Library construction and targeted BGC screening for more efficient discovery of microbial natural products

doi:10.12211/2096-8280.2023-083

Abstract

Abstract:

Microbial natural products (NPs) are a major source for mining small molecule drugs, which have been widely used in medicine, agriculture, and other fields. Growing antimicrobial resistance and other public health problems necessitate the rapid discovery of microbial NPs with novel structures and bioactivities. With rapid advances in high-throughput screening and low-cost DNA sequencing technologies, highly diverse biosynthetic gene clusters (BGCs) have been detected in bacteria and fungi, but characterized compounds are limited, representing the tip of an iceberg, and much more novel small molecules are awaiting for being discovered. Although various strategies have been developed for NP discovery, effectively linking the biosynthetic pathways to their encoded products remains a challenge. Recently, (meta)genomic library construction strategies have shown advantages in elucidating NP biosynthetic pathways more efficiently, and significantly accelerated the discovery of novel NPs by combining with high-efficient targeted BGC screening approaches. In this review, we summarize three strategies for discovering microbial NPs based on (meta)genomic library construction and targeted BGC screening. We also discuss the cloning vectors including Cosmid/Fosmid, BAC/PAC and FAC/YAC, and comment strategies for library construction and targeted BGC screening, such as LEXAS and CONKAT-Seq. Furthermore, we compare strengths, limitations, and applicability of different libraries. At the end, we prospect the future developments of these strategies for the high-throughput discovery of microbial NPs.

Key words: microbial natural products, (meta)genomic mining, biosynthetic gene cluster, library construction, targeted BGC screening

摘要：

微生物天然产物作为小分子药物的主要来源，已被广泛应用于医药与农业等领域。随着全球抗生素耐药性与其他公共健康问题的加剧，新结构、新靶点微生物天然产物发现迫在眉睫。大规模（宏）基因组测序揭示微生物蕴含了巨大的生物合成潜力，相继催生了多种不同类型的天然产物挖掘策略。然而，目前仍然缺乏将天然产物合成基因簇与编码产物快速关联的高效方案。近年来，（宏）基因组文库构建在获取批量天然产物合成基因簇方面展现出明显优势，结合高效的基因簇靶向筛选方法，显著加速了新结构天然产物系统发现。本文综述了三类基于（宏）基因组文库构建与靶向筛选驱动天然产物创新发现的策略，主要从克隆载体类型、文库构建方式、基因簇靶向筛选方法等角度进行了阐述，并对Cosmid/Fosmid文库、BAC/PAC文库、FAC/YAC文库等不同文库类型的优缺点及应用范围进行了对比，最后对这些策略的发展前景进行了展望。未来，基于文库构建与基因簇靶向筛选策略将极大驱动不同生境微生物来源的活性天然产物挖掘，预期大量新靶点、新结构天然产物将不断涌现。

关键词: 微生物天然产物, （宏）基因组挖掘, 基因簇, 文库构建, 基因簇靶向筛选

CLC Number:

Q819

Xuchang YU, Hui WU, Lei LI. Library construction and targeted BGC screening for more efficient discovery of microbial natural products[J]. Synthetic Biology Journal, 2024, 5(3): 492-506.

虞旭昶, 吴辉, 李雷. 文库构建与基因簇靶向筛选驱动的微生物天然产物高效发现[J]. 合成生物学, 2024, 5(3): 492-506.

Figures/Tables 4

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文库类型	插入大小	核心元件	筛选方法	文库针对类型	基因簇获取通量	获得化合物	优点	缺点	参考文献
Cosmid	约40 kb	COS位点质粒元件	CONKAT-seq	宏基因组	10⁷个克隆	Omnipeptin（NRP）	适合宏基因组挖掘	克隆片段大小相对较小，在克隆大尺度BGC（>40 kb）方面存在局限	Libis等(2019)^[51]
Cosmid	约40 kb	COS位点质粒元件	eSNaPD	宏基因组	>2×10⁷个克隆	MBA3（NRP）			Li等 (2022)^[52]
Fosmid	约40 kb	COS位点 F因子元件	序列引导的PCR筛选	（宏）基因组	2880个克隆	Actinonin（NRP）			Wolf等(2018)^[59]
BAC	约100 kb	loxP F因子元件	LEXAS	基因组	784个克隆	Lexapeptide （羊毛硫肽）等	①转化效率高 ②克隆100～300 kb片段	不适合宏基因组挖掘	徐敏 (2017)^[78]
PAC	约140 kb	F因子元件 P1噬菌体元件	CONKAT-seq	基因组	60 000个克隆	Prolinolexin（NRP） Cinnamexin（NRP） Conkatamycin（PK）	①转化效率高 ②克隆100～300 kb片段	不适合宏基因组挖掘	Libis等(2022)^[85]
FAC	约100 kb	F因子元件真菌ARS	FAC-MS	基因组	156个FAC	Benzomalvin A/D（NRP） Sesterterpenoid（Terpene） Valactamide A（Hybrid NRP-PK）	①克隆100～300 kb片段 ②适合真菌基因组挖掘	克隆稳定性差	Clevenger等(2017)^[96]
YAC	100～ 2000 kb	着丝粒端粒酵母ARS	NA	基因组	1896个YAC	NA	克隆100～2000 kb片段	①克隆稳定性差 ②转化效率低 ③重组率、嵌合率高	Saji等(2001)^[101]

文库类型	插入大小	核心元件	筛选方法	文库针对类型	基因簇获取通量	获得化合物	优点	缺点	参考文献
Cosmid	约40 kb	COS位点质粒元件	CONKAT-seq	宏基因组	10⁷个克隆	Omnipeptin（NRP）	适合宏基因组挖掘	克隆片段大小相对较小，在克隆大尺度BGC（>40 kb）方面存在局限	Libis等(2019)^[51]
Cosmid	约40 kb	COS位点质粒元件	eSNaPD	宏基因组	>2×10⁷个克隆	MBA3（NRP）			Li等 (2022)^[52]
Fosmid	约40 kb	COS位点 F因子元件	序列引导的PCR筛选	（宏）基因组	2880个克隆	Actinonin（NRP）			Wolf等(2018)^[59]
BAC	约100 kb	loxP F因子元件	LEXAS	基因组	784个克隆	Lexapeptide （羊毛硫肽）等	①转化效率高 ②克隆100～300 kb片段	不适合宏基因组挖掘	徐敏 (2017)^[78]
PAC	约140 kb	F因子元件 P1噬菌体元件	CONKAT-seq	基因组	60 000个克隆	Prolinolexin（NRP） Cinnamexin（NRP） Conkatamycin（PK）	①转化效率高 ②克隆100～300 kb片段	不适合宏基因组挖掘	Libis等(2022)^[85]
FAC	约100 kb	F因子元件真菌ARS	FAC-MS	基因组	156个FAC	Benzomalvin A/D（NRP） Sesterterpenoid（Terpene） Valactamide A（Hybrid NRP-PK）	①克隆100～300 kb片段 ②适合真菌基因组挖掘	克隆稳定性差	Clevenger等(2017)^[96]
YAC	100～ 2000 kb	着丝粒端粒酵母ARS	NA	基因组	1896个YAC	NA	克隆100～2000 kb片段	①克隆稳定性差 ②转化效率低 ③重组率、嵌合率高	Saji等(2001)^[101]

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