Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery.

IF 3.6 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2026-08-25 eCollection Date: 2026-01-01 DOI:10.3389/fbinf.2026.1893206
Veilumuthu Pattapulavar, Sathiyabama Ramanujam, Avanthi Yellampalli, Henu Sree Badiginchala, John Godwin Christopher
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引用次数: 0

Abstract

Antimicrobial resistance (AMR) has been identified as one of the 21st century's severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targeted interventions. During the same period, the number of novel antibiotics discovered has decreased drastically as many researchers are rediscovering known antibiotics, non-model microorganisms are poorly understood or difficult to culture and antibiotic research and development investment has declined drastically. However, high-throughput whole genome sequencing and the subsequent application of bioinformatics in bacterial and fungal genomes have shown that a numerous of cryptic or silent biosynthetic gene clusters (BGCs) remain latent at ambient laboratory conditions since their genes are transcriptionally inactive. Cryptic BGCs represent a vast source of unique secondary metabolites, many of which may yield novel antibacterial, antifungal, anti-cancer and other potentially valuable natural products. This review discusses the biological relevance of cryptic BGCs, the major limiting factors that restricts their activation and novel strategies that have been employed to activate them and exploit their potential to produce novel natural products. The review focuses on biological approaches including CRISPR-Cas mediation for the activation of cryptic BGCs, promoter engineering, pathway refactoring, and heterologous expression; biochemical strategies such as Osman, OsMAC, Precursor Feeding, Chemical Elicitation, Epigenetic Regulation and Co-cultivation and technology-based strategies such as Genome mining, Microfluidic Cultivation systems, High-Throughput Screening, Metabolomics, Molecular Networking and Artificial Intelligence and Machine Learning based prediction of BGCs and their metabolites. The use of multi-omics technologies combined with synthetic biology to achieve better discovery, characterization and large-scale production of novel natural products is also discussed herein. Finally, we will talk about the ecological significance and evolutionary advantage of cryptic BGCs' role in interactions between microorganisms, such as competition, communication, symbiosis and environmental adaptability, so as to provide a useful background for accelerating next-generation antibiotics.

激活隐秘生物合成基因簇的分子生物学和综合策略,以发现下一代抗生素。
抗菌素耐药性(AMR)已被确定为21世纪最严重的全球公共卫生危机之一。据估计,抗菌素耐药性在2019年导致495万人死亡,如果不采取有针对性的干预措施,到2050年,每年将夺去1000万人的生命。在同一时期,由于许多研究人员正在重新发现已知的抗生素,非模式微生物知之甚少或难以培养,抗生素研究和开发投资急剧下降,新发现的抗生素数量急剧减少。然而,高通量全基因组测序和随后在细菌和真菌基因组中的生物信息学应用表明,许多隐型或沉默的生物合成基因簇(BGCs)在环境实验室条件下仍然潜伏,因为它们的基因转录不活跃。隐性bgc代表了独特的次生代谢物的巨大来源,其中许多可能产生新的抗菌,抗真菌,抗癌和其他潜在有价值的天然产物。本文讨论了隐性bgc的生物学相关性、限制其激活的主要限制因素以及用于激活它们的新策略,并利用它们产生新的天然产物的潜力。综述的重点是生物学方法,包括CRISPR-Cas介导隐性bgc的激活、启动子工程、途径重构和异源表达;生化策略,如Osman、OsMAC、前体喂养、化学激发、表观遗传调控和共培养,以及基于技术的策略,如基因组挖掘、微流控培养系统、高通量筛选、代谢组学、分子网络和基于人工智能和机器学习的bgc及其代谢物预测。本文还讨论了利用多组学技术与合成生物学相结合,更好地发现、表征和大规模生产新的天然产物。最后,我们将讨论隐性bgc在微生物之间的竞争、交流、共生和环境适应性等相互作用中的生态意义和进化优势,从而为加速下一代抗生素的开发提供有益的背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.60
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