Aral Ali Mubin, Zamora Ruben, Barclay Derek, Yin Jinling, El-Dehaibi Fayten, Erbas Vasil E, Dong Liwei, Zhang Zhaoxiang, Sahin Huseyin, Gorantla Vijay S, Vodovotz Yoram
Department of Surgery, University of Pittsburgh, Pittsburgh, PA, United States.
Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
Front Immunol. 2021 May 4;12:591154. doi: 10.3389/fimmu.2021.591154. eCollection 2021.
Systems-level insights into inflammatory events after vascularized composite allotransplantation (VCA) are critical to the success of immunomodulatory strategies of these complex procedures. To date, the effects of tacrolimus (TAC) immunosuppression on inflammatory networks in VCA, such as in acute rejection (AR), have not been investigated. We used a systems biology approach to elucidate the effects of tacrolimus on dynamic networks and principal drivers of systemic inflammation in the context of dynamic tissue-specific immune responses following VCA. Lewis (LEW) rat recipients received orthotopic hind limb VCA from fully major histocompatibility complex-mismatched Brown Norway (BN) donors or matched LEW donors. Group 1 (syngeneic controls) received LEW limbs without TAC, and Group 2 (treatment group) received BN limbs with TAC. Time-dependent changes in 27 inflammatory mediators were analyzed in skin, muscle, and peripheral blood using Principal Component Analysis (PCA), Dynamic Bayesian Network (DyBN) inference, and Dynamic Network Analysis (DyNA) to define principal characteristics, central nodes, and putative feedback structures of systemic inflammation. Analyses were repeated on skin + muscle data to construct a "Virtual VCA", and in skin + muscle + peripheral blood data to construct a "Virtual Animal." PCA, DyBN, and DyNA results from individual tissues suggested important roles for leptin, VEGF, various chemokines, the NLRP3 inflammasome (IL-1β, IL-18), and IL-6 after TAC treatment. The chemokines MCP-1, MIP-1α; and IP-10 were associated with AR in controls. Statistical analysis suggested that 24/27 inflammatory mediators were altered significantly between control and TAC-treated rats in peripheral blood, skin, and/or muscle over time. "Virtual VCA" and "Virtual Animal" analyses implicated the skin as a key control point of dynamic inflammatory networks, whose connectivity/complexity over time exhibited a U-shaped trajectory and was mirrored in the systemic circulation. Our study defines the effects of TAC on complex spatiotemporal evolution of dynamic inflammation networks in VCA. We also demonstrate the potential utility of computational analyses to elucidate nonlinear, cross-tissue interactions. These approaches may help define precision medicine approaches to better personalize TAC immunosuppression in VCA recipients.
对血管化复合组织移植(VCA)后炎症事件的系统层面洞察对于这些复杂手术免疫调节策略的成功至关重要。迄今为止,尚未研究他克莫司(TAC)免疫抑制对VCA炎症网络的影响,如在急性排斥反应(AR)中的影响。我们采用系统生物学方法,以阐明在VCA后动态组织特异性免疫反应背景下,他克莫司对全身炎症动态网络和主要驱动因素的影响。Lewis(LEW)大鼠受体接受来自完全主要组织相容性复合体不匹配的Brown Norway(BN)供体或匹配的LEW供体的原位后肢VCA。第1组(同基因对照组)接受未用TAC的LEW肢体,第2组(治疗组)接受用TAC的BN肢体。使用主成分分析(PCA)、动态贝叶斯网络(DyBN)推理和动态网络分析(DyNA)分析皮肤、肌肉和外周血中27种炎症介质随时间的变化,以定义全身炎症的主要特征、中心节点和假定的反馈结构。对皮肤+肌肉数据重复进行分析以构建“虚拟VCA”,并对皮肤+肌肉+外周血数据重复进行分析以构建“虚拟动物”。来自各个组织的PCA、DyBN和DyNA结果表明,TAC治疗后瘦素、VEGF、各种趋化因子、NLRP3炎性小体(IL-1β、IL-18)和IL-6发挥重要作用。趋化因子MCP-1、MIP-1α和IP-10与对照组的AR相关。统计分析表明,随着时间的推移,对照组和TAC治疗组大鼠在外周血、皮肤和/或肌肉中的24/27种炎症介质有显著变化。“虚拟VCA”和“虚拟动物”分析表明皮肤是动态炎症网络的关键控制点,其随时间的连通性/复杂性呈现U形轨迹,并反映在体循环中。我们的研究定义了TAC对VCA中动态炎症网络复杂时空演变的影响。我们还证明了计算分析在阐明非线性跨组织相互作用方面的潜在效用。这些方法可能有助于确定精准医学方法,以便更好地使VCA受体的TAC免疫抑制个性化。