生物活性驱动的真菌代谢基因组学识别了抗增殖干细胞类似物及其生物合成基因集群
Navid J Ayon1,2, Cody E Earp3, Raveena Gupta1
1Department of Chemistry, Northwestern University, Evanston, IL, USA.
Metabolomics : Official journal of the Metabolomic Society
|August 2, 2024
概括
科学家们使用生物活性驱动的代谢基因组学工作流程,从真菌中发现新的抗癌化合物. 这种方法成功地识别了具有抗增殖活性的新型干电话类似物,将它们与它们的生物合成途径联系起来.
科学领域:
- 自然产品化学 自然产品化学
- 生物信息学是一种生物信息学.
- 代谢学 代谢学 代谢学
- 基因组学就是基因组学.
背景情况:
- 菌产生各种具有重要的生物活动的二次代谢物.
- 生物信息学结合了代谢学和基因组学,对于识别这些代谢物及其生物合成途径至关重要.
- 一项初步的代谢基因组学研究将超过230种代谢物与110种真菌中的代谢途径联系起来.
研究的目的:
- 开发一种生物活性驱动的代谢基因组学工作流程,以优先考虑生物活性天然产品的发现.
- 结合定量化学数据,抗扩散活性和基因组序列,以确定新型化合物和途径.
- 为有针对性的自然产品发现利用综合的"omics"数据.
主要方法:
- 测试了110种真菌菌株对抗癌细胞系的抗增殖活性.
- 精选的活性菌株用于分化,生物活性测试和质谱分析.
- 采用生物化学分析来预测活性化合物和代谢基因组学来确定它们的生物合成途径.
主要成果:
- 隔离了三种新的干细胞类似物 (19-乙干细胞G,B和E) 与抗增殖活性 (35μM) 对黑色素瘤和卵巢癌细胞.
- 为分离的化合物提出了一个生物合成途径.
- 证明了生物活性作为波器在综合"omics"数据分析中的实用性.
结论:
- 将生物化学测量纳入代谢基因组学可以提高生物活性代谢物的识别.
- 这种综合方法有效地将天然产品与其生物合成机制联系起来.
- 这项研究突出了从真菌来源发现新生物活性化合物的强大策略.
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