Marine environments harbour a wealth of diverse and underexplored microbiota, including species from the actinobacterial genus Streptomyces (Actinomycetota)― remarkably prolific producers of a wide array of natural products with unique bioactivities and high potential for drug discovery and other applications.
In our study, we explored liquid culture supernatants from various Streptomyces strains sourced from deep-sea environments, corresponding to different species, aiming to uncover their chemical diversity and potentially identify valuable natural products. To achieve this, we followed a multi-step extraction procedure involving liquid–liquid and sorbent-assisted extraction steps. Leveraging a high-throughput ultra-high-performance liquid chromatography‒electrospray ionisation‒high-resolution mass spectrometry (UPLC‒ESI‒HRMS) dereplication workflow, we employed molecular networking (MN) and cheminformatic approaches to obtain insights from complex spectral datasets. Our dual focus was to identify known compounds (chemical dereplication) and highlight potentially novel ones within the extracts' "chemical spaces". We further fractionated the extracts, performed general and targeted thin-layer chromatography (TLC) assays, and purified the fractions for structural elucidation using UPLC‒ESI‒HRMS and nuclear magnetic resonance (NMR) spectroscopy, guided by the dereplication.
The investigated strains of marine-derived Streptomyces displayed diverse and intriguing chemical profiles both within and between species. The primary dereplicated compounds included linear and cyclic hydroxamate siderophores from the “ferrioxamine family” and autoregulatory inhibitors of spore germination from the “germicidin family”. Additionally, other natural products, such as carboxylic acid derivatives, dipeptides, and nucleosides, were annotated, all of which with significant application potential.
The described analytical workflow fortified by state-of-the-art cheminformatic approaches allowed us to gain insights into the chemical spaces of the extracts and distinguish potential compounds of interest. The data from MNs are crucial for guided purification during extract fractionation, complementing classical techniques for efficient compound identification and, ultimately, NMR structural elucidation.
Funding: SECRETed project—European Union’s Horizon 2020 research and innovation programme; Grant Agreement No. 101000794.
