A dual negative regulation model of Toll-like receptor 4 signaling for endotoxin preconditioning in human endotoxemia

Preconditioning increases brain resistance against acute brain injury via neuroinflammation modulation

Acute brain injury (ABI) is a broad concept mainly comprised of sudden parenchymal brain injury. Acute brain injury outcomes are dependent not only on the severity of the primary injury, but the delayed secondary injury that subsequently follows as well. These are both taken into consideration when determining the patient's prognosis. Growing clinical and experimental evidence demonstrates that "preconditioning," a prophylactic approach in which the brain is exposed to various pre-injury stressors, can induce varying degrees of "tolerance" against the impact of the ABI by modulating neuroinflammation. In this review, we will summarize the pathophysiology of ABI, and discuss the involved mechanisms of neuroinflammation in ABI, as well as existing experimental and clinical studies demonstrating the efficacy of preconditioning methods in various types of ABI by modulating neuroinflammation.

Whole blood assay as a model for in vitro evaluation of inflammasome activation and subsequent caspase-mediated interleukin-1 beta release

Processing of pro-interleukin (IL)-1β and IL-18 is regulated by multiprotein complexes, known as inflammasomes. Inflammasome activation results in generation of bioactive IL-1β and IL-18, which can exert potent pro-inflammatory effects. Our aim was to develop a whole blood-based assay to study the inflammasome in vitro and that also can be used as an assay in clinical studies. We show whole blood is a suitable milieu to study inflammasome activation in primary human monocytes. We demonstrated that unprocessed human blood cells can be stimulated to activate the inflammasome by the addition of adenosine 5'-triphosphate (ATP) within a narrow timeframe following lipopolysaccharide (LPS) priming. Stimulation with LPS resulted in IL-1β release; however, addition of ATP is necessary for "full-blown" inflammasome stimulation resulting in high IL-1β and IL-18 release. Intracellular cytokine staining demonstrated monocytes are the major producers of IL-1β in human whole blood cultures, and this was associated with activation of caspase-1/4/5, as detected by a fluorescently labelled caspase-1/4/5 probe. By applying caspase inhibitors, we show that both the canonical inflammasome pathway (via caspase-1) as well as the non-canonical inflammasome pathway (via caspases-4 and 5) can be studied using this whole blood-based model.

Pharmacokinetics and Pharmacodynamics of Curcumin in regulating anti-inflammatory and epigenetic gene expression

Chronic inflammation is a key driver of cancer development. Nitrite levels, which are regulated by inducible nitric oxide synthase (iNOS), play a critical role in inflammation. While the anti-oxidant and anti-inflammatory effects of curcumin, a natural product present in the roots of Curcuma longa have been studied widely, the acute pharmacokinetics (PK) and pharmacodynamics (PD) of curcumin in suppressing pro-inflammatory markers and epigenetic modulators remain unclear. This study evaluated the PK and PD of curcumin-induced suppression of lipopolysaccharide (LPS)-mediated inflammation in rat lymphocytes. LPS was administered intravenously either alone or with curcumin to female Sprague-Dawley rats. Plasma samples were analysed for curcumin concentration and mRNA expression was quantified in lymphocytes. The relative gene expression of several inflammatory and epigenetic modulators was analysed. To investigate the relationship between curcumin concentration and iNOS, TNF-α, and IL-6 gene expression, PK/PD modeling using Jusko's indirect response model (IDR) integrating transit compartments (TC) describing the delayed response was conducted. The concentration-time profile of curcumin exhibited a bi-exponential decline, which was well described by a two-compartmental pharmacokinetic model. Importantly the results demonstrate that LPS induced gene expression of pro-inflammatory markers in lymphocytes, with peak expression at approximately 3 h and curcumin suppressed the gene expression in animals administered with LPS. These effects were well captured using the IDR model and an IDR model with the transit compartments. In summary, the PK/PD modeling approach could potentially provide a robust quantitative framework for evaluating the acute anti-inflammatory and epigenetic effects of curcumin in future clinical trials.

Low Dose of Lipopolysaccharide Pretreatment Preventing Subsequent Endotoxin-Induced Uveitis Is Associated with PI3K/AKT Pathway

Purpose

To explore the effects of LPS pretreatment on endotoxin-induced uveitis and PI3K/AKT pathway.

Methods

Endotoxin-induced uveitis was induced by a single subcutaneous injection of 200 μg LPS. For the endotoxin tolerance group, induction of EIU was preceded by daily subcutaneous injection of 0.1 mg/kg LPS for five days. Clinical scores were graded at 24 h after EIU under a slit lamp microscope. HE stain was performed to observe the histopathology. Aqueous humor TNF-α concentration was quantified with enzyme-linked immunosorbent assay. The expressions of PI3K and AKT were detected through Western blot analyses, and the activation of AKT was detected through immunofluorescence study.

Results

Endotoxin tolerance produced suppressive effects by significantly reducing the inflammatory reaction of anterior segment of the rats as measured by slit lamp and histopathology. Low dose of LPS pretreatment significantly reduced TNF-α concentrations and the expressions of PI3K and AKT. Furthermore, the activation of AKT was also inhibited.

Conclusions

LPS pretreatment can ameliorate endotoxin-induced uveitis in rats. This protection of endotoxin tolerance against EIU is associated with PI3K/AKT pathway by reducing level of TNF-α in the aqueous humor.

Modeling cytokine regulatory network dynamics driving neuroinflammation in central nervous system disorders

A central goal of pharmacological efforts to treat central nervous system (CNS) diseases is to develop systemic therapeutics that can restore CNS homeostasis. Achieving this goal requires a fundamental understanding of CNS function within the organismal context so as to leverage the mechanistic insights on the molecular basis of cellular and tissue functions towards novel drug target identification. The immune system constitutes a key link between the periphery and CNS, and many neurological disorders and neurodegenerative diseases are characterized by immune dysfunction. We review the salient opportunities for applying computational models to CNS disease research, and summarize relevant approaches from studies of immune function and neuroinflammation. While the accurate prediction of disease-related phenomena is often considered the central goal of modeling studies, we highlight the utility of computational modeling applications beyond making predictions, particularly for drawing counterintuitive insights from model-based analysis of multi-parametric and time series data sets.

Understanding Physiology in the Continuum: Integration of Information from Multiple -Omics Levels

In this paper, we discuss approaches for integrating biological information reflecting diverse physiologic levels. In particular, we explore statistical and model-based methods for integrating transcriptomic, proteomic and metabolomics data. Our case studies reflect responses to a systemic inflammatory stimulus and in response to an anti-inflammatory treatment. Our paper serves partly as a review of existing methods and partly as a means to demonstrate, using case studies related to human endotoxemia and response to methylprednisolone (MPL) treatment, how specific questions may require specific methods, thus emphasizing the non-uniqueness of the approaches. Finally, we explore novel ways for integrating -omics information with PKPD models, toward the development of more integrated pharmacology models.

Regulation of signal transduction by spatial parameters: a case in NF-κB oscillation

NF-κB is a transcription factor regulating expression of more than 500 genes, and its dysfunction leads to the autoimmune and inflammatory diseases. In malignant cancer cells, NF-κB is constitutively activated. Thus the elucidation of mechanisms for NF-κB regulation is important for the establishment of therapeutic treatment caused by incorrect NF-κB responses. Cytoplasmic NF-κB translocates to the nucleus by the application of extracellular stimuli such as cytokines. Nuclear NF-κB is known to oscillate with the cycle of 1.5-4.5 h, and it is thought that the oscillation pattern regulates the expression profiles of genes. In this review, first we briefly describe regulation mechanisms of NF-κB. Next, published computational simulations on the oscillation of NF-κB are summarised. There are at least 60 reports on the computational simulation and analysis of NF-κB oscillation. Third, the importance of a 'space' for the regulation of oscillation pattern of NF-κB is discussed, showing altered oscillation pattern by the change in spatial parameters such as diffusion coefficient, nuclear to cytoplasmic volume ratio (N/C ratio), and transport through nuclear membrane. Finally, simulations in a true intracellular space (TiCS), which is an intracellular 3D space reconstructed in a computer with organelles such as nucleus and mitochondria are discussed.

Mathematical Modeling of Early Cellular Innate and Adaptive Immune Responses to Ischemia/Reperfusion Injury and Solid Organ Allotransplantation

A mathematical model of the early inflammatory response in transplantation is formulated with ordinary differential equations. We first consider the inflammatory events associated only with the initial surgical procedure and the subsequent ischemia/reperfusion (I/R) events that cause tissue damage to the host as well as the donor graft. These events release damage-associated molecular pattern molecules (DAMPs), thereby initiating an acute inflammatory response. In simulations of this model, resolution of inflammation depends on the severity of the tissue damage caused by these events and the patient's (co)-morbidities. We augment a portion of a previously published mathematical model of acute inflammation with the inflammatory effects of T cells in the absence of antigenic allograft mismatch (but with DAMP release proportional to the degree of graft damage prior to transplant). Finally, we include the antigenic mismatch of the graft, which leads to the stimulation of potent memory T cell responses, leading to further DAMP release from the graft and concomitant increase in allograft damage. Regulatory mechanisms are also included at the final stage. Our simulations suggest that surgical injury and I/R-induced graft damage can be well-tolerated by the recipient when each is present alone, but that their combination (along with antigenic mismatch) may lead to acute rejection, as seen clinically in a subset of patients. An emergent phenomenon from our simulations is that low-level DAMP release can tolerize the recipient to a mismatched allograft, whereas different restimulation regimens resulted in an exaggerated rejection response, in agreement with published studies. We suggest that mechanistic mathematical models might serve as an adjunct for patient- or sub-group-specific predictions, simulated clinical studies, and rational design of immunosuppression.

Computational modelling of the inflammatory response in trauma, sepsis and wound healing: implications for modelling resilience

Resilience refers to the ability to recover from illness or adversity. At the cell, tissue, organ and whole-organism levels, the response to perturbations such as infections and injury involves the acute inflammatory response, which in turn is connected to and controlled by changes in physiology across all organ systems. When coordinated properly, inflammation can lead to the clearance of infection and healing of damaged tissues. However, when either overly or insufficiently robust, inflammation can drive further cell stress, tissue damage, organ dysfunction and death through a feed-forward process of inflammation → damage → inflammation. To address this complexity, we have obtained extensive datasets regarding the dynamics of inflammation in cells, animals and patients, and created data-driven and mechanistic computational simulations of inflammation and its recursive effects on tissue, organ and whole-organism (patho)physiology. Through this approach, we have discerned key regulatory mechanisms, recapitulated in silico key features of clinical trials for acute inflammation and captured diverse, patient-specific outcomes. These insights may allow for the determination of individual-specific tolerances to illness and adversity, thereby defining the role of inflammation in resilience.

A new IRAK-M-mediated mechanism implicated in the anti-inflammatory effect of nicotine via α7 nicotinic receptors in human macrophages

Nicotine stimulation of α7 nicotinic acetylcholine receptor (α7 nAChR) powerfully inhibits pro-inflammatory cytokine production in lipopolysaccharide (LPS)-stimulated macrophages and in experimental models of endotoxemia. A signaling pathway downstream from the α7 nAChRs, which involves the collaboration of JAK2/STAT3 and NF-κB to interfere with signaling by Toll-like receptors (TLRs), has been implicated in this anti-inflammatory effect of nicotine. Here, we identifiy an alternative mechanism involving interleukin-1 receptor-associated kinase M (IRAK-M), a negative regulator of innate TLR-mediated immune responses. Our data show that nicotine up-regulates IRAK-M expression at the mRNA and protein level in human macrophages, and that this effect is secondary to α7 nAChR activation. By using selective inhibitors of different signaling molecules downstream from the receptor, we provide evidence that activation of STAT3, via either JAK2 and/or PI3K, through a single (JAK2/PI3K/STAT3) or two convergent cascades (JAK2/STAT3 and PI3K/STAT3), is necessary for nicotine-induced IRAK-M expression. Moreover, down-regulation of this expression by small interfering RNAs specific to the IRAK-M gene significantly reverses the anti-inflammatory effect of nicotine on LPS-induced TNF-α production. Interestingly, macrophages pre-exposed to nicotine exhibit higher IRAK-M levels and reduced TNF-α response to an additional LPS challenge, a behavior reminiscent of the ‘endotoxin tolerant’ phenotype identified in monocytes either pre-exposed to LPS or from immunocompromised septic patients. Since nicotine is a major component of tobacco smoke and increased IRAK-M expression has been considered one of the molecular determinants for the induction of the tolerant phenotype, our findings showing IRAK-M overexpression could partially explain the known influence of smoking on the onset and progression of inflammatory and infectious diseases.

Formal modelling of toll like receptor 4 and JAK/STAT signalling pathways: insight into the roles of SOCS-1, interferon-β and proinflammatory cytokines in sepsis

Sepsis is one of the major causes of human morbidity and results in a considerable number of deaths each year. Lipopolysaccharide-induced sepsis has been associated with TLR4 signalling pathway which in collaboration with the JAK/STAT signalling regulate endotoxemia and inflammation. However, during sepsis our immune system cannot maintain a balance of cytokine levels and results in multiple organ damage and eventual death. Different opinions have been made in previous studies about the expression patterns and the role of proinflammatory cytokines in sepsis that attracted our attention towards qualitative properties of TLR4 and JAK/STAT signalling pathways using computer-aided studies. René Thomas' formalism was used to model septic and non-septic dynamics of TLR4 and JAK/STAT signalling. Comparisons among dynamics were made by intervening or removing the specific interactions among entities. Among our predictions, recurrent induction of proinflammatory cytokines with subsequent downregulation was found as the basic characteristic of septic model. This characteristic was found in agreement with previous experimental studies, which implicate that inflammation is followed by immunomodulation in septic patients. Moreover, intervention in downregulation of proinflammatory cytokines by SOCS-1 was found desirable to boost the immune responses. On the other hand, interventions either in TLR4 or transcriptional elements such as NFκB and STAT were found effective in the downregulation of immune responses. Whereas, IFN-β and SOCS-1 mediated downregulation at different levels of signalling were found to be associated with variations in the levels of proinflammatory cytokines. However, these predictions need to be further validated using wet laboratory experimental studies to further explore the roles of inhibitors such as SOCS-1 and IFN-β, which may alter the levels of proinflammatory cytokines at different stages of sepsis.

From data patterns to mechanistic models in acute critical illness

The complexity of the physiologic and inflammatory response in acute critical illness has stymied the accurate diagnosis and development of therapies. The Society for Complex Acute Illness was formed a decade ago with the goal of leveraging multiple complex systems approaches to address this unmet need. Two main paths of development have characterized the society's approach: (i) data pattern analysis, either defining the diagnostic/prognostic utility of complexity metrics of physiologic signals or multivariate analyses of molecular and genetic data and (ii) mechanistic mathematical and computational modeling, all being performed with an explicit translational goal. Here, we summarize the progress to date on each of these approaches, along with pitfalls inherent in the use of each approach alone. We suggest that the next decade holds the potential to merge these approaches, connecting patient diagnosis to treatment via mechanism-based dynamical system modeling and feedback control and allowing extrapolation from physiologic signals to biomarkers to novel drug candidates. As a predicate example, we focus on the role of data-driven and mechanistic models in neuroscience and the impact that merging these modeling approaches can have on general anesthesia.

In silico modeling: methods and applications to trauma and sepsis

OBJECTIVES

To familiarize clinicians with advances in computational disease modeling applied to trauma and sepsis.

DATA SOURCES

PubMed search and review of relevant medical literature.

SUMMARY

Definitions, key methods, and applications of computational modeling to trauma and sepsis are reviewed.

CONCLUSIONS

Computational modeling of inflammation and organ dysfunction at the cellular, organ, whole-organism, and population levels has suggested a positive feedback cycle of inflammation → damage → inflammation that manifests via organ-specific inflammatory switching networks. This structure may manifest as multicompartment "tipping points" that drive multiple organ dysfunction. This process may be amenable to rational inflammation reprogramming.

Fractal-like kinetics of intracellular enzymatic reactions: a chemical framework of endotoxin tolerance and a possible non-specific contribution of macromolecular crowding to cross-tolerance

BACKGROUND

The response to endotoxin (LPS), and subsequent signal transduction lead to the production of cytokines such as tumor necrosis factor-α (TNF-α) by innate immune cells. Cells or organisms pretreated with endotoxin enter into a transient state of hyporesponsiveness, referred to as endotoxin tolerance (ET) which represents a particular case of negative preconditioning. Despite recent progress in understanding the molecular basis of ET, there is no consensus yet on the primary mechanism responsible for ET and for the more complex cases of cross tolerance. In this study, we examined the consequences of the macromolecular crowding (MMC) and of fractal-like kinetics (FLK) of intracellular enzymatic reactions on the LPS signaling machinery. We hypothesized that this particular type of enzyme kinetics may explain the development of ET phenomenon.

METHOD

Our aim in the present study was to characterize the chemical kinetics framework in ET and determine whether fractal-like kinetics explains, at least in part, ET. We developed an ordinary differential equations (ODE) mathematical model that took into account the links between the MMC and the LPS signaling machinery leading to ET. We proposed that the intracellular fractal environment (MMC) contributes to ET and developed two mathematical models of enzyme kinetics: one based on Kopelman's fractal-like kinetics framework and the other based on Savageau's power law model.

RESULTS

Kopelman's model provides a good image of the potential influence of a fractal intracellular environment (MMC) on ET. The Savageau power law model also partially explains ET. The computer simulations supported the hypothesis that MMC and FLK may play a role in ET.

CONCLUSION

The model highlights the links between the organization of the intracellular environment, MMC and the LPS signaling machinery leading to ET. Our FLK-based model does not minimize the role of the numerous negative regulatory factors. It simply draws attention to the fact that macromolecular crowding can contribute significantly to the induction of ET by imposing geometric constrains and a particular chemical kinetic for the intracellular reactions.

Modeling physiologic variability in human endotoxemia

The control and management of inflammation is a key aspect of clinical care for critical illnesses such as sepsis. In an ideal reaction to injury, the inflammatory response provokes a strong enough response to heal the injury and then restores homeostasis. When inflammation becomes dysregulated, a persistent inflammatory state can lead to significant deleterious effects and clinical challenges. Thus, gaining a better biological understanding of the mechanisms driving the inflammatory response is of the utmost importance. In this review, we discuss our work with the late Stephen F. Lowry to investigate systemic inflammation through systems biology of human endotoxemia. We present our efforts in modeling the human endotoxemia response with a particular focus on physiologic variability. Through modeling, with a focus ultimately on translational applications, we obtain more fundamental understanding of relevant physiological processes. And by taking advantage of the information embedded in biological rhythms, ranging in time scale from high-frequency autonomic oscillations reflected in heart rate variability to circadian rhythms in inflammatory mediators, we gain insight into the underlying physiology.

Translational applications of evaluating physiologic variability in human endotoxemia

Dysregulation of the inflammatory response is a critical component of many clinically challenging disorders such as sepsis. Inflammation is a biological process designed to lead to healing and recovery, ultimately restoring homeostasis; however, the failure to fully achieve those beneficial results can leave a patient in a dangerous persistent inflammatory state. One of the primary challenges in developing novel therapies in this area is that inflammation is comprised of a complex network of interacting pathways. Here, we discuss our approaches towards addressing this problem through computational systems biology, with a particular focus on how the presence of biological rhythms and the disruption of these rhythms in inflammation may be applied in a translational context. By leveraging the information content embedded in physiologic variability, ranging in scale from oscillations in autonomic activity driving short-term heart rate variability to circadian rhythms in immunomodulatory hormones, there is significant potential to gain insight into the underlying physiology.

Effects of aging on endotoxin tolerance induced by lipopolysaccharides derived from Porphyromonas gingivalis and Escherichia coli

BACKGROUND

Periodontitis is a bacterially induced chronic inflammatory disease. Exposure of the host to periodontal pathogens and their virulence factors induces a state of hyporesponsiveness to subsequent stimulations, termed endotoxin tolerance. Aging has a profound effect on immune response to bacteria challenge. The aim of this study was to explore the effects of aging on endotoxin tolerance induced by Porphyromonas gingivalis (P. gingivalis) lipopolysaccharide (LPS) and Escherichia coli (E. coli) LPS in murine peritoneal macrophages.

METHODOLOGY/PRINCIPAL FINDINGS

We studied the cytokine production (TNF-α and IL-10) and Toll-like receptor 2, 4 (TLR2, 4) gene and protein expressions in peritoneal macrophages from young (2-month-old) and middle-aged (12-month-old) ICR mice following single or repeated P. gingivalis LPS or E. coli LPS stimulation. Pretreatment of peritoneal macrophages with P. gingivalis LPS or E. coli LPS resulted in a reduction in TNF-α production and an increase in IL-10 production upon secondary stimulation (p<0.05), and the markedly lower levels of TNF-α and higher levels of IL-10 were observed in macrophages from young mice compared with those from middle-aged mice (p<0.05). In addition, LPS restimulations also led to the significantly lower expression levels of TLR2, 4 mRNA and protein in macrophages from young mice (p<0.05).

CONCLUSIONS/SIGNIFICANCE

Repeated LPS stimulations triggered endotoxin tolerance in peritoneal macrophages and the ability to develop tolerance in young mice was more excellent. The impaired ability to develop endotoxin tolerance resulted from aging might be related to TLR2, 4 and might lead to the incontrollable periodontal inflammation in older adults.