Glutamine dependence is a prominent feature of cancer metabolism, and here we show that melanoma cells, irrespective of their oncogenic background, depend on glutamine for growth. A quantitative audit of how carbon from glutamine is used showed that TCA-cycle-derived glutamate is, in most melanoma cells, the major glutamine-derived cataplerotic output and product of glutaminolysis. In the absence of glutamine, TCA cycle metabolites were liable to depletion through aminotransferase-mediated α-ketoglutarate-to-glutamate conversion and glutamate secretion. Aspartate was an essential cataplerotic output, as melanoma cells demonstrated a limited capacity to salvage external aspartate. Also, the absence of asparagine increased the glutamine requirement, pointing to vulnerability in the aspartate-asparagine biosynthetic pathway within melanoma metabolism. In contrast to melanoma cells, melanocytes could grow in the absence of glutamine. Melanocytes use more glutamine for protein synthesis rather than secreting it as glutamate and are less prone to loss of glutamate and TCA cycle metabolites when starved of glutamine.
Glutamine dependence is a prominent feature of cancer metabolism, and here we show that melanoma cells, irrespective of their oncogenic background, depend on glutamine for growth. A quantitative audit of how carbon from glutamine is used showed that TCA-cycle-derived glutamate is, in most melanoma cells, the major glutamine-derived cataplerotic output and product of glutaminolysis. In the absence of glutamine, TCA cycle metabolites were liable to depletion through aminotransferase-mediated α-ketoglutarate-to-glutamate conversion and glutamate secretion. Aspartate was an essential cataplerotic output, as melanoma cells demonstrated a limited capacity to salvage external aspartate. Also, the absence of asparagine increased the glutamine requirement, pointing to vulnerability in the aspartate-asparagine biosynthetic pathway within melanoma metabolism. In contrast to melanoma cells, melanocytes could grow in the absence of glutamine. Melanocytes use more glutamine for protein synthesis rather than secreting it as glutamate and are less prone to loss of glutamate and TCA cycle metabolites when starved of glutamine.
Melanoma is the deadliest form of skin cancer and is difficult to treat once it
metastasizes. Immunotherapy is significantly improving long-term survival in a subset of
melanomapatients [1], and new drugs, particularly
those that target mutant BRAF found in about 50% of melanoma, have provided some hope,
but resistance and relapse are typically encountered [2]. Therefore there is still an urgent need for the discovery and
development of novel targets for melanoma therapy. Among the prominent areas where such
targets are sought is metabolism, as it is well established that cancers have divergent
metabolism compared to normal tissues. In previous studies on melanoma cells, we found a
typical highly glycolytic (glucose-to-lactate) metabolism [3]. Additionally, though, glutamine usage by melanoma cells was
increased compared with melanocytes, the normal cellular precursors of melanoma [3]. This appeared to be a general phenomenon
regardless of the melanoma mutational background. Although glucose uptake was
5–10-fold greater than glutamine uptake, most of the glucose was converted to
lactate, and glutamine was therefore demonstrated to provide essential input into the
tricarboxylic acid (TCA) cycle [3].A glutamine requirement for the proliferation of many cell types is well established
[4, 5]
and certain tumor or oncogene-modified cell lines undergo apoptosis when deprived of
glutamine [6-8]. The metabolism of glutamine begins by its conversion to glutamate by
glutaminase, or other amidases which have various functions in biosynthetic pathways
[9]. Deamination of glutamate yields
α-ketoglutarate, an intermediate in the TCA cycle, and thereby glutamine acts as
an anaplerotic substrate [10], contributing to
the maintenance of pools of carboxylic acids in the TCA cycle and sustaining cellular
oxidative phosphorylation (Figure 1A). This use of
glutamine as an energy substrate is known as glutaminolysis, by analogy to glycolysis
[11]. Additionally, the carbon contributed to
the TCA cycle by glutamine can be used in biosynthetic reactions [12] (Figure 1A), and the
processes of glutaminolysis and biosynthesis can run in parallel. Anaplerosis and
cataplerosis (green and red arrows respectively in Figure 1A) must be balanced to maintain the TCA cycle in equilibrium [13]. Studies on tumor cells using
13C-glutamine have confirmed the use of glutamine as an anaplerotic substrate
[3, 14–18], and have outlined some
of the cataplerotic roles of carbon derived from glutamine, including use for fatty acid
synthesis under hypoxia [3, 19–21] and export
from the mitochondrion as aspartate and generation of NADPH (which maintains cellular
redox state) via malic enzyme activity [16]. It
is also well known that tumor or normal cells fed with glutamine will secrete glutamate
[22, 23], and the secretion of some partially-13C glutamate from cells
labeled with universally-13C-glutamine, which indicates TCA cycle-origin
(Figure 1B), has been reported [15]. Glutamate derived from the TCA cycle
contributes to cataplerosis and therefore provides a potential route for loss of TCA
cycle metabolites, a process which has been observed in glutamine-starved cells
undergoing apoptosis [6].
Figure 1
Maps of glutamine metabolism
(A) Anaplerotic conversion of glutamate to α-ketoglutarate
(αKG) is highlighted by green arrows (alternate enzymatic reactions for
this step are contained within the brackets); cataplerotic reactions are shown
by red arrows; TCA cycle is within the shaded area. Dashed lines indicate
secretion of metabolites. Genes for key steps are shown: gls1, glutaminase-1;
got, glutamate-oxaloacetate transaminase (aspartate aminotransferase); gpt,
glutamate-pyruvate transaminase (alanine aminotransferase); glud, glutamate
dehydrogenase. Other abbreviations: Pyr, pyruvate; OAA, oxaloacetate; AcCoA,
acetyl-coenzyme-A. (B) Using 13C-labeling to quantify
glutaminolysis. Metabolic trafficking from universally 13C-glutamine
is indicated by brown arrows, with 13C atoms, including
13C lost as CO2, indicated by brown circles, and
recombination with unlabeled (open circles) acetyl-CoA in the TCA cycle. Routes
to glutamate, aspartate and lactate are shown, as well as example mass profiles
of cellular glutamate and aspartate. The x axis designations of
“m+1”, “m+2”, etc., indicate
metabolite mass greater than the unlabeled (no 13C) mass of
“m+0”, and together indicate the distribution of
13C label. 13C-Glutamine is deamidated to (m+5)
glutamate. This is not glutaminolysis, as no energy is produced. But glutamate
can then be converted to α-ketoglutarate and circuit the TCA cycle. After
one circuit, two carbons are lost as CO2 and replaced by unlabeled
acetyl-CoA. This results in m+3 glutamate. Further circuits of the TCA
cycle result in exchange of more 13C carbon. Similarly for aspartate,
the initial pass through the TCA cycle yields m+4 aspartate (one carbon
lost as CO2), and another circuit through the cycle yields m+2
aspartate (three carbons lost as CO2). Glutaminolysis can be
quantified in terms of CO2 production by comparing the 13C
content and quantities of metabolites after 13C-glutamine labeling
with the amount of 13C-glutamine taken up by cells.
Maps of glutamine metabolism
(A) Anaplerotic conversion of glutamate to α-ketoglutarate
(αKG) is highlighted by green arrows (alternate enzymatic reactions for
this step are contained within the brackets); cataplerotic reactions are shown
by red arrows; TCA cycle is within the shaded area. Dashed lines indicate
secretion of metabolites. Genes for key steps are shown: gls1, glutaminase-1;
got, glutamate-oxaloacetate transaminase (aspartate aminotransferase); gpt,
glutamate-pyruvate transaminase (alanine aminotransferase); glud, glutamate
dehydrogenase. Other abbreviations: Pyr, pyruvate; OAA, oxaloacetate; AcCoA,
acetyl-coenzyme-A. (B) Using 13C-labeling to quantify
glutaminolysis. Metabolic trafficking from universally 13C-glutamine
is indicated by brown arrows, with 13C atoms, including
13C lost as CO2, indicated by brown circles, and
recombination with unlabeled (open circles) acetyl-CoA in the TCA cycle. Routes
to glutamate, aspartate and lactate are shown, as well as example mass profiles
of cellular glutamate and aspartate. The x axis designations of
“m+1”, “m+2”, etc., indicate
metabolite mass greater than the unlabeled (no 13C) mass of
“m+0”, and together indicate the distribution of
13C label. 13C-Glutamine is deamidated to (m+5)
glutamate. This is not glutaminolysis, as no energy is produced. But glutamate
can then be converted to α-ketoglutarate and circuit the TCA cycle. After
one circuit, two carbons are lost as CO2 and replaced by unlabeled
acetyl-CoA. This results in m+3 glutamate. Further circuits of the TCA
cycle result in exchange of more 13Ccarbon. Similarly for aspartate,
the initial pass through the TCA cycle yields m+4 aspartate (one carbon
lost as CO2), and another circuit through the cycle yields m+2
aspartate (three carbons lost as CO2). Glutaminolysis can be
quantified in terms of CO2 production by comparing the 13C
content and quantities of metabolites after 13C-glutamine labeling
with the amount of 13C-glutamine taken up by cells.Despite these numerous studies, there are significant gaps in our knowledge of glutamine
metabolism in tumor cells. In particular, apart from one seminal example in which a
glioma cell line was found to convert 60% of the consumed glutamine into lactate [24], there have been few studies to define exactly
how the carbon content of glutamine is distributed between biosynthesis, glutaminolysis,
or secretion as glutamate or other metabolites. Here, quantitative audit of glutamine
utilization by melanoma cells demonstrated that TCA cycle-derived glutamate, not
lactate, was generally the major product of glutaminolysis, irrespective of the
cells' oncogenic background. Additionally, experiments where glutamine was
limited, but alternate metabolites were added, supported a role for glutamine in
maintaining the TCA cycle but also identified aspartate and asparagine synthesis as
important cataplerotic pathways which contribute to “glutamine addiction”
in melanoma. In contrast to melanoma cells, melanocytes could grow in the absence of
glutamine, and exhibited metabolic differences consistent with less glutaminolysis.
RESULTS
Melanoma cells require glutamine for asparagine synthesis and to maintain the
TCA cycle
We tested the glutamine dependence of nine melanoma lines with different
oncogenic drivers (4 mutant BRAF, 4 mutant NRAS, 1 mutant p53). All required at
least 1 mM glutamine for maximal growth (Figure 2A) and there was no proliferation in the absence of glutamine
(Figure S1A, S1B),
while most cell lines could grow in the absence of glucose (Figure S1C). In contrast,
growth of melanocytes was similar with or without glutamine (Figure S1D). As
melanocytes were grown in a melanocyte-specific medium, we checked growth of
Lu1205melanoma cells in this medium and confirmed that growth was substantially
inhibited by the absence of glutamine (Figure S1E).
Figure 2
Glutamine is required for growth and used to sustain TCA cycle
metabolite levels and for aspartate and asparagine synthesis
(A) Effects of titrating glutamine in DMEM on growth of
melanoma cells lines. Mutated oncogenes in cell lines are designated:
(B) BRAF; (N) NRAS; (P53) TP53. (B) Growth of Lu1205 cells
in DMEM with varied glutamine and supplementation with 3 mM DMaK, 0.1 mM
NEAA, 0.1 mM asparagine (Asn), or 5 mM DMGlu. “NEAA-Asn”
indicates addition of a reconstituted NEAA mixture lacking asparagine.
Growth is shown relative to growth in medium containing 2 mM glutamine
(Mean ± SEM of N = 3). (C)
Changes in metabolite pools in Lu1205 cells or melanocytes after 6 h in
glutamine-free medium(Gln-), relative to cells with 2 mM glutamine
(Gln+). Lu1205 Gln− cultures were supplemented as shown
with 3 mM DMaK, 0.1 mM Asn, 0.1 mM aspartate (Asp), or
(“Both”) DMaK and Asn. Source data for part (C) are shown
in Supplementary
Dataset 1.
Glutamine is required for growth and used to sustain TCA cycle
metabolite levels and for aspartate and asparagine synthesis
(A) Effects of titrating glutamine in DMEM on growth of
melanoma cells lines. Mutated oncogenes in cell lines are designated:
(B) BRAF; (N) NRAS; (P53) TP53. (B) Growth of Lu1205 cells
in DMEM with varied glutamine and supplementation with 3 mM DMaK, 0.1 mM
NEAA, 0.1 mM asparagine (Asn), or 5 mM DMGlu. “NEAA-Asn”
indicates addition of a reconstituted NEAA mixture lacking asparagine.
Growth is shown relative to growth in medium containing 2 mM glutamine
(Mean ± SEM of N = 3). (C)
Changes in metabolite pools in Lu1205 cells or melanocytes after 6 h in
glutamine-free medium(Gln-), relative to cells with 2 mM glutamine
(Gln+). Lu1205Gln− cultures were supplemented as shown
with 3 mM DMaK, 0.1 mM Asn, 0.1 mM aspartate (Asp), or
(“Both”) DMaK and Asn. Source data for part (C) are shown
in Supplementary
Dataset 1.To test whether glutamine could be replaced by other nutrients, we measured the
effects of cell-permeable di-methyl derivatives of α-ketoglutarate (DMaK)
or glutamate (DMGlu), or non-essential amino acids (NEAA culture supplement) on
the growth of Lu1205 cells. Each of these reduced the amount of glutamine
required for maximum growth by 50%, to 0.5 mM (Figure 2B). Other potential biosynthetic products of glutamine
utilization, uridine, hypoxanthine, glutathione and hemin, did not reduce the
glutamine requirement (Figure
S2A). Addition of NEAA and DMaK together further reduced the
concentration of glutamine required for optimal growth, to 0.25 mM (Figure 2B). Analysis of the NEAA requirement showed
that addition of asparagine alone could substitute for NEAA, and that adding the
other components of NEAA without asparagine only slightly reduced the glutamine
requirement (Figure 2B). This result
indicates that, in the absence of external asparagine, asparagine synthesis
accounted for up to 50% of the glutamine used in these cells. Similar
improvement in growth in low-glutamine medium was observed by addition of
asparagine or DMaK to cultures of six other melanoma cell lines (Figure S2B). We confirmed
that glutamine could contribute to the carbon backbone of asparagine by labeling
Lu1205 cells with 13C-glutamine and determining synthesis of
asparagine and its immediate biosynthetic precursor, aspartate, from glutamine
(Figure S2C).As another approach to investigating the roles of glutamine in melanoma cells, we
deprived Lu1205 cells of glutamine (with or without DMaK, asparagine or
aspartate) and measured changes in cellular metabolite levels after 6 h (Figure
2C, Supplementary Dataset 1).
Glutamine deprivation resulted in reductions in glutamine, TCA cycle
metabolites, and metabolites peripheral to the TCA cycle - glutamate, aspartate,
asparagine, pyruvate and lactate. Addition of DMaK restored, or enhanced, levels
of most metabolites depleted with glutamine removal, with the exception of
glutamine and asparagine. Addition of 0.1 mM aspartate, a concentration
five-fold greater than physiological concentrations of aspartate in the blood
[25], did not reverse the effects of
glutamine deprivation. Asparagine (0.1 mM) was also without effect on the
depletion of most metabolites, but elevated the level of cellular asparagine by
> 10-fold. The effect of combined DMaK and asparagine supplementation was
additive. These results indicated, first, that glutamine deprivation leads to
loss of metabolites in the TCA cycle and associated pathways, and are consistent
with its role as an anaplerotic substrate. Secondly, aspartate uptake was weak
and insufficient to compensate for loss of glutamine. Thirdly, exogenous
asparagine restored cellular asparagine pools, but due to an apparent lack of
asparaginase activity, asparagine was not converted to aspartate and TCA cycle
metabolites. These conclusions were supported by labeling cells using 0.1 mM
13C-aspartate or 3C-asparagine.
13C-aspartate addition to cultures only weakly labeled aspartate or
TCA cycle metabolites (Figure
S2D). In cells provided with 13C-asparagine, cellular
asparagine was labeled, but lack of labeling of aspartate or TCA cycle
metabolites confirmed that there was negligible conversion of asparagine into
these metabolites (Figure
S2E). In contrast to these melanoma cells, glutamine deprivation of
melanocytes for 6 h resulted in much less loss of cellular glutamate (45% loss
in melanocytes versus 92% loss in Lu1205) and TCA cycle metabolites (maximally,
41% loss of malate in melanocytes versus 85% loss in Lu1205, Figure 2C, Supplementary Dataset 1). This resilience to glutamine
depletion likely contributes to the ability of melanocytes to grow in the
absence of glutamine.
TCA cycle-derived glutamate is the major end product of glutaminolysis in
melanoma cells
To establish more generally how glutamine is used, we quantified the fate of
carbon derived from glutamine in melanoma cells or melanocytes. Cells were
cultured for 72 h with universally-13C-labeled glutamine and the
major metabolites into which 13C accumulated – total cellular
(protein-digested) amino acids and secreted metabolites in culture medium - were
quantified and their degree of 13C-labeling was determined using
GC-MS. Quantification of 13C in metabolites, relative to the amount
of 13C-glutamine taken up by cells, allowed us to calculate the
distribution of carbon from glutamine into cellular and extracellular
metabolites (Figure 3A; see also Supplementary Dataset 2).
We also estimated the amount of carbon from glutamine converted to
CO2, based on quantities and mass isotopomer distributions of
13C-labeled metabolites (Figure 3A,
3B; see Methods and Figure 1B
for details). The combination of cellular amino acids, secreted metabolites and
CO2 on average accounted for 90% of glutamine usage by melanoma
cells or melanocytes (Figure 3A). Secreted
glutamate generally represented the largest destination for carbon from
glutamine – as much as 35% of the total in WM793 cells. Exceptions were
melanocytes, where 32% of the carbon from glutamine was assimilated into protein
as glutamate or glutamine but only 12% was secreted as glutamate, and UACC903
cells, where extracellular glutamate was a minor product of glutamine (5% of
total glutamine carbon). Consistent with this, UACC903 cells, unlike other cell
lines, took up glutamate rather than secreting it (Figure 3C).
Figure 3
Distribution of carbon from glutamine in melanoma cells and
melanocytes emphasizes role of glutamate secretion
(A) Yield of carbon from glutamine in total cellular amino
acids (including protein), in secreted metabolites, and estimated
fraction lost as CO2 after culture of cells for 72 h in
medium containing U-13C-glutamine. Abbreviations: Melcytes:
melanocytes; Asp-asn: combined cellular aspartate and asparagine;
Glu-gln: combined cellular glutamate and glutamine. (B)
Metabolites associated with calculated CO2 production
(products of glutaminolysis). CO2 production was estimated as
the sum of “missing” 13C in partially labeled
end-point metabolites plus CO2 necessarily lost between
glutamine and the measured metabolites. Metabolites associated with at
least 5% of estimated CO2 production are shown, with Asp-asn
representing combined cellular and secreted aspartate and asparagine,
and Glu-gln, combined cellular glutamate and glutamine and secreted
glutamate. (C) UACC903 cells show net uptake of glutamate,
unlike other melanoma cell lines, which secrete glutamate.
(D) Fraction of secreted glutamate of TCA-cycle origin
(partially 13C-labeled). For UACC903 cells, there was no net
secretion, but there was exchange of labeled glutamate into the medium
(Mean ± SEM of N = 3). Source data for
parts (A, B) are shown in Supplementary Dataset 2.
Distribution of carbon from glutamine in melanoma cells and
melanocytes emphasizes role of glutamate secretion
(A) Yield of carbon from glutamine in total cellular amino
acids (including protein), in secreted metabolites, and estimated
fraction lost as CO2 after culture of cells for 72 h in
medium containing U-13C-glutamine. Abbreviations: Melcytes:
melanocytes; Asp-asn: combined cellular aspartate and asparagine;
Glu-gln: combined cellular glutamate and glutamine. (B)
Metabolites associated with calculated CO2 production
(products of glutaminolysis). CO2 production was estimated as
the sum of “missing” 13C in partially labeled
end-point metabolites plus CO2 necessarily lost between
glutamine and the measured metabolites. Metabolites associated with at
least 5% of estimated CO2 production are shown, with Asp-asn
representing combined cellular and secreted aspartate and asparagine,
and Glu-gln, combined cellular glutamate and glutamine and secreted
glutamate. (C) UACC903 cells show net uptake of glutamate,
unlike other melanoma cell lines, which secrete glutamate.
(D) Fraction of secreted glutamate of TCA-cycle origin
(partially 13C-labeled). For UACC903 cells, there was no net
secretion, but there was exchange of labeled glutamate into the medium
(Mean ± SEM of N = 3). Source data for
parts (A, B) are shown in Supplementary Dataset 2.The fraction of inferred total CO2 production associated with
different end-products of glutamine (Figure 3B) indicates the relative importance of these metabolites as
products of glutaminolysis. For most cell lines, the major product of
glutaminolysis was glutamate. Importantly, this indicated that this glutamate
was not simply the deamidation product of glutamine but had traversed the TCA
cycle, replacing carbon released as CO2 with unlabeled carbon from
acetyl-CoA before reaching its final destination (Figure 1B). Of the glutamate that was secreted, 30–50% was
partially 13C-labeled, indicating that it originated from the TCA
cycle (where 13C atoms were exchanged; Figure 3D). This result is significant because it shows that
glutamate secretion is a conduit through which TCA cycle metabolites could be
lost during glutamine deprivation (as in Figure 2C). In the case of the UACC903 cell line, where there was no net
glutamate secretion, lactate was a more significant product of glutaminolysis
than glutamate. In general, though, lactate labeling from glutamine and the
associated CO2 production were low, and were undetectable in two cell
lines, Lu1205 and sbcl2 (Figure 3A,
3B).
Roles of aminotransferases and glutamate dehydrogenase in anaplerosis and
cataplerosis
The above results pointed to the importance of two input/output reactions on
either side of the TCA cycle for glutamine metabolism. The conversion of
glutamate to α-ketoglutarate is an anaplerotic reaction, and, in reverse,
a cataplerotic reaction for the production of TCA-cycle-derived glutamate
(Figure 1). Potential enzymes for this
reaction are mitochondrial alanine aminotransferase (GPT2), aspartate
aminotransferases (cytosolic GOT1 and mitochondrial GOT2), and glutamate
dehydrogenase (GLUD, Figure 1A). On the
other side of the TCA cycle, the GOT2-catalyzed cataplerotic
oxaloacetate-to-aspartate reaction is required for aspartate and thence
asparagine synthesis. To test the role of aminotransferases in glutamine
utilization, we used the general mechanism-based inhibitor aminooxyacetate
(AOA). AOA in the absence of amino acid supplements potently inhibited growth
(Figure S3A), but a
combination of 0.1 mM alanine or NEAA, plus ≥ 2.5 mM aspartate or
dimethyl-asparate substantially reversed AOA inhibition of growth of Lu1205
cells (Figure S3A, S3B)
or other melanoma cell lines (Figure S3C). The requirement for supra-physiological levels of
aspartate further indicated poor aspartate uptake in these cells.To assay the roles of aminotransferases in controlling flux into and out of the
TCA cycle, we labeled Lu1205 cells or melanocytes with either
13C-glucose or 13C-glutamine, and compared the effects of
AOA treatment on the 13C-enrichment of glutamate or
α-ketoglutarate. In untreated Lu1205 cells (Figure 4A, left panel), cellular α-ketoglutarate and
glutamate were both approximately 30% derived from glucose and 50% derived from
glutamine, demonstrating equilibration in the interconversion of these
metabolites. In AOA-treated cells, 13C input from glutamine (via
glutamate) to α-ketoglutarate was maintained or increased, indicating
active glutamate to α-ketoglutarate conversion. However, 13C
input from glucose (via α-ketoglutarate) to glutamate was much reduced,
indicating that the α-ketoglutarate to glutamate reaction was inhibited
(see Figure 1A). Therefore, these cells
convert α-ketoglutarate to glutamate largely using AOA-sensitive
aminotransferases, but they retain the capacity to convert glutamate to
α-ketoglutarate even when aminotransferases are inhibited (apparently due
to the contribution of oxidative deamination by GLUD1 as discussed below).
Figure 4
Testing the metabolic functions of aminotransferases and glutamate
dehydrogenase (GLUD1) in Lu1205 cells
(A) Comparative enrichment of α-ketoglutarate or
glutamate from glucose or glutamine in Lu1205 cells (left panel) or
melanocytes (right panel) ± 0.5 mM AOA. (B–D)
Effects of combined AOA treatment and GLUD1 knockdown
on metabolism and growth. (B) Labeling of TCA cycle
metabolites fumarate and citrate from 13C-glutamine.
(C) Quantities of cellular free glutamate and
glutamine. (D) Mass distribution of secreted glutamate
(corrected for natural labeling and 13C-glutamine impurity).
(Mean ± SEM of N = 3 for all, except mean
± range of N = 2 for D).
**p < 0.05, ***p <
0.01 by Student's unpaired t-test.
Testing the metabolic functions of aminotransferases and glutamate
dehydrogenase (GLUD1) in Lu1205 cells
(A) Comparative enrichment of α-ketoglutarate or
glutamate from glucose or glutamine in Lu1205 cells (left panel) or
melanocytes (right panel) ± 0.5 mM AOA. (B–D)
Effects of combined AOA treatment and GLUD1 knockdown
on metabolism and growth. (B) Labeling of TCA cycle
metabolites fumarate and citrate from 13C-glutamine.
(C) Quantities of cellular free glutamate and
glutamine. (D) Mass distribution of secreted glutamate
(corrected for natural labeling and 13C-glutamine impurity).
(Mean ± SEM of N = 3 for all, except mean
± range of N = 2 for D).
**p < 0.05, ***p <
0.01 by Student's unpaired t-test.In melanocytes (Figure 4A, right panel), the
same type of analysis revealed a substantially lower relative contribution of
glutamine to the synthesis of α-ketoglutarate and glutamate (in the
absence of AOA). Notably, there was not a corresponding increase in the fraction
of these metabolites derived from glucose, which implied that other unlabeled
carbon sources were contributing to their synthesis. After addition of AOA,
though, the derivation of these metabolites from glucose or glutamine closely
matched the Lu1205 results, and the contribution from unlabeled sources was
largely eliminated. This suggests that melanocytes use AOA-sensitive
aminotransferases to convert other amino acids (e.g., branched chain amino
acids) into TCA cycle metabolites, thus making melanocytes less dependent on
anaplerotic utilization of glutamine.The most likely candidate for the AOA-resistant unidirectional deaminating
activity was glutamate dehydrogenase, and to test this, we used Lu1205
containing two different inducible glutamate dehydrogenase (GLUD1) knockdown
constructs, which reduced the expression of GLUD1 by ~90% as
indicated by both qPCR and measurement of glutamate dehydrogenase activity
(Figures 4B–4D and S3D–G). Labeling
of TCA cycle metabolites by 13C-glutamine was not reduced in GLUD1
knockdown cells, except with the addition of AOA, indicating that both
aminotransferase and glutamate dehydrogenase reactions contribute to anaplerotic
flux from glutamine into the TCA cycle (Figure 4B). GLUD1 knockdown increased cellular glutamate pools, consistent
with less conversion of glutamate to α-ketoglutarate, and this effect was
further enhanced by the addition of AOA (Figure 4C). Only combined GLUD1 knockdown and AOA treatment increased
cellular glutamine (Figure 4C). Meanwhile,
analysis of 13C-labeling of glutamate in medium from these cultures
indicated that GLUD1 knockdown had no effect on the labeling pattern of
glutamate (Figure 4D), but AOA treatment
eliminated partially-labeled (m+1, m+2, m+3) glutamate and
increased the proportion of fully labeled (m+5) glutamate. This indicated
that, with AOA treatment, glutamate could be synthesized directly from glutamine
(m+5 labeling), but its synthesis from the TCA cycle (via
partially-labeled α-ketoglutarate) was blocked. These results confirmed
that GLUD1 and aminotransferases were together responsible for
glutamate-to-α-ketoglutarate conversion in these cells, but the reverse
reaction, required for glutamate-generating glutaminolysis (Figure 1B), was mediated only by
aminotransferases.To test the roles of specific aminotransferases, we knocked down GOT1,
GOT2 and GPT2. Knockdown of GPT2
totally inhibited alanine secretion (Figure S4A), and GOT2 knockdown led to an
accumulation of glutamate (Figure S4B), implying that the net flux from both these reactions
was in the direction of α-ketoglutarate production (Figure 1A). Knockdown of GOT1 but
not GOT2 led to an accumulation of aspartate (Figure S4C), confirming
that GOT1 was mainly responsible for α-ketoglutarate-to-glutamate and
aspartate to oxaloacetate conversion (the classic role of GOT1 in the
malate-aspartate shuttle [12]). The
knockdown of any individual aminotransferase (GOT1, GOT2 or
GPT2), unlike AOA treatment (Figure 4D), did not affect the labeling pattern of secreted
glutamate originating from 13C-glutamine (shown as the
m+3/m+5 ratio, Figure S4D). These results implied that no one aminotransferase
fully controlled the glutamate-α-ketoglutarate reaction in either
direction.
DISCUSSION
This study leads to the following salient conclusions: (i) unlike melanocytes,
melanoma cells cannot grow without millimolar quantities of glutamine, and
correspondingly melanoma cells consume up to 7-fold more glutamine than melanocytes
[3]; (ii) Glutamate/α-ketoglutarate
or asparagine are the only metabolites that substantially reduce the glutamine
requirement of melanoma cells (by ~50% or ~75% if used in combination); (iii)
Glutamine, via glutamate, is a major anaplerotic substrate, entering the TCA cycle
by combined action of aminotransferases (GOT2 and GPT2) and glutamate dehydrogenase
(GLUD1); (iv) Paradoxically, glutamate is also the primary cataplerotic output from
the TCA cycle (Figure 1A), and the major
endpoint of (CO2-producing) glutaminolysis; (v) Asparagine is not
metabolized and is apparently only used for protein synthesis. Its precursor
aspartate is an essential cataplerotic product as it cannot be salvaged at
physiological concentrations.One objective of this study was to determine how the metabolism of glutamine differs
in melanoma cells versus melanocytes. Glutamine was essential for the growth of
melanoma cells of diverse oncogenic backgrounds (mutated BRAF, NRAS or p53).
Comparative analysis of these cell lines suggests that glutamine addiction is
probably independent of the initial oncogenic insult, and could be regulated by
factors that are commonly downstream of many oncogenes. Indeed, where there were
differences in melanomaglutamine metabolism, as in the case of glutamate secretion
by UACC903 cells, it was individual cell lines that were different and not a whole
oncogenic class of cell lines. The resistance of melanocytes to glutamine
deprivation compared to melanoma cells may be based on a combination of glutamine
conservation and use of other carbon sources. First, they use a larger fraction of
glutamine for protein synthesis and secrete less as glutamate (Figure 3A). Second, when deprived of glutamine, the loss
of metabolites from the TCA cycle is much less in melanocytes than Lu1205 cells
(Figure 3C). Third, 13C-labeling
combined with AOA treatment indicated a large fraction of
glutamate/α-ketoglutarate in melanocytes (but not Lu1205 cells) is probably
derived from amino acid(s) other than glutamine (Figure 4A).Previous work on glioma cells [24] established
that, in at least some cases, glutaminolysis leads predominantly to production of
lactate. However, we determined that lactate was a relatively minor product of
glutaminolysis in melanoma cells: 0–9% of glutamine carbon taken up by cells
was destined for secreted lactate (Figure 3A;
Supplementary Dataset
2) and only in UACC903 cells was lactate the main glutaminolysis product
(Figure 3B). Whether this flux to lactate
represents a significant pathway for NADPH synthesis and therefore maintenance of
redox balance in any of these cells, as recently shown in pancreatic cancer cells
[16], is an open question, as the
importance of this pathway for NADPH production depends on the relative activity of
other routes for NADPH synthesis (e.g., the pentose phosphate pathway).In general, glutamine-consuming tumor cells secrete glutamate [26]. Recent papers using 13C tracers and flux
analysis [14, 27] calculated rates of glutamate secretion and glutamine uptake but did
not specifically calculate how much of the carbon in the secreted glutamate is
derived from glutamine (as opposed to other carbon sources). Here, we used
13C tracing to determine whether the secreted glutamate comes
straight from glutamine (remaining fully 13C-labeled), or has circuited
the TCA cycle (partial 13C-labeling indicating loss of
13CO2 and acquisition of unlabeled carbon). This is
important as it measures the degree to which glutamate is an end-product of
glutaminolysis in the TCA cycle. Additionally, by measuring the proportion of
secreted glutamate that is only partially 13C-labeled (versus the
fully-13C-labeled input glutamine), we can measure how much of the
secreted glutamate is of TCA cycle origin. This is of relevance for growth
inhibition upon glutamine deprivation (as we observe for melanoma cell lines,
Figures 2A and S1), as removing the
glutamine input to the TCA cycle leads to loss from cells of TCA cycle metabolites
(Figure 2C).It may seem obvious, given the well-known reversibility of aminotransferase-mediated
reactions, that secreted glutamate could be derived from the TCA cycle. What is less
obvious is the relative contribution of aminotransferases versus glutamate
dehydrogenase to the inter-conversion of α-ketoglutarate and glutamate in
cells. As our results in Figure 4A indicate,
glutamate dehydrogenase in these cells only mediates the unidirectional conversion
of glutamate to α-ketoglutarate, whereas PLP-dependent aminotransferases
(such as GOT and GPT) can drive this transformation in both directions (Figure 1A). The balance between glutamate dehydrogenase
and aminotransferase activity in tumor cells has been shown to vary as demonstrated
by changing KRAS expression in pancreatic cancer cells [16], so the actual direction of flux between glutamate and
α-ketoglutarate may vary depending on cell type.Various data indicate melanoma cells rely on aspartate synthesis rather than uptake.
The normal physiological (blood) concentration of aspartate is 20 μM [25], but addition of 100 μM aspartate
did not reverse aspartate depletion following glutamine deprivation (Figure 2C), and the same concentration of
13C-labeled aspartate only weakly labeled cellular aspartate (Figure S2D). In most melanoma
lines studied, AOA was a potent inhibitor of growth even in the presence of NEAA,
which includes 100 μM aspartate. Inhibition was only reversed by adding
≥ 2.5 mM aspartate or dimethyl-aspartate (Figure S3). Aspartate
synthesis is therefore of interest as a point of vulnerability in melanoma. In
studies on other cancers, the role of GOT, but not aspartate synthesis per se, has
been considered. In breast cancer [28], siRNA
was used against GOT1, which, as we confirm in Figure S4, is functional
physiologically in the direction of aspartate to oxaloacetate conversion rather than
aspartate synthesis. Likewise, in pancreatic cancer [16], the focus was on GOT1 in a pathway leading to NADPH production by
malic enzyme.As aspartate is a biosynthetic precursor to asparagine, inhibition of aspartate
synthesis could be usefully potentiated by combination with asparaginase treatment,
which is a long-established therapy for leukemia [29]. Asparaginase treatment would drive melanoma cells to increase
asparagine synthesis from aspartate and glutamine (Figure 1A). Importantly, the microbial asparaginases used for leukemia
have activity on glutamine as well as asparagine [30], and therefore could reduce exogenous glutamine supply at the same
time as demand for glutamine increased. Glutamine deprivation has been demonstrated
to induce asparagine synthetase expression via a GCN2/ATF4 signaling pathway [31], which ironically would further increase
demand for glutamine. Indeed, it has recently been shown that SF188glioma cells
deprived of glutamine turn on asparagine synthetase expression even with the
addition of external asparagine [32].In essence, “glutamine addiction” is an enhanced requirement for
glutamine, the restriction of which threatens cell survival. In this paper, we have
tracked the major uses of glutamine in melanoma cells. The high-demand of glutaminecarbon for certain reactions may limit its availability for other minor, yet vital,
roles, including use by biosynthetic amidases (for purines, NAD, hexosamines, etc.)
and, as glutamate, for glutathione. All of these functions may contribute to the
glutamine requirement of melanoma in vivo.
METHODS
Cell lines and media
The melanoma cell lines used were described previously [33]. The identified tumorigenic mutations in these lines
are: Lu1205, WM793, mel501, UACC903, and WM3629: BRAF mutation; WM1346, WM1366,
and sbcl2: NRAS mutation; MeWo: p53 mutation. Primary human dermal melanocytes
were a kind gift of Dr. Mikhail Nikiforov, Roswell Park Cancer Institute.
Melanoma cells were routinely grown in DMEM (high glucose) supplemented with 4
mM Glutamine (Cellgro), 100 U/mL penicillin, 100 μg/mL streptomycin and
10% (v/v) fetal bovine serum (Hyclone) (FBS) in a humidified incubator, in the
presence of 5% CO2, at 37°C. Melanocytes were grown in Dermal
Cell Basal Medium supplemented with the Melanocyte Growth Kit (ATCC). For
glucose or glutamine deprivation and AOA-inhibition experiments, melanoma cells
were cultured in glucose- and glutamine-free DMEM (Sigma), supplemented with 10%
dialyzed FBS (Gibco) for 72 h. Control cultures contained 2 g/L glucose and 2 mM
L-glutamine, except as noted. AOA was added to cultures at 0.5 mM, except as
noted. Glutamine deprivation in melanocytes was assayed by omitting the
glutamine component of the melanocyte medium and comparing growth with or
without 2 mM glutamine over 240 h (or 72 h for cultures of Lu1205 cells in this
medium). Growth was monitored by cell counting following trypsinization, or
relative viable cell number was measured after 72 h using the Cell Titer 96
Aqueous Assay (Promega).
13C-metabolic labeling procedures
For purposes of accounting for glutamine utilization in melanoma, cells were
seeded at 100,000/well in 6-well tissue culture plates in DMEM medium. The next
day medium was changed to MEM (Cellgro) containing 10% FBS, NEAA, 2 g/L glucose
and 2 mM 50% 13C-uniformly labeled glutamine (Sigma). Cells were
incubated for a further 72 h. To take into account glutamine breakdown or medium
evaporation, medium without cells was incubated in parallel. Fractional
distribution of 13C from glutamine into a metabolite
M was calculated as [(average per-C 13C labeling
of M) × (number of C in M) ×
(amount of M in nmol)]/[(average per-C 13C labeling
of glutamine) × (number of C in glutamine) × (uptake of glutamine
in nmol)]. For labeling in the presence of AOA, cells were incubated for 24 h in
this MEM plus NEAA medium or, for glucose labeling, the same medium was used
except that the glucose component was 50% 13C-uniformly labeled
(Sigma) and glutamine was unlabeled. For aspartate or asparagine13C-labeling, the labeling medium was DMEM, 10% dialyzed FBS, 2 g/L
glucose, 2 mM glutamine and 100 μM uniformly-13C L-asparagine
or uniformly-13CL-aspartate (both Sigma).
CO2 calculation
To determine how much carbon was converted to CO2 during the synthesis
of metabolites from (13C-) glutamine, first, the CO2 that
was necessarily generated in the synthesis of (13C-) metabolites with
fewer carbons than glutamine was counted (e.g., each 13C-labeled
aspartate with 4 carbons, even if fully labeled, was associated with the
production of one molecule of CO2 from glutamine with 5 carbons).
Secondly, the difference between average fractional per-carbon13C-labeling of a metabolite and the fraction of that metabolite that
was 13C-labeled to any extent was determined to measure additional
13C atoms that were converted to CO2 in the production
of that metabolite (e.g., in Figure 1B, the
M+3 glutamate fraction, with 3 13C-labeled carbons, is
associated with the loss of 2 13C-CO2 molecules). These
calculations assumed that glutamine metabolic pathways were linear and that
there was no recombination of 13C derived from glutamine. The
CO2 from glutamine calculated by this method may be
underestimated, as glutamine molecules that were fully oxidized leaving no trace
of 13C in other metabolites are not counted. However, in order to be
fully oxidized, the carbons from glutamine would have to circuit the TCA cycle
at least three times.
Gene knockdowns
The effect of gene silencing on metabolic activity of Lu1205 cells was studied
using RNAi or stable inducible knockdowns. Expression of GOT1,
GOT2 and GPT2 were knocked down using
siRNA. Equimolar (10 nM) mixtures of oligonucleotide duplexes targeted the
following sequences: GOT1 (NM_002079.2):
CCUGGGAGUGGGAGCAUAU, GGUAAUGUGAAGACAAUGG, CCACAUCACUGAUC AAAUU, and
GGUGCACUUCGAAUUGGA; GOT2 (NM_001286220.1):
GCUACAAGGUUAUCGGUA, GCCAAAAGGGUAGAGUCA, GGGACACCAAUAGCA AAAA, and
GGAAUACCUGCCCAUUGGG; GPT2 (NM_133443.2):
CCAUCCAGGUGAAUUACUA, GAUCUUCAUUCCUGCCAAA, and GAAGGCACUUAC CACUUCA. The
GOT1 and 2 siRNA oligos were purchased
from Ambion, the GPT2 siRNA oligo mixture (sc-45647) from Santa
Cruz Biotechnology Inc. The non-targeting control siRNA 1 was purchased from
Thermo Scientific. RNAi Max reagent (Life Technologies) was used mixed at 1% in
OptiMEM with siRNA duplexes for 20 minutes (Life Technologies) followed by
5-fold dilution with growth medium to perform transfections. After 6 hours of
incubation transfection media were changed to growth medium of appropriate
composition. The efficiency of gene expression knockdowns was verified by
western blotting using the following antibodies against: GPT2: SAB1409901
(Sigma) and beta-actin: sc-1618 (Santa Cruz Biotechnology) or by qPCR run on a
Stratagene MX3000 analyzer using SYBR green qPCR Supermix (Life Technologies)
and the following primers: GOT1 forward: GAAGACAATGGCTGACCGGA; GOT1 reverse:
ACTCAACCTGCTTGGGGTTC; GOT2 forward: GGGCTTATATGGTGAGCGTGT; GOT2 reverse:
TCGCAAATCTGGGGTGTTCA.Stable inducible knockdowns were constructed as described [34]. The following oligonucleotides targeting
GLUD1 (NM_005271.3), GTGAATGCCTATAGAAATA (sh#3) or
CCATGAAGTGCTAGATAAT (sh#5), and GOT2 (NM_001286220.1),
TCAGGTTCCTCGTGAGAAA, were designed using the algorithm available at http://www.thermoscientificbio.com/design-center and cloned into
the lentiviral Tet-pLKO-puro vector (Addgene). The constructs were sequenced and
used for transfection of HEK293T cells. Lentiviral particle production and
infection of Lu1205 melanoma cells were done per manufacturer's
instructions. Following selection at 1 μg/mL puromycin, efficiency of
knockdown induced by addition of 100 ng/mL doxycycline (Sigma) for 96 hours was
measured by real time qPCR using the primers described above for
GOT2 or, for GLUD1, forward:
GGAAGCTGCGGCTTAAAAGG; reverse: GTAGCGGTACATGGCCACAA. Additionally, for
GLUD1 knockdown, glutamate dehydrogenase activity was
measured in an assay mix containing 0.25 mM NADH, 100 mM sodium phosphate
buffer, pH 7.5, 0.1 mM EDTA, 5 mM α-ketoglutarate, 50 mM ammonium
chloride, and cell lysate (~1 μg protein in 100 μl volume).
Activity was measured in a plate reader at 340 nm and 30°C.
GC-MS methods
For GC-MS analysis of intracellular metabolites, cells were grown to about 1
million cells/0.5 mg cell protein per culture well. Medium was removed and saved
for analysis, cells were washed quickly 3 times with cold PBS, and 0.45 ml cold
methanol (50% v/v in water with 20 μM L-norvaline as internal standard)
was added to each well. Culture plates were transferred to dry ice for 30 min.
After thawing on ice, the methanol extract was transferred to a microcentrifuge
tube (the described treatment disrupted cells without the necessity of
scraping). Chloroform (0.225 ml) was added, the tube was vortexed and
centrifuged at 10,000g for 5 min at 4°C. The upper layer was dried in a
centrifugal evaporator and derivatized with 30 μl O-isobutylhydroxylamine
hydrochloride (20 mg/ml in pyridine, TCI) for 20 min at 80°C, followed by
30 μl
N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide
(Sigma or Regis) for 60 min at 80°C. After cooling, the derivatization
mixture was transferred to an autosampler vial for analysis.For digestion of cellular proteins, cells washed as above (while still attached
to plates) were lysed in 0.6 ml 10 mM tris-HCl, pH 7.3 containing 1 mM EDTA, 1%
Triton X100 and 0.4 mM L-norvaline. A small fraction (20 μl) was dried
and digested for 18 h with 200 μl 6N HCl. After drying under nitrogen,
the digest was derivatized for GC-MS as above.For GC-MS analysis of medium, 40 μl of medium was mixed with 0.4 ml cold
methanol (50% v/v in water with 20 μM L-norvaline as internal standard).
The methanolic extract was counter-extracted with 0.2 ml chloroform, dried, and
derivatized as for cell extracts.GC-MS protocols were similar to those described before [3], except a modified temperature gradient was used for GC:
Initial temperature was 130°C, held for 4 min, rising at 6°C/min
to 243°C, rising at 60°C/min to 280°C, held for 2 min. Data
were corrected for natural 13C labeling as before [3]. Metabolites were quantified against
varied amounts of standard mixtures run in parallel and data were analyzed using
Metaquant [35]. Quantities were corrected
for recovery using the L-norvaline internal standard. Glutamine uptake from
medium and lactate secretion into medium were measured using a YSI model 7100
enzyme analyzer rather than by GC-MS.
Reagents
Reagents not listed above were obtained from the following suppliers:
dimethyl-aspartate (Bachem); dimethyl-glutamate (Santa Cruz Biotechnology);
other reagents were from Sigma.
Authors: David R Wise; Ralph J DeBerardinis; Anthony Mancuso; Nabil Sayed; Xiao-Yong Zhang; Harla K Pfeiffer; Ilana Nissim; Evgueni Daikhin; Marc Yudkoff; Steven B McMahon; Craig B Thompson Journal: Proc Natl Acad Sci U S A Date: 2008-11-24 Impact factor: 11.205
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