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DeepRiPP integrates multiomics data to automate discovery of novel ribosomally synthesized natural products. Proc Natl Acad Sci U S A 2019; 117:371-380. [PMID: 31871149 DOI: 10.1073/pnas.1901493116] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Microbial natural products represent a rich resource of evolved chemistry that forms the basis for the majority of pharmacotherapeutics. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a particularly interesting class of natural products noted for their unique mode of biosynthesis and biological activities. Analyses of sequenced microbial genomes have revealed an enormous number of biosynthetic loci encoding RiPPs but whose products remain cryptic. In parallel, analyses of bacterial metabolomes typically assign chemical structures to only a minority of detected metabolites. Aligning these 2 disparate sources of data could provide a comprehensive strategy for natural product discovery. Here we present DeepRiPP, an integrated genomic and metabolomic platform that employs machine learning to automate the selective discovery and isolation of novel RiPPs. DeepRiPP includes 3 modules. The first, NLPPrecursor, identifies RiPPs independent of genomic context and neighboring biosynthetic genes. The second module, BARLEY, prioritizes loci that encode novel compounds, while the third, CLAMS, automates the isolation of their corresponding products from complex bacterial extracts. DeepRiPP pinpoints target metabolites using large-scale comparative metabolomics analysis across a database of 10,498 extracts generated from 463 strains. We apply the DeepRiPP platform to expand the landscape of novel RiPPs encoded within sequenced genomes and to discover 3 novel RiPPs, whose structures are exactly as predicted by our platform. By building on advances in machine learning technologies, DeepRiPP integrates genomic and metabolomic data to guide the isolation of novel RiPPs in an automated manner.
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Ratnayake AS, Chang LP, Tumey LN, Loganzo F, Chemler JA, Wagenaar M, Musto S, Li F, Janso JE, Ballard TE, Rago B, Steele GL, Ding W, Feng X, Hosselet C, Buklan V, Lucas J, Koehn FE, O'Donnell CJ, Graziani EI. Natural Product Bis-Intercalator Depsipeptides as a New Class of Payloads for Antibody-Drug Conjugates. Bioconjug Chem 2018; 30:200-209. [PMID: 30543418 DOI: 10.1021/acs.bioconjchem.8b00843] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
A potent class of DNA-damaging agents, natural product bis-intercalator depsipeptides (NPBIDs), was evaluated as ultrapotent payloads for use in antibody-drug conjugates (ADCs). Detailed investigation of potency (both in cells and via biophysical characterization of DNA binding), chemical tractability, and in vitro and in vivo stability of the compounds in this class eliminated a number of potential candidates, greatly reducing the complexity and resources required for conjugate preparation and evaluation. This effort yielded a potent, stable, and efficacious ADC, PF-06888667, consisting of the bis-intercalator, SW-163D, conjugated via an N-acetyl-lysine-valine-citrulline- p-aminobenzyl alcohol- N, N-dimethylethylenediamine (AcLysValCit-PABC-DMAE) linker to an engineered variant of the anti-Her2 mAb, trastuzumab, catalyzed by transglutaminase.
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Affiliation(s)
- Anokha S Ratnayake
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Li-Ping Chang
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - L Nathan Tumey
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Frank Loganzo
- Oncology Research , Pfizer Worldwide Research and Development , 401 North Middletown Road , Pearl River , New York 10965 , United States
| | - Joseph A Chemler
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Melissa Wagenaar
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Sylvia Musto
- Oncology Research , Pfizer Worldwide Research and Development , 401 North Middletown Road , Pearl River , New York 10965 , United States
| | - Fengping Li
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Jeffrey E Janso
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - T Eric Ballard
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Brian Rago
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Greg L Steele
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - WeiDong Ding
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Xidong Feng
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Christine Hosselet
- Oncology Research , Pfizer Worldwide Research and Development , 401 North Middletown Road , Pearl River , New York 10965 , United States
| | - Vlad Buklan
- Oncology Research , Pfizer Worldwide Research and Development , 401 North Middletown Road , Pearl River , New York 10965 , United States
| | - Judy Lucas
- Oncology Research , Pfizer Worldwide Research and Development , 401 North Middletown Road , Pearl River , New York 10965 , United States
| | - Frank E Koehn
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Christopher J O'Donnell
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
| | - Edmund I Graziani
- Medicine Design , Pfizer Worldwide Research and Development , 445 Eastern Point Road , Groton , Connecticut 06340 , United States
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Walsh CT. Are highly morphed peptide frameworks lurking silently in microbial genomes valuable as next generation antibiotic scaffolds? Nat Prod Rep 2017; 34:687-693. [PMID: 28513710 DOI: 10.1039/c7np00011a] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Antibiotics are a therapeutic class that, once deployed, select for resistant bacterial pathogens and so shorten their useful life cycles. As a consequence new versions of antibiotics are constantly needed. Among the antibiotic natural products, morphed peptide scaffolds, converting conformationally mobile, short-lived linear peptides into compact, rigidified small molecule frameworks, act on a wide range of bacterial targets. Advances in bacterial genome mining, biosynthetic gene cluster prediction and expression, and mass spectroscopic structure analysis suggests many more peptides, modified both in side chains and peptide backbones, await discovery. Such molecules may turn up new bacterial targets and be starting points for combinatorial or semisynthetic manipulations to optimize activity and pharmacology parameters.
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Ziemert N, Alanjary M, Weber T. The evolution of genome mining in microbes - a review. Nat Prod Rep 2016; 33:988-1005. [PMID: 27272205 DOI: 10.1039/c6np00025h] [Citation(s) in RCA: 404] [Impact Index Per Article: 50.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Covering: 2006 to 2016The computational mining of genomes has become an important part in the discovery of novel natural products as drug leads. Thousands of bacterial genome sequences are publically available these days containing an even larger number and diversity of secondary metabolite gene clusters that await linkage to their encoded natural products. With the development of high-throughput sequencing methods and the wealth of DNA data available, a variety of genome mining methods and tools have been developed to guide discovery and characterisation of these compounds. This article reviews the development of these computational approaches during the last decade and shows how the revolution of next generation sequencing methods has led to an evolution of various genome mining approaches, techniques and tools. After a short introduction and brief overview of important milestones, this article will focus on the different approaches of mining genomes for secondary metabolites, from detecting biosynthetic genes to resistance based methods and "evo-mining" strategies including a short evaluation of the impact of the development of genome mining methods and tools on the field of natural products and microbial ecology.
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Affiliation(s)
- Nadine Ziemert
- Interfaculty Institute for Microbiology and Infection Medicine Tübingen (IMIT), Microbiology and Biotechnology, University of Tuebingen, Germany.
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Johnston CW, Plumb J, Li X, Grinstein S, Magarvey NA. Informatic analysis reveals Legionella as a source of novel natural products. Synth Syst Biotechnol 2016; 1:130-136. [PMID: 29062936 PMCID: PMC5640695 DOI: 10.1016/j.synbio.2015.12.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2015] [Revised: 12/07/2015] [Accepted: 12/14/2015] [Indexed: 01/08/2023] Open
Abstract
Microbial natural products are a crucial source of bioactive molecules and unique chemical scaffolds. Despite their importance, rediscovery of known natural products from established productive microbes has led to declining interest, even while emergent genomic data suggest that the majority of microbial natural products remain to be discovered. Now, new sources of microbial natural products must be defined in order to provide chemical scaffolds for the next generation of small molecules for therapeutic, agricultural, and industrial purposes. In this work, we use specialized bioinformatic programs, genetic knockouts, and comparative metabolomics to define the genus Legionella as a new source of novel natural products. We show that Legionella spp. hold a diverse collection of biosynthetic gene clusters for the production of polyketide and nonribosomal peptide natural products. To confirm this bioinformatic survey, we create targeted mutants of L. pneumophila and use comparative metabolomics to identify a novel polyketide surfactant. Using spectroscopic techniques, we show that this polyketide possesses a new chemical scaffold, and firmly demonstrate that this unexplored genus is a source for novel natural products.
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Affiliation(s)
- Chad W. Johnston
- The Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada L8N 3Z5
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, Canada L8N 3Z5
| | - Jonathan Plumb
- Cell Biology Program, Hospital for Sick Children, Toronto, Ontario, Canada M5G 1X8
| | - Xiang Li
- The Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada L8N 3Z5
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, Canada L8N 3Z5
| | - Sergio Grinstein
- Cell Biology Program, Hospital for Sick Children, Toronto, Ontario, Canada M5G 1X8
| | - Nathan A. Magarvey
- The Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada L8N 3Z5
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, Canada L8N 3Z5
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Draft Genome Sequence of
Streptomyces silvensis
ATCC 53525, a Producer of Novel Hormone Antagonists. GENOME ANNOUNCEMENTS 2016; 4:4/1/e00001-16. [PMID: 26893408 PMCID: PMC4759055 DOI: 10.1128/genomea.00001-16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Streptomyces silvensis produces nonribosomal peptides that act as antagonists of the human oxytocin and vasopressin receptors. Here, we present the genome sequence of S. silvensis ATCC 53525 and demonstrate that this organism possesses a number of additional biosynthetic gene clusters and might be a promising source for genome-guided drug discovery efforts.
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Weber T, Kim HU. The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production. Synth Syst Biotechnol 2016; 1:69-79. [PMID: 29062930 PMCID: PMC5640684 DOI: 10.1016/j.synbio.2015.12.002] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 12/10/2015] [Accepted: 12/26/2015] [Indexed: 01/02/2023] Open
Abstract
Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org) is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field.
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Key Words
- A, adenylation domain
- Antibiotics
- BGC, biosynthetic gene cluster
- Bioinformatics
- Biosynthesis
- C, condensation domain
- GPR, gene-protein-reaction
- HMM, hidden Markov model
- LC, liquid chromatography
- MS, mass spectrometry
- NMR, nuclear magnetic resonance
- NRP, non-ribosomally synthesized peptide
- NRPS
- NRPS, non-ribosomal peptide synthetase
- Natural product
- PCP, peptidyl carrier protein
- PK, polyketide
- PKS
- PKS, polyketide synthase
- RiPP, ribosomally and post-translationally modified peptide
- SVM, support vector machine
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Affiliation(s)
- Tilmann Weber
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kogle Alle 6, 2970 Hørsholm, Denmark
| | - Hyun Uk Kim
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kogle Alle 6, 2970 Hørsholm, Denmark.,BioInformatics Research Center, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
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Johnston CW, Skinnider MA, Wyatt MA, Li X, Ranieri MRM, Yang L, Zechel DL, Ma B, Magarvey NA. An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products. Nat Commun 2015; 6:8421. [PMID: 26412281 PMCID: PMC4598715 DOI: 10.1038/ncomms9421] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2015] [Accepted: 08/19/2015] [Indexed: 12/04/2022] Open
Abstract
Bacterial natural products are a diverse and valuable group of small molecules, and genome sequencing indicates that the vast majority remain undiscovered. The prediction of natural product structures from biosynthetic assembly lines can facilitate their discovery, but highly automated, accurate, and integrated systems are required to mine the broad spectrum of sequenced bacterial genomes. Here we present a genome-guided natural products discovery tool to automatically predict, combinatorialize and identify polyketides and nonribosomal peptides from biosynthetic assembly lines using LC–MS/MS data of crude extracts in a high-throughput manner. We detail the directed identification and isolation of six genetically predicted polyketides and nonribosomal peptides using our Genome-to-Natural Products platform. This highly automated, user-friendly programme provides a means of realizing the potential of genetically encoded natural products. Microbial natural products represent a large reservoir of potential pharmaceutical agents. Here, Johnston et al. describe a computer-automated programme for connecting genome sequences with identified and isolated natural products.
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Affiliation(s)
- Chad W Johnston
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
| | - Michael A Skinnider
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
| | - Morgan A Wyatt
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
| | - Xiang Li
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
| | - Michael R M Ranieri
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
| | - Lian Yang
- The David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1
| | - David L Zechel
- Department of Chemistry; Queens University, Kingston, Ontario, Canada K7L 3N6
| | - Bin Ma
- The David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1
| | - Nathan A Magarvey
- Department of Biochemistry &Biomedical Sciences, M. G. DeGroote Institute for Infectious Disease Research; McMaster University, Hamilton, Ontario, Canada L8N 3Z5.,Department of Chemistry &Chemical Biology, M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5
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