Department of Systems Biology, Center for Microbial Biotechnology, Technical University of Denmark, Lyngby, Denmark.
PLoS One. 2010 Oct 25;5(10):e13606. doi: 10.1371/journal.pone.0013606.
Identifying causative biological networks associated with relevant phenotypes is essential in the field of systems biology. We used ferulic acid (FA) as a model antioxidant to characterize the global expression programs triggered by this small molecule and decipher the transcriptional network controlling the phenotypic adaptation of the yeast Saccharomyces cerevisiae.
METHODOLOGY/PRINCIPAL FINDINGS: By employing a strict cut off value during gene expression data analysis, 106 genes were found to be involved in the cell response to FA, independent of aerobic or anaerobic conditions. Network analysis of the system guided us to a key target node, the FMP43 protein, that when deleted resulted in marked acceleration of cellular growth (∼15% in both minimal and rich media). To extend our findings to human cells and identify proteins that could serve as drug targets, we replaced the yeast FMP43 protein with its human ortholog BRP44 in the genetic background of the yeast strain Δfmp43. The conservation of the two proteins was phenotypically evident, with BRP44 restoring the normal specific growth rate of the wild type. We also applied homology modeling to predict the 3D structure of the FMP43 and BRP44 proteins. The binding sites in the homology models of FMP43 and BRP44 were computationally predicted, and further docking studies were performed using FA as the ligand. The docking studies demonstrated the affinity of FA towards both FMP43 and BRP44.
This study proposes a hypothesis on the mechanisms yeast employs to respond to antioxidant molecules, while demonstrating how phenome and metabolome yeast data can serve as biomarkers for nutraceutical discovery and development. Additionally, we provide evidence for a putative therapeutic target, revealed by replacing the FMP43 protein with its human ortholog BRP44, a brain protein, and functionally characterizing the relevant mutant strain.
在系统生物学领域，识别与相关表型相关的因果生物网络至关重要。我们使用阿魏酸（FA）作为模型抗氧化剂，以表征该小分子引发的全局表达程序，并破译控制酵母酿酒酵母表型适应的转录网络。
方法/主要发现：通过在基因表达数据分析过程中采用严格的截止值，发现 106 个基因参与了细胞对 FA 的反应，与需氧或厌氧条件无关。系统的网络分析引导我们找到了一个关键的目标节点，即 FMP43 蛋白，当该蛋白缺失时，细胞生长明显加快（在最小和丰富培养基中均约为 15%）。为了将我们的发现扩展到人细胞，并鉴定可作为药物靶点的蛋白质，我们在酵母菌株Δ fmp43 的遗传背景中用其人类同源物 BRP44 替换了酵母 FMP43 蛋白。两种蛋白质的保守性在表型上显而易见，BRP44 恢复了野生型的正常比生长速率。我们还应用同源建模来预测 FMP43 和 BRP44 蛋白质的 3D 结构。在 FMP43 和 BRP44 的同源模型中计算预测了结合位点，并使用 FA 作为配体进行了进一步的对接研究。对接研究表明 FA 对 FMP43 和 BRP44 均具有亲和力。
本研究提出了一个关于酵母应对抗氧化分子的机制的假设，同时证明了表型和代谢组学酵母数据如何可以作为营养发现和开发的生物标志物。此外，我们通过用其人类同源物 BRP44 替换 FMP43 蛋白提供了一个潜在的治疗靶点的证据，该蛋白是一种脑蛋白，并对相关突变株进行了功能表征。
