From the depths of the Java Trench: genomic analysis of Priestia flexa JT4 reveals bioprospecting and lycopene production potential

来自爪哇海沟深处:对 Priestia flexa JT4 的基因组分析揭示了其生物勘探和番茄红素生产潜力

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Abstract

BACKGROUND: The marine environment boasts distinctive physical, chemical, and biological characteristics. While numerous studies have delved into the microbial ecology and biological potential of the marine environment, exploration of genetically encoded, deep-sea sourced secondary metabolites remains scarce. This study endeavors to investigate marine bioproducts derived from deep-sea water samples at a depth of 1,000 m in the Java Trench, Indonesia, utilizing both culture-dependent and whole-genome sequencing methods. RESULTS: Our efforts led to the successful isolation and cultivation of a bacterium Priestia flexa JT4 from the water samples, followed by comprehensive genome sequencing. The resultant high-quality draft genome, approximately 4 Mb, harbored 5185 coding sequences (CDSs). Notably, 61.97% of these CDSs were inadequately characterized, presenting potential novel CDSs. This study is the first to identify the "open-type" (α < 1) pangenome within the genus Priestia. Moreover, our analysis uncovered eight biosynthetic gene clusters (BGCs) using the common genome mining pipeline, antiSMASH. Two non-ribosomal peptide synthetase (NRPS) BGCs within these clusters exhibited the potential to generate novel biological compounds. Noteworthy is the confirmation that the terpene BGC in P. flexa JT4 can produce lycopene, a compound in substantial industrial demand. The presence of lycopene in the P. flexa JT4 cells was verified using Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) in multiple reaction modes. CONCLUSIONS: This study highlights the bioprospecting opportunity to explore novel bioproducts and lycopene compounds from P. flexa JT4. It marks the pioneering exploration of deep-sea bacterium bioprospecting in Indonesia, seeking to unveil novel bioproducts and lycopene compounds through a genome mining approach.

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