Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

被引:84
作者
Caesar, Lindsay K. [1 ]
Montaser, Rana [1 ]
Keller, Nancy P. [2 ]
Kelleher, Neil L. [1 ,3 ]
机构
[1] Northwestern Univ, Dept Chem, Evanston, IL 60208 USA
[2] Univ Wisconsin, Dept Med Microbiol & Immunol & Bacteriol, Madison, WI USA
[3] Northwestern Univ, Dept Mol Biosci, Evanston, IL USA
基金
美国国家卫生研究院;
关键词
BIOSYNTHETIC GENE CLUSTERS; FUNGAL SECONDARY METABOLITES; MASS-SPECTROMETRY; MOLECULAR NETWORKING; ASPERGILLUS-FUMIGATUS; NONRIBOSOMAL PEPTIDE; GUIDED FRACTIONATION; SELF-RESISTANCE; RARE-EARTH; WEB SERVER;
D O I
10.1039/d1np00036e
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Covering: 2010 to 2021 Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.
引用
收藏
页码:2041 / 2065
页数:25
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