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Schnitzer B, Österberg L, Skopa I, Cvijovic M. Multi-scale model suggests the trade-off between protein and ATP demand as a driver of metabolic changes during yeast replicative ageing. PLoS Comput Biol 2022; 18:e1010261. [PMID: 35797415 PMCID: PMC9295998 DOI: 10.1371/journal.pcbi.1010261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/19/2022] [Accepted: 05/31/2022] [Indexed: 11/18/2022] Open
Abstract
The accumulation of protein damage is one of the major drivers of replicative ageing, describing a cell’s reduced ability to reproduce over time even under optimal conditions. Reactive oxygen and nitrogen species are precursors of protein damage and therefore tightly linked to ageing. At the same time, they are an inevitable by-product of the cell’s metabolism. Cells are able to sense high levels of reactive oxygen and nitrogen species and can subsequently adapt their metabolism through gene regulation to slow down damage accumulation. However, the older or damaged a cell is the less flexibility it has to allocate enzymes across the metabolic network, forcing further adaptions in the metabolism. To investigate changes in the metabolism during replicative ageing, we developed an multi-scale mathematical model using budding yeast as a model organism. The model consists of three interconnected modules: a Boolean model of the signalling network, an enzyme-constrained flux balance model of the central carbon metabolism and a dynamic model of growth and protein damage accumulation with discrete cell divisions. The model can explain known features of replicative ageing, like average lifespan and increase in generation time during successive division, in yeast wildtype cells by a decreasing pool of functional enzymes and an increasing energy demand for maintenance. We further used the model to identify three consecutive metabolic phases, that a cell can undergo during its life, and their influence on the replicative potential, and proposed an intervention span for lifespan control.
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Affiliation(s)
- Barbara Schnitzer
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Linnea Österberg
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Iro Skopa
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- * E-mail:
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Persson S, Shashkova S, Österberg L, Cvijovic M. Modelling of glucose repression signalling in yeast Saccharomyces cerevisiae. FEMS Yeast Res 2022; 22:foac012. [PMID: 35238938 PMCID: PMC8916112 DOI: 10.1093/femsyr/foac012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/11/2022] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
Saccharomyces cerevisiae has a sophisticated signalling system that plays a crucial role in cellular adaptation to changing environments. The SNF1 pathway regulates energy homeostasis upon glucose derepression; hence, it plays an important role in various processes, such as metabolism, cell cycle and autophagy. To unravel its behaviour, SNF1 signalling has been extensively studied. However, the pathway components are strongly interconnected and inconstant; therefore, elucidating its dynamic behaviour based on experimental data only is challenging. To tackle this complexity, systems biology approaches have been successfully employed. This review summarizes the progress, advantages and disadvantages of the available mathematical modelling frameworks covering Boolean, dynamic kinetic, single-cell models, which have been used to study processes and phenomena ranging from crosstalks to sources of cell-to-cell variability in the context of SNF1 signalling. Based on the lessons from existing models, we further discuss how to develop a consensus dynamic mechanistic model of the entire SNF1 pathway that can provide novel insights into the dynamics of nutrient signalling.
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Affiliation(s)
- Sebastian Persson
- Department of Mathematical Sciences, Chalmers University of Technology, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
| | - Sviatlana Shashkova
- Department of Mathematical Sciences, Chalmers University of Technology, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
| | - Linnea Österberg
- Department of Mathematical Sciences, Chalmers University of Technology, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
- Department of Biology and Biological Engineering, Chalmers University of Technology, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
- Department of Mathematical Sciences, University of Gothenburg, Chalmers tvärgata 3, 412 96 Gothnburg, Sweden
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Brink DP, Borgström C, Persson VC, Ofuji Osiro K, Gorwa-Grauslund MF. D-Xylose Sensing in Saccharomyces cerevisiae: Insights from D-Glucose Signaling and Native D-Xylose Utilizers. Int J Mol Sci 2021; 22:12410. [PMID: 34830296 PMCID: PMC8625115 DOI: 10.3390/ijms222212410] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 11/17/2022] Open
Abstract
Extension of the substrate range is among one of the metabolic engineering goals for microorganisms used in biotechnological processes because it enables the use of a wide range of raw materials as substrates. One of the most prominent examples is the engineering of baker's yeast Saccharomyces cerevisiae for the utilization of d-xylose, a five-carbon sugar found in high abundance in lignocellulosic biomass and a key substrate to achieve good process economy in chemical production from renewable and non-edible plant feedstocks. Despite many excellent engineering strategies that have allowed recombinant S. cerevisiae to ferment d-xylose to ethanol at high yields, the consumption rate of d-xylose is still significantly lower than that of its preferred sugar d-glucose. In mixed d-glucose/d-xylose cultivations, d-xylose is only utilized after d-glucose depletion, which leads to prolonged process times and added costs. Due to this limitation, the response on d-xylose in the native sugar signaling pathways has emerged as a promising next-level engineering target. Here we review the current status of the knowledge of the response of S. cerevisiae signaling pathways to d-xylose. To do this, we first summarize the response of the native sensing and signaling pathways in S. cerevisiae to d-glucose (the preferred sugar of the yeast). Using the d-glucose case as a point of reference, we then proceed to discuss the known signaling response to d-xylose in S. cerevisiae and current attempts of improving the response by signaling engineering using native targets and synthetic (non-native) regulatory circuits.
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Affiliation(s)
- Daniel P. Brink
- Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; (C.B.); (V.C.P.); (K.O.O.)
| | - Celina Borgström
- Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; (C.B.); (V.C.P.); (K.O.O.)
- BioZone Centre for Applied Bioscience and Bioengineering, Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St., Toronto, ON M5S 3E5, Canada
| | - Viktor C. Persson
- Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; (C.B.); (V.C.P.); (K.O.O.)
| | - Karen Ofuji Osiro
- Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; (C.B.); (V.C.P.); (K.O.O.)
- Genetics and Biotechnology Laboratory, Embrapa Agroenergy, Brasília 70770-901, DF, Brazil
| | - Marie F. Gorwa-Grauslund
- Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; (C.B.); (V.C.P.); (K.O.O.)
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AMPK Phosphorylation Is Controlled by Glucose Transport Rate in a PKA-Independent Manner. Int J Mol Sci 2021; 22:ijms22179483. [PMID: 34502388 PMCID: PMC8431435 DOI: 10.3390/ijms22179483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 11/18/2022] Open
Abstract
To achieve growth, microbial organisms must cope with stresses and adapt to the environment, exploiting the available nutrients with the highest efficiency. In Saccharomyces cerevisiae, Ras/PKA and Snf1/AMPK pathways regulate cellular metabolism according to the supply of glucose, alternatively supporting fermentation or mitochondrial respiration. Many reports have highlighted crosstalk between these two pathways, even without providing a comprehensive mechanism of regulation. Here, we show that glucose-dependent inactivation of Snf1/AMPK is independent from the Ras/PKA pathway. Decoupling glucose uptake rate from glucose concentration, we highlight a strong coordination between glycolytic metabolism and Snf1/AMPK, with an inverse correlation between Snf1/AMPK phosphorylation state and glucose uptake rate, regardless of glucose concentration in the medium. Despite fructose-1,6-bisphosphate (F1,6BP) being proposed as a glycolytic flux sensor, we demonstrate that glucose-6-phosphate (G6P), and not F1,6BP, is involved in the control of Snf1/AMPK phosphorylation state. Altogether, this study supports a model by which Snf1/AMPK senses glucose flux independently from PKA activity, and thanks to conversion of glucose into G6P.
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Österberg L, Domenzain I, Münch J, Nielsen J, Hohmann S, Cvijovic M. A novel yeast hybrid modeling framework integrating Boolean and enzyme-constrained networks enables exploration of the interplay between signaling and metabolism. PLoS Comput Biol 2021; 17:e1008891. [PMID: 33836000 PMCID: PMC8059808 DOI: 10.1371/journal.pcbi.1008891] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 04/21/2021] [Accepted: 03/18/2021] [Indexed: 12/11/2022] Open
Abstract
The interplay between nutrient-induced signaling and metabolism plays an important role in maintaining homeostasis and its malfunction has been implicated in many different human diseases such as obesity, type 2 diabetes, cancer, and neurological disorders. Therefore, unraveling the role of nutrients as signaling molecules and metabolites together with their interconnectivity may provide a deeper understanding of how these conditions occur. Both signaling and metabolism have been extensively studied using various systems biology approaches. However, they are mainly studied individually and in addition, current models lack both the complexity of the dynamics and the effects of the crosstalk in the signaling system. To gain a better understanding of the interconnectivity between nutrient signaling and metabolism in yeast cells, we developed a hybrid model, combining a Boolean module, describing the main pathways of glucose and nitrogen signaling, and an enzyme-constrained model accounting for the central carbon metabolism of Saccharomyces cerevisiae, using a regulatory network as a link. The resulting hybrid model was able to capture a diverse utalization of isoenzymes and to our knowledge outperforms constraint-based models in the prediction of individual enzymes for both respiratory and mixed metabolism. The model showed that during fermentation, enzyme utilization has a major contribution in governing protein allocation, while in low glucose conditions robustness and control are prioritized. In addition, the model was capable of reproducing the regulatory effects that are associated with the Crabtree effect and glucose repression, as well as regulatory effects associated with lifespan increase during caloric restriction. Overall, we show that our hybrid model provides a comprehensive framework for the study of the non-trivial effects of the interplay between signaling and metabolism, suggesting connections between the Snf1 signaling pathways and processes that have been related to chronological lifespan of yeast cells.
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Affiliation(s)
- Linnea Österberg
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Iván Domenzain
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden
| | - Julia Münch
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden
- BioInnovation Institute, Copenhagen, Denmark
| | - Stefan Hohmann
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
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