Contribution of ROS and metabolic status to neonatal and adult CD8+ T cell activation

The relationship of redox signaling with the risk for atherosclerosis

Oxidative balance plays a pivotal role in physiological homeostasis, and many diseases, particularly age-related conditions, are closely associated with oxidative imbalance. While the strategic role of oxidative regulation in various diseases is well-established, the specific involvement of oxidative stress in atherosclerosis remains elusive. Atherosclerosis is a chronic inflammatory disorder characterized by plaque formation within the arteries. Alterations in the oxidative status of vascular tissues are linked to the onset, progression, and outcome of atherosclerosis. This review examines the role of redox signaling in atherosclerosis, including its impact on risk factors such as dyslipidemia, hyperglycemia, inflammation, and unhealthy lifestyle, along with dysregulation, vascular homeostasis, immune system interaction, and therapeutic considerations. Understanding redox signal transduction and the regulation of redox signaling will offer valuable insights into the pathogenesis of atherosclerosis and guide the development of novel therapeutic strategies.

Neonatal CD4+ T cells have a characteristic transcriptome and epigenome and respond to TCR stimulation with proliferation and yet a limited immune response

The adaptive immune response is coordinated by CD4+ T cells, which determine the type and strength of the immune response and the effector cells involved. It has been reported that CD4+ T cells are less responsive in neonates, leading to low activation of the cellular response and poor antibody production by B cells. This low response is essential for the tolerant window that favors birth transition from the sterile environment in the womb to the outside world but leaves neonates vulnerable to infection, which is still an important health issue. Neonates have a high morbidity and mortality rate due to infections, and the molecular reasons are still understudied. We asked whether the neonatal naive CD4+ T cells have a genomic program that predisposes them to a low response. Therefore, we evaluated the transcriptome and epigenome of human neonatal and adult naive CD4+ T cells. Our results point to a gene expression profile forming a distinct regulatory network in neonatal cells, which favors proliferation and a low T-cell response. Such expression profile is supported by a characteristic epigenetic landscape of neonatal CD4+ T cells, which correlates with the characteristic transcriptome of the neonatal cells. These results were confirmed by experiments showing a low response to activation signals, higher proliferation, and lower expression of cytokines of neonatal CD4+ T cells as compared to adult cells. Understanding this network could lead to novel vaccine formulations and better deal with life-threatening diseases during this highly vulnerable period of our lives.

Reducing Boolean networks with backward equivalence

BACKGROUND

Boolean Networks (BNs) are a popular dynamical model in biology where the state of each component is represented by a variable taking binary values that express, for instance, activation/deactivation or high/low concentrations. Unfortunately, these models suffer from the state space explosion, i.e., there are exponentially many states in the number of BN variables, which hampers their analysis.

RESULTS

We present Boolean Backward Equivalence (BBE), a novel reduction technique for BNs which collapses system variables that, if initialized with same value, maintain matching values in all states. A large-scale validation on 86 models from two online model repositories reveals that BBE is effective, since it is able to reduce more than 90% of the models. Furthermore, on such models we also show that BBE brings notable analysis speed-ups, both in terms of state space generation and steady-state analysis. In several cases, BBE allowed the analysis of models that were originally intractable due to the complexity. On two selected case studies, we show how one can tune the reduction power of BBE using model-specific information to preserve all dynamics of interest, and selectively exclude behavior that does not have biological relevance.

CONCLUSIONS

BBE complements existing reduction methods, preserving properties that other reduction methods fail to reproduce, and vice versa. BBE drops all and only the dynamics, including attractors, originating from states where BBE-equivalent variables have been initialized with different activation values The remaining part of the dynamics is preserved exactly, including the length of the preserved attractors, and their reachability from given initial conditions, without adding any spurious behaviours. Given that BBE is a model-to-model reduction technique, it can be combined with further reduction methods for BNs.

Metabolic alterations impair differentiation and effector functions of CD8+ T cells

CD8+ T lymphocytes are one of the main effector cells of the immune system, they protect the organism against intracellular threats such as viruses and bacteria, as well as neoplasms. It is currently well established that CD8+ T cells have distinct immune responses, given by their phenotypes Tc1, Tc2, Tc17, and TcReg. The cellular plasticity of such phenotypes depends on the presence of different combinations of cytokines in the extracellular medium. It is known that metabolic imbalances play an important role in immune response, but the precise role of metabolic disturbances on the differentiation and function of CD8+ T cells, however, has not been explored. In this work, we used a computational model to explore the potential effect of metabolic alterations such as hyperglycemia, high alcohol consumption, dyslipidemia, and diabetes on CD8+ T cell differentiation. Our model predicts that metabolic alterations preclude the effector function of all CD8+ T cell phenotypes except for TcReg cells. It also suggests that such inhibition originates from the increase of reactive oxygen species in response to metabolic stressors. Finally, we simulated the outcome of treating metabolic-inhibited CD8+ T cells with drugs targeting key molecules such as mTORC1, mTORC2, Akt, and others. We found that overstimulation of mTORC2 may restore cell differentiation and functions of all effector phenotypes, even in diabetic patients. These findings highlight the importance of our predictive model to find potential targets to strengthen immunosuppressed patients in chronic diseases, like diabetes.

Oxidative Stress in Cancer Immunotherapy: Molecular Mechanisms and Potential Applications

Immunotherapy is an effective treatment option that revolutionizes the management of various cancers. Nevertheless, only a subset of patients receiving immunotherapy exhibit durable responses. Recently, numerous studies have shown that oxidative stress induced by reactive oxygen species (ROS) plays essential regulatory roles in the tumor immune response, thus regulating immunotherapeutic effects. Specifically, studies have revealed key roles of ROS in promoting the release of tumor-associated antigens, manipulating antigen presentation and recognition, regulating immune cell phenotypic differentiation, increasing immune cell tumor infiltration, preventing immune escape and diminishing immune suppression. In the present study, we briefly summarize the main classes of cancer immunotherapeutic strategies and discuss the interplay between oxidative stress and anticancer immunity, with an emphasis on the molecular mechanisms underlying the oxidative stress-regulated treatment response to cancer immunotherapy. Moreover, we highlight the therapeutic opportunities of manipulating oxidative stress to improve the antitumor immune response, which may improve the clinical outcome.

Multiplexed functional metagenomic analysis of the infant microbiome identifies effectors of NF-κB, autophagy, and cellular redox state

The human microbiota plays a critical role in host health. Proper development of the infant microbiome is particularly important. Its dysbiosis leads to both short-term health issues and long-term disorders lasting into adulthood. A central way in which the microbiome interacts with the host is through the production of effector molecules, such as proteins and small molecules. Here, a metagenomic library constructed from 14 infant stool microbiomes is analyzed for the production of effectors that modulate three distinct host pathways: immune response (nuclear factor κB [NF-κB] activation), autophagy (LC3-B puncta formation), and redox potential (NADH:NAD ratio). We identify microbiome-encoded bioactive metabolites, including commendamide and hydrogen sulfide and their associated biosynthetic genes, as well as a previously uncharacterized autophagy-inducing operon from Klebsiella spp. This work extends our understanding of microbial effector molecules that are known to influence host pathways. Parallel functional screening of metagenomic libraries can be easily expanded to investigate additional host processes.

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Construction of a metagenomic library from stool of infants

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A multiplexed screen for bacterial effectors of host cellular processes

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Identification of microbiome-encoded effectors hydrogen sulfide and commendamide

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The products of a Klebsiella pneumoniae operon induce autophagy

Computational Verification of Large Logical Models-Application to the Prediction of T Cell Response to Checkpoint Inhibitors

At the crossroad between biology and mathematical modeling, computational systems biology can contribute to a mechanistic understanding of high-level biological phenomenon. But as knowledge accumulates, the size and complexity of mathematical models increase, calling for the development of efficient dynamical analysis methods. Here, we propose the use of two approaches for the development and analysis of complex cellular network models. A first approach, called "model verification" and inspired by unitary testing in software development, enables the formalization and automated verification of validation criteria for whole models or selected sub-parts. When combined with efficient analysis methods, this approach is suitable for continuous testing, thereby greatly facilitating model development. A second approach, called "value propagation," enables efficient analytical computation of the impact of specific environmental or genetic conditions on the dynamical behavior of some models. We apply these two approaches to the delineation and the analysis of a comprehensive model for T cell activation, taking into account CTLA4 and PD-1 checkpoint inhibitory pathways. While model verification greatly eases the delineation of logical rules complying with a set of dynamical specifications, propagation provides interesting insights into the different potential of CTLA4 and PD-1 immunotherapies. Both methods are implemented and made available in the all-inclusive CoLoMoTo Docker image, while the different steps of the model analysis are fully reported in two companion interactive jupyter notebooks, thereby ensuring the reproduction of our results.

IL-12 Signaling Contributes to the Reprogramming of Neonatal CD8+ T Cells

Neonates are highly susceptible to intracellular pathogens, leading to high morbidity and mortality rates. CD8⁺ T lymphocytes are responsible for the elimination of infected cells. Understanding the response of these cells to normal and high stimulatory conditions is important to propose better treatments and vaccine formulations for neonates. We have previously shown that human neonatal CD8⁺ T cells overexpress innate inflammatory genes and have a low expression of cytotoxic and cell signaling genes. To investigate the activation potential of these cells, we evaluated the transcriptome of human neonatal and adult naïve CD8⁺ T cells after TCR/CD28 signals ± IL-12. We found that in neonatal cells, IL-12 signals contribute to the adult-like expression of genes associated with cell-signaling, T-cell cytokines, metabolism, and cell division. Additionally, IL-12 signals contributed to the downregulation of the neutrophil signature transcription factor CEBPE and other immaturity related genes. To validate the transcriptome results, we evaluated the expression of a series of genes by RT-qPCR and the promoter methylation status on independent samples. We found that in agreement with the transcriptome, IL-12 signals contributed to the chromatin closure of neutrophil-like genes and the opening of cytotoxicity genes, suggesting that IL-12 signals contribute to the epigenetic reprogramming of neonatal lymphocytes. Furthermore, high expression of some inflammatory genes was observed in naïve and stimulated neonatal cells, in agreement with the high inflammatory profile of neonates to infections. Altogether our results point to an important contribution of IL-12 signals to the reprogramming of the neonatal CD8⁺ T cells.