Origin of adaptive mutants: a quantum measurement?
This is a supplement to the paper arXiv:q-bio/0701050, containing the text of correspondence sent to Nature in 1990.
q-bio.PE↗
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Quantitative Resolution to some "Absolute Discrepancies" in Cancer Theories: a View from Phage lambda Genetic Switch
Is it possible to understand cancer? Or more specifically, is it possible to understand cancer from genetic side? There already many answers in literature. The most optimistic one has claimed that it is mission-possible. Duesberg and his colleagues reviewed the impressive amount of research results on cancer accumulated over 100 years. It confirms the a general opinion that considering all available experimental results and clinical observations there is no cancer theory without major difficulties, including the prevailing gene-based cancer theories. They have then listed 9 "absolute discrepancies" for such cancer theory. In this letter the quantitative evidence against one of their major reasons for dismissing mutation cancer theory, by both in vivo experiment and a first principle computation, is explicitly pointed out.
q-bio.SC↗
A quantitative study on the growth variability of tumour cell clones in vitro
Objectives: In this study, we quantify the growth variability of tumour cell clones from a human leukemia cell line. Materials and methods: We have used microplate spectrophotometry to measure the growth kinetics of hundreds of individual cell clones from the Molt3 cell line. The growth rate of each clonal population has been estimated by fitting experimental data with the logistic equation. Results: The growth rates were observed to vary among different clones. Up to six clones with a growth rate above or below the mean growth rate of the parent population were further cloned and the growth rates of their offsprings were measured. The distribution of the growth rates of the subclones did not significantly differ from that of the parent population thus suggesting that growth variability has an epigenetic origin. To explain the observed distributions of clonal growth rates we have developed a probabilistic model assuming that the fluctuations in the number of mitochondria through successive cell cycles are the leading cause of growth variability. For fitting purposes, we have estimated experimentally by flow cytometry the maximum average number of mitochondria in Molt3 cells. The model fits nicely the observed distributions of growth rates, however, cells in which the mitochondria were rendered non functional (rho-0 cells) showed only a 30% reduction in the clonal growth variability with respect to normal cells. Conclusions: A tumor cell population is a dynamic ensemble of clones with highly variable growth rate. At least part of this variability is due to fluctuations in the number of mitochondria.
q-bio.CB↗
Self assembly of a model multicellular organism resembling the Dictyostelium slime molds
The evolution of multicellular organisms from monocellular ancestors represents one of the greatest advances of the history of life. The assembly of such multicellular organisms requires signalling and response between cells: over millions of years these signalling processes have become extremely sophisticated and refined by evolution, such that study of modern organisms may not be able to shed much light on the original ancient processes . Here we are interested in determining how simple a signalling method can be, while still achieving self-assembly. In 2D a coupled cellular automaton/differential equation approach models organisms and chemotaxic chemicals, producing spiralling aggregation. In 3D Lennard-Jones-like particles are used to represent single cells, and their evolution in response to signalling is followed by molecular dynamics. It is found that if a single cell is able to emit a signal which induces others to move towards it, then a colony of single-cell organisms can assemble into shapes as complex as a tower, a ball atop a stalk, or a fast-moving slug. The similarity with the behaviour of modern Dictyostelium slime molds signalling with cyclic adenosine monophosphate (cAMP) is striking.
q-bio.CB↗
Simulating non-small cell lung cancer with a multiscale agent-based model
Background The epidermal growth factor receptor (EGFR) is frequently overexpressed in many cancers, including non-small cell lung cancer (NSCLC). In silcio modeling is considered to be an increasingly promising tool to add useful insights into the dynamics of the EGFR signal transduction pathway. However, most of the previous modeling work focused on the molecular or the cellular level only, neglecting the crucial feedback between these scales as well as the interaction with the heterogeneous biochemical microenvironment. Results We developed a multiscale model for investigating expansion dynamics of NSCLC within a two-dimensional in silico microenvironment. At the molecular level, a specific EGFR-ERK intracellular signal transduction pathway was implemented. Dynamical alterations of these molecules were used to trigger phenotypic changes at the cellular level. Examining the relationship between extrinsic ligand concentrations, intrinsic molecular profiles and microscopic patterns, the results confirmed that increasing the amount of available growth factor leads to a spatially more aggressive cancer system. Moreover, for the cell closest to nutrient abundance, a phase-transition emerges where a minimal increase in extrinsic ligand abolishes the proliferative phenotype altogether. Conclusions Our in silico results indicate that, in NSCLC, in the presence of a strong extrinsic chemotactic stimulus, and depending on the cell's location, downstream EGFR-ERK signaling may be processed more efficiently, thereby yielding a migration-dominant cell phenotype and overall, an accelerated spatio-temporal expansion rate.
q-bio.CB↗
Relating Biophysical Properties Across Scales
A distinguishing feature of a multicellular living system is that it operates at various scales, from the intracellular to organismal. Very little is known at present on how tissue level properties are related to cell and subcellular properties. Modern measurement techniques provide quantitative results at both the intracellular and tissue level, but not on the connection between these. In the present work we outline a framework to address this connection. We specifically concentrate on the morphogenetic process of tissue fusion, by following the coalescence of two contiguous multicellular aggregates. The time evolution of this process can accurately be described by the theory of viscous liquids. We also study fusion by Monte Carlo simulations and a novel Cellular Particle Dynamics (CPD) model, which is similar to the earlier introduced Subcellular Element Model (Newman, 2005). Using the combination of experiments, theory and modeling we are able to relate the measured tissue level biophysical quantities to subcellular parameters. Our approach has validity beyond the particular morphogenetic process considered here and provides a general way to relate biophysical properties across scales.
physics.bio-ph↗
Bistability of the lac operon during growth of Escherichia coli on lactose and lactose + glucose
The lac operon of Escherichia coli exhibits bistability. Early studies showed that bistability occurs during growth on TMG/succinate and lactose + glucose, but not during growth on lactose. More recent studies with lacGFP-transfected cells show bistability with TMG/succinate, but not with lactose and lactose + glucose. In the literature, these results are attributed to variations of the positive feedback generated by induction. Specifically, during growth on TMG/succinate, induction generates positive feedback because the permease stimulates the accumulation of TMG, which, in turn, promotes the synthesis of more permease. This positive feedback is attenuated during growth on lactose because hydrolysis of lactose by galactosidase suppresses the stimulatory effect of the permease. But the stabilizing effect of dilution also changes dramatically as a function of the medium composition. For instance, during growth on TMG/succinate, the dilution rate of the permease is proportional to its activity, $e$, because the specific growth rate is independent of $e$. However, during growth on lactose, the permease dilution rate is proportional to $e^2$ because the specific growth rate is proportional to the specific lactose uptake rate, which in turn, proportional to $e$. Here, we show that: (a) This dependence on $e^2$ creates such a strong stabilizing effect that bistability is virtually impossible during growth on lactose, even in the face of positive feedback. (b) This stabilizing effect is weakened during growth on lactose + glucose because the specific growth rate on glucose is independent of $e$, so that the dilution rate once again contains a term that is proportional to $e$. We discuss the experimental data in the light of these results.
q-bio.MN↗
Post-transcriptional Regulation Drives Temporal Compartmentalization of the Yeast Metabolic Cycle
The maintainance of a stable periodicity during the yeast metabolic cycle involving approximately half of the genome requires a very strict and efficient control of gene expression. For this reason, the metabolic cycle is a very good candidate for testing the role of a class of post-transcriptional regulators, the so called PUF-family, whose genome-wide mRNA binding specificity was recently experimentally assessed. Here we show that an integrated computational analysis of gene expression time series during the metabolic cycle and the mRNA binding specificity of PUF-family proteins allow for a clear demonstration of the very specific role exerted by selective post-transcriptional mRNA degradation in yeast metabolic cycle global regulation.
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Immune response to a malaria infection: properties of a mathematical model
We establish some properties of a within host mathematical model of malaria proposed by Recker et al which includes the role of the immune system during the infection. The model accounts for the antigenic variation exhibited by the malaria parasite (P. falciparum). We show that the model can exhibit a wide variety of dynamical behaviors. We provide criteria for global stability, competitive exclusion, and persistence. We also demonstrate that the disease equilibrium can be destabilized by non-symmetric cross-reactive responses.
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Multi-strain virus dynamics with mutations: A global analysis
We consider within-host virus models with more than one strain and allow mutation between the strains. If there is no mutation, a Lyapunov function establishes global stability of the steady state corresponding to the fittest strain. For small perturbations this steady state persists, perhaps with small concentrations of some or all other strains, depending on the connectivity of the graph describing all possible mutations. Moreover, using a perturbation result due to Smith and Waltman, we show that this steady state also preserves global stability.
q-bio.CB↗
A Map-Based Model of the Cardiac Action Potential
A discrete time model that is capable of replicating the basic features of cardiac cell action potentials is suggested. The paper shows how the map-based approaches can be used to design highly efficient computational models (algorithms) that enable large-scale simulations and analysis of discrete network models of cardiac activity.
q-bio.CB↗
Landscape phage, phage display, stripped phage, biosensors, detection, affinity reagent, nanotechnology, Salmonella typhimurium, Bacillus anthracis
Filamentous phage, such as fd used in this study, are thread-shaped bacterial viruses. Their outer coat is a tube formed by thousands equal copies of the major coat protein pVIII. We constructed libraries of random peptides fused to all pVIII domains and selected phages that act as probes specific for a panel of test antigens and biological threat agents. Because the viral carrier is infective, phage borne bio-selective probes can be cloned individually and propagated indefinitely without needs of their chemical synthesis or reconstructing. We demonstrated the feasibility of using landscape phages and their stripped fusion proteins as new bioselective materials that combine unique characteristics of affinity reagents and self assembling membrane proteins. Biorecognition layers fabricated from phage-derived probes bind biological agents and generate detectable signals. The performance of phage-derived materials as biorecognition films was illustrated by detection of streptavidin-coated beads, Bacillus anthracis spores and Salmonella typhimurium cells. With further refinement, the phage-derived analytical platforms for detecting and monitoring of numerous threat agents may be developed, since the biodetector films may be obtained from landscape phages selected against any bacteria, virus or toxin. As elements of field-use detectors, they are superior to antibodies, since they are inexpensive, highly specific and strong binders, resistant to high temperatures and environmental stresses.
cond-mat.mtrl-sci↗
Dynamics of glucose-lactose diauxic growth in E. coli
We present a mathematical model of glucose-lactose diauxic growth in Escherichia coli including both the postive and negative regulation mechanisms of the lactose operon as well as the inducer exclusion. To validate this model, we first calculated the time evolution of beta-galactosidase for only the lactose nutrient and compared the numerical results with experimental data. Second, we compared the calculated cell biomass of the glucose-lactose diauxic growth with the experimental optical density of the diauxic growth for a particular E. coli MG 1655. For both cases, the numerical calculations from this model are in good agreement with these two experiments' data. The diauxic growth pattern of a wild type E. coli was also investigated.
q-bio.OT↗
A probabilistic regulatory network for the human immune system
In this paper we made a review of some papers about probabilistic regulatory networks (PRN), in particular we introduce our concept of homomorphisms of PRN with an example of projection of a regulatory network to a smaller one. We apply the model PRN (or Probabilistic Boolean Network) to the immune system, the PRN works with two functions. The model called ""The B/T-cells interaction"" is Boolean, so we are really working with a Probabilistic Boolean Network. Using Markov Chains we determine the state of equilibrium of the immune response.
q-bio.CB↗
Intermittent dynamics and 1/f^beta noise in single cardiac muscle cells
Fluctuations in the spontaneous beating activity of isolated cardiac cells were studied over a timescale of six decades. The beat dynamics of single cardiac cells were heterogeneous and intermittent. The interbeat intervals (IBIs) were power-law distributed in a long-time regime. Furthermore, for long timescales up to the experimental window, the autocorrelation of IBIs exhibits a scaling behavior of 1/f^beta-noise type. These observations suggest that 1/f^beta noise is an intrinsic characteristic of spontaneous activity of single cardiac cells.
q-bio.CB↗
Selective advantage for sexual reproduction with random haploid fusion
This paper develops a simplified set of models describing asexual and sexual replication in unicel- lular diploid organisms. The models assume organisms whose genomes consist of two chromosomes, where each chromosome is assumed to be functional if it is equal to some master sequence $ σ_0 $, and non-functional otherwise. The first-order growth rate constant, or fitness, of an organism, is determined by whether it has zero, one, or two functional chromosomes in its genome. For a population replicating asexually, a given cell replicates both of its chromosomes, and splits its genetic material evenly between the two cells. For a population replicating sexually, a given cell first divides into two haploids, which enter a haploid pool, fuse into diploids, and then divide via the normal mitotic process. Haploid fusion is modeled as a second-order rate process. When the cost for sex is small, as measured by the ratio of the characteristic haploid fusion time to the characteristic growth time, we find that sexual replication with random haploid fusion leads to a greater mean fitness for the population than a purely asexual strategy. However, independently of the cost for sex, we find that sexual replication with a selective mating strategy leads to a higher mean fitness than the random mating strategy. This result is based on the assumption that a selective mating strategy does not have any additional time or energy costs over the random mating strategy, an assumption that is discussed in the paper. The results of this paper are consistent with previous studies suggesting that sex is favored at intermediate mutation rates, for slowly replicating organisms, and at high population densities.
q-bio.PE↗
Dissecting Subsecond Cadherin Bound States Reveals an Efficient Way for Cells to Achieve Ultrafast Probing of their Environment
Cells continuously probe their environment with membrane receptors, achieving subsecond adaptation of their behaviour [1-3]. Recently, several receptors, including cadherins, were found to bind ligands with a lifetime of order of one second. Here we show at the single molecule level that homotypic C-cadherin association involves transient intermediates lasting less than a few tens of milliseconds. Further, these intermediates transitionned towards more stable states with a kinetic rate displaying exponential decrease with piconewton forces. These features enable cells to detect ligands or measure surrounding mechanical behaviour within a fraction of a second, much more rapidly than was previously thought.
q-bio.CB↗
Endogenous versus Exogenous Origins of Diseases
Many illnesses are associated with an alteration of the immune system homeostasis due to any combination of factors, including exogenous bacterial insult, endogenous breakdown (e.g., development of a disease that results in immuno suppression), or an exogenous hit like surgery that simultaneously alters immune responsiveness and provides access to bacteria, or genetic disorder. We conjecture that, as a consequence of the co-evolution of the immune system of individuals with the ecology of pathogens, the homeostasis of the immune system requires the influx of pathogens. This allows the immune system to keep the ever present pathogens under control and to react and adjust fast to bursts of infections. We construct the simplest and most general system of rate equations which describes the dynamics of five compartments: healthy cells, altered cells, adaptive and innate immune cells, and pathogens. We study four regimes obtained with or without auto-immune disorder and with or without spontaneous proliferation of infected cells. Over all regimes, we find that seven different states are naturally described by the model: (i) strong healthy immune system, (ii) healthy organism with evanescent immune cells, (iii) chronic infections, (iv) strong infections, (v) cancer, (vi) critically ill state and (vii) death. The analysis of stability conditions demonstrates that these seven states depend on the balance between the robustness of the immune system and the influx of pathogens.
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