The inflammatory twitch as a general strategy for controlling the host response

Probabilistic cellular automata modelling of intercellular interactions in airways: complex pattern formation in patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a highly prevalent lung disease characterized by chronic inflammation and tissue remodeling possibly induced by unusual interactions between fibrocytes and CD8+ T lymphocytes in the peribronchial area. To investigate this phenomenon, we developed a probabilistic cellular automata type model where the two types of cells follow simple local interaction rules taking into account cell death, proliferation, migration and infiltration. We conducted a rigorous mathematical analysis using multiscale experimental data obtained in control and disease conditions to estimate the model's parameters accurately. The simulation of the model is straightforward to implement, and two distinct patterns emerged that we can analyse quantitatively. In particular, we show that the change in fibrocyte density in the COPD condition is mainly the consequence of their infiltration into the lung during exacerbations, suggesting possible explanations for experimental observations in normal and COPD tissue. Our integrated approach that combines a probabilistic cellular automata model and experimental findings will provide further insights into COPD in future studies.

Multi-scale models of lung fibrosis

The architectural complexity of the lung is crucial to its ability to function as an organ of gas exchange; the branching tree structure of the airways transforms the tracheal cross-section of only a few square centimeters to a blood-gas barrier with a surface area of tens of square meters and a thickness on the order of a micron or less. Connective tissue comprised largely of collagen and elastic fibers provides structural integrity for this intricate and delicate system. Homeostatic maintenance of this connective tissue, via a balance between catabolic and anabolic enzyme-driven processes, is crucial to life. Accordingly, when homeostasis is disrupted by the excessive production of connective tissue, lung function deteriorates rapidly with grave consequences leading to chronic lung conditions such as pulmonary fibrosis. Understanding how pulmonary fibrosis develops and alters the link between lung structure and function is crucial for diagnosis, prognosis, and therapy. Further information gained could help elaborate how the healing process breaks down leading to chronic disease. Our understanding of fibrotic disease is greatly aided by the intersection of wet lab studies and mathematical and computational modeling. In the present review we will discuss how multi-scale modeling has facilitated our understanding of pulmonary fibrotic disease as well as identified opportunities that remain open and have produced techniques that can be incorporated into this field by borrowing approaches from multi-scale models of fibrosis beyond the lung.

Agent-based models of inflammation in translational systems biology: A decade later

Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.

Pathophysiology to Phenotype in the Asthma of Obesity

Obesity affects numerous diseases, including asthma, for reasons that remain incompletely understood. Recent research suggests that the asthma of obesity is not a single disease, and that it breaks out into at least two distinct phenotypes. One phenotype is conventional allergic asthma modulated by obesity, whereas another arises solely due to the presence of obesity. The latter is postulated to be a consequence of the chronic lung compression caused by the obese chest wall in individuals with particularly collapsible lungs. Allergic obese asthma, on the other hand, appears to result from the way that obesity affects the immune system, which we hypothesize can be understood in terms of effects on the dynamic regulation of the inflammatory response.

Mouse Modeling of Obese Lung Disease. Insights and Caveats

As the obesity epidemic has worsened, its impact on lung health and disease has become progressively evident. The interactions between obesity and the accompanying metabolic syndrome and diseases such as asthma, pneumonia, and acute respiratory distress syndrome (ARDS) have proven complex and often counterintuitive in human studies. Hence, there is a growing need for relevant experimental approaches to understand the interactions between obesity and the lung. To this end, researchers have increasingly exploited mouse models combining both obesity and lung diseases, including ARDS, pneumonia, and asthma. Such models have both complemented and advanced the understanding we have gained from clinical studies and have allowed elegant dissections of obesity's effects on the pathogenesis of lung disease. Yet these models come with several critically important caveats that we must reflect on when interpreting their results.

A Computational Model of Cellular Engraftment on Lung Scaffolds

The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior.

Systems physiology of the airways in health and obstructive pulmonary disease

Fresh air entering the mouth and nose is brought to the blood-gas barrier in the lungs by a repetitively branching network of airways. Provided the individual airway branches remain patent, this airway tree achieves an enormous amplification in cross-sectional area from the trachea to the terminal bronchioles. Obstructive lung diseases such as asthma occur when airway patency becomes compromised. Understanding the pathophysiology of these obstructive diseases thus begins with a consideration of the factors that determine the caliber of an individual airway, which include the force balance between the inward elastic recoil of the airway wall, the outward tethering forces of its parenchymal attachments, and any additional forces due to contraction of airway smooth muscle. Other factors may also contribute significantly to airway narrowing, such as thickening of the airway wall and accumulation of secretions in the lumen. Airway obstruction becomes particularly severe when these various factors occur in concert. However, the effect of airway abnormalities on lung function cannot be fully understood only in terms of what happens to a single airway because narrowing throughout the airway tree is invariably heterogeneous and interdependent. Obstructive lung pathologies thus manifest as emergent phenomena arising from the way in which the airway tree behaves a system. These emergent phenomena are studied with clinical measurements of lung function made by spirometry and by mechanical impedance measured with the forced oscillation technique. Anatomically based computational models are linking these measurements to underlying anatomic structure in systems physiology terms. WIREs Syst Biol Med 2016, 8:423-437. doi: 10.1002/wsbm.1347 For further resources related to this article, please visit the WIREs website.

Dissecting the inflammatory twitch in allergically inflamed mice

We have previously advanced the hypothesis that the allergic inflammatory response in the lungs occurs as a self-limited sequence of events that begins with the onset of inflammation and then resolves back to baseline over a predetermined time course (Pothen JJ, Poynter ME, Bates JH. J Immunol 190: 3510-3516, 2013). In the present study we tested a key prediction of this hypothesis, which is that the instigation of the allergic inflammatory response should be accompanied by a later refractory period during which the response cannot be reinitiated. We challenged groups of ovalbumin-sensitized BALB/c mice for 3, 14, 21 and 31 consecutive days with aerosolized ovalbumin. We measured airways responsiveness as well as cell counts and cytokines in bronchoalveolar lavage fluid after the final challenge in subgroups from each group. In other subgroups we performed the same measurements following rest periods and after a final single recall challenge with antigen. We determined that the refractory periods for GM-CSF, KC, and IL-5 are no longer than 10 days, while those for IFNγ and IL-10 are no longer than 28 days. The refractory periods for total leukocytes and neutrophils were no greater than 28 days, while that for eosinophils was more than 28 days. The refractory period for airways resistance was less than 17, while for lung elastance it was longer than 28 days. Our results thus demonstrate that the components of the allergic inflammatory response in the lung have finite refractory periods, with the refractory period of the entire response being in the order of a month.

A computational model of unresolved allergic inflammation in chronic asthma

We have previously developed an agent-based computational model to demonstrate the feasibility of a novel hypothesis we term the inflammatory twitch. This hypothesis potentially explains the dynamics of the normal response to allergic inflammation in the lung (Pothen JJ, Poynter ME, Bates JH. J Immunol 190: 3510-3516, 2013) on the basis that antigenic stimulation sets in motion both the onset of inflammation and its subsequent resolution. The result is a self-limited inflammatory event that is similar in a formal sense to a skeletal muscle twitch. We hypothesize here that the chronic airway inflammation characteristic of asthma may represent the failure of the inflammatory twitch to resolve back to baseline. Our model provides a platform with which to perform virtual experiments aimed at investigating possible mechanisms leading to accentuation and/or prolongation of the inflammatory twitch. We used our model to determine how the inflammatory twitch is modified by knocking out certain cell types, interfering with cell activity, and altering cell lifetimes. Increasing the duration of activation of proinflammatory cells (considered to be chiefly neutrophils and eosinophils) markedly accentuated and prolonged the inflammatory twitch. This aberrant twitch behavior was largely abrogated by knocking out T-helper cells (simulating the effect of corticosteroids). The aberrant inflammatory twitch was also normalized by reducing the lifetime of the proinflammatory cells, suggesting that increasing apoptosis of these cells may be a therapeutic target in asthma.

The immune profile associated with acute allergic asthma accelerates clearance of influenza virus

Asthma was the most common comorbidity in hospitalized patients during the 2009 influenza pandemic. For unknown reasons, hospitalized asthmatics had less severe outcomes and were less likely to die from pandemic influenza. Our data with primary human bronchial cells indicate that changes intrinsic to epithelial cells in asthma may protect against cytopathology induced by influenza virus. To further study influenza virus pathogenesis in allergic hosts, we aimed to develop and characterize murine models of asthma and influenza comorbidity to determine structural, physiological and immunological changes induced by influenza in the context of asthma. Aspergillus fumigatus-sensitized and -challenged C57BL/6 mice were infected with pandemic H1N1 influenza virus, either during peak allergic inflammation or during airway remodeling to gain insight into disease pathogenesis. Mice infected with the influenza virus during peak allergic inflammation did not lose body weight and cleared the virus rapidly. These mice exhibited high eosinophilia, preserved airway epithelial cell integrity, increased mucus, reduced interferon response and increased insulin-like growth factor-1. In contrast, weight loss and viral replication kinetics in the mice that were infected during the late airway remodeling phase were equivalent to flu-only controls. These mice had neutrophils in the airways, damaged airway epithelial cells, less mucus production, increased interferons and decreased insulin-like growth factor-1. The state of the allergic airways at the time of influenza virus infection alters host responses against the virus. These murine models of asthma and influenza comorbidity may improve our understanding of the epidemiology and pathogenesis of viral infections in humans with asthma.

Systems approaches for synthetic biology: a pathway toward mammalian design

We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.