A mass spectrometry-guided genome mining approach for natural product peptidogenomics - PubMed (original) (raw)

A mass spectrometry-guided genome mining approach for natural product peptidogenomics

Roland D Kersten et al. Nat Chem Biol. 2011.

Abstract

Peptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.

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Figures

Figure 1

Figure 1

Structural diversity of peptide natural products.

Figure 2

Figure 2. General workflow of Natural Product Peptidogenomics (NPP)

NPP can be applied to characterize both ribosomal and nonribosomal peptide natural products in their genotype and chemotype from genome-sequenced organisms. Two proof of concept NPP experiments are outlined: Ribosomal peptides (RNPs) or nonribosomal peptides (NRPs) and their respective biosynthetic gene cluster can be characterized from a Streptomyces extract by MALDI-TOF MS detection, MSn sequence tagging and PNP genome mining. The iterative approach in matching MSn data to genomics-derived peptide structures is shown by dashed arrows. See Figures 3 and 4, respectively, for detailed NPP analysis of ribosomal and nonribosomal peptides.

Figure 3

Figure 3. Peptidogenomic connection of a ribosomal peptide (RNP) chemotype with its biosynthetic genes (genotype) via sequence tagging and genome mining – Characterization of class III lantipeptide AmfS from Streptomyces griseus IFO 13350

Iterative aspects in connecting MS data of the peptide chemotype to the genotype are highlighted in blue and in dashed arrows. Steps are as follows: (A) Detection of putative peptide mass signals by MALDI-TOF MS or Imaging MS, (B) determination of molecular weight, (C) MSn fragmentation (CID), (D) assignment of charge states, (E) identification of mass shifts, (F) substitution of proteinogenic mass shifts (Supplementary Table 5), (G) substitution of nonproteinogenic mass shifts with putative RNP monomers (Supplementary Table 6), (H) MSn sequence tag processing of putative biosynthetic or MS gas-phase modifications, (I) MSn sequence tag processing of sequence tag direction, (J) search in 6-frame translation of target genome, (K) identification of candidate precursor peptide via RNP biosynthetic rationale, (L) verification of precursor peptide sequence, (M) prediction of core peptide sequence based on observed mass and putative PTM mass shifts, (N) verification of core peptide sequence and mass, (O) prediction of biosynthetic gene cluster, (P) verification of putative PTMs, (Q) RNP classification, (R) structure prediction based on RNP class and MSn data, and (S) structure verification by MSn data.

Figure 4

Figure 4. Peptidogenomic connection of a nonribosomal peptide (NRP) chemotype with its biosynthetic genes (genotype) via sequence tagging and genome mining – Characterization of the lipopeptide stendomycin complex from Streptomyces hygroscopicus ATCC 53653

Iterative aspects in connecting MSn data of the peptide chemotype to the genotype are highlighted in blue and in dashed arrows. Steps are as follows: (A) Detection of putative peptide mass signals by MALDI-TOF MS or Imaging-MS, (B) determination of molecular weight, (C) MSn fragmentation (CID), (D) Assignment of charge states, (E) identification of mass shifts, (F) substitution of proteinogenic mass shifts (Supplementary Table 5), (G) substitution of nonproteinogenic mass shifts with putative NRP monomers (Supplementary Table 7), (H) MSn sequence tag processing of putative biosynthetic and MS gas-phase modifications, (I) MSn sequence tag processing of sequence tag direction, (J) search predicted NRP sequences from target genome with all search tags (NP.searcher/antiSMASH), (K) biosynthetic gene cluster analysis, (L) verification of predicted NRPS assembly-line, (M) NRP structure prediction, (N) verification of predicted NRP structure, (O) full structure elucidation based on MSn and NMR data, and (P) verification of NRP structure. Abbreviations: Dha – dehydroalanine; Dhb – dehydrobutyrine; HseL – homoserine lactone; Orn – ornithine.

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