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Jaewook Joo

Publications and source records attributed to Jaewook Joo.

16 recordsLinked to original sources
arXiv2023

Rigorous results of limiting behaviors of total tumor size under cyclic intermittent therapy for the system of reversible phenotype-switchable tumor cells

We are keenly interested in finding the limiting behaviors of total tumor size when tumor cells are subject to the periodic repetition of therapy and rest periods, called intermittent cyclic therapy. We hypothesize that each tumor cell can take either therapy-sensitive or therapy-tolerant phenotype, its phenotype transition is mainly driven by the presence or absence of environmental stress, and such a transition is reversible. Even though those aforementioned hypotheses make the model system simple, most of prior papers attempted to numerically find the optimal therapeutic scheduling that minimizes total tumor size, and there is no rigorous proof of the limiting behaviors of total tumor size to my knowledge. Here we present such long-waited mathematically rigorous results. In the first part of the paper, we present the derivation of total tumor size reduction criterion and prove two theorems of two different limiting behaviors of total tumor size under two different therapy strategies, one leading to an asymptotic finite tumor size according to an iterated map method and anther leading to asymptotically diminishing of total tumor size. In the second part of the paper, we discuss the effects of the intratumoral competition between sensitive and tolerant phenotypes on the total tumor size reduction criterion.

q-bio.TO↗
arXiv2014

Design principles of noise-induced oscillation in biochemical reaction networks: II. coupled positive and negative feedback loops

According to the chemical reaction network theory, the topology of a certain class of chemical reaction networks, regardless of the kinetic details, sets a limit on the dynamical properties that a particular network can potentially admit; the structure of a network predetermines the dynamic capacity of the network. We note that stochastic fluctuations can possibly confer a new dynamical capability to a network. Thus, it is of tremendous value to understand and be able to control the landscape of stochastic dynamical behaviors of a biochemical reaction network as a function of network architecture. Here we investigate such a case where stochastic fluctuations can give rise to the new capability of noise-induced oscillation in a subset of biochemical reaction networks, the networks with only three biochemical species whose reactions are governed by mass action kinetics and with the coupling of positive and negative feedback loops. We model the networks with the master equations and approximate them, using the linear noise approximation. For each network, we read the signal-to-noise ratio value, an indicator of amplified and coherent noise-induced oscillation, off from the analytically derived power spectra. We classify the networks into three performance groups based on the average values of the signal-to-noise ratio and the robustness. We identify the common network architecture among the networks belonging to the same performance group, from which we learn that the coupling of negative and positive feedback loops generally enhance the noise-induced oscillation performance better than the negative feedback loops alone. The performance of networks also depends on the relative size of the positive and negative feedback loops; the networks with the bigger positive and smaller negative feedbacks are much worse oscillators than the networks with only negative feedback loops.

q-bio.MN↗
arXiv2011

Identification of network motifs capable of frequency-tunable and robust oscillation

Oscillation has an important role in bio-dynamical systems such as circadian rhythms and eukaryotic cell cycle. John Tyson et. al. in Nature Review Mol Cell Biol 2008 examined a limited number of network topologies consisting of three nodes and four or fewer edges and identified the network design principles of biochemical oscillations. Tsai et. al. in Science 2008 studied three different network motifs, namely a negative feedback loop, coupled negative feedback loops, and coupled positive and negative feedback loops, and found that the interconnected positive and negative feedback loops are capable of generating frequency-tunable oscillations. We enumerate 249 topologically unique network architectures consisting of three nodes and at least three cyclic inhibitory edges, and identify network architectural commonalities among three functional groups: (1) most frequency-tunable yet less robust oscillators, (2) least frequency-tunable and least robust oscillators, and (3) less frequency-tunable yet most robust oscillators. We find that Frequency-tunable networks cannot simultaneously express high robustness, indicating a tradeoff between frequency tunability and robustness.

q-bio.MN↗
arXiv2011

Network architectural conditions for prominent and robust stochastic oscillations

Understanding relationship between noisy dynamics and biological network architecture is a fundamentally important question, particularly in order to elucidate how cells encode and process information. We analytically and numerically investigate general network architectural conditions that are necessary to generate stochastic amplified and coherent oscillations. We enumerate all possible topologies of coupled negative feedbacks in the underlying biochemical networks with three components, negative feedback loops, and mass action kinetics. Using the linear noise approximation to analytically obtain the time-dependent solution of the master equation and derive the algebraic expression of power spectra, we find that (a) all networks with coupled negative feedbacks are capable of generating stochastic amplified and coherent oscillations; (b) networks with a single negative feedback are better stochastic amplified and coherent oscillators than those with multiple coupled negative feedbacks; (c) multiple timescale difference among the kinetic rate constants is required for stochastic amplified and coherent oscillations.

q-bio.MN↗
arXiv2010

Linear noise approximation of noise-induced oscillation in NF-κB signaling network

NF-κB, one of key regulators of inflammation, apoptosis, and differentiation, was found to have noisy oscillatory shuttling between the nucleus and the cytoplasm in single cells when cells are stimulated by cytokine TNFα. We present the analytical analysis which uncovers the underlying physical mechanisms of this spectacular noise-induced transition in biological networks. Starting with the master equation describing both signaling and transcription events in NF-κB signaling network, we derived the macroscopic and the Fokker-Planck equations by using van Kampen's sysem size expansion. Using the noise-induced oscillatory signatures present in the power spectrum, we constructed the two-dimensional phase diagram where the noise-induced oscillation emerges in the dynamically stable parameter space.

q-bio.MN↗
arXiv2010

Sensitivity analysis of a computational model of the IKK-NF-κB-IκBα-A20 signal transduction network

The NF-κB signaling network plays an important role in many different compartments of the immune system during immune activation. Using a computational model of the NF-κB signaling network involving two negative regulators, IκBα and A20, we performed sensitivity analyses with three different sampling methods and present a ranking of the kinetic rate variables by the strength of their influence on the NF-κB signaling response. We also present a classification of temporal response profiles of nuclear NF-κB concentration into six clusters, which can be regrouped to three biologically relevant clusters. Lastly, based upon the ranking, we constructed a reduced network of the IKK-NF-κB-IκBα-A20 signal transduction.

q-bio.QM↗
arXiv2010

Noise-induced oscillatory shuttling of NF-κB in a two compartment IKK-NF-κB-IκB-A20 signaling model

NF-κB is a pleiotropic protein whose nucleo-cytoplasmic trafficking is tightly regulated by multiple negative feedback loops embedded in the NF-κB signaling network and contributes to diverse gene expression profiles important in immune cell differentiation, cell apoptosis, and innate immunity. The intracellular signaling processes and their control mechanisms, however, are susceptible to both extrinsic and intrinsic noise. In this article, we present numerical evidence for a universal dynamic behavior of NF-κB, namely oscillatory nucleo-cytoplasmic shuttling, due to the fundamentally stochastic nature of the NF-κB signaling network. We simulated the effect of extrinsic noise with a deterministic ODE model, using a statistical ensemble approach, generating many copies of the signaling network with different kinetic rates sampled from a biologically feasible parameter space. We modeled the effect of intrinsic noise by simulating the same networks stochastically using the Gillespie algorithm. The results demonstrate that extrinsic noise diversifies the shuttling patterns of NF-κB response, whereas intrinsic noise induces oscillatory behavior in many of the otherwise non-oscillatory patterns. We identify two key model parameters which significantly affect the NF-κB dynamic response and deduce a two-dimensional phase-diagram of the NF-κB response as a function of these parameters. We conclude that if single-cell experiments are performed, a rich variety of NF-κB response will be observed, even if population-level experiments, which average response over large numbers of cells, do not evidence oscillatory behavior.

q-bio.MN↗
arXiv2010

Modeling the effects of cymene on the distribution of germination and growth of Beauveria bassiana

Essential oils have antifungal and antipathogenic effects and therefore are targets in plant pathology research for their potential uses as natural substitutes for inorganic plant pesticides. Beauveria bassiana, an entomopathogenic fungus, can endophytically colonize a vast number of plant species and trigger induced systemic resistance against plant pathogens. Spore germination is the most vulnerable in the fungal life cycle and is therefore a good candidate for monitoring the effect of essential oils on the growth of B. bassiana. Percentage germination of fungal spores and length of germination tubes were recorded from experiments. A mathematical model that was able to capture the effects of cymene, an essential oil produced by Monarda, on the germination and growth was developed. This is the first report of a model for the impact of essential oils on B. bassiana spore germination.

q-bio.QM↗
arXiv2010

Novel statistical ensemble analysis for simulating extrinsic noise-driven response in NF-κB signaling network

Cellular responses in the single cells are known to be highly heterogeneous and individualistic due to the strong influence by extrinsic and intrinsic noise. Here, we are concerned about how to model the extrinsic noise-induced heterogeneous response in the single cells under the constraints of experimentally obtained population-averaged response, but without much detailed kinetic information. We propose a novel statistical ensemble scheme where extrinsic noise is regarded as fluctuations in the values of kinetic parameters and such fluctuations are modeled by randomly sampling the kinetic rate constants from a uniform distribution. We consider a large number of signaling system replicates, each of which has the same network topology, but a uniquely different set of kinetic rate constants. A protein dynamic response from each replicate should represent the dynamics in a single cell and the statistical ensemble average should be regarded as a population-level response averaged over a population of the cells. We devise an optimization algorithm to find the correct uniform distribution of the network parameters, which produces the correct statistical distribution of the response whose ensemble average and distribution agree well with the population-level experimental data and the experimentally observed heterogeneity. We apply this statistical ensemble analysis to a NF-κB signaling system and (1) predict the distributions of the heterogeneous NF-κB (either oscillatory or non-oscillatory) dynamic patterns and of the dynamic features (e.g., period), (2) predict that both the distribution and the statistical ensemble average of the NF-κB dynamic response depends sensitively on the dosage of stimulant, and lastly (3) demonstrate the sigmoidally shaped dose-response from the statistical ensemble average and the individual replicates.

q-bio.MN↗
arXiv2006

Effects of Noise on Ecological Invasion Processes: Bacteriophage-mediated Competition in Bacteria

Pathogen-mediated competition, through which an invasive species carrying and transmitting a pathogen can be a superior competitor to a more vulnerable resident species, is one of the principle driving forces influencing biodiversity in nature. Using an experimental system of bacteriophage-mediated competition in bacterial populations and a deterministic model, we have shown in [Joo et al 2005] that the competitive advantage conferred by the phage depends only on the relative phage pathology and is independent of the initial phage concentration and other phage and host parameters such as the infection-causing contact rate, the spontaneous and infection-induced lysis rates, and the phage burst size. Here we investigate the effects of stochastic fluctuations on bacterial invasion facilitated by bacteriophage, and examine the validity of the deterministic approach. We use both numerical and analytical methods of stochastic processes to identify the source of noise and assess its magnitude. We show that the conclusions obtained from the deterministic model are robust against stochastic fluctuations, yet deviations become prominently large when the phage are more pathological to the invading bacterial strain.

q-bio.PE↗
arXiv2005

Population Dynamics in Spatially Heterogeneous Systems with Drift: the generalized contact process

We investigate the time evolution and stationary states of a stochastic, spatially discrete, population model (contact process) with spatial heterogeneity and imposed drift (wind) in one- and two-dimensions. We consider in particular a situation in which space is divided into two regions: an oasis and a desert (low and high death rates). Carrying out computer simulations we find that the population in the (quasi) stationary state will be zero, localized, or delocalized, depending on the values of the drift and other parameters. The phase diagram is similar to that obtained by Nelson and coworkers from a deterministic, spatially continuous model of a bacterial population undergoing convection in a heterogeneous medium.

cond-mat.stat-mech↗
arXiv2005

Bacteriophage-mediated competition in Bordetella bacteria

Apparent competition between species is believed to be one of the principle driving forces that structure ecological communities, although the precise mecha nisms have yet to be characterized. Here we develop a model system that isolates phage-mediated interactions by neutralizing resource competition using two genetically identical Bordetella bronchiseptica strains that differ only in that one is the carrier of a phage and the other is susceptible to the phage. We observe and quantify the competitive advantage of the bacterial strain bearing the prophage in both invading and in resisting invasion by bacteria susceptible to the phage, and use our measurements to develop a mathematical model of phage-mediated competition. The model predicts, and experimental evidence confirms, that the competitive advantage conferred by the phage depends only on the relative phage pathology and is independent of other phage and host parameters. This work combines experimental and mathematical approaches to the study of phage-driven competition, and provides an experimentally tested framework for evaluation of the effects of pathogens/parasites on interspecific competition.

q-bio.PE↗
arXiv2004

Pair approximation of the stochastic susceptible-infected-recovered-susceptible epidemic model on the hypercubic lattice

We investigate the time-evolution and steady states of the stochastic susceptible-infected-recovered-susceptible(SIRS) epidemic model on one- and two- dimensional lattices. We compare the behavior of this system, obtained from computer simulations, with those obtained from the mean-field approximation(MFA) and pair-approximation(PA). The former(latter) approximates higher order moments in terms of first(second) order ones. We find that the PA gives consistently better results than the MFA. In one dimension the improvement is even qualitative.

q-bio.PE↗
arXiv2004

Behavior of susceptible-infected-susceptible epidemics on heterogeneous networks with saturation

We investigate saturation effects in susceptible-infected-susceptible (SIS) models of the spread of epidemics in heterogeneous populations. The structure of interactions in the population is represented by networks with connectivity distribution $P(k)$,including scale-free(SF) networks with power law distributions $P(k)\sim k^{-γ}$. Considering cases where the transmission of infection between nodes depends on their connectivity, we introduce a saturation function $C(k)$ which reduces the infection transmission rate $λ$ across an edge going from a node with high connectivity $k$. A mean field approximation with the neglect of degree-degree correlation then leads to a finite threshold $λ_{c}>0$ for SF networks with $2<γ\leq 3$. We also find, in this approximation, the fraction of infected individuals among those with degree $k$ for $λ$ close to $λ_{c}$. We investigate via computer simulation the contact process on a heterogeneous regular lattice and compare the results with those obtained from mean field theory with and without neglect of degree-degree correlations.

cond-mat.stat-mech↗
arXiv2000

Quantum Monte Carlo calculation of the finite temperature Mott-Hubbard transition

We present clear numerical evidence for the coexistence of metallic and insulating dynamical mean field theory(DMFT) solutions in a half-filled single-band Hubbard model with bare semicircular density of states at finite temperatures. Quantum Monte Carlo(QMC) method is used to solve the DMFT equations. We discuss important technical aspects of the DMFT-QMC which need to be taken into account in order to obtain the reliable results near the coexistence region. Among them are the critical slowing down of the iterative solutions near phase boundaries, the convergence criteria for the DMFT iterations, the interpolation of the discretized Green's function and the reduction of QMC statistical and systematic errors. Comparison of our results with those of other numerical methods is presented in a phase diagram.

cond-mat.str-el↗