1
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Braam S, Tripodi F, Österberg L, Persson S, Welkenhuysen N, Coccetti P, Cvijovic M. Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based approaches. Microb Cell 2024; 11:143-154. [PMID: 38756204 PMCID: PMC11097897 DOI: 10.15698/mic2024.05.822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 03/05/2024] [Accepted: 03/12/2024] [Indexed: 05/18/2024]
Abstract
The AMPK/SNF1 pathway governs energy balance in eukaryotic cells, notably influencing glucose de-repression. In S. cerevisiae, Snf1 is phosphorylated and hence activated upon glucose depletion. This activation is required but is not sufficient for mediating glucose de-repression, indicating further glucose-dependent regulation mechanisms. Employing fluorescence recovery after photobleaching (FRAP) in conjunction with non-linear mixed effects modelling, we explore the spatial dynamics of Snf1 as well as the relationship between Snf1 phosphorylation and its target Mig1 controlled by hexose sugars. Our results suggest that inactivation of Snf1 modulates Mig1 localization and that the kinetic of Snf1 localization to the nucleus is modulated by the presence of non-fermentable carbon sources. Our data offer insight into the true complexity of regulation of this central signaling pathway in orchestrating cellular responses to fluctuating environmental cues. These insights not only expand our understanding of glucose homeostasis but also pave the way for further studies evaluating the importance of Snf1 localization in relation to its phosphorylation state and regulation of downstream targets.
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Affiliation(s)
- Svenja Braam
- Department of Mathematical Sciences, Chalmers University of Technology, University of GothenburgSweden.
| | - Farida Tripodi
- Department of Biotechnology and Biosciences, University of MilanoBicoccaItaly.
| | - Linnea Österberg
- Department of Mathematical Sciences, Chalmers University of Technology, University of GothenburgSweden.
- Department of Biology and Biological Engineering, Department of Mathematical Sciences, Chalmers University of TechnologySweden.
- Department of Biotechnology and Biosciences, Chalmers University of Technology, University of GothenburgGothenburg, SE412 96Sweden.
- University of MilanoBicoccaMilano, 20126Italy.
| | - Sebastian Persson
- Department of Mathematical Sciences, Chalmers University of Technology, University of GothenburgSweden.
| | - Niek Welkenhuysen
- Department of Mathematical Sciences, Chalmers University of Technology, University of GothenburgSweden.
- Department of Biology and Biological Engineering, Department of Mathematical Sciences, Chalmers University of TechnologySweden.
- Department of Biotechnology and Biosciences, Chalmers University of Technology, University of GothenburgGothenburg, SE412 96Sweden.
- University of MilanoBicoccaMilano, 20126Italy.
| | - Paola Coccetti
- Department of Biotechnology and Biosciences, University of MilanoBicoccaItaly.
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology, University of GothenburgSweden.
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2
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Cvijovic M, Polster A. Network medicine: facilitating a new view on complex diseases. Front Bioinform 2023; 3:1163445. [PMID: 37293293 PMCID: PMC10244535 DOI: 10.3389/fbinf.2023.1163445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/15/2023] [Indexed: 06/10/2023] Open
Abstract
Complex diseases are prevalent medical conditions which are characterized by inter-patient heterogeneity with regards to symptom profiles, disease trajectory, comorbidities, and treatment response. Their pathophysiology involves a combination of genetic, environmental, and psychosocial factors. The intricacies of complex diseases, encompassing different levels of biological organization in the context of environmental and psychosocial factors, makes them difficult to study, understand, prevent, and treat. The field of network medicine has progressed our understanding of these complex mechanisms and highlighted mechanistic overlap between diagnoses as well as patterns of symptom co-occurrence. These observations call into question the traditional conception of complex diseases, where diagnoses are treated as distinct entities, and prompts us to reconceptualize our nosological models. Thus, this manuscript presents a novel model, in which the individual disease burden is determined as a function of molecular, physiological, and pathological factors simultaneously, and represented as a state vector. In this conceptualization the focus shifts from identifying the underlying pathophysiology of diagnosis cohorts towards identifying symptom-determining traits in individual patients. This conceptualization facilitates a multidimensional approach to understanding human physiology and pathophysiology in the context of complex diseases. This may provide a useful concept to address both the significant interindividual heterogeneity of diagnose cohorts as well as the lack of clear distinction between diagnoses, health, and disease, thus facilitating the progression towards personalized medicine.
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Affiliation(s)
- Marija Cvijovic
- Department of Applied Mathematics and Statistics, University of Gothenburg, Gothenburg, Sweden
| | - Annikka Polster
- Division of Systems and Synthetic Biology, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
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3
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Larsson J, Hoppe E, Gautrois M, Cvijovic M, Jirstrand M. Optimizing study design in LPS challenge studies for quantifying drug induced inhibition of TNFα response: Did we miss the prime time? Eur J Pharm Sci 2022; 176:106256. [PMID: 35820630 DOI: 10.1016/j.ejps.2022.106256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/30/2022] [Accepted: 07/07/2022] [Indexed: 11/03/2022]
Abstract
In this work we evaluate the study design of LPS challenge experiments used for quantification of drug induced inhibition of TNFα response and provide general guidelines of how to improve the study design. Analysis of model simulated data, using a recently published TNFα turnover model, as well as the optimal design tool PopED have been used to find the optimal values of three key study design variables - time delay between drug and LPS administration, LPS dose, and sampling time points - that in turn could make the resulting TNFα response data more informative. Our findings suggest that the current rule of thumb for choosing the time delay should be reconsidered, and that the placement of the measurements after maximal TNFα response are crucial for the quality of the experiment. Furthermore, a literature study summarizing a wide range of published LPS challenge studies is provided, giving a broader perspective of how LPS challenge studies are usually conducted both in a preclinical and clinical setting.
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Affiliation(s)
- Julia Larsson
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg 412 88, Sweden; Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg 412 96, Sweden.
| | | | | | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg 412 96, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg 412 88, Sweden
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4
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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5
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Persson S, Welkenhuysen N, Shashkova S, Wiqvist S, Reith P, Schmidt GW, Picchini U, Cvijovic M. Scalable and flexible inference framework for stochastic dynamic single-cell models. PLoS Comput Biol 2022; 18:e1010082. [PMID: 35588132 PMCID: PMC9159578 DOI: 10.1371/journal.pcbi.1010082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 06/01/2022] [Accepted: 04/05/2022] [Indexed: 01/22/2023] Open
Abstract
Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population. However, extracting mechanistic information from single-cell data has proven difficult. This requires statistical methods to infer unknown model parameters from dynamic, multi-individual data accounting for heterogeneity caused by both intrinsic (e.g. variations in chemical reactions) and extrinsic (e.g. variability in protein concentrations) noise. Although several inference methods exist, the availability of efficient, general and accessible methods that facilitate modelling of single-cell data, remains lacking. Here we present a scalable and flexible framework for Bayesian inference in state-space mixed-effects single-cell models with stochastic dynamic. Our approach infers model parameters when intrinsic noise is modelled by either exact or approximate stochastic simulators, and when extrinsic noise is modelled by either time-varying, or time-constant parameters that vary between cells. We demonstrate the relevance of our approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. We identify hexokinase activity as a source of extrinsic noise and deduce that sugar availability dictates cell-to-cell variability.
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Affiliation(s)
- Sebastian Persson
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Niek Welkenhuysen
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Sviatlana Shashkova
- Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Samuel Wiqvist
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Patrick Reith
- 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
| | - Gregor W. Schmidt
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Umberto Picchini
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, 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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6
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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7
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Schnitzer B, Welkenhuysen N, Leake MC, Shashkova S, Cvijovic M. The effect of stress on biophysical characteristics of misfolded protein aggregates in living Saccharomyces cerevisiae cells. Exp Gerontol 2022; 162:111755. [PMID: 35240259 DOI: 10.1016/j.exger.2022.111755] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 02/11/2022] [Accepted: 02/24/2022] [Indexed: 11/28/2022]
Abstract
Aggregation of misfolded or damaged proteins is often attributed to numerous metabolic and neurodegenerative disorders. To reveal underlying mechanisms and cellular responses, it is crucial to investigate protein aggregate dynamics in cells. Here, we used super-resolution single-molecule microscopy to obtain biophysical characteristics of individual aggregates of a model misfolded protein ∆ssCPY* labelled with GFP. We demonstrated that oxidative and hyperosmotic stress lead to increased aggregate stoichiometries but not necessarily the total number of aggregates. Moreover, our data suggest the importance of the thioredoxin peroxidase Tsa1 for the controlled sequestering and clearance of aggregates upon both conditions. Our work provides novel insights into the understanding of the cellular response to stress via revealing the dynamical properties of stress-induced protein aggregates.
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Affiliation(s)
- Barbara Schnitzer
- Department of Mathematical Sciences, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Mathematical Sciences, University of Gothenburg, 412 96 Gothenburg, Sweden
| | - Niek Welkenhuysen
- Department of Mathematical Sciences, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Mathematical Sciences, University of Gothenburg, 412 96 Gothenburg, Sweden
| | - Mark C Leake
- Department of Physics, University of York, YO10 5DD York, UK; Department of Biology, University of York, YO10 5DD York, UK
| | - Sviatlana Shashkova
- Department of Mathematical Sciences, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Mathematical Sciences, University of Gothenburg, 412 96 Gothenburg, Sweden; Department of Physics, University of York, YO10 5DD York, UK.
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Mathematical Sciences, University of Gothenburg, 412 96 Gothenburg, Sweden.
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8
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Larsson J, Hoppe E, Gautrois M, Cvijovic M, Jirstrand M. Second-generation TNFα turnover model for improved analysis of test compound interventions in LPS challenge studies. Eur J Pharm Sci 2021; 165:105937. [PMID: 34260892 DOI: 10.1016/j.ejps.2021.105937] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 05/31/2021] [Accepted: 07/04/2021] [Indexed: 11/30/2022]
Abstract
This study presents a non-linear mixed effects model describing tumour necrosis factor alpha (TNFα) release after lipopolysaccharide (LPS) provocations in absence or presence of anti-inflammatory test compounds. Inter-occasion variability and the pharmacokinetics of two test compounds have been added to this second-generation model, and the goal is to produce a framework of how to model TNFα response in LPS challenge studies in vivo and demonstrate its general applicability regardless of occasion or type of test compound. Model improvements based on experimental data were successfully implemented and provided a robust model for TNFα response after LPS provocation, as well as reliable estimates of the median pharmacodynamic parameters. The two test compounds, Test Compound A and roflumilast, showed 81.1% and 74.9% partial reduction of TNFα response, respectively, and the potency of Test Compound A was estimated to 0.166 µmol/L. Comparing this study with previously published work reveals that our model leads to biologically reasonable output, handles complex data pooled from different studies, and highlights the importance of accurately distinguishing the stimulatory effect of LPS from the inhibitory effect of the test compound.
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Affiliation(s)
- Julia Larsson
- Fraunhofer-Chalmers Centre, Chalmers Science Park, 412 88 Gothenburg, Sweden.; Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, 412 96 Gothenburg, Sweden..
| | | | | | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, 412 96 Gothenburg, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Centre, Chalmers Science Park, 412 88 Gothenburg, Sweden
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9
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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: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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10
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Polster A, Öhman L, Tap J, Derrien M, Le Nevé B, Sundin J, Törnblom H, Cvijovic M, Simrén M. A novel stepwise integrative analysis pipeline reveals distinct microbiota-host interactions and link to symptoms in irritable bowel syndrome. Sci Rep 2021; 11:5521. [PMID: 33750831 PMCID: PMC7943560 DOI: 10.1038/s41598-021-84686-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 02/15/2021] [Indexed: 12/15/2022] Open
Abstract
Although incompletely understood, microbiota-host interactions are assumed to be altered in irritable bowel syndrome (IBS). We, therefore, aimed to develop a novel analysis pipeline tailored for the integrative analysis of microbiota-host interactions and association to symptoms and prove its utility in a pilot cohort. A multilayer stepwise integrative analysis pipeline was developed to visualize complex variable associations. Application of the pipeline was demonstrated on a dataset of IBS patients and healthy controls (HC), using the R software package to analyze colonic host mRNA and mucosal microbiota (16S rRNA gene sequencing), as well as gastrointestinal (GI) and psychological symptoms. In total, 42 IBS patients (57% female, mean age 33.6 (range 18–58)) and 20 HC (60% female, mean age 26.8 (range 23–41)) were included. Only in IBS patients, mRNA expression of Toll-like receptor 4 and genes associated with barrier function (PAR2, OCLN, TJP1) intercorrelated closely, suggesting potential functional relationships. This host genes-based “permeability cluster” was associated to mucosa-adjacent Chlamydiae and Lentisphaerae, and furthermore associated to satiety as well as to anxiety, depression and fatigue. In both IBS patients and HC, chromogranins, secretogranins and TLRs clustered together. In IBS patients, this host genes-based “immune-enteroendocrine cluster” was associated to specific members of Firmicutes, and to depression and fatigue, whereas in HC no significant association to microbiota was identified. We have developed a stepwise integrative analysis pipeline that allowed identification of unique host-microbiota intercorrelation patterns and association to symptoms in IBS patients. This analysis pipeline may aid in advancing the understanding of complex variable associations in health and disease.
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Affiliation(s)
- Annikka Polster
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, 41345, Göteborg, Sweden.
| | - Lena Öhman
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, 41345, Göteborg, Sweden.,Department of Microbiology and Immunology, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
| | - Julien Tap
- Danone Nutricia Research, Palaiseau, France
| | | | | | - Johanna Sundin
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, 41345, Göteborg, Sweden.,Department of Microbiology and Immunology, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
| | - Hans Törnblom
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, 41345, Göteborg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
| | - Magnus Simrén
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, 41345, Göteborg, Sweden.,Center for Functional Gastrointestinal and Motility Disorders, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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11
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Schnitzer B, Borgqvist J, Cvijovic M. The synergy of damage repair and retention promotes rejuvenation and prolongs healthy lifespans in cell lineages. PLoS Comput Biol 2020; 16:e1008314. [PMID: 33044956 PMCID: PMC7598927 DOI: 10.1371/journal.pcbi.1008314] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 10/30/2020] [Accepted: 09/04/2020] [Indexed: 01/29/2023] Open
Abstract
Damaged proteins are inherited asymmetrically during cell division in the yeast Saccharomyces cerevisiae, such that most damage is retained within the mother cell. The consequence is an ageing mother and a rejuvenated daughter cell with full replicative potential. Daughters of old and damaged mothers are however born with increasing levels of damage resulting in lowered replicative lifespans. Remarkably, these prematurely old daughters can give rise to rejuvenated cells with low damage levels and recovered lifespans, called second-degree rejuvenation. We aimed to investigate how damage repair and retention together can promote rejuvenation and at the same time ensure low damage levels in mother cells, reflected in longer health spans. We developed a dynamic model for damage accumulation over successive divisions in individual cells as part of a dynamically growing cell lineage. With detailed knowledge about single-cell dynamics and relationships between all cells in the lineage, we can infer how individual damage repair and retention strategies affect the propagation of damage in the population. We show that damage retention lowers damage levels in the population by reducing the variability across the lineage, and results in larger population sizes. Repairing damage efficiently in early life, as opposed to investing in repair when damage has already accumulated, counteracts accelerated ageing caused by damage retention. It prolongs the health span of individual cells which are moreover less prone to stress. In combination, damage retention and early investment in repair are beneficial for healthy ageing in yeast cell populations.
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Affiliation(s)
- Barbara Schnitzer
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Johannes Borgqvist
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
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12
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Schmidt GW, Welkenhuysen N, Ye T, Cvijovic M, Hohmann S. Mig1 localization exhibits biphasic behavior which is controlled by both metabolic and regulatory roles of the sugar kinases. Mol Genet Genomics 2020; 295:1489-1500. [PMID: 32948893 PMCID: PMC7524853 DOI: 10.1007/s00438-020-01715-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 07/20/2020] [Indexed: 12/01/2022]
Abstract
Glucose, fructose and mannose are the preferred carbon/energy sources for the yeast Saccharomyces cerevisiae. Absence of preferred energy sources activates glucose derepression, which is regulated by the kinase Snf1. Snf1 phosphorylates the transcriptional repressor Mig1, which results in its exit from the nucleus and subsequent derepression of genes. In contrast, Snf1 is inactive when preferred carbon sources are available, which leads to dephosphorylation of Mig1 and its translocation to the nucleus where Mig1 acts as a transcription repressor. Here we revisit the role of the three hexose kinases, Hxk1, Hxk2 and Glk1, in glucose de/repression. We demonstrate that all three sugar kinases initially affect Mig1 nuclear localization upon addition of glucose, fructose and mannose. This initial import of Mig1 into the nucleus was temporary; for continuous nucleocytoplasmic shuttling of Mig1, Hxk2 is required in the presence of glucose and mannose and in the presence of fructose Hxk2 or Hxk1 is required. Our data suggest that Mig1 import following exposure to preferred energy sources is controlled via two different pathways, where (1) the initial import is regulated by signals derived from metabolism and (2) continuous shuttling is regulated by the Hxk2 and Hxk1 proteins. Mig1 nucleocytoplasmic shuttling appears to be important for the maintenance of the repressed state in which Hxk1/2 seems to play an essential role.
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Affiliation(s)
- Gregor W Schmidt
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Niek Welkenhuysen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden.,Department of Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, Göteborg, Sweden
| | - Tian Ye
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, Göteborg, Sweden
| | - Stefan Hohmann
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden. .,Department of Biology and Biological Engineering, Chalmers University of Technology, Göteborg, Sweden.
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13
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Persson S, Welkenhuysen N, Shashkova S, Cvijovic M. Fine-Tuning of Energy Levels Regulates SUC2 via a SNF1-Dependent Feedback Loop. Front Physiol 2020; 11:954. [PMID: 32922308 PMCID: PMC7456839 DOI: 10.3389/fphys.2020.00954] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/15/2020] [Indexed: 11/22/2022] Open
Abstract
Nutrient sensing pathways are playing an important role in cellular response to different energy levels. In budding yeast, Saccharomyces cerevisiae, the sucrose non-fermenting protein kinase complex SNF1 is a master regulator of energy homeostasis. It is affected by multiple inputs, among which energy levels is the most prominent. Cells which are exposed to a switch in carbon source availability display a change in the gene expression machinery. It has been shown that the magnitude of the change varies from cell to cell. In a glucose rich environment Snf1/Mig1 pathway represses the expression of its downstream target, such as SUC2. However, upon glucose depletion SNF1 is activated which leads to an increase in SUC2 expression. Our single cell experiments indicate that upon starvation, gene expression pattern of SUC2 shows rapid increase followed by a decrease to initial state with high cell-to-cell variability. The mechanism behind this behavior is currently unknown. In this work we study the long-term behavior of the Snf1/Mig1 pathway upon glucose starvation with a microfluidics and non-linear mixed effect modeling approach. We show a negative feedback mechanism, involving Snf1 and Reg1, which reduces SUC2 expression after the initial strong activation. Snf1 kinase activity plays a key role in this feedback mechanism. Our systems biology approach proposes a negative feedback mechanism that works through the SNF1 complex and is controlled by energy levels. We further show that Reg1 likely is involved in the negative feedback mechanism.
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Affiliation(s)
- Sebastian Persson
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.,Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Niek Welkenhuysen
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.,Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Sviatlana Shashkova
- Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 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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14
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Abstract
Understanding the complex interactions of biochemical processes underlying human disease represents the holy grail of systems biology. When processes are modelled in ordinary differential equation (ODE) fashion, the most common tool for their analysis is linear stability analysis where the long-term behaviour of the model is determined by linearizing the system around its steady states. However, this asymptotic behaviour is often insufficient for completely determining the structure of the underlying system. A complementary technique for analysing a system of ODEs is to consider the set of symmetries of its solutions. Symmetries provide a powerful concept for the development of mechanistic models by describing structures corresponding to the underlying dynamics of biological systems. To demonstrate their capability, we consider symmetries of the nonlinear Hill model describing enzymatic reaction kinetics and derive a class of symmetry transformations for each order of the model. We consider a minimal example consisting of the application of symmetry-based methods to a model selection problem, where we are able to demonstrate superior performance compared to ordinary residual-based model selection. Moreover, we demonstrate that symmetries reveal the intrinsic properties of a system of interest based on a single time series. Finally, we show and propose that symmetry-based methodology should be considered as the first step in a systematic model building and in the case when multiple time series are available it should complement the commonly used statistical methodologies.
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Affiliation(s)
- Fredrik Ohlsson
- Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, 412 96 Gothenburg, Sweden
| | - Johannes Borgqvist
- Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, 412 96 Gothenburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, 412 96 Gothenburg, Sweden
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15
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Ali Q, Dainese R, Cvijovic M. Adaptive damage retention mechanism enables healthier yeast population. J Theor Biol 2019; 473:52-66. [PMID: 30980870 DOI: 10.1016/j.jtbi.2019.04.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 03/04/2019] [Accepted: 04/08/2019] [Indexed: 11/29/2022]
Abstract
During cytokinesis in budding yeast (Saccharomyces cerevisiae) damaged proteins are distributed asymmetrically between the daughter and the mother cell. Retention of damaged proteins is a crucial mechanism ensuring a healthy daughter cell with full replicative potential and an ageing mother cell. However, the protein quality control (PQC) system is tuned for optimal reproduction success which suggests optimal health and size of the population, rather than long-term survival of the mother cell. Modelling retention of damage as an adaptable mechanism, we propose two damage retention strategies to find an optimal way of decreasing damage retention efficiency to maximize population size and minimize the damage in the individual yeast cell. A pedigree model is used to investigate the impact of small variations in the strategies over the whole population. These impacts are based on the altruistic effects of damage retention mechanism and are measured by a cost function whose minimum value provides the optimal health and size of the population. We showed that fluctuations in the cost function allow yeast cell to continuously vary its strategy, suggesting that optimal reproduction success is a local minimum of the cost function. Our results suggest that a rapid decrease in the efficiency of damage retention, at the time when the mother cell is almost exhausted, produces fewer daughters with high levels of damaged proteins. In addition, retaining more damage during the early divisions increases the number of healthy daughters in the population.
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Affiliation(s)
- Qasim Ali
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Chalmers tvärgata 3, SE-41296 Gothenburg, Sweden; Department of Mathematics, North Carolina State University, NC 27607, USA
| | - Riccardo Dainese
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Chalmers tvärgata 3, SE-41296 Gothenburg, Sweden; Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Chalmers tvärgata 3, SE-41296 Gothenburg, Sweden.
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16
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Ognissanti D, Bjurman C, Holzmann MJ, Theodorsson E, Petzold M, Cvijovic M, Hammarsten O. Cardiac troponin T concentrations and patient-specific risk of myocardial infarction using the novel PALfx parameter. Clin Biochem 2019; 66:21-28. [DOI: 10.1016/j.clinbiochem.2019.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 01/23/2019] [Accepted: 02/03/2019] [Indexed: 11/16/2022]
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17
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Held F, Hoppe E, Cvijovic M, Jirstrand M, Gabrielsson J. Challenge model of TNF α turnover at varying LPS and drug provocations. J Pharmacokinet Pharmacodyn 2019; 46:223-240. [PMID: 30778719 PMCID: PMC6529397 DOI: 10.1007/s10928-019-09622-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/08/2019] [Indexed: 11/28/2022]
Abstract
A mechanism-based biomarker model of TNFα-response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as kt, kout), challenge characteristics (such as ks, kLPS, Km, LPS, Smax, SC50) and test-compound-related parameters (Imax, IC50). The exposure to test compound was modelled by means of first-order input and Michaelis–Menten type of nonlinear elimination. Test compound potency was estimated to 20 nM with a 70% partial reduction in TNFα-response at the highest dose of 30 mg·kg−1. Future selection of drug candidates may focus the estimation on potency and efficacy by applying the selected structure consisting of TNFα system and LPS challenge characteristics. A related aim was to demonstrate how an exploratory (graphical) analysis may guide us to a tentative model structure, which enables us to better understand target biology. The analysis demonstrated how to tackle a biomarker with a baseline below the limit of detection. Repeated LPS-challenges may also reveal how the rate and extent of replenishment of TNFα pools occur. Lack of LPS exposure-time courses was solved by including a biophase model, with the underlying assumption that TNFα-response time courses, as such, contain kinetic information. A transduction type of model with non-linear stimulation of TNFα release was finally selected. Typical features of a challenge experiment were shown by means of model simulations. Experimental shortcomings of present and published designs are identified and discussed. The final model coupled to suggested guidance rules may serve as a general basis for the collection and analysis of pharmacological challenge data of future studies.
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Affiliation(s)
- Felix Held
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg, Sweden. .,Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
| | | | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg, Sweden
| | - Johan Gabrielsson
- Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Box 7028, 75007, Uppsala, Sweden
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18
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Held F, Ekstrand C, Cvijovic M, Gabrielsson J, Jirstrand M. Modelling of oscillatory cortisol response in horses using a Bayesian population approach for evaluation of dexamethasone suppression test protocols. J Pharmacokinet Pharmacodyn 2019; 46:75-87. [PMID: 30673914 PMCID: PMC6394511 DOI: 10.1007/s10928-018-09617-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 12/31/2018] [Indexed: 11/12/2022]
Abstract
Cortisol is a steroid hormone relevant to immune function in horses and other species and shows a circadian rhythm. The glucocorticoid dexamethasone suppresses cortisol in horses. Pituitary pars intermedia dysfunction (PPID) is a disease in which the cortisol suppression mechanism through dexamethasone is challenged. Overnight dexamethasone suppression test (DST) protocols are used to test the functioning of this mechanism and to establish a diagnosis for PPID. However, existing DST protocols have been recognized to perform poorly in previous experimental studies, often indicating presence of PPID in healthy horses. This study uses a pharmacokinetic/pharmacodynamic (PK/PD) modelling approach to analyse the oscillatory cortisol response and its interaction with dexamethasone. Two existing DST protocols were then scrutinized using model simulations with particular focus on their ability to avoid false positive outcomes. Using a Bayesian population approach allowed for quantification of uncertainty and enabled predictions for a broader population of horses than the underlying sample. Dose selection and sampling time point were both determined to have large influence on the number of false positives. Advice on pitfalls in test protocols and directions for possible improvement of DST protocols were given. The presented methodology is also easily extended to other clinical test protocols.
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Affiliation(s)
- Felix Held
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg, Sweden.
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
| | - Carl Ekstrand
- Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Johan Gabrielsson
- Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Centre, Chalmers Science Park, Gothenburg, Sweden
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19
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Welkenhuysen N, Schnitzer B, Österberg L, Cvijovic M. Robustness of Nutrient Signaling Is Maintained by Interconnectivity Between Signal Transduction Pathways. Front Physiol 2019; 9:1964. [PMID: 30719010 PMCID: PMC6348271 DOI: 10.3389/fphys.2018.01964] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 12/31/2018] [Indexed: 12/16/2022] Open
Abstract
Systems biology approaches provide means to study the interplay between biological processes leading to the mechanistic understanding of the properties of complex biological systems. Here, we developed a vector format rule-based Boolean logic model of the yeast S. cerevisiae cAMP-PKA, Snf1, and the Snf3-Rgt2 pathway to better understand the role of crosstalk on network robustness and function. We identified that phosphatases are the common unknown components of the network and that crosstalk from the cAMP-PKA pathway to other pathways plays a critical role in nutrient sensing events. The model was simulated with known crosstalk combinations and subsequent analysis led to the identification of characteristics and impact of pathway interconnections. Our results revealed that the interconnections between the Snf1 and Snf3-Rgt2 pathway led to increased robustness in these signaling pathways. Overall, our approach contributes to the understanding of the function and importance of crosstalk in nutrient signaling.
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Affiliation(s)
- Niek Welkenhuysen
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.,Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Barbara Schnitzer
- Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.,Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - 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
| | - 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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20
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Polster A, Friberg P, Gunterberg V, Öhman L, Le Nevé B, Törnblom H, Cvijovic M, Simren M. Heart rate variability characteristics of patients with irritable bowel syndrome and associations with symptoms. Neurogastroenterol Motil 2018; 30:e13320. [PMID: 29575352 DOI: 10.1111/nmo.13320] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 01/29/2018] [Indexed: 02/08/2023]
Abstract
BACKGROUND Disturbed brain-gut interactions are assumed to be of importance for symptom generation in patients with irritable bowel syndrome (IBS). The autonomic nervous system (ANS) is part of the bidirectional brain-gut communication, but previous studies in IBS show diverging results. We aimed to identify subgroups of IBS patients with distinct ANS characteristics differentiating them from healthy controls (HC), and to study associations between ANS status and symptoms. METHODS Heart rate variability (HRV) was measured in IBS patients and HC (Holter monitoring: supine and standing positions with controlled respiration and ambulatory 24-hour period). Frequency (5 minutes, supine, standing) and time domains (24 hours, day, night) were analyzed. Validated questionnaires were used to measure gastrointestinal and psychological symptoms in patients. Patients and HC were compared on a univariate and multivariate level (principal component analysis [PCA] and orthogonal partial least squares discriminatory analysis (OPLS-DA)). KEY RESULTS We analyzed 158 IBS patients (Rome III) and 39 HC. Patients differed significantly from HC in HRV parameters during daytime and in standing position. In the PCA, a majority of patients overlapped with HC, but the weighted means differed (P < .01). A subset of patients (n = 30; 19%) with an aberrant global HRV profile was identified through PCA and OPLS-DA; these patients reported more severe symptoms of frequent (P < .05) and loose stools (P = .03), as well as urgency (P = .01). CONCLUSIONS AND INFERENCES Altered ANS function was demonstrated in patients with IBS, and this might be of particular relevance for symptoms in a subset of the patients.
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Affiliation(s)
- A Polster
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska University Hospital, Göteborg, Sweden
| | - P Friberg
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy at Göteborg University, Göteborg, Sweden
| | - V Gunterberg
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska University Hospital, Göteborg, Sweden
| | - L Öhman
- Department of Microbiology and Immunology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - B Le Nevé
- Danone Nutricia Research, Palaiseau, France
| | - H Törnblom
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska University Hospital, Göteborg, Sweden
| | - M Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and Göteborg University, Göteborg, Sweden
| | - M Simren
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska University Hospital, Göteborg, Sweden.,Center for Functional Gastrointestinal and Motility Disorders, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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21
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Welkenhuysen N, Borgqvist J, Backman M, Bendrioua L, Goksör M, Adiels CB, Cvijovic M, Hohmann S. Single-cell study links metabolism with nutrient signaling and reveals sources of variability. BMC Syst Biol 2017; 11:59. [PMID: 28583118 PMCID: PMC5460408 DOI: 10.1186/s12918-017-0435-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 05/24/2017] [Indexed: 01/02/2023]
Abstract
BACKGROUND The yeast AMPK/SNF1 pathway is best known for its role in glucose de/repression. When glucose becomes limited, the Snf1 kinase is activated and phosphorylates the transcriptional repressor Mig1, which is then exported from the nucleus. The exact mechanism how the Snf1-Mig1 pathway is regulated is not entirely elucidated. RESULTS Glucose uptake through the low affinity transporter Hxt1 results in nuclear accumulation of Mig1 in response to all glucose concentrations upshift, however with increasing glucose concentration the nuclear localization of Mig1 is more intense. Strains expressing Hxt7 display a constant response to all glucose concentration upshifts. We show that differences in amount of hexose transporter molecules in the cell could cause cell-to-cell variability in the Mig1-Snf1 system. We further apply mathematical modelling to our data, both general deterministic and a nonlinear mixed effect model. Our model suggests a presently unrecognized regulatory step of the Snf1-Mig1 pathway at the level of Mig1 dephosphorylation. Model predictions point to parameters involved in the transport of Mig1 in and out of the nucleus as a majorsource of cell to cell variability. CONCLUSIONS With this modelling approach we have been able to suggest steps that contribute to the cell-to-cell variability. Our data indicate a close link between the glucose uptake rate, which determines the glycolytic rate, and the activity of the Snf1/Mig1 system. This study hence establishes a close relation between metabolism and signalling.
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Affiliation(s)
- Niek Welkenhuysen
- Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Johannes Borgqvist
- Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Mattias Backman
- Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Loubna Bendrioua
- Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Mattias Goksör
- Department of Physics, University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Caroline B Adiels
- Department of Physics, University of Gothenburg, SE-412 96, Gothenburg, Sweden
| | - Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, SE-412 96, Gothenburg, Sweden.
| | - Stefan Hohmann
- Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96, Gothenburg, Sweden. .,Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden.
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22
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Cvijovic M, Höfer T, Aćimović J, Alberghina L, Almaas E, Besozzi D, Blomberg A, Bretschneider T, Cascante M, Collin O, de Atauri P, Depner C, Dickinson R, Dobrzynski M, Fleck C, Garcia-Ojalvo J, Gonze D, Hahn J, Hess HM, Hollmann S, Krantz M, Kummer U, Lundh T, Martial G, dos Santos VM, Mauer-Oberthür A, Regierer B, Skene B, Stalidzans E, Stelling J, Teusink B, Workman CT, Hohmann S. Strategies for structuring interdisciplinary education in Systems Biology: an European perspective. NPJ Syst Biol Appl 2016; 2:16011. [PMID: 28725471 PMCID: PMC5516850 DOI: 10.1038/npjsba.2016.11] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 03/10/2016] [Accepted: 03/14/2016] [Indexed: 11/08/2022] Open
Abstract
Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor's level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master's level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master's programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student's ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development.
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Affiliation(s)
- Marija Cvijovic
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Thomas Höfer
- Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jure Aćimović
- Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Lilia Alberghina
- University of Milano-Bicocca, Department of Biotechnology and Biosciences, Milano, Italy
| | - Eivind Almaas
- Department of Biotechnology, NTNU – Norwegian University of Science and Technology, Trondheim, Norway
| | - Daniela Besozzi
- Department of Informatics, Systems and Communication, University of Milano-Bicocca and SYSBIO Centre of Systems Biology, Milano, Italy
| | - Anders Blomberg
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | | | - Marta Cascante
- Department of Biochemistry and Molecular Biology, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | | | - Pedro de Atauri
- Department of Biochemistry and Molecular Biology, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Cornelia Depner
- Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - Christian Fleck
- Laboratory for Systems and Synthetic Biology, Wageningen UR, Wageningen, Netherlands
| | - Jordi Garcia-Ojalvo
- Universitat Pompeu Fabra, Department of Experimental and Health Sciences, Barcelona, Spain
| | - Didier Gonze
- Unité de Chronobiologie Théorique, Faculté des Sciences, CP 231 and Interuniversity Institute of Bioinformatics in Brussels (IB)2, Université Libre de Bruxelles, Brussels, Belgium
| | - Jens Hahn
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | | | - Marcus Krantz
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Torbjörn Lundh
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
| | - Gifta Martial
- BioQuant Center, University of Heidelberg, Heidelberg, Germany
| | | | | | | | | | - Egils Stalidzans
- Institute of Microbiology and Biotechnology, University of Latvia, Riga, Latvia
| | | | - Bas Teusink
- Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Stefan Hohmann
- Department of Biology and Bioengineering, Chalmers University of Technology, Göteborg, Sweden
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Song J, Yang Q, Yang J, Larsson L, Hao X, Zhu X, Malmgren-Hill S, Cvijovic M, Fernandez-Rodriguez J, Grantham J, Gustafsson CM, Liu B, Nyström T. Essential genetic interactors of SIR2 required for spatial sequestration and asymmetrical inheritance of protein aggregates. PLoS Genet 2014; 10:e1004539. [PMID: 25079602 PMCID: PMC4117435 DOI: 10.1371/journal.pgen.1004539] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 06/16/2014] [Indexed: 11/19/2022] Open
Abstract
Sir2 is a central regulator of yeast aging and its deficiency increases daughter cell inheritance of stress- and aging-induced misfolded proteins deposited in aggregates and inclusion bodies. Here, by quantifying traits predicted to affect aggregate inheritance in a passive manner, we found that a passive diffusion model cannot explain Sir2-dependent failures in mother-biased segregation of either the small aggregates formed by the misfolded Huntingtin, Htt103Q, disease protein or heat-induced Hsp104-associated aggregates. Instead, we found that the genetic interaction network of SIR2 comprises specific essential genes required for mother-biased segregation including those encoding components of the actin cytoskeleton, the actin-associated myosin V motor protein Myo2, and the actin organization protein calmodulin, Cmd1. Co-staining with Hsp104-GFP demonstrated that misfolded Htt103Q is sequestered into small aggregates, akin to stress foci formed upon heat stress, that fail to coalesce into inclusion bodies. Importantly, these Htt103Q foci, as well as the ATPase-defective Hsp104Y662A-associated structures previously shown to be stable stress foci, co-localized with Cmd1 and Myo2-enriched structures and super-resolution 3-D microscopy demonstrated that they are associated with actin cables. Moreover, we found that Hsp42 is required for formation of heat-induced Hsp104Y662A foci but not Htt103Q foci suggesting that the routes employed for foci formation are not identical. In addition to genes involved in actin-dependent processes, SIR2-interactors required for asymmetrical inheritance of Htt103Q and heat-induced aggregates encode essential sec genes involved in ER-to-Golgi trafficking/ER homeostasis.
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Affiliation(s)
- Jia Song
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Qian Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Junsheng Yang
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Lisa Larsson
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Xinxin Hao
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Xuefeng Zhu
- Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Göteborg, Sweden
| | - Sandra Malmgren-Hill
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Marija Cvijovic
- Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
- Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | | | - Julie Grantham
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
| | - Claes M. Gustafsson
- Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Göteborg, Sweden
| | - Beidong Liu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
- * E-mail:
| | - Thomas Nyström
- Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden
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24
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Almquist J, Cvijovic M, Hatzimanikatis V, Nielsen J, Jirstrand M. Kinetic models in industrial biotechnology - Improving cell factory performance. Metab Eng 2014; 24:38-60. [PMID: 24747045 DOI: 10.1016/j.ymben.2014.03.007] [Citation(s) in RCA: 158] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2013] [Revised: 03/07/2014] [Accepted: 03/09/2014] [Indexed: 11/16/2022]
Abstract
An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed.
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Affiliation(s)
- Joachim Almquist
- Fraunhofer-Chalmers Centre, Chalmers Science Park, SE-412 88 Göteborg, Sweden; Systems and Synthetic Biology, Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Göteborg, Sweden.
| | - Marija Cvijovic
- Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-412 96 Göteborg, Sweden; Mathematical Sciences, University of Gothenburg, SE-412 96 Göteborg, Sweden
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne, CH 1015 Lausanne, Switzerland
| | - Jens Nielsen
- Systems and Synthetic Biology, Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Göteborg, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Centre, Chalmers Science Park, SE-412 88 Göteborg, Sweden
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25
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Cvijovic M, Almquist J, Hagmar J, Hohmann S, Kaltenbach HM, Klipp E, Krantz M, Mendes P, Nelander S, Nielsen J, Pagnani A, Przulj N, Raue A, Stelling J, Stoma S, Tobin F, Wodke JAH, Zecchina R, Jirstrand M. Bridging the gaps in systems biology. Mol Genet Genomics 2014; 289:727-34. [DOI: 10.1007/s00438-014-0843-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Accepted: 03/21/2014] [Indexed: 12/17/2022]
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26
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Bendrioua L, Smedh M, Almquist J, Cvijovic M, Jirstrand M, Goksör M, Adiels CB, Hohmann S. Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels. J Biol Chem 2014; 289:12863-75. [PMID: 24627493 DOI: 10.1074/jbc.m114.547976] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Analysis of the time-dependent behavior of a signaling system can provide insight into its dynamic properties. We employed the nucleocytoplasmic shuttling of the transcriptional repressor Mig1 as readout to characterize Snf1-Mig1 dynamics in single yeast cells. Mig1 binds to promoters of target genes and mediates glucose repression. Mig1 is predominantly located in the nucleus when glucose is abundant. Upon glucose depletion, Mig1 is phosphorylated by the yeast AMP-activated kinase Snf1 and exported into the cytoplasm. We used a three-channel microfluidic device to establish a high degree of control over the glucose concentration exposed to cells. Following regimes of glucose up- and downshifts, we observed a very rapid response reaching a new steady state within less than 1 min, different glucose threshold concentrations depending on glucose up- or downshifts, a graded profile with increased cell-to-cell variation at threshold glucose concentrations, and biphasic behavior with a transient translocation of Mig1 upon the shift from high to intermediate glucose concentrations. Fluorescence loss in photobleaching and fluorescence recovery after photobleaching data demonstrate that Mig1 shuttles constantly between the nucleus and cytoplasm, although with different rates, depending on the presence of glucose. Taken together, our data suggest that the Snf1-Mig1 system has the ability to monitor glucose concentration changes as well as absolute glucose levels. The sensitivity over a wide range of glucose levels and different glucose concentration-dependent response profiles are likely determined by the close integration of signaling with the metabolism and may provide for a highly flexible and fast adaptation to an altered nutritional status.
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Affiliation(s)
- Loubna Bendrioua
- From the Department of Chemistry and Molecular Biology, University of Gothenburg, 40530 Göteborg, Sweden
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27
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Hernebring M, Fredriksson Å, Liljevald M, Cvijovic M, Norrman K, Wiseman J, Semb H, Nyström T. Removal of damaged proteins during ES cell fate specification requires the proteasome activator PA28. Sci Rep 2013; 3:1381. [PMID: 23459332 PMCID: PMC3587881 DOI: 10.1038/srep01381] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2012] [Accepted: 02/14/2013] [Indexed: 11/09/2022] Open
Abstract
In embryonic stem cells, removal of oxidatively damaged proteins is triggered upon the first signs of cell fate specification but the underlying mechanism is not known. Here, we report that this phase of differentiation encompasses an unexpected induction of genes encoding the proteasome activator PA28αβ (11S), subunits of the immunoproteasome (20Si), and the 20Si regulator TNFα. This induction is accompanied by assembly of mature PA28-20S(i) proteasomes and elevated proteasome activity. Inhibiting accumulation of PA28α using miRNA counteracted the removal of damaged proteins demonstrating that PA28αβ has a hitherto unidentified role required for resetting the levels of protein damage at the transition from self-renewal to cell differentiation.
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Affiliation(s)
- Malin Hernebring
- Department of Chemistry and Molecular Biology, University of Gothenburg, SE-413 90 Göteborg, Sweden.
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28
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Abstract
In the past few years, programmed cell death (PCD) has become a popular research area due to its fundamental aspects and its links to human diseases. Yeast has been used as a model for studying PCD, since the discovery of morphological markers of apoptotic cell death in yeast in 1997. Increasing knowledge in identification of components and molecular pathways created a need for organization of information. To meet the demands from the research community, we have developed a curated yeast apoptosis database, yApoptosis. The database structurally collects an extensively curated set of apoptosis, PCD and related genes, their genomic information, supporting literature and relevant external links. A web interface including necessary functions is provided to access and download the data. In addition, we included several networks where the apoptosis genes or proteins are involved, and present them graphically and interactively to facilitate rapid visualization. We also promote continuous inputs and curation by experts. yApoptosis is a highly specific resource for sharing information online, which supports researches and studies in the field of yeast apoptosis and cell death. Database URL:http://www.ycelldeath.com/yapoptosis/
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Affiliation(s)
- Kwanjeera Wanichthanarak
- Department of Chemical and Biological Engineering, Chalmers University of Technology, Kemivägen 10, 41296, Gothenburg, Sweden, Department of Mathematics, Chalmers University of Technology, Chalmers tvärgata 3, 41296, Gothenburg, Sweden, Department of Mathematics, University of Gothenburg, Chalmers tvärgata 3, 41296, Gothenburg, Sweden and Fine Chemicals and Biocatalysis Research, BASF SE, GVF/D - A030, 67056 Ludwigshafen, Germany
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29
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Kazemzadeh L, Cvijovic M, Petranovic D. Boolean model of yeast apoptosis as a tool to study yeast and human apoptotic regulations. Front Physiol 2012; 3:446. [PMID: 23233838 PMCID: PMC3518040 DOI: 10.3389/fphys.2012.00446] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2012] [Accepted: 11/07/2012] [Indexed: 01/14/2023] Open
Abstract
Programmed cell death (PCD) is an essential cellular mechanism that is evolutionary conserved, mediated through various pathways and acts by integrating different stimuli. Many diseases such as neurodegenerative diseases and cancers are found to be caused by, or associated with, regulations in the cell death pathways. Yeast Saccharomyces cerevisiae, is a unicellular eukaryotic organism that shares with human cells components and pathways of the PCD and is therefore used as a model organism. Boolean modeling is becoming promising approach to capture qualitative behavior and describe essential properties of such complex networks. Here we present large literature-based and to our knowledge first Boolean model that combines pathways leading to apoptosis (a type of PCD) in yeast. Analysis of the yeast model confirmed experimental findings of anti-apoptotic role of Bir1p and pro-apoptotic role of Stm1p and revealed activation of the stress protein kinase Hog proposing the maximal level of activation upon heat stress. In addition we extended the yeast model and created an in silico humanized yeast in which human pro- and anti-apoptotic regulators Bcl-2 family and Valosin-contain protein (VCP) are included in the model. We showed that accumulation of Bax in silico humanized yeast shows apoptotic markers and that VCP is essential target of Akt Signaling. The presented Boolean model provides comprehensive description of yeast apoptosis network behavior. Extended model of humanized yeast gives new insights of how complex human disease like neurodegeneration can initially be tested.
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Affiliation(s)
- Laleh Kazemzadeh
- Department of Chemical and Biological Engineering, Chalmers University of Technology Gothenburg, Sweden ; Digital Enterprise Research Institute, National University of Ireland Galway, Ireland
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30
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Cuklev F, Fick J, Cvijovic M, Kristiansson E, Förlin L, Larsson DGJ. Does ketoprofen or diclofenac pose the lowest risk to fish? J Hazard Mater 2012; 229-230:100-6. [PMID: 22721833 DOI: 10.1016/j.jhazmat.2012.05.077] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2012] [Revised: 04/30/2012] [Accepted: 05/21/2012] [Indexed: 05/24/2023]
Abstract
Ketoprofen and diclofenac are non-steroidal anti-inflammatory drugs (NSAIDs) often used for similar indications, and both are frequently found in surface waters. Diclofenac affects organ histology and gene expression in fish at around 1 μg/L. Here, we exposed rainbow trout to ketoprofen (1, 10 and 100 μg/L) to investigate if this alternative causes less risk for pharmacological responses in fish. The bioconcentration factor from water to fish blood plasma was <0.05 (4 for diclofenac based on previous studies). Ketoprofen only reached up to 0.6 ‰ of the human therapeutic plasma concentration, thus the probability of target-related effects was estimated to be fairly low. Accordingly, a comprehensive analysis of hepatic gene expression revealed no consistent responses. In some contrast, trout exposed to undiluted, treated sewage effluents bioconcentrated ketoprofen and other NSAIDs much more efficiently, according to a meta-analysis of recent studies. Neither of the setups is however an ideal representation of the field situation. If a controlled exposure system with a single chemical in pure water is a reasonable representation of the environment, then the use of ketoprofen is likely to pose a lower risk for wild fish than diclofenac, but if bioconcentration factors from effluent-exposed fish are applied, the risks may be more similar.
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Affiliation(s)
- Filip Cuklev
- Institute for Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden.
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31
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Cuklev F, Gunnarsson L, Cvijovic M, Kristiansson E, Rutgersson C, Björlenius B, Larsson DGJ. Global hepatic gene expression in rainbow trout exposed to sewage effluents: a comparison of different sewage treatment technologies. Sci Total Environ 2012; 427-428:106-114. [PMID: 22575374 DOI: 10.1016/j.scitotenv.2012.04.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2011] [Revised: 04/04/2012] [Accepted: 04/04/2012] [Indexed: 05/31/2023]
Abstract
Effluents from sewage treatment plants contain a mixture of micropollutants with the potential of harming aquatic organisms. Thus, addition of advanced treatment techniques to complement existing conventional methods has been proposed. Some of the advanced techniques could, however, potentially produce additional compounds affecting exposed organisms by unknown modes of action. In the present study the aim was to improve our understanding of how exposure to different sewage effluents affects fish. This was achieved by explorative microarray and quantitative PCR analyses of hepatic gene expression, as well as relative organ sizes of rainbow trout exposed to different sewage effluents (conventionally treated, granular activated carbon, ozonation (5 or 15 mg/L), 5 mg/L ozone plus a moving bed biofilm reactor, or UV-light treatment in combination with hydrogen peroxide). Exposure to the conventionally treated effluent caused a significant increase in liver and heart somatic indexes, an effect removed by all other treatments. Genes connected to xenobiotic metabolism, including cytochrome p450 1A, were differentially expressed in the fish exposed to the conventionally treated effluents, though only effluent treatment with granular activated carbon or ozone at 15 mg/L completely removed this response. The mRNA expression of heat shock protein 70 kDa was induced in all three groups exposed to ozone-treated effluents, suggesting some form of added stress in these fish. The induction of estrogen-responsive genes in the fish exposed to the conventionally treated effluent was effectively reduced by all investigated advanced treatment technologies, although the moving bed biofilm reactor was least efficient. Taken together, granular activated carbon showed the highest potential of reducing responses in fish induced by exposure to sewage effluents.
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Affiliation(s)
- Filip Cuklev
- Institute of Neuroscience and Physiology, Department of Physiology, The Sahlgrenska Academy at the University of Gothenburg, Box 434, SE-405 30 Göteborg, Sweden.
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32
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Abstract
Industrial biotechnology involves the utilization of cell factories for the production of fuels and chemicals. Traditionally, the development of highly productive microbial strains has relied on random mutagenesis and screening. The development of predictive mathematical models provides a new paradigm for the rational design of cell factories. Instead of selecting among a set of strains resulting from random mutagenesis, mathematical models allow the researchers to predict in silico the outcomes of different genetic manipulations and engineer new strains by performing gene deletions or additions leading to a higher productivity of the desired chemicals. In this review we aim to summarize the main modelling approaches of biological processes and illustrate the particular applications that they have found in the field of industrial microbiology.
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Affiliation(s)
- Marija Cvijovic
- Department of Chemical and Biological Engineering, Chalmers University of Technology, Göteborg, Sweden
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33
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Cvijovic M, Olivares-Hernández R, Agren R, Dahr N, Vongsangnak W, Nookaew I, Patil KR, Nielsen J. BioMet Toolbox: genome-wide analysis of metabolism. Nucleic Acids Res 2010; 38:W144-9. [PMID: 20483918 PMCID: PMC2896146 DOI: 10.1093/nar/gkq404] [Citation(s) in RCA: 83] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The rapid progress of molecular biology tools for directed genetic modifications, accurate quantitative experimental approaches, high-throughput measurements, together with development of genome sequencing has made the foundation for a new area of metabolic engineering that is driven by metabolic models. Systematic analysis of biological processes by means of modelling and simulations has made the identification of metabolic networks and prediction of metabolic capabilities under different conditions possible. For facilitating such systemic analysis, we have developed the BioMet Toolbox, a web-based resource for stoichiometric analysis and for integration of transcriptome and interactome data, thereby exploiting the capabilities of genome-scale metabolic models. The BioMet Toolbox provides an effective user-friendly way to perform linear programming simulations towards maximized or minimized growth rates, substrate uptake rates and metabolic production rates by detecting relevant fluxes, simulate single and double gene deletions or detect metabolites around which major transcriptional changes are concentrated. These tools can be used for high-throughput in silico screening and allows fully standardized simulations. Model files for various model organisms (fungi and bacteria) are included. Overall, the BioMet Toolbox serves as a valuable resource for exploring the capabilities of these metabolic networks. BioMet Toolbox is freely available at www.sysbio.se/BioMet/.
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Affiliation(s)
- Marija Cvijovic
- Department of Chemical and Biological Engineering, Chalmers University of Technology, Göteborg, Sweden
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34
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Cvijovic M, Soueidan H, Sherman DJ, Klipp E, Nikolski M. Exploratory simulation of cell ageing using hierarchical models. Genome Inform 2008; 21:114-125. [PMID: 19425152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Thorough knowledge of the model organism S. cerevisiae has fueled efforts in developing theories of cell ageing since the 1950s. Models of these theories aim to provide insight into the general biological processes of ageing, as well as to have predictive power for guiding experimental studies such as cell rejuvenation. Current efforts in in silico modeling are frustrated by the lack of efficient simulation tools that admit precise mathematical models at both cell and population levels simultaneously. We developed a novel hierarchical simulation tool that allows dynamic creation of entities while rigorously preserving the mathematical semantics of the model. We used it to expand a single-cell model of protein damage segregation to a cell population model that explicitly tracks mother-daughter relations. Large-scale exploration of the resulting tree of simulations established that daughters of older mothers show a rejuvenation effect, consistent with experimental results. The combination of a single-cell model and a simulation platform permitting parallel composition and dynamic node creation has proved to be an efficient tool for in silico exploration of cell behavior.
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Affiliation(s)
- Marija Cvijovic
- Max-Planck Institute for Molecular Genetics, Berlin, Germany.
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35
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Abstract
Summary We have taken a first step towards learning which upstream Open Reading Frames (uORFs) regulate gene expression (i.e., which uORFs are functional) in the yeast Saccharomyces cerevisiae. We do this by integrating data from several resources and combining a bioinformatics tool, ORF Finder, with a machine learning technique, inductive logic programming (ILP). Here, we report the challenge of using ILP as part of this integrative system, in order to automatically generate a model that identifies functional uORFs. Our method makes searching for novel functional uORFs more efficient than random sampling. An attempt has been made to predict novel functional uORFs using our method. Some preliminary evidence that our model may be biologically meaningful is presented.
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Affiliation(s)
| | - Christopher H. Bryant
- 2School of Computing, The Robert Gordon University, St. Andrew Street, Aberdeen, AB25 1HG, United Kingdom of Great Britain and Northern Ireland
| | - Graham J.L. Kemp
- 3Department of Computer Science and Engineering, Chalmers University of Technology, SE-412 96, Göteborg, Sweden
| | - Marija Cvijovic
- 4Max Planck Institute for Molecular Genetics, Department Lehrach, Kinetic Modelling Group, Ihnestrasse 63-73, 14195, Germany
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