It is widely recognised that defined culture conditions enabling the formation of neurospheres lead to an enrichment of stem-like properties of these cells, which can be functionally distinguished from their differentiated counterpart at many levels ranging from genetic expression to metabolic regulation. Our results support this notion by showing that changes in culture conditions from adherent ML to suspension NS cause a global rewiring of the transcriptome and metabolome, with a high degree of separation shown by PCA and hierarchical clustering. Although U87 cells are adapted to grow under ML conditions, it is evident that their NS cultures are capable of triggering a more stem-like phenotype, by inducing the upregulation of a stem cell-related gene set and the downregulation of differentiation-related gene sets. Similarly, NCH644 cells, which are adapted to grow under NS conditions, also showed downregulation of the same differentiation-related gene sets, supporting that culture conditions may dictate the more stem or differentiated state of cells, respectively. Thus, both U87 and NCH644 are appropriate cellular systems to study stem and differentiated states in GBM, by challenging cells with defined culture conditions.
Since the main purpose of this work was to study metabolic similarities and differences between U87 and NCH644 cells under ML vs. NS conditions, the approach was to perform a general metabolic profiling using LC-MS metabolomics followed by detailed pathway analysis using the MetaboAnalyst platform and a Joint Pathway analysis, which integrates metabolomics and gene expression data. General metabolome analysis revealed that, from the 36 metabolites that were equally regulated in both U87 and NCH644 cells, 35 were found to be downregulated in NS compared to ML. These included TCA cycle metabolites (citrate, α-ketoglutarate, succinate, fumarate and malate), amino acids (alanine, aspartate, isoleucine, citrulline, glutamate, histidine, methionine, ornithine, phenylalanine, proline, sarcosine, serine, threonine and tyrosine) and purine/pyrimidine metabolism-related metabolites (xanthine, xanthosine, UDP, thymidine and thymine), suggesting that NS of both U87 and NCH644 NS may be exhibiting reduced overall cellular metabolic activity, compared to their ML counterparts. On the other hand, hypoxanthine was the only metabolite presenting higher levels in both U87 and NCH644 NS, which points out a possible role of this metabolite in stem-like cells. Hypoxanthine is converted into inosine monophosphate (IMP) by the enzyme hypoxanthine guanine phosphoribosyltransferase (HPRT), which plays a major role in the salvage pathway for purine biosynthesis. Thus, hypoxanthine accumulation could be indicative of an impaired salvage pathway and a consequent increase in the de novo purine synthesis as a compensatory mechanism. In fact, despite the existence of two different pathways for purine synthesis – de novo and salvage pathways – cancer cells tend to display a high rate of the de novo nucleotide synthesis [18, 19]. U87 NS presented significantly higher levels of guanine and guanosine, possibly due to this increase in the de novo purine synthesis. However, NCH644 NS presented significantly lower levels of guanine and guanosine, suggesting that in these cells, these metabolites are either being less produced or rapidly metabolized. The HPRT enzyme may be using guanine for guanine monophosphate (GMP) production in NCH644 NS, instead of using hypoxanthine for IMP synthesis in the salvage pathway. Since the salvage pathway recycles components of existing nucleotides and skips energetically expensive steps of de novo nucleotide biosynthesis , the production of purines via the salvage pathway in NCH644 NS may be more energy efficient in comparison to U87 NS. This may also support the high proliferative state of NCH644 NS and prevent the induction of stress and apoptosis. However, since these results only represent a snapshot of the metabolic pathways that are active in the cells, decrease in guanine and guanosine levels in NCH644 NS could also be indicative of higher demands for nucleotides for rapid proliferation. Nevertheless, both hypotheses are in line with the gene signatures found to be significantly regulated in U87 NS, which pointed towards reduced proliferation in NS compared to ML condition, which was not observed in NCH644 NS. In fact, although the general metabolome analysis pointed towards a global decrease in metabolic activity of both U87 and NCH644 NS, only U87 cells displayed several altered gene sets indicating reduced proliferation. Gene sets related to proliferation (cell cycle, translation, DNA synthesis and repair) and metabolism (TCA cycle, mitochondrial activity, PPP and glutamine metabolism) were all downregulated in U87 NS, while an apoptosis gene set and a gene signature assigned for a negative regulation of nucleotide metabolism were upregulated, all supporting a lower cellular activity. Contrarily, NCH644 NS presented downregulation of an apoptosis and oxidative stress gene sets, suggesting that ML cells may be facing slower proliferation in contrast with NS in this cell line. Again, adaptation to certain culture conditions may explain why U87 cells, which are not adapted to grow in NS, and NHC644 cells, which are not adapted to grow under ML conditions, may proliferate slower when challenged with different culture conditions.
Noteworthy, metabolic adaptations triggered by NS conditions did not differ substantially between the two cell lines. Actually, both Metaboanalyst analyses using only metabolites or metabolites and genes together, identified similar metabolic pathways regulated in U87 and NCH644 NS cells. In particular, “Arginine biosynthesis” was the most significantly regulated pathway in both cell lines. While this suggests that arginine biosynthesis constitutes a key metabolic pathway in the stimulation and maintenance of the stem-like phenotype, there were clear differences in the regulation of specific components of this pathway between the two cell lines. Indeed, the significant upregulation of ASS1 in U87 NS and the downregulation of the same gene in NCH644 NS was identified as a major difference that could determine differences in the metabolic fate of aspartate in the two cellular systems.
Aspartate can be used for the synthesis of arginine as part of the cytoplasmic arm of the urea cycle. Through the ATP-dependent activity of ASS1, aspartate is condensed with citrulline to form argininosuccinate and subsequently cleaved into arginine and fumarate by argininosuccinate lyase (ASL). Aspartate can either be synthesized from the TCA cycle metabolite oxaloacetate and then transported to the cytoplasm by the mitochondrial SLC25A13 transporter or taken up by the cells through the SLC1A3 transporter. Since aspartate is also an essential precursor for nucleotide synthesis, conversion of aspartate to argininosuccinate by ASS1 can prevent this metabolite to enter nucleotide biosynthesis, possibly resulting in reduced proliferation. ASS1 upregulation has been reported in ovarian, colorectal, gastric and lung cancers, compared to the corresponding normal tissues [21–24]. While the role of ASS1 in cancer as well as the molecular mechanism mediating ASS1 upregulation remains unclear, it has been described that high ASS1 expression is associated with increased proliferation and tumourigenicity of colorectal cancer . On the other hand, it has been reported that downregulation of urea cycle metabolism, specifically decreased activity of ASS1 expression, diverts aspartate towards pyrimidine biosynthesis to support cell proliferation, while evading arginine biosynthesis, as part of metabolic reprograming in cancer [26, 27]. Reduced ASS1 expression in cancer is accompanied by increased aspartate metabolism through the trifunctional protein CAD (Carbamoyl-Phosphate Synthetase 2, Aspartate Transcarbamylase and Dihydroorotase), leading to increased pyrimidine synthesis . Importantly, decreased ASS1 expression or arginine depletion in gastric cancer is described to inhibit cancer cell migration and motility, therefore affecting metastasis formation in vivo .
Besides ASS1, the urea cycle consists of four other main catalytic enzymes: two cytosolic enzymes, ASL and ARG, and two mitochondrial enzymes, CPS1 and ornithine transcarbamylase (OTC) . These enzymes catalyse the synthesis of arginine, ornithine and citrulline, respectively, and the urea cycle not only plays a role in the removal of excess amino-groups but also produces metabolic intermediates for the synthesis of metabolites that are essential for cell survival and proliferation [29, 30]. Additionally, NAGS and the two amino acid transporters – SLC25A13 or citrin and SLC25A15 or ORNT1 (mitochondrial ornithine transporter 1) – also participate in urea metabolism .
Among the urea cycle metabolites, we found that both U87 and NCH644 NS presented significantly lower levels of aspartate in comparison with their ML counterpart. Additionally, expression of the high-affinity amino acid transporter SLC1A3 that mediates the uptake of glutamate and aspartate by cells, was significantly increased in both U87 and NCH644 NS, although much stronger in U87 cells. Since ASS1 was differentially regulated in the two cell lines, this may suggest that although aspartate is synthesised/taken up by NS cells, its metabolic fate may be very different between the two cell lines. While in U87 NS, aspartate may be shuttled towards arginine synthesis in the urea cycle, NS of NCH644 cells could use aspartate mainly for nucleotide synthesis. In fact, although ASL expression was not significantly changed between ML and NS in both cell lines, arginine levels were significantly increased in U87 NS compared to ML, while being significantly decreased in NCH644 NS. This suggests that U87 cells increase arginine synthesis via the urea cycle when placed in NS conditions while this is not taking place in NCH644 cells. Additionally, ARG2 was significantly increased in U87 NS, along with ADC, an enzyme that catabolizes arginine into agmatine, suggesting that arginine could be further metabolized by these two enzymes for ornithine and agmatine production, respectively. In contrast, the same enzymes were not changed in NCH644 cells. OAT and ODC expression was significantly increased in NCH644 NS, while not being regulated in U87 NS. OAT and ODC are involved in proline and polyamines biosynthesis, respectively, by metabolizing the urea cycle intermediate ornithine. This could suggest that while ornithine in U87 NS is diverted to citrulline to fuel the high demand for arginine through ASS1, ornithine is being diverted in NCH644 NS towards proline and polyamine synthesis. Indeed, the very low levels of ornithine present in NCH644 NS also indicate a diminished arginine metabolism in these cells. Interestingly, the SLC25A15 transporter, which transports ornithine from the cytoplasm to the mitochondria, was found to be significantly upregulated in NCH644 NS, suggesting that the low amount of ornithine in NCH644 NS may be directed to the mitochondria and away from arginine biosynthesis. Although U87 NS also display significantly reduced levels of ornithine, this reduction was not as strong as in NCH644 NS, possibly due to the high expression of ARG2 and NAGS, which maintain an influx of ornithine into the urea cycle for arginine biosynthesis. NAGS catalyses the production of N-acetylglutamate (NAG) from glutamate and acetyl-CoA, which is then used for the production of ornithine, or as an allosteric cofactor for CPS1. Again, supporting the notion that NCH644 NS rewire their metabolism to lower the production of ornithine to feed arginine biosynthesis, CPS1 in these cells was significantly reduced. Finally, NOS1, which produces nitric oxide and citrulline from arginine, was downregulated in NCH644 NS, again pointing to a low arginine catabolism in these cells. In U87 NS, although not presenting significant regulation of the NOS1 gene itself, a significant downregulation of a gene set assigned to NOS1 metabolism was found, indicating alterations in nitric oxide signalling. However, upregulation of ARG2 and ADC indicates a higher catabolism of arginine in the urea cycle and for agmatine production in these cells.
Together, our results identify arginine metabolism as a key metabolic process associated with stemness in two different cellular systems. While altered arginine metabolism is clearly associated with culture conditions that enrich for stem-like cells, the exact metabolic rewiring or arginine metabolism is distinct between the two cell lines to fulfil cell line specific demands. Thus, the use of different metabolic routes within this pathway ensures cell survival by accomplishing the metabolic needs of each cell system through transcriptional and metabolic adaptations.