A cellular automaton model to find the risk of developing autism through gut-mediated effects. (July 2019) - Nagaraju, K.; Sudeep, K.S.; Kurhekar, M.P.
Abstract: Background: One of the risk factors for the development of Autism Spectrum Disorder (ASD) is hypothesized to be an imbalance in the gut microbiome. Alterations in the relative numbers of gut microbiota may contribute to such a disruption in normal bacterial diversity. It is assumed that this process may be adequately mirrored for the purpose of the current paper by modeling the dynamic shifts in the numbers of three bacterial species, namely Clostridium, Desulfovibrio, and Bifidobacterium . Such imbalances in the gut microbiome are thought to promote the development of increased gut permeability (the so-called "leaky gut") which in turn is a potential risk factor for the development of ASD. Methods: We constructed a mathematical model using 2-D Cellular Automata to simulate the growth rates and interactions of three bacterial species, namely Bifidobacterium, Clostridium and Desulfovibrio, with each other and with available nutrients in the gut, and particularly following the introduction of lysozyme into the gut. Results: It was observed from the modeled simulation that increasing or decreasing the population of C l o s t r i d i u m in the gut produces key shifts in the gut microbiome which could potentially increase or decrease the risk of ASD. Conclusion: Simulations using our cellular automaton model suggest that it could be useful in predicting the effects produced by alterations to key components of the gut microbiome. In particular, the model demonstrated that the introduction of l y s o z y m e in the gut results in steep reductions in C l o s t r i d i u m growth rate, which in turn could potentially alter the gut microbiome population in such a way as to significantly reduce the risk of developing ASD. Graphical abstract: Image 1 Highlights: Autism Spectrum Disorder (ASD) is hypothesized to be caused at least in part by gut microbiome alterations causing "leaky gut". The current paper uses a mathematical 2-D Cellular Automata model to examine the ASD risk following certain changes in the gut microbiome. The dynamic population shifts and interactions between three representative gut bacteria (Bifidobacterium, Clostridium and Desulfovibrio) are modeled to predict ASD risk. The model demonstrates that a relative abundance of Clostridium in the gut is a key change linked to increased ASD risk. Lysozyme addition into the gut significantly alters the gut microbiome, with a prominent decrease in the Clostridium growth rate and population, and reduced ASD risk.