Continuous Modeling of T CD4 Lymphocyte Activation and Function

Polyamine Signal through HCC Microenvironment: A Key Regulator of Mitochondrial Preservation and Turnover in TAMs

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, and, with increasing research on the tumor immune microenvironment (TIME), the immunosuppressive micro-environment of HCC hampers further application of immunotherapy, even though immunotherapy can provide survival benefits to patients with advanced liver cancer. Current studies suggest that polyamine metabolism is not only a key metabolic pathway for the formation of immunosuppressive phenotypes in tumor-associated macrophages (TAMs), but it is also profoundly involved in mitochondrial quality control signaling and the energy metabolism regulation process, so it is particularly important to further investigate the role of polyamine metabolism in the tumor microenvironment (TME). In this review, by summarizing the current research progress of key enzymes and substrates of the polyamine metabolic pathway in regulating TAMs and T cells, we propose that polyamine biosynthesis can intervene in the process of mitochondrial energy metabolism by affecting mitochondrial autophagy, which, in turn, regulates macrophage polarization and T cell differentiation. Polyamine metabolism may be a key target for the interactive dialog between HCC cells and immune cells such as TAMs, so interfering with polyamine metabolism may become an important entry point to break intercellular communication, providing new research space for developing polyamine metabolism-based therapy for HCC.

Artesunate targets cellular metabolism to regulate the Th17/Treg cell balance

INTRODUCTION

Metabolic reprogramming is one of the important mechanisms of cell differentiation, and different cells have different preferences for energy sources. During the differentiation of naive CD4 + T cells into Th17 and Treg cells, these cells show specific energy metabolism characteristics. Th17 cells depend on enhanced glycolysis, fatty acid synthesis, and glutaminolysis. In contrast, Treg cells are dependent on oxidative phosphorylation, fatty acid oxidation, and amino acid depletion. As a potent antimalarial drug, artesunate has been shown to modulate the Th17/Treg imbalance and regulate cell metabolism.

METHODOLOGY

Relevant literatures on ART, cellular metabolism, glycolysis, lipid metabolism, amino acid metabolism, CD4 + T cells, Th17 cells, and Treg cells published from January 1, 2010 to now were searched in PubMed database.

CONCLUSION

In this review, we will highlight recent advances in which artesunate can restore the Th17/Treg imbalance in disease states by altering T-cell metabolism to influence differentiation and lineage selection. Data from the current study show that few studies have focused on the effect of ART on cellular metabolism. ART can affect the metabolic characteristics of T cells (glycolysis, lipid metabolism, and amino acid metabolism) and interfere with their differentiation lineage, thereby regulating the balance of Th17/Treg and alleviating the symptoms of the disease.

An integrative systems biology view of host-pathogen interactions: The regulation of immunity and homeostasis is concomitant, flexible, and smart

The systemic bio-organization of humans and other mammals is essentially "preprogrammed", and the basic interacting units, the cells, can be crudely mapped into discrete sets of developmental lineages and maturation states. Over several decades, however, and focusing on the immune system, we and others invoked evidence - now overwhelming - suggesting dynamic acquisition of cellular properties and functions, through tuning, re-networking, chromatin remodeling, and adaptive differentiation. The genetically encoded "algorithms" that govern the integration of signals and the computation of new states are not fully understood but are believed to be "smart", designed to enable the cells and the system to discriminate meaningful perturbations from each other and from "noise". Cellular sensory and response properties are shaped in part by recurring temporal patterns, or features, of the signaling environment. We compared this phenomenon to associative brain learning. We proposed that interactive cell learning is subject to selective pressures geared to performance, allowing the response of immune cells to injury or infection to be progressively coordinated with that of other cell types across tissues and organs. This in turn is comparable to supervised brain learning. Guided by feedback from both the tissue itself and the neural system, resident or recruited antigen-specific and innate immune cells can eradicate a pathogen while simultaneously sustaining functional homeostasis. As informative memories of immune responses are imprinted both systemically and within the targeted tissues, it is desirable to enhance tissue preparedness by incorporating attenuated-pathogen vaccines and informed choice of tissue-centered immunomodulators in vaccination schemes. Fortunately, much of the "training" that a living system requires to survive and function in the face of disturbances from outside or within is already incorporated into its design, so it does not need to deep-learn how to face a new challenge each time from scratch. Instead, the system learns from experience how to efficiently select a built-in strategy, or a combination of those, and can then use tuning to refine its organization and responses. Efforts to identify and therapeutically augment such strategies can take advantage of existing integrative modeling approaches. One recently explored strategy is boosting the flux of uninfected cells into and throughout an infected tissue to rinse and replace the infected cells.

Modeling the effect of environmental cytokines, nutrient conditions and hypoxia on CD4+ T cell differentiation

Upon antigen stimulation and co-stimulation, CD4⁺ T lymphocytes produce soluble factors that promote the activity of other immune cells against pathogens or modified tissues; this task must be performed in presence of a variety of environmental cytokines, nutrient, and oxygen conditions, which necessarily impact T cell function. The complexity of the early intracellular processes taking place upon lymphocyte stimulation is addressed by means of a mathematical model based on a network that integrates variable microenvironmental conditions with intracellular activating, regulatory, and metabolic signals. Besides the phenotype subsets considered in previous works (Th1, Th2, Th17, and Treg) the model includes the main early events in differentiation to the T_FH phenotype. The model describes how cytokines, nutrients and oxygen availability regulate the differentiation of naïve CD4⁺ T cells into distinct subsets. Particularly, it shows that elevated amounts of an all-type mixture of effector cytokines under optimal nutrient and oxygen availability conduces the system towards a highly-polarized Th1 or Th2 state, while reduced cytokine levels allow the expression of the Th17, Treg or T_FH subsets, or even hybrid phenotypes. On the other hand, optimal levels of an all-type cytokine mixture in combination with glutamine or tryptophan restriction implies a shift from Th1 to Th2 expression, while decreased levels of the Th2-inducing cytokine IL-4 leads to the rupture of the Th1-Th2 axis, allowing the manifestation of different (or hybrid) subsets. Modeling proposes that, even under reduced levels of pro-inflammatory cytokines, the sole action of hypoxia boost Th17 expression.