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Unravelling Evolutionary Strategies of Yeast for Improving Galactose Utilization Through Integrated Systems Level Analysis

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Unravelling Evolutionary Strategies of Yeast for Improving Galactose Utilization Through Integrated Systems Level Analysis Unravelling evolutionary strategies of yeast for improving galactose utilization through integrated systems level analysis Kuk-Ki Honga,b, Wanwipa Vongsangnaka,1, Goutham N. Vemuria, and Jens Nielsena,c,2 aDepartment of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden; bCJ Research Institute of Biotechnology, CJ CheilJedang, Seoul 157-724, Korea; and cNovo Nordisk Centre for Biosustainability, Technical University of Denmark, DK2800 Lyngby, Denmark Edited by Arnold L. Demain, Drew University, Madison, NJ, and approved June 8, 2011 (received for review February 28, 2011) Identification of the underlying molecular mechanisms for a de- There is extensive knowledge on the regulation of the Leloir rived phenotype by adaptive evolution is difficult. Here, we pathway in S. cerevisiae, the catabolic route for galactose metab- performed a systems-level inquiry into the metabolic changes oc- olism, because this regulon has served as a paradigm for un- curring in the yeast Saccharomyces cerevisiae as a result of its ad- derstanding eukaryotic transcription principles (9). Consequently, aptive evolution to increase its specific growth rate on galactose much information on the regulation and structure of the compo- and related these changes to the acquired phenotypic properties. nents involved in galactose metabolism has accumulated. There is Three evolved mutants (62A, 62B, and 62C) with higher specific also a vast amount of high throughput data available that eluci- growth rates and faster specific galactose uptake were isolated. dates galactose metabolism (10). Exploiting this abundant in- formation, many elegant metabolic engineering approaches have The evolved mutants were compared with a reference strain and been implemented to increase the galactose uptake rate by mod- two engineered strains, SO16 and PGM2, which also showed fi fi i cation of transporters, regulators, metabolic genes, or a combi- higher galactose uptake rate in previous studies. The pro le of nation of them (11, 12). Based on analysis of these and other intermediates in galactose metabolism was similar in evolved strains, it has been found that accumulation of metabolic inter- and engineered mutants, whereas reserve carbohydrates metabo- mediates in the galactose metabolism, such as galactose-1- lism was specifically elevated in the evolved mutants and one phosphate and glucose-1-phosphate, may inhibit the flux through evolved strain showed changes in ergosterol biosynthesis. Muta- the Leloir pathway and, hence, lead to a lower galactose uptake tions were identified in proteins involved in the global carbon rate (10). Therefore, successful strain development was performed sensing Ras/PKA pathway, which is known to regulate the reserve by balanced expression of structural genes through modification of carbohydrates metabolism. We evaluated one of the identified the regulatory system (12) or through overexpression of the final Tyr112 mutations, RAS2 , and this mutation resulted in an increased enzyme of galactose metabolism, PGM2, which converts glucose-1- specific growth rate on galactose. These results show that adap- phosphate to glucose-6-phospate (11). Both these engineered cells tive evolution results in the utilization of unpredicted routes to had lower concentrations of the intermediates and a higher ga- accommodate increased galactose flux in contrast to rationally lactose uptake rate (8). Despite these successes on improving ga- engineered strains. Our study demonstrates that adaptive evolu- lactose uptake in yeast through metabolic engineering, there has tion represents a valuable alternative to rational design in bioen- so far not been any description of using an evolutionary approach gineering of improved strains and, that through systems biology, for improving galactose utilization. Adaptive evolution of bacteria has enabled increasing the it is possible to identify mutations in evolved strain that can serve fi as unforeseen metabolic engineering targets for improving micro- speci c growth rate due to mutations that were not predicted by rational engineering (5). We therefore decided to apply the bial strains for production of biofuels and chemicals. concept of adaptive evolution for the improvement of galactose utilization by yeast, with the objective to evaluate if unique nthefield of industrial biotechnology, there is a need to develop strategies for improving galactose uptake could be identified. Iefficient cell factories for the production of fuels and chemicals. Furthermore, through detailed characterization of evolved mu- Even though the concept of metabolic engineering (1) is fre- tants, we expected to expand our understanding of the galactose quently used in both academia and industry for the development metabolism in yeast. We therefore characterized adaptively of unique cell factories, evolutionary engineering methods are still evolved mutants at the systems level for gaining better un- widely performed (2). The power of adaptive evolution, some- derstanding of the molecular mechanisms that are responsible times in combination with metabolic engineering, is well illus- for acquired phenotypes. We evolved a laboratory strain of yeast trated in several recent examples (3, 4). Despite its advantages, for ≈400 generations in three different serial transfer lines and conventional random mutagenesis and screening are hampered analyzed the changes in transcriptome, metabolome, and genome fi fi by the dif culties associated with nding the underlying molecular sequence that contribute to the phenotypic changes. Here, we mechanisms for a derived phenotype and, hence, the combination present results of integrated analysis of the data from the three of adaptive evolution with more rational approaches like meta- evolved mutants compared with wild-type yeast and two engineered bolic engineering is attractive. Tools from systems biology and the ability to perform deep sequencing of several strains have offered new opportunities for establishing links between genotype and phenotype and, hereby, allow for combinations of random and Author contributions: K.-K.H., G.N.V., and J.N. designed research; K.-K.H. performed re- search; K.-K.H. contributed new reagents/analytic tools; K.-K.H., W.V., G.N.V., and J.N. rational approaches to strain improvement (5, 6). analyzed data; and K.-K.H., G.N.V., and J.N. wrote the paper. Understanding the evolutionary strategies of a cell to metab- fl olize nonfavored carbon sources is an integral part of strain The authors declare no con ict of interest. development in cost efficient bioprocesses. Galactose is an This article is a PNAS Direct Submission. abundant sugar in nonfood crops (7), and it is therefore in- Data deposition: The data reported in this paper have been deposited in the Gene Ex- teresting to generate strains that can efficiently use galactose as pression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE27185). a carbon source. However, the yeast Saccharomyces cerevisiae, 1Present address: Center for Systems Biology, Soochow University, Suzhou 215006, China. which is a frequently used cell factory in industrial biotechnology, 2To whom correspondence should be addressed. E-mail: [email protected]. grows at half the rate on galactose compared with glucose, de- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. SYSTEMS BIOLOGY spite the structural similarity between galactose and glucose (8). 1073/pnas.1103219108/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1103219108 PNAS | July 19, 2011 | vol. 108 | no. 29 | 12179–12184 Downloaded by guest on September 28, 2021 strains that were developed by the rational approach in previous several engineered strains were lying on a linear regression curve studies (11, 12). Based on our analysis of the evolved strains, when their specific ethanol production rate was plotted against unique strategies for improving galactose uptake were identified, the specific galactose uptake rate (12). This experience led us to and one of these strategies was proven to result in an improved plot data from all of the strains in a similar kind of plot, but we galactose uptake. Furthermore, our analysis highlights that it is only found there to be a grouping pattern that clearly separated all by an integrated systems biology approach that it is possible to map of the strains into two groups (Fig. 1B). The reference and the out the mechanisms underlying evolved phenotypes. two engineered strains were on the same regression curve (R2 = 0.99), whereas all of the evolved mutants were on a different Results regression curve (R2 = 0.98), indicating a common phenomenon Physiological Changes in Evolved Mutants. Three adaptively evolved underlying the increased galactose uptake rates. If data from all strains that had 24% faster specific growth rates on galactose of the strains are included in the same linear regression, a rather fi 2 were obtained through 62-d serial transfers of cultures to fresh poor correlation coef cient is obtained (R = 0.64). medium with galactose as the sole carbon source. The strains were isolated from the last culture and were designated 62A, Changes in the Transcriptome and the Metabolome. The evolved 62B, and 62C. The gross phenotype of the three evolved strains mutants showed clear separation from the reference and the two engineered strains in their transcriptome profile, using principal was compared with those of the reference strain (CEN.PK113- fi 7D) and two engineered strains characterized
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