Different Levels of Catabolite Repression Optimize Growth in Stable and Variable Environments

New, Aaron M.; Cerulus, Bram; Govers, Sander K.; Perez-Samper, Gemma; Zhu, Bo; Boogmans, Sarah; Xavier, João B.; Verstrepen, Kevin J.

doi:10.1371/journal.pbio.1001764

Cited by 187 publications

(276 citation statements)

References 73 publications

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“…Further, despite our increasing level of knowledge about the effect of feedback regulation 4,9,25,26 on gene network activity in single species and the effect of carbon metabolism gene regulation on fitness 27 , a systematic experimental and quantitative study characterizing the role of feedback-mediating promoters on the evolved activity of modular gene networks has been missing. At the cross section 28 of evolutionary biology and systems biology, our work provides an example to how gene network evolution could occur through tuning the strength of negative-feedback regulation.…”

Section: Discussionmentioning

confidence: 99%

Evolution of gene network activity by tuning the strength of negative-feedback regulation

et al. 2015

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Despite the examples of protein evolution via mutations in coding sequences, we have very limited understanding on gene network evolution via changes in cis-regulatory elements. Using the galactose network as a model, here we show how the regulatory promoters of the network contribute to the evolved network activity between two yeast species. In Saccharomyces cerevisiae, we combinatorially replace all regulatory network promoters by their counterparts from Saccharomyces paradoxus, measure the resulting network inducibility profiles, and model the results. Lowering relative strength of GAL80-mediated negative feedback by replacing GAL80 promoter is necessary and sufficient to have high network inducibility levels as in S. paradoxus. This is achieved by increasing OFF-to-ON phenotypic switching rates. Competitions performed among strains with or without the GAL80 promoter replacement show strong relationships between network inducibility and fitness. Our results support the hypothesis that gene network activity can evolve by optimizing the strength of negative-feedback regulation.

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Section: Discussionmentioning

confidence: 99%

Evolution of gene network activity by tuning the strength of negative-feedback regulation

et al. 2015

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“…After 45 batches of subculturing, 82.28% xylose could be utilized in 24 h of initial sugar provided, i.e., 20 g l −1 and produced 5.8 g l −1 cell biomass as compared to 17.43% for native strain under same conditions. Furthermore, the improvement in xylose utilization was slow, which might be due to reprogramming of internal metabolic pathway through increased xylose utilization (New et al, 2014). Furthermore, subculturing was continued up to 60 batches to check the further improvement in xylose utilization.…”

Section: Adaptation Of K Marxianus Nire-k3mentioning

confidence: 99%

Evolutionary Adaptation of Kluyveromyces marxianus NIRE-K3 for Enhanced Xylose Utilization

et al. 2017

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The evolutionary adaptation was approached on the thermotolerant yeast Kluyveromyces marxianus NIRE-K3 at 45°C on xylose as a sole source of carbon for enhancement of xylose uptake. After 60 cycles, evolved strain K. marxianus NIRE-K3.1 showed comparatively 3.75-and 3.0-fold higher specific growth and xylose uptake rates, respectively, than that of native strain. Moreover, the short lag phase was also observed on adapted strain. During batch fermentation with xylose concentration of 30 g l −1, K. marxianus NIRE-K3.1 could utilize about 96% of xylose in 72 h and produced 4.67 and 15.7 g l −1 of ethanol and xylitol, respectively, which were 9.72-and 4.63-fold higher than that of native strain. Similarly, specific sugar consumption rate, xylitol, and ethanol yields were 5.07-, 1.15-, and 2.44-fold higher as compared to the native strain, respectively. The results obtained after evolutionary adaptation of K. marxianus NIRE-K3 show the significant improvement in the xylose utilization, ethanol and xylitol yields, and productivities. By understanding the results obtained, the significance of evolutionary adaptation has been rationalized, since the adapted culture could be more stable and could enhance the productivity.

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“…Experimental evolution experiments (New et al, 2014) demonstrate that there is an optimal duration. The optimum depends on the environmental conditions, in particular the frequency with which carbon sources change.…”

Section: Introductionmentioning

confidence: 94%

“…Diauxic growth and the network that controls it has since been subject to intense experimental (Stülke and Hillen, 1999;Brückner and Titgemeyer, 2002;Boulineau et al, 2013;Boianelli et al, 2012;Inada et al, 1996;Kompala et al, 1986;New et al, 2014) and theoretical (Boianelli et al, 2012;Narang, 2006;Narang and Pilyugin, 2007;Kremling et al, 2009) investigation. There are two main mechanisms responsible for two phase growth in bacteria, both of which depend on the phosphotransferase (PTS) system (Deutscher, 2008): (i Regulation of metabolic genes via global transcription regulators, especially cAMP.…”

Section: Introductionmentioning

confidence: 99%

“…An implication of this is that the episodic fitness cost of the lag-phase is balanced by some long-term benefit. The experiments described in (New et al, 2014) suggest that the evolution of the lag-phase is driven by a general trade-off between the ability of the cell to switch rapidly between metabolic states and maximum steady-state growth rates on a particular nutrient. Such a trade-off between the ability to grow fast and adapt well is known empirically (Kotte et al, 2014), but its ultimate mechanistic origin remains unclear.…”

Section: Introductionmentioning

confidence: 99%

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Limited by sensing - A minimal stochastic model of the lag-phase during diauxic growth

Chu

2017

Journal of Theoretical Biology

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Many microbes when grown on a mixture of two carbon sources utilise first and exclusively the preferred sugar, before switching to the less preferred carbon source. This results in two distinct exponential growth phases, often interrupted by a lag-phase of reduced growth termed the lag-phase. While the lag-phase appears to be an evolved feature, it is not clear what drives its evolution, as it comes with a substantial up-front fitness penalty due to lost growth. In this article a minimal mathematical model based on a master-equation approach is proposed. This model can explain many empirically observed phenomena. It suggests that the lag-phase can be understood as a manifestation of the trade-off between switching speed and switching efficiency. Moreover, the model predicts heterogeneity of the population during the lag-phase. Finally, it is shown that the switch from one carbon source to another one is a sensing problem and the lag-phase is a manifestation of known fundamental limitations of biological sensors.

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Different Levels of Catabolite Repression Optimize Growth in Stable and Variable Environments

Abstract: This study uses experimentally evolved brewer's yeasts to explore the costs and benefits of different nutrient-switching strategies when energy sources vary or remain constant.

Cited by 187 publications

References 73 publications

Evolution of gene network activity by tuning the strength of negative-feedback regulation

Evolution of gene network activity by tuning the strength of negative-feedback regulation

Evolutionary Adaptation of Kluyveromyces marxianus NIRE-K3 for Enhanced Xylose Utilization

Limited by sensing - A minimal stochastic model of the lag-phase during diauxic growth

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