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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Representative Results
  • Discussion
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

A mass spectrometry-guided genome mining protocol is established and described here. It is based on genome sequence information and LC-MS/MS analysis and aims to facilitate identification of molecules from complex microbial and plant extracts.

Abstract

The chemical space covered by natural products is immense and widely unrecognized. Therefore, convenient methodologies to perform wide-ranging evaluation of their functions in nature and potential human benefits (e.g., for drug discovery applications) are desired. This protocol describes the combination of genome mining (GM) and molecular networking (MN), two contemporary approaches that match gene cluster-encoded annotations in whole genome sequencing with chemical structure signatures from crude metabolic extracts. This is the first step towards the discovery of new natural entities. These concepts, when applied together, are defined here as MS-guided genome mining. In this method, the main components are previously designated (using MN), and structurally related new candidates are associated with genome sequence annotations (using GM). Combining GM and MN is a profitable strategy to target new molecule backbones or harvest metabolic profiles in order to identify analogues from already known compounds.

Introduction

Investigations of secondary metabolism often consist of screening crude extracts for specific biological activities followed by purification, identification, and characterization of the constituents belonging to active fractions. This process has proved to be efficient, promoting the isolation of several chemical entities. However, nowadays this is seen as unfeasible, mainly due to the high rates of rediscovery. As the pharmaceutical industry revolutionized without knowledge of the roles and functions of specialized metabolites, their identification was carried out under laboratory conditions that did not accurately represent nature1. Today, th....

Protocol

1. Genome mining for biosynthetic gene clusters

  1. Perform whole genome sequencing (WGS) as the first step to electing a biosynthetic gene cluster (BCG) for MS-guided genome mining. The whole genome draft of the strain of interest (bacteria) can be obtained by Illumina MiSeq technology using the following with high quality genomic DNA: shotgun TruSeq PCR-Free library prep and Nextera Mate Pair Library Preparation Kit33.
    NOTE: After sequencing, the Illumina shotgun library and Illum.......

Representative Results

The protocol was successfully exemplified using a combination of genome mining, heterologous expression, and MS-guided/code approaches to access new specialized valinomycin analogues molecules. The genome-to-molecule workflow for the target, valinomycin (VLM), is represented in Figure 8. Streptomyces sp. CBMAI 2042 draft genome was analyzed in silico, and the VLM gene cluster was then identified and transferred to a heterologous host. Heterologous and wild type strains were cultivat.......

Discussion

The strongest advantage of this protocol is its ability to rapidly dereplicate metabolic profiles and bridge genomic information with MS data in order to elucidate the structures of new molecules, especially structural analogues2. Based on genomic information, different natural products chemotypes can be investigated, such as polyketides (PK), nonribosomal peptides (NRP), and glycosylated natural products (GNP), as well as cryptic BGCs. Metabolomic screening yields evidence of activated BGC profil.......

Acknowledgements

The financial support for this study was provided by São Paulo Research Foundation - FAPESP (2019/10564-5, 2014/12727-5 and 2014/50249-8 to L.G.O; 2013/12598-8 and 2015/01013-4 to R.S.; and 2019/08853-9 to C.F.F.A). B.S.P, C.F.F.A., and L.G.O. received fellowships from the National Council for Scientific and Technological Development - CNPq (205729/2018-5, 162191/2015-4, and 313492/2017-4). L.G.O. is also grateful for the grant support provided by the program For Women in Science (2008, Brazilian Edition). All authors acknowledge CAPES (Coordination for the Improvement of Higher Education Personnel) for supporting the post-graduation programs in Brazil.

....

Materials

NameCompanyCatalog NumberComments
AcetonitrileTediaAA1120-048HPLC grade
AgarOxoidLP0011NA
ApramycinSigma AldrichA2024NA
CarbenicillinSigma AldrichC9231NA
CentrifugeEppendorfNA5804
ChloramphenicolSigma AldrichC3175NA
Column C18Agilent TechnologiesNAZORBAX RRHD Extend-C18, 80Å, 2.1 x 50 mm, 1.8 µm, 1200 bar pressure limit P/N 757700-902
KanamycinSigma AldrichK1377NA
Manitol P.A.- A.C.S.SynthNANA
MicrocentrifugeEppendorfNA5418
Nalidixic acidSigma AldrichN4382NA
Phusion Flash High-Fidelity PCR Master MixThermoFisher ScientificF548SNA
Q-TOF mass spectrometerAgilent technologiesNA6550 iFunnel Q-TOF LC/MS
Sacarose P.A.- A.C.S.SynthNANA
Shaker/IncubatorMarconiMA420NA
Sodium ChlorideSynthNAP. A. - ACS
Soy extractNANANA
SucroseSynthNAP. A. - ACS
Thermal CyclesEppendorfNAMastercycler Nexus Gradient
ThiostreptonSigma AldrichT8902NA
TryptoneOxoidLP0042NA
Tryptone Soy BrothOxoidCM0129NA
UPLCAgilent TechnologiesNA1290 Infinity LC System
Yeast extractOxoidLP0021NA

References

  1. Davies, J. Specialized microbial metabolites: functions and origins. The Journal of Antibiotics. 66 (7), 361-364 (2013).
  2. Ziemert, N., Alanjary, M., Weber, T. The evolution of genome mining in microbes - a review.

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Mass SpectrometryGenome MiningNatural Product DiscoveryMolecular NetworkingWhole Genome SequencingGenotype to chemotypeBiosynthetic ClustersSecondary MetabolismGNPSStreptomycesFungiPlants

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