Abstract
Major advances in genome sequencing and large-scale biosynthetic gene cluster (BGC) analysis have prompted an age of natural product discovery driven by genome mining. Still, connecting molecules to their cognate BGCs is a substantial bottleneck for this approach. We have developed a mass-spectrometry-based parallel stable isotope labeling platform, termed IsoAnalyst, which assists in associating metabolite stable isotope labeling patterns with BGC structure prediction to connect natural products to their corresponding BGCs. Here we show that IsoAnalyst can quickly associate both known metabolites and unknown analytes with BGCs to elucidate the complex chemical phenotypes of these biosynthetic systems. We validate this approach for a range of compound classes, using both the type strain Saccharopolyspora erythraea and an environmentally isolated Micromonospora sp. We further demonstrate the utility of this tool with the discovery of lobosamide D, a new and structurally unique member of the family of lobosamide macrolactams.
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Data availability
Whole genome sequence (WGS) data for Micromonospora sp. RL09-050-HVF-A was uploaded to NCBI GenBank under the accession number JAGKQP000000000 and the BioProject ID PRJNA718589. The version described in this paper is version JAGKQP010000000. WGS data for Saccharopolyspora erythraea are available in NCBI with the accession code NC_009142. The processed mass spectrometry data, antiSMASH output for Micromonospora sp. RL09-050-HVF-A, and IsoAnalyst output files that support the findings of this study have been deposited in Zenodo [10.5281/zenodo.4711483]. The MIBiG database used in this study is available at https://mibig.secondarymetabolites.org/. Raw mass spectrometry data have been deposited to MassIVE under the accession numbers MSV000087824 (S. erythraea) and MSV00008723 (Micromonospora sp.). The structure of lobosamide D has been deposited to the Natural Products Atlas (www.npatlas.org). The NMR data for lobosamide D have been deposited to the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org) under accession number NP0044012. MS/MS spectra for lobosamides C and D have been deposited to the Global Natural Products Social molecular networking database (GNPS; https://gnps.ucsd.edu) under accession numbers CCMSLIB00006685341 and CCMSLIB00006709936, respectively.
Code availability
The IsoAnalyst package is freely available via GitHub under an open access MIT software license (https://github.com/liningtonlab/isoanalyst).
References
Kalkreuter, E., Pan, G., Cepeda, A. J. & Shen, B. Targeting bacterial genomes for natural product discovery. Trends Pharmacol. Sci. 41, 13–26 (2020).
Medema, M. H. & Fischbach, M. A. Computational approaches to natural product discovery. Nat. Chem. Biol. 11, 639–648 (2015).
Skinnider, M. A. et al. Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences. Nat. Commun. 11, 6058 (2020).
Cimermancic, P. et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell 158, 412–421 (2014).
Helfrich, E. J. N. et al. Automated structure prediction of trans-acyltransferase polyketide synthase products. Nat. Chem. Biol. 15, 813–821 (2019).
Del Carratore, F. et al. Computational identification of co-evolving multi-gene modules in microbial biosynthetic gene clusters. Commun. Biol. 2, 83 (2019).
Blin, K. et al. AntiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 47, W81–W87 (2019).
Séelem-Mojica, N., Aguilar, C., Gutiéerrez-García, K., Martínez-Guerrero, C. E. & Barona-Gómez, F. EvoMining reveals the origin and fate of natural product biosynthetic enzymes. Microb. Genom. 5, e000260 (2019).
Kautsar, S. A. et al. MIBiG 2.0: a repository for biosynthetic gene clusters of known function. Nucleic Acids Res. 48, D454–D458 (2020).
Palaniappan, K. et al. IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase. Nucleic Acids Res. 48, D422–D430 (2020).
Van Santen, J. A. et al. The Natural Products Atlas: an open access knowledge base for microbial natural products discovery. ACS Cent. Sci. 5, 1824–1833 (2019).
Rutz, A. et al. The LOTUS Initiative for Open Natural Products Research: Knowledge Management through Wikidata. Preprint at bioRxiv https://doi.org/10.1101/2021.02.28.433265 (2021).
Navarro-Muñoz, J. C. et al. A computational framework to explore large-scale biosynthetic diversity. Nat. Chem. Biol. 16, 60–68 (2020).
Kautsar, S. A., Blin, K., Shaw, S., Weber, T. & Medema, M. H. BiG-FAM: the biosynthetic gene cluster families database. Nucleic Acids Res. 49, D490–D497 (2021).
Van Der Hooft, J. J. J. et al. Linking genomics and metabolomics to chart specialized metabolic diversity. Chem. Soc. Rev. 49, 3297–3314 (2020).
Kloosterman, A. M. et al. Expansion of RiPP biosynthetic space through integration of pan-genomics and machine learning uncovers a novel class of lantibiotics. PLoS Biol. 18, e3001026 (2020).
Jensen, P. R. Natural products and the gene cluster revolution. Trends Microbiol. 24, 968–977 (2016).
Ziemert, N., Alanjary, M. & Weber, T. The evolution of genome mining in microbes – a review. Nat. Prod. Rep. 33, 988–1005 (2016).
Zhang, M. M., Wang, Y., Ang, E. L. & Zhao, H. Engineering microbial hosts for production of bacterial natural products. Nat. Prod. Rep. 33, 963–987 (2016).
Xu, F. et al. A genetics-free method for high-throughput discovery of cryptic microbial metabolites. Nat. Chem. Biol. 15, 161–168 (2019).
Zhang, M. M. et al. CRISPR–Cas9 strategy for activation of silent Streptomyces biosynthetic gene clusters. Nat. Chem. Biol. 13, 607–609 (2017).
Kenshole, E., Herisse, M., Michael, M. & Pidot, S. J. Natural product discovery through microbial genome mining. Curr. Opin. Chem. Biol. 60, 47–54 (2021).
Soldatou, S., Eldjarn, G. H., Huerta-Uribe, A., Rogers, S. & Duncan, K. R. Linking biosynthetic and chemical space to accelerate microbial secondary metabolite discovery. FEMS Microbiol. Lett. 366, fnz142 (2019).
Ernst, M. et al. MolNetEnhancer: enhanced molecular networks by integrating metabolome mining and annotation tools. Metabolites 9, 144 (2019).
Mohimani, H. et al. Dereplication of peptidic natural products through database search of mass spectra. Nat. Chem. Biol. 13, 30–37 (2017).
Duncan, K. R. et al. Molecular networking and pattern-based genome mining improves discovery of biosynthetic gene clusters and their products from Salinispora species. Chem. Biol. 22, 460–471 (2015).
Mohimani, H. et al. NRPquest: coupling mass spectrometry and genome mining for nonribosomal peptide discovery. J. Nat. Prod. 77, 1902–1909 (2014).
Behsaz, B. et al. Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery. Nat. Commun. 12, 3225 (2021).
Rittenberg, D. & Bloch, K. The utilization of acetic acid for the synthesis of fatty acids. J. Biol. Chem. 160, 417–424 (1945).
Bloch, K. & Rittenberg, D. On the utilization of acetic acid for cholesterol formation. J. Biol. Chem. 145, 625–636 (1942).
Kaneda, T., Butte, J. C., Taubman, S. B. & Corcoran, J. W. Actinomycete antibiotics. III. The biogenesis of erythronolide, the C-21 branched chain lactone in erythromycin. J. Biol. Chem. 237, 322–328 (1962).
Chokkathukalam, A., Kim, D.-H., Barrett, M. P., Breitling, R. & Creek, D. J. Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks. Bioanalysis 6, 511–524 (2014).
Huang, X. et al. X13CMS: global tracking of isotopic labels in untargeted metabolomics. Anal. Chem. 86, 1632–1639 (2014).
Chokkathukalam, A. et al. MzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data. Bioinformatics 29, 281–283 (2013).
Tang, J. K. H., You, L., Blankenship, R. E. & Tang, Y. J. Recent advances in mapping environmental microbial metabolisms through 13C isotopic fingerprints. J. R. Soc. Interface 9, 2767–2780 (2012).
Khosla, C., Tang, Y., Chen, A. Y., Schnarr, N. A. & Cane, D. E. Structure and mechanism of the 6-deoxyerythronolide B synthase. Annu. Rev. Biochem. 76, 195–221 (2007).
Zhang, H., Wang, Y., Wu, J., Skalina, K. & Pfeifer, B. A. Complete biosynthesis of erythromycin A and designed analogs using E. coli as a heterologous host. Chem. Biol. 17, 1232–1240 (2010).
Chevrette, M. G., Aicheler, F., Kohlbacher, O., Currie, C. R. & Medema, M. H. SANDPUMA: ensemble predictions of nonribosomal peptide chemistry reveal biosynthetic diversity across Actinobacteria. Bioinformatics 33, 3202–3210 (2017).
Röttig, M. et al. NRPSpredictor2 – a web server for predicting NRPS adenylation domain specificity. Nucleic Acids Res. 39, W362–W367 (2011).
Tietz, J. I. et al. A new genome-mining tool redefines the lasso peptide biosynthetic landscape. Nat. Chem. Biol. 13, 470–478 (2017).
Robbel, L., Knappe, T. A., Linne, U., Xie, X. & Marahiel, M. A. Erythrochelin – a hydroxamate-type siderophore predicted from the genome of Saccharopolyspora erythraea. FEBS J. 277, 663–676 (2009).
Schulze, C. J. et al. Genome-directed lead discovery: biosynthesis, structure elucidation, and biological evaluation of two families of polyene macrolactams against Trypanosoma brucei. ACS Chem. Biol. 10, 2373–2381 (2015).
Barona-Gómez, F., Wong, U., Giannakopulos, A. E., Derrick, P. J. & Challis, G. L. Identification of a cluster of genes that directs desferrioxamine biosynthesis in Streptomyces coelicolor M145. J. Am. Chem. Soc. 126, 16282–16283 (2004).
Lee, H.-S. et al. Cyclic peptides of the nocardamine class from a marine-derived bacterium of the genus Streptomyces. J. Nat. Prod. 68, 623–625 (2005).
Schulze, C. J. et al. ‘Function-first’ lead discovery: mode of action profiling of natural product libraries using image-based screening. Chem. Biol. 20, 285–295 (2013).
Hoshino, S. et al. Mycolic acid containing bacterium stimulates tandem cyclization of polyene macrolactam in a lake sediment derived rare actinomycete. Org. Lett. 19, 4992–4995 (2017).
Hoshino, S. et al. Mirilactams C-E, novel polycyclic macrolactams isolated from combined-culture of Actinosynnema mirum NBRC 14064 and mycolic acid-containing bacterium. Chem. Pharm. Bull. 66, 660–667 (2018).
Mosey, R. A. & Floreancig, P. E. Isolation, biological activity, synthesis, and medicinal chemistry of the pederin/mycalamide family of natural products. Nat. Prod. Rep. 29, 980–995 (2012).
Karas, J. A. et al. Structure–activity relationships of daptomycin lipopeptides. J. Med. Chem. 63, 13266–13290 (2020).
Duetz, W. A. et al. Methods for intense aeration, growth, storage, and replication of bacterial strains in microtiter plates. Appl. Environ. Microbiol. 66, 2641–2646 (2000).
Acknowledgements
We thank E. Ye for assistance with NMR experiments, J. Shoults for fabricating 24-well plate holders, K. Kurita for discussion about label incorporation rates, and T. Clark for providing desferrioxamine compound standards. Funding was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery program (R.G.L.), the National Institutes of Health (AT008718 to R.G.L.) and the Netherlands eScience Center (NLeSC) Accelerating Scientific Discoveries Grant (ASDI.2017.030 to J.J.J.v.d.H. and M.H.M.).
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C.S.M. and R.G.L. designed the study. C.S.M. performed all microbial cultures, isotopic labeling and mass spectrometric analyses. C.S.M. and J.A.v.S. wrote the code and code documentation. J.J.J.v.d.H. and M.H.M. identified the BGCs from the genome sequences and determined the predicted labeling for each BGC. C.S.M. isolated and identified all compounds. C.S.M. and R.G.L. wrote the manuscript with assistance from all authors. All authors approved the final version of the manuscript.
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J.A.v.S. is a consultant for Unnatural Products Inc. M.H.M. is a member of the Scientific Advisory Board of Hexagon Bio and co-founder of Design Pharmaceuticals.
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Peer review information Nature Chemical Biology thanks Camila Crnkovic, Hosein Mohimani and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 TCA cycle labeling by [1-13C]acetate.
Red filled circles represent 13C derived from [1-13C]acetate following its direct transformation to acetyl-CoA. When a 13C labeled succinyl-CoA is converted to succinate, the position of the 13C label becomes ambiguous due to the symmetry of succinate, represented by open red circles, indicating that either position has an equal chance of being labeled. Labeled oxaloacetate re-enters the TCA cycle resulting in up to two 13C incorporation events in citrate, isocitrate, and a-ketoglutarate. Groups of amino acids that are derived from TCA cycle biosynthetic precursors are indicated. The interconversion of succinate and succinyl-CoA leads to the indirect incorporation of 13C into the C1 position of methylmalonyl-CoA as indicated by an open red circle while the direct labeling of the C4 position of methylmalonyl-CoA is lost to decarboxylation during the PKS condensation of methylmalonyl-CoA units.
Extended Data Fig. 2 IsoAnalyst MS data processing workflow.
(a) Required data pre-processing steps to generate input files for IsoAnalyst. Files (indicated as parallelograms) highlighted with a light gray box are required input files generated by third party tools that can perform the processes shown in dashed rectangles. We recommend MSconvert and MZmine for these processes however other programs may be used as long as the.csv input meets the requirements described in the software documentation available in the GitHub repository. The ground truth feature list of features aligned across samples is highlighted in a dark gray box and may be generated by the ‘Prep’ step of the IsoAnalyst program (highlighted in green) or by third party tools (for example, MZmine). (b) IsoAnalyst performs the following steps: all isotopologue peak information for every feature is first scraped from the.mzML data files in the ‘Scrape’ step (highlighted in blue). In the ‘Analyze’ step (highlighted in orange), the isotopologue ratios are compared for every feature in each SIL condition to determine the extent of labeling. Finally, a summary file is generated containing all of the SIL incorporation profiles for every feature that contains labeling in two or more conditions.
Extended Data Fig. 3 MS Data centroiding and isotopologue ratio plotting.
(a) Diagram of LC-MS data acquisition showing mass spectra collected at regular time intervals across a chromatographic peak. Each orange line represents a single mass spectrum, or scan, containing m/z vs. intensity values across the instrument’s range. Data are first centroided, or peak picked, to give a single data point corresponding to the intensity of every m/z value in a scan. (b) All centroided scan data for a given feature plotted together as single points. (c) All centroided scan data for the first two isotopologue peaks, M1 and M0, plotted by matching scans. The slope of the linear trend line in (c) is the isotopologue ratio used in the analysis step of the IsoAnalyst workflow.
Extended Data Fig. 4 SIL incorporation for erythrochelin (7).
(a) Substrates used in the biosynthesis of 7, and both the expected and observed labeling of 7. (b) Structures and mass spectra for the iron adduct (m/z 657.2064) and the protonated adduct (m/z 604.2950) of 7 in the [1-13C]acetate and [1-15N]glutamate conditions. [1-13C]Propionate and [methyl-13C] methionine conditions are not shown as 7 was not produced under the [1-13C] propionate condition and no SIL incorporation occurred under the [methyl-13C]methionine condition.
Extended Data Fig. 5 SIL incorporation in fragments of 7.
Mass spectra of fragments m/z 390.1990 (a), m/z 303.1666 (b), m/z 173.0932 (c) and m/z 131.0827 (d) under [1-13C]acetate and [1-15N]glutamate conditions indicate that the detected SIL incorporation is within the expected labeling maximums for the biosynthetic subunits derived from ornithine and acetyl-CoA.
Extended Data Fig. 6 IsoAnalyst profiles for desferrioxamine analogues.
(a) Diagram showing all labeled MS features detected in the metabolome of Micromonospora sp. Circles represent features with IsoAnalyst profiles resembling the desferrioxamines. Diamonds represent features with IsoAnalyst profiles resembling the lobosamides. (b) Structures and IsoAnalyst profiles for desferrioxamine compounds indicated by filled gray circles in (a).
Extended Data Fig. 7 IsoAnalyst profiles of microferrioxamines and their fragments.
Each box contained the expected and observed SIL incorporation for various ions associated with compounds 11, 12, and 13. Due to the substrate flexibility of the acyl transferase DesC39, the exact number of acetate-derived subunits cannot be accurately predicted.
Extended Data Fig. 8 IsoAnalyst profiles of desferrioxamines and their fragments.
(a) Structures with observed fragmentation indicated and mass spectra for [M + H]+ ions of 8 and 14. Expected (Exp.) and observed (Obs.) labeling for 8 and 14 in each condition is indicated in boxes. (b) Mass spectra of observed b-ion and y-ion fragments for 8 and 14. Expected and observed labeling for fragments indicated in boxes.
Extended Data Fig. 9 Lobosamide MS adducts.
Adducts and in-source fragment ions corresponding to compounds 15, 16, and 17, which had SIL incorporation detected by IsoAnalyst.
Supplementary information
Supplementary Information
Supplementary Figs. 1–37, Tables 1–5 and Notes 1–3.
Supplementary Table 6
Supplementary_Table_6_Saccharopolyspora.xlsx.
Supplementary Table 7
Supplementary_Table_7_Micromonospora.xlsx.
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McCaughey, C.S., van Santen, J.A., van der Hooft, J.J.J. et al. An isotopic labeling approach linking natural products with biosynthetic gene clusters. Nat Chem Biol 18, 295–304 (2022). https://doi.org/10.1038/s41589-021-00949-6
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DOI: https://doi.org/10.1038/s41589-021-00949-6