Integrated Metabolomics Approach Facilitates Discovery of an

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Integrated Metabolomics Approach Facilitates Discovery of an Unpredicted Natural Product Suite from Streptomyces coelicolor M145 Ashley M Sidebottom, Andrew R Johnson, Jonathan A. Karty, Darci J. Trader, and Erin E. Carlson ACS Chem. Biol., Just Accepted Manuscript • DOI: 10.1021/cb4002798 • Publication Date (Web): 18 Jun 2013 Downloaded from http://pubs.acs.org on June 19, 2013

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ACS Chemical Biology

Integrated Metabolomics Approach Facilitates Discovery of an Unpredicted Natural Product Suite from Streptomyces coelicolor M145 Ashley M. Sidebottom,a Andrew R. Johnson,a Jonathan A. Karty,a Darci J. Trader,a Erin E. Carlsona,b,* a

b

Department of Chemistry, Indiana University, 800 E. Kirkwood, Bloomington, Indiana, USA. Department of Molecular and Cellular Biochemistry, 212 S. Hawthorne Dr., Bloomington, Indiana, USA. *Corresponding Author: [email protected]

Abstract Natural products exhibit a broad range of biological properties and have been a crucial source of therapeutic agents and novel scaffolds. Although bacterial secondary metabolomes are widely explored, they remain incompletely cataloged by current isolation and characterization strategies. To identify metabolites residing in unexplored chemical space, we have developed an integrated discovery approach that combines bacterial growth perturbation, accurate mass spectrometry, comparative mass spectra data analysis, and fragmentation spectra clustering for the identification of low-abundant, novel compounds from complex biological matrices. In this investigation, we analyzed the secreted metabolome of the extensively studied Actinomycete, Streptomyces coelicolor M145, and discovered a low-abundant suite of 15 tri-hydroxamate, amphiphilic siderophores. Compounds in this class have primarily been observed in marine microorganisms making their detection in the soil-dwelling S. coelicolor M145 significant. At least ten of these ferrioxamine-based molecules are not known to be produced by any organism and none have previously been detected from S. coelicolor M145. In addition, we confirmed the production of ferrioxamine D1, a relatively hydrophilic family member that has not been shown to be biosynthesized by this organism. The identified molecules are part of only a small list of secondary metabolites that have been discovered since sequencing of S. coelicolor M145 revealed that it possessed numerous putative secondary metabolite-producing gene clusters with no known metabolites. Thus, the identified siderophores represent the unexplored metabolic

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potential of both well-studied and new organisms that could be uncovered with our sensitive and robust approach.

Discovery of natural products from the Actinomycete genus has been extremely successful because of the high propensity of these organisms to generate natural products. As a critical source for new drugs and chemical scaffolds, Actinomycetes devote much of their immense genome (>8 Mb) to the production of secondary metabolites, compounds that have led to the development of over half of all FDA approved microbially-derived drugs.(1) In 2003, Streptomyces coelicolor M145 became the largest completely sequenced bacterial genome and is an important model organism for this genus.(2) Prior to sequencing, this organism was reported to produce a number of secondary metabolites including actinorhodin, hopanoids, and prodiginines.(2) However, sequencing revealed approximately 18 additional orphan gene clusters that are thought to encode for enzymes that likely produce polyketides, chalcones, fatty acids and siderophores along with several unknown compounds.(2-4) Efforts to characterize the products of orphan clusters have utilized numerous strategies including genome mining, gene inactivation and targeting,(5-7) heterologous expression,(8, 9) and/or the one strain many compounds (OSMAC) approach.(10, 11) Despite the success of these methods, a significant proportion of the metabolites constructed by these clusters remain unidentified. Compound discovery efforts are impaired by multiple factors; however, the analysis methods utilized to evaluate crude extracts represent a major barrier. Secondary metabolites can range in size (2,000 Da), core-structure (e.g., lipid, glycopeptide) and physicochemical properties, making development of general analytical methods difficult. Accordingly, targeted metabolomics strategies are often designed for particular compound classes that are expected to

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be produced by a gene(s) of interest.(12) This approach requires a priori knowledge and has been important for answering specific biological questions(13) but does not enable a wide breadth of profiling coverage. In contrast, untargeted strategies utilize robust approaches for the detection of a broad range of compounds but are plagued by two major issues; the vast dynamic range over which secondary metabolites are produced and the overwhelming amount of data generated by these efforts.(14) Liquid chromatography (LC) coupled with ultraviolet (UV) detection has traditionally dominated discovery efforts, but can generally only detect highly abundant compounds and yields little structural information for dereplication, or the elimination of known compounds.(15) The recent incorporation of mass spectrometry (MS)-based platforms has increased the dynamic range of compound detection and dramatically decreased the quantity of material required (i.e., detection limit). Despite these advantages, a major challenge of untargeted MS-based analysis is processing and prioritizing the data produced; a LC-MS separation of the secondary metabolites from a single organism can yield hundreds of features. Unlike other -omics fields, comprehensive MS databases are not available for small molecules meaning that compound deconvolution and identification often requires extensive searching of individual databases that represent only subsets of the metabolome from various organisms. In addition, most databases do not contain fragmentation spectra, which are invaluable for small molecule structure elucidation and unambiguous dereplication. To address these difficulties, we sought to integrate tools for both data acquisition and processing to yield an efficient and untargeted approach capable of quickly detecting, dereplicating and characterizing novel secondary metabolites. For our novel discovery workflow, we united accurate mass data acquisition, comparative MS analysis software (XCMS),(16, 17) tandem mass spectrometry analysis(18) and a molecular

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networking platform,(19) with the goal of revealing unknown compounds from S. coelicolor M145; the data processing workflow is shown in Figure 1. The organism was grown under normal and stress-inducing conditions (28 °C and 37 °C incubation) for the generation of standard (28 °C) and perturbed (37 °C) metabolite profiles. The secreted metabolomes were subjected to liquid chromatography-time-of-flight-MS (LC-TOF-MS; Figure 1, input data). This type of analysis typically results in detection of >150 features (i.e., unique compounds and adducts, M+H+, M+NH4+) creating a major bottleneck in previous discovery efforts because further characterization of this many leads would be impractical.(20) To overcome this obstacle, we prioritized and eliminated compounds from our workflow by processing the data with the comparative analysis software, XCMS (Figure 1, Stage 1). This software is designed to detect differences between sample groups and has most commonly been used to monitor primary metabolite levels.(21) We postulated that compounds produced under typical growth conditions were more likely to be known and treated them as the “standard metabolome” of S. coelicolor M145. Accordingly, the two secondary metabolomes were compared and >100 features were removed from the discovery pipeline due to the high likelihood that they were known compounds. Elimination of these features dramatically decreased the number of compounds that we then subjected to extensive manual database searching (Figure 1, Stage 2). All features surviving Stage 2 were deemed leads, as they have a high likelihood of being novel natural products. Next, tandem mass spectrometry was used to generate fragmentation profiles for the lead molecules. These spectra were compiled into a molecular network, which clusters compounds based on fragmentation similarity (common losses), putatively indicating structural resemblance (Figure 1, Stage 3).(19) Leads not found to cluster are expected to be novel scaffolds, but will likely require full purification for structural elucidation. Alternatively,

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clustered leads may be more readily identified if a common structural motif and/or known natural product is present within the cluster, either of which could simplify the structural elucidation process (Figure 1, Stage 4). With the combination of these tools, we discovered a suite of 15 amphiphilic siderophores previously unknown to be produced by the model organism, Streptomyces coelicolor M145. These molecules contain a variable lipid tail and are structurally related to the formerly characterized compound, ferrioxamine B. We also confirmed the production of a hydrophilic family member, ferrioxamine D1, which differs from B by an acetyl group. The identified siderophores were only produced at detectable levels when the organism was grown at elevated temperature, suggesting that their synthesis is stimulated in response to stress. We estimate that these molecules are present at 0.01, low fold change (

Integrated Metabolomics Approach Facilitates Discovery of an

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