No abstract

Genome mining has become a key technology to exploit natural product diversity. While initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. Here, we provide a streamlined computational workflow consisting of two new software tools: The 'Biosynthetic Gene Similarity Clustering And Prospecting Engine' (BiG-SCAPE) facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families. 'CORe Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Natural products from microbes have provided humans with beneficial antibiotics for millennia. However, a decline in the pace of antibiotic discovery exerts pressure on human health as antibiotic resistance spreads, a challenge that may better faced by unveiling chemical diversity produced by microbes. Current microbial genome mining approaches have revitalized research into antibiotics, but the empirical nature of these methods limits the chemical space that is explored.Here, we address the problem of finding novel pathways by incorporating evolutionary principles into genome mining. We recapitulated the evolutionary history of twenty-three enzyme families previously uninvestigated in the context of natural product biosynthesis in Actinobacteria, the most proficient producers of natural products. Our genome evolutionary analyses where based on the assumption that expanded—repurposed enzyme families—from central metabolism, occur frequently and thus have the potential to catalyze new conversions in the context of natural products biosynthesis. Our analyses led to the discovery of biosynthetic gene clusters coding for hidden chemical diversity, as validated by comparing our predictions with those from state-of-the-art genome mining tools; as well as experimentally demonstrating the existence of a biosynthetic pathway for arseno-organic metabolites in Streptomyces coelicolor and Streptomyces lividans, Using a gene knockout and metabolite profile combined strategy.As our approach does not rely solely on sequence similarity searches of previously identified biosynthetic enzymes, these results establish the basis for the development of an evolutionary-driven genome mining tool termed EvoMining that complements current platforms. We anticipate that by doing so real ‘chemical dark matter’ will be unveiled.

Genome mining has become a key technology to explore and exploit natural product diversity through the identification and analysis of biosynthetic gene clusters (BGCs). Initially, this was performed on a single-genome basis; currently, the process is being scaled up to large-scale mining of pan-genomes of entire genera, complete strain collections and metagenomic datasets from which thousands of bacterial genomes can be extracted at once. However, no bioinformatic framework is currently available for the effective analysis of datasets of this size and complexity. Here, we provide a streamlined computational workflow, tightly integrated with antiSMASH and MIBiG, that consists of two new software tools, BiG-SCAPE and CORASON. BiG-SCAPE facilitates rapid calculation and interactive visual exploration of BGC sequence similarity networks, grouping gene clusters at multiple hierarchical levels, and includes a 'glocal' alignment mode that accurately groups both complete and fragmented BGCs. CORASON employs a phylogenomic approach to elucidate the detailed evolutionary relationships between gene clusters by computing high-resolution multi-locus phylogenies of all BGCs within and across gene cluster families (GCFs), and allows researchers to comprehensively identify all genomic contexts in which particular biosynthetic gene cassettes are found. We validate BiG-SCAPE by correlating its GCF output to metabolomic data across 403 actinobacterial strains. Furthermore, we demonstrate the discovery potential of the platform by using CORASON to comprehensively map the phylogenetic diversity of the large detoxin/rimosamide gene cluster clan, prioritizing three new detoxin families for subsequent characterization of six new analogs using isotopic labeling and analysis of tandem mass spectrometric data.

The complete genome sequence of the original isolate of the model actinomycete Streptomyces lividans 66, also referred to as 1326, was deciphered after a combination of next-generation sequencing platforms and a hybrid assembly pipeline. Comparative analysis of the genomes of S. lividans 66 and closely related strains, including S. coelicolor M145 and S. lividans TK24, was used to identify strain-specific genes. The genetic diversity identified included a large genomic island with a mosaic structure, present in S. lividans 66 but not in the strain TK24. Sequence analyses showed that this genomic island has an anomalous (G + C) content, suggesting recent acquisition and that it is rich in metal-related genes. Sequences previously linked to a mobile conjugative element, termed plasmid SLP3 and defined here as a 94 kb region, could also be identified within this locus. Transcriptional analysis of the response of S. lividans 66 to copper was used to corroborate a role of this large genomic island, including two SLP3-borne “cryptic” peptide biosynthetic gene clusters, in metal homeostasis. Notably, one of these predicted biosynthetic systems includes an unprecedented nonribosomal peptide synthetase—tRNA-dependent transferase biosynthetic hybrid organization. This observation implies the recruitment of members of the leucyl/phenylalanyl-tRNA-protein transferase family to catalyze peptide bond formation within the biosynthesis of natural products. Thus, the genome sequence of S. lividans 66 not only explains long-standing genetic and phenotypic differences but also opens the door for further in-depth comparative genomic analyses of model Streptomyces strains, as well as for the discovery of novel natural products following genome-mining approaches.

Rapid increases of energy consumption and human dependency on fossil fuels have led to the accumulation of greenhouse gases and consequently, climate change. As such, major efforts have been taken to develop, test, and adopt clean renewable fuel alternatives. Production of bioethanol and biodiesel from crops is well developed, while other feedstock resources and processes have also shown high potential to provide efficient and cost-effective alternatives, such as landfill and plastic waste conversion, algal photosynthesis, as well as electrochemical carbon fixation. In addition, the downstream microbial fermentation can be further engineered to not only increase the product yield but also expand the chemical space of biofuels through the rational design and fine-tuning of biosynthetic pathways toward the realization of ''designer fuels'' and diverse future applications.

Desferrioxamines are hydroxamate siderophores widely conserved in both aquatic and soil-dwelling Actinobacteria. While the genetic and enzymatic bases of siderophore biosynthesis and their transport in model families of this phylum are well understood, evolutionary studies are lacking. Here, we perform a comprehensive desferrioxamine-centric (des genes) phylogenomic analysis, which includes the genomes of six novel strains isolated from an iron and phosphorous depleted oasis in the Chihuahuan desert of Mexico. Our analyses reveal previously unnoticed desferrioxamine evolutionary patterns, involving both biosynthetic and transport genes, likely to be related to desferrioxamines chemical diversity. The identified patterns were used to postulate experimentally testable hypotheses after phenotypic characterization, including profiling of siderophores production and growth stimulation of co-cultures under iron deficiency. Based in our results, we propose a novel des gene, which we term desG, as responsible for incorporation of phenylacetyl moieties during biosynthesis of previously reported arylated desferrioxamines. Moreover, a genomic-based classification of the siderophore-binding proteins responsible for specific and generalist siderophore assimilation is postulated. This report provides a much-needed evolutionary framework, with specific insights supported by experimental data, to direct the future ecological and functional analysis of desferrioxamines in the environment.

P. putida lysine metabolism can produce multiple commodity chemicals, conferring great biotechnological value. Despite much research, the connection of lysine catabolism to central metabolism in P. putida remained undefined. Here, we used random barcode transposon sequencing to fill the gaps of lysine metabolism in P. putida. We describe a route of 2-oxoadipate (2OA) catabolism, which utilizes DUF1338-containing protein P. putida 5260 (PP_5260) in bacteria. Despite its prevalence in many domains of life, DUF1338-containing proteins have had no known biochemical function. We demonstrate that PP_5260 is a metalloenzyme which catalyzes an unusual route of decarboxylation of 2OA to d-2-hydroxyglutarate (d-2HG). Our screen also identified a recently described novel glutarate metabolic pathway. We validate previous results and expand the understanding of glutarate hydroxylase CsiD by showing that can it use either 2OA or 2KG as a cosubstrate. Our work demonstrated that biological novelty can be rapidly identified using unbiased experimental genetics and that RB-TnSeq can be used to rapidly validate previous results.