.3 E F Aspartate Asp Fraction 13C6Glc0.8 13C5Ino 0.5 Aspartate 0.30.5 5’ J 13C5Ino 1 Citrate Oxaloacetate4 Citrate 0.1 13C5Ino Isocitrate0.0 αKG 0.4 Fraction Fraction 0.1 0.6 0.20 1 2 3 4 0.40.0 4 13C6Glc 6 1 0.0 0.0 0.6 Fraction F

0.5 Aspartate1 Asp 13C6GlcOxaloacetate 1 Acetyl CoA CitrateCitrate4 0.1 1 13C5Ino 0.20 1 2 13C6Glc3 α4 KG5 6 0.4 13C6Glc 0.4 NADPH PCB Isocitrate0.2 0.4 Fraction Fraction 0.20.1 4 13C5Ino 1 0.0 0.8 Fraction

0.0 0.5 Aspartate 1 0.3 0 J1 2 3 4 1 Citrate6 0 1 Fraction 2 3 4 5 6 0 1F 2 3 4 5 0.66 PCB PCB 13C6Glc1 PCB Asp 1 13C5Ino 0.6 0.4 13C5Ino 13C5Ino OxaloacetateNADPH 0.0 Isocitrate0.8 0.4 0.8 13C6Glc 0.2

0.3 J 0 1 2 30.10.3 0.0 4 J1 ME 1 0.1 04 1 2 3 Fraction 4 5 6 αKG 13C6Glc PCB 6 1 CO 0.0F 0.4 Fraction 0.8 0.3 J 13C5Ino NADPH0.2 Asp 1 Oxaloacetate4 4 1 4 0 Isocitrate1 2 3 40.2 5 6 2α KG 13C5Inoα KG0.6

0.5 Aspartate ME Citrate Fraction 0.4 Fraction Fraction PCB Fraction Fraction 0.2 1 40.00.2 13C5Ino 0 3 1 2 3 4 4 1 0.8 F CO 13C6Glc 0.3 J 1 ME 0.1 NADPH 4 0.0 6 0.6 13C6Glc0.2 α0.6KG0 1 2 32 4 13C6Glc5 0.0 Fraction Fraction 0.4 0.2 13C6Glc0 1 14 2 3 4 3 Asp14 CO 0.0 0.6 Fraction 13C5Ino

0.1 0.1 ME 6 1 4Oxaloacetate Krebs6 0 1 2 3 4 5 6 Isocitrate0.2 αKG13C6Glc 0.4 0 1 2 3 4 5

Fraction Fraction NADPH 0.2 Asp 4 Asp PCB 13C5Ino 13C5Ino 0.1 3 13C5InoPyruvate Oxaloacetate0.0 Oxaloacetate Isocitrate4 Isocitrate0.4 CO0 0.81 0.62 3 0.04 5 0.4 F 0.0 0.3 J 0.0 1Asp 1 6 αKetoglutarateF2 13C6Glc13C5InoGlu F Oxaloacetate4 Malate Krebs Fraction 0.1 3 Asp0.6 0 ME1Pyruvate Oxaloacetate2 3 4 46 IsocitrateIsocitrate CO0.4 0 αKG1 2 3 4 5

Fraction Fraction 0.0 0.2 0.0 Asp NADPH F 13C5Ino Fraction 0 Fraction 0.21 2 3 4 0 41 2 3 4 Oxaloacetate Cycle 2 Ketoglutarate Glu Pyruvate 4 Malate1 KetoglutarateIsocitrateKrebs 0.2 Glu0.6 0.4 α 0.2 1 0.0 0 1 2 3 NADPH4 3 0.5 Malate1 NADPHMalate 0.6 Krebs α Fraction F 13C6Glc0 1 2 3 4 5 0.11 0.6 Pyruvate1 NADPH 1 ME1 6 0.2 1 0 1 2 3ME 4Asp ME Malate4 KrebsCycle αKetoglutarate1 Fraction Glu13C5InoCO 2 0.0 1 0.40.6 Oxaloacetate13C6Glc1 0.5 Malate IsocitrateCO 0.0 0.4 0.2CO 0.0 0.5 PyruvatePyruvateMEMalateNADPH NADPH3 2 KetoglutarateF2 1 0.0Glu 0 1 2 3 4 5 3 1 3 Malate13C5Ino1 Malate 0.4 13C6Glc Krebs αCycleCOCO2 0.0 0 1 2 3 40.4 ME13C6Glc0.3 0.60.5 I 1Cycle 4 2 0 Fraction 1 2 3 4 5 0 1 2 3 4 5 3 4 CO 0.2 0.0 1 5 NADPH0.4 13C6Glc 4 13C5Ino Cycle 2 0 1 2 3 4 5 13C5Ino Fraction 0.2 PyruvateMalate 0.3 I Pyruvate1 3 0.3 PyruvateI 0.5 1 4 Malate 1 Krebs 5 α0Ketoglutarate 1 2 3 4 5 Glu5 MEMalate 0.3 I 13C5Ino0.6 Krebs CycleαKetoglutarate KetoglutarateCOGlu 0.5 Glu 0.1 13C6Glc4 Fraction 0.2 Krebs COα 0.0 2 Pyruvate Fraction 0.2 0.4 Malate1 2 5 0.6 0.6 Malate 4 Krebs αKetoglutarate Glu 1 3 Fraction 0.2 Malate CO 1 CO Glu Pyruvate0.1 0.6 0.00.3 I Malate13C5Ino0.5 0.1 Ketoglutarate!-Ketoglutarate2 0.5 0 1 Glu2 3 0.44 5 12 0.5 0.5 Malate 0.5 Malate4 Malate 1 Krebs α CO 1 5 0.6 0.1 0 1 2 4 3 4 0.4 13C6Glc 4 Cycle 2 Glu0.5 K 13C6Glc Glu

Fraction Fraction Malate Fumarate Succinyl CoA Pyruvate0.4 0.0 0.5 13C6Glc 0.2 0.0 Cycle4 Cycle 0.4 1 0.3 Glu 0.4 0.00.4 13C6Glc 13C5Ino KetoglutarateCO K Glu13C6Glc0.4 13C5Ino K 13C6Glc 0.60.5 00.4 1 2 3 0.1Malate 413C6Glc MalateFumarate 1.0 0.3 0 I 1 Krebs2 Cycle3 4 Succinyl α CoA 0.7 2Succinyl 0.5 CoA 0.3 0.6I 13C5Ino 13C5Ino Fumarate1 0.3 K 13C6Glc 0.35 Fumerate0.313C6Glc 0 11 I 2 3 4 FumarateSuccinate4 Cycle Succinyl CoA 5 113C5Ino 0.2 Glu 13C5Ino

0.6 Fraction 0.4 1.0 Fraction 1 0.3 0.5 0.3 IMalate 0.0 13C5Ino0.6 0.8 0.2 1.0 0.7 0.6 GSH 0.40.7 13C5Ino5 Fraction Fraction 0.2 0.5 0.6 1.0 1 0.7 0.2 5 Fumerate 13C6Glc Fraction 0.213C5Ino Succinate 13C6Glc 0.1CO K 13C6Glc 0.2 0.5 0.40.3 I 0 1 2 3 Fumerate40.1 Succinate 0.6 GSH 0.5 Fraction 13C6Glc 2 0.5 0.8 Fumarate Succinyl CoA 0.2 0.6 Fraction Fraction Fraction 0.2 Fumerate 0.5 1 Succinate Cycle0.8 CO 0.5 0.3 GSH 0.1 0.4 0.5 13C6Glc 0.6 Succinate 2 0.6 GSHCO Fraction 5 0.5 13C5Ino 0.4 13C6Glc0.6 13C5Ino0.1 13C6Glc0.8 13C5Ino 4 0.5 13C6Glc0.4 0.1 13C5Ino2 Glu Fraction Fraction 1.0 0.30.2 0.1 13C6Glc4 0.4 0.0 13C6Glc13C6Glc 13C6Glc CO0.7 2 L 0.5 0.1 0.50.0 13C6Glc 0.4 0.1 0.0 13C5Ino0.3 0.4 I 0.6 13C5Ino Succinate4 1 0.5 CO2 13C6Glc Glu 0.2 H Fumerate0.0 13C5Ino0.40.6 1 4 Succinate 0.6 0.4 LSuccinate13C5InoCO0.3 0.4 Glu K 13C6Glc 0.3 0.5 13C5Ino0 1 2 3 4 Succinate13C5Ino 0.6 0.0 GSH0.5 5 Fraction 0.4 Glu0.40 1 2 13C5Ino3 4 5

Fraction Fraction 2 0.20.1 13C5Ino Fraction 13C5Ino Fumarate 0.4 Succinyl CoA 0.8 Fraction 13C5Ino L H0 1 0.30.02 3 0.44 0.3 1 0.3 L K 0.4 13C6Glc0.0 0.3 0.0 Fraction Fraction 0.2 Fumarate13C6Glc0 1 2 3 4 4 G13C6Glc Succinyl 1CoA 0.50.2 10 1 2 3 4 0.15 K 13C6Glc 13C5Ino Fraction Fraction 0.2 Fraction H Succinyl0.3 CoA13C6Glc 0.3 Glu 0.10.40.0 0 H1 2 3 0.64 0.20.4 Fumarate1.00.4 Fraction 0.3 0.4 13C5Ino0.7K 0 1 13C6Glc20.3 3 4 5 0 1 2 3 4 5 Fraction Fraction Fraction Fraction Succinyl0.2 CoA Fraction Fraction G0.2 Fumarate Fraction CO 0.2 0.6 Fraction 0.6 0.1 1.0 13C5Ino 13C5Ino SuccinateGlu-GSH0.7 Fraction 20.4 0.1 0.5 0.3 13C5Ino0.2 0.1 0.30.6 0 0.21 2 3 4 1.0Fumerate G SuccinateG 0.2 0.7 L 13C5Ino K0.00.2 13C6Glc13C5Ino 0.5 0.2 0.6 GSH Fraction Fumerate0.6 0.0 0.1 Succinate1.0 0.1Fumarate 0.00.2 4 Glu-GSH 0.80.2 Succinyl0.1 1 0.7 CoA0.0 0.3 Glu 0.5 0.0 0.8 HFumerate 0.4 Succinate Glu-GSH0.6 5 GSH0.1 0.3 Fraction 0.4 0.1 0 13C5Ino0.21 2 3 4 5 0.0 0.0 Fumarate SuccinylGlu-GSHCoA 0.6 0.2 Fraction

Fraction Fraction 0.5 GSH 0.2 Fraction 13C6Glc 13C6Glc 0.0 0.5 0.1 0.6 Fumerate0 1 2 1.03 4 0.4 Succinate0.80 1 2 3 4 5 0.7 Fraction 13C6Glc 0.5 0.6 GSH0 1 2 3 Fraction 4 5 0.4 13C6Glc 0.00 1 2 30.8 13C6Glc4 0.0 0.0 G 0.60.0 0.5 5 13C6Glc0.0 0.2 0.1Glu -GSH K 0.0 13C6Glc 0 1 2 Fumerate30.1 0.40.6 4 0 13C6Glc1 2Fumarate Succinate3 0.2 4 13C5Ino 13C6Glc 13C5InoSuccinyl 0 Succinate1 CoA2 3 4 5 0.5 5 0.3 0.2 13C6Glc0.4 0.1 13C5Ino 13C6Glc 13C6Glc 0.6 Fraction 0.1 0.50.4 13C5Ino 0 1 2 0.8 313C5Ino 40.3 00.6 01 12 Succinate 2 3 3 4 4 0 1 Glu-GSH2 3 40.4 0.5 13C5Ino0.1 0 GSH1 13C6Glc2 3 4 5 13C5Ino0 L1 2 3 4 5 0.0 0.3 0.6 1.0 0.613C5Ino H 13C5Ino0.4 Succinate0.7L 0.00.4 1 13C5Ino0.3 H0.4 0.00.313C6Glc 13C5Ino 0.0 13C6Glc13C5Ino Succinate1 0.3 0.50.4 0.0 13C6Glc13C5Ino L0.1 0.0 0 1 2 3 4 5 Fraction Fraction 0.4 0.2 Fraction 5 L 0.2 0.3 1 0 1 20.0 3 Fraction 4 5

Fraction Fraction Fumerate Fraction Fraction H 0.6 Succinate 0.3 0.2 0.4 0.6 Fraction 0.2 0.5 H 13C5Ino0 1 0.8 2 0.43 4 13C5Ino0 1 2 3 4 SuccinateG 1 Fraction 0.40.3 GSH013C5Ino 1 2 3 4 5 0 1 2 3 4 5 Fraction Fraction 0.2 G Fraction 0.2 0.2 0.3 0.1 L Fraction 0.0 0 1 2 3 4 5 Fraction Fraction 0.2 Fraction 0.1 0.4 H 13C6Glc0.2 13C6Glc G Succinate1 0.5Glu-GSH Fraction 0.30.2 13C6Glc0.2 0.1 0.1 0.1 0.6 0.4 G0.2 Glu-GSH 0.1 0 1 2 3 4 5 Fraction Fraction 0.2 Fraction 0.2 0.1 13C5Ino 0.0 13C5Ino Succinate0.0 0.4 Fraction 13C5Ino0.1 0.0 0.0 0.3 0.0 G Glu-GSHGlu-GSH 0.0 0.20.1 L 5 0.0 0.1 H 0.0 0.2 0 0.01 2 3 4 0 51 2 31 4 0.3 0.0 0 1 2 3 4 5 0 1 0.02 3 4 0 0.41 0.02 3 4 0 1 50.120.0 3 4 5 0 1 2 3 4 5 Fraction Fraction 0.2 Fraction Glu-GSH 5 0 1 2 3 4 0 1 2 3 4 Fraction 0.0 0 1 2 3 4 0.0 0 G1 2 3 4 0.2 0.0 0 1 2 3 4 0 5 1 2 3 4 5 0.1 0.2 5 0 1 2 3 4 0 1 2 3 4 Glu-GSH 0.1 0 1 2 3 4 5 Figure0.0 2. The ribose0.0 moiety of inosine5 can0.0 replace glucose and feed 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 5 into the central carbon metabolism in T effector cells. Glutaminolysis 1.5 B Control Glutamine free FAO inhibitor A Glutaminolysis FAOFAO

1.0 1.0 CD8 T cell

0.5 0.5 Metabolic Rate (CPMA) Metabolic Rate (CPMA) T cells Mouse

Relative Activity (CPM) 0.0 0.0 GlucoseGlucose Inosine Inosine GlucoseGlucose InosineInosine Count

CD8+ CFSE Human CD8

Inosine C D

Glucose free Glucose Guanosine Hypoxanthine Inosine

Count CD8+ CFSE Ribose-1-P hypoxanthine

Central carbon Purine nucleotide 14.6% 66.8% 22.1% 19.5% catabolism salvage 7AAD CD8+ FSC-H

Figure S3. Inosine does not support T effector cell proliferation by enhancing glutamine and fatty acids catabolism or through purine nucleotide salvage. A Inosine B 0 6 24 48hr PNP * Forodesine

PNP Actin PNP 4 Hypoxanthine 3 R-1-P qPCR - 2 PNP 1 (Relative value) (Relative

The central carbon metabolism Fold change (qPCR) 0

0 4h4 12 24hr 12h 24h Naïve

C D Glucose Inosine Glucose free Glucose + Foro Inosine +Foro

Glucose/ Inosine/ Foro Foro Background Glucose Inosine

Count CD8+ CFSE 100

50

% of% Rescue 12.1% 64.9% 69.3% 63.5% 18.3%

7AAD CD8+ FSC-H

E F 2 mM Glucose 2 mM Inosine

Foro: - + - + 2mM Inosine B - 24.6% 19.9% 32.6% 0.15% 2mM Inosine + 2µM Foro Granzyme 19.1% 15% 17.4% 4.2% α ** - TNF %tumor cell killing %tumorcell 22.3% 20.3% 37.6% 0.3% γ - IFN

Time (h) CD8+

Figure 3. The purine nucleoside phosphorylase (PNP) is required for inosine-dependent mouse T effector cell proliferation and effector functions. A B Glucose Inosine Glucose free Glucose + Foro Inosine +Foro Glucose/ Inosine/ Foro Foro Background Glucose Inosine 100

Count CD8+ CFSE 50 % of% Rescue 21.1% 73.1% 69.1% 71.2% 26.4%

7AAD CD8+ FSC-H C D Inosine Inosine + Foro

B 30.2% 8.79% - Inosine Inosine + Foro

*** Granzyme 68.1% 4.59% α - TNF %tumor cell killing %tumorcell 30.9% 3.07% γ - IFN Time (h) CD8+ Csi growth curve 1.5 PNPsi growth curve Glucose 2mM 2.0 G free 1.0 GlucoseGlucose 2mM G free Inosine 2mM E 1.5 F Glucose free /ml) 6 InosineInosine 2mM Ctrl PNP 1.0 0.5

150 Glucose Glucose free Inosine Glucose Glucose free Inosine PNP 0.5 Cell # (10 ns Cell Growth (million/mL) 100 0.0 PNPsi growth curve

Cell Growth (million/mL) Days 0 1 2 3 4 5 2.0 50 0.0 ** actin of Rescue 0 1 2 3 4 5 Ctrl siRNADays Glucose 2mM

% Days G free 0 1.5 Inosine 2mM /ml)

Ctrl siRNA PNP siRNA 6 1.0 **

0.5 Cell # (10 Cell Growth (million/mL) 0.0 Days 0 1 2 3 4 5 PNP siRNADays Figure S4. The purine nucleoside phosphorylase (PNP) is required for inosine-dependent human T effector cell proliferation and effector functions. 1,200 Inosine ***

6 1,000 Ctl 800 Foro PPP 600 400 A O NormInt/10 200 1’ N 1 Ctl 0 NH 0.8 R1P 1,200 H PNP Foro ** Inosine *** 0 1 2 3 4 5 6 1,000 0.6 Ctl N N H 1.0 800 Foro 5’ 5’ PPPInosine *** HO O 5 0.4 C 600 0.8 1’ P P Ctl * Fraction 400 A Foro 13 0.2 O 0.6 * OH* *OH * C -Ino R1P NormInt/10 5 200 1’ 0.0 N 10.4 Ctl NH 0.8 R1P 0 1,200 Fraction H PNP Inosine *** B Foro ** 0 1 2 3 4 5

6 0.2 0 1 2 1,2003 4 5 1,000 Inosine N***N H Ctl 0.6 1 0.8

6 800 1 1.0 1,000 5’ 5’ Foro0.0 COPPP 1 Ctl Sed7P Inosine *** HO Ctl O 600 5 0 1 2 30.4 4 5 C 2 Foro * 0.8 800 1’ P P G6PDH 0.6

Foro Fraction Ctl * 400 A PPP Foro600 1,200 13 0.8 Ctl 0.2 O 0.6 * * * * NormInt/10 E OHInosineOH ***C -Ino200 R1PForo Glc6P * 0.4 6 1’ 1 400 1,000 1,200 5 N 5 Ctl A Ctl Inosine0 O*** 0.0 6 NH 0.8 R1P 0.4 0.6 P P ** Fraction

6 NormInt/10 1,000 H P NADPHPNP Foro Fraction Fraction 200 800 B Foro Ctl 0 1 21’ 3 4 5 H 0 1 2 PPP3 4 5 Ctl 0.2 0.2 N N 0.6 7 0 600 800 Foro NH 0.4 N H 0.8 Ctl R1P ** P P P 1 H 1.0 PNP5’ Glc6P 0.80.8 ForoPPP R5P *** X5P 0.0 0400 1,2001 2 3 4 5 600 Inosine Fraction 1 *** HO 1 5’ CtlForo 5 0.4 TKC 0.0 InosineA *** NCO O O 0.6 Sed7PP P 6 1,000 0.8 N 2 H 0.2 1’ 0.6 * 0 1 2 3 4 5 6 7 B Fraction A NormInt/10 Foro Sed7P 0 1 2 3 1.04 5 200 G6PDHCtl 400 A Ctl * 0.6 5’ 1’ O 131 Ctl D 0.2 800Inosine ***NormInt/10 HO N 5’Foro 5 C 0 Foro200 O 0.6 0.0NH * * * * C -Ino0.4 0.8 R1PR1P 0.8 Ctl 0.8 1’ PNPOH OH 1’P PPP P 5 0.4 1 Foro ** Ctl Glc6P * 600 Ctl H N Fraction 0.4 E 0.8 0.0 * 0 1 2 3 4 5 6 Fraction R1P Foro 0 1 2 3 4 0 5 0.4 13 NH PNP0.2 Foro ** + 0.6 4006 Foro * * * Fraction * N NB5 H H 1 0.2 0.6 0 1 2 3 4 5 0.6 A 0 1 2 3 4 5 P P P Fraction 1.0 P NADPH OH OH0.2 C51.0O-Ino R1P 0.6 1 NormInt/10 200 5’ N NCtl H 0.2 1 H 0.4 Inosine *** HO 5’1’Glc1P 1 7 15 0.0 0.4 C 0.8 0.4 1.0 Ctl 0.0O N 5’ Foro P P 0.0 Ctl 1 Ctl Fraction Fraction 0.8 0 0.8 1’ 0.8 NH 5’ P P P 0.80 1 2 3R1P 14 5 Glc6PB Ctl Inosine* R5P ****** HOX5PO PNP CO Fraction 5 Foro **0.4 C Sed7P * Fraction Fraction H TK 0.0 0 P12 2 P3 4 5 Foro 0.2 0.8 Foro 0 1 132 3 4 5 1’ G6PDH 0.2 3 0.6 0.6 0 1 Foro2 3 4 5 * Ctl* * * 0.6 * Fraction P 0.2 0.6 1 OH OHN N CH -Ino Sed7PR1P 0.6 0 1 2 3 4 5 6 0.27 0.8 0.0 Foro Ctl * 5 I 13 1 PNP 1 5 Ctl 1.0 0.61,200 0.85’D Glc6P OH* *COOH * C -Ino6 0.0 R1P Sed7P E 0.0 0.4 Inosine *** HOInosine Foro ***0.4 *5’ 13 2 ** 5 5 0.4 C P ForoP * 0.4 Fraction Fraction PPP 6 O 0 Fraction 1 2 3 4 5 0.8 B 0.40.41,000 G6PDH1’ C -6Ino P P 0 1 2 5 3 0.04 5 0.6 Gly3P Fraction Fraction Ctl 0.6 Ctl 5 P P Fraction 0 1 2 3 4 5 6 Fraction * P 0.2 Fraction NADPH+ Ctl 1 800 B 0.213 Glc1P P0.2 0 1 2 3 4 5 0.2 0.8 0.6Glc6P P Foro0.2 0.2 1 * *Foro * * H R1P PPP R5P0.8 E7 1.0 Foro0.0 * 600 0.4OH OH 1C 5-Ino 1 Ctl R1P 1 0.4 Ctl P P P Ctl 0.0 1 Glc6PCO 5 10.8 R5P0.0 *** X5P Sed7P0.8 Glc1P 0.4 0.0 6 Fraction 2 Foro 1TK Foro *Ctl 0.0 13 0.6 0 1 2 3 4 0.0400 5 G6PDH0 1 2 3 4 5 6 P P 1 Fraction 0.8 C5-Inosine Foro Fraction P 0.2A NADPH CO 0 1 2 3 4 5 0.6 Sed7P B 0 1 2 3 4 5 O 0.6 2 0.2 Sed7P ForoTA 0 1 2 3 *4 5 6 7 H NormInt/10 0 1 2 3 4 5 G6PDH 0.8 0.2Ctl 200 4 1’ 3 D 1 7 0.6 0.6 0.4 0.8 Glc6P 10.0 0.8 Ctl N P P PFruc6P P Ctl 0.8 E I 0.0Foro *Glc6P Ctl0 R5P *** NH X5P0.4 1 0.8 * 0.4R1P Ctl Fraction Fraction 1 1 0.8 Glc6P Foro5 CO COPNP2 TK 0.6 0.0Foro **Sed7P E 5 Fraction 0.4 ** 6 Foro 6 0 * 1 2 3 4 P5 6 PH 2 6 Ctl Foro + 0.4* 0.2 0 1 2 3 4 5 Fraction Forodesine 0.6 0 1 2 3 4 5 P 0.6G6PDH 11 P P 0 1 2 3 4 5 6 7 Ery4P*** Fraction Fraction NADPH 5 0.6 6 N PN 1 H Gly3P0.2 n Sed7PForo0.6 0.2 0.6 ** H 0.6 1.0 PG6PDH P P1 Fraction 1 0.2 Ctl 1.0 Ctl5’ D NADPH 0.4 7 1 0.2 Ctl 0.0 0.4Glc1P 0.8 Glc6P HInosineGlc1P *** HO Ctl 5’ 5 P P P C E Foro * Glc6P0.8 0.4 0.8R5P Foro O R5P *** X5P0.0 P P 0.4 0.47 Foro

Fraction Fraction 1 4

Ctl Fraction PNP 0.4 0.8 Foro TK 0.0P P P 0 1 2 3 4 5 6 Fraction 1’ 0.8 5 + 0.4 0.0 6 Ctl Glc6P* R5P0 ***1 2 3 4X5P 5 + Fraction 3 P P 0.2 G Fraction 0.6 Fraction 0.2 1 0.6P 0.2 NADPH0.6 13 Foro P 0.2TK 0 1 2 3 4P 0.05 6 47 0 1 2 3 41.0 5 6 0.6 P Foro P* * * NADPH* 1 4 n Sed7P 0.2 6 H 0.2 I OH OHD 0.6 C1 -InoTA R5P R1P7 5 Sed7PP P P 0 1P 2 3P 4 5 Fraction 6 7 0.0 0.4 Ctl 0.8 Ctl 6 5 1P PP PP 0.2 F 4 Glc1P 0.4 Glc6P0.4 0.0 0.40.8 ** R5P *** X5P 0.0 0.0 P Fraction Fraction D 0.8 Fraction Foro 0.0 Fruc6P Foro TK 0.0 Gly3P Fraction Fraction Glc6P* 0 1 2 3 4 5 6 B 0 Fraction 1 2 13 4 5 0.413 0 1 +2 3 4 50 61 2 3 4 5 Hypoxanthine 0.2 0.2 0.61 0.2 0.6 3TK 0 1 2 3 4 5 6 7 0.0 0.6 6 0 1 2 3 4 5 Ctl6 0.2 Glc1P Fraction [ C-U]-Glycogen Sed7PPR5P Sed7P Fruc6P+ Ery4P 1 1.0 P 1 1 D 1 Ery4P*** 0.8 1 0.0 I n Ctl 0.0 Foro P 0.2 5 1 0.6 **1 1 Ctl 0 1 2 3 4 Glc1P 1.0 0.06 0.4 0.4 CO 11 0.4 0.8 ** Foro 0Ctl 1 2 3 0.04 5 6 P P 2 Ctl 1 Sed7P * 0 1 2 3 4 5 6 Fraction Foro R-1-P Fraction 1 4 Glc1P0 1 2 3 4 5 G6PDH0.0 Gly3PForo + TA0.6 0.8 Fraction 1 Foro 0.2 0 1 2 3 4 5 + Glycolysis0.8 0.4 3 + 0.2 1.0 0.2 P G 4 0 1 12 3 4 5 P 0.6 Glc1PCtl0.8 Ctl 4 Fruc6P *1 3 I1 0.64 n Glc6P * 6 R5P 1 P 0.4 E Glc1P Foro 5 P P Fraction 0.0 0.8 Foro 6 I 0.0 P P6 P 0.6 Ctl 0.4 ** 0.0 1 6 P P 0.2 55 F Ery4P*** Fraction Fraction Fraction Fraction 0.6 6 0P 11 2 3 4 5 PForo Gly3PP 0 1 2 3 4 5 6 0.4 ** NADPHn P P 3 P 1 0.2 0.6 ** 13 0.6 Fraction 0 1 2 3 4 5 6 0.4 P TAP Gly3P Ctl 0.2 I H 0.8 7 [ C-U]-Glycogen40.2 0.4 Glc1P Fruc6P1 0.8 4 CtlEry4P 5R5P 0.0 P P P Foro 0.4 ** 6 Glc1PGlc6P Fruc6P PR5P P Fraction *** X5P + 0.4 Fraction Fraction * Foro 0 R5PG1 2 3 4 TKGly3P 0.0 0.0 Fraction 1 X5P0.2 Gly3P 0.0 0.2 6 0.6P 1 4 n 6 4 0 1 2 3 4 5 6 7 0.20 1 2 3 4 5 6 Ctl 0.6 P PSed7PP P P Fraction 1 Glc1P TA Ery4P *** 0.2 Glycolysis1 0 1 2 n3 4 5 6 0.8 Foro R5PD 0.0 1 0.6 TA ** F 0.0 0.04 0.4 0.4 PPP, Glycolysis and Krebs cycle 4 Glc1P 13 Fruc6P0.8 * 0 1 2 3 4 5 6 Ctl 0 1 2 3 4 5 6 01 1 24 3 4 5 6 [ C-U]-Glycogen Fraction 1 Fruc6PTA + ForoEry4P 0.0

Fraction Fraction Fruc6P 6 1 0.6 0.2Ctl * + 1 TA 0.4 1 1.0 0.26 P 0.8 G 0.6 1 Ery4P*** 0 1 2 3 4 1 4 1 1n 4Ctl n Fruc6PForo 6 Ctl 4 1 0.6 1 ** Ery4P*** Glc1P 1 n0.4 0.0 * P 1 ForoP P P P Fraction 1 Ctl 0.6 ** 0.8 6 Foro 0.0 0.6 0.2 F 1 1 4 Ctl 0 Glycolysis0.41 2 3 4 5 Ery4PForo*** Ctl Fraction Fraction 3 13 0.6 1 n 1 0 41 2 3 4 Foro5 6 + 1 0.60.4 P ** Foro 0.2 G Fraction + 0.4 [ C-U]-GlycogenI 1 4 n 0.4 0.2 Fruc6P6 G 5 Ery4P4 0.0 Ctl 0.4 1 4 ** 6 1 4 P P P 6P P P Fraction 4 Foro Fraction Fraction n 0 1 2 3 4 + 0.40.2 P P Fraction Fraction Fraction P P P Gly3P F 0.00.2 G 0.2 F 0.2 1 4 n 0.0 6 4 + 13 Glc1P 0 1 2 3 4 5 6 P P P P P P Fraction [ C-U]-GlycogenGlycolysis13 0 1 2Fruc6P 3 4 5 6R5P Ery4P 0.20.0 0.0 0.0 P F 0.0 [ C-U]-Glycogen Fruc6P Ery4P0 1 2 3 4 130 1 2 3 4 5 6 0 1 2 3 4 5 6 0 1 2 3 4 [ C-U]-Glycogen1.0 0.0 TA 0.8 Fruc6P Ery4P Glycolysis4PEP ** Glycolysis0.8 Pyruvate Fruc6P Ery4P0 1 2 3 4 1.0 0.8 GlycolysisFruc6PGlycolysis * 1 Ctl 0.6 PEP1.0 1.0 0.8 Pyruvate 6 0.6 Ctl Ctl 0.8 ** 0.6 1 Glycolysis Ery4P*** PEP 0.8 0.8 Pyruvate1ForoGlycolysis n Foro *** Foro 0.8 1 0.6 ** Ctl 0.8 PEP ** ** Ctl Pyruvate Lactate 0.8 1.0 0.6Ctl 0.4Glycolysis 0.4 Ctl 0.6 Foro Ctl Foro0.40.6 *** Ctl Glycolysis Ctl Fraction Fraction Ctl 0.8 1 Fraction 4 0.8 0.6 Foro C 0.6 ForoPEP 0.6 ForoPyruvate *** Fraction Lactate + 0.4 0.6 0.8 ** 0.8 0.4 Foro0.4 0.2 ForoA *** 0.2 GlycolysisB0.2 0.8 G Lactate Foro 1.0 Ctl 0.4 Ctl Lactate 4 ** Fraction Fraction 6 Fraction Fraction Ctl 1 4 0.6 n 1.0 0.4 0.8 0.4 0.6 Ctl P 0.4P P P P Fraction 0.4 Fraction 1.0 PEPA 0.6 0.2 ForoPyruvate B Fraction Foro *** Foro0.6 Ctl 0.2 Fraction Fraction 1.0** Fraction Fraction 1.0 0.80.2 0.8 0.0 0.0 0.0 0.6 **0.8 Lactate Fraction F PEP0.2 ** A Pyruvate0.2 PEPGlycolysisB 0.8 Pyruvate Foro 0.8 0.2Ctl A PEP 0.2Ctl0.8 0.8 0.4 B Pyruvate** 0.4 Foro ** 0.2 C PEP 0.8 0.40.8 0.6 Pyruvate** 0 131 Glycolysis2 3 0 1 2 03 0.41 2Glycolysis1 3 4 5 6 ** Fraction Fraction Ctl 0.0 ** Fraction 0.0 0.8 0.6 ForoCtl O Ctl *** Fraction [ CtlC -U]-GlycogenGlycolysis 0.4 0.6 0.0 0.6 Foro Glycolysis0.6 0.8 Ctl Fruc6P Ery4P 0.6 Ctl 0.0Foro Ctl A 0.0 0.6 0.21 *** CtlB 0.2 LactateC Fraction Foro 0 10.0 2 0.23 0 Ctl 10.0 0.6 2 Foro 3 Fraction 0.0 0.6 0.6 0.4 Foro 1’ Foro1 *** 0.8Foro ***Lactate0.2 Lactate C 0.8** 0 1 2 3 4 O 0.6 0.4 Foro 0 N 1 2 Foro3 *** 0 1 2Foro 3 1 1 0.2Ctl 0.83 0.4 C Lactate Fraction Fraction Lactate 0 1 Fraction 2 0.4NH 3 0 1 2 3 0.8 0.6 0 1 2 3 0.4O 1 0.4 1 0.4 0.0 Lactate O H 0.0 0.4 0.0 Lactate Ctl Fraction

1’ Fraction A 0.4 0.4 Fraction B 0.6 Foro Ctl 1 0.2 Fraction N 0.4 0.2 1 3 Pyruvate Fraction Lactate 0.0 1** Ctl 0.6 Fraction Fraction 1 C NH 13 1’ B Fraction GlycolysisCtl 0.6 0.2 Fraction Fraction 03 10.0 2 3 N A Fraction N 0 0.2 1 2 3 0 1 1 2 Lactate3 0.6 B Foro H 0.2C NH-1’Ino N H 0.2 1A B 0.23 10.4 ** Foro N 5 AO 0.2Pyruvate 0.2 A B 0.2 3 Foro 0 1 2Foro 3 ** Ctl** H 0.2 0.0 NH 5’ 0.01 1 Fraction 0.4 **0 1Ala 2 3 0.40.8 Citrate N H H HO Pyruvate5’ 3 Lactate 0.43 0.0 Foro N 0.0 1’ 0.0Pyruvate CO 1 0.4 0.2 Fraction C N N0 1 2 O 3 0 1 0.02 36 3 21 1 0.0 CO Ctl Fraction N H NH 0.0 1’ 0.0 31 Ala 0.83 C Fraction

5’ O N 0.0 H 0 1 2 0.03 0 1 2 P3 Fraction 0.2 Citrate2 0 1 Ctl 2 0.63 C HO 5’ 5’ NH 1 *CO 0 1 3 21 3 Ala0 PDH 1 2 C3 0.8 1Foro0.2 Citrate Ctl C 0.2

O 5’HO O 1’ 0 61 5’2 3 2 0 O01 CO 12 CO23 Pyruvate3 0 1Lactate 2 3 Ala3 0.21 10.0 0.8 Citrate Foro

NHO1’ O N O5’P 1 * * * 6* CO13 2 1 2 1 3 3 0.6 Foro D * O H OH OH PDH 1 CO3 Glycolysis0.0

NHO 1’1’ N 6 P1 C2 -Ino1’ F6PCO 2Lactate 0 1 0.621 3Lactate Ctl0.00.4

H N * 1’ 1 1’ PEPPN Pyruvate5 1 PDH 23 0.0 LactateAla1 0.6 0.00.8 ** 5’ LactateAcetyl CoA Fraction * PDH Citrate OH* *OH * *13 1’NH N 5’ PyruvateNH 1 Lactate 1 3 0 D1 32 3 0 **1 2 3 N H *C HO* -Ino* *O 13 F6PNH CO3 2 3 1 0.43 0 D1 2 Foro3 *****

N *NH N* *OHH 5*OH 13 1’ H Pyruvate6 1 1 COPyruvate0 1 ** 2 0.4 3 D 0.2

H OH OH H C -Ino1.0 F6PAcetyl P Pyruvate CoA3 21 Fraction 1Ctl 0.6 N *H C -Ino5 Pyruvate PDH Ala 1 0.8 3 **0.4 **

F6P Acetyl CoA Fraction 5’ N N 5 N N CtlH CO 1 3 1 0.2 Citrate***** **Ctl **

5’ Acetyl2 CoA Fraction *** HO 5’ON H * * * * N 13H CO Asp 3 3 Ala 0.8 Foro** *****D 0.0 Ctl 1.0 N OH5’ OH 6 0.8 5’ 2 Foro CO Ala Citrate0.2CtlCitrate 0.8 0.4Ala Ctl0.8 Citrate

5’ HO O1’ 1.0 Ctl5’ PHOC -InoCO F6P 5’ 2 AlaCO3 0.81 0.6 0.2 3 Foro*****Citrate Foro

* Asp HO 6 5’5 O 2 COPDH 1 CO 2 3 0.0 Citrate *** ** Foro 0 1 2 3 4 5 6 Acetyl CoA Fraction

HO 1.0 1’ Foro5’ O Ctl COP 1’6 2 26 3Citrate 0.6CO Foro ** ***

0.8 O * Asp Ctl6 2 CO2 PDH P CO 2 0.0 0.6

* * 1’* * 13 1’ 0.6 * P CO 2 Citrate PDH D1 0.6 0.2 ******** PCB PCB

OH OH 0.8 *Asp 1 PForo I 2 PDH 0.6 0.4 0 1 2 0.03 4 5 6 1.2 * * * 0.8* * C131.0-Ino Foro F6P PDH Citrate D 0.6 OH OH 5 1* * * * 13 11 ** 0 1 2 3 4 5 6 D Ctl *C * -Ino* * 13 0.4Ctl OH OH Acetyl CoA Fraction 0.4 0 1 2 3 4 5D 6

* * * * 13I0.6 OH5 OHAsp F6P1 PCB CAcetyl-Ino CoA F6P1 1 **D ** 14 0.4 0.0 1.2 0.4*** 1.0 KG

OH OH Fraction ** α

C -Ino Acetyl5 CoA Fraction ***** F6P PCB 10.4 Citrate 0.2 1.2

0.6 C -Ino0.8 IF6P 5Foro ***** 4 1 1 Acetyl **CoA ** ** Fraction Ctl Foro PCB PCB ** 1.00.4 5 I Acetyl CoA Fraction 1.0 1.2 0.2 1 Acetyl CoA 4 Fraction 0.2 ***** 0 **1 2 3 4 5KG 6 ***** Ctl 0.8 Fraction Fraction ** α0.2 1.0 *****0.4 Ctl 4 4 ***** 0.2*** ***** 1.0 Foro KG Ctl

Asp0.4 Fraction 0.6 1.04 4 10.2 0.0 6 0.8 1.0 α 1.0 Ctl Asp PCB Citrate 1.2KG 0.6 1.0 0.80.2 Fraction Foro ***** I Ctl CitrateOxaloacetate *** Isocitrateα Foro E Asp0.2Ctl ***** 4Ctl 0.0 Asp 6 Citrate 0.00 1 2 3 4 5 6 ***0.0 0.8 ***Foro 0.8 0.2 0.4Foro Asp1 Asp 0.8 Foro ***Citrate0.0 0.6 0.8 Ctl 0.0 Asp 0.8 Foro Oxaloacetate0 1 2 3 4 Citrate 6 Citrate0.04 Isocitrate0 1 2 3 4 5 6 E 1.0 KG Fraction 0.4 0.8 0.6 Foro Fraction 1 Asp 1 1 6 00.6 1 2 3 4 E5 α 6

I0.0 *****Asp 1 4 PCB Oxaloacetate 0 1 2 3 4 5 Isocitrate6 0 1 21.2 3 4 5 60.6 E Foro **

0.6 0 1 0.02 3 0.241 0.6 OxaloacetateNADPH1 Isocitrate1 Fraction 0.4 0.8 0.2 PCB PCB 1.2 Ctl

I Fraction

0.6 0.4 0.6 0 1 2 3 4 1 I 1 PCB 1 1.0 0.4 1.2 ***

PCB 1 ** 1.2

I 4 6 Fraction 0.4 PCB PCB KG Fraction Fraction I 0 1 2 3 4NADPH Asp ME 1.2 0.2 α 0.6Ctl ** E 0.0 Ctl 0.4 1***** 0.0 4 0.4 NADPH Oxaloacetate4 Isocitrate1.0 KG0.2 *** Foro CO Ctl1.0 Fraction Fraction 0.4 1 4 0.8 α Ctl ** KG 0.4 0.2 1 4 Fraction NADPH 4 1.0 0.2 1.0 Foro KG ***2 α ***** Fraction 0.0 0 1 2 3 4 5 ME 4 1 4 KG Fraction 0.4 α Foro Fraction Fraction 0.2 1 0 1***** 2 3 4 4 3***** 1 6 Krebs CO 0.8α *** Foro ***** 4 Asp 0.2 OxaloacetateME 2 0.6 EForo0.0 0.8 ** 0.8 0.2 0.0 3 0.2 ME NADPH 6 4 Isocitrate6 0.8 CO0 1 20.02 3 4 0.25 3Asp Asp1 OxaloacetateOxaloacetateAsp 6 IsocitrateIsocitrate CO0.6 2 E 0 1 2 3 4 5 0.6*** E 0.00 1 2 3 4 Asp 6 1 Oxaloacetate Fraction 0.4 Isocitrate0 0.61 2 3 4E 5 0.0 Asp3 0.0Oxaloacetate PyruvateME4 Oxaloacetate Cycle Isocitrate0.6 E 0.0 0.0 Isocitrate Fraction 0.4 ** Ketoglutarate Glu 0 1 2 3 4 0 1 2 3 4 4 Malate Krebs0.2 COα Fraction 0.4 Pyruvate NADPH 2 Fraction 0.4 0 1 2 3 4 4 Fraction 0.4 ***** 0 1 2 3 4 5 0 1 2 1 3 4 Pyruvate3 NADPH Malate 1 1.0 Krebs αKetoglutarate 0.2 Glu ** ** 1 PyruvateME NADPH1 Malate NADPH Ctl Krebs αKetoglutarate0.0 ** 0.2 *** Glu 0.2 1 1.0Pyruvate 1NADPH NADPH 1 Malate Malate4 Krebs1 αKetoglutarateCO 0.2 Glu *** *** 1 ME1.0 Ctl 1 0.8 ME1 Foro COCO2 2 0.00 1 2 13*** 4 5 0.0 3 MEPyruvateMalate 1.0 ME Ctl Cycle0.0 2 0.0 CO1 3 0.8 Foro MalateCtl Krebs CO αKetoglutarateCO0 1 2 2 3 4 51 Glu2 0 1 2 3 4 5 3 0.8 Malate3 4 Foro 0.6Malate Cycle 2 0 1 2 3 4 5 0 1 2 3 4 5 3 0.8 1.0 Foro4 H Cycle Pyruvate0.6 Ctl 4 Cycle4 1 1 5 Pyruvate H0.6 MalatePyruvate4 Malate 1 0.4 Krebs αKetoglutarate Glu Pyruvate0.6 0.8 H Fraction Foro Ketoglutarate 5 Glu Pyruvate1.0 0.4 MalateHMalate 1 *****Krebs Malate Cycleα !-Ketoglutarate KrebsKetoglutarate αGlu1Ketoglutarate 5 Glu Glu Ctl Fraction Fraction Krebs α CO 0.8 1.0 *****0.4Malate Ctl Malate0.2 1 Krebs αKetoglutarate Glu 5 2 Glu Malate0.4 Fraction 1.0 0.6Ctl ***** 1.0 CO 0.8 1 Ctl 1 Foro 1.0 0.80.2 Fraction Foro H 4 Glu Ctl Malate0.2 ***** Ctl Cycle1 Ctl 2 CO 1 0.8 Foro 1 0.8 Ctl ForoMalate 4 0.0 Malate CO 2 0.8 Glu5 Ctl Foro 0.6 Malate0.2 0.8 0.4 Foro0.8 CycleForo 2 Glu J 0.8 0.60.0 Foro Fraction 0 14 2 3 4 Cycle 0.6 Foro H0.0 ***** 4 CycleFumarate Cycle Succinyl0.6 CoA Ctl 0.60 1 0.02 3 0.24 1 0.6 CO 0.6J 0.8 0.4 0.4 H0.6 Fumarate Succinyl CoA 52 J Glu Foro 0.6 0 1 1.0 2 H3 4 1 FumarateH Succinyl CoA0.4 1.0 J Fraction ***** Fraction Fraction 0.4 H 0 1 2 3 4 11.0 4 1 Succinyl CoA 5 0.4 Ctl 5 1.0 ***** 0.0 1 FumarateFumarate0.4 1.0 Fraction ***** Ctl0.6 5 0.2 Fraction Fraction 1.0 0.4 Succinate CO 0.8 5 0.4 GSH 0.21.0 Fraction 0.4 ***** 0.8 Fraction 21.0 Ctl Glu0.8 *****Foro Fumarate Fraction 1.0 0.2 ForoCtl J 1.0 0.8 Fraction Fraction Fraction Succinate0 1***** 2 3 4 ***** GSH1.0CO 0.8 Ctl ***** Ctl 0.8 0.2 *****Fumarate 1.0 4 SuccinateCtl0.2 Fumarate Ctl 0.8 SuccinylCO2Foro GSH CoA Ctl Glu0.2Ctl CO Ctl0.8 0.00.8 Fumarate0.8 0.2 CO 0.8 0.8 CO0.6 Foro 0.2 0.8 0.4Foro 2 Glu 0.0 Glu 0.2 Ctl 0.6Ctl 0.8 Succinate4Foro G 0.6 Foro F 2 GSH 2Glu 0.6 Foro Foro 0.8 1.0 Ctl Ctl 4 Succinate0.8 1.0 0.0 Foro Foro Fraction ***** 0.6 Foro0.0 0G 1 2 3 4 0.8Foro 4 F1.0 0.0 4 0.6 0.6 CtlJ0.0 K 0.6 0 1 2 3 4 5 0.0 0.6 Ctl0.6 Fumarate0.0 Fumarate Ctl Succinate Succinyl CoA0.6 0 1 2 3 40.6 0.25 0.6 0.80 1 Foro2 3G 4 0.4 0.6 ForoSuccinate F 0.4 Succinate K 0.6 10.4 GSH 0.00.4 J J Fraction Fraction Fumarate0 1 2 3 4 Succinyl CoA0.6 0.8 K Foro 0 1 2 3 4 5 Foro G 0.6 0.8 Foro F Fraction 1 Fraction J 1.00.4 0 1 2 3 4 Succinate Fraction J 0 1 2 0.43 4 Ctl *****Fumarate Ctl Fumarate 1.00.4 Succinyl KCoASuccinyl0.4 ***** 0 CoA 1 2 3 4 5 0.4 Fraction Fraction 0.4 1.0 Succinyl1 CoA Fraction Fraction Fumarate0.2 0.4 Fraction 0.4 Ctl 0.4 0.0 ***** 1.0 0.4 Fraction ***** Fraction 0.2 1.0 0.2 0.2 ***** Fumarate0.4 0.6 Fraction 1 Fraction 1.0 ForoSuccinate 0.41.0 Foro *** GSH0.4***** 0.6 1.0 Fraction ***** 1.0 ***** G 0.6 F 1.0 Ctl Fraction 0.80.2 Fraction Fumarate SuccinateSuccinyl CoA Foro *****

1.0 Fraction

Fraction Fraction 1.0 Fraction Fumarate0.2 *****0.80.2 Succinate*** 1.0 1.0 0.80.2 GluGSH-GSH *****0.2 K***** Ctl 0 1 Ctl2 3 4 5 0.8 Ctl 1.0 Fumarate 0.0Ctl 0.2 FumarateSuccinate*** 0.0 Succinate** ** 0.8 0.2Ctl GluForo*****-GSH 0.0 0.2 GSH 0.2 Fumarate0.2 0.8 0.4 0.8Succinate 0.20.8 0.4 Glu-GSH GSH1 0.2 0.4 0.2 0.0GSH Foro0.8 Foro 0.60.0 Ctl Fraction ** ** *** 0.8 0.8 0.8 Ctl Fraction 0.6 Fraction 5 Foro0.0 G 0.8 0.60.0 ***** Foro 00.8 F 1 **Ctl2 3 4 **Succinate 0 1 Ctl2Glu 3 -GSH4 0.8 0.0 Foro 0.0 0 1 2 3 4 5 0.6 Ctl Foro Ctl Ctl 0.0 Ctl Glu-GSH5 0.6 K0.0 0***** 1 2 3 40.0 5 0.0 0 1 0.02 30.6 0.24G 0.60 1 0.00.62 Foro3 **0.2 4 F Foro G** SuccinateForo F 5 0 1 0.02 3 4 0.25 0.0 0.6 0.6 0.4 Foro G 0 1 0.42 Foro3 4ForoG F0.6 0 1 2 Foro3 *** 4 F 0.6 Succinate1 0.6 0.4 SuccinateK0.6 0 1 2 3 4 05 1 2 3 4 K5 0 1 2 3 4 5 Fraction Fraction 0.6 5 0.4 0 1 2 Fraction 3 4 0 1 2 3 4Succinate Glu1 -GSH Fraction 0 1 2 3 0 4 K1 5 2 3 4 5 0 1 2 3 4 5 ***** 0.0 0.4 0.4 0.0 ** ** 0.4 K 1 Fraction Fraction ***** 0.0 0.4 0.2 0.4 Fraction 0.4 Fraction 1 0.4 0.4 Fraction 0.4 1 0.2 0.2 Fraction 0.4 Fraction ***** Fraction 0.4 Succinate *** Fraction 5 Fraction Fraction Fraction ***** 0.2 Fraction 0 1***** 2 3 4 *****0 1 2 3 4 Fraction 0.2 0 1 2 3 4 5 ***** ***** 0.2 0.2 ** 0.2 ***** Glu0.2 -GSH ***** ***** 0.2 0.2 0.0 0.2 0.0 *** 0.2 *** Glu-GSH*** 0.2 0.0 0.2 0.0 0.0 ** ** 5 0.0Glu -GSH 0 1 2 30.0 4 0 1 0.02 3 4 ** Glu**0.0 -GSH** Glu** -GSH 0 1 2 3 4 5 0.0 0.0 0 1 2 3 0.04 ** **0.0 5 0.0 0.0 0 1 2 0 3 1 4 2 3 4 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 0 1 0 2 1 3 2 4 3 4 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 Figure 4. PNP inhibitor forodesine suppresses inosine catabolism in T effector cells. A 13 HuT- C5-Ino-Foro 13 HuT- C5-Ino-Ctl 1.5 25 Lac/Ala Ino/Glu -4-Glu 20 C 1.0 Ctl Ctl Foro 15 Foro 13 10

mole/g protein mole/g protein 0.5 mole/g protein mole/g protein µ µ

C 5 C 13 13 0.0 0 13C3-Lac 13C3-Ala 13C-Ino 13C-Glu -3-Glu -3-Glu 10 30

Gluta/Asp C 8 25 AXP/UXP

Ctl 13 20 Ctl + 6 Foro Foro 15 4

mole/g protein mole/g protein 10 mole/g protein mole/g protein µ

µ

2 C 5 C 13 0 13 0 -1’-Inosine

13C-Gluta 13C-Asp 13C-AXP 13C-UXP -2-Glu+GSG+GSSH C C -A1’-NAD -2-Asp 13 13

C C 13 13

-3-Asp -GSH+GSSG+citrate

C C 13 13 -NMe-PCholine -NMe-PCholine -2-Gly -3-Ala -1’ -UXP -1’ C -1’-AXP -1’-AXP C -G1- C -5-UXP -4-Gln -4-Gln C C 13 13 C C 13 C 13 13 13 -3-Lac 13 Glycoen 13 C 13

13 B HuT- C6Glc-Foro 13 HuT- C6Glc-Ctl

40 Lac/Ala Ctl Ino/Glu 1.5 Foro 30 Ctl

1.0 Foro -4-Glu 20 C mole/g protein mole/g protein mole/g protein mole/g protein

0.5 13 µ µ 10

C C 13 13 0.0 0

13C3-Lac 13C3-Ala 13C-Ino 13C-Glu -3-Glu C 14 20 + Gluta/Asp 12 AXP/UXP 13 10 Ctl 15 Ctl 8 Foro Foro 10 6 mole/g protein mole/g protein 4 mole/g protein µ µ 5

C 2 C 13 13

0 0 -A1’-NAD -2-Glu+GSG+GSSH -2-Glu+GSG+GSSH -1’-Inosine 13C-Gluta 13C-Asp 13C-AXP 13C-UXP

C C C -2-Asp 13 13 13 C

13 -GSH+GSSG+citrate -3-Asp C -1’ -UXP -1’ -3-Ala C -5-UXP -NMe-PCholine -NMe-PCholine 13 C C -2-Gly C 13 -G1- C -4-Gln -4-Gln 13 13 C -1’-AXP -1’-AXP C 13 13 C 13 -3-Lac C 13 13 Glycoen C 13 13

Figure S5. PNP inhibitor forodesine blocks 13C incorporation from 13 [ C5]-ribose-inosine into central metabolites but has little effect on 13 [ C6]-glucose catabolism. Hela cells Human T cells 1.2 1.0 1.2 13C6-Glc 1.0 13C6Glc 0.8 0.8 13C6Glc Inosine S7P G6P 1.0 Inosine 13C5-Ino S7P G6P 1.0 13C5-Ino 0.8 13C6-Glc 0.8 13C6Glc 13C5-Ino 0.6 13C6-Glc 0.8 0.6 0.8 13C5-Ino 0.6 13C5-Ino 13C5-Ino 0.6 0.6 0.6 0.4 0.4 0.4

Fraction Fraction a’

0.4 Fraction Fraction Fraction Fraction Fraction 0.4 Fraction 0.4 g’ a 0.2 d g 0.2 0.2 d’ 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 Hela0 cells5 Ring 0 1 2 3 4 5 6 7 0 1 2 3 4 5Human 6 0 T5 cellsRing 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 1.0 1.0 1.2 1.0 1.0 1.0 1.2 13C6-Glc 1.0 1.0 13C6Glc 13C6Glc 1.0 0.8 R1P E4P G1P 0.8 13C6Glc13C6Glc G1P Inosine 0.8 S7P G6P 1.0 Inosine 13C5-Ino S7P R1P G6PE4P 1.0 13C5-Ino 13C6-Glc 0.8 0.8 13C5-Ino 0.8 0.8 13C5-Ino 13C6-Glc 0.8 13C6-Glc 0.8 13C6-Glc 13C6Glc 13C5-Ino 0.8 13C6Glc 0.6 13C6-Glc 0.8 0.6 0.8 0.6 13C5-Ino13C5-Ino 0.6 13C5-Ino 13C5-Ino 0.6 13C5-Ino 0.6 13C5-Ino 0.6 13C5-Ino 0.6 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.4 Fraction 0.4 0.4 0.4 Fraction Fraction 0.4 Fraction Fraction Fraction Fraction Fraction Fraction Fraction

a’ Fraction

0.4 Fraction Fraction Fraction Fraction Fraction 0.4 Fraction 0.4 b’ g’ e’ h’ a 0.2 0.2 d b 0.2 g e h 0.2 0.2 0.2 0.2 0.2 d’ 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1 2 3 4 50.0 0 1 2 3 4 0 5 Ring 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 0 0 1 52 3 Ring4 5 6 0 1 20 3 14 25 63 7 4 5 0 1 20 3 1 4 25 63 4 0 1 2 3 4 5 6 1.0 1.0 1.0 0.5 1.0 1.0 0.5 1.0 13C6-Glc 1.0 1.0 13C6Glc 1.0 13C6Glc R1P R5P 1.0 F6P 13C6GlcUDPG 13C6Glc R5P F6P UDPG 0.8 E4P 13C5-Ino 0.8 G1P 0.4 R1P E4P G1P 0.4 0.8 0.8 13C6-Glc 0.8 0.8 13C5-Ino 0.8 13C5-Ino 13C6Glc 13C6-Glc 13C6-Glc 0.8 13C6-Glc 13C5-Ino13C6-Glc 0.8 13C5-Ino 0.8 13C6Glc C 0.6 0.6 13C5-Ino 0.3 0.3 13C5-Ino A 13C5-Ino 0.6 13C5-Ino 0.6 0.6 Hela Csi 0.6 13C5-Ino 0.6 13C5-Ino 0.6 0.6 0.6 13C5-Ino Hela Csi 0.4 0.4 0.4 0.2 0.4 0.4 0.2 Fraction Fraction Fraction Fraction 0.4 Fraction 0.4 Fraction Fraction Fraction 0.4 0.4 Fraction Fraction 0.4 Fraction Fraction Fraction Fraction Fraction Fraction Fraction c’ f’ 50 0.2 c 0.2 f 0.1 b’ i e’ h’ 0.1 i’ 0.2 b 0.2 e h 0.2 0.2 0.2 0.2 50 Glucosecomplete 0.2 0.2 complete 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1 2 3 4 0.05 0 1 2 3 4 5 6 0.0 0 5 6 11 Ring 0.0 0.0 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 6 0 1 2 3 4 5 0 10 21 23 3 4 4 5 0 1 02 13 24 35 46 5 6 0 5 6 11 Ring 40 40 GlucoseG- free G- 1.0 1.0 0.5 1.0 1.0 0.5 13C6-Glc F6P 13C6Glc 13C6Glc UDPG 13 R5PPNP PPP UDPG R5P F6P C -Ino0.8 0.8 0.4Hela cells Human0.4 T cells InosineG-/Inosine G-/Inosine 5 13C5-Ino 13C6-Glc 0.8 13C5-Ino 0.8 13C5-Ino 13C6Glc 30 P 13C6-Glc 1.2 1.0 30 1.2 13C5-Ino13C6-Glc 1.0 13C6Glc 0.6 0.6 0.80.3 13C5-InoS7P 0.6 G6P 0.6Inosine 0.80.3 13C5-InoS7P 13C6Glc G6P R1P Inosine 13C5-Ino 1.0 13C5-Ino Hela cells 1.0 Human13C6-Glc 0.8 T cells 0.8 13C5-Ino 0.4 0.4 0.2 0.4 13C6-Glc 0.4 0.2 13C6Glc Fraction Fraction Fraction Fraction Fraction 0.8 0.6 Fraction Fraction 0.6 20 0.8 1.2 13C5-Ino 13C5-Ino *** 1.2 1.0 c f 13C6Glc i 0.6 13C5-Inoc1.0’ f’ i’ 0.6 20 13C6-Glc 0.8 0.2 0.2 0.1 0.8 0.2 13C6Glc 0.60.2 0.1 Inosine S7P G6P0.6 1.0 Inosine 0.413C5-Ino S7P G6P 0.4 Cell growth Cell 1.0 13C5-Ino CO2 0.8 13C5-Ino 0.4

Fraction Fraction a’

0.4 Fraction Fraction 0.8 Fraction 13C6-Glc0.0 Fraction 0.0 0.0 13C6Glc Fraction 0.0 0.40.0 0.0 0.6 13C6-Glc0.4 0.8 0.6 g’ 10 0.8 13C5-Ino 0 1 2 3 4 5 0 1 2 3 a4 5 6 0.2 0 5 d6 11 Ring g0 1 2 3 4 5 0 1 2 3 4 5 6 0.2 0 5 6 11 Ring 0.6 13C5-Ino 13C5-Ino0.2 0.6 0.2 d’ 0.2 10 G6PDH 0.2 0.6 0.6 0.4 0.4 (relative confluence %) confluence (relative HeLa 0.0 0.0 0.0 0.4 0.0 0.0 0.0

Fraction Fraction a’

0.4 Fraction Fraction Fraction

Fraction Fraction Fraction 0.4 Relative cell confluence (%) confluence cell Relative 0 0.4 P 0 5 Ring 0 1 2 3 4 5 6 7 0 1 2 3 4 5 g’6 0 5 Ring 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 a 0.2P d g 0.2 0 50 100 hrs 0.2 1.0 0.2 Hela cellsd’ 0.2 Human T cells Relative cell confluence (%) confluence cell Relative 0.2 NADPH R5P 1.0 1.0 1.0 0 R1P P 1.0 13C6Glc 1.0 13 0.0 0.0 E4P G1P0.0 1.2 R1P 13C6Glc 1.0 G1P 0.0 C -Glc 0.0 0.81.2 13C6-Glc 0.0 1.0 13C6Glc E4P 0 50 100 Hours Hela cells 6 Glc6P0 1 2 3 4 5 6 7 Human T13C6-Glc cells0 50.8 0.8 Ring S7P0 1 2 3 0.84 5 6 7 0 1 2 3 0.84 5 13C5-Ino6 0.8 0.8 13C5-Ino 0.8 13C6Glc 0 5 Ring 0 1 2 3 4 5 Inosine6 13C6-Glc 13C6-GlcG6P 1.0 Inosine 13C5-Ino S7P 13C6GlcG6P 1.0 TK 13C5-InoSed7P 0.8 13C5-Ino 1.0 1.2 0.6 13C5-Ino1.0 13C5-Ino13C6-Glc 0.8 13C5-Ino 13C6Glc 13C5-Ino 1.2 13C6-Glc 1.0 1.0 13C6Glc 1.0 0.6 1.0 0.6 13C6-Glc 0.6 0.6 0.6 0.8 S7P R1P 1.0 0.8 0.8S7P 13C6Glc13C6Glc 0.6 1.0 0.8 0.6 HelaHours Csi Inosine G6P 1.0 E4PInosine 13C5-Ino G1P R1P G6P 13C5-Ino13C6Glc 13C5-Ino G1P 13C5-Ino 0.6 1.0 13C5-Ino 0.8 0.4 0.8 13C5-Ino0.4 E4P0.6 0.4 0.8 Fraction + 0.4 0.4 0.8 0.8 Fraction 0.4 0.6

B Fraction 13C5-Ino 0.8 Fraction 13C6-Glc 13C5-Ino Fraction 13C6-Glc13C6-Glc 13C6-Glc 0.8 13C6-Glc0.613C6Glc 0.4 0.8 13C6Glc Fraction Lan-1 Ino w/o G curve till 66hr0.6 0.8 0.6 0.4 0.4

0.8 Fraction ba’’ e’ h’

0.2 0.4 Fraction Fraction 13C5-Ino 13C5-Ino 13C5-Ino Fraction 0.6 13C5-Ino Fraction b0.6 0.2 e Fraction h 0.2 0.4 0.2 0.6 13C5-Ino 0.6 0.6 13C5-Ino0.4 0.6 0.6 0.2 0.6 13C5-Ino 0.2 g’ 50 0.6 a 0.2 d g 0.2 0.6 0.4 0.4 0.0 0.2 0.2 d’ 0.2 60 0.4 0.4 0.2 0.4 P 0.0 0.0 0.0 0.0 0.0 Glucose Fraction a’

0.4 0.4 Fraction Fraction Fraction Fraction 0.4 0.4 Fraction Fraction 0.4 P Fraction Fraction Fraction complete 0.4 Fraction

0 1 2 3 4 5 Fraction Fraction Fraction 0.4 Complete g’ 0 1 2 Fraction 3 4 0 1 2 3 4 5 6 0.0 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 6 a 0.2 d g 0.2 0.0 b’ 0.0 e’0.0 h’ 0.0 0.0 0.2 0.2 0.2 d’ 0.2 0.2 0.2 b e 0.2 Helah cells1.0 0 0.25 Gly3PRing 1.0 0 1 2 0.23 4 5 6 7 0.5 Human0 1 20.2 3 4 T5 6cells 1.0 0 5 Ring 1.0 0 1 2 3 4 5 6 7 0.5 0 1 2 3 4 5 6 40 GlucoseG- free X5P R5P 13C6-Glc F6P 13C6Glc 13C6Glc UDPG 0.0 0.0G- 0.0 0.0 1.0 0.7 0.0 1.0 UDPG 1.0 R5P F6P 0.0 0.0 0.01.0 0.00.6 0.8 0.013C5-Ino 0.8 1.0 0.0 0.41.0 0.6 0.0 0.8 13C5-Ino0.7 0.8 1.0 13C5-Ino 0.41.0 0 5 Ring 0 1 2 3 4 5 6 7 0 1 0 2 1 32 43 45 5 6 0 1 PEP2 0 3 54 Ring 0 1 2 3 4 5 6 R1P7 Malate0 1 2 3 4 13C6-Glc5 E4P6 13C6-GlcG1P0 1 2 3 4 5 6 13C6Glc 13C6Glc 13C6GlcG1P 0.5 0 1Isocitrate 2 3 4 0.85 6 0.6 0 1 2 3 4 5 0 PEP1 2 3 4 0.5 Isocitrate 0.6 MalateR1P E4P 40 InosineG-/Inosine G-/Inosine 0.8 0.6 13C6-Glc 0.6 0.8 13C5-Ino0.8 0.3 0.8 13C5-Ino 0.8 13C5-Ino 0.30.8 13C5-Ino 1.0 1.0 1.0 1.0 1.0 13C6-Glc 0.5 1.0 13C6-Glc 0.5 1.0 13C6-Glc 13C6-Glc1.0 13C6Glc 0.8 13C5-Ino13C6-Glc0.5 13C6Glc0.6 13C6Glc 0.6 13C6Glc 30 1.0 13C6-Glc 13C6Glc 0.4 Hela cells 13C6Glc1.0TA 13C6Glc 0.4 Human T cells0.5 R1P E4P R5P G1P 0.6 F6P13C5-Ino UDPG13C5-Ino13C6Glc0.6 13C5-Ino13C5-Ino 0.6G1P 13C5-Ino 13C5-Ino UDPG 13C5-Ino 0.8 R1P0.4 0.4 E4P0.4 0.4R5P 0.6 13C5-Ino0.2F6P 0.6 13C5-Ino0.4 0.6 0.4 13C5-Ino 0.4 0.6 0.20.6 0.8 0.8 0.6 Fraction 0.7 Fraction 0.4 0.6 Fraction 0.8*** 13C5-Ino 0.81.0 Fraction 0.8 0.8 13C6-Glc 13C6-Glc 0.8 13C6-Glc 13C6-Glc13C5-Ino 0.3 0.8 13C5-Ino 13C5-Ino0.8 13C6Glc 13C5-Ino1.0 0.3 13C6Glc Fraction 0.7 Fraction 13C6-Glc 0.4 0.3 Malate 0.3c ’ f’ Fraction Fraction 0.4 PEP Isocitrate c0.6 0.4 0.4 f PEP i Isocitrate0.4 Malate i’ Fraction 0.4 0.4 Fraction Fraction Fraction 0.5 0.2 0.2 0.10.4 0.6 0.1 Fraction

13C5-Ino Fraction 0.5 Fraction Fraction Fraction Fraction 0.6 0.2 0.2 Fraction 0.2 Fraction Fraction 0.6 13C5-Ino 0.6 13C5-Ino 0.6 0.813C5-Ino 0.3 e Fraction 13C5-Ino 0.2 0.3 13C5-Ino 0.6 0.6 a 0.613C5-Ino 0.2 0.6 0.6 i 13C6-Glc 0.6 0.8 a e 0.2 i 13C6-Glc 0.213C6-Glc 0.5 13C6Glc 13C6Glcb’ 0.5 13C6Glc e’ h’ 20 0.2 0.1 0.4 b 0.2 0.2 e h 0.4 0.2 0.2 0.2 20 0.4 0.4 0.4 0.6 13C5-Ino0.2 0.0 13C5-Ino 0.1 0.0 13C5-Ino 0.00.2 0.1 0.2 0.0 0.1 0.0 0.0 Cell growth Cell 0.4 0.4 0.4 0.4 0.4 0.6 13C5-Ino 13C5-Ino 13C5-Ino Fraction Fraction Fraction Fraction 0.4 0.4 Fraction Fraction 0.4 0.4 Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction 0.3 0 1 2 3 4 5 0 1 2 3 4 5 6 0 5 6 110.3Ring 0 1 2 3 4 5 0 1 2 3 4 5 6 0 5 6 11 Ring 0.0 0.0 0.0 0.0 c’ 0.0 0.0 f’ 0.0 0.0 0.0 0.2 c Hela bfcells’ i e’ 0.3 h’ Human T cells0.0 i’ 0.0 0.3 0.0 0.2 0.2 0.2 0 Fraction 0.41 2 3 0.1 0 1 2 3 4 5 0 1 0.22 0 3 14 25 3 4 0.2 0.4 0.10 1 2 3 4 5 0.2 Fraction + 0.2 0 1 2 3 0 1 2 3 4 b e 0.2 h 0.2 0 1 2 3 4 Fraction 0.2 Fraction Fraction 0 1 2 3 4 5 6 e Fraction 0.2 i 0 1 2 3 40.2 5 6 e 0 1 2 3 4 5 i 0 1 2 3 4 1.0 0.6 a1.00.7 0.71.0 P 0.6 a 0.7 0.2 10 0.0 1.0 1.0 1.0 1.0 0.5 1.0 0.7 0.5 0.0 0.0 0.0 0.0 0.00.2 0.0 0.00.1 KG 0.0 0.10.0 0.0 0.2 0.0 0.1 1.0 1.0 (relative confluence %) confluence (relative PEP Malateα P Isocitrate 0 1 2 3 4 5 0.5 PyruvateIsocitrate 0.6 0.6 13C6-GlcAspPEP 0.5 Pyruvate 0.6 MalateαKG 13C6Glc0.1 Asp 13C6Glc Lan-1 0 1 2 3 4 0.8 0 1 0 21 32 34 45 5 6 0.8 0 1 2 03 14 52 63 4 0.85 0 5 06 111 Ring2 3R5P 0.84 0 1 02 1 3 2 43 54 5 F6P6 0 1 2 3 4 5 6 UDPG0 5 6 11 Ring0.6 R5P F6P UDPG 13C6-Glc 0.013C6-Glc 0.013C6-Glc13C6-Glc0.8 0.013C6-Glc 0.8 0.8 0.4 0.8 0.0 0.4 0 13C6-Glc 0.5 0.5 13C5-InoEry4P13C6Glc 0.0 13C6Glc13C6Glc 0.5 13C6Glc13C6Glc 0.8 13C5-Ino0.0 13C6Glc 0.8 13C5-Ino 1.0 1.0 0.5 0.4 1.0 0 1 2 3 1.0 0 1 2 3 4 5 0.5 0 1 2 3 0.4413C6-Glc 13C6-Glc 0 1 2 3 40.5 5 13C6Glc 0.6 13C5-Ino 0.6 13C5-Ino 0.60.4 13C5-Ino13C5-Ino 0.6 13C5-Ino13C5-Ino 0 13C5-Ino1 2 3 13C5-Ino 0 1 2 3 4 Relative cell confluence (%) confluence cell Relative 13C6-Glc 0.4 0 R5P F6P 13C6Glc 1.0 13C6Glc0.6 0.7 UDPG0.6 0.613C5-Ino 13C5-Ino0.3 0.40.6 13C5-Ino 0.4 13C5-Ino 0.3 13C5-Ino 0 25 50 75 hrs UDPG 0.3 Glycolysis1.0 R5P F6PFruc6P 0.3 1.0 13C5-Ino 1.0 0.6 0.7 0.6 0.8 13C5-Ino 0.8 0.4 0.8 13C5-Ino 0.3 0.8 13C5-InoαKG 0.3 0.4 0.3 Fraction Fraction 0.4 0.4 Pyruvate0.4 0.4 0.6 Asp 0.3 13C6-Glc Fraction 13C6Glc

Fraction Pyruvate KG

Fraction Asp Fraction Fraction α 0 50 100 13C6-Glc 0.2 Fraction j 0.4 Fraction 0.4 Fraction 0.2 0.6 0.8 f Fraction 0.2 0.2 0.8 e 0.2 i0.4 0.4 Fraction e Fraction i 0.4 Fraction 0.4 a Fraction 0.2 a Fraction 0.8 0.8 Fraction 13C6-Glc Fraction 0.2 0.6 0.6 13C5-Ino 0.3 b13C6-Glc 0.50.3 13C5-Ino13C6-Glc b f Fraction 0.2 Fraction Cell growth (relative growth Cell %) confluence Hours 0.2 13C5-Ino 0.2 0.6 0.2 0.6 0.2 13C6Glc 13C6Glc c’ 0.5 j 13C6Glc 0.1 0.1 0.1 c 0.20.1 f 0.2i f’ i’ 0.6 13C5-Ino 0.6 0.213C5-Ino 0.4 0.213C5-Ino 0.1 0.1 0.1 Hours 0.6 13C5-Ino 0.6 13C5-Ino0.2 0.1 0.4 13C5-Ino0.2 0.4 0.4 0.0 0.2 0.0 0.4 0.00.0 0.4 0.0 0.2 Fraction Fraction Fraction 0.0 0.0 0.0 0.0 Fraction Fraction Fraction Fraction Fraction 0.3 Hela cells 0 0.41 2 3 4 5 0 0.41 2 3 4 Human T cells 0.0 0.0 0.0 0.3 0 1 2 3 0 1 2 3 0 Fraction 1 2 3 40.0 5 0 1 2 3 0.04 0 1 2 3 40.0 5 0.0 Fraction Fraction c’ f’ 0 1 2 3 j 0.4 0 10.4 2 3 4 0.0 0.0

c f i f Fraction i’ 0 1 2 3 0 1 2 3 4 5 0 1 2 3 4 0.2 0.2 0.1 0.20.1 Fraction Fraction Fraction 1.0 1.00.6 1.00.7 0.2 b0.7 1.0 0.2 0 1 0.62 3 4 5 0 1 0.72 3 4 5 6 b0 5 6 11 Ring f 0 1 2 0.23 4 5 0 1 2 3 4 5 6 0 5 6 11 Ring 0.8 0.2 0.2 0.8 1.0 1.0 0.7 0.8 j PEP PyruvateIsocitrate 0.6 LactateMalateαKG 0.80.6 SuccinateAspPEP 0.1IsocitrateGlu 0.8 0.2Lactate Malate 0.2Succinate Glu 0.0 0.80.0 0.50.0 0.8 0.0 0.0 0.7 0.5 0.0 Pyruvate 0.6 αKG 0.60.8 Asp 0.7 0.1 0.8 13C6-Glc 13C6-Glc13C6-Glc 0.8 0.0 0.8 0.0 0.8 0 1 2 3 4 5 0 1 13C6-Glc2 3 4 5 6 0 13C6-Glc5 6 11 Ring0.60.5 0.013C6-Glc 0 1 2 3 4 0.55 13C6-Glc13C6-Glc013C6Glc 1 2 3 4 50.6 6 13C6-Glc0 13C6Glc5 6 11 Ring0.5 0.013C6Glc 13C6Glc 0.0 13C6Glc 0.6 0.013C6Glc D 0.4 0.6 0 1 2 3 4 50.4 013C6Glc1 2 3 0.64 13C6Glc 0.5 13C6Glc 13C5-Ino 13C5-Ino13C5-Ino0 1 2 3 0.6 0.6 13C5-Ino 0.6 13C5-Ino 0.60.4 13C5-Ino 0.4 0.6 13C5-Ino13C5-Ino13C5-Ino 0.5 13C5-Ino13C5-Ino 0.4 13C5-Ino13C5-Ino0 1 2 3 13C5-Ino0 1 2 3 0.54 5 13C5-Ino0 1 2 3 4 0.3 0.6 13C5-Ino 0.6 13C5-Ino 0.4 13C5-Ino 0.4 0.8 0.4 0.3 0.8 0.8 0.3 0.40.3 0.40.3 0.8 0.4 Fraction Fraction 0.4 0.4 0.4 Lactate 0.4 0.8 Succinate Glu Lactate0.30.4 Succinate Fraction Fraction 0.7 0.8 Glu

Fraction 0.7 Fraction Fraction Fraction

Fraction Fraction 0.4 Fraction 0.4 0.2 j Fraction 0.3

Fraction 0.2 0.3 Fraction Fraction Fraction

f Fraction Fraction Fraction e Fraction Fraction Fraction a 0.2 i Fraction 0.2 a ke 0.2 i b 0.2 0.6 c13C6-Glc g 13C6-Glc0.2 0.6 b13C6-Glc cf 13C6Glc0.2 g 13C6Glc 0.6 k 13C6Glc 13 0.2 0.20.1 0.2 0.2 0.2 0.6 0.2 0.6 0.2 j 0.2 0.1 0.1 0.20.1 0.5 0.20.1 0.6 C5-Ino 13C5-Ino 13C5-Ino0.1 13C5-Ino 13C5-Ino0.1 13C5-Ino0.1 0.5 13C5-Ino 0.0 0.0 0.00.0 0.0 0.4 0.0 0.0 0.4 0.0 0.0 0.4 0.0 0.00.0 0.00.0 0.4 0.00.0 0.0 0.4 Ala 0 1 2 3 00 1 1 2 32 4 3 5 0 0 1 112 232 43 3 54 0 01 21 3 2 4 3 0 1 2 3 4 5 0 1 2 3 4 0.4 0 1 2 3 4 0 Fraction 10.3 2 3 4 5 0 1 2 3 4 0.3 Fraction Fraction

0 1 2 3 0 Fraction 1 1 2 32 4 3 5 0 1 2 3 4 0 Fraction 1 2 3 4 5 Fraction 1.0 0.7 Fraction g0.8 k g 1.0 0.4 0.2 c0.80.8 1.0 1.0 0.2 0.40.7 c 0.80.8 0.8 0.2 k 0.8 KG 0.2 0.8 0.2 0.2 Pyruvate Lactateα 0.80.6 SuccinateCitrateAsp 0.7 FumarateGlu 0.7 0.1GSH Lactate Succinate FumarateGlu 0.8 0.7 PyruvateHela cells αKG 0.80.6 CitrateAsp 0.70.7 Human T cells0.7 0.1 GSH 0.8 13C6-Glc 0.0 13C6-Glc 0.8 0.6 0.8 13C6-Glc 0.6 13C6-GlcGlycolysis0.30.5 13C6-Glc13C6-Glc 0.60.6 0.013C6-GlcHela13C6-Glc13C6Glc cells 0.013C6-Glc 13C6Glc 0.3 0.0 13C6Glc13C6Glc13C6Glc 0.60.6Human 0.013C6Glc 13C6Glc T cells0.6 0.0 13C6Glc Ala Hela cells Human T cells 0.6 1.0 0 1 2 3 0.6 0 1 2 3 40.6 0.7 0 13C6Glc1 2 3 4 50.5 1.0 0.6 0.7 0.6 PEP 13C5-InoPyruvate 0.6 13C5-Ino13C5-Ino 13C5-Ino13C5-Ino 0.50.5 13C5-Ino13C5-Ino 0.5 13C5-Ino 0.6 0 1 2 0.50.53 0 1 2 30.5 4 0 1 2 3 4 5 Lactate 0.4 13C5-InoPEP 0.6 13C5-InoIsocitrate 0.6 0.70.8 13C5-Ino13C5-InoMalate 13C5-Ino13C5-Ino13C5-Ino 13C5-Ino13C5-InoIsocitrate 13C5-Ino 1.0 0.6 0.7 1.0 0.6 0.7 1.00.4 0.4 0.60.80.5 0.4 0.6 0.4 1.00.4 PEP 0.60.80.5 0.70.8 0.6 Malate 0.4 0.20.40.3 0.8 0.4 0.4 0.2 0.8 0.40.4 0.4 PEP Isocitrate Malate 0.4 Isocitrate0.4 CitratePEP13C6-Glc 0.7 IsocitrateFumarate13C6-Glc 0.60.70.5 MalateGSH13C6-Glc 0.40.3 PEPCitrate IsocitrateFumarate MalateGSH13C6Glc 0.6 PEP Fraction Malate 0.3 0.5 0.3 13C6Glc 0.7 13C6Glc 0.60.7 0.5 Fraction Fraction 0.5

0.5 0.6 Fraction 0.3 0.4 0.4 0.5 Fraction j 0.4 0.30.3 0.4 0.3 Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction

Fraction f 0.8 Fraction Fraction Fraction Fraction Fraction 0.8 0.8 CO Fraction 0.2 d 0.6 0.8 d 13C6-Glc 13C6-Glc 0.5 13C6-Glc b 0.2 2 c 0.30.6 g13C6-Glc13C5-Ino13C6-Glc 0.2 0.6 hk13C6-Glcb13C6-Glc13C5-Ino0.2 0.5 0.4 lc13C6-Glcf13C6-Glc13C5-Ino 0.2 0.30.6 g13C6Glc13C5-Ino 0.6 hk 13C6Glc13C5-Ino 0.6 13C6Glc13C5-Ino 13C6Glc0.2 13C6Glc0.2 0.5 13C6Glc0.10.2 0.2 0.4 0.2 0.10.2 j 13C6Glc0.20.2 0.4 13C6Glc0.2 0.5 0.4 l 13C6Glc 0.4 Hela cells 0.4 0.1 Human T 0.2cells 0.50.3 13C5-Ino 0.2 0.5 13C5-Ino13C5-Ino 0.3 0.6 13C5-Ino 13C5-Ino 0.4 13C5-Ino 0.6 13C5-Ino 13C5-Ino 13C5-Ino 0.6 13C5-Ino13C5-Ino 0.10.1 13C5-Ino0.1 0.4 0.3 0.1 0.6 13C5-Ino13C5-Ino 0.10.1 0.5 13C5-Ino13C5-Ino0.1 0.40.5 0.3 13C5-Ino13C5-Ino 13 0.4 Fraction 0.4 0.3 0.4 0.4 HelaFraction cells Human0.3 T cells 0.3 0.4 Fraction CO 0.3 0.0 0.0 0.2 0.2 Fraction Fraction C -Glc 0.0 2 0.0 0.0 0.00.0 0.0 Fraction 0.2 0.40.2 0.4 0.3 1.0 0.66 0.7 1.0 0.0 0.6 a 0.0 0.7 e 0.00.0 0.3 0.2 i 0.00.00.0 a0.00.0 Ala e0.0 0.3 0.2 i 0.3 Fraction 0.4 0.3 Fraction Fraction 0.4 00 1 1 2 23 4 3 5 0 1 2 3 4 0.3 0 1 2 3 4 5 0.4 0.4 0 1 2 3 0 Fraction 1 2 3 4 0 1 2 3 4 Fraction Fraction Fraction 0 1 2 3 4 5 0.7 Fraction Fraction Fraction Fraction 0 1 2 3 4 5 0.6 0.2 0 1 2 3 4 0.6 0.3 0.3 Fraction Fraction 1.0 0.2 Fraction Fraction Fraction Fraction 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 0.2 Fraction Malate Fraction 0 1 2 3 00 1 1 2 23 4 3 5 1.0 0 0.21 2 3 4 0 0.21 2 3 4 5 0.7 PEP IsocitrateFraction e Fraction Isocitrate 0.20.6 PEP d 0.1 e Malate0.2 0.1 i d 0.1 e i a 0.2 i 0.5 a e 0.2 0.8i 0.5 a 0.8 0.2 0.6 h 0.2 l a h 0.2 0.1 0.8 0.8 Acetyl0.4 CoA 0.8 0.8 0.20.1 PEP Isocitrate 0.60.4 Malate 0.80.8 0.1 PEP 0.8 Isocitrate0.2 0.2 Malate l 0.2 0.1 13C6-Glc 0.2 13C6-Glc 0.10.5 13C6-Glc 13C6Glc 0.50.813C6Glc0.1 0.0 13C6Glc0.1 0.0 0.2 0.5 0.1 0.6 0.1 0.4 Lactate 0.8 SuccinateCitrate0.1Hela cells0.70.80.7 Fumarate0.0 Glu0.4 0.7 0.1GSHLactate0.5 0.8 Human0.1 13C6-GlcCitrateSuccinate T cells0.70.70.8 Fumarate0.0 Glu 0.7 0.10.0GSH 0.10.1 0.0 0.6 13C5-Ino 13C5-Ino 13C6-Glc0 1 2 3 13C6-Glc0 1 2 3 40.55 0 1 2 3 4 13C6Glc 0 13C6Glc1 2 3 40.5 5 13C6Glc 0.0 0.0 13C5-Ino 13C6-Glc0.4 0.6 13C5-Ino0.6 0.0 0.60.4 13C5-Ino0.00.0 13C6-Glc0.4 13C5-Ino0.00.0 0 1 2 0.43 0.0 0 1 2 3 4 0.0 0.00.3 0.6 1.0 0.0 0.3 0.60.013C6-Glc 13C6-Glc 0.6 0.00.7 13C6-Glc13C6-Glc0.3 13C5-Ino1.0 13C6Glc 0.3 0.613C5-Ino13C6Glc13C6Glc 0.60.6 0.00.00.7 13C6Glc13C6Glc 0.6 0.0 13C6Glc 0.00.0 0 1 2 3 4 5 0 1 2 3 4 0.6 0.6 1.013C5-Ino 0 1 2 3 0.6 1.00 0 1 12 23 43 50.44 0.700 11 22 33 4 4 50.6 13C5-Ino 0 1 13C5-Ino2 3 4 0.45 13C5-Ino 0 1 2 3 0 1 2 3 13C5-Ino0.3 0 1 2 3 4 5 Citrate0 1 2 0.50.53 4 13C5-Ino13C5-Ino0 1 Malate2 3 40.5 0.35 13C5-Ino0.3 0.6 0.50.5 1.0 00 11 2 23 40.53 5 1.0 0 1 2 3 4 0.70 0 11 2 33 4 4 5 Fraction Fraction 0.4 PEP 13C5-Ino13C5-Ino0.4Isocitrate 0.6 13C5-InoαPEPKG 13C5-Ino13C5-InoIsocitrate 13C5-Ino13C5-InoMalate 0.3 13C5-Ino

Fraction Asp 0.5 Fraction Pyruvate 0.7 0.5 0.6 0.2 Fraction 1.0 Fraction 0.3 0.6 1.0 0.7 e 0.8 Fraction 0.4 1.0 0.2 0.4 Pyruvate αKG 0.3 Asp 1.0 a 1.0 0.4 1.00.2 0.2 i 0.7 Fraction 0.40.4 a e 0.80.8 0.2 0.2 i 0.40.4 1.0 0.4 1.0 0.7 0.6

0.8 Fraction 13C6-Glc 13C6-Glc 0.4 Fraction 13C6-Glc 0.4 0.5 0.2 KG Fraction 0.8 13C6Glc 0.8 Fraction KG Pyruvate α 13C6-Glc13C6GlcFraction 0.4 Asp13C6-Glc13C6Glc 0.2 Pyruvate α 0.6 0.2 Asp 0.1 0.4 0.2 0.3 a13C6-Glc0.3 e 0.2 0.6 0.50.4 i 0.5 Pyruvatea 13C6Glc e αKG iAsp13C6Glc Fraction Fraction Pyruvate 0.1 αKG Fraction Asp0.3 0.1 0.30.3 0.3 13C6Glc0.2 0.6 0.5

0.8 Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction

0.6 Fraction 0.8 0.8 0.6 13C5-InoFraction dg13C5-Ino 0.2 0.8 0.4 k13C5-Ino 0.60.6 0.1l13C6-Glc 13C5-Ino13C5-Ino d13C6-Glcg13C5-Ino13C5-Ino0.2 0.8 13C5-Ino 0.8 13C6-Glc 13C6-Glc 0.5 13C6-Glc 0.8 0.2 0.8 c 0.1 0.20.2 0.6 h13C6-Glc13C5-Ino 0.20.1 c 0.10.1 0.5 0.4 0.2 0.40.6 hk13C6Glc13C5-Ino 0.20.1 0.6 l 13C5-Ino 13C6Glc13C5-Ino 0.0 0.0 13C6Glc 0.0 13C6Glc0.2 0.3 0.5 0.0 13C6Glc 0.0 0.2 0.0 0.2 0.3 0.2 13C6Glc 0.1 0.5 0.4 0.6 13C5-Ino 13C5-Ino 0.10.1 0.6 0.3 13C5-Ino 0.1 0.6 13C5-Ino 0.4 13C5-Ino 0.3 0.6 13C5-Ino 0.4 0 1 2 3 0 1 2 3 4 5 Fraction 0.4 0 1 2 3 4 0 10.0 2 3 0 1 20.0 3 4 0.450.4 0 1 0.02 3 0.34 0.10.10.0 0.6 13C5-Ino 0.10.0 0.6 13C5-Ino 0.0 13C5-Ino 0.6 13C5-Ino 0.6 Fraction 13C5-Ino 13C5-Ino 0.4 Fraction 0.4 0.3 Fraction Fraction Fraction 0.2 Fraction Fraction 0.4Krebs e Fraction i0.0 0.2 ej 0.4 i 0.4 0.0 0.0 0.2 0 1 2 3 4 5 f 0 Fraction 1 2 3 4 1.0 0.7 a0.00.0 0.0 0 1 2 3 0.0 a0.00.0 0.3 0.2 0.00.0 0 0.2 Fraction 1 2 3 0.0 0 1 Fraction 2 3 4 5 0 Fraction 1 2 3 4 0.3 1.0 1.0 0.4 1.0 b 0.4 0.7 Ala 0.3 0.4 0 0.2 1 2 3 0 1 2 3 4 0 Fraction 1 2 3 4 5 b f 0.2 0.4 0 1 0.32 3 4 Fraction Fraction Fraction 0 10.1 2 3 4 5 0 1 2 3 4 5 1.0 0.20.2 0.7 0 1 2 3 j4 0.4 0.4 j Fraction Fraction KG 0 10.1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 j 0.4 α 0.4 0.10.2 0 1 2 f 3 Fraction 0 1 2 3 4 5 Pyruvate Asp 1.0 Fraction Fraction Fraction f Fraction Asp 0.6 Fraction Fraction Fraction Fraction 0.10.2 0.2 0.2 Oxaloacetate 0.8 Pyruvate0.8 Isocitrateb αKG 0.6 Asp0.2 0.1 1.0 1.0 0.7 b 0.8 0.8 b0.4 f 0.2 Cycle Pyruvate 0.4 0.2 αKG 0.6 0.8 Asp 0.8 b f 0.2 0.1 j 0.2 0.2 13C6-Glc 13C6-Glc 0.0 0.5 13C6-Glc 0.0 0.8 j 0.2 0.0 0.8 0.0 0.1 0.0 0.20.0 Pyruvate 0.2 αKG Asp 0.1 0.2 Citrate0.2 0.7 Fumarate 0.813C6Glc0.7 0.0GSH 0.813C6Glc 0.0 Citrate0.5 13C6Glc 0.0 Fumarate GSH 0.6 13C5-Ino 0 1 2 3 0.10 1 2 3 4 5 13C6-Glc0 1 2 3 4 13C6-Glc 0.5 0.7 13C6-Glc0 1 2 3 40.70.8 5 0.0 0.8 0.0 0.1 0.0 0.6 13C5-Ino 0.6 0.4 13C5-Ino 0.6 0 1 2 3 0 01 21 3 24 53 0 1 2 3 4 13C6Glc0 1 2 3 4 13C6Glc 13C6Glc 0.0 0.0 0.0 0.3 0.6 13C6-Glc0.6 13C5-Ino0.0 13C6-Glc0.6 13C5-Ino0.3 0.0 0.4 13C5-Ino0.6 0.0 0.6 0 1 2 3 0 1 2 3 0.54 5 0 1 2 3 4 0.0 1.0 0.0 13C6-Glc 1.0 0.0 0.6 0.713C5-Ino 0.6 13C5-Ino13C6Glc 0.4 13C5-Ino13C6Glc 0.0 13C6Glc 0.0 0.0 0 1 2 3 0 1 2 3 4 5 0 1 2 3 4 Pyruvate 0.3 0.5 0.5 0 1 2 3 1.00 1 2 3 4 5 0.81.00 1 2 3 4 0.6 0.7 13C5-Ino 0.6 13C5-Ino 0.8 13C5-Ino 0.4 0.4 0 1 NADPH2 3 13C5-InoPyruvate0 1 2 3 4 5 13C5-Ino0 α1KG 2 3 4 0.813C5-Ino Asp 0.3 13C5-Ino 0.5 13C5-Ino 0.5 0.8 0 1 2 3 0 1 2 3 4 0.45 0 1 2 3 4 Fraction Fraction 0.6 CO 0.8 13C5-Ino Fraction Fraction j 0.4 0.4Lactate 2 SuccinatePyruvate0.3 0.7 GluαKG LactateAsp 0.8 Succinate Glu f Fraction 0.4 0.8 0.6 0.7 0.8 0.2 0.8 0.2 0.4 0.8 0.8 Fraction 0.4 0.8 Fraction 0.4 0.2 Fraction 0.4 0.4 0.3 0.8 Fraction Fraction 0.8 0.8 0.8 b 0.8 13C6-Glc Fraction b 13C6-Glc f 0.2 j 0.4 0.8 0.4 13C6-Glc 0.5 0.8 f Fraction

13C6-Glc Fraction Fraction Fraction Lactate 0.8 Succinate 0.2 Glu 0.2 Lactate 0.8 Succinate0.3 Glu 0.3 0.6 Lactate Succinate13C6-Glc13C6Glc0.2 j0.7 0.6 Glu13C6-Glc 13C6Glc 0.5 Lactate13C6Glc13C6Glc 0.8 Succinate13C6Glc 0.7 0.6 Glu13C6Glc 0.7 Fraction 0.1 0.7 0.2 0.2 0.3 0.3 0.6 Fraction Fraction Fraction Fraction Fraction b 0.6 0.2

Fraction b f 0.6 d13C5-Ino 0.6 13C5-Ino0.2 0.4 l 13C5-Ino0.2 0.1d 0.5 0.6 j 13C6-Glc 13C6-Glc 0.6 13C6-Glc 0.1 0.2 0.6 h 0.2 0.6 13C6-Glc13C5-Ino 0.6 13C6-Glc13C5-Ino13C5-Ino0.1 0.6 0.6 13C6-Glch13C5-Ino13C5-Ino 0.2 l13C6Glc13C5-Ino13C5-Ino0.2 13C6Glc13C5-Ino 0.6 0.5 13C6Glc13C5-Ino 0.6 0.0 0.60.0 13C6Glc 0.0 13C6Glc 13C6Glc 0.1 0.6 0.2 0.2 0.60.4 0.1 0.6 Hela cells 0.6 Human T cells0.0 0.1 0.30.4 0.013C5-Ino 0.0 0.5 0.4 13C5-Ino 0.6 0.5 0.4 13C5-Ino 13C5-Ino 0.5 0 13C5-Ino1 2 3 0 1 13C5-Ino2 3 4 50.4 0 113C5-Ino20.1 3 40.4 0.5 13C5-Ino0.0 0.0 0.4 13C5-Ino 0.0 0.1 0.1 0.30.4 13C5-Ino 0.4 13C5-Ino 13C5-Ino Fraction Fraction Fraction Fraction 0 1 2 3 0 1 j 2 3 4 50.4 0 1 2 3 4 0.4 0.0 0.0 0.0

Fraction Fraction 0.3 f Fraction !-Ketoglutarate

Fraction Fraction 0.4 Fraction Fraction 0.3

0.0 0.4 Fraction

Fraction 0.4Fraction 0.7 0.0 Fraction 0 1 2 3 4 5 Glu 0 1 2 3 4 0.4 1.0 0.6 0.4 1.0 0.0 Malate 0.6 0.4 0.7 0 0.21 2 3 0.0 0.4Fraction 0.0 k 0.0 0.4 0.4 0.4 0.8 0.4 0.40.8 b 0 0.21 2 3 4 0 10.2 2 3 4 5 c 0.8 gb 0.2 f 0 0.2 1 2 3 cj 0 1 2 3 4 5 g 0 1 2 3 4 k 0 0.21 2 3 4 5 0.8 0.2 Fraction 0.3 0.2 0.3 0.2 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 Fraction 0.2 Fraction Fraction Fraction Fraction 0.3 Malate PEP Isocitrate Isocitrate Fraction 0.6 0.8 PEP 0.3 Malate0.1 Fraction 0.2 0.8 0.2 Fraction Fraction 0.8

Lactate Fraction Glu Fraction Fraction Succinate Lactate 0.8 Succinate Glu Fraction 0.5 k 0.7 0.5 0.6 0.8 0.7 g 0.1 k 0.1 g 0.2 0.8 c g 0.2 0.8 c g k 0.2 Lactate c 0.8 0.2 0.2 Glu 0.8 0.2 c 0.2 0.1 k 13C6-Glc0.2 13C6-Glc 0.513C6-Glc 13C6-Glc0.2 13C6-Glc 13C6Glc0.0 0.20.6 13C6-Glc 0.0 0.213C6Glc 0.013C6Glc Succinate0.6 0.7 Lactate 0.8 0.2 Succinate 0.7 Glu 0.4 0.6 0.4 0.6 0.5 13C6Glc 0.0 13C6Glc 0.00.0 13C6Glc0.1 0.00.0 0.00.0 0.0 0.0 13C5-Ino0.1 13C5-Ino0.6 0 1 2 3 0.10 1 2 3 4 5 13C6-Glc0 0.61 2 3 4 13C6-Glc 0.6 13C6-Glc 13C6Glc 0.6 0.1 13C6Glc Ala 0.6 13C5-Ino 0.413C5-Ino 13C5-Ino0.6 13C5-Ino0.5 13C5-Ino 13C5-Ino 0.4 13C5-Ino0.6 0.0 13C5-Ino0 1 2 13C5-Ino3 0 0.50 1 12 3213C5-Ino 4 3 0 0 1 1 2 2 3 3 4 40.6 5 5 00 1 1 2 23 34 13C6Glc0 1 2 3 4 0 1 2 3 4 5 0.0 0.0 0.3 0.0 0.6 0.0 0.0 0.0 0.6 0.0 0.0 Ala 0.4 0.0 0.00.4 0.3 0.0 Ala 0.80.413C5-Ino 0 1 2 3 0.813C5-Ino0.4 0.5 0.813C5-Ino 0.8 13C5-Ino 13C5-Ino 0.5 13C5-Ino 0 1 2 3 0 1 2 3 4 0 1 2 0.33 4 5 0.4 0.8 0.4 0.3 0.80 1 2 3 4 0 1 2 3 4 5 0.4 0 1 2 3 0.80 1 2 3 4 0.80 1 2 3 4 5 Fraction Fraction 0.4 0 1 0.4 2 3 0 1 2 3 4 0.8 0 1 2 3 4 5 0.4 0.4 Fraction 0.4 Glu 0.7 LactateFraction Succinate Citrate Lactate GSHSuccinate 0.4 Fraction Fraction Fraction 0.7 0.8 Glu 0.2 Fraction 0.3 0.7 Fumarate 0.8 0.7 Citrate Fumarate GSH Fraction 0.2 0.8 0.3

0.4 Fraction 0.4 0.4 0.7 0.7 0.8 Fraction Fraction 0.8 eFraction 0.4 0.8 0.8 0.4 a 0.2 0.4Fraction i g 0.8a k 0.8e 0.2 i g 0.4 0.2 c 13C6-Glc c Fraction 0.3 k 0.6 0.3 0.2 0.6 0.6 0.7 13C6-Glc Fraction Citrate13C6-Glc GSH Fraction Fraction 13C6-GlcFraction 0.3 0.7 Fumarate0.2 13C6-Glc13C6Glc 0.6 13C6Glc Fumarate 0.2 0.2 0.6 Fraction 0.3 Citrate 0.6 0.6 GSH Citrate 0.7 Fumarate0.1 0.7 GSH0.1 Citrate0.2 0.7 Fumarate0.1 0.6 0.7 0.2 GSH 0.2 13C6-GlcCO 2 0.6 g k 13C6Glc 13C6Glc 0.7 g 13C6Glc 0.7 13C6Glc 0.1 13C5-Ino 0.1 0.2 0.5 c 0.2 0.5 0.2 0.6 0.50.6 0.2 0.5 c 0.2 k 0.3 0.6 0.6 13C6-Glc 13C5-Ino 0.3 13C5-Ino13C6-Glc13C5-Ino 0.6 0.113C6-Glc13C5-Ino13C5-Ino 13C6-Glc13C5-Ino13C5-Ino 0.3 13C5-Ino13C6Glc13C5-Ino0.2 0.6 0.5 13C6Glc13C5-Ino 0.6 0.5 13C5-Ino 0.0 13C6-Glc 13C6-Glc0.0 0.0 0.3 13C6Glc 0.6 13C6Glc0.0 0.6 13C6Glc 0.1 13C6Glc 0.0 0.0 0.0 0.4 0.0 0.0 0.0 0.40.2 0.0 0.5 0.4 0.0 0.5 0.4 0.40.2 0.4 0.1 0.4 0 1 0.52 3 13C5-Ino0 1 2 0.53 4 5 13C5-Ino0 1 2 3 4 0.5 0 1 0.42 0.53 4 5 13C5-Ino 0.4 13C5-Ino Ala 0.4 13C5-Ino 13C5-Ino 0.5 13C5-Ino 0.5 13C5-Ino 13C5-Ino 0 1 2 3 0 1 213C5-Ino30 4 1 2 30 1 13C5-Ino2 3 4 5 0 13C5-Ino10.0 0 2 1 32 3 4 0 1 0.02 3 0.34 0 1 20.0 3 0.44 0.35 0.0 0.0 0.0 Fraction Fraction 0.3 0.4 Ala Fraction Fraction 0.3

0.2 Fraction 0.3 0.3 0.4 Fraction Fraction Fraction Fraction Fraction Fraction Fraction 0.4 Fraction 0.2 0.4 0.4 Fraction 0.2 1.0 1.0 0.4 0.7 0.20.8 0.40.8 0.4 g 0 1 2 3 kd 0 Fraction 1 2 3 4 0 1 2 3 4 5 gl 0 1 2 3 d 0 1 2 3 4 0 1 2 3 4 5 1.0 0.2 1.0c 0.2 0.4 0.7 0.20.1 0.8 0.3 0.2 0.8 hc 0.3 0.2 0.2 k h l 0.3 KG0.3 Fraction 0.2 0.8 0.2 0.1 0.3 0.2 0.3 0.2 Fraction Fraction Fraction Fraction α 0.8 Fraction Fraction Fraction Asp Pyruvate Citrate0.6 0.7 0.30.7 GSH 0.3 0.4 Fraction Fraction Fraction Fraction Fraction Fraction Fumarate Citrate dFumarate GSH 0.4 d 0.8 0.8 d Fraction d Pyruvate αKG Asp 0.7 0.7 0.1 l 0.8 0.8 0.2 l Fumarateh 0.6 0.1 0.1Succinyl CoA 0.2 0.1 h 0.2 0.10.1 0.2 0.1 h 0.2 0.1 l 0.1 0.2 h 13C6-Glc 13C6-Glc0.10.6 0.8 0.20.6 13C6-Glc0.8 0.2 l Citrate 0.7 Fumarate 0.7 GSH Citrate 0.7 Fumarate 0.7 GSH 13C6-Glc 0.3 0.5 13C6-Glc 13C6-Glc 0.013C6Glc 0.013C6Glc0.3 13C6Glc0.00.013C6Glc 0.6 13C6Glc0.1 Glu0.0 -GSH0.6 13C6Glc0.1 0.00.0 0.1 0.1 0.5 0.6 0.0 0.6 13C6-Glc 0.00.0 Ala 0.1 0.0 0.1 0.0 0.6 13C5-Ino 0.6 13C5-Ino 0.4 13C5-Ino0.5 13C5-Ino 0.10.50 1 213C5-Ino3 0.10 1 2 3 0.3 4 00 13C6-Glc0.511 22 33 44 5 13C6-Glc0 0.5 1 2 3 4 0 01 12 32 43 0.35 4 13C6Glc 0.6 13C6Glc 0.6 13C6Glc 0.0 13C5-Ino 0.6 13C5-Ino 0.6 13C5-Ino 0.4 13C5-Ino0.0 13C5-Ino 13C5-Ino0.0 0 1 213C5-Ino3 0.0 0.0 00 11 22 33 44 55 0.0 0 1 2 3 4 0.0 0 1 2 3 4 5 0.0 0.0 0.00.4 0.00.4 0.8 0.0 0.8 0.5 0.5 13C5-Ino 0.5 0.5 0.20 1 2 0.33 4 5 0.4 0.2 0 1 13C5-Ino0.42 3 4 5 13C5-Ino0.40 10.4 2 3 4 00.8 1 2 3 4 5 0.8 13C5-Ino 13C5-Ino 13C5-Ino 0 1 20.4 3 4 5 0 1 0.42 3 4 0 1 2 3 4 5 0 1 2 3 4 0 1 2 0.33 4 5 0.4 0.4 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 Fraction Fraction 0.3 0.2 0.7 Fraction Fraction j0.3 0.4 Citrate0.4 0.7 Fumarate GSH Fumarate0.2 0.4 0.4

Fraction Fraction Citrate GSH

f Fraction 0.3 0.3 0.7 0.7 Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction Fraction 0.2 Fraction b d 0.2 l d 0.3 h 0.3 0.2 h b 0.6 f 0.2 Fraction 0.6 13C6-Glc l 0.3 0.3

0.1 Fraction Fraction Fraction 0.2 0.3 Succinate0.1 13C6-Glc j 0.2 0.2 Fraction 0.2 13C6-Glc d Fraction 0.3 13C6Glc 0.6 13C6Glc 0.6 d 13C6Glc 0.1 0.2 0.2 0.2 h 0.2 l h 0.1 0.1 0.5 13C5-Ino0.10.1 0.5 0.1 13C5-Ino 0.1 0.5 0.1 0.5 0.2 0.2 l 13C5-Ino 13C5-Ino0.1 13C5-Ino 13C5-Ino 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.4 0.4 0.1 0.1 0.1 0 1 2 3 4 5 0 1 2 3 4 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.4 0.4 0 1 2 3 0 1 2 3 4 5 0 1 2 30 4 1 2 03 1 2 3 0 4 1 50.32 3 4 50 1 0.02 03 14 0.352 3 4 0 1 0.0 2 3 4 0 1 20.0 3 4 5 0.0 0.0 0.0 Fraction Fraction 0.3 0.3 Fraction Fraction Fraction Fraction Fraction 0.8 d Fraction 0.8 0 1 2 3 4 5 l 0 1 2 3 4 d 0 1 2 3 4 5 h 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 0.8 0.8 0.1 0.2 h 0.2 0.1 0.2 0.2 l Lactate 0.8 Succinate 0.7 Glu Lactate 0.8 Succinate 0.7 Glu 0.1 0.1 0.1 0.1 0.6 13C6-Glc 13C6-Glc 0.6 13C6-Glc 13C6Glc 0.013C6Glc 0.6 0.013C6Glc 0.6 0.6 0.0 0.6 0.0 0.0 0.0 13C5-Ino 13C5-Ino 0.5 13C5-Ino 13C5-Ino0 1 2 3 4 5 13C5-Ino0 1 2 0.53 4 13C5-Ino0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 0.4 0.4 0.4 0.4 0.4 0.4

Fraction Fraction 0.3 0.3 Fraction Fraction Fraction Fraction Fraction c Fraction g k c g k 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.0 Figure0.0 5. Transformed0.0 0.0 cells display0.0 diverse0.0 Alacapacity to utilize 0 1 2 3 0 1 2 3 4 0 1 2 3 4 5 0 1 2 3 0 1 2 3 4 0 1 2 3 4 5 0.4 0.8 0.8 0.4 0.8 0.8 Citrate 0.7 Fumarate 0.7 GSH Citrate 0.7 Fumarate 0.7 GSH inosine0.6 as 0.6a carbon source. 0.3 13C6-Glc 13C6-Glc 13C6-Glc 0.3 13C6Glc 0.6 13C6Glc 0.6 13C6Glc 0.5 0.5 13C5-Ino 13C5-Ino 13C5-Ino 13C5-Ino 0.5 13C5-Ino 0.5 13C5-Ino 0.2 0.4 0.4 0.2 0.4 0.4 0.3 0.3

Fraction Fraction 0.3 0.3 Fraction Fraction Fraction Fraction Fraction d Fraction l d 0.1 0.2 h 0.2 0.1 0.2 h 0.2 l 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 200 A 200 200 200 NS GlucoseGlucoseGlucose Glucose Glucose GlucoseGlucoseInosine free/Inosine free/InosineGlucose free/Inosine Glucose free/Inosine 150150 150 150 *** ** NS NS *** *** *** *** *** 100 100 100 100 Cell growth 50 50 50 50 (relative confluence %) 0 0 0 Rescue (%) compare to Glucose group Rescue (%) compare to Glucose group Rescue (%) compare to Glucose group RD RD RD Hela Hela Hela MEF MEF MEF Rh30 Rh30 Rh30 Lan-1 Lan-1 Lan-1 HT-29 HT-29 HT-29 U-2OS U-2OS 0 U-2OS B16-F10 B16-F10 B16-F10 Rescue (%) compare to Glucose group Human Human T Human Human T Human Human T NB-EBC1 NB-EBC1 NB-EBC1 RD Colo 320DM Colo 320DM Colo 320DM Hela MEF Rh30

Lan-1 Colorectal Colorectal Colorectal Neuroblastoma RhabdomyosarcomaNeuroblastoma RhabdomyosarcomaHT-29 Neuroblastoma Rhabdomyosarcoma Adenocarcinoma AdenocarcinomaU-2OS Adenocarcinoma B16-F10 Human Human T

NB-EBC1 Melanoma Fibroblast Melanoma Fibroblast Melanoma Fibroblast

Colo 320DM Osteosarcoma Osteosarcoma Osteosarcoma Neuroblastoma Rhabdomyosarcoma Colorectal Adenocarcinoma

Melanoma Fibroblast

Osteosarcoma

B 200 C GlucoseGlucose Glucose/ Inosine/ 150 Day 4 GlucoseInosine free/Inosine Glucose 150 Foro Foro G-/Inosine Ctrl PNP 100 Background Glucose Inosine PNP 100 100 50 actin

Relative confluence % 0 50 50 (%) confluence cell Relative siRNA: Ctrlcsi PNP

% of Rescue PNPsi 0

0 Rescue (%) compare to Glucose group RD Hela MEF Rh30 Lan-1 HT-29 U-2OS B16-F10 Human Human T NB-EBC1 Colo 320DM Neuroblastoma Rhabdomyosarcoma Colorectal Adenocarcinoma

Melanoma Fibroblast

Osteosarcoma

Figure S6. Transformed cells display diverse capacity to utilize inosine as a carbon source. A

) 2500 IgG Control

3 100 Inosine 100 Anti PDL1 2000 Anti PDL1+Inosine 7575 1500 5050 IgG Control 1000 *** Inosine 25 500 Percent survival 25 Anti PDL1 Tumor Volume (mm Volume Tumor Percent Survival (%) Anti PDL1+Inosine ** 0 0 8 10 12 14 16 18 20 22 0 0 18182020 2222 2424 2626 2828 Days after tumor inoculation Days after tumor inoculation B Days after B16F10 injection 2500 Control

) Inosine 3 2000 Pmel Pmel+Inosine 100100

1500 7575

** Control 1000 5050 Inosine

Tumor Volume (mm Volume Tumor 500 2525 Pmel Pmel+Inosine *** Percent Survival (%) 0 0 6 8 10 12 14 16 18 0 0 1010 1616 1818 2020 22 24 26 Days after tumor inoculation Days after tumor inoculation C 100 2000 Control ***

) Inosine 3 CAR-T 75 * 1500 CAR-T+Inosine 50 1000 Control Inosine 25 500 CAR-T Percent survival (%) CAR-T+Inosine Tumor Volume (mm Volume Tumor 0 6 16 26 36 46 56 0 6 26 36 46 56 Days after tumor inoculation Days after tumor inoculation

Figure 6. Inosine supplement enhances immunotherapy in targeting solid tumor. A CD45+

10.56% 24.2%

12.5% + ε SSC SSC SSC CD3 FSC CD45 CD45 CD8

* * ** ** Day 10 CD3+ cells (%) cells CD3+ CD8+ cells (%) cells CD8+

Control Inosine Anti PDL1 Anti PDL1 Control Inosine Anti PDL1 Anti PDL1 +Inosine +Inosine * * ** Day 15 ** CD3+ cells (%) cells CD3+ CD8+ cells (%) cells CD8+

Control Inosine Anti PDL1 Anti PDL1 Control Inosine Anti PDL1 Anti PDL1 +Inosine +Inosine B Day 4 Day 7 2 ns 30 ** 1.5 20 1 10 0.5

0 0 Relative Fold Change Fold Relative Relative Fold Change Fold Relative

Figure S7. Inosine supplement prolongs CAR-T cell proliferation and survival in tumor environment.