4.0 Article

A survey of the biosynthetic potential and specialized metabolites of archaea and understudied bacteria

Journal

CURRENT RESEARCH IN BIOTECHNOLOGY
Volume 5, Issue -, Pages -

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ELSEVIER
DOI: 10.1016/j.crbiot.2022.11.004

Keywords

Biosynthetic gene clusters (BGCs); Archaea; Specialized metabolites (SMs)

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Biosynthetic gene clusters (BGCs) are genes involved in specialized metabolite (SM) production and provide advantages to producing microbes. Some SMs have pharmaceutical importance, such as antibacterial activity. Mining under-studied microbes' genomes can contribute to the discovery of novel antibiotics.
Biosynthetic gene clusters (BGCs) are genes in proximity that are involved in the production of specialized metabolites (SMs) and provide additional in situ advantages to the producing microbes such as antagonism and quorum sensing. A subset of SMs exhibit functions of pharmaceutical importance, such as antibacterial activity, which could address the current antibiotic resistance problem. Genome mining of under-studied microbes will contribute to the repertoire of currently known BGCs and hence SMs and will advance the finding of novel antibiotics. We aimed to provide a primary assessment of several archaeal genera as to their potential of producing SMs by mining a total of 133 genomes pertaining to three archaeal taxa and understudied bacteria: Thermococcus genus (n = 34), Halobacteria class (n = 39) and Methanococcus genus (n = 26), in addition to the DPANN superphylum (an acronym of the names of the first included phyla Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanohaloarchaeota, and Nanoarchaeota) archaeal genomes (n = 14) and CPR (candidate phyla radiation) bacterial genomes (n = 20), for the presence of BGCs. This study aimed to assess the predicted BGCs from representatives of archaeal and bacterial genomes using the current BGC detection tools, with particular interest in the similarities and discrepancies between the tools. The bioinformatics tools used comprise antiSMASH -as it encompasses several diverse BGC classes-, PRISM -for chemical structure prediction-, the Natural Products Atlas -for NP detection-, and BAGEL4 -for ribosomally synthesized and post-translationally modified peptide (RiPP) mining-. The group with the most predicted BGCs was CPR (9.47 BGCs per Mb), followed by DPANN (6.33 BGCs per Mb), Methanococcus (2.08 BGCs per Mb), Thermococcus (0.55 BGCs per Mb), and lastly Halobacteria (0.53 BGCs per Mb). Under-explored lineages are promising SM producers, as they harbor potential BGCs in their genomes. However, it remains a current challenge to capture all the biosynthetic potential of archaeal microbes, as more specific computational tools, functional screening assays, and characterization of their SMs are needed.

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