MS05 - ECOP-2
Brutus Buckeye Room (#3044) in The Ohio Union

Mathematical models of community: a journey through the scales

Wednesday, July 19 at 10:30am

SMB2023 SMB2023 Follow Wednesday during the "MS05" time block.
Room assignment: Brutus Buckeye Room (#3044) in The Ohio Union.
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Alexander Browning, Sara Hamis


All biological systems consist of interacting parts. With this minisymposium, we will bring together mathematical models of communities with interacting individuals from various scales: from cell-bacteria interactions, to cell and bacteria communities, to interactions at the macroscale between insects and birds. This minisymposium will stimulate discussion and identify common threads, enabling collaboration between modellers who may not otherwise interact. Through a succession of talks, we will discuss how decisions, actions and interactions on the individual-level affect population level dynamics. Moreover, the talks will exemplify how we can manipulate these individual-level decisions, actions and interactions to steer population dynamics towards desired states.

Pierre Haas

Max Planck Institute for the Physics of Complex Systems (Biological Physics)
"Impossible ecologies: interaction networks and stability of coexistence in ecological communities"
Does an ecological community allow stable coexistence? In particular, what is the interplay between stability of coexistence and the network of competitive, mutualistic, and predator-prey interactions between the species of the community? These are fundamental questions of theoretical ecology, and, since meaningful analytical progress is generally impossible for communities of more than two species, they must be addressed statistically, as pioneered by May four decades ago. In this talk, I will thus show how we addressed this interplay between stability of coexistence and the network of interaction types by sampling Lotka–Volterra model parameters randomly and computing the probability of steady-state coexistence being stable and feasible in Lotka–Volterra dynamics. Surprisingly, our analysis, covering all non-trivial networks of interaction types of N less than or equal to 5 species, revealed 'impossible ecologies', very rare non-trivial networks of interaction types that do not allow stable and feasible steady-state coexistence. I will classify these impossible ecologies, and then prove, somewhat conversely, that any non-trivial ecology that has a possible subecology is itself possible. This theorem highlights the 'irreducible ecologies' that allow stable and feasible steady-state coexistence, but do not contain a possible subecology. I will conclude by showing the classification of all irreducible ecologies of N less than or equal to 5 species which indicates that the proportion of non-trivial ecologies that are irreducible decreases exponentially with the number N of species. Our results thus suggest that interaction networks and stability of coexistence are linked crucially by the very small subset of ecologies that are irreducible.
Additional authors: Yu Meng, Max Planck Institute for the Physics of Complex Systems & Center for Systems Biology Dresden; Carl D. Modes, Max Planck Institute of Molecular Cell Biology and Genetics & Center for Systems Biology Dresden

Aminat Yetunde Saula

University of Bath (Department of Mathematical Sciences)
"Immune cell-bacteria interactions in tuberculosis"
Tuberculosis (TB) is the second deadliest infectious disease in the world after COVID-19, with over 10 million people infected yearly. Although the causative agent - Mycobacterium tuberculosis (Mtb) has long been known, TB bacteria are still able to evade protective immune responses. Herein, as a response to TB infection, immune cells self-organise to form TB granulomas and isolate bacteria within their structures. While TB granulomas are capable of slowing or halting the growth of Mtb, it also provides a survival niche from which bacteria may disseminate. Hence, an increased understanding of the disease in the lung where the bacteria primarily attack is needed. In this work, we integrate the mechanisms involved in immune cell-bacteria interaction in tuberculosis following an established hybrid individual-based model for the development of a continuum model counterpart. The continuum model consists of a system of partial differential equations (PDEs) describing the dynamics of TB granulomas. The numerical and analytical results of the model allow the determination of different conditions under which the infection clears early, stays latent, or progresses to active disease. Our findings are compared to the results obtained using the hybrid individual-based model, where differential equations are used to track the diffusion of molecules and the individual-based model component facilitates the tracking of cellular interaction, thus, allowing the study of localised spatial effects.
Additional authors: Ruth Bowness (University of Bath); Tommaso Lorenzi (Politecnico di Torino); Chandrasekhar Venkataraman (University of Sussex).

Moriah Echlin

Tampere University (Medicine and Health Technology)
"Characterizing the Impact of Communication on Cellular and Collective Behavior Using a Three-Dimensional Multiscale Cellular Model"
Communication between cells enables the coordination that drives structural and functional complexity in biological systems. In both single and multicellular organisms, systems of communication have evolved for a range of purposes, including synchronization of behavior, division of labor, and spatial organization. Synthetic systems are also increasingly being engineered to utilize cell–cell communication. While research has elucidated the form and function of cell–cell communication in many biological systems, our knowledge is still limited by confounding effects from other biological phenomena as well as the bias of evolution. In this work, our goal is to push forward the context-free understanding of what impact cell–cell communication can have on cellular behavior at the cell and population levels. We use an in silico model of 3D multiscale cellular populations, with dynamic intracellular networks interacting via diffusible signals. To explore communication, we focus on two key communication parameters: the effective distance at which cells can interact and the threshold at which the signal receptor is activated. We find that cell–cell communication can be divided into six different categories along the parameter axes, three asocial and three social. We characterize behavior at both the cellular and population level and show clear shifts in behavior between the different categories of communication. With this work, we also highlight the surprising diversity and flexibility in the responses of different cellular backgrounds to the same communication conditions. Thus, we describe some of the effects that cell-cell communication can introduce to cellular populations which can be fine-tuned for function via engineering, artificial modification, or natural selection.
Additional authors: Boris Aguilar ; Ilya Shmulevich ; Juha Kesseli ; Matti Nykter

Daniel Strömbom

Lafayette College (Department of Biology)
"Facilitating the emergence of collective biological controls to combat the spotted lanternfly and similar invasive pests"
The spotted lanternfly (Lycorma delicatula) is an emerging global invasive insect pest. Due to a lack of natural enemies in regions where it is invasive human intervention is required. Standard control measures have been extensively applied but the spread and growth of the population continues, and a recent study indicates that currently used approaches may be futile and suggests that non-standard approaches are necessary. Recently the idea of bird based biological controls has re-emerged and shown to be effective in a number of studies involving native birds and native pests. However, whether birds can be effective in dealing with invasive pests is unclear. In particular, if the invaders are occasionally toxic, it may take many generations before birds or other vertebrates will start contributing to controlling it naturally, if ever. Unless, perhaps, if the birds are effective social learners and the toxicity of the invaders is rare. For example, the Great Tit (Parus major) is an exceptional social learner and have been reported to eat lanternfly that have not fed on their toxicity inducing preferred host plant (Ailanthus altissima), but avoid eating them if they have. Here we introduce a simple mathematical model for social learning in a great tit-like bird to investigate the conditions for the emergence of a collective biological control of a pest that is occasionally toxic, like the lanternfly. We find that the relationship between the social observation rate and the proportion of toxic lanternfly effectively dictate when a collective biological control will emerge, and when it will not. We also implemented the mathematical social learning model into a spatially explicit model of collective motion in bird-like animals to investigate the conditions under which lanternfly eating would emerge in the simulated flocks as a function of lanternfly toxicity. We found that the spatially explicit model reproduces key predictions of the mathematical model over a range of parameters. Our work suggests that social birds may be useful in management of the spotted lanternfly, and that to facilitate the emergence of lanternfly eating communities of social birds, removal of the toxicity inducing preferred host of the lanternfly (Ailanthus altissima) should be a priority.
Additional authors: Amanda Crocker; Grace Tulevech; Autumn Sands; Kelly Ward; Swati Pandey; Alison Gery.

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Annual Meeting for the Society for Mathematical Biology, 2023.