Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments.
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Fletcher E, Feizi A, Bisschops MMM, Hallström BM, Khoomrung S, Siewers V, Nielsen J
Metab. Eng. 39 (-) 19-28 [2017-01-00; online 2016-11-02]
Tolerance of yeast to acid stress is important for many industrial processes including organic acid production. Therefore, elucidating the molecular basis of long term adaptation to acidic environments will be beneficial for engineering production strains to thrive under such harsh conditions. Previous studies using gene expression analysis have suggested that both organic and inorganic acids display similar responses during short term exposure to acidic conditions. However, biological mechanisms that will lead to long term adaptation of yeast to acidic conditions remains unknown and whether these mechanisms will be similar for tolerance to both organic and inorganic acids is yet to be explored. We therefore evolved Saccharomyces cerevisiae to acquire tolerance to HCl (inorganic acid) and to 0.3M L-lactic acid (organic acid) at pH 2.8 and then isolated several low pH tolerant strains. Whole genome sequencing and RNA-seq analysis of the evolved strains revealed different sets of genome alterations suggesting a divergence in adaptation to these two acids. An altered sterol composition and impaired iron uptake contributed to HCl tolerance whereas the formation of a multicellular morphology and rapid lactate degradation was crucial for tolerance to high concentrations of lactic acid. Our findings highlight the contribution of both the selection pressure and nature of the acid as a driver for directing the evolutionary path towards tolerance to low pH. The choice of carbon source was also an important factor in the evolutionary process since cells evolved on two different carbon sources (raffinose and glucose) generated a different set of mutations in response to the presence of lactic acid. Therefore, different strategies are required for a rational design of low pH tolerant strains depending on the acid of interest.
Bioinformatics Support for Computational Resources [Service]
NGI Stockholm (Genomics Applications) [Service]
NGI Stockholm (Genomics Production) [Service]
NGI Uppsala (Uppsala Genome Center) [Service]
National Genomics Infrastructure [Service]
PubMed 27815194
DOI 10.1016/j.ymben.2016.10.010
Crossref 10.1016/j.ymben.2016.10.010
pii: S1096-7176(16)30175-6