Metabologenomics: Correlation of Microbial Gene Clusters with Metabolites Drives Discovery of a Nonribosomal Peptide with an Unusual Amino Acid Monomer.

For more than half a century the pharmaceutical industry has sifted through natural products produced by microbes, uncovering new scaffolds and fashioning them into a broad range of vital drugs. We sought a strategy to reinvigorate the discovery of natural products with distinctive structures using bacterial genome sequencing combined with metabolomics. By correlating genetic content from 178 actinomycete genomes with mass spectrometry-enabled analyses of their exported metabolomes, we paired new secondary metabolites with their biosynthetic gene clusters. We report the use of this new approach to isolate and characterize tambromycin, a new chlorinated natural product, composed of several nonstandard amino acid monomeric units, including a unique pyrrolidine-containing amino acid we name tambroline. Tambromycin shows antiproliferative activity against cancerous human B- and T-cell lines. The discovery of tambromycin via large-scale correlation of gene clusters with metabolites (a.k.a. metabologenomics) illuminates a path for structure-based discovery of natural products at a sharply increased rate.

Fungal artificial chromosomes for mining of the fungal secondary metabolome.

BACKGROUND: With thousands of fungal genomes being sequenced, each genome containing up to 70 secondary metabolite (SM) clusters 30-80 kb in size, breakthrough techniques are needed to characterize this SM wealth. RESULTS: Here we describe a novel system-level methodology for unbiased cloning of intact large SM clusters from a single fungal genome for one-step transformation and expression in a model host. All 56 intact SM clusters from Aspergillus terreus were individually captured in self-replicating fungal artificial chromosomes (FACs) containing both the E. coli F replicon and an Aspergillus autonomously replicating sequence (AMA1). Candidate FACs were successfully shuttled between E. coli and the heterologous expression host A. nidulans. As proof-of-concept, an A. nidulans FAC strain was characterized in a novel liquid chromatography-high resolution mass spectrometry (LC-HRMS) and data analysis pipeline, leading to the discovery of the A. terreus astechrome biosynthetic machinery. CONCLUSION: The method we present can be used to capture the entire set of intact SM gene clusters and/or pathways from fungal species for heterologous expression in A. nidulans and natural product discovery.

Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.

The microbial world offers a rich source of bioactive compounds for those able to sift through it. Technologies capable of quantitatively detecting natural products while simultaneously identifying known compounds would expedite the search for new pharmaceutical leads. Prior efforts have targeted histone deacetylases in fungi to globally activate the production of new secondary metabolites, yet no study has directly assessed its effects with minimal bias at the metabolomic level. Using untargeted metabolomics, we monitored changes in >1000 small molecules secreted from the model fungus, Aspergillus nidulans, following genetic or chemical reductions in histone deacetylase activity (HDACi). Through quantitative, differential analyses, we found that nearly equal numbers of compounds were up- and down-regulated by >100 fold. We detected products from both known and unknown biosynthetic pathways and discovered that A. nidulans is capable of producing fellutamides, proteasome inhibitors whose expression was induced by ∼100 fold or greater upon HDACi. This work adds momentum to an "omics"-driven resurgence in natural products research, where direct detection replaces bioactivity as the primary screen for new pharmacophores.

A roadmap for natural product discovery based on large-scale genomics and metabolomics.

Actinobacteria encode a wealth of natural product biosynthetic gene clusters, whose systematic study is complicated by numerous repetitive motifs. By combining several metrics, we developed a method for the global classification of these gene clusters into families (GCFs) and analyzed the biosynthetic capacity of Actinobacteria in 830 genome sequences, including 344 obtained for this project. The GCF network, comprising 11,422 gene clusters grouped into 4,122 GCFs, was validated in hundreds of strains by correlating confident mass spectrometric detection of known small molecules with the presence or absence of their established biosynthetic gene clusters. The method also linked previously unassigned GCFs to known natural products, an approach that will enable de novo, bioassay-free discovery of new natural products using large data sets. Extrapolation from the 830-genome data set reveals that Actinobacteria encode hundreds of thousands of future drug leads, and the strong correlation between phylogeny and GCFs frames a roadmap to efficiently access them.

Strain-specific proteogenomics accelerates the discovery of natural products via their biosynthetic pathways.

The use of proteomics for direct detection of expressed pathways producing natural products has yielded many new compounds, even when used in a screening mode without a bacterial genome sequence available. Here we quantify the advantages of having draft DNA-sequence available for strain-specific proteomics using the latest in ultrahigh-resolution mass spectrometry for both proteins and the small molecules they generate. Using the draft sequence of Streptomyces lilacinus NRRL B-1968, we show a >tenfold increase in the number of peptide identifications vs. using publicly available databases. Detected in this strain were six expressed gene clusters with varying homology to those known. To date, we have identified three of these clusters as encoding for the production of griseobactin (known), rakicidin D (an orphan NRPS/PKS hybrid cluster), and a putative thr and DHB-containing siderophore produced by a new non-ribosomal peptide sythetase gene cluster. The remaining three clusters show lower homology to those known, and likely encode enzymes for production of novel compounds. Using an interpreted strain-specific DNA sequence enables deep proteomics for the detection of multiple pathways and their encoded natural products in a single cultured bacterium.

Gobichelin A and B: Mixed-Ligand Siderophores Discovered Using Proteomics.

"Omic" strategies have been increasingly applied to natural product discovery processes, with (meta-)genome sequencing and mining implemented in many laboratories to date. Using the proteomics-based discovery platform called PrISM (Proteomic Investigation of Secondary Metabolism), we discovered two new siderophores gobichelin A and B from Streptomyces sp. NRRL F-4415, a strain without a sequenced genome. Using the proteomics information as a guide, the 37 kb gene cluster responsible for production of gobichelins was sequenced and its 20 open reading frames interpreted into a biosynthetic scheme. This led to the targeted detection and structure elucidation of the new compounds produced by nonribosomal peptide (NRP) synthesis.

Identifying gel-separated proteins using in-gel digestion, mass spectrometry, and database searching: Consider the chemistry.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is an important bioanalytical technique in drug discovery, proteomics, and research at the biology-chemistry interface. This is an especially powerful tool when combined with gel separation of proteins and database mining using the mass spectral data. Currently, few hands-on laboratory opportunities exist for undergraduate students to master this technique despite the usefulness of this technique in biological research. One reason for this lack of incorporation into the teaching curriculum is the relatively low number of published laboratory experiments that demonstrate how mass spectrometry can be incorporated into undergraduate laboratories. We present a simple experiment designed to introduce students to the analysis of gel separated proteins using mass spectrometry. In this experiment, students analyze one or more proteins using gel electrophoresis, followed by in-gel digestion, MALDI-time-of-flight (TOF) mass spectrometry and database mining. The experiment also demonstrates how erroneous results can be obtained if careful attention is not paid to all aspects of the experimental process. The data presented here can be used in a classroom or laboratory setting even if hands-on access to a MALDI-TOF mass spectrometer is not possible.