Pullen Krista M, Finethy Ryan, Ko Seung-Hyun B, Reames Charlotte J, Sassetti Christopher M, Lauffenburger Douglas A
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Microbiology and Physiological Systems, UMass Chan Medical School, Worcester, MA, USA.
NPJ Syst Biol Appl. 2025 Feb 15;11(1):19. doi: 10.1038/s41540-024-00487-6.
Numerous studies have identified similarities in blood transcriptomic signatures of tuberculosis (TB) phenotypes between mice and humans, including type 1 interferon production and innate immune cell activation. However, murine infection pathophysiology is distinct from human disease. We hypothesized that this is partly due to differences in the relative importance of biological pathways across species. To address this animal-to-human gap, we applied a systems modeling framework, Translatable Components Regression, to identify the axes of variation in the preclinical data most relevant to human TB disease state. Among the pathways our cross-species model pinpointed as highly predictive of human TB phenotype was the infection-induced unfolded protein response. To validate this mechanism, we confirmed that this cellular stress pathway modulates immune functions in Mycobacterium tuberculosis-infected mouse macrophages. Our work demonstrates how systems-level computational models enhance the value of animal studies for elucidating complex human pathophysiology.
众多研究已确定小鼠和人类结核病（TB）表型的血液转录组特征存在相似性，包括1型干扰素产生和先天免疫细胞激活。然而，小鼠感染的病理生理学与人类疾病不同。我们推测，这部分是由于跨物种生物途径的相对重要性存在差异。为了弥合这种从动物到人类的差距，我们应用了一个系统建模框架——可翻译成分回归，以确定临床前数据中与人类结核病疾病状态最相关的变异轴。我们的跨物种模型确定为对人类结核病表型具有高度预测性的途径之一是感染诱导的未折叠蛋白反应。为了验证这一机制，我们证实了这种细胞应激途径可调节结核分枝杆菌感染的小鼠巨噬细胞中的免疫功能。我们的工作展示了系统水平的计算模型如何提高动物研究在阐明复杂人类病理生理学方面的价值。
