ABSTRACT
Protein synthesis rates are determined, at the translational level, by properties of the transcript's sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. According to our results, the proximity of the 3' end to the ribosomal recruitment site of the mRNA could induce a feedback in the translation process that would favour the recycling of ribosomes. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.
Subject(s)
Gene Expression Regulation , Genes , Models, Biological , Protein Biosynthesis , Ribosomes/metabolism , Animals , Computer Simulation , Feedback, Physiological , Gene Expression Regulation/genetics , Gene Expression Regulation/physiology , Genes/physiology , HEK293 Cells , Humans , Kinetics , Mice , Monte Carlo Method , Plasmodium falciparum , Protein Biosynthesis/physiology , RNA, Messenger/metabolism , Saccharomyces cerevisiae , Stochastic ProcessesABSTRACT
Mechanosensitive channels are ion channels which act as cells' safety valves, opening when the osmotic pressure becomes too high and making cells avoid damage by releasing ions. They are found on the cellular membrane of a large number of organisms. They interact with each other by means of deformations they induce in the membrane. We show that collective dynamics arising from the interchannel interactions lead to first- and second-order phase transitions in the fraction of open channels in equilibrium relating to the formation of channel clusters. We show that this results in a considerable delay of the response of cells to osmotic shocks, and to an extreme cell-to-cell stochastic variations in their response times, despite the large numbers of channels present in each cell. We discuss how our results are relevant for E. coli.
Subject(s)
Cell Membrane/metabolism , Membrane Transport Proteins/metabolism , Models, Biological , Biomechanical Phenomena , Computer Simulation , Escherichia coli/metabolism , Monte Carlo Method , Osmosis , Stochastic Processes , Stress, Physiological , Time FactorsABSTRACT
Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition to the traditional differential gene expression and ontology analysis, would enable identification of the effects of anaesthesia on interactions between genes. Rats (n=10 per group) were randomised to anaesthesia with isoflurane in oxygen or oxygen only for 15min, and 6h later brains were removed. Differential gene expression and gene ontology analysis of microarray data was performed. Standard clustering techniques and principal component analysis with Bayesian rules were used along with social network analysis methods, to quantitatively model and describe the gene networks. Anaesthesia had marked effects on genes in the brain with differential regulation of 416 probe sets by at least 2 fold. Gene ontology analysis showed 23 genes were functionally related to the anaesthesia and of these, 12 were involved with neurotransmitter release, transport and secretion. Gene network analysis revealed much greater connectivity in genes from brains from anaesthetised rats compared to controls. Other importance measures were also altered after anaesthesia; median [range] closeness centrality (shortest path) was lower in anaesthetized animals (0.07 [0-0.30]) than controls (0.39 [0.30-0.53], p<0.0001) and betweenness centrality was higher (53.85 [32.56-70.00]% compared to 5.93 [0-30.65]%, p<0.0001). Simply studying the actions of individual components does not fully describe dynamic and complex systems. Network analysis allows insight into the interactions between genes after anaesthesia and suggests future targets for investigation.
Subject(s)
Anesthetics, Inhalation/therapeutic use , Brain/drug effects , Gene Expression/drug effects , Gene Ontology , Gene Regulatory Networks/drug effects , Isoflurane/pharmacology , Animals , Cluster Analysis , Male , Microarray Analysis , Rats , Rats, Sprague-DawleyABSTRACT
Xenografts--as simplified animal models of cancer-differ substantially in vasculature and stromal architecture when compared to clinical tumours. This makes mathematical model-based predictions of clinical outcome challenging. Our objective is to further understand differences in tumour progression and physiology between animal models and the clinic. To achieve that, we propose a mathematical model based upon tumour pathophysiology, where oxygen--as a surrogate for endocrine delivery--is our main focus. The Oxygen-Driven Model (ODM), using oxygen diffusion equations, describes tumour growth, hypoxia and necrosis. The ODM describes two key physiological parameters. Apparent oxygen uptake rate (k'R) represents the amount of oxygen cells seem to need to proliferate. The more oxygen they appear to need, the more the oxygen transport. k'R gathers variability from the vasculature, stroma and tumour morphology. Proliferating rate (kp) deals with cell line specific factors to promote growth. The KH,KN describe the switch of hypoxia and necrosis. Retrospectively, using archived data, we looked at longitudinal tumour volume datasets for 38 xenografted cell lines and 5 patient-derived xenograft-like models. Exploration of the parameter space allows us to distinguish 2 groups of parameters. Group 1 of cell lines shows a spread in values of k'R and lower kp, indicating that tumours are poorly perfused and slow growing. Group 2 share the value of the oxygen uptake rate (k'R) and vary greatly in kp, which we interpret as having similar oxygen transport, but more tumour intrinsic variability in growth. However, the ODM has some limitations when tested in explant-like animal models, whose complex tumour-stromal morphology may not be captured in the current version of the model. Incorporation of stroma in the ODM will help explain these discrepancies. We have provided an example. The ODM is a very simple -and versatile- model suitable for the design of preclinical experiments, which can be modified and enhanced whilst maintaining confidence in its predictions.
Subject(s)
Models, Biological , Neoplasms/pathology , Neoplasms/physiopathology , Oxygen Consumption , Oxygen/metabolism , Animals , Cell Hypoxia , Cell Line, Tumor , Cell Proliferation , Computer Simulation , Humans , Oxidative StressABSTRACT
The major fungal pathogen of humans, Candida albicans, mounts robust responses to oxidative stress that are critical for its virulence. These responses counteract the reactive oxygen species (ROS) that are generated by host immune cells in an attempt to kill the invading fungus. Knowledge of the dynamical processes that instigate C. albicans oxidative stress responses is required for a proper understanding of fungus-host interactions. Therefore, we have adopted an interdisciplinary approach to explore the dynamical responses of C. albicans to hydrogen peroxide (H2O2). Our deterministic mathematical model integrates two major oxidative stress signalling pathways (Cap1 and Hog1 pathways) with the three major antioxidant systems (catalase, glutathione and thioredoxin systems) and the pentose phosphate pathway, which provides reducing equivalents required for oxidative stress adaptation. The model encapsulates existing knowledge of these systems with new genomic, proteomic, transcriptomic, molecular and cellular datasets. Our integrative approach predicts the existence of alternative states for the key regulators Cap1 and Hog1, thereby suggesting novel regulatory behaviours during oxidative stress. The model reproduces both existing and new experimental observations under a variety of scenarios. Time- and dose-dependent predictions of the oxidative stress responses for both wild type and mutant cells have highlighted the different temporal contributions of the various antioxidant systems during oxidative stress adaptation, indicating that catalase plays a critical role immediately following stress imposition. This is the first model to encapsulate the dynamics of the transcriptional response alongside the redox kinetics of the major antioxidant systems during H2O2 stress in C. albicans.
Subject(s)
Adaptation, Physiological , Antioxidants/metabolism , Candida albicans/physiology , Hydrogen Peroxide/pharmacology , Oxidative Stress , Adaptation, Physiological/drug effects , Candida albicans/drug effects , Fungal Proteins/genetics , Fungal Proteins/metabolism , Host-Pathogen Interactions , Humans , Models, Biological , Mutation , Oxidative Stress/drug effects , Reactive Oxygen Species/metabolismABSTRACT
Eukaryotic genomes are replicated from multiple DNA replication origins. We present complementary deep sequencing approaches to measure origin location and activity in Saccharomyces cerevisiae. Measuring the increase in DNA copy number during a synchronous S-phase allowed the precise determination of genome replication. To map origin locations, replication forks were stalled close to their initiation sites; therefore, copy number enrichment was limited to origins. Replication timing profiles were generated from asynchronous cultures using fluorescence-activated cell sorting. Applying this technique we show that the replication profiles of haploid and diploid cells are indistinguishable, indicating that both cell types use the same cohort of origins with the same activities. Finally, increasing sequencing depth allowed the direct measure of replication dynamics from an exponentially growing culture. This is the first time this approach, called marker frequency analysis, has been successfully applied to a eukaryote. These data provide a high-resolution resource and methodological framework for studying genome biology.
Subject(s)
DNA Replication , Genome , High-Throughput Nucleotide Sequencing/methods , Sequence Analysis, DNA/methods , Replication Origin , Saccharomyces cerevisiae/geneticsABSTRACT
Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.
Subject(s)
DNA Replication/genetics , Replication Origin/genetics , Saccharomyces cerevisiae/genetics , Base Sequence , Genome, Fungal/genetics , Genomic Instability , Models, Theoretical , S Phase/genetics , Sequence Analysis, DNAABSTRACT
Inside the nucleus, DNA replication is organized at discrete sites called replication factories, consisting of DNA polymerases and other replication proteins. Replication factories play important roles in coordinating replication and in responding to replication stress. However, it remains unknown how replicons are organized for processing at each replication factory. Here we address this question using budding yeast. We analyze how individual replicons dynamically organized a replication factory using live-cell imaging and investigate how replication factories were structured using super-resolution microscopy. Surprisingly, we show that the grouping of replicons within factories is highly variable from cell to cell. Once associated, however, replicons stay together relatively stably to maintain replication factories. We derive a coherent genome-wide mathematical model showing how neighboring replicons became associated stochastically to form replication factories, which was validated by independent microscopy-based analyses. This study not only reveals the fundamental principles promoting replication factory organization in budding yeast, but also provides insight into general mechanisms by which chromosomes organize sub-nuclear structures.
Subject(s)
Cell Nucleus/genetics , DNA Replication/genetics , DNA, Fungal/genetics , Replication Origin/genetics , Replicon/genetics , Saccharomycetales/genetics , Stochastic Processes , Cell Nucleus/ultrastructure , Chromosomes, Fungal/genetics , Image Processing, Computer-Assisted , Microscopy , Models, Theoretical , Saccharomycetales/cytologyABSTRACT
Methylglyoxal (MG) elicits activation of K(+) efflux systems to protect cells against the toxicity of the electrophile. ChIP-chip targeting RNA polymerase, supported by a range of other biochemical measurements and mutant creation, was used to identify genes transcribed in response to MG and which complement this rapid response. The SOS DNA repair regulon is induced at cytotoxic levels of MG, even when exposure to MG is transient. Glyoxalase I alone among the core MG protective systems is induced in response to MG exposure. Increased expression is an indirect consequence of induction of the upstream nemRA operon, encoding an enzyme system that itself does not contribute to MG detoxification. Moreover, this induction, via nemRA only occurs when cells are exposed to growth inhibitory concentrations of MG. We show that the kdpFABCDE genes are induced and that this expression occurs as a result of depletion of cytoplasmic K(+) consequent upon activation of the KefGB K(+) efflux system. Finally, our analysis suggests that the transcriptional changes in response to MG are a culmination of the damage to DNA and proteins, but that some integrate specific functions, such as DNA repair, to augment the allosteric activation of the main protective system, KefGB.
Subject(s)
Escherichia coli/drug effects , Gene Expression Regulation, Bacterial , Lactoylglutathione Lyase/biosynthesis , Operon , Pyruvaldehyde/toxicity , Stress, Physiological , Transcription, Genetic , Escherichia coli/genetics , Escherichia coli/physiology , Escherichia coli Proteins/genetics , Genes, Bacterial/genetics , Lactoylglutathione Lyase/genetics , SOS Response, Genetics , Transcription Factors/geneticsABSTRACT
Eukaryotic DNA replication is initiated from multiple sites on the chromosome, but little is known about the global and local regulation of replication. We present a mathematical model for the spatial dynamics of DNA replication, which offers insight into the kinetics of replication in different types of organisms. Most biological experiments involve average quantities over large cell populations (typically >10(7) cells) and therefore can mask the cell-to-cell variability present in the system. Although the model is formulated in terms of a population of cells, using mathematical analysis we show that one can obtain signatures of stochasticity in individual cells from averaged quantities. This work generalizes the result by Retkute et al. [Phys. Rev. Lett. 107, 068103 (2011)] to a broader set of parameter regimes.
Subject(s)
DNA Replication/genetics , Genome/genetics , Models, Genetic , Chromosomes, Fungal/genetics , DNA, Fungal/biosynthesis , Kinetics , Normal Distribution , Probability , Saccharomyces cerevisiae/genetics , Stochastic ProcessesABSTRACT
BACKGROUND: Saccharomyces cerevisiae senses hyperosmotic conditions via the HOG signaling network that activates the stress-activated protein kinase, Hog1, and modulates metabolic fluxes and gene expression to generate appropriate adaptive responses. The integral control mechanism by which Hog1 modulates glycerol production remains uncharacterized. An additional Hog1-independent mechanism retains intracellular glycerol for adaptation. Candida albicans also adapts to hyperosmolarity via a HOG signaling network. However, it remains unknown whether Hog1 exerts integral or proportional control over glycerol production in C. albicans. RESULTS: We combined modeling and experimental approaches to study osmotic stress responses in S. cerevisiae and C. albicans. We propose a simple ordinary differential equation (ODE) model that highlights the integral control that Hog1 exerts over glycerol biosynthesis in these species. If integral control arises from a separation of time scales (i.e. rapid HOG activation of glycerol production capacity which decays slowly under hyperosmotic conditions), then the model predicts that glycerol production rates elevate upon adaptation to a first stress and this makes the cell adapts faster to a second hyperosmotic stress. It appears as if the cell is able to remember the stress history that is longer than the timescale of signal transduction. This is termed the long-term stress memory. Our experimental data verify this. Like S. cerevisiae, C. albicans mimimizes glycerol efflux during adaptation to hyperosmolarity. Also, transient activation of intermediate kinases in the HOG pathway results in a short-term memory in the signaling pathway. This determines the amplitude of Hog1 phosphorylation under a periodic sequence of stress and non-stressed intervals. Our model suggests that the long-term memory also affects the way a cell responds to periodic stress conditions. Hence, during osmohomeostasis, short-term memory is dependent upon long-term memory. This is relevant in the context of fungal responses to dynamic and changing environments. CONCLUSIONS: Our experiments and modeling have provided an example of identifying integral control that arises from time-scale separation in different processes, which is an important functional module in various contexts.
Subject(s)
Candida albicans/enzymology , MAP Kinase Signaling System , Mitogen-Activated Protein Kinases/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/enzymology , Stress, Physiological , Systems Biology , Adaptation, Physiological , Enzyme Activation , Glycerol/metabolism , Models, Biological , Osmotic Pressure , Phosphorylation , Time FactorsABSTRACT
Pathogenic microbes exist in dynamic niches and have evolved robust adaptive responses to promote survival in their hosts. The major fungal pathogens of humans, Candida albicans and Candida glabrata, are exposed to a range of environmental stresses in their hosts including osmotic, oxidative and nitrosative stresses. Significant efforts have been devoted to the characterization of the adaptive responses to each of these stresses. In the wild, cells are frequently exposed simultaneously to combinations of these stresses and yet the effects of such combinatorial stresses have not been explored. We have developed a common experimental platform to facilitate the comparison of combinatorial stress responses in C. glabrata and C. albicans. This platform is based on the growth of cells in buffered rich medium at 30°C, and was used to define relatively low, medium and high doses of osmotic (NaCl), oxidative (H(2)O(2)) and nitrosative stresses (e.g., dipropylenetriamine (DPTA)-NONOate). The effects of combinatorial stresses were compared with the corresponding individual stresses under these growth conditions. We show for the first time that certain combinations of combinatorial stress are especially potent in terms of their ability to kill C. albicans and C. glabrata and/or inhibit their growth. This was the case for combinations of osmotic plus oxidative stress and for oxidative plus nitrosative stress. We predict that combinatorial stresses may be highly significant in host defences against these pathogenic yeasts.
Subject(s)
Candida albicans/physiology , Candida glabrata/physiology , Microbial Viability/drug effects , Stress, Physiological , Candida albicans/drug effects , Candida albicans/growth & development , Candida glabrata/drug effects , Candida glabrata/growth & development , Culture Media/chemistry , Humans , Mycology/methods , Nitroso Compounds/toxicity , Osmotic Pressure , Oxidative Stress , TemperatureABSTRACT
DNA replication is an essential process in biology and its timing must be robust so that cells can divide properly. Random fluctuations in the formation of replication starting points, called origins, and the subsequent activation of proteins lead to variations in the replication time. We analyze these stochastic properties of DNA and derive the positions of origins corresponding to the minimum replication time. We show that under some conditions the minimization of replication time leads to the grouping of origins, and relate this to experimental data in a number of species showing origin grouping.
Subject(s)
DNA Replication/physiology , Replication Origin/physiology , Algorithms , Animals , Chromosomes/physiology , DNA/genetics , DNA, Fungal/biosynthesis , DNA, Fungal/genetics , Eukaryotic Cells , Humans , Kinetics , Models, Statistical , S Phase/physiology , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/physiology , Stochastic Processes , Xenopus laevisABSTRACT
We show that common circulatory diseases, such as stenoses and aneurysms, generate chaotic advection of blood particles. This phenomenon has major consequences on the way the biochemical particles behave. Chaotic advection leads to a peculiar filamentary particle distribution, which in turn creates a favorable environment for particle reactions. Furthermore, we argue that the enhanced stretching dynamics induced by chaos can lead to the activation of platelets, particles involved in the thrombus formation. In particular, we vary the size of both stenoses and aneurysms, and model them under resting and exercising conditions. We show that the filamentary particle distribution, governed by the fractal skeleton, depends on the size of the vessel wall irregularity, and investigate how it varies under resting or exercising conditions.
Subject(s)
Carotid Stenosis/physiopathology , Fractals , Models, Cardiovascular , Computer Simulation , Hemodynamics , Humans , Nonlinear DynamicsABSTRACT
DNA within cells is subject to damage from various sources. Organisms have evolved a number of mechanisms to repair DNA damage. The activity of repair enzymes carries its own risk, however, because the repair of two nearby lesions may lead to the breakup of DNA and result in cell death. We propose a mathematical theory of the damage and repair process in the important scenario where lesions are caused in bursts. We use this model to show that there is an optimum level of repair enzymes within cells which optimises the cell's response to damage. This optimal level is explained as the best trade-off between fast repair and a low probability of causing double-stranded breaks. We derive our results analytically and test them using stochastic simulations, and compare our predictions with current biological knowledge.
Subject(s)
DNA Repair/genetics , Models, Genetic , Animals , Cell Death/genetics , Cell Survival/genetics , DNA Damage/genetics , DNA Repair Enzymes/physiology , Stochastic ProcessesABSTRACT
We present a mathematical model for the spatial dynamics of DNA replication. Using this model we determine the probability distribution for the time at which each chromosomal position is replicated. From this we show, contrary to previous reports, that mean replication time curves cannot be used to directly determine origin parameters. We demonstrate that the stochastic nature of replication dynamics leaves a clear signature in experimentally measured population average data, and we show that the width of the activation time probability distribution can be inferred from this data. Our results compare favorably with experimental measurements in Saccharomyces cerevisae.
Subject(s)
DNA Replication , DNA, Fungal/metabolism , Saccharomyces cerevisiae/metabolism , Chromosomes, Fungal/metabolism , DNA Replication TimingABSTRACT
Mechanosensitive channels are ion channels activated by membrane tension. We investigate the influence of the spatial distribution of bacterial mechanosensitive channels on activation (gating). Based on elastic short-range interactions we map this physical process onto an Ising-like model, which enables us to predict the clustering of channels and the effects of clustering on their gating. We conclude that the aggregation of channels and the consequent interactions among them leads to a global cooperative gating behavior with potentially dramatic consequences for the cell.
Subject(s)
Bacterial Proteins/physiology , Cell Membrane/physiology , Ion Channel Gating/physiology , Ion Channels/physiology , Mechanotransduction, Cellular/physiology , Models, Biological , Bacterial Proteins/chemistry , Cell Membrane/chemistry , Computer Simulation , Ion Channels/chemistry , Models, ChemicalABSTRACT
DNA damage is a hazard all cells must face, and evolution has created a number of mechanisms to repair damaged bases in the chromosome. Paradoxically, many of these repair mechanisms can create double-strand breaks in the DNA molecule which are fatal to the cell. This indicates that the connection between DNA repair and death is far from straightforward, and suggests that the repair mechanisms can be a double-edged sword. In this report, we formulate a mathematical model of the dynamics of DNA damage and repair, and we obtain analytical expressions for the death rate. We predict a counterintuitive relationship between survival and repair. We can discriminate between two phases: below a critical threshold in the number of repair enzymes, the half-life decreases with the number of repair enzymes, but becomes independent of the number of repair enzymes above the threshold. We are able to predict quantitatively the dependence of the death rate on the damage rate and other relevant parameters. We verify our analytical results by simulating the stochastic dynamics of DNA damage and repair. Finally, we also perform an experiment with Escherichia coli cells to test one of the predictions of our model.
Subject(s)
DNA Damage , DNA Repair , Escherichia coli/cytology , Escherichia coli/metabolism , Microbial Viability , Models, Biological , Computer Simulation , DNA Repair/drug effects , Escherichia coli/drug effects , Microbial Viability/drug effects , Pyruvaldehyde/toxicity , Stochastic ProcessesABSTRACT
We study the collision probability p of particles advected by open flows with chaotic advection. We show that p scales with the particle size (or, alternatively, reaction distance) δ as a power law whose coefficient is determined by the fractal dimensions of the invariant sets defined by the advection dynamics. We also argue that this same scaling also holds for the reaction rate of active particles in the low-density regime. These analytical results are compared to numerical simulations, and they are found to agree very well.
ABSTRACT
Recent advances in the field of chaotic advection provide the impetus to revisit the dynamics of particles transported by blood flow in the presence of vessel wall irregularities. The irregularity, being either a narrowing or expansion of the vessel, mimicking stenoses or aneurysms, generates abnormal flow patterns that lead to a peculiar filamentary distribution of advected particles, which, in the blood, would include platelets. Using a simple model, we show how the filamentary distribution depends on the size of the vessel wall irregularity, and how it varies under resting or exercise conditions. The particles transported by blood flow that spend a long time around a disturbance either stick to the vessel wall or reside on fractal filaments. We show that the faster flow associated with exercise creates widespread filaments where particles can get trapped for a longer time, thus allowing for the possible activation of such particles. We argue, based on previous results in the field of active processes in flows, that the non-trivial long-time distribution of transported particles has the potential to have major effects on biochemical processes occurring in blood flow, including the activation and deposition of platelets. One aspect of the generality of our approach is that it also applies to other relevant biological processes, an example being the coexistence of plankton species investigated previously.