Metabolic Reprogramming of the Innate Immune System

1. Introduction
Monocytes are a subclass of white blood cell that form part of our innate immune system. Monocytes are primarily found circulating in the blood where their functions include phagocytosis, antigen presentation, and cytokine production. Impairments in the functioning of the cells of the innate immune system have been associated with aging and obesity have been directly implicated in the development of atherosclerosis and the chronic low-grade inflammation associated with type 2 diabetes mellitus [1]. A number of recent studies have demonstrated that the functioning of immune cells including monocytes is intimately related to the metabolic capacity of these cells [2] suggesting nutritional or pharmacological interventions targeted towards specific metabolic deviations of monocytes could help mitigate the loss of function associated with disease development. However, the complexity of immune functioning and metabolism coupled with considerable inter-individual heterogeneity presents many challenges for experimentalists.
2. Approach
The monocyte model from the Harvey whole body metabolic reconstruction is extracted as a base model [3]. Context specific monocyte models are generated for each individual using gene expression data for monocyte isolated from young, elderly, and obese donors. The similarity of the resulting personalised monocyte models is assessed across a range of features. The Jaccard Distance is used to compare the topological differences between pairs of personalised monocyte models while the correlation of flux distributions is used to compare differences in predicted model fluxes [4]. These distance metrics were used to identify sub-groups within the larger population of monocyte models which were characterised using independent measures of metabolic and immune health. The Kruskal-Wallis test is applied to identify specific metabolic reactions which were significantly different between these immune-metabolic subgroups.
3. Results
The personalised monocyte models did not cluster by age or BMI. In comparing the young versus elderly models two clusters were identified based on the topological differences in the personalised monocyte models. Comparison of these clusters revealed significant difference in pathways governing lipid metabolism.
4. Discussion
Personalised metabolic reconstructions of monocytes can reveal differences in the metabolic capacity of immune cell associated with the development in non-communicable diseases in aging and overweight populations providing potential targets for nutritional intervention to promote healthy aging.
References
1. TS Kapellos, Bongauro L, Gemünd I, Reusch N et al. Human Monocyte Subsets and Phenotypes in Major Chronic and Inflammatory Diseases. Front Immunol. 10:2035 (2019).
2. E Lachmandas, L Boutens, JM Ratter, A Hijmans et al. Microbial stimulation of different Toll-like receptor signaling pathways induces diverse metabolic programmes in human monocytes. Nat Microbio. 2;16246 (2017).
3. I Thiele, S Sahoo, A Heinken, J Hertel et al. Personalized whole-body models integrate metabolism, physiology, and the gut microbiome. Mol Syst Biol. 16:e8982 (2020).
4. A Cabbia, PA Hilbers, NAW van Riel. A Distance-Based Framework for the Characterization of Metabolic Heterogenity in Large Sets of Genome-Scale Metabolic Models. Patterns. 1:1000080 (2020).