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.

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.

The Virtual Microbiome: Computational Approaches to the Study of Microbe-Host Interactions

The GI tract of a normal adult human contains on the order of 1014 foreign living organisms, collectively known as the gut microbiome, the proper maintenance of which is critical for health. Because the gut microbiome is a dynamic system of vast complexity, computational modeling is assuming an increasingly important role in helping us to understand how and why it behaves as it does. In particular, computational models can serve as a rapid, cost-effective means of simulating the microbiome on multiple scales, from that of an individual bacterium to the microbiome as a whole. This not only allows questions to be addressed in ways that are impractical in the experimental laboratory; it also permits competing hypotheses to be interrogated for feasibility before they are subjected to expensive and time-consuming experimental testing. Here we review some of the differential equation-based and agent-based approaches that have been applied to the computational modeling of the gut microbiome and its effects on the rest of the body. The models discussed are helping us understand how the microbiome works as a system, how it maintains its crucial symbiotic relationship with its host, and, in particular, how its malfunctions can lead to a number of important and often serious pathologies.

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 inflammatory twitch as a general strategy for controlling the host response

Allergic inflammation is a general host-defense mechanism for dealing with perceived foreign invaders. Although most effort has been directed toward understanding how this response gets turned on, how it gets turned off again when no longer needed is just as important to an organism's survival. We postulate that the control of the allergic inflammatory response is achieved via frequency modulation whereby a sequence of self-resolving events is repetitively invoked only so long as Ag is present. This leads to the notion of a unitary inflammatory event that we argue has formal similarity to the skeletal muscle twitch, albeit manifest over a much longer time scale. To test the plausibility of this hypothesis, we created an agent-based computational model of the allergic inflammatory response in the lungs. Continual stimulation of the model results in cycles of tissue damage and repair interspersed with periods of nonresponsiveness indicative of a refractory period. These findings are consistent with the inflammatory twitch hypothesis and the notion that the allergic inflammatory response is controlled via frequency modulation. We speculate that chronic inflammatory diseases may represent a failure of the inflammatory twitch to resolve toward baseline.