The impact of viral infection on the chemistries of the Earth’s most abundant photosynthesisers : metabolically talented aquatic cyanobacteria

Funding: The authors thank BBSRC BB/T017058/1 (YW) IBioIC, MASTS, Xanthella (SF) and the Royal Society (RJMG) for financial support.Cyanobacteria are the most abundant photosynthesizers on earth, and as such, they play a central role in marine metabolite generation, ocean nutrient cycling, and the control of planetary oxygen generation. Cyanobacteriophage infection exerts control on all of these critical processes of the planet, with the phage-ported homologs of genes linked to photosynthesis, catabolism, and secondary metabolism (marine metabolite generation). Here, we analyze the 153 fully sequenced cyanophages from the National Center for Biotechnology Information (NCBI) database and the 45 auxiliary metabolic genes (AMGs) that they deliver into their hosts. Most of these AMGs are homologs of those found within cyanobacteria and play a key role in cyanobacterial metabolism-encoding proteins involved in photosynthesis, central carbon metabolism, phosphate metabolism, methylation, and cellular regulation. A greater understanding of cyanobacteriophage infection will pave the way to a better understanding of carbon fixation and nutrient cycling, as well as provide new tools for synthetic biology and alternative approaches for the use of cyanobacteria in biotechnology and sustainable manufacturing.Publisher PDFPeer reviewe

Gifts from nature : genomic and metabolomic approaches to natural product discovery from cyanobacteria and actinomycetes

Cyanobacteria represent a treasure trove of uncovered natural products (NPs) and unbeknown biosynthetic machinery. Currently the exponential rise in genome sequencing of cyanobacteria and other organisms has revealed a wealth of biosynthetic gene clusters, many of which cannot be linked to a NP. This work describes the investigation of cyanobacterial strains for the presence of non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS) genes screened by PCR and Sanger sequencing. In addition to whole genome sequencing (WGS) using Illumina and Oxford Nanopore was undertaken of selected strains. Bioinformatic tools were used to detect biosynthetic gene clusters (BGCs) and identify regions of interest. Furthermore, publicly available data, in the form of publications and nucleotide data from genome assemblies was gathered to form several datasets to analyse and link cyanobacterial metabolites to their genomes, and to uncover the diversity of cyanobacterial NPs. Recent development has been undergoing to establish heterologous expression tools for cyanobacteria. Currently only a dozen cyanobacterial natural products have been heterologously expressed, this work details the heterologous expression of a ribosomally synthesised and post-translationally modified peptide (RiPP) named viridisamide A from Oscillatoria nigro-viridis PCC 7112 using the DiPaC method. This thesis also describes the use of this method for the cloning of the Fischerazole BGC from Fischerella sp. 9431. Furthermore, the NP cyclomarin A, a marine natural product from an actinomycetes rather than a cyanobacterium, which possesses potent bioactivities against both tuberculosis and malaria was investigated. Here precursor directed biosynthesis of the fermented strain Streptomyces sp. BCC41611 was used to created halogenated cyclomarin variants. In addition, synthetic chemistry methods were used to functionalise the epoxide of the biosynthesised NP by azidolysis and copper(I) catalysed alkyne-azide cycloaddition. Lastly, the halogenase VirX1 from the cyanophage syn10 was studied. This phage infects the marine cyanobacterial genera Synechococcus and Prochlorococcus which are responsible for over a quarter of global photosynthesis. Here, the halogenase was investigated in order to attempt to uncover its natural substrates."This work was supported by the University of St Andrews (School of Chemistry), IBioIC, MASTS and Xanthella [grant number ACH7-BDTPRG]. Conference attendance was supported by the RSC Researcher Development Grant [D22-5593926529]."--Fundin

Gifts from Nature. Genomic and Metabolomic Approaches to Natural Product Discovery from Cyanobacteria and Actinomycetes (thesis data)

LC-MS/MS data HPLC data NMR data The data files are embargoed until 23/06/202

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation. [Abstract copyright: © 2023. Springer Nature Limited.