Introduction. Infection caused by Mycobacterium tuberculosis (M. tb) is still a leading cause of mortality worldwide with estimated 1.4 million deaths annually. Hypothesis/Gap statement. Despite macrophages' ability to kill bacterium, M. tb can grow inside these innate immune cells and the exploration of the infection has traditionally been characterized by a one-sided relationship, concentrating solely on the host or examining the pathogen in isolation. Aim. Because of only a handful of M. tb–host interactions have been experimentally characterized, our main goal is to predict protein–protein interactions during the early phases of the infection. Methodology. In this work, we performed an integrative computational approach that exploits differentially expressed genes obtained from Dual RNA-seq analysis combined with known domain–domain interactions. Results. A total of 2381 and 7214 genes were identified as differentially expressed in M. tb and in THP-1-like macrophages, respectively, revealing different transcriptional profiles in response to infection. Over 48 h of infection, the host–pathogen network revealed 25 016 PPIs. Analysis of the resulting predicted network based on cellular localization information of M. tb proteins, indicated the implication of interacting nodes including the bacterial PE/PPE/PE_PGRS family. In addition, M. tb proteins interacted with host proteins involved in NF-kB signalling pathway as well as interfering with the host apoptosis ability via the potential interaction of M. tb TB16.3 with human TAB1 and M. tb GroEL2 with host protein kinase C delta, respectively. Conclusion. The prediction of the full range of interactions between M. tb and host will contribute to better understanding of the pathogenesis of this bacterium and may provide advanced approaches to explore new therapeutic targets against tuberculosis.

中文翻译：

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通过双RNA-seq分析和计算方法揭示结核分枝杆菌-THP-1样巨噬细胞蛋白质-蛋白质相互作用图

介绍。结核分枝杆菌 (M. tb )引起的感染仍然是全世界死亡的主要原因，估计每年有 140 万人死亡。假设/差距陈述。尽管巨噬细胞具有杀死细菌的能力，但结核分枝杆菌可以在这些先天免疫细胞内生长，并且传统上对感染的探索具有片面关系的特征，即仅关注宿主或孤立地检查病原体。目的。由于只有少数结核分枝杆菌与宿主的相互作用得到了实验表征，我们的主要目标是预测感染早期阶段的蛋白质-蛋白质相互作用。方法。在这项工作中，我们采用了一种综合计算方法，利用从双 RNA-seq 分析中获得的差异表达基因，并结合已知的域-域相互作用。结果。共有 2381 个和 7214 个基因分别被鉴定为在结核分枝杆菌和 THP-1 样巨噬细胞中差异表达，揭示了对感染的不同转录谱。感染 48 小时后，宿主-病原体网络显示出 25 016 个 PPI。基于结核分枝杆菌蛋白的细胞定位信息对所得预测网络进行分析，表明了包括细菌 PE/PPE/PE_PGRS 家族在内的相互作用节点的含义。此外，M. tb蛋白与参与 NF-kB 信号通路的宿主蛋白相互作用，并通过M. tb TB16.3 与人 TAB1 和M. tb GroEL2 与宿主蛋白激酶的潜在相互作用干扰宿主细胞凋亡能力。分别为 C δ。结论。对结核分枝杆菌与宿主之间全方位相互作用的预测将有助于更好地了解该细菌的发病机制，并可能为探索结核病新的治疗靶点提供先进的方法。