Genome-Guided Discovery of an Antimicrobial Peptide Scaffold from an Undescribed Antarctic Rhodococcus Lineage: A Proof-of-Concept Study

Complete genome sequence and mass spectrometry assist mining siderophore turnerbactin analogs in a non-model Pseudoduganella strain with biocontrol potential

Findings indicate that Pseudoduganella sp.

Genome mining reveals an architecturally expanded pyoluteorin-associated biosynthetic gene cluster and a divergent flavin-dependent halogenase-like sequence in deep-sea Pseudomonas Aeruginosa from the Gulf of Guinea

Genomic and pan-genomic analyses of Bacillus subtilis B13 provide insights into biosynthetic potential and genetic traits associated with environmental adaptation

Insight is provided into genomic features related to the biosynthetic potential, genomic plasticity, and safety profile of B13, and suggest putative determinants of environmental adaptation, while reflecting pan-genome diversity in strain-specific traits.

Genome mining and comparative genome analysis of Pseudomonas fluorescens revealed diverse biosynthetic and metabolic potential

Understanding of the metabolic capabilities and genomic landscape of the P. fluorescens species is enhanced, providing a foundation for natural product discovery using bioinformatic approaches.

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

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.

Complete genome sequence of Idiomarina sp. D18 from the Western Pacific Ocean reveals biosynthetic potential for β-lactone and RiPP-like compounds.

Findings suggest that strain D18 possesses adaptive strategies for survival in deep-sea environments and highlight its potential as a source of novel secondary metabolites.