Enterococcus faecalis depletes intestinal collagen, activates the host tissue protease MMP9, and contributes to anastomotic leak.

Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. “Systems biology” is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians.

To introduce a form of mathematical modeling, agent-based modeling (ABM), and demonstrate its potential uses in the evaluation of the dynamics of the innate immune response (IIR) and the development of possible treatments for systemic inflammatory response syndrome (SIRS)/multiple organ failure (MOF). The IIR can be categorized as a complex system that responds to interventions in a nonintuitive fashion, leading to difficulty in translating basic science knowledge into effective treatments for SIRS/MOF. It is proposed that ABM is particularly well suited to examining the complex interactions of the IIR and its disordered states of SIRS/MOF. Computer simulation and mathematical modeling. Review articles on components and mechanisms involved in the IIR. Published results from phase III anticytokine/mediator trials. Published results from smaller clinical trials and animal studies. An abstract ABM of the IIR was created. The model reproduces the general behavior of the IIR with respect to outcome and cause of system “death.” Patterns of levels of individual cytokines matched patterns of measured cytokines reported in the existing literature. Clinical trials of anticytokine therapy were simulated and produced outcomes qualitatively similar to those reported in the literature. A series of hypothetical treatment regimes (variation of dose and length of treatment [anti-tumor necrosis factor and anti-interleukin-1], anti-CD-18, and multiple-drug regimes [combination of anti-tumor necrosis factor, anti-interleukin-1, and anti-CD-18]) were formulated and implemented in the ABM. None of the simulated therapies showed a statistically significant improvement in system mortality. Presented herein is an abstracted ABM of the IIR. This model is intended primarily as an introduction to and demonstration of this technique. However, even this relatively simple model demonstrates counterintuitive system responses and the difficulty of effectively manipulating a complex system like the IIR. ABM may provide a synthetic, analytical platform to integrate basic science data on the IIR, thus eventually aiding in formulating and testing future mediator-directed therapies for SIRS/MOF before clinical trials, and it may provide insights into directions of future research.

Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient’s immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.

The most feared complication following intestinal resection is anastomotic leakage. In high risk areas (esophagus/rectum) where neoadjuvant chemoradiation is used, the incidence of anastomotic leaks remains unacceptably high (∼10%) even when performed by specialist surgeons in high volume centers. The aims of this study were to test the hypothesis that anastomotic leakage develops when pathogens colonizing anastomotic sites become in vivo transformed to express a tissue destroying phenotype. We developed a novel model of anastomotic leak in which rats were exposed to pre-operative radiation as in cancer surgery, underwent distal colon resection and then were intestinally inoculated with Pseudomonas aeruginosa, a common colonizer of the radiated intestine. Results demonstrated that intestinal tissues exposed to preoperative radiation developed a significant incidence of anastomotic leak (>60%; p<0.01) when colonized by P. aeruginosa compared to radiated tissues alone (0%). Phenotype analysis comparing the original inoculating strain (MPAO1- termed P1) and the strain retrieved from leaking anastomotic tissues (termed P2) demonstrated that P2 was altered in pyocyanin production and displayed enhanced collagenase activity, high swarming motility, and a destructive phenotype against cultured intestinal epithelial cells (i.e. apoptosis, barrier function, cytolysis). Comparative genotype analysis between P1 and P2 revealed a single nucleotide polymorphism (SNP) mutation in the mexT gene that led to a stop codon resulting in a non-functional truncated protein. Replacement of the mutated mexT gene in P2 with mexT from the original parental strain P1 led to reversion of P2 to the P1 phenotype. No spontaneous transformation was detected during 20 passages in TSB media. Use of a novel virulence suppressing compound PEG/Pi prevented P. aeruginosa transformation to the tissue destructive phenotype and prevented anastomotic leak in rats. This work demonstrates that in vivo transformation of microbial pathogens to a tissue destroying phenotype may have important implications in the pathogenesis of anastomotic leak.