| 1. |
- Cuklev, Filip, 1981, et al.
(författare)
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Global hepatic gene expression in rainbow trout exposed to sewage effluents: A comparison of different sewage treatment technologies
- 2012
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 427-428, s. 106-114
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Tidskriftsartikel (refereegranskat)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, zonation (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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| 2. |
- Cvijovic, Marija, 1977, et al.
(författare)
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BioMet Toolbox: genome-wide analysis of metabolism
- 2010
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 38:SUPPL. 2, s. W144-W149
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Tidskriftsartikel (refereegranskat)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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| 3. |
- Persson, Sebastian, 1996, et al.
(författare)
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Scalable and flexible inference framework for stochastic dynamic single-cell models
- 2022
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Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358.
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Tidskriftsartikel (refereegranskat)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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| 4. |
- Ali, Qasim, 1986, et al.
(författare)
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Adaptive damage retention mechanism enables healthier yeast population
- 2019
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Ingår i: Journal of Theoretical Biology. - : Elsevier BV. - 0022-5193 .- 1095-8541. ; 473, s. 52-66
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Tidskriftsartikel (refereegranskat)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. (C) 2019 Elsevier Ltd. All rights reserved.
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| 5. |
- Almquist, Joachim, 1980, et al.
(författare)
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Kinetic models in industrial biotechnology - Improving cell factory performance
- 2014
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Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 24, s. 38-60
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Tidskriftsartikel (refereegranskat)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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| 6. |
- Bendrioua, Loubna, et al.
(författare)
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Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels
- 2014
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Ingår i: Journal of Biological Chemistry. - 0021-9258 .- 1083-351X. ; 289:18, s. 12863-12875
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Tidskriftsartikel (refereegranskat)abstract
- Background: Little is known about the signaling dynamics of AMP-activated protein kinase. Results: We define the dynamics of yeast AMPK signaling under different glucose concentrations. Conclusion: The Snf1-Mig1 signaling system monitors glucose concentration changes and absolute glucose levels to adjust the metabolism to a wide range of conditions. Significance: This description of AMPK signaling dynamics will stimulate studies defining the integration of signaling and metabolism. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
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| 7. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability
- 2021
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Ingår i: Npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- The GTPase Cdc42 is the master regulator of eukaryotic cell polarisation. During this process, the active form of Cdc42 is accumulated at a particular site on the cell membrane called the pole. It is believed that the accumulation of the active Cdc42 resulting in a pole is driven by a combination of activation-inactivation reactions and diffusion. It has been proposed using mathematical modelling that this is the result of diffusion-driven instability, originally proposed by Alan Turing. In this study, we developed, analysed and validated a 3D bulk-surface model of the dynamics of Cdc42. We show that the model can undergo both classic and non-classic Turing instability by deriving necessary conditions for which this occurs and conclude that the non-classic case can be viewed as a limit case of the classic case of diffusion-driven instability. Using three-dimensional Spatio-temporal simulation we predicted pole size and time to polarisation, suggesting that cell polarisation is mainly driven by the reaction strength parameter and that the size of the pole is determined by the relative diffusion.
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| 8. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Synergistic effects of repair, resilience and retention of damage determine the conditions for replicative ageing
- 2020
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Accumulation of damaged proteins is a hallmark of ageing, occurring in organisms ranging from bacteria and yeast to mammalian cells. During cell division in Saccharomyces cerevisiae, damaged proteins are retained within the mother cell, resulting in an ageing mother while a new daughter cell exhibits full replicative potential. The cell-specific features determining the ageing remain elusive. It has been suggested that the replicative ageing is dependent on the ability of the cell to repair and retain pre-existing damage. To deepen the understanding of how these factors influence the life of individual cells, we developed and experimentally validated a dynamic model of damage accumulation accounting for replicative ageing on the single cell level. The model includes five essential properties: cell growth, damage formation, damage repair, cell division and cell death, represented in a theoretical framework describing the conditions allowing for replicative ageing, starvation, immortality or clonal senescence. We introduce the resilience to damage, which can be interpreted as the difference in volume between an old and a young cell. We show that the capacity to retain damage deteriorates with high age, that asymmetric division allows for retention of damage, and that there is a trade-off between retention and the resilience property. Finally, we derive the maximal degree of asymmetry as a function of resilience, proposing that asymmetric cell division is beneficial with respect to replicative ageing as it increases the lifespan of a given organism. The proposed model contributes to a deeper understanding of the ageing process in eukaryotic organisms.
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| 9. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Systems Biology of Aging
- 2017
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Ingår i: Systems Biology, VI. Jens Nielsen Stefan Hohmann (red.). - Weinheim, Germany : Wiley‐VCH. - 1939-5094 .- 1939-005X. - 9783527335589 ; , s. 243-264
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Bokkapitel (refereegranskat)
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| 10. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Systems biology of aging
- 2017
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Ingår i: Systems Biology. - 9783527696178 ; , s. 262-283
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Mathematical modeling has emerged as a powerful descriptive and predictive tool to analyze complex biological systems. It is deeply embedded in the systems biology cycle, providing the means to deliver predictive quantitative models. Aging is a highly complex, irreversible process that arises from interactions of many different components. It is characterized by the accumulation of harmful molecules that damage the cell over the course of time coupled with progressive functional decline, inevitably culminating in death. This underpins the universal hallmark of aging - the accumulation and segregation of aging factors. Integrating mathematical modeling and experimental work may prove to be a powerful way to address certain evolutionary questions that might have profound implications for the whole study of aging.This systems biology approach may reveal the underlying mechanisms that cause the functions of the cell to deteriorate over the course of time and predict optimal division strategies that will lead to increased fitness and prolonged lifespan. In this chapter, we provide an overview of the biology of the aging process including several aging theories and the current state of mathematical models in aging research, together with a case study illustrating damage accumulation theory.
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