Transcriptional complex assembly represented in SBGN PD

This poster shows how transcriptional complex assembly can be represented in SBGN Process Description language. Example: LPS-induced TNF-alpha enhancer complex formation

The in silico macrophage: toward a better understanding of inflammatory disease

Macrophages function as sentinel, cell-regulatory hubs capable of initiating, perpetuating and contributing to the resolution of an inflammatory response, following their activation from a resting state. Highly complex and varied gene expression programs within the macrophage enable such functional diversity. To investigate how programs of gene expression relate to the phenotypic attributes of the macrophage, the development of in silico modeling methods is needed. Such models need to cover multiple scales, from molecular pathways in cell-autonomous immunity and intercellular communication pathways in tissue inflammation to whole organism response pathways in systemic disease. Here, we highlight the potential of in silico macrophage modeling as an amenable and important yet under-exploited tool in aiding in our understanding of the immune inflammatory response. We also discuss how in silico macrophage modeling can help in future therapeutic strategies for modulating both the acute protective effects of inflammation (such as host defense and tissue repair) and the harmful chronic effects (such as autoimmune diseases).Comment: 7 pages plus 1 figur

Patients with transplantation have reduced mortality in bacteraemia:Analysis of data from a randomised trial

Objectives Infection remains a major complication of organ transplantation. Paradoxically, epidemiological studies suggest better survival from serious infection. We analysed the relationship between organ transplantation and short -term mortality of patients with bloodstream infection. Methods Data on transplantation status was extracted from a large prospective, multi-centre clinical trial in bloodstream infection. Logistic regression for 28-day mortality was performed on the whole cohort and a propensity-matched cohort (3:1). Infective pathogen, focus of infection, and clinical variables were included in the model. Mediation analysis was performed on clinical variables to explore causation. Results 4,178 participants were included in the full cohort, with 868 in the matched cohort, of which 217 received an organ transplant. Haematopoietic stem cell transplants (HSCT) were the most common transplant (n = 99), followed by kidney (n = 70). The most common pathogens were staphylococci and Enterobacterales. Transplantation status was associated with a reduced mortality in both the whole (Odds Ratio, OR 0.53; 95% CI 0.28, 0.77) and matched (OR 0.55, 95% CI 0.34, 0.90) cohort, while steroid use was robustly associated with increased mortality OR 4.4 (95% CI 3.12, 6.20) in the whole cohort and OR 5.24 (95% CI 2.79, 9.84) in the matched cohort. There was no interaction between steroid use and transplant status, so transplant patients on steroids generally had increased mortality relative to those without either. Conclusions Organ transplantation is associated with a near halving of short term mortality in bloodstream infection, including a cohort matched for comorbidities, infective pathogen and focus. Steroid usage is associated with increased mortality regardless of transplant status. Understanding the mechanism and causation of this mortality benefit should be a focus of future research

Use of logic theory in understanding regulatory pathway signaling in response to infection

Biological pathways link the molecular and cellular levels of biological activity and perform complex information processing seamlessly. Systems biology aims to combine an understanding of the cause–effect relationships of each individual interaction to build an understanding of the function of whole pathways. Therapies that target the ‘host’ biological processes in infectious diseases are often limited to the use of vaccines and biologics rather than small molecules. The development of host drug targets for small molecules is constrained by a limited knowledge of the underlying role of each target, particularly its potential to cause harmful side effects after targeting. By considering the combinatorial complexity of pathways from the outset, we can develop modeling tools that are better suited to analyzing large pathways, enabling us to identify new causal relationships. This could lead to new drug target strategies that beneficially disrupt host–pathogen interactions, minimizing the number of side effects. We introduce logic theory as part of a pathway modeling approach that can provide a new framework for understanding pathways and refine ‘host-based’ drug target identification strategies

Sepsis target validation for repurposing and combining complement and immune checkpoint inhibition therapeutics

Introduction: Sepsis is a disease that occurs due to an adverse immune response to infection by bacteria, viruses and fungi and is the leading pathway to death by infection. The hallmarks for maladapted immune reactions in severe sepsis, which contribute to multiple organ failure and death, are bookended by the exacerbated activation of the complement system to protracted T-cell dysfunction states orchestrated by immune checkpoint control. Despite major advances in our understanding of the condition, there remains to be either a definitive test or an effective therapeutic intervention. Areas covered: The authors consider a combinational drug therapy approach using new biologics, and mathematical modeling for predicting patient responses, in targeting innate and adaptive immune mediators underlying sepsis. Special consideration is given for emerging complement and immune checkpoint inhibitors that may be repurposed for sepsis treatment. Expert opinion: In order to overcome the challenges inherent to finding new therapies for the complex dysregulated host response to infection that drives sepsis, it is necessary to move away from monotherapy and promote precision for personalized combinatory therapies. Notably, combinatory therapy should be guided by predictive systems models of the immune-metabolic characteristics of an individual’s disease progression

Time-to-positivity in bloodstream infection is not a prognostic marker for mortality:analysis of a prospective multicentre randomized control trial

Objectives Time to positivity (TTP), calculated automatically in modern blood culture systems, is considered a proxy for microbial load and has been suggested as a potential prognostic marker in bloodstream infections. In this large, multicentre, prospectively collected cohort, our primary analysis aimed to quantify the relationship between the TTP of monomicrobial blood cultures and mortality. Methods Data from a multicentre randomized controlled trial (RAPIDO) in bloodstream infection were analysed. Bloodstream infections were classified into 13 groups/subgroups. The relationship between mortality and TTP was assessed by logistic regression, adjusted for site, organism, and clinical variables, and linear regression was applied to examine the association between clinical variables and TTP. Robustness was assessed by sensitivity analysis. Results In total 4468 participants were included in the RAPIDO. After exclusions, 3462 were analysed, with the most common organisms being coagulase-negative staphylococci (1072 patients) and Escherichia coli (861 patients); 785 patients (22.7%) died within 28 days. We found no relationship between TTP and mortality for any groups except for streptococci (odds ratio (OR) with each hour 0.98, 95%CI 0.96–1.00) and Candida (OR 1.03, 95%CI 1.00–1.05). There was large variability between organisms and sites in TTP. Fever (geometric mean ratio (GMR) 0.95, 95%CI 0.92–0.99), age (GMR per 10 years 1.01, 95%CI 1.00–1.02), and neutrophilia were associated with TTP (GMR 1.03, 95%CI 1.02–1.04). Conclusions Time to positivity is not associated with mortality, except in the case of Candida spp. (longer times associated with worse outcomes) and possibly streptococci (shorter times associated with worse outcomes). There was a large variation between median times across centres, limiting external validity

Infection homeostasis:implications for therapeutic and immune programming of metabolism in controlling infection

Homeostasis underpins at a systems level the regulatory control of immunity and metabolism. While physiologically these systems are often viewed as independent, there is increasing evidence showing a tight coupling between immune and metabolic functions. Critically upon infection, the homeostatic regulation for both immune and metabolic pathways is altered yet these changes are often investigated in isolation. Here, we summarise our current understanding of these processes in the context of a clinically relevant pathogen, cytomegalovirus. We synthesise from the literature an integrative view of a coupled immune–metabolic infection process, centred on sugar and lipid metabolism. We put forward the notion that understanding immune control of key metabolic enzymatic steps in infection will promote the future development of novel therapeutic modalities based on metabolic modifiers that either enhance protection or inhibit infection