Machine Perfusion of Porcine Livers with Oxygen-Carrying Solution Results in Reprogramming of Dynamic Inflammation Networks

Abstract

Background:Ex vivo machine perfusion (MP) can better preserve organs for transplantation. We have recently reported on the first application of an MP protocol in which liver allografts were fully oxygenated, under dual pressures and subnormothermic conditions, with a new hemoglobin-based oxygen carrier (HBOC) solution specifically developed for ex vivo utilization. In those studies, MP improved organ function post-operatively and reduced inflammation in porcine livers. Herein, we sought to refine our knowledge regarding the impact of MP by defining dynamic networks of inflammation in both tissue and perfusate. Methods: Porcine liver allografts were preserved either with MP (n = 6) or with cold static preservation (CSP; n = 6), then transplanted orthotopically after 9 h of preservation. Fourteen inflammatory mediators were measured in both tissue and perfusate during liver preservation at multiple time points, and analyzed using Dynamic Bayesian Network (DyBN) inference to define feedback interactions, as well as Dynamic Network Analysis (DyNA) to define the time-dependent development of inflammation networks. Results: Network analyses of tissue and perfusate suggested an NLRP3 inflammasome-regulated response in both treatment groups, driven by the pro-inflammatory cytokine interleukin (IL)-18 and the anti-inflammatory mediator IL-1 receptor antagonist (IL-1RA). Both DyBN and DyNA suggested a reduced role of IL-18 and increased role of IL-1RA with MP, along with increased liver damage with CSP. DyNA also suggested divergent progression of responses over the 9 h preservation time, with CSP leading to a stable pattern of IL-18-induced liver damage and MP leading to a resolution of the pro-inflammatory response. These results were consistent with prior clinical, biochemical, and histological findings after liver transplantation. Conclusion: Our results suggest that analysis of dynamic inflammation networks in the setting of liver preservation may identify novel diagnostic and therapeutic modalities.

Keywords: inflammation; modeling; networks; porcine; reprogramming; transplant.

FIGURE 1

Tissue sample DyBNs suggest conserved network structure with central nodes IL-18 and IL-1RA, but decreased pro-inflammatory response with MP. CSP, cold static preservation (n = 6). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. Multiple inflammatory mediators were interrelated using DyBN inference. While the overall network structure is maintained, MP features fewer edges from the pro-inflammatory IL-18 than CSP.

FIGURE 2

Perfusate sample DyBNs suggest conserved network structure with central nodes IL-18 and IL-1RA, but decreased pro-inflammatory response and liver damage with MP. CSP, cold static preservation (n = 5). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. Multiple inflammatory mediators and liver damage markers AST and ALT were interrelated using DyBN inference. While the overall network structure is maintained, MP features fewer edges from the pro-inflammatory IL-18 than CSP, including a loss of both IL-18 self-feedback and an edge from IL-18 to major pro-inflammatory mediator IL-6. The centrality of liver damage markers AST and ALT is also decreased with MP, as seen most notably by the loss of bidirectional edges between AST and both IL-18 and IL-1RA.

FIGURE 3

Tissue sample DyNA networks contain more variables, total and negative edges than perfusate. CSP, cold static preservation (n = 6, tissue; n = 5, perfusate). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6, tissue; n = 6, perfusate). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. DyNA networks were then constructed for all timeframes, with variables and edges included in each network. Tissue networks consistently include more variables and connections than perfusate. Tissue networks also feature numerous negative (red, anticorrelated) edges. Within the tissue analyses, MP networks contain more negative edges and feature the earlier appearance of negative edges than CSP.

FIGURE 4

Network complexity DyNA. CSP, cold static preservation (n = 6, tissue; n = 5, perfusate). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6, tissue; n = 6, perfusate). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. Network complexity scores are consistently higher in tissue networks than perfusate. For both sample types, the initial CSP network is the most complex, with CSP network complexity decreasing over time. MP networks, which for both sample types start with lower complexity than CSP, remain relatively static in complexity throughout the preservation period.

FIGURE 5

Tissue sample DyNA networks suggest different network stability between preservation methods. CSP, cold static preservation (n = 6). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. IL-18, IL-1β, IL-1RA and IFN-γ are among the variables included in every tissue DyNA network. In the CSP analysis a complex initial network is followed by two networks in which a majority of variables only have two edges and whose structures are almost identical. Unlike CSP, the MP networks continue to fluctuate throughout the experimental time course.

FIGURE 6

Perfusate sample DyNA networks suggest divergent responses to preservation methods. CSP, cold static preservation (n = 5). Organs were preserved at standard hypothermic and anoxic conditions. MP, machine perfusion (n = 6). Organs were fully oxygenated under dual pressures under subnormothermic conditions with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. CSP networks show initial inclusion and interrelation of numerous pro-inflammatory mediators, including IL-18, and progress to stable connections between IL-18 and both AST and ALT, suggesting continual inflammation-driven liver damage. Anti-inflammatory IL-1RA never appears. MP networks show a restrained initial network, with IL-18 connected to IL-1RA and damage marker AST, but not to pro-inflammatory mediators. IL-18 then loses its connection to AST and by the final time period IL-18, IL-1RA, AST and ALT are not included, suggesting control and resolution of inflammation with minimal liver damage.

FIGURE 7

Hepatic response to insult regulated by IL-18, IL-1RA. Levels of IFN-γ, and by extension the strength of the IFN-γ-driven positive feedback loop of hepatic damage, are connected in three pathways to the early, NLRP3-driven hepatic response to insult. One of these pathways can be downregulated by IL-1RA (C), one can be upregulated by IL-18 (A), and one can be both downregulated by IL-1RA and upregulated by IL-18 (B). Thus, the relative balance of these two mediators may control the level of response.