Kadarmideen Haja N, Watson-Haigh Nathan S, Andronicos Nicholas M
Commonwealth Scientific and Industrial Research Organisation, Livestock Industries, Davies Laboratory, PMB PO Aitkenvale, Townsville, QLD 4814, Australia.
Mol Biosyst. 2011 Jan;7(1):235-46. doi: 10.1039/c0mb00190b. Epub 2010 Nov 11.
This study reports on the molecular systems biology of gastrointestinal nematode (GIN) infection and potential biomarkers for GIN resistance in sheep. Microarray gene expression data were obtained for 3 different tissues at 4 time points from sheep artificially challenged with two types of nematodes, Haemonchus contortus (HC) and Trichostrongylus colubriformis (TC). We employed an integrated systems biology approach, integrating 3 main methods: standard differential gene expression analyses, weighted gene co-expression network analyses (WGCNA) and quantitative genetic analyses of gene expression traits of key biomarkers. Using standard differential gene expression analyses we identified differentially expressed genes (DE) which responded differently in sheep challenged with HC compared to those challenged with TC. These interaction genes (e.g. MRPL51, SMEK2, CAT, MAPK1IP1 and SLC25A20A) were enriched in Wnt receptor signalling pathway (p = 0.0132) and positive regulation of NFκβ transcription factor activity (p = 0.00208). We report FCER1A, a gene encoding a high-affinity receptor for the Fc region of immunoglobulin E, which is linked to innate immunity to GIN in sheep. Using weighted gene co-expression network analysis (WGCNA) methods, we identified gene modules that were correlated with the length of infection (disease modules). Hub genes (with high intramodular connectivity) were filtered further to identify biomarkers that are related to the length of infection (e.g. CAT, FBX033, COL15A1, IGFBP7, FBLN1 and IgCgamma). The biomarkers we found in HC networks were significantly associated with functions such as T-cell and B-cell regulations, TNF-alpha, interleukin and cytokine production. In TC networks, biomarkers were significantly associated with functions such as protein catabolic process, heat shock protein binding, protein targeting and localization, cytokine receptor binding, TNF receptor binding, apoptosis and IGF binding. These results provide specific gene targets for therapeutic interventions and provide insights into GIN infections in sheep which may be used to infer the same in related host species. This is also the first study to apply the concept of estimating breeding values of animals to expression traits and reveals 11 heritable candidate biomarkers (0.05 to 0.92) that could be used in selection of animals for GIN resistance.
本研究报告了胃肠道线虫(GIN)感染的分子系统生物学以及绵羊对GIN抗性的潜在生物标志物。从人工感染两种线虫,即捻转血矛线虫(HC)和蛇形毛圆线虫(TC)的绵羊身上,在4个时间点获取了3种不同组织的微阵列基因表达数据。我们采用了一种综合系统生物学方法,整合了3种主要方法:标准差异基因表达分析、加权基因共表达网络分析(WGCNA)以及关键生物标志物基因表达性状的数量遗传分析。使用标准差异基因表达分析,我们鉴定出了差异表达基因(DE),这些基因在感染HC的绵羊与感染TC的绵羊中的反应不同。这些相互作用基因(如MRPL51、SMEK2、CAT、MAPK1IP1和SLC25A20A)在Wnt受体信号通路(p = 0.0132)和NFκβ转录因子活性的正调控(p = 0.00208)中富集。我们报告了FCER1A,这是一个编码免疫球蛋白E Fc区高亲和力受体的基因,它与绵羊对GIN的固有免疫相关。使用加权基因共表达网络分析(WGCNA)方法,我们鉴定出了与感染时长相关的基因模块(疾病模块)。进一步筛选出枢纽基因(具有高模块内连通性),以鉴定与感染时长相关的生物标志物(如CAT、FBX033、COL15A1、IGFBP7、FBLN1和IgCgamma)。我们在HC网络中发现的生物标志物与T细胞和B细胞调节、TNF-α、白细胞介素和细胞因子产生等功能显著相关。在TC网络中,生物标志物与蛋白质分解代谢过程、热休克蛋白结合、蛋白质靶向和定位、细胞因子受体结合、TNF受体结合、细胞凋亡和IGF结合等功能显著相关。这些结果为治疗干预提供了特定的基因靶点,并为绵羊的GIN感染提供了见解,这些见解可能用于推断相关宿主物种中的相同情况。这也是第一项将动物育种值估计概念应用于表达性状的研究,并揭示了11个可用于选择抗GIN动物的可遗传候选生物标志物(0.05至0.92)。