Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

Aminian-Dehkordi, Javad; Valiei, Amin; Mofrad, Mohammad R. K.

doi:10.3389/fcvm.2022.987104

Cited by 4 publications

References 146 publications

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Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

Valiei,

Dickson,

Aminian-Dehkordi

et al. 2024

npj Biofilms Microbiomes

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The gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange. Results showed that, across scenarios with different initial species abundances, cross-feeding promotes species coexistence. Morphologically, competition and neutralism resulted in segregation, while mutualism and commensalism fostered high intermixing. In addition, cooperative relations resulted in community properties with little sensitivity to the selective uptake of metabolites produced by the host. Moreover, metabolic interactions strongly influenced colonization success following the invasion of newcomer species. These results provide important insights into the utility of ABM in deciphering complex microbiome patterns.

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Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

Valiei,

Dickson,

Aminian-Dehkordi

et al. 2024

npj Biofilms Microbiomes

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Gut-on-a-chip models for dissecting the gut microbiology and physiology

2023

Self Cite

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Microfluidic technologies have been extensively investigated in recent years for developing organ-on-a-chip-devices as robust in vitro models aiming to recapitulate organ 3D topography and its physicochemical cues. Among these attempts, an important research front has focused on simulating the physiology of the gut, an organ with a distinct cellular composition featuring a plethora of microbial and human cells that mutually mediate critical body functions. This research has led to innovative approaches to model fluid flow, mechanical forces, and oxygen gradients, which are all important developmental cues of the gut physiological system. A myriad of studies has demonstrated that gut-on-a-chip models reinforce a prolonged coculture of microbiota and human cells with genotypic and phenotypic responses that closely mimic the in vivo data. Accordingly, the excellent organ mimicry offered by gut-on-a-chips has fueled numerous investigations on the clinical and industrial applications of these devices in recent years. In this review, we outline various gut-on-a-chip designs, particularly focusing on different configurations used to coculture the microbiome and various human intestinal cells. We then elaborate on different approaches that have been adopted to model key physiochemical stimuli and explore how these models have been beneficial to understanding gut pathophysiology and testing therapeutic interventions.

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MetaBiome: A Multiscale Model Integrating Agent-Based Modeling and Metabolic Networks Reveals Spatial Regulation in Mucosal Microbial Communities

Aminian-Dehkordi,

Dickson,

Valiei

et al. 2024

Preprint

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Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut, essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents, each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing environmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology as it offers new insights into predicting and analyzing microbial communities.ImportanceOur study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally.Key findings from our model include:Prediction of metabolic cross-feeding and spatial organization in multi-species communitiesInsights into how oxygen gradients and nutrient availability shape community composition in different gut regionsIdentification of spatially-regulated metabolic pathways and enzymes in E. coliWe believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

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Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

Cited by 4 publications

References 146 publications

Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

Gut-on-a-chip models for dissecting the gut microbiology and physiology

MetaBiome: A Multiscale Model Integrating Agent-Based Modeling and Metabolic Networks Reveals Spatial Regulation in Mucosal Microbial Communities

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