Abstracts

Abstracts

Aniello Lampo

UC3M

Structural dynamics of plant-pollinator mutualistic networks

The discourse surrounding the structured interactions of species within mutualistic communities predominantly centers on modularity and nestedness. The former is known to enhance the stability of communities while the latter is related to their feasibility, albeit compromising the stability. However, their joint structural emergence poses challenges and consequently limits the inheritance of their respective dynamical properties. We hypothesize

that compound structures, combining modules with internal nested organization, may offer valuable insights in this debate. Analyzing the temporal structural dynamics of 20 plant-pollinator interaction networks and find that compound structures are highly prevalent during the peak of the season with approximately 50% of the communities modifying their predominant structural pattern throughout the year. Motivated by these empirical findings

emphasizing the temporal plasticity of plant-pollinator networks, we synthetically investigate the dynamics of the structural patterns observed in the data across two control parameters—community size and connectance levels—mimicking the progression of the pollination season. Our analysis reveals contrasting impacts on the stability and feasibility of species’ interaction networks. We characterize the consistent relationship between network structure and stability, which follows a monotonic pattern. But, in terms of feasibility, we observe non-linear relationships. Compound structures exhibit a favorable balance between stability and feasibility, particularly in middle-sized ecological communities, suggesting they may effectively navigate the simultaneous requirements of

stability and feasibility. These findings allow us to resolve that the assembly process of mutualistic communities may be driven by the delicate balance between multiple properties, rather than the dominance of a single property.

Chantal Valeriani

UCM

Collective behavior of bacteria: from confined motion to biofilm formation

Self-generated motion is ubiquitous in Nature: microorganisms are required to move to execute vital biological functions.  One of the most paradigmatic Active Matter system is a suspension of bacteria, whose locomotion mechanism and collective behaviour are highly influenced by the supporting medium.

Asymmetric obstacles can be used to direct bacteria’s motion and induce sorting. 

This physical effect has been observed in Nature in carnivorous plants and can be reproduced in the lab with designed microchannels.

However, bacteria in Nature can be rarely found in their planktonic state and are rather embedded in biofilms, whose mechanical features are strongly affected by external stimuli.

Caterina Landi

UCM

Self-Assembly of Active Bifunctional Patchy Particles

Colloidal self-assembly represents one of the most exciting topics in soft matter. In this context, activity emerges as a powerful tool, as it gives rise to a remarkable range of interesting collective behaviors. While most research on active colloidal matter has focused on suspensions of active particles interacting via isotropic potentials, the field has recently branched out to explore the interplay between activity and anisotropic interactions.

Considering the ‘‘patchy particle’’ model as a practical model to study anisotropic interactions, we intend to investigate a system made of active patchy particles that form linear chains.

With the intent of exploring the polymerization of active patchy particles in linear chains, we study a two-dimensional suspension of active bifunctional Brownian particles (ABBPs).

At all studied temperatures and densities, ABBPs self-assemble in aggregating chains, in contrast to the uniformly space-distributed chains observed in the corresponding passive systems. The main effect of activity in the system, other than inducing chain aggregation, is to reduce the average chain length and to increase the probability of two ABBPs to bond with the same orientation.

 Interestingly, at the lowest temperature studied, as density increases, we observe a novel state, which we term MIPS (Motility-Induced Spiral Phase). In this state, chains aggregate to form spirals characterized by a finite angular velocity. On the contrary, at the highest temperature, density, and activity chains aggregate forming a different novel state characterized by a compact and hexagonally ordered structure, both translating and rotating. The rotation arises from an effective torque generated by the presence of competing domains where particles self-propel in the same direction.

Pablo Catalán

UC3M

Optimization of Sequential Therapies to Maximize Extinction of Resistant Bacteria through Collateral Sensitivity

The development of bacterial resistance to antibiotics poses a critical challenge in infection treatment. In this work, we present a stochastic model describing the population dynamics of bacteria under antibiotic therapies, considering a population structured into four genotypes: susceptible bacteria, bacteria resistant to one antibiotic, bacteria resistant to the other, and bacteria resistant to both. This model incorporates the phenomenon of collateral sensitivity, where resistance to one antibiotic increases susceptibility to another. We analyze the impact of alternating sequential therapies and find that the presence of collateral sensitivity is essential to identify optimal switching times between treatments that maximize the probability of resistant population extinction. Without collateral sensitivity, these optimal times cannot be determined. Furthermore, we show that the optimal times are critically dependent on the therapy's final duration, providing a theoretical framework to guide therapeutic strategies that exploit collateral sensitivity as a tool to combat resistance.

Pilar Guerrero

UC3M

Modelling the Influence of Loss of E-Catherin and Stroma Attachment in Cancer Cell Invasion.

Hereditary diffuse gastric cancer (HDGC) evolution depends on E-cadherin dysfunction [2, 1]. We demonstrate experimentally that the low E-cadherin expression strongly correlates with basal epithelial extrusion. Using three different mathematical models, we explore computationally how differential adhesion of the mutated cell to the ECM fibres and epithelial tissue geometry regulates basal extrusion. We introduce a novel phase-field model to describe epithelial tissue dynamics and its interaction with the ECM, and use this model in tandem with a vertex model and a dissipative particle dynamics simulation of epithelial tissues. In these simulations, we observe that the adhesion to the matrix strongly accelerates basal extrusion, thus expecting that, in the progression of HDGC, an increase in cell-ECM adhesion will play an important role. We further observe that the curvature of the epithelial tissue, which increases the mutated cell exposure to the ECM and the mechanical stress imposed on the cell, facilitates the initial steps of cell extravasation. The implementation of different mathematical modelling strategies that yield comparable results strengthens the confidence in these predictions, thus suggesting novel avenues to explore experimentally [3].

REFERENCES

[1] U. Carvallaro, G. Christofor. Nature Publishing Group 2, pp. 118-132 (2004). DOI: 10.1038/nrc1276

[2] B. Angst, C. Marcozzi, and M. Magee. The Company of Biologists Ltd 4, pp 629-641.  DOI: 10.1242/jcs.114.4.629

[3] S. Melo, P. Guerrero, M. Moreira, J. R. Bordin, F. Carneiro, P. Carneiro, M. B. Dias, J. Carvalho, J. Figueiredo, R. Seruca, R. Travasso. Communications Biology 6, 1132 (2023). D.O.I: 10.1038/s42003-023-05482-x

Luis Dinis

UCM

Do living organisms care about fluctuations?

Most biological systems can cope with some degree of variation of their conditions. The problem becomes more acute in the case of unpredictably varying environments. In some cases, it may be advantageous for a growing population to accept a reduction of its short-term reproductive success in exchange for long-term risk reduction. This phenomenon, called bet-hedging, protects individuals from potential damages associated with environmental variations. It is an important topic in biology which is associated with a number of phenomena such as species polymorphism, antibiotic resistance of bacteria or the resistance of cancer cells to anti-cancer drugs, or more generally to the phenomenon of adaptation. Bet-hedging is also a widely studied phenomenon in ecology. For instance, plants use it to delay germination as a form of insurance policy against potentially damaging environmental fluctuations. 

In this talk I will present some of the results of my ongoing research on bet-hedging in growing populations and on adaptation in systems with varying environments, developed during the past years. 

Rodrigo Fernández-Quevedo García

UCM

Dynamics and rupture of doped Motility Induced Phase Separation

Adding a small amount of passive (Brownian) particles to a two-dimensional dense suspension of repulsive Active Brownian Particles does not affect the appearance of a Motility-Induced Phase Separation into a dense and a dilute phase, caused by the persistence of the active particles' direction of motion.

Unlike a purely active suspension, the dense slab formed in an elongated system of a passive-active mixture is characterized by a stable and well-defined propagation of the interfaces because of the symmetry breaking caused by the depletion of passive particles on one side of the slab. 

Our work aimed at  investigating this structure via average density profile calculations, revealing an asymmetry between the two interfaces, and enabling a kinetic analysis of the slab movement. 

This analysis supported the characterization  of  the dense slab's movement as induced by a source/sink effect or by the presence of currents within the system. 

Furthermore, significant fluctuations appear, capable of either disrupting the slab or abruptly changing its direction of motion due to the nucleation of low-density bubbles within the slab.

Saúl Ares

CNB

La Cúpula de Norton: Indeterminismo y Límites de la Mecánica Clásica

El problema de "La Cúpula de Norton" plantea un desafío único a la mecánica de Newton, al describir un sistema en el que una partícula en reposo puede comenzar a moverse espontáneamente, aparentemente sin causa. Este fenómeno pone en cuestión la visión determinista de la física clásica y abre interrogantes sobre los fundamentos de la causalidad en los sistemas dinámicos. Vídeo sobre el problema, con referencias en la descripción: https://youtu.be/EjZB81jCGj4?si=UgAR0dujE769mWCo

En esta charla, se presentará el problema en detalle, desde su formulación matemática original hasta sus implicaciones conceptuales. Además, se ampliarán las cuentas y se abordará el problema desde formalismos alternativos que permitan explorar nuevas perspectivas y enriquecer la discusión. El objetivo es fomentar un debate en torno a los límites de los modelos clásicos y su relación con nuestra comprensión de las leyes físicas.

Adolfo Alsina

URJC

Model-based inference of cell cycle dynamics captures alterations of the DNA replication programme

The cell cycle of eukaryotic cells is composed of several steps that need to be carefully orchestrated and completed in a timely manner. Alterations of the cell cycle dynamics have been linked with the onset of several diseases, highlighting the need for quantitative approaches to infer cell cycle dynamics. Here, using a combination of high-throughput experimental data and theoretical modelling, we develop a model-based approach to infer cell cycle dynamics from flow cytometry data of asynchronous cell populations. We model the distribution of DNA content across a population as resulting from a combination of noisy measurements of the DNA content of single cells and the age structure of the population. Our approach accurately extracts interpretable parameters corresponding to the relative timings of the main cell cycle phases and the mode of replication from asynchronous DNA profiles. To showcase the applicability of our approach, we first apply it to the yeast deletion collection, a comprehensive dataset of all non-essential single-gene budding yeast mutants. We show that our method captures not only changes of the length of each cell cycle phase but also alterations in the underlying DNA replication dynamics. Furthermore, by applying our method to previously published mammalian cell data, we show that we can reproduce the replication dynamics inferred by nucleotide incorporation experiments from DNA content distributions alone. Taken together, our work provides a robust, scalable framework to infer cell cycle dynamics from flow cytometry data that can be used to characterise alterations of the replication programme.

Sara Ghivarello

UC3M

Coevolution of individual perception and cooperative behaviour in the Norm Compliance Dilemma 

Mathematical epidemiology has, now more than ever, attracted great attention in the scientific community. However, little exploration has been done in the direction of modelling human behavioural response when facing an epidemic outbreak. In this context, individuals may employ containment measures to prevent the disease spreading, i.e. providing a benefit to the entire population, at a cost that is heterogeneously perceived by each individual. In our work we study the coevolution of cooperative behaviour and individual perception through the lens of evolutionary game theory, considering the adoption of a disease containment measure as a cooperative act. We introduce this game-theoretical framework as the "Norm Compliance Dilemma", where the evolution of agents’ behaviors depends on their distinct, time-evolving perceptions. Starting from a simplified model of a well-mixed infinite population having homogeneous perceptions, we studied and analytically solved a system of ordinary differential equations to predict the game equilibria.

Subsequently, we compared the theoretical results with those obtained in finite populations having heterogeneous individual perceptions and organised in network structures. We show that the disease prevalence promotes cooperation, finding that this result is qualitatively confirmed regardless of the spatial arrangement of individuals or the heterogeneity of their perception. On the other hand, networked structures may hinder and slow down the evolution of cooperation with respect to well-mixed populations. Our model offers an alternative and general methodology to study heterogeneous coevolving perceptions which can be applied to different types of epidemic spreading 

and norm compliance scenarios.