Abstract
Metabolic reprogramming extensively occurs in proliferating cancer cells. This phenomenon occurs highly heterogeneously, but its origin has remained unclear. Here we use a physicochemical concept of free electron potential (FEP) and its equation of state to profile metabolites. We demonstrate that FEP change between substrates and products exactly reflects electrons dissipated in a metabolic transformation. Based on the law of conservation of electron in chemical reactions, a function of FEP change for central metabolism in proliferating cells are further derived, and it can accurately predict metabolic behaviors under hypoxia by maximizing the cellular FEP change to consume electrons. Therefore, enabling electron transfer dictates metabolic reprogramming in hypoxic cells, which underlies the major findings in cancer metabolism and is supported by our experiments. Importantly, our model established on FEP helps to reveal a combination of promising targets to inhibit tumor growth under hypoxia by blocking electron consumption, and could also guide future studies on cancer metabolism under hypoxia.
Although proliferating cells, such as cancer cells, develop significant metabolic heterogeneity1–3 to cope with the changing microenvironment, we notice that hypoxia and mitochondrial dysfunction, both of which block the electron transport chain (ETC), lead to the similar metabolic reprogramming4,5. It prompts us to hypothesize that the accumulation of electrons probably drives metabolic reprogramming.
As a pool of integrated chemical transformations in cells, metabolism must observe the chemical laws. If we can find out the chemical law underlying metabolic reprogramming in proliferating cancer cells, we may design a cocktail of broad-spectrum treatments for cancers regardless of the heterogeneity. Classically, chemical reactions involve the forming and breaking of chemical bonds between atoms. Since chemical bonds result from a redistribution of the outer electrons of atoms, chemical reactions may encompass electron transfer between each other or release electrons to the system. As for mammalian cells, the established fact is that oxygen is used to accept the net electrons released from the whole cellular metabolism, which is mediated by the mitochondrial electron-transport chain (ETC). Therefore, the mitochondrion plays an essential role as the electron acceptor in enabling cell proliferation in addition to energy generation4–6. However, when the ETC is disabled by hypoxia or pathological/pharmacological inhibition, how to enable electron transfer to support cell proliferation remains elusive. Here, we build up a physicochemical model to reveal the chemical nature of metabolic reprogramming in cells.
The similar metabolic reprogramming induced by hypoxia and mitochondrial inhibition
Based on the observations from different research groups, hypoxia7 and mitochondrial deficiency8 led to the similar metabolic phenomena, especially the reductive carboxylation of glutamine-derived α-ketoglutarate (Figure 1A). Here we parallelably compared the metabolic effects of hypoxia and antimycin A, a mitochondrial ETC inhibitor, on cancer cells. First, we traced the metabolic pathways by using [U-13C-glutamine in HeLa cells. Normally, through the CAC, glutamine-derived α-ketoglutarate m+5 was predominantly oxidized to succinate m+4, malate m+4, oxaloacetate m+4 that could be converted into aspartate m+4, citrate m+4 and isocitrate m+4 (Figure 1B-1E and S1A-S1D). Upon hypoxia or ETC inhibition, glutamine-derived α-ketoglutarate m+5 was reduced by carboxylation to isocitrate m+5 and citrate m+5 that was further lysed to acetyl-CoA m+2 and oxaloacetate for the generation of aspartate m+3 and malate m+3 (Figure 1B-1E and S1A-S1D). In the meantime, glutamine-derived lactate m+2 from malate m+3 in the reductive pathway dramatically increased while that m+3 from malate m+4 in the oxidative pathway decreased under the condition of hypoxia or ETC inhibition (Figure 1F). The similar results were also obtained in 4T1 cells (Figure 1G, 1H, S1E and S1F). These results indicate that cellular metabolism is reprogrammed toward glutamine-initiated lipogenesis through the non-canonical reductive pathway (Figure 1A) in the conditions of hypoxia and ETC inhibition. In addition, hypoxia and antimycin A induced the typically increased metabolic flux of glucose to lactate (Figure S2A-S2C), and they also induced similar changes in intracellular metabolites as revealed by the metabolomics (Figure S3). Taken together, these data clearly confirm that hypoxia and ETC inhibition trigger the similar metabolic reprogramming.
Antimycin A can induce the accumulation of electrons. We then measured the cellular NADH and NADPH upon hypoxia and ETC inhibition. Both hypoxia and antimycin A accumulated cellular NADH and enhanced the ratio of NADH/NAD+ (Figure S4A and S4B). Although we did not observe the accumulated NADPH and increased NADPH/NADP+ ratio (Figure S4C and S4D), NADH and NADPH can be easily transhydrogenated between each other or translocated spatially by various biochemical shuttles or reversible biochemical reactions8,9 (Figure S5). These observations urged us to hypothesize that electron transfer may determine the metabolic reprogramming.
The constant electron consumption between substrates and products
Electron transfer is directly associated with the oxidation and reduction of metabolites. To comprehensively understand electron transfer in cells, we derived a concept from the previous established degree of reduction in bioprocess engineering10, referred to as free electron potential (FEP). FEP characterizes the potential ability of a typical biological metabolite, with the molecular formula of CCHHOONN, to release electrons upon its complete oxidation to CO2, H2O and NH3 in cells. The degree of reduction of any element in a compound is equal to the valence of this element, and the degree of reduction of some elements are C = 4, H = 1, N = −3 and O = −2 in metabolites10. Therefore, we derived an equation of state for FEP, in which Y is used as the symbol for FEP and NC, NH, NN and NO are the number of carbon, hydrogen, oxygen and nitrogen atoms in the molecule. Here we listed Y values of intracellular metabolites involved in the metabolism of glucose, amino acids, nucleic acids and lipids (Table 1, and S1). Interestingly, the Y per carbon atom values (γ) of metabolites show somehow internal properties determined by “4” (detailed in Supplemental Discussion).
Equation (1) can be used to quantitatively calculate electrons required for metabolic conversions by FEP change, ΔYP,S, between Y values of initial substrates and those of final products. As for a transformation, where S and P are the carbon-containing metabolites with the quantity of carbon atoms being made conserved,
A positive FEP change means the consumption of electrons while a negative value indicates the release of electrons in this conversion. Phosphate group and Co-enzyme are often used to facilitate metabolic transformations, however, their addition to metabolites do not involve the transfer of electrons. Thus we only need to simply focus on the form of compounds without phosphate and Co-enzyme when ΔY is calculated.
To prove equation (2), we then make the quantities of nitrogen and oxygen atoms conserved by adding x moles of NH3 and y moles of H2O as the products, and thus change reaction (a) to
In reaction (b), the quantities of carbon, nitrogen and oxygen atoms are conserved. Notably, x and y could be negative, meaning that NH3 and H2O are actually substrates. Thus,
NC-S, NN-S and NO-S are the numbers of carbon, nitrogen and oxygen atoms in substrates while NC-P, NN-P and NO-P are those in products.
Based on equation (1), Y = 4NC + NH - 3NN - 2NO, for metabolites,
In equation (f) and equation (g), NH-S and NH-P are the numbers of hydrogen atoms in substrates and products.
As for reaction (b) where Y of NH3 and H2O is 0,
Hence
By inserting equation (f) and (g) into equation (2), we obtained
Substituting equation (c), equation (d) and equation (e) into equation (i) yields
In equation (k), is actually the difference of the quantities of hydrogen atoms between substrates and products in reaction (b). Based on the Law of Conservation of Mass, these hydrogen atoms (the electron carriers) must be integrated into electron acceptors, such as NAD(P)+ and FMN/FAD, if the difference is positive. Otherwise they come from the electron donor, for example, NAD(P)H + H+ or FMNH2/FADH2. Therefore, ΔYP,S represents the number of electrons produced or consumed in reactions (a) and (b).
The conversion of substrates to products may have several metabolic routes with different energy requirements, but ΔY between substrates and products keeps constant based on the above analyses.
As for most of redox reactions, NAD(P)+, FMN/FAD or their reductive forms are used in the electron transfer. However, in some cases, reactions may directly use other electron donors, such as tetrahydrofolic acid and ascorbic acid. The resultant oxidized electron donors, dihydrofolic acid and dehydroascorbic acid, need to be finally reduced back for the sake of redox homeostasis usually using NADPH + H+ as electron donor11,12. Therefore, in essence, these reactions equivalently consume NADPH + H+. In some other cases, oxygen could be directly used as electron acceptor in the reactions. Oxygen is expected to accept electrons from NADH + H+ through the mitochondrial electron transport chain. If oxygen accepts electrons from metabolites in reactions, the same equivalents of NADH + H+ are left in cells, in particular under hypoxic conditions. Thus, when used as electron acceptor, oxygen is essentially equal to NAD+. Taken together, the analyses on the transfer of global electrons in cells are not restricted to the forms of electron acceptor/donor.
Electron transfer in proliferating cells
Proliferating cells must produce ATP and duplicate all the building bricks to make new cells. Mammalian and bacterial cells share the similar chemical compositions13 (Table S2). Macromolecules including proteins, nucleic acids, lipids and polysaccharides account for 87% and their precursors involving amino acids, nucleotides, fatty acids, sugars and the related intermediates make up 9.3% of cell mass. The rest chemicals are inorganic ions (3%) that are unrelated to electron transfer and other small molecules (0.7%) that could be negligible to the analysis of global intracellular electrons. Protein synthesis from amino acids, nucleic acid synthesis from nucleosides, polysaccharide synthesis from sugars and lipid synthesis from fatty acids do not involve the transfer of electrons. Therefore, here we mainly focus on the synthesis of amino acids (non-essential amino acids), nucleosides, fatty acids and sugars. The major carbon source in blood includes glucose and glutamine. We calculated the possible ΔY of these building bricks, including ATP generation, lipid biosynthesis, sugar biosynthesis, amino acid synthesis and nucleotide biosynthesis, for cell proliferation based on Y values of metabolites in Table 1 and S1 (Figure 2A-2E and S6 and Table S3).
We can calculate the total electrons consumed by ATP generation (Figure 2A), lipid biosynthesis (Figure 2B), sugar biosynthesis (Figure 2C), amino acid synthesis (Figure 2D) and nucleotide biosynthesis (Figure 2E). Based on the law of electron conservation in chemical reactions, the total electrons produced in a cell (maxΦ(δ)) should be around 0.
Hence, Σ means the sum of electrons from all the intracellular reactions, and variables with slashes from different metabolic pathways are optional depending on the availability of nutrients and cellular states (Figure 2). As a cell is a self-organizing system, equation (3) can be flexibly set up to 0 by using different metabolic pathways. When oxygen is sufficient, the ETC works efficiently. To support ATP generation coupled to the ETC, cells may use the metabolic pathways producing electrons.
Metabolic reprogramming of proliferating cells upon ETC dysfunction
Under the condition of ETC dysfunction, such as hypoxia and ETC inhibition, the electron flow to oxygen is blocked (here let ), thus
It could lead to accumulated electrons that unlikely rises infinitely (Figure S4A-S4D). Therefore, to equate Φ(δ) with 0 while still enable anabolic processes, proliferating cells have to rewire their metabolic reactions to balance electron transfer by reducing the production and enhancing the dissipation of electrons. In doing so, Φ(δ) is maximized by selecting higher ΔY values from alternative metabolic pathways, thus gives
Based on maxΦ(δ), glycolytic pyruvate shunts to lactate and avoids entering the CAC to produce electrons , which results in the increased lactate production (Figure S2B and S2C). This pathway does not release any electron (ΔY = 0), because ΔYPyr-Glc is negatively equal to ΔYLac+,Pyr (Figure 2A). Normally, the CAC produced a great many electrons for mitochondrial ATP generation by completely oxidizing its participants to carbon dioxides, but also provided on purpose some essential intermediates for biosynthesis. Therefore, upon ETC dysfunction, the CAC had to be shaped to a state of low activity required for cell proliferation, endowed with a in equation (4). Our results showed that both [U-13C]-glucose-derived citrate m+2 and [U-13C]-glutamine-derived succinate m+4 were significantly reduced in the condition of hypoxia and ETC inhibition (Figure S1A, S1B and S7A-S7C), indicating a decrease in the metabolic flux of both glucose and glutamine the oxidative CAC. In addition, fatty acid biosynthesis is initiates from glutamine (ΔY(Palm,Asp)+5.5,Glu/ΔY(Palm,Lac)+5.5,Glu) instead of from glucose (ΔY(Palm,Asp)-0.5,Glc/ΔY(Palm,Lac)-0.5,Glc), and this process can dissipate electrons (ΔY > 0) and concomitantly produce glutamine-derived aspartate and/or lactate through the reductive pathway (Figure 2B). These metabolic preferences explain the experimental observations7,8 (Figure 1 and S1-S3).
Sugar, serine, alanine and glycerol are directly derived from glucose or glycolytic intermediates, thus their biosynthesis initiated from glucose prevails in proliferating cells (Figure 3A and S8A-S8E). In contrast, proline is always synthesized from glutamate that is mainly produced from glutamine (Figure 3B and S8F). Consistently, these metabolic preferences support maxΦ(δ), but hypoxia and ECT inhibition promote glucose-derived glycerol 3-phosphate (Figure 3A) and glutamine-derived proline (Figure 3B) because of their positive ΔY values (ΔYGlo+2,Glc and ΔYPro+4,Glu > 0) (Figure 2C and 2D), which contributes to maxΦ(δ).
There are currently controversial opinions on the roles of NADPH produced in the oxidative pentose phosphate pathway (PPP) in cancers. Supporting data mainly focus on the antioxidant activity of PPP-produced NADPH14. However, many reports recently showed that the oxidative PPP could be shut down in cancer cells15–17. Moreover, the epidemiological investigations demonstrated that G6PD deficiency, the rate-limiting enzyme in the oxidative pathway, did not affect the incidence of cancers18,19. As shown in equation (4), maxΦ(δ) prefers the non-oxidative PPP to reduce the production of electrons in the condition of hypoxia and ECT inhibition (Figure 2E). Our result also confirm that the fraction of [3–2H]-glucose-derived [2H]-labeled NADPH m+1 via the oxidative PPP was observed to decline upon hypoxia and ETC inhibition (Figure S9A and S9B). The analysis of enrichment of [1,6–13C2]-glucose in sedoheptulose 7-phosphate, a specific intermediate of PPP, further demonstrated that sedoheptulose 7-phosphate m+2 in the non-oxidative PPP increased while sedoheptulose 7-phosphate m+1 via the oxidative PPP decreased under hypoxia or ETC inhibition (Figure 3C-3E). These data suggest that the non-oxidative PPP, instead of the oxidative PPP, is preferentially used by cancer cells under hypoxia.
Furthermore, simplifying equation (4) by removing all the variables with ΔY = 0 and rearranging it yielded
Electrons were minimally produced by the anabolic transformations including CAC, serine synthesis and nucleic acid synthesis, here designated as ΣΔY-. In fact, cells may release additional electrons (detailed in Supplemental Discussion). The assimilation of glycerol is coupled to glutamate-initiated lipid synthesis (Figure 2B), with the electron production being denoted as ΣΔYLip+,Glu. Thus, equation (5) is simplified as equation (6),
Obviously, glutamine/glutamate-initiated syntheses of both lipid and proline essentially play a determinative role in metabolically dissipating electrons to support cell proliferation under the condition of hypoxia and ETC inhibition.
Glutamate is the product of glutamine degradation and can be directly excreted if beyond the cellular requirement. Therefore, we measured the level of glutamate and proline in the medium, and found that glutamine-derived glutamate reduced while glutamine-derived proline significantly enhanced in the medium under hypoxia or ETC inhibition (Figure 3F). These results suggest that the metabolic conversation of glutamate to proline is advantageous to cell survival under hypoxia or ETC inhibition. This speculation was further confirmed by the result that supplementation with glutamate facilitated cell growth under hypoxia or ETC inhibition (Figure 3G).
Furthermore, we demonstrated that glutamine-13C was significantly enriched almost in all the measured fatty acids upon hypoxia and ETC inhibition (Figure 3H and S10A-S10I). Moreover, the contents of these fatty acids were boosted under these conditions (Figure 3I and S11), suggesting that cancer cells can adapt to hypoxic microenvironments by accumulating lipid mass. This finding could explain why cancer cells contain increased numbers of lipid droplets20.
The metabolic equivalent of glutamine-associated metabolic reactions
As revealed in equation (6), cancer cells can accommodate to hypoxia by initiating glutamine/glutamate-derived lipid and/or proline. Here the overall ΔY value for the metabolic equivalent of each glutamine/glutamate-associated metabolic reactions (GMR) is denoted as where palmitate is used for quatitation. The total available glutamate (Glut) could be primarily diverted to synthesize lipid to consume more electrons under hypoxia (Figure 4A). Hence,
Nevertheless, the conversion of glutamate to proline has a more efficient ΔY/ATP ratio of +4, compared to the glutamate-initiated palmitate synthesis with a ΔY/ATP of +2.93 (Figure S12). Therefore, cells may utilize extracellular lipid and shift glutamate from lipid synthesis to secretory proline synthesis in the hypoxic in vivo microenvironment, only if they can directly acquire amino acids or obtain nitrogen source for amino acid synthesis, such as alanine, the second most abundant amino acid in human blood (Figure 4B). The carbon atoms of alanine can be converted to excretory lactate, and this process does not produce electron (ΔY = 0) (Figure 4B). As for these transformations, where is the ΔY of secretory proline synthesized from the total available glutamate (Figure 4B).
In addition, cells could synthesize lipid from other carbon sources with positive ΔY/GMR. Since acetyl-CoA is the precursor of fatty acids, ΔY/GMR depends on the synthesis of acetyl-CoA from other nutrients. Hence,
As listed in Table S4, some nutrients have a positive ΔY/GMR. In particular, acetate with ΔY/GMR = +7.5 (Table S4 and Figure S13A) is higher than that of glutamine/glutamate with ΔY/GMR = +4 ~ +5.5, and thus could be preferentially utilized for lipogensis under hypoxia21,22. In addition, leucine with ΔY/GMR = +5.5 (Table S4 and Figure S13B) should also be an alternative carbon source for lipid biosynthesis. These metabolic pathways could be cell type-specific and context-dependent, but all of them are centered on biosynthesis of lipid and proline.
The potential treatments for cancers
Based on all the above analyses, the simultaneous blockage of both proline and lipid syntheses should effectively disable in vivo growth of cancers due to their hypoxic micro-environment. P5CS is the critical enzyme involved the proline biosynthesis pathway, and ACC1/2 and HMGR are the rate-limiting enzymes in the biosynthesis of lipids, mainly fatty acids and sterols23,24 (Figure 4C). Since no inhibitor against proline synthesis is available, we generated P5CS-null and -wild type HeLa and 4T1 cells. However, inhibition of proline synthesis by depleting P5CS marginally sensitized cells to hypoxia in the proline-contained medium (Figure S13C and S13D). This should be attributable to the fact that cells usually have active de novo lipogenesis, the major electron-dissipated process. Consistently, P5CS knockout did not affect tumor growth but sensitize tumors to PF-05175157 and/or lovastatin, the inhibitors of 25ACC1/2 and 26HMGR (Figure 4D and S14), suggesting that praline biosynthesis can partially compensate the blockage of lipogenesis. Therefore, inhibitions of the biosynthesis of proline and lipid can synergistically suppressed tumor growth.
Discussion
Due to the fast growth rate and poor vasculature, tumor cells often suffer from insufficient supply with nutrition and oxygen3. To maintain uptake of nutrients, tumor cells usually enhance expression of their transporters27–29. However, oxygen passively diffuses into cells, and thus tumor cells are unable to acquire enough oxygen under hypoxia. Instead, they adapt to such harsh conditions by genetically or epigenetically optimizing their metabolism according to maxΦ(δ), as revealed in the current study. Therefore, cancer cells still display some hypoxia-associated metabolic phenomena even if they are in vitro cultured. This essentially interprets metabolic reprogramming in cancers1,2,30, such as abnormal glucose metabolism31, ectopic utilization of alanine32 and branched-chain amino acid33,34 and de novo lipid synthesis from glutamine7,8,35 or acetate21,22,36,37.
In addition to the interpretations on the typical metabolic phenomena in cancers, maxΦ(δ) chemically explains why hypoxia and ETC inhibition almost induce the same metabolic reprogramming, reveals that hypoxia and ETC inhibition stimulate the biosynthesis of glucose-derived glycerol 3-phosphate and glutamine-derived proline, and emphasizes the role of non-oxidative PPP, proline excretion and lipid droplets in cancer cells under the hypoxic conditions. Complementary to several recent reports showing that proline synthesis may play a critical role in supporting in vivo growth of some cancers38, 39, our model reveals that the process of proline biosynthesis, rather than proline itself, is important for cancer cell growth under hypoxic conditions. Catabolism of branched-chain amino acids, including leucine, isoleucine and valine, share the first two enzymes, branched-chain amino acid transaminase (BCAT) and branched-chain α-keto acid dehydrogenase complex (BCKD), thus the three amino acids are often equally studied for caners33,34. However, our theory distinguishes them by their metabolic equivalents, ΔΥ/GMR values (Table S4), and indicates that only leucine could be potentially advantageous to cell survival under hypoxia. Although this speculation needs further experimental validation, leucine indeed shows some specific functions, such as regulation of mTOR pathway40, different from isoleucine and valine. It is impossible to cover all the metabolic transformations in the current study, but equation (2) can be conveniently used to analyze the additional metabolic pathways. To maximize Φ(δ), any metabolic transformation with ΔΥ > 0 could be of benefit for the survival of cancer cells under hypoxia or with deficient mitochondria. Furthermore, equation (2) in combination with its derivative equation (7) can calculate the metabolic equivalent of nutrients to determine its potential assimilation into lipids.
Metabolic reprogramming can be promoted by numerous signal transduction pathways with a high degree of heterogeneity in cancer cells1–3. Importantly, bypassing these intricate and interchangeable cascades, now we can mainly control electron transfer under hypoxia by inhibiting the synthesis of both proline and lipid through a cocktail of treatments. Moreover, these inhibitors are expected to be nontoxic to normal cells that can survive on blood lipid and proline supply. Therefore, they appear to be a promising broad-spectrum treatment for solid tumors, and can be potentiated by disabling maxΦ(δ). One may expect some strategies for counteracting maxΦ(δ), inhibiting lactate dehydrogenases to increase electron production from intracellularly metabolized pyruvate, blocking angiogenesis to reduce supply with oxygen as the electron acceptor, impairing the ETC with biguanides to exacerbate hypoxia, starving with serine/glycine and nucleotides to force cells synthesize these metabolites (ΔY < 0), and so on. Generally, any means to neutralize maxΦ(δ) established on equation (2) could be a potential treatment for cancers alone or in combination with inhibition biosynthesis of lipid and proline. (See Supplemental Discussion for more)
Online Contents including Supplemental Figure S1-S14, Table S1-S4, Methods, Discussion.
Authors Contributions
B.L. conceived and designed the study, and developed the model and derived the equations; Y.W. and M.L. performed experiments; Y.W., M.L. and B.L. analyzed the data; Y.R., Q.C. and Y.C. created some constructs and cell lines; C.C. provided constructive advice; G.Y. provided constructive advice and in particular coined the term of "free electron potential" whose symbol, "Y", is the first letter of his last name; B.L. wrote the paper.
Acknowledgements
We thank Dr. Qunying Lei (Fudan University, China) and Dr. Wei Du (University of Chicago, USA) for carefully reading through the manuscript and valuable discussion and also thank Dr. Xiaohui Liu (Metabolomics Facility at Tsinghua University Branch of China National Center for Protein Sciences, China) for technical help. This work is supported by Grants 81622037, 81372185 and 81672762 from Natural Science Foundation of China.