Background
The metabolic reprogramming of cancer cells is likely a tool for the cells to rapidly respond to micro-environmental changes and to the demand of nutrients for cell growth and survival [
1‐
4]. Evidence shows that cancer cells with a KRAS mutation or an electron transport chain defect depended on glutamate oxaloacetate transaminase 1
(GOT1) to support cell proliferation [
5‐
7]. GOT1 reversibly catalyzes the interconversion of aspartate and oxaloacetate (OAA), and thus coordinates the carbohydrate and amino acid metabolism. In pancreatic ductal adenocarcinoma (PDAC) cells, glutamine-derived aspartate was shown to be converted to OAA by GOT1 and GOT1 was also involved in the maintenance of the redox homeostasis through the sequential conversion of OAA into pyruvate. This reprogramming of glutamine metabolism was driven by KRAS, one of the most common genetic alterations in pancreatic cancer [
6]. However, the metabolic KRAS-GOT1 link was not found in primary human pancreatic tumors and the mechanisms behind the GOT1 involvement have remained unclear [
8]. Interestingly, in contrast to PDAC cells, where aspartate was converted to OAA by GOT1, cancer cells with defects in the electron transport chain reversibly used GOT1 to provide aspartate from OAA to maintain cell growth [
5]. Through further analysis of GOT1 with the Oncomine database, we found the GOT1 gene expression levels to vary in different types of cancers, for instance the GOT1 expression was up-regulated in breast and lung cancer [
9‐
12], while down-regulated in brain and colorectal cancer [
13‐
16]. Taken together, these data do not only show the importance of GOT1 in supporting cancer cell proliferation, but also imply a complexity of the GOT1 function in cancer cell metabolism. The microenvironment and nutrient levels in solid tumors are constantly changed [
17]. To survive such conditions, cancer cells have to rapidly alter metabolic pathways. We hypothesized that GOT1 can be used by tumor cells to deal with unfavorable growth conditions. Therefore, studies of GOT1 may give new insights in cancer cell metabolism, and may also provide novel targets for cancer treatment. Here, we found that GOT1 is involved in the regulation of glycolytic metabolism and redox homeostasis. Inhibition of GOT1 leads to increased glucose consumption and lactate secretion rates. Moreover, GOT1-null 143B osteosarcoma cells showed accumulation of NADH and decreased NADH/NAD
+ ratios when exposed to nutrient depletion. Our results also show that the GOT1 pathway is dispensable for cancer cells when nutrients are sufficient. However, GOT1 is indispensable for cell survival at low nutrient levels, probably as the key source of OAA to fuel the rewired metabolic pathways.
Methods
Cell lines, plasmids and reagents
143B (ATCC® CRL-8303™) and A549 (ATCC® CCL-185™) cells were cultured in DMEM supplemented with 10% FBS, 1% penicillin and streptomycin at 37 °C, 5% CO2. siRNA expression vector pSilencer™ Puro Expression Vectors kit (Applied Biosystems,Life technologies), the CRISPR/CAS 9 plasmid pSpCas9(BB)-2A-GFP was from Addgene and TurboFect transfection reagent from Thermo Scientific. The kits: The quick ligation kit (NEB); RNeasy mini kit (Qiagen); High Capacity cDNA Reverse Transcription Kit (Applied Biosystems); KAPA SYBR® FAST qPCR Kit (Kapa Biosystems); Cell Proliferation Kit II (XTT) (Sigma-Aldrich); Reagents: L-glutamine solution, dialyzed FBS, glucose, galactose, glycine, serine, L-aspartic acid sodium salt monohydrate, OAA, phosphoenolpyruvate (PEP), β-nicotinamide adenine dinucleotide sodium salt and aminooxyacetate (AOA), Antimycin A and 2-thenoyltrifluoroacetone were from Sigma. The glucose and pyruvate-free and glutamine free-DMEM were from Thermo Fisher Scientific.
Establishment of GOT1 knockout cell line with CRISPR/Cas 9 system
The targeting sequences for single strand guide RNAs were determined with the online tool CRISPR RNA Configurator from Dharmacon, and the sequence of AGTCTTTGCCGAGGTTCCGC was selected for making CRISPR/Cas 9 construct. Briefly, sgRNA specifying oligos (5′---caccgAGTCTTTGCCGAGGTTCCGC---3′; 5′---aaacGCGGAACCTCGGCAAAGACTc---3′) were synthesized, annealed and cloned into pSpCas9(BB)-2A-GFP vector as described by Ran FA [
18]. The plasmid with specific insertion was confirmed by DNA sequencing and purified for cell transfection. The 143B cell line was used for cell transfection. The cell transfection experiment was performed according to the manufacturer’s instructions. After 48 h post-transfection, the single GFP expressing cells were sorted and seeded in 96-well plates with BD FACSAria™ III. The clones with indel mutations were pre-screened by real-time quantitative PCR with two pairs of primers. Primers specific for wild allele: Forward 5’-AGTCTTTGCCGAGGTTCCG-3′; Reverse 5’-GTGCGATATGCTCCCACTC-3. Primers for wild and mutated alleles: Forward 5′- TGCTCCTGAGTTCTCCATTG-3′; Reverse 5′- AACAGAAACCGGTGCTTCAT-3′. For mutated allele primers, the forward primer was located in the region where expected indel might occur. If the indel mutation is introduced via CRISPR7CAS9 system, the efficiency of the PCR will be compromised. After the pre-screening, the clones with lower GOT1 mRNA level were further confirmed by gene sequencing. Primers for amplification of the DNA fragment of the mutated DNA region for sequencing were: Forward: 5’-GCTAATAGCGTTCCTTCTCCCC-3′; Reverse: 5’-TACATCCTTACCTCCCACTCCC-3′. The knockout of GOT1 was further confirmed with Western blot with specific anti-GOT1 antibody (Abcam). For loading control, the primary antibody was β-actin (Sigma). The secondary antibody was anti-mouse (Santa Cruz).
Establishment of stable GOT1 knock-down cell lines in 143B and A549 cells with siRNA
GOT1 specific siRNAs and mock control siRNA expression plasmids were prepared as described by the manufacturer. Briefly, two specific oligonucleotides were designed using online tools BLOCK-iT™ RNAi designer (
http://rnaidesigner.lifetechnologies.com/rnaiexpress/). The siRNA target sequences are 5′---TAGCCTAAATCACGAGTAT---3′ and 5′---TGGACAGGTAATGTGAAGA---3′ respectively. The two complimentary oligonucleotides were annealed and ligated into pSilencer 2.1-U6 puro siRNA expression vector and transfected into 143B and A549 cells with TurboFect Transfection Reagent. Stable expression cells were selected with puromycin at 1000 ng/ml for 2 weeks and the knock-down clones were screened with real-time PCR with the primers used for the CRISP/Cas 9 mutated cells. The GOT1 knock-down cell lines and mock controls were maintained with puromycin at concentration of 200 ng/ml.
Growth curves of CRISPR/cas9 knockout and siRNA knock-down 143B cell lines
25 × 103 cells in exponential phase were seeded in 24-well plates in triplicate. The cell numbers were counted every day for 5 days with a Bürker chamber under light microscope.
Soft agar colony assay
The soft agar experiment was performed as described previously [
19]. Briefly, 500 CRISPR/Cas9 mutated and wild type143B cells were suspended in 0.35% agarose in DMEM supplemented with 10% FBS, 1% penicillin and streptomycin, and seeded over a basal layer of 0.5% agarose. For 143B siRNA knock-down cell lines, 500 cells were used for the soft agar assay. For A549 cell lines, 1000 cells were seeded in the plates. After 10 days culture for 143B cell lines and 3 weeks for A549 cell lines at 37 °C, 5% CO
2, plates were stained with 0.01% crystal violet for 1 h, and colonies were scored manually from 3 wells for each cell type.
AOA treatment
Briefly, wild type 143B and A549 cells were seeded in triplicate in 96-well plates at density of 1 × 104 cells per well. After 24 h, the AOA was added into the wells at different concentrations as indicated in the figures. The cell viability was measured with XTT assay 24 h after the addition of AOA.
Gene expression profile changes determined with real-time PCR
Since GOT1 has been linked to growth arrest, metabolism and oxidative stress, genes involved in these pathways were analysed with real-time PCR. The gene expression levels were analysed forCDNK1A, HIF1α, ATG5, BECN1, BIP, G6PC3, CHOP, GADD34 and GOT1. S18 was used as a loading control. Briefly, 2 × 105 wild type and mutated 143B cells were seeded in 6-well plates in triplicate. After 24 h, three wells of each wild type and mutated 143B the cells were collected for total RNA extraction as time point zero. For the rest of the wells, the medium was replaced with glucose-free medium. After 4 h incubation, the total RNA was extracted and the cDNA was synthesized according to the manufacture’s instruction. The real-time PCR experiments were conducted using an Applied Biosystems 7500 Fast Real-time PCR with the following primers:
P21: 5’-CAGACCAGCATGACAGATTTC-3′; 5’-TTAGGGCTTCCTCTTGGAGA-3’.
HIF1α: 5’-TGCAACATGGAAGGTATTGC-3; 5’AATGGGTTCACAAATCAGCA-3′.
ATG5: 5’-TGGGATTGCAAAATGACAGA -3′; 5’-TTTCCCCATCTTCAGGATCA -3’.
BENC1:5′- CCAGGATGGTGTCTCTCGCA -3′; 5′- CTGCGTCTGGGCATAACGCA-3’.
BIP: 5’-CTCAACATGGATCTGTTCCG -3′; 5’-CCAGTTGCTGAATCTTTGGA -3’.
G6PC-3: 5’-ATAATGACGGCCCTGTCTTC-3′; 5’-TGGTGAGGGAAATGTGCTAA-3’.
CHOP: 5’-TCATACATCACCACACCTGA-3′; 5’-TAGGTACCCCCATTTTCATC-3′.
GADD34: 5’-ATGATGATGGCATGTATGGT-3′;'5’-TTAACTCCCTCCTCTTCAGC-3’.
S18: 5’-TCACTGAGGATGAGGTGGAA-3′; 5′- GCTTGTTGTCCAGACCATTG -3′.
Analysis of autophagy with western blot
Wild type and GOT1-null 143B cells were grown at a density of 1 × 106 in 10 ml DMEM with 10% FBS, 1% % penicillin and streptomycin into two 10 cm Petri dishes for each cell types. After 24 h, one plate from each cell type was collected. The medium in the rest of plates was replaced with glucose-free DMEM supplemented with 10% dialyzed FBS, 1% penicillin and streptomycin, and the cells were cultured for 4 h, then harvested. The cells were lysed in RIPA buffer, and 25 μg total protein was used for Western blot. To study autophagy in GOT1-null cells, the primary antibody was anti-LC3 (Sigma, L8918), and the secondary antibody was donkey anti-rabbit (Santa Cruz). For loading control, the primary antibody was β-actin (Sigma). The secondary antibody was anti-mouse (Santa Cruz).
Glucose and glutamine deprivation
To investigate the glucose and glutamine dependency of GOT1-null 143B cells, wild type and GOT1-null 143B cells were seeded in 96-well plates in triplicate at a density of 5 × 103 cells per well in DMEM supplemented with 10% FBS, 1% penicillin and streptomycin. After 24 h, the medium was replaced with DMEM with glucose concentration at 0, 0.2, 1 and 4.5 g/L glucose. For glutamine deprivation, the cells were grown in DMEM with or without glutamine at concentration of 2 mM. The 10% dialyzed FBS was added into the medium. After 24 h, the cell viability was determined with XTT assay.
To study the rescue of GOT1-null 143B cells with different metabolites, 5 × 103 wild type and mutated 143B cells were seeded in 96-well plates in triplicate. After 24 h, the cell medium was replaced with glucose free DMEM supplemented with different metabolites: galactose, glycine, serine, pyruvate, aspartate, OAA and PEP. The concentrations of the metabolites are indicated in the figures. For GOT1 siRNA knock-down A549 cells, the same number of non-template control (NTC) cells and siRNA-1 cells were seeded in 96-well plates in triplicate. After 24 h, the culture was replaced with DMEM supplemented with different metabolites as indicated in the figures. For the combined AOA and metabolites experiments, 5 × 103 wild type 143B and A549 cells were seeded in 96-well plates, and after 24 h the medium was replaced with glucose-free DMEM supplemented with AOA and metabolites as indicated in the figures. Dialyzed FBS was used in these experiments. The cell viability was determined with XTT assay.
H2O2 challenge
For H2O2 resistance, both wild type and GOT1-null 143B cells were seeded in 96-well plates in triplicate at density of 1 × 104. After 24 h, the medium was replaced with fresh DMEM with H2O2 concentrations at 0.2, 2 and 20 mM. The viability was determined with XTT after 24 h.
Nutrient depletion and rescue of GOT1-null 143B cells with different metabolites
To deplete nutrients in the medium, both wild type and GOT1-null 143B cells were seeded in 96-well plates in triplicate at a density of 5 × 103. The cells were continuously grown for 4 days without changing medium. Then the medium was replaced with glucose-free and 1 g/L glucose DMEM supplemented with 10 mM aspartate, 5 mM OAA, 2.5 mM PEP respectively. For glucose-free DMEM, malate (10 mM), succinate (10 mM) and NAD+ (100 μM) were also tested. The cell morphological changes were recorded. The cell viability treated with malate, succinate and NAD+ for 24 h were determined with XTT assy.
Antimycin a and 2-thenoyltrifluoroacetone treatment
Both wild type and GOT1-null 143B cells were seeded in 96-well plates in triplicate at density of 5 × 104. After 24 h, 0.1 μM of antimycin A and 1 mM of 2-thenoyltrifluoroacetone (TTFA) were added into the medium respectively. The viability of cells was measured after 48 h with XTT assay.
Cell viability determination
Cell viability was determined with XTT assay. Briefly, 50 μl of XTT labelling reagent and 1 μl of electron coupling reagent were mixed and 50 μl of mixture added into each well of a microtiter plate. The plate was incubated in a humidified atmosphere for 3 h and the absorbance was measured using an ELISA reader (Infinite® M200, Tecan trading AG) at 450 nm with a reference wavelength at 690 nm. All the data were normalized with untreated control groups in the experiments.
Measurements of the levels of glucose, lactate and NADH/NAD+
Wild type and GOT1-null 143B cells were seeded in 24-well plates in triplicate at density of 5 × 104. The culture supernatants were collected at day 2 and day 4. The concentrations of glucose and lactate in the supernatants were measured with Glucose assay kit (Biovision) and Lactate assay kit (Sigma) respectively. The NADH/NAD+ levels were analysed with NADH/NAD+ assay kit from Sigma. For NADH/NAD+ levels in nutrient-complete condition, 1 × 106 wild type and mutated 143B cells were seeded in 10 cm Petri dishes, after 24 h the cells were harvested; For the NADH/NAD+ levels in low nutrient condition, the cells were continuously cultured for 4 days and then harvested. The assays were performed according to the instruction of manufacture.
Wild type A549, 143B and Mia PaCa-2 cells were seeded in 96-well plates in duplicate at a density of 5 × 103. After 24 h, the medium was replaced with complete, glucose-free and glutamine-free DMEM with metformin at a concentration of 5 mM. The cell viability was measured 24 h later with XTT.
Data set analysis and mining
To confirm the relevance of GOT1 to cancer growth in vivo, we first analyzed the GOT1 expression profile in a lung cancer RNA-seq data set [
20]. In order to confirm the analysis result from our own data set, we also mined and examined another two data sets: the early stage NSCLC data base GEO:GSE19188 [
21] and the metastatic melanoma data base GEO: GDS3966 [
22]. GEPIA is a newly established gene expression analysis web server [
23], which integrates TCGA and GTEx databases, totally including 9736 cancers and 8587 normal samples, and improves the efficiency in various differential analyses. With the GEPIA web tool, we investigated the GOT1 expression patterns and the relationship between GOT1 expression profiles and the overall survival rates. The GOT1 gene expressions were checked in 33 types of cancers, and the overall survival rates were also investigated with quartile cut-off.
Statistics
Unpaired student’s t-test, one way ANOVA or Wilcoxon test was used for statistics analysis.
Discussion
The microenvironment in solid tumors is constantly changing and the nutrient levels will accordingly be affected. Adaptation to these changes is important for survival of tumor cells and published data have demonstrated that GOT1 plays a key role in the metabolic reprogramming and maintenance of redox homeostasis in cancer cells. In this study, we focused on the role of GOT1 in the metabolic adaptation to changes of nutrient levels. Our results show that GOT1 plays a key role to coordinate glucose consumption and glycolysis for cancer cells to survive the stress of low levels of nutrients. Inhibition of GOT1 led to glucose dependency and increased vulnerability to low nutrient levels. We found that knockout of GOT1 had neglectable effect on cell growth and survival when nutrients are sufficient. However, the GOT1-null or down-regulated cancer cells were highly sensitive to nutrient depletion or glucose deprivation. Withdrawal of glucose led to rapid death of both GOT1-null 143B and GOT1 siRNA knockdown A549 cancer cells compared to their controls. Interestingly, only OAA and PEP were able to partially rescue the cells. Although cancer cells with defects in electron transport chain were able to produce aspartate from OAA to support proliferation [
5], addition of aspartate could not rescue either the GOT1-null or GOT1 siRNA knockdown A549 cancer cells. Since OAA can be converted to PEP by PEPCK, these results indicate that OAA is a key intermediate in rapidly altered metabolism in cancer cells exposed to unfavorable growth conditions. In addition to GOT1, OAA can, in mammalian cells, be produced by malate dehydrogenase, via conversion of malate to OAA, and by ATP citrate lyase, via conversion of citrate to OAA. Supplement of malate and succinate to GOT1-null cells could not rescue the cells indicating that malate dehydrogenases and ATP citrate lyases are not major sources of OAA when glucose levels are decreased. Our data suggest that GOT1 is the main source of OAA necessary for cancer cells to maintain cell viability upon nutrient scarcity.
Both OAA and PEP are substrates for gluconeogenesis. Although gluconeogenesis has been thought to exclusively occur in certain organs, PEPCK, the mitochondrial isoform of PEPCK and fructose-1,6-bisphophatase, are key enzymes in the gluconeogenesis pathway that have been shown to be involved in cancer cell proliferation and inhibition of those enzymes significantly inhibited cancer growth [
30‐
32]. Recently, it was shown that carbons from
13C3-lactate appeared in PEP along the gluconeogenesis pathway during glucose deprivation in A549 and H23 lung cancer cell lines [
30‐
33]. In our study the gene expression of
G6PC3, an enzyme catalyzing the last step in the gluconeogenic and glyconeolytic pathways, was significantly increased in GOT1-null 143B cells. In addition the expression of BIP, a glucose-regulated protein, was also changed. Our study suggests that GOT1 is important for intracellular glucose homeostasis. Supplementation with substrates up-stream of GOT1 in the gluconeogenesis pathway did not improve cell viability in GOT1-null cells grown in glucose free medium, further supporting a pivotal role of GOT1 in providing metabolites necessary for gluconeogenesis. Galactose supports cancer cell proliferation mainly through fueling the pentose phosphate pathway and not glycolysis [
34]. Therefore, the slightly increased viability by addition of galactose indicated that the pentose phosphate pathway partially contributed to cell viability, but was not the key pathway for GOT1-null cells to survive glucose deprivation. Metformin is a well-known gluconeogenesis inhibitor that has been shown to cause accumulation of NADH in cells [
31]. A similar pattern of NADH accumulation was found in GOT1-null 143B cells grown in nutrient-depleted conditions. Supplement with NAD
+ improved the NADH/NAD
+ ratio and could partially rescue the GOT1-null cells grown in nutrient-scarcity.
Pyruvate conversion to lactate is one of the major sources to regenerate NAD
+ in cells [
35]. In GOT1-null 143B cells, the lactate secretion rate was considerably higher than in wild type control cells. This data indicated that increased glucose consumption might be utilized to support the pyruvate-to-lactate-reaction and thereby regenerate NAD
+ to balance up the accumulation of NADH in GOT1-null cells. The addition of pyruvate was able to protect GOT1-null 143B to maintain viability upon glucose withdrawal. The recently published work by Abrego showed that up-regulation of GOT1 decreased the lactate release rate in low pH microenvironment [
36]. Instead of making macromolecules for cell proliferation, pyruvate was secreted into the extracellular microenvironment. Such non-economic metabolism occurred at the expense of glucose dependency. Actually, the GOT1-null 143B cells increased autophagy, as a possible compensatory mechanism. When nutrient levels were high, the new rewired pathways could function well. However, when the nutrient levels dropped, the GOT1-null cells had lost the metabolic flexibility to survive unfavorable conditions [
25,
26]. Furthermore, inhibition of GOT1 led to rapid ischemic-like cell death upon glucose deprivation and only OAA and PEP were able to fully prevent, and NAD
+ partially prevent such morphological changes. The ischemic-like cell death is also called oncosis and has been shown to be involved in diseases such as ischemic heart disease and stroke [
37‐
39]. Consistent with our results, other studies have shown that OAA is neuroprotective against ischemic stroke and that a combination of human rGOT1 with low doses of OAA induces a protective effect after cerebral ischemia [
40,
41]. Moreover, evidence also indicates that NAD
+ is able to protect cells against ischemic injury [
42,
43].
Finally, analysis of a sequencing dataset and mRNA expression datasets showed that increased GOT1 expression is found in lung adenocarcinoma and melanoma. Moreover, higher levels of GOT1 were linked to poor survival in certain types of cancers. However, we also found GOT1 significantly decreased in other types of cancers. The diversity of GOT1 expression is probably a result of the pivotal role of GOT1 in cancer metabolic plasticity. Cancer cells are able to control the aerobic glycolysis rate via GOT1 and thereby regulate the NADH/NAD+ ratio. Up- or down-regulation of GOT1 most likely depends on cancer type, growth properties and micro environment. GOT1 might be a useful candidate target for treatment of cancers with high GOT1 expression.