Heidari Maryam, Pakdel Abbas, Bakhtiarizadeh Mohammad Reza, Dehghanian Fariba
Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran.
Front Vet Sci. 2022 Jul 27;9:974444. doi: 10.3389/fvets.2022.974444. eCollection 2022.
Johne's disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) is a major concern in dairy industry. Since, the pathogenesis of the disease is not clearly known, it is necessary to develop an approach to discover molecular mechanisms behind this disease with high confidence. Biological studies often suffer from issues with reproducibility. Lack of a method to find stable modules in co-expression networks from different datasets related to Johne's disease motivated us to present a computational pipeline to identify non-preserved consensus modules. Two RNA-Seq datasets related to MAP infection were analyzed, and consensus modules were detected and were subjected to the preservation analysis. The non-preserved consensus modules in both datasets were determined as they are modules whose connectivity and density are affected by the disease. Long non-coding RNAs (lncRNAs) and TF genes in the non-preserved consensus modules were identified to construct integrated networks of lncRNA-mRNA-TF. These networks were confirmed by protein-protein interactions (PPIs) networks. Also, the overlapped hub genes between two datasets were considered hub genes of the consensus modules. Out of 66 consensus modules, 21 modules were non-preserved consensus modules, which were common in both datasets and 619 hub genes were members of these modules. Moreover, 34 lncRNA and 152 TF genes were identified in 12 and 19 non-preserved consensus modules, respectively. The predicted PPIs in 17 non-preserved consensus modules were significant, and 283 hub genes were commonly identified in both co-expression and PPIs networks. Functional enrichment analysis revealed that eight out of 21 modules were significantly enriched for biological processes associated with Johne's disease including "inflammatory response," "interleukin-1-mediated signaling pathway", "type I interferon signaling pathway," "cytokine-mediated signaling pathway," "regulation of interferon-beta production," and "response to interferon-gamma." Moreover, some genes (hub mRNA, TF, and lncRNA) were introduced as potential candidates for Johne's disease pathogenesis such as . This study expanded our knowledge of molecular mechanisms involved in Johne's disease, and the presented pipeline enabled us to achieve more valid results.
由副结核分枝杆菌（MAP）引起的约内氏病是乳制品行业的一个主要问题。由于该病的发病机制尚不清楚，因此有必要开发一种方法来高度可靠地发现该疾病背后的分子机制。生物学研究常常存在可重复性问题。由于缺乏一种方法来从与约内氏病相关的不同数据集中找到共表达网络中的稳定模块，促使我们提出一种计算流程来识别非保守的共表达模块。分析了两个与MAP感染相关的RNA测序数据集，检测到共表达模块并进行了保守性分析。确定了两个数据集中的非保守共表达模块，因为它们是其连通性和密度受疾病影响的模块。鉴定了非保守共表达模块中的长链非编码RNA（lncRNA）和转录因子（TF）基因，以构建lncRNA-mRNA-TF的整合网络。这些网络通过蛋白质-蛋白质相互作用（PPI）网络得到了证实。此外，两个数据集之间重叠的枢纽基因被视为共表达模块的枢纽基因。在66个共表达模块中，有21个是非保守共表达模块，这在两个数据集中都很常见，并且有619个枢纽基因是这些模块的成员。此外，分别在12个和19个非保守共表达模块中鉴定出34个lncRNA和152个TF基因。17个非保守共表达模块中的预测PPI具有显著性，并且在共表达和PPI网络中共同鉴定出283个枢纽基因。功能富集分析表明，21个模块中有8个显著富集了与约内氏病相关的生物学过程，包括“炎症反应”、“白细胞介素-1介导的信号通路”、“I型干扰素信号通路”、“细胞因子介导的信号通路”、“干扰素-β产生的调节”和“对干扰素-γ的反应”。此外，一些基因（枢纽mRNA、TF和lncRNA）被作为约内氏病发病机制的潜在候选基因引入，例如 。这项研究扩展了我们对约内氏病相关分子机制的认识，并且所提出的流程使我们能够获得更有效的结果。
