Biology subjects

Araujo, R. P.

Publications and source records attributed to Araujo, R. P..

4 recordsLinked to original sources

bioRxiv2025

Therapeutic targeting of oligodendrocytes in an agent-based model of multiple sclerosis

Multiple sclerosis (MS) is a neurodegenerative disease in which misdirected, persistent activity of the immune system degrades the protective myelin sheaths of nerve axons. Historically, treatment of MS has relied on disease-modifying therapies that involve immunosuppression, such as targeting of the blood-brain barrier (BBB) to restrict lymphocyte movement. New therapeutic ideas in the development pipeline are instead designed to promote populations of myelin producing cells, oligodendrocytes, by exploiting their innate resilience to the stressors of MS or restoring their numbers. Given the significant advancements made in immunological disease understanding due to mathematical and computational modelling, we sought to develop a platform to (1) interrogate our understanding of the neuroimmunological mechanisms driving MS development and (2) examine the impact of different therapeutic strategies. To this end we propose a novel, open-source, agent-based model of lesion development in the CNS. Our model includes crucial populations of T cells, perivascular macrophages, and oligodendrocytes. We examine the sensitivity of the model to key parameters related to disease targets and conclude that lesion stabilisation can be achieved when targeting the integrated stress response of oligodendrocytes. Most significantly, complete prevention of lesion formation is observed when a combination of approved BBB-permeability targeting therapies and integrated-stress response targeting therapies is administered, suggesting the potential to strike a balance between a patients immune inflammation and their reparative capacity. Given that there are many open questions surrounding the etiology and treatment of MS, we hope that this malleable platform serves as a tool to test and generate further hypotheses regarding this disease. Author summaryMultiple sclerosis is a disease that is not yet fully understood and has no cure. Some patient phenotypes see little benefit from current therapeutic interventions besides symptomatic treatment. Typically, MS studies have focused on the prevention of damage to brain tissue. As such, there are unanswered questions about how to reverse the damage in the brain and spinal cord of MS patients caused by immune cells. In light of this there is an urgent need for mathematical modelling of new therapeutic strategies - some of which remain to be clinically examined - shifting the attention from the targeting of aberrant immune activity to the upregulation of resident, reparative cells called oligodendrocytes. Here, we have developed a mathematical model to probe the potential benefits of oligodendrocyte targeted therapies in silico. We focus on T cells as damaging agents and monitor oligodendrocyte function in response to their activity. We show that oligodendrocytes strongly influence the tissues ability to stabilise and even recover under persistent, harmful immune activity. In practice, these therapies could hold the potential to unlock neuroprotection by means of enhanced remyelination.

immunology↗

bioRxiv2024

A distributed integral control mechanism for the regulation of cholesterol concentration in the human retina.

Tight homeostatic control of cholesterol concentration within the complex tissue microenvironment of the retina is a hallmark of the healthy eye. By contrast, dysregulation of the biochemical mechanisms governing retinal cholesterol homeostasis is thought to be a major contributor to the aetiology and progression of age-related macular degeneration (AMD) in the ageing human eye. Although the signalling mechanisms that contribute to cholesterol homeostasis at the cellular level have been studied extensively, there is currently no systems-level description of the molecular interactions that could explain cholesterol homeostasis at the level of the human retina. Here were provide a comprehensive overview of all currently-known molecular-level interactions involved in the regulation of cholesterol across all major compartments of the human retina, encompassing the retinal pigment epithelium (RPE), the photoreceptor cell layer, the Muller cell layer, and Bruchs membrane. We develop a detailed chemical reaction network (CRN) of this complex collection of biochemical interactions, comprising seventy-one (71) molecular species, which we show may be partitioned into ten (10) independent subnetworks. These ten subnetworks work together to confer robust homeostasis on thirteen different forms of cholesterol distributed through distinct cellular compartments of the retina. Remarkably, we provide compelling evidence that three independent antithetic integral controllers are responsible for the tight regulation of endoplasmic reticulum (ER) cholesterol in retinal cells, and that several additional independent mechanisms transfer this homeostatic property to other forms of cholesterol throughout the human retina. Our novel and exquisitely detailed mathematical description of retinal cholesterol regulation provides a framework for considering potential mechanisms of cholesterol dysregulation in the diseased eye, and for the study of potential therapeutic strategies against these pathologies.

systems biology↗

bioRxiv2021

Biological networks with singular Jacobians: their origins and adaptation criteria

This work is focused on Ordinary Differential Equations(ODE)-based models of biochemical systems that possess a singular Jacobian manifesting in non-hyperbolic equilibria. We show that there are several classes of systems that exhibit this behavior: a)systems with monomial-type interaction terms and b)systems with linear or nonlinear conservation laws. While models derived from mass-action principles often present with linear conservation laws stemming from the underlying biologic rationale, nonlinear conservation laws are more subtle and harder to detect. Nevertheless, in both situations the corresponding ODE system will contain non-hyperbolic equilibria. While having a potentially more complex dynamics and falling outside of the scope of existing theoretical frameworks, this class of systems can still exhibit adapting behavior associated with certain nodes and inputs. We derive a generalized adaptation condition that extends to singular systems and is compatible with both single-input/single-output and multiple-input/multiple-output settings. The approach explored herein, based on the notion of Moore-Penrose pseudoinverse, is tested on several synthetic systems that are shown to exhibit homeostatic behavior but are not covered by existing methods. These results highlight the role of the network structure and modeling assumptions when understanding system response to input and can be helpful in discovering intrinsic relationships between the nodes.

systems biology↗

bioRxiv2020

Design Principles Underlying Robust Perfect Adaptation of Complex Biochemical Networks

Biochemical networks are often characterised by tremendous complexity - both in terms of the sheer number of interacting molecules ("nodes") and in terms of the varied and incompletely understood interactions among these molecules ("interconnections" or "edges"). Strikingly, the vast and intricate networks of interacting proteins that exist within each living cell have the capacity to perform remarkably robustly, and reproducibly, despite significant variations in concentrations of the interacting components from one cell to the next, and despite mutability over time of biochemical parameters. Here we consider the ubiquitously observed and fundamentally important signalling response known as Robust Perfect Adaptation (RPA). We have recently shown that all RPA-capable networks, even the most complex ones, must satisfy an extremely rigid set of design principles, and are modular, being decomposable into just two types of network building-blocks - Opposer modules, and Balancer modules. Here we present an overview of the design principles that characterize all RPA-capable network topologies through a detailed examination of a collection of simple examples. We also introduce a diagrammatic method for studying the potential of a network to exhibit RPA, which may be applied without a detailed knowledge of the complex mathematical principles governing RPA.

systems biology↗