Centro de Genómica y Bioinformática, Facultad de Ciencias, Ingeniería y Tecnología, Universidad Mayor, Santiago, Chile.
Programa de Doctorado en Genómica Integrativa, Vicerrectoría de Investigación, Universidad Mayor, Santiago, Chile.
Front Immunol. 2023 Dec 14;14:1264599. doi: 10.3389/fimmu.2023.1264599. eCollection 2023.
is the most important health problem facing Chilean Aquaculture. Previous reports suggest that can survive in salmonid macrophages by interfering with the host immune response. However, the relevant aspects of the molecular pathogenesis of have been poorly characterized. In this work, we evaluated the transcriptomic changes in macrophage-like cell line SHK-1 infected with at 24- and 48-hours post-infection (hpi) and generated network models of the macrophage response to the infection using co-expression analysis and regulatory transcription factor-target gene information. Transcriptomic analysis showed that 635 genes were differentially expressed after 24- and/or 48-hpi. The pattern of expression of these genes was analyzed by weighted co-expression network analysis (WGCNA), which classified genes into 4 modules of expression, comprising early responses to the bacterium. Induced genes included genes involved in metabolism and cell differentiation, intracellular transportation, and cytoskeleton reorganization, while repressed genes included genes involved in extracellular matrix organization and RNA metabolism. To understand how these expression changes are orchestrated and to pinpoint relevant transcription factors (TFs) controlling the response, we established a curated database of TF-target gene regulatory interactions in , SalSaDB. Using this resource, together with co-expression module data, we generated infection context-specific networks that were analyzed to determine highly connected TF nodes. We found that the most connected TF of the 24- and 48-hpi response networks is KLF17, an ortholog of the KLF4 TF involved in the polarization of macrophages to an M2-phenotype in mammals. Interestingly, while KLF17 is induced by infection, other TFs, such as NOTCH3 and NFATC1, whose orthologs in mammals are related to M1-like macrophages, are repressed. In sum, our results suggest the induction of early regulatory events associated with an M2-like phenotype of macrophages that drives effectors related to the lysosome, RNA metabolism, cytoskeleton organization, and extracellular matrix remodeling. Moreover, the M1-like response seems delayed in generating an effective response, suggesting a polarization towards M2-like macrophages that allows the survival of . This work also contributes to SalSaDB, a curated database of TF-target gene interactions that is freely available for the Atlantic salmon community.
是智利水产养殖面临的最重要的健康问题。先前的报告表明, 可以通过干扰宿主免疫反应在鲑鱼巨噬细胞中存活。然而, 的分子发病机制的相关方面尚未得到很好的描述。在这项工作中,我们评估了感染后 24 小时和 48 小时的 SHK-1 巨噬细胞样细胞系中 的转录组变化,并使用共表达分析和调节转录因子-靶基因信息生成了巨噬细胞对感染反应的网络模型。转录组分析表明,感染后 24 小时和/或 48 小时有 635 个基因表达差异。通过加权共表达网络分析(WGCNA)对这些基因的表达模式进行分析,将基因分为 4 个表达模块,包括对细菌的早期反应。诱导基因包括参与代谢和细胞分化、细胞内运输和细胞骨架重排的基因,而抑制基因包括参与细胞外基质组织和 RNA 代谢的基因。为了了解这些表达变化是如何协调的,并确定控制反应的相关转录因子(TFs),我们在 中建立了一个经过验证的 TF-靶基因调控相互作用数据库,SalSaDB。利用这一资源和共表达模块数据,我们生成了感染背景特异性网络,对其进行分析以确定高连接的 TF 节点。我们发现,24 小时和 48 小时反应网络中最连接的 TF 是 KLF17,这是哺乳动物中参与巨噬细胞极化到 M2 表型的 KLF4 TF 的同源物。有趣的是,虽然 感染诱导了 KLF17 的表达,但其他 TF,如 NOTCH3 和 NFATC1,其在哺乳动物中的同源物与 M1 样巨噬细胞有关,却被抑制。总之,我们的研究结果表明,与 M2 样巨噬细胞表型相关的早期调控事件的诱导,驱动与溶酶体、RNA 代谢、细胞骨架组织和细胞外基质重塑相关的效应物。此外,M1 样反应似乎在产生有效反应时被延迟,这表明向 M2 样巨噬细胞极化,从而允许 的存活。这项工作也为 SalSaDB 做出了贡献,这是一个经过验证的 TF-靶基因相互作用数据库,可供大西洋鲑鱼社区免费使用。