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Roberto Chignola

Publications and source records attributed to Roberto Chignola.

16 recordsLinked to original sources
arXiv2022

Efficient ensemble stochastic algorithms for agent-based models with spatial predator-prey dynamics

Experiments in predator-prey systems show the emergence of long-term cycles. Deterministic model typically fails in capturing these behaviors, which emerge from the microscopic interplay of individual based dynamics and stochastic effects. However, simulating stochastic individual based models can be extremely demanding, especially when the sample size is large. Hence, we propose an alternative simulation approach, whose computation cost is lower than the one of the classic stochastic algorithms. First, we describe the agent-based model with predator-prey dynamics, and its mean-field approximation. Then, we provide a consistency result for the novel stochastic algorithm at the microscopic and mesoscopic scale. Finally, we perform different numerical experiments in order to test the efficiency of the proposed algorithm, focusing also on the analysis of the different nature of oscillations between mean-field and stochastic simulations.

math.NA↗
arXiv2019

Fine-grained simulations of the microenvironment of vascularized tumours

One of many important features of the tumour microenvironment is that it is a place of active Darwinian selection where different tumour clones become adapted to the variety of ecological niches that make up the microenvironment. These evolutionary processes turn the microenvironment into a powerful source of tumour heterogeneity and contribute to the development of drug resistance in cancer. Here, we describe a computational tool to study the ecology of the microenvironment and report results about the ecology of the tumour microenvironment and its evolutionary dynamics.

physics.bio-ph↗
arXiv2012

Bridging the gap between the micro- and the macro-world of tumors

At present it is still quite difficult to match the vast knowledge on the behavior of individual tumor cells with macroscopic measurements on clinical tumors. On the modeling side, we already know how to deal with many molecular pathways and cellular events, using systems of differential equations and other modeling tools, and ideally, we should be able to extend such a mathematical description up to the level of large tumor masses. An extended model should thus help us forecast the behavior of large tumors from our basic knowledge of microscopic processes. Unfortunately, the complexity of these processes makes it very difficult -- probably impossible -- to develop comprehensive analytical models. We try to bridge the gap with a simulation program which is based on basic biochemical and biophysical processes -- thereby building an effective computational model -- and in this paper we describe its structure, endeavoring to make the description sufficiently detailed and yet understandable.

q-bio.TO↗
arXiv2010

Computational challenges of tumor spheroid modeling

The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we put forward general considerations that apply to any fine-grained numerical model of tumors. We discuss ways to bypass computational limitations and discuss our incremental approach, where each step is validated by experimental observations on a quantitative basis. We present a few results on the growth of tumor cells in closed and open environments and of tumor spheroids. This study suggests new ways to explore the initial growth phase of solid tumors and to optimize anti-tumor treatments.

q-bio.TO↗
arXiv2010

Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids

Multicellular tumor spheroids are an important {\it in vitro} model of the pre-vascular phase of solid tumors, for sizes well below the diagnostic limit: therefore a biophysical model of spheroids has the ability to shed light on the internal workings and organization of tumors at a critical phase of their development. To this end, we have developed a computer program that integrates the behavior of individual cells and their interactions with other cells and the surrounding environment. It is based on a quantitative description of metabolism, growth, proliferation and death of single tumor cells, and on equations that model biochemical and mechanical cell-cell and cell-environment interactions. The program reproduces existing experimental data on spheroids, and yields unique views of their microenvironment. Simulations show complex internal flows and motions of nutrients, metabolites and cells, that are otherwise unobservable with current experimental techniques, and give novel clues on tumor development and strong hints for future therapies.

q-bio.TO↗
arXiv2009

Precision and Stability Issues in VBL, the Virtual Biophysics Lab simulation program

The network of biochemical reactions inside living organisms is characterized by an overwhelming complexity which stems from the sheer number of reactions and from the complicated topology of biochemical cycles. However the high speed of computers and the sophisticated computational methods that are available today are powerful tools that allow the numerical exploration of these exceedingly interesting dynamical systems. We are now developing a program, the Virtual Biophysics Lab (VBL), that simulates tumor spheroids, and which includes a reduced - but still quite complex - description of the biochemistry of individual cells, plus many diffusion processes that bring oxygen and nutrients into cells and metabolites into the environment. Each simulation step requires the integration of nonlinear differential equations that describe the individual cell's clockwork and the integration of the diffusion equations. These integrations are carried out under widely different conditions, in a changing environment, and for this reason they need integrators that are both unconditionally stable and that do not display unwanted algorithmic artifacts. These conditions are not always fulfilled in the existing literature, and we feel that a review of the underlying mathematical principles may be important not just for us but for other workers in the field of system biology as well.

physics.bio-ph↗
arXiv2009

Balance between cell survival and death: a minimal quantitative model of tumor necrosis factor alpha cytotoxicity

Tumor Necrosis Factor alpha (TNF) initiates a complex series of biochemical events in the cell upon binding to its type R1 receptor (TNF-R1). Recent experimental work has unravelled the molecular regulation of the recruitment of initial signaling complexes that lead either to cell survival or death. Survival signals are activated by direct binding of TNF to TNF-R1 at the cell membrane whereas apoptotic signals by endocytosed TNF/TNF-R1 complexes. Here we investigate these aspects by developing a quantitative mathematical model of TNF binding, internalization and intracellular signaling. Model outputs compare favorably with experimental data and allow to compute TNF-mediated cytotoxicity as observed in different cell systems. We extensively study the space of parameters to show that the model is structurally stable and robust over a broad range of parameter values. Thus, our model is suitable for implementation in multi-scale simulation programs that are presently under development to study the behavior of large tumor cell populations.

q-bio.MN↗
arXiv2009

Dynamics of intracellular Ca$^{2+}$ oscillations in the presence of multisite Ca$^{2+}$-binding proteins

We study the dynamics of intracellular calcium oscillations in the presence of proteins that bind calcium on multiple sites and that are generally believed to act as passive calcium buffers in cells. We find that multisite calcium-binding proteins set a sharp threshold for calcium oscillations. Even with high concentrations of calcium-binding proteins, internal noise, which shows up spontaneously in cells in the process of calcium wave formation, can lead to self-oscillations. This produces oscillatory behaviors strikingly similar to those observed in real cells. In addition, for given intracellular concentrations of both calcium and calcium-binding proteins the regularity of these oscillations changes and reaches a maximum as a function noise variance, and the overall system dynamics displays stochastic coherence. We conclude that calcium-binding proteins may have an important and active role in cellular communication.

q-bio.SC↗
arXiv2009

Numerical integration methods for large-scale biophysical simulations

Simulations of biophysical systems inevitably include steps that correspond to time integrations of ordinary differential equations. These equations are often related to enzyme action in the synthesis and destruction of molecular species, and in the regulation of transport of molecules into and out of the cell or cellular compartments. Enzyme action is almost invariably modeled with the quasi-steady-state Michaelis-Menten formula or its close relative, the Hill formula: this description leads to systems of equations that may be stiff and hard to integrate, and poses unusual computational challenges in simulations where a smooth evolution is interrupted by the discrete events that mark the cells' lives. This is the case of a numerical model (Virtual Biophysics Lab - VBL) that we are developing to simulate the growth of three-dimensional tumor cell aggregates (spheroids). The program must be robust and stable, and must be able to accept frequent changes in the underlying theoretical model: here we study the applicability of known integration methods to this unusual context and we describe the results of numerical tests in situations similar to those found in actual simulations.

physics.bio-ph↗
arXiv2007

Ab initio phenomenological simulation of the growth of large tumor cell populations

In a previous paper we have introduced a phenomenological model of cell metabolism and of the cell cycle to simulate the behavior of large tumor cell populations (Chignola R and Milotti E, Phys. Biol. 2 (2005) 8-22). Here we describe a refined and extended version of the model that includes some of the complex interactions between cells and their surrounding environment. The present version takes into consideration several additional energy-consuming biochemical pathways such as protein and DNA synthesis, the tuning of extracellular pH and of the cell membrane potential. The control of the cell cycle - that was previously modeled by means of ad hoc thresholds - has been directly addressed here by considering checkpoints from proteins that act as targets for phosphorylation on multiple sites. As simulated cells grow, they can now modify the chemical composition of the surrounding environment which in turn acts as a feedback mechanism to tune cell metabolism and hence cell proliferation: in this way we obtain growth curves that match quite well those observed in vitro with human leukemia cell lines. The model is strongly constrained and returns results that can be directly compared with actual experiments, because it uses parameter values in narrow ranges estimated from experimental data, and in perspective we hope to utilize it to develop in silico studies of the growth of very large tumor cell populations (10^6 cells or more) and to support experimental research. In particular, the program is used here to make predictions on the behaviour of cells grown in a glucose-poor medium: these predictions are confirmed by experimental observation.

physics.bio-ph↗
arXiv2007

Dynamical hysteresis in multisite protein modification

Multisite protein modification is a ubiquitous mechanism utilized by cells to control protein functions. We have recently proposed a dynamical description of multisite protein modification which embodies all the essential features of the process (E. Milotti, A. Del Fabbro, C. Dalla Pellegrina, and R. Chignola, Physica A, in press), and we have used this model to analyze the stability and the time-scales of this mechanism. The same model can be used to understand how the system responds to stimuli: here we show that it displays frequency-dependent dynamical hysteresis. This behavior closely parallels -- with the due differences -- what is observed in magnetic systems. By selecting model parameters that span the known biological ranges, we find that the frequency-dependent features cover the band of the observed oscillations of molecular intracellular signals, and this suggests that this mechanism may have an important role in cellular information processing.

physics.bio-ph↗
arXiv2006

Dynamics of allosteric action in multisite protein modification

Protein functions in cells may be activated or modified by the attachment of several kinds of chemical groups. While protein phosphorylation, i.e. the attachment of a phosphoryl (PO$_3^-$) group, is the most studied form of protein modification, and is known to regulate the functions of many proteins, protein behavior can also be modified by nitrosylation, acetylation, methylation, etc. A protein can have multiple modification sites, and display some form of transition only when enough sites are modified. In a previous paper we have modeled the generic equilibrium properties of multisite protein modification (R.Chignola, C. Dalla Pellegrina, A. Del Fabbro, E.Milotti, Physica A {\bf 371}, 463 (2006)) and we have shown that it can account both for sharp, robust thresholds and for information transfer between processes with widely separated timescales. Here we use the same concepts to expand that analysis starting from a dynamical description of multisite modification: we give analytical results for the basic dynamics and numerical results in an example where the modification chain is cascaded with a Michaelis-Menten step. We modify the dynamics and analyze an example with realistic phosphorylation/dephosphorylation steps, and give numerical evidence of the independence of the allosteric effect from the details of the attachment-detachment processes. We conclude that multisite protein modification is dynamically equivalent to the classic allosteric effect.

physics.bio-ph↗
arXiv2006

Fine-grained Delaunay triangulation in a simulation of tumor spheroid growth

The simulation of many-particle systems often requires the detailed knowledge of proximity relations to reduce computational complexity and to provide a basis for specific calculations. Here we describe the basic scheme of a simulator of tumor spheroid growth: the calculation of mechanical interactions between cells and of the concentrations of diffusing chemicals requires a backbone provided by the Delaunay triangulation and the volumes of the associated Voronoi regions. Thus the Delaunay triangulation provides both the proximity relations needed to reduce the computational complexity and the basic structures that are needed to carry out the calculation of the biochemical interactions between cells and with the enviroment. A 3D version of the simulator uses the CGAL library as an essential component for the efficient computation of the Delaunay triangulation and of the Voronoi regions.

physics.bio-ph↗
arXiv2006

Thresholds, long delays and stability from generalized allosteric effect in protein networks

Post-transductional modifications tune the functions of proteins and regulate the collective dynamics of biochemical networks that determine how cells respond to environmental signals. For example, protein phosphorylation and nitrosylation are well-known to play a pivotal role in the intracellular transduction of activation and death signals. A protein can have multiple sites where chemical groups can reversibly attach in processes such as phosphorylation or nitrosylation. A microscopic description of these processes must take into account the intrinsic probabilistic nature of the underlying reactions. We apply combinatorial considerations to standard enzyme kinetics and in this way we extend to the dynamic regime a simplified version of the traditional models on the allosteric regulation of protein functions. We link a generic modification chain to a downstream Michaelis-Menten enzymatic reaction and we demonstrate numerically that this accounts both for thresholds and long time delays in the conversion of the substrate by the enzyme. The proposed mechanism is stable and robust and the higher the number of modification sites, the greater the stability. We show that a high number of modification sites converts a fast reaction into a slow process, and the slowing down depends on the number of sites and may span many orders of magnitude; in this way multisite modification of proteins stands out as a general mechanism that allows the transfer of information from the very short time scales of enzyme reactions (milliseconds) to the long time scale of cell response (hours).

q-bio.CB↗
arXiv2005

A phenomenological approach to the simulation of metabolism and proliferation dynamics of large tumour cell populations

A major goal of modern computational biology is to simulate the collective behaviour of large cell populations starting from the intricate web of molecular interactions occurring at the microscopic level. In this paper we describe a simplified model of cell metabolism, growth and proliferation, suitable for inclusion in a multicell simulator, now under development (Chignola R and Milotti E 2004 Physica A 338 261-6). Nutrients regulate the proliferation dynamics of tumor cells which adapt their behaviour to respond to changes in the biochemical composition of the environment. This modeling of nutrient metabolism and cell cycle at a mesoscopic scale level leads to a continuous flow of information between the two disparate spatiotemporal scales of molecular and cellular dynamics that can be simulated with modern computers and tested experimentally.

physics.bio-ph↗