| 1. |
- Cuklev, Filip, 1981, et al.
(author)
-
Global hepatic gene expression in rainbow trout exposed to sewage effluents: A comparison of different sewage treatment technologies
- 2012
-
In: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 427-428, s. 106-114
-
Journal article (peer-reviewed)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.
(author)
-
BioMet Toolbox: genome-wide analysis of metabolism
- 2010
-
In: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 38:SUPPL. 2, s. W144-W149
-
Journal article (peer-reviewed)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.
(author)
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Scalable and flexible inference framework for stochastic dynamic single-cell models
- 2022
-
In: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 18
-
Journal article (peer-reviewed)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.
(author)
-
Adaptive damage retention mechanism enables healthier yeast population
- 2019
-
In: Journal of Theoretical Biology. - : Elsevier BV. - 0022-5193 .- 1095-8541. ; 473, s. 52-66
-
Journal article (peer-reviewed)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.
(author)
-
Kinetic models in industrial biotechnology - Improving cell factory performance
- 2014
-
In: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 24, s. 38-60
-
Journal article (peer-reviewed)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.
(author)
-
Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels
- 2014
-
In: Journal of Biological Chemistry. - 0021-9258 .- 1083-351X. ; 289:18, s. 12863-12875
-
Journal article (peer-reviewed)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.
(author)
-
Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability
- 2021
-
In: Npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 7:1
-
Journal article (peer-reviewed)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.
(author)
-
Synergistic effects of repair, resilience and retention of damage determine the conditions for replicative ageing
- 2020
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 10:1
-
Journal article (peer-reviewed)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.
(author)
-
Systems Biology of Aging
- 2017
-
In: Systems Biology, VI. Jens Nielsen Stefan Hohmann (red.). - Weinheim, Germany : Wiley‐VCH. - 1939-5094 .- 1939-005X. - 9783527335589 ; , s. 243-264
-
Book chapter (peer-reviewed)
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| 10. |
- Borgqvist, Johannes, 1990, et al.
(author)
-
Systems biology of aging
- 2017
-
In: Systems Biology. - 9783527696178 ; , s. 262-283
-
Book chapter (other academic/artistic)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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| 11. |
- Braam, Svenja, 1989, et al.
(author)
-
Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based a pproaches
- 2024
-
In: MICROBIAL CELL. - 2311-2638. ; 11:1, s. 143-154
-
Journal article (peer-reviewed)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 glucosedependent 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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| 12. |
- Cuklev, Filip, 1981, et al.
(author)
-
Does ketoprofen or diclofenac pose the lowest risk to fish?
- 2012
-
In: Journal of Hazardous Materials. - : Elsevier BV. - 0304-3894 .- 1873-3336. ; 229-230, s. 100-106
-
Journal article (peer-reviewed)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 mu g/L. Here, we exposed rainbow trout to ketoprofen (1, 10 and 100 mu g/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 parts per thousand 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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| 13. |
- Cvijovic, Marija, 1977, et al.
(author)
-
Bridging the gaps in systems biology
- 2014
-
In: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 289:5, s. 727-734
-
Journal article (peer-reviewed)abstract
- Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.
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| 14. |
- Cvijovic, Marija, 1977, et al.
(author)
-
Identification of putative regulatory upstream ORFs in the yeast genome using heuristics and evolutionary conservation
- 2007
-
In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 8
-
Journal article (peer-reviewed)abstract
- BACKGROUND: The translational efficiency of an mRNA can be modulated by upstream open reading frames (uORFs) present in certain genes. A uORF can attenuate translation of the main ORF by interfering with translational reinitiation at the main start codon. uORFs also occur by chance in the genome, in which case they do not have a regulatory role. Since the sequence determinants for functional uORFs are not understood, it is difficult to discriminate functional from spurious uORFs by sequence analysis. RESULTS: We have used comparative genomics to identify novel uORFs in yeast with a high likelihood of having a translational regulatory role. We examined uORFs, previously shown to play a role in regulation of translation in Saccharomyces cerevisiae, for evolutionary conservation within seven Saccharomyces species. Inspection of the set of conserved uORFs yielded the following three characteristics useful for discrimination of functional from spurious uORFs: a length between 4 and 6 codons, a distance from the start of the main ORF between 50 and 150 nucleotides, and finally a lack of overlap with, and clear separation from, neighbouring uORFs. These derived rules are inherently associated with uORFs with properties similar to the GCN4 locus, and may not detect most uORFs of other types. uORFs with high scores based on these rules showed a much higher evolutionary conservation than randomly selected uORFs. In a genome-wide scan in S. cerevisiae, we found 34 conserved uORFs from 32 genes that we predict to be functional; subsequent analysis showed the majority of these to be located within transcripts. A total of 252 genes were found containing conserved uORFs with properties indicative of a functional role; all but 7 are novel. Functional content analysis of this set identified an overrepresentation of genes involved in transcriptional control and development. CONCLUSION: Evolutionary conservation of uORFs in yeasts can be traced up to 100 million years of separation. The conserved uORFs have certain characteristics with respect to length, distance from each other and from the main start codon, and folding energy of the sequence. These newly found characteristics can be used to facilitate detection of other conserved uORFs.
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| 15. |
- Cvijovic, Marija, 1977, et al.
(author)
-
Mathematical models of cell factories: moving towards the core of industrial biotechnology
- 2011
-
In: Microbial Biotechnology. - : Wiley. - 1751-7907 .- 1751-7915. ; 4:5, s. 572-584
-
Journal article (peer-reviewed)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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| 16. |
- Cvijovic, Marija, 1977, et al.
(author)
-
Network medicine: facilitating a new view on complex diseases
- 2023
-
In: Frontiers in Bioinformatics. - 2673-7647. ; 3
-
Journal article (peer-reviewed)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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| 17. |
- Cvijovic, Marija, 1977, et al.
(author)
-
Strategies for structuring interdisciplinary education in systems biology: An European perspective
- 2016
-
In: npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 2
-
Journal article (peer-reviewed)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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| 18. |
- Held, Felix, et al.
(author)
-
Bayesian hierarchical model of oscillatory cortisol response during drug intervention
- 2018
-
In: 27th meeting of the Population Approach Group in Europe Montreux, Switzerland, 2018-05-29 - 2018-06-01.
-
Conference paper (other academic/artistic)abstract
- Introduction: Oscillating biomarker response-time courses challenge modelling of drug intervention. A periodically recurring pattern is typically seen for the stress hormone cortisol. This pattern can be captured by mechanism-based turnover models. However, analysing experimental data requires new mathematical techniques. Bayesian hierarchical modelling allows for full quantification of parameter uncertainty while also capturing the population aspects typical to nonlinear mixed effects modelling. Inter-occasion variability (IOV) is incorporated in addition to inter-individual variability (IIV). Objectives: - Propose a model based workflow for oscillating baseline turnover models including IIV and IOV. - Apply the workflow to cortisol- and dexamethasone time-series data obtained from horses. - An additional aim was to predict test performance of a two-sample dexamethasone suppression test-protocol (DST-protocol) [1, 2] in horses. Methods: Cortisol- and dexamethasone time courses were collected [1]. Four different doses of dexamethasone were given (no drug and 0.1, 1, 10 µg/kg bolus + 0.07, 0.7, 7 µg/kg infusion over three hours). The pharmacokinetic/pharmacodynamic model was adapted from [1]. Cortisol was described by a turnover model with oscillating turnover rate (average baseline kavg, amplitude α, phase-shift t0) and fractional turnover rate kout. Drug intervention was modelled with Hill-type suppression (maximum inhibition Imax, potency IC50, hill coefficient n). Dexamethasone exposure was described by a two-compartment model. The model was then extended to a population model by introduction of inter-individual and inter-occasion effects. The final model was inferred from data using a Bayesian framework with the Hamiltonian Monte Carlo algorithm in Stan [3]. Ordinary differential equations were solved analytically for the case of constant drug exposure. The performance of the two-sample DST-protocol was studied by calculation of the specificity of the test. Specificity was predicted by Monte Carlo simulations and compared to two previously published experimental results. Results: The proposed model described the data well. Estimated ranges for pharmacodynamic parameters were estimated as median (95% credible intervals): kavg = 12.7 (6.44, 23.5) µg L-1 h-1, α = 5.40 (1.38, 17.9) µg L-1 h-1, t0 = -3.71 (-7.54, 0.494) h, kout = 0.315 (0.221, 0.493) h-1, Imax = 0.923 (0.874, 0.965), IC50 = 0.0298 (0.00490, 0.155) µg L-1, n = 1.57 (1.03, 2.61 ). Low precision was found in the standard deviations of the random effect parameters. IIV and IOV present in the data were captured by the model. The average cortisol response level and its amplitude are suppressed with respect to magnitude and variability with increasing exposure to dexamethasone. The maximum and minimum levels of cortisol response were also suppressed by increasing exposure to dexamethasone. Mathematical expressions were derived describing cortisol oscillations with inhibition and were consistent with experimental data. Dependence of predicted specificity on drug administration time and time until measurement was observed. Different levels of variability (IIV and IOV) led to a fraction of healthy subjects with positive test results. The oscillatory behaviour of cortisol response led to an oscillatory pattern in predicted specificity. Conclusions: - New techniques were developed for graphical analysis of the oscillatory cortisol response - These were successfully applied to equine cortisol data after dexamethasone intervention - Oscillatory behaviour and level of variability had great impact on the sparse-sample DST-design
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| 19. |
- Held, Felix, et al.
(author)
-
Challenge model of TNFα turnover at varying LPS and drug provocations
- 2019
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 46:3, s. 223-240
-
Journal article (peer-reviewed)abstract
- A mechanism-based biomarker model of TNF α -response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as k t , k out ), challenge characteristics (such as k s , k LPS , K m,LPS , S max , SC 50 ) and test-compound-related parameters (I max , IC 50 ). 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 20nM with a 70% partial reduction in TNF α -response at the highest dose of 30mg·kg −1 . Future selection of drug candidates may focus the estimation on potency and efficacy by applying the selected structure consisting of TNF α 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 TNF α pools occur. Lack of LPS exposure-time courses was solved by including a biophase model, with the underlying assumption that TNF α -response time courses, as such, contain kinetic information. A transduction type of model with non-linear stimulation of TNF α 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. © 2019, The Author(s).
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| 20. |
- Held, Felix, et al.
(author)
-
Modelling of oscillatory cortisol response in horses using a Bayesian population approach for evaluation of dexamethasone suppression test protocols
- 2019
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 46:1, s. 75-87
-
Journal article (peer-reviewed)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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| 21. |
- Hernebring, Malin, 1978, et al.
(author)
-
Removal of damaged proteins during ES cell fate specification requires the proteasome activator PA28
- 2013
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 3:3, s. artikel nr 1381-
-
Journal article (peer-reviewed)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 PA28 alpha beta (11S), subunits of the immunoproteasome (20Si), and the 20Si regulator TNF alpha. This induction is accompanied by assembly of mature PA28-20S(i) proteasomes and elevated proteasome activity. Inhibiting accumulation of PA28 alpha using miRNA counteracted the removal of damaged proteins demonstrating that PA28 alpha beta 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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| 22. |
- Hohmann, Stefan, 1956, et al.
(author)
-
Focus on resolution
- 2018
-
In: Current Opinion in Systems Biology. - : Elsevier BV. - 2452-3100. ; 7
-
Journal article (other academic/artistic)
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| 23. |
- Kazemzadeh, Laleh, et al.
(author)
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Boolean model of yeast apoptosis as a tool to study yeast and human apoptotic regulations
- 2012
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In: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 3
-
Journal article (peer-reviewed)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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| 24. |
- Larsson, Julia, et al.
(author)
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Optimizing study design in LPS challenge studies for quantifying drug induced inhibition of TNF? response: Did we miss the prime time?
- 2022
-
In: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 176
-
Journal article (peer-reviewed)abstract
- In this work we evaluate the study design of LPS challenge experiments used for quantification of drug induced inhibition of TNF alpha response and provide general guidelines of how to improve the study design. Analysis of model simulated data, using a recently published TNF alpha 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 TNF alpha 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 TNF alpha 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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| 25. |
- Larsson, Julia, 1995, et al.
(author)
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Second-generation TNFα turnover model for improved analysis of test compound interventions in LPS challenge studies
- 2021
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In: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 165
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Journal article (peer-reviewed)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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| 26. |
- Ognissanti, Damiano, et al.
(author)
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Cardiac troponin T concentrations and patient-specific risk of myocardial infarction using the novel PALfx parameter
- 2019
-
In: Clinical Biochemistry. - : Elsevier BV. - 1873-2933 .- 0009-9120. ; 66, s. 21-28
-
Journal article (peer-reviewed)abstract
- Myocardial infarction (MI) is more likely if the heart damage biomarker cardiac troponin T (cTnT) is elevated in a blood sample from a patient with chest pain. There is no conventional method to estimate the risk of MI at a specific cTnT concentration. The purpose of this study was to evaluate the performance of a novel method that converts cTnT concentrations to patient-specific risks of MI. Methods: Admission cTnT measurements in 15,425 ED patients from three hospitals with a primary complaint of chest pain, with or without a clinical diagnosis of MI, were Box-Cox-transformed to normality density functions to calculate the percentage with MI among patients with a given cTnT concentration, the parametric predictive value among lookalikes (PALfx). The ability of the PALfx to generate stable risk estimates of MI was examined by bootstrapping and expressed as the coefficient of variation (CV). Results: Four age and sex-specific subgroups above or below 60 years of age with distinct cTnT distributions were identified among patients without MI. The cTnT distributions across subgroups with MI were similar, allowing us to use all admissions with MI to calculate the PALfx in the four subgroups. For instance, at a baseline cTnT concentration of 7 ng/L, a female patient < 60 years would have a 0.5% risk of MI whereas a male patient > 60 years would have a 1.9% risk of MI. To assess the stability of the PALfx method we bootstrapped smaller and smaller subsets of the 15,422 ED visits. We found that 1950 patients without MI and 50 patients with MI were sufficient to limit the variation of the PALfx with a CV of 0.8–5.4%, close to the CV using the entire dataset. The MI risk estimates were similar when data from the three hospitals were used separately to derive the PALfx equations. Conclusions: The PALfx can be used to estimate the risk of MI at patient-specific cTnT concentrations with acceptable margins of error. The patient-specific risk of disease using the PALfx could complement decision limits.
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| 27. |
- Ohlsson, Fredrik, et al.
(author)
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Symmetry structures in dynamic models of biochemical systems
- 2020
-
In: Journal of the Royal Society Interface. - : The Royal Society. - 1742-5689 .- 1742-5662. ; 17:168
-
Journal article (peer-reviewed)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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| 28. |
- Persson, Sebastian, 1996, et al.
(author)
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Fine-Tuning of Energy Levels Regulates SUC2 via a SNF1-Dependent Feedback Loop
- 2020
-
In: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 11
-
Journal article (peer-reviewed)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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| 29. |
- Persson, Sebastian, 1996, et al.
(author)
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Modelling of glucose repression signalling in yeast Saccharomyces cerevisiae
- 2022
-
In: FEMS Yeast Research. - : Oxford University Press (OUP). - 1567-1356 .- 1567-1364. ; 22:1
-
Research review (peer-reviewed)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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| 30. |
- Polster, Annikka, et al.
(author)
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A novel stepwise integrative analysis pipeline reveals distinct microbiota-host interactions and link to symptoms in irritable bowel syndrome
- 2021
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 11:1
-
Journal article (peer-reviewed)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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| 31. |
- Polster, Annikka, et al.
(author)
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Heart rate variability characteristics of patients with irritable bowel syndrome and associations with symptoms
- 2018
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In: Neurogastroenterology and Motility. - : Wiley. - 1350-1925 .- 1365-2982. ; 30:7
-
Journal article (peer-reviewed)abstract
- BackgroundDisturbed 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. MethodsHeart 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 (5minutes, supine, standing) and time domains (24hours, 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 ResultsWe 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 InferencesAltered 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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| 32. |
- Reith, Patrick Philipp, 1991, et al.
(author)
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The Effect of Lithium on the Budding Yeast Saccharomyces cerevisiae upon Stress Adaptation
- 2022
-
In: Microorganisms. - : MDPI AG. - 2076-2607. ; 10:3
-
Journal article (peer-reviewed)abstract
- Lithium salts are used in the treatment of mood disorders, cancer, and Alzheimer's disease. It has been shown to prolong life span in several phyla; however, not yet in budding yeast. In our study, we investigate the influence of lithium on yeast cells' viability by characterizing protein aggregate formation, cell volume, and molecular crowding in the context of stress adaptation. While our data suggest a concentration-dependent growth inhibition caused by LiCl, we show an extended long-term survival rate as an effect of lithium addition upon glucose deprivation. We show that caloric restriction mitigates the negative impact of LiCl on cellular survival. Therefore, we suggest that lithium could affect glucose metabolism upon caloric restriction, which could explain the extended long-term survival observed in our study. We find furthermore that lithium chloride did not affect an immediate salt-induced Hsp104-dependent aggregate formation but cellular adaptation to H2O2 and acute glucose starvation. We presume that different salt types and concentrations interfere with effective Hsp104 recruitment or its ATP-dependent disaggregase activity as a response to salt stress. This work provides novel details of Li+ effect on live eukaryotic cells which may also be applicable in further research on the treatment of cancer, Alzheimer's, or other age-related diseases in humans.
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| 33. |
- Schmidt, G. W., et al.
(author)
-
Mig1 localization exhibits biphasic behavior which is controlled by both metabolic and regulatory roles of the sugar kinases
- 2020
-
In: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 295, s. 1489-1500
-
Journal article (peer-reviewed)abstract
- Glucose, fructose and mannose are the preferred carbon/energy sources for the yeastSaccharomyces 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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| 34. |
- Schnitzer, Barbara Maria, 1992, et al.
(author)
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The effect of stress on biophysical characteristics of misfolded protein aggregates in living Saccharomyces cerevisiae cells
- 2022
-
In: Experimental Gerontology. - : Elsevier BV. - 1873-6815 .- 0531-5565. ; 162
-
Research review (peer-reviewed)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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| 35. |
- Schnitzer, Barbara Maria, 1992, et al.
(author)
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The synergy of damage repair and retention promotes rejuvenation and prolongs healthy lifespans in cell lineages
- 2020
-
In: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 16:10
-
Journal article (peer-reviewed)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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| 36. |
- Schnitzer, Barbara, et al.
(author)
-
Multi-scale model suggests the trade-off between protein and ATP demand as a driver of metabolic changes during yeast replicative ageing
- 2022
-
In: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 18:7
-
Journal article (peer-reviewed)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. © 2022 Schnitzer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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| 37. |
- Schnitzer, Barbara, et al.
(author)
-
The choice of the objective function in flux balance analysis is crucial for predicting replicative lifespans in yeast
- 2022
-
In: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 17:10
-
Journal article (peer-reviewed)abstract
- Flux balance analysis (FBA) is a powerful tool to study genome-scale models of the cellular metabolism, based on finding the optimal flux distributions over the network. While the objective function is crucial for the outcome, its choice, even though motivated by evolutionary arguments, has not been directly connected to related measures. Here, we used an available multi-scale mathematical model of yeast replicative ageing, integrating cellular metabolism, nutrient sensing and damage accumulation, to systematically test the effect of commonly used objective functions on features of replicative ageing in budding yeast, such as the number of cell divisions and the corresponding time between divisions. The simulations confirmed that assuming maximal growth is essential for reaching realistic lifespans. The usage of the parsimonious solution or the additional maximisation of a growth-independent energy cost can improve lifespan predictions, explained by either increased respiratory activity using resources otherwise allocated to cellular growth or by enhancing antioxidative activity, specifically in early life. Our work provides a new perspective on choosing the objective function in FBA by connecting it to replicative ageing.
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| 38. |
- Song, J., et al.
(author)
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Essential Genetic Interactors of SIR2 Required for Spatial Sequestration and Asymmetrical Inheritance of Protein Aggregates
- 2014
-
In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 10:7
-
Journal article (peer-reviewed)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 Hsp104(Y662A)-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 Hsp104(Y662A) 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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| 39. |
- Wanichthanarak, Kwanjeera, 1981, et al.
(author)
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yApoptosis: yeast apoptosis database
- 2013
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In: DATABASE - THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION. - : Oxford University Press (OUP). - 1758-0463. ; 2013:Art. no. bat068
-
Journal article (peer-reviewed)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.
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| 40. |
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| 41. |
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| 42. |
- Welkenhuysen, Niek, 1988, et al.
(author)
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Robustness of Nutrient Signaling Is Maintained by Interconnectivity Between Signal Transduction Pathways
- 2019
-
In: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9
-
Journal article (peer-reviewed)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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| 43. |
- Welkenhuysen, Niek, 1988, et al.
(author)
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Single-cell study links metabolism with nutrient signaling and reveals sources of variability
- 2017
-
In: Bmc Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 11:59
-
Journal article (peer-reviewed)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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| 44. |
- Yang, Xiaoxue, et al.
(author)
-
Stress granule-defective mutants deregulate stress responsive transcripts
- 2014
-
In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 10:11
-
Journal article (peer-reviewed)abstract
- To reduce expression of gene products not required under stress conditions, eukaryotic cells form large and complex cytoplasmic aggregates of RNA and proteins (stress granules; SGs), where transcripts are kept translationally inert. The overall composition of SGs, as well as their assembly requirements and regulation through stress-activated signaling pathways remain largely unknown. We have performed a genome-wide screen of S. cerevisiae gene deletion mutants for defects in SG formation upon glucose starvation stress. The screen revealed numerous genes not previously implicated in SG formation. Most mutants with strong phenotypes are equally SG defective when challenged with other stresses, but a considerable fraction is stress-specific. Proteins associated with SG defects are enriched in low-complexity regions, indicating that multiple weak macromolecule interactions are responsible for the structural integrity of SGs. Certain SG-defective mutants, but not all, display an enhanced heat-induced mutation rate. We found several mutations affecting the Ran GTPase, regulating nucleocytoplasmic transport of RNA and proteins, to confer SG defects. Unexpectedly, we found stress-regulated transcripts to reach more extreme levels in mutants unable to form SGs: stress-induced mRNAs accumulate to higher levels than in the wild-type, whereas stress-repressed mRNAs are reduced further in such mutants. Our findings are consistent with the view that, not only are SGs being regulated by stress signaling pathways, but SGs also modulate the extent of stress responses. We speculate that nucleocytoplasmic shuttling of RNA-binding proteins is required for gene expression regulation during stress, and that SGs modulate this traffic. The absence of SGs thus leads the cell to excessive, and potentially deleterious, reactions to stress.
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| 45. |
- Österberg, Linnea, 1992, et al.
(author)
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A novel yeast hybrid modeling framework integrating Boolean and enzyme-constrained networks enables exploration of the interplay between signaling and metabolism
- 2021
-
In: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 17:4
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Journal article (peer-reviewed)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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- Österlund, Tobias, 1984, et al.
(author)
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Integrative analysis of omics data
- 2017
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In: Systems Biology. - 9783527696178 ; , s. 1-24
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Book chapter (other academic/artistic)abstract
- Data generation and analysis are essential parts of systems biology. Today, large amounts of omics data can be generated fast and cost-efficiently thanks to the development of modern high-throughput measurement techniques. Their interpretation is, however, challenging because of the high dimensionality and the often substantial levels of noise. Integrative analysis provides a framework for analysis of the omics data from a biological perspective, starting from the raw data, via preprocessing and statistical analysis, to the interpretation of the results. By integrating the data into structures created from biological information available in resources, databases, or genome-scale models, the focus moves from the individual transcripts or proteins to the entire pathways and other relevant biochemical functions present in the cell. The result provides a context-based interpretation of the omics data, which can be used to form a holistic and unbiased view of biological systems at a molecular level.The concept of integrative analysis can be used formany forms of omics data, including genome sequencing, transcriptomics, and proteomics, and can be applied to a wide range of fields within the life sciences.
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