Data_Sheet_3_Independent Component Analysis Identifies the Modulons Expanding the Transcriptional Regulatory Networks of Enterohemorrhagic Escherichia coli.XLSX

The elucidation of the transcriptional regulatory networks (TRNs) of enterohemorrhagic Escherichia coli (EHEC) is critical to understand its pathogenesis and survival in the host. However, the analyses of current TRNs are still limited to comprehensively understand their target genes generally co-regulated under various conditions regardless of the genetic backgrounds. In this study, independent component analysis (ICA), a machine learning-based decomposition method, was used to decompose the large-scale transcriptome data of EHEC into the modulons, which contain the target genes of several TRNs. The locus of enterocyte effacement (LEE) and the Shiga toxin (Stx) modulons mainly consisted of the Ler regulon and the Stx prophage genes, respectively, confirming that ICA properly grouped the co-regulated major virulence genes of EHEC. Further investigation revealed that the LEE modulon contained the hypothetical Z0395 gene as a novel member of the Ler regulon, and the Stx modulon contained the thi and cus locus genes in addition to the Stx prophage genes. Correspondingly, the Stx prophage genes were also regulated by thiamine and copper ions known to control the thi and cus locus genes, respectively. The modulons effectively clustered the genes co-regulated regardless of the growth conditions and the genetic backgrounds of EHEC. The changed activities of the individual modulons successfully explained the differential expressions of the virulence and survival genes during the course of infection in bovines. Altogether, these results suggested that ICA of the large-scale transcriptome data can expand and enhance the current understanding of the TRNs of EHEC.

解析肠出血性大肠杆菌（enterohemorrhagic Escherichia coli, EHEC）的转录调控网络（transcriptional regulatory networks, TRNs），对于理解其致病机制与宿主内生存能力至关重要。然而，当前对转录调控网络的分析仍存在局限，难以全面阐明不同遗传背景下、多种条件下共同调控的靶基因。本研究采用基于机器学习的分解方法——独立成分分析（independent component analysis, ICA），将肠出血性大肠杆菌的大规模转录组数据分解为多个调控模块（modulons），每个模块包含多个转录调控网络的靶基因。肠细胞脱落位点（locus of enterocyte effacement, LEE）与志贺毒素（Shiga toxin, Stx）调控模块分别主要由Ler调控子与志贺毒素原噬菌体基因构成，这证实独立成分分析能够正确将肠出血性大肠杆菌的主要共同调控毒力基因进行聚类。进一步研究发现，LEE调控模块包含假定基因Z0395，将其鉴定为Ler调控子的新成员；而Stx调控模块除志贺毒素原噬菌体基因外，还包含thi与cus位点基因。相应地，志贺毒素原噬菌体基因同样受到硫胺素与铜离子的调控——这两种物质分别已知可调控thi与cus位点基因。这些调控模块能够有效聚类共同调控的基因，且不受肠出血性大肠杆菌的生长条件与遗传背景影响。各调控模块的活性变化，成功阐释了牛宿主感染过程中，毒力与生存相关基因的差异表达情况。综上，本研究结果表明，对大规模转录组数据开展独立成分分析，能够拓展并加深我们对肠出血性大肠杆菌转录调控网络的认知。