Whole genomes of deep-sea sponge-associated bacteria exhibit high novel natural product potential

Abstract

Global antimicrobial resistance is a health crisis that can change the face of modern medicine. Exploring diverse natural habitats for bacterially-derived novel antimicrobial compounds has historically been a successful strategy. The deep-sea presents an exciting opportunity for the cultivation of taxonomically novel organisms and exploring potentially chemically novel spaces. In this study, the draft genomes of 12 bacteria previously isolated from the deep-sea sponges Phenomena carpenteri and Hertwigia sp. are investigated for the diversity of specialized secondary metabolites. In addition, early data support the production of antibacterial inhibitory substances produced from a number of these strains, including activity against clinically relevant pathogens Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus. Draft whole-genomes are presented of 12 deep-sea isolates, which include four potentially novel strains: Psychrobacter sp. PP-21, Streptomyces sp. DK15, Dietzia sp. PP-33, and Micrococcus sp. M4NT. Across the 12 draft genomes, 138 biosynthetic gene clusters were detected, of which over half displayed less than 50% similarity to known BGCs, suggesting that these genomes present an exciting opportunity to elucidate novel secondary metabolites. Exploring bacterial isolates belonging to the phylum Actinomycetota, Pseudomonadota, and Bacillota from understudied deep-sea sponges provided opportunities to search for new chemical diversity of interest to those working in antibiotic discovery.

Keywords: antibiotic discovery; bacterial genomics; biosynthetic gene clusters; deep sea; natural products; porifera.

Figure 1.

Map of sampling sites and sponges used for bacterial cultivation. (A) Map of deep-sea sampling points for sponges. Blue marker points from top to bottom, sampling sites for Deep Links JC136, SeaRovers RH17001 and SeaRovers CE19015. In situ images of deep-sea sponges, (B)P. carpenteri JC136_125 (Deep Links), and (C)Hertwigia sp. GRNL_81 (SeaRovers RH17001). Two red laser dots visible in (C) illustrate a 10 cm distance.

Figure 2.

Maximum likelihood phylogenetic tree of 16S rRNA gene sequences from cultivable sponge-associated bacteria showing that antibiotic producers are phylogenetically diverse across all classes and species of sponge. Cultivable sponges presented here include reference organisms, a selection of bacteria cultivated in this study that display antimicrobial activity and those from published studies (Lafi et al. , Kim and Fuerst , Jiang et al. , Mangano et al. , Zhang et al. , Sipkema et al. , Xin et al. , Bibi et al. , Koch et al. 2021). The outer ring represents whether organisms were screened for antibiotic activity in the published study, the middle ring the class of the sponge bacteria were cultivated, and the inner ring the taxonomy of the sponge. Regions of interest are marked numerically (i-iv). Sequence names as part of this study are labelled first with an NCBI accession number and the taxonomic classification and isolate name of the bacteria from the original study (see Supplementary Table 2). Bacterial isolates investigated in this study are labelled with their unique isolate name in bold and a grey strip.

Figure 3.

Predicted biosynthetic gene clusters (BGCs) from sponge-associated bacterial genomes. Summary of the predicted BGCs, and the proportion of BGCs classified based on similarity to known BGCs. Strains are ordered from highest to lowest number of predicted BGCs going from the left to the right. For a detailed breakdown of all predicted BGCs refer to Table S2. (RiPP, ribosomally synthesized post-translationally modified; PKS, Polyketide synthase; NRPS, non-ribosomal peptide synthase; *, potentially novel species).

Figure 4.

Summary of biosynthetic gene clusters (BGCs) and proposed activity as predicted by DeepBGC. (A) Comparison of BGCs as detected by the two tools utilized, including a stringent filtering step using DeepBGC to remove low-quality hits. Breakdown of the (B) classes of BGCs and (C) the predicted biological activity of proposed BGCs as detected by DeepBGC.

Figure 5.

Evaluation of antibacterial activity of producer isolates as screened by a soft agar overlay. Isolates are listed on the y-axis, pathogens on the x-axis, and antibacterial activity is quantified by size of zone of inhibition (mm) and represented as colour shifts from white (no observed activity; 0 mm) to red (high antibacterial activity; 40 mm).