Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

Gelbach, Patrick E.; Finley, Stacey D.

doi:10.1101/2023.03.09.532000

Cited by 6 publications

(3 citation statements)

References 107 publications

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“…Future work can explore alternative metrics to assess cellular behavior. This is especially important because genome-scale modeling is increasingly used for eukaryotic (principally human) cells, where growth rate as a proxy for cell health is less supported [64][65][66][67][68][69] . For example, rather than focusing on growth, we could instead study flux through a specific reaction or pathway known to mediate the behavior of a particular cell type.…”

Section: Discussionmentioning

confidence: 99%

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

Gelbach

Finley

2023

Preprint

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Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model. However, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling may capture additional heterogeneity across cells, especially when cells exhibit sub-maximal growth rates. In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. We find significant differences in the predicted metabolism with sampling, including increased cooperative interactions and pathway-specific changes in predicted flux. Our results suggest the importance of sampling-based and objective function-independent approaches to evaluate metabolic interactions and emphasize their utility in quantitatively studying interactions between cells and organisms.

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Section: Discussionmentioning

confidence: 99%

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

Gelbach

Finley

2023

Preprint

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“…M1 pro-tumor and M2 anti-tumor macrophages. While it is now known that macrophages exist on a continuum, whereby their functions vary, and they can exhibit a range of phenotypes and functions, 44,45 we retain these broad M1 and M2 groupings for the purposes of exploring the effects of anti-and pro-tumor macrophages.…”

Section: Macrophages Classical In Vitro Characterization Of Macrophag...mentioning

confidence: 99%

Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions

Tangella,

Cess,

Ildefonso

et al. 2024

Preprint

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Interactions between cancer cells and immune cells in the tumor microenvironment influence tumor growth and can contribute to the response to cancer immunotherapies. It is difficult to gain mechanistic insights into the effects of cell-cell interactions in tumors using a purely experimental approach. However, computational modeling enables quantitative investigation of the tumor microenvironment, and agent-based modeling in particular provides relevant biological insights into the spatial and temporal evolution of tumors. Here, we develop a novel agent-based model (ABM) to predict the consequences of intercellular interactions. Furthermore, we leverage our prior work that predicts the transitions of CD8+ T cells from a naive state to a terminally differentiated state using Boolean modeling. Given the detailed incorporated to predict T cell state, we apply the integrated Boolean-ABM framework to study how the properties of CD8+ T cells influence the composition and spatial organization of tumors and the efficacy of an immune checkpoint blockade. Overall, we present a mechanistic understanding of tumor evolution that can be leveraged to study targeted immunotherapeutic strategies.

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“…Using Flux Balance Analysis (FBA) and Flux Variability Analysis (FVA) the fluxes of the reactions can be predicted for a given condition/timepoint. The study by Gelbach et al, on M1 and M2 subtypes of human colorectal cancer cells via generation of GSM models marks a significant step towards understanding and manipulating the polarization mechanism of macrophages (27). However, it is also important to explore the metabolic network and capabilities of M1 and M2 phenotypes in tissue-specific macrophages (e.g., AM) where they show unique behaviors and patterns.…”

Section: Introductionmentioning

confidence: 99%

Dissecting Metabolic Landscape of Alveolar Macrophage

Malla,

Sajeevan,

Acharya

et al. 2023

Preprint

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The highly plastic nature of Alveolar Macrophage (AM) plays a crucial role in the defense against inhaled particulates and pathogens in the lungs. Depending upon the signal, AM acquires either classically activated M1 phenotype or alternatively activated M2 phenotype. These phenotypes have specific functions and unique metabolic traits such as upregulated glycolysis and pentose phosphate pathway in M1 phase and enhanced oxidative phosphorylation and tricarboxylic acid cycle during M2 phase that help maintain the sterility of the lungs. In this study, we investigate the metabolic shift in the activated phases of AM (M1 and M2 phase) and highlight the roles of pathways other than the typical players of central carbon metabolism. Pathogenesis is a complex and elongated process where the heightened requirement for energy is matched by metabolic shifts that supplement immune response and maintain homeostasis. The first step of pathogenesis is fever; however, analyzing the role of physical parameters such as temperature is challenging. Here, we observe the effect of an increase in temperature on pathways such as glycolysis, pentose phosphate pathway, oxidative phosphorylation, tricarboxylic acid cycle, amino acid metabolism, and leukotriene metabolism. We report the role of temperature as a catalyst to the immune response of the cell. The activity of pathways such as pyruvate metabolism, arachidonic acid metabolism, chondroitin/heparan sulfate biosynthesis, and heparan sulfate degradation are found to be important driving forces in the M1/M2 phenotype. We have also identified a list of 34 reactions such as nitric oxide production from arginine and the conversion of glycogenin to UDP which play major roles in the metabolic models and prompt the shift of the M2 phenotype to M1 and vice versa. In future, these reactions could further be probed as major contributors in designing effective therapeutic targets against severe respiratory diseases.Author SummaryAlveolar macrophage (AM) is highly plastic in nature and has a wide range of functions including invasion/killing of bacteria to maintaining the homeostasis in the lungs. The regulatory mechanism involved in the alveolar macrophage polarization is essential to fight against severe respiratory conditions (pathogens and particulates). Over the years, experiments on mouse/rat models have been used to draw insightful inferences. However, recent advances have highlighted the lack of transmission from non-human models to successfulin vivohuman experiments. Hence using genome-scale metabolic (GSM) models to understand the unique metabolic traits of human alveolar macrophages and comprehend the complex metabolic underpinnings that govern the polarization can lead to novel therapeutic strategies. The GSM models of AMs thus far, has not incorporated the activated phases of AM. Here, we aim to exhaustively dissect the metabolic landscape and capabilities of AM in its healthy and activated stages. We carefully explore the changes in reaction fluxes under each of the conditions to understand the role and function of all the pathways with special attention to pathways away from central carbon metabolism. Understanding the characteristics of each phase of AM has applications that could help improve the therapeutic approaches against respiratory conditions.

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Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

Cited by 6 publications

References 107 publications

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions

Dissecting Metabolic Landscape of Alveolar Macrophage

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