Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan 6;19(1):20.
doi: 10.3390/md19010020.

A Multi-Omics Characterization of the Natural Product Potential of Tropical Filamentous Marine Cyanobacteria

Tiago Leão  1   2 , Mingxun Wang  2 , Nathan Moss  1 , Ricardo da Silva  2   3 , Jon Sanders  4   5   6 , Sergey Nurk  7 , Alexey Gurevich  7 , Gregory Humphrey  4   5 , Raphael Reher  1 , Qiyun Zhu  4   5   8 , Pedro Belda-Ferre  4   5 , Evgenia Glukhov  1 , Syrena Whitner  1   9 , Kelsey L Alexander  1   10 , Robert Rex  1 , Pavel Pevzner  11 , Pieter C Dorrestein  1   2   5 , Rob Knight  4   5   12 , Nuno Bandeira  2   11 , William H Gerwick  1   2 , Lena Gerwick  1
Affiliations

A Multi-Omics Characterization of the Natural Product Potential of Tropical Filamentous Marine Cyanobacteria

Tiago Leão et al. Mar Drugs. .

Abstract

Microbial natural products are important for the understanding of microbial interactions, chemical defense and communication, and have also served as an inspirational source for numerous pharmaceutical drugs. Tropical marine cyanobacteria have been highlighted as a great source of new natural products, however, few reports have appeared wherein a multi-omics approach has been used to study their natural products potential (i.e., reports are often focused on an individual natural product and its biosynthesis). This study focuses on describing the natural product genetic potential as well as the expressed natural product molecules in benthic tropical cyanobacteria. We collected from several sites around the world and sequenced the genomes of 24 tropical filamentous marine cyanobacteria. The informatics program antiSMASH was used to annotate the major classes of gene clusters. BiG-SCAPE phylum-wide analysis revealed the most promising strains for natural product discovery among these cyanobacteria. LCMS/MS-based metabolomics highlighted the most abundant molecules and molecular classes among 10 of these marine cyanobacterial samples. We observed that despite many genes encoding for peptidic natural products, peptides were not as abundant as lipids and lipopeptides in the chemical extracts. Our results highlight a number of highly interesting biosynthetic gene clusters for genome mining among these cyanobacterial samples.

Keywords: biosynthetic potential; genomics; marine cyanobacteria; metabolomics; natural products.

PubMed Disclaimer

Conflict of interest statement

These studies were supported by the University of California, San Diego, Scripps Institution of Oceanography from NIH grant (GM 107550 and GM118815). William Gerwick has an equity interest in NMRFinder and in SirenasMD Inc., companies that may potentially benefit from the research results and also serves on the company’s Scientific Advisory Boards. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies.

Figures

Figure 1
Figure 1
Phylogenomic analyses of completed cyanobacterial genomes using 29 conserved genes from Calteau et al. [16]. Tips were labeled either according to phylogenomic cladding and 16S rRNA identity, where our 24 high quality genome are indicated by red arrows. Bootstrap values are labeling the branches. Moorea was renamed to Moorena in 2019; however, because the NCBI records are still labeled as Moorea, we use the latter name in this phylogenomic tree.
Figure 2
Figure 2
(a) Cutoff comparison networking the expert-annotated biosynthetic gene clusters from MIBIG database, highlighting the best outcome for the cutoff of 0.3 distance (70% similarity). Top violin plot illustrates the distribution of the average similarity scores and bottom box plot also illustrates these scores but focusing on the number of outliers per cutoff. (b) Principal Coordinate Analysis (PCoA) for beta-diversity scores from 1650 genomes that were networked (including the 24 marine cyanobacterial genomes generated in this project). The blue group represents the most diverse samples in the dataset (samples for which the beta-diversity was over 95%; includes a total of 654 cyanobacterial genomes including the 24 reported herein; genomes listed at Dataset S1, sheet 3) and the red group represents low diversity samples (genomes with an average beta-diversity score below 95%; includes a total of 996 cyanobacterial genomes).
Figure 3
Figure 3
(a) Histogram counting all gene cluster families separated by common biosynthetic class (classification according to BiG-SCAPE and cutoff of at least 10 occurrences in all cyanobacteria). (b) A similar histogram to panel A using only the 24 marine cyanobacteria newly reported herein and with a cutoff of at least 2 occurrences in these cyanobacteria. NRPS = nonribosomal peptide synthetase; T1PKS = type 1 polyketide synthase; T3PKS = type 3 polyketide synthase; CDPS = cyclodipeptide synthase; hglE-KS = heterocyst glycolipid synthase.
Figure 4
Figure 4
Classical molecular networking improved via in silico tools and MolNetEnhancer. Self-loops (singletons) annotated as “no match” were removed. Nodes are colored according to the ClassyFire predicted Superclass. Nodes with black border represent library hits and one representative per molecular family is displayed in the network. Genus-specific families with library hits are labeled in red. Diamonds represent Leptolyngbya samples; hexagons represent Moorena; squares represent Okeania; triangles represent Symploca. Circles represent two or more genera. Molecules without a common name are represented by the ClassyFire most detailed structure type prediction (listed in Dataset S1, sheet 2). For the predicted structures of compounds without a common name, see Figure S4.
Figure 4
Figure 4
Classical molecular networking improved via in silico tools and MolNetEnhancer. Self-loops (singletons) annotated as “no match” were removed. Nodes are colored according to the ClassyFire predicted Superclass. Nodes with black border represent library hits and one representative per molecular family is displayed in the network. Genus-specific families with library hits are labeled in red. Diamonds represent Leptolyngbya samples; hexagons represent Moorena; squares represent Okeania; triangles represent Symploca. Circles represent two or more genera. Molecules without a common name are represented by the ClassyFire most detailed structure type prediction (listed in Dataset S1, sheet 2). For the predicted structures of compounds without a common name, see Figure S4.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Newman D.J., Cragg G.M. Natural Products as Sources of New Drugs from 1981 to 2014. J. Nat. Prod. 2016;79:629–661. doi: 10.1021/acs.jnatprod.5b01055. - DOI - PubMed
    1. Blin K., Kim H.U., Medema M.H., Weber T. Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters. Brief. Bioinform. 2017;1:11. doi: 10.1093/bib/bbx146. - DOI - PMC - PubMed
    1. Pye C.R., Bertin M.J., Lokey R.S., Gerwick W.H., Linington R.G. Retrospective analysis of natural products provides insights for future discovery trends. Proc. Natl. Acad. Sci. USA. 2017;114:5601–5606. doi: 10.1073/pnas.1614680114. - DOI - PMC - PubMed
    1. Komarek J., Kastovsky J., Mares J., Johansen J.R. Taxonomic classification of cyanoprokaryotes (cyanobacterial genera) 2014, using a polyphasic approach. Preslia. 2014;86:295–335.
    1. Keller L., Leão T., Gerwick W.H. Chemical Biology of Natural Products. Taylor & Francis Group; Oxfordshire, UK: 2017. Chemical Biology of Marine Cyanobacteria; pp. 43–87.

Substances