Requirement for multiple activation signals by anti-inflammatory feedback in macrophages

Combining Mathematical Models With Experimentation to Drive Novel Mechanistic Insights Into Macrophage Function

This perspective outlines an approach to improve mechanistic understanding of macrophages in inflammation and tissue homeostasis, with a focus on human inflammatory bowel disease (IBD). The approach integrates wet-lab and in-silico experimentation, driven by mechanistic mathematical models of relevant biological processes. Although wet-lab experimentation with genetically modified mouse models and primary human cells and tissues have provided important insights, the role of macrophages in human IBD remains poorly understood. Key open questions include: (1) To what degree hyperinflammatory processes (e.g., gain of cytokine production) and immunodeficiency (e.g., loss of bacterial killing) intersect to drive IBD pathophysiology? and (2) What are the roles of macrophage heterogeneity in IBD onset and progression? Mathematical modeling offers a synergistic approach that can be used to address such questions. Mechanistic models are useful for informing wet-lab experimental designs and provide a knowledge constrained framework for quantitative analysis and interpretation of resulting experimental data. The majority of published mathematical models of macrophage function are based either on animal models, or immortalized human cell lines. These experimental models do not recapitulate important features of human gastrointestinal pathophysiology, and, therefore are limited in the extent to which they can fully inform understanding of human IBD. Thus, we envision a future where mechanistic mathematical models are based on features relevant to human disease and parametrized by richer human datasets, including biopsy tissues taken from IBD patients, human organ-on-a-chip systems and other high-throughput clinical data derived from experimental medicine studies and/or clinical trials on IBD patients.

Regulation of Early Steps of GPVI Signal Transduction by Phosphatases: A Systems Biology Approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

A mathematical representation of the development of Mycobacterium tuberculosis active, latent and dormant stages

The majority of individuals infected with Mycobacterium tuberculosis (Mtb) bacilli develop latent infection. Mtb becomes dormant and phenotypically drug resistant when it encounters multiple stresses within the host, and expresses a set of genes, known as the dormancy regulon, in vivo. These genes are expressed in vitro in response to nitric oxide (NO), hypoxia (oxygen deprivation), and nutrient starvation. The occurrence and reactivation of latent tuberculosis (TB) is not clearly understood. The ability of the pathogen to enter and exit from different states is associated with its ability to cause persistent infection. During infection it is not known whether the organism is in a persistent slow replicating state or a dormant non-replicating state, with the latter ultimately causing a latent infection with the potential to reactivate to active disease. We collected gene expression data for Mtb bacilli under different stress conditions that simulate latency or dormancy. Time course experiments were selected and differentially expressed gene profiles were determined at each time point. A mathematical model was then developed to show the dynamics of Mtb latency based on the profile of differentially expressed genes. Analysis of the time course data show the dynamics of latency occurrence in vitro and the mathematical model reveals all possible scenarios of Mtb latency development with respect to the different conditions that may be produced by the immune response in vivo. The mathematical model provides a biological explanation of how Mtb latency occurs based on observed gene expression changes in in vitro latency models.

The timing of TNF and IFN-gamma signaling affects macrophage activation strategies during Mycobacterium tuberculosis infection

During most infections, the population of immune cells known as macrophages are key to taking up and killing bacteria as an integral part of the immune response. However, during infection with Mycobacterium tuberculosis (Mtb), host macrophages serve as the preferred environment for mycobacterial growth. Further, killing of Mtb by macrophages is impaired unless they become activated. Activation is induced by stimulation from bacterial antigens and inflammatory cytokines derived from helper T cells. The key macrophage-activating cytokines in Mtb infection are tumor necrosis factor-alpha (TNF) and interferon (IFN)-gamma. Due to differences in cellular sources and secretion pathways for TNF and IFN-gamma, the possibility of heterogeneous cytokine distributions exists, suggesting that the timing of macrophage activation from these signals may affect activation kinetics and thus impact the outcome of Mtb infection. Here we use a mathematical model to show that negative feedback from production of nitric oxide (the key mediator of mycobacterial killing) that typically optimizes macrophage responses to activating stimuli may reduce effective killing of Mtb. Statistical sensitivity analysis predicts that if TNF and IFN-gamma signals precede infection, the level of negative feedback may have a strong effect on how effectively macrophages kill Mtb. However, this effect is relaxed when IFN-gamma or TNF+IFN-gamma signals are received coincident with infection. Under these conditions, the model suggests that negative feedback induces fast responses and an initial overshoot of nitric oxide production for given doses of TNF and IFN-gamma, favoring killing of Mtb. Together, our results suggest that direct entry of macrophages into a granuloma site (and not distal to it) from lung vascular sources represents a preferred host strategy for mycobacterial control. We examine implications of these results in establishment of latent Mtb infection.

Effect of perioperative autologous versus allogeneic blood transfusion on the immune system in gastric cancer patients

BACKGROUND

Allogeneic blood transfusion-induced immunomodulation (TRIM) and its adverse effect on the prognosis of patients treated surgically for cancer remain complex and controversial. However, the potential risk associated with allogeneic blood transfusion has heightened interest in the use of autologous blood transfusion. In the present study, the serum concentrations of neopterin, interferon-gamma (IFN-gamma), T lymphocyte subsets (CD3(+), CD4(+), CD8(+), CD4(+)/CD8(+)) and a possible association between these variables were investigated. The purpose was to further evaluate the effect of autologous versus allogeneic blood transfusion on immunological status in patients undergoing surgery for gastric cancer.

METHODS

Sixty ASA I-II (American Society of Anesthesiologists) patients undergoing elective radical resection for stomach cancer were randomly allocated to receive either allogeneic blood transfusion (n=30) or autologous blood transfusion (n=30). Serum concentrations of the neopterin, IFN-gamma and T lymphocyte subsets in the recipients were measured before induction of anesthesia, after operation, and on the 5th postoperative day.

RESULTS

Both two groups, serum neopterin, IFN-gamma, percentages of T-cell subsets (CD3(+), CD4(+)), and CD4(+)/CD8(+) ratio had significantly decreased after operation, but decreased more significantly in group H (receiving allogeneic blood transfusion) than those in group A (receiving autologous whole blood transfusion) (P<0.05). On the 5th postoperative day, serum neopterin, IFN-gamma, CD3(+), CD4(+) T-cells, and CD4(+)/CD8(+) ratio returned to the baseline values in group A. In contrast, the above remain decreasing in group H, where there were no significant relations between serum neopterin and IFN-gamma.

CONCLUSION

Perioperative surgical trauma and stress have an immunosuppressive impact on gastric cancer patients. Allogeneic blood transfusion exacerbates the impaired immune response. Autologous blood transfusion might be significantly beneficial for immune-compromised patients in the perioperative period, clearly showing its superiority over allogeneic blood transfusion.