The role of the SNF1 signaling pathway in the growth of Saccharomyces cerevisiae in different carbon and nitrogen sources

Abstract

Cancer is a leading cause of death worldwide, reporting nearly 10 million deaths in 2020. One of the hallmarks of cancer cells is their capability to evade growth suppressors and sustain proliferative signaling resulting in uncontrolled growth. The AMPK pathway, a catabolic via to economize ATP, has been associated with cancer. AMPK activation is related to cancer progression in advanced stages, while its activation by metformin or phenformin is associated with cancer chemoprevention. Thus, the role of the AMPK pathway in cancer growth modulation is not clear. Saccharomyces cerevisiae might be a useful model to elucidate AMPK participation in growth regulation since it shares a highly conserved AMPK pathway. Therefore, this work is aimed at evaluating the role of the AMPK pathway on S. cerevisiae growth under different nutritional conditions. Herein, we provide evidence that the SNF1 gene is necessary to maintain S. cerevisiae growth with glucose as a sole carbon source at every concentration tested. Resveratrol supplementation inhibited the exponential growth of snf1∆ strain at low glucose levels and decreased it at high glucose levels. SNF1 gene deletion impaired exponential growth in a carbohydrate concentration-dependent manner independently of nitrogen source or concentration. Interestingly, deletion of genes encoding for upstream kinases (SAK1, ELM1, and TOS3) also had a glucose dose-dependent effect upon exponential growth. Furthermore, gene deletion of regulatory subunits of the AMPK complex impacted exponential growth in a glucose-dependent manner. Altogether, these results suggest that the SNF1 pathway affects the exponential growth of S. cerevisiae in a glucose-dependent manner.

Keywords: AMPK/Snf1p; Cancer; Glucose concentration; Growth; Nitrogen sources; SNF1 signaling pathway.

Fig. 1

Effect of SNF1 gene deletion in S. cerevisiae growth. (a) Serial plot dilution plates of snf1∆ and WT strain under different glucose concentrations. (b) Specific growth rate of snf1∆ and WT strains. The results represent mean values ± SD from seven to nine independent experiments. Statistical significance was calculated by t-test (^**P < 0.01; ^***P < 0.0001)

Fig. 2

Impact of resveratrol supplementation on the growth of S. cerevisiae and its SNF1 gene deletion. The specific growth rate of snf1∆ and WT strains. The results represent mean values ± SD from seven to nine independent experiments. Statistical significance was calculated by t-test (^**P < 0.01; ^***P < 0.0001)

Fig. 3

Influence of chemical nature and concentration of carbon and nitrogen sources on growth of the mutant snf1Δ. Data in the heat map shows the cluster membership of the mutant snf1Δ growth relative to the WT strain times 100. The average linkage clustering method was used, while the Euclidean distance measurement method was used. The results represent mean values from 3 to 5 independent experiments, including mean values of 3 technical repetitions

Fig. 4

Influence SAK1, ELM1, and TOS3 gene deletion on S. cerevisiae growth. The specific growth rate of sak1∆, elm1∆, tos3∆, and WT strains at (a) 0.1%, (b) 1%, and (c) 10% glucose. The results represent mean values ± SD from seven to nine independent experiments. Statistical significance was calculated by one-way ANOVA followed by Dunnet’s test (^*P < 0.05 vs. WT; ^**P < 0.001 vs. WT; ns, not significant)

Fig. 5

Effect of genes SNF4 and GAL83 on cell growth. The specific growth rate of snf4∆, gal83∆, and WT strains at (a) 0.1%, (b) 1%, and (c) 10% glucose. The results represent mean values ± SD from seven to nine independent experiments. Statistical significance was calculated by one-way ANOVA followed by Dunnet’s test (^***P < 0.001 vs. WT; ^****P < 0.0001 vs. WT; ns, not significant)