Natural Product Discovery with LC-MS/MS Diagnostic Fragmentation Filtering: Application for Microcystin Analysis

Summary

Diagnostic fragmentation filtering, implemented into MZmine, is an elegant, post-acquisition approach to screen LC-MS/MS datasets for entire classes of both known and unknown natural products. This tool searches MS/MS spectra for product ions and/or neutral losses that the analyst has defined as being diagnostic for the entire class of compounds.

Abstract

Natural products are often biosynthesized as mixtures of structurally similar compounds, rather than a single compound. Due to their common structural features, many compounds within the same class undergo similar MS/MS fragmentation and have several identical product ions and/or neutral losses. The purpose of diagnostic fragmentation filtering (DFF) is to efficiently detect all compounds of a given class in a complex extract by screening non-targeted LC-MS/MS datasets for MS/MS spectra that contain class specific product ions and/or neutral losses. This method is based on a DFF module implemented within the open-source MZmine platform that requires sample extracts be analyzed by data-dependent acquisition on a high-resolution mass spectrometer such as quadrupole Orbitrap or quadrupole time-of-flight mass analyzers. The main limitation of this approach is the analyst must first define which product ions and/or neutral losses are specific for the targeted class of natural products. DFF allows for the subsequent discovery of all related natural products within a complex sample, including new compounds. In this work, we demonstrate the effectiveness of DFF by screening extracts of Microcystis aeruginosa, a prominent harmful algal bloom causing cyanobacteria, for the production of microcystins.

Introduction

Tandem mass spectrometry (MS/MS) is a widely used mass spectrometry method that involves isolating a precursor ion and inducing fragmentation via application of activation energy such as collision induced dissociation (CID)¹. The manner in which an ion fragments is intimately linked to its molecular structure. Natural products are often biosynthesized as mixtures of structurally similar compounds rather than as a single unique chemical². As such, structurally related compounds that are part of the same biosynthetic class often share key MS/MS fragmentation characteristics, including shared product ions and/or ne....

Protocol

1. Preparation of non-targeted liquid chromatography (LC)-MS/MS datasets

NOTE: DFF can be performed using any high-resolution mass spectrometer and analytical method optimized for a target class of analytes. MC optimized LC-MS/MS conditions on Orbitrap mass spectrometer are listed in the Table of Materials.

1. Downloading MZmine 2 (http://mzmine.github.io/)
   NOTE: Example data CPCC300.raw can be found at https://drive.google.com/open?id=1HHbLdvxCMycSasyNXPRqIe5pkaSqQoS0.
   1. Under the Raw data methods drop down menu, select the Raw data import optio....

Results

The DFF plot generated following the analysis of M. aeruginosa CPCC300 is shown in Figure 4. The x-axis of this plot is the m/z of the precursor ions that satisfied the defined DFF criteria while the y-axis shows the m/z of all product ions within the MCs MS/MS spectra. For this analysis, the criteria for MC detection included precursor ions within the m/z range of 440-1200, retention times between 2.00–6........

Discussion

DFF is a straight-forward and rapid strategy for detecting entire classes of compounds, especially relevant for natural product compound discovery. The most important aspect of DFF is defining the specific MS/MS fragmentation criteria for the targeted class of compounds. In this representative example, DFF was used to detect all Adda residue containing MCs present in an M. aeruginosa cellular extract. Although the vast majority of MCs contain an Adda residue, other residues at this position have been known, nota.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Cyanobacteria
Microcystis aeruginosaCPCC300	CANADIAN PHYCOLOGICAL CULTURE CENTRE	CPCC300	https://uwaterloo.ca/canadian-phycological-culture-centre/
Software
Proteowizard (software)		software	http://proteowizard.sourceforge.net/
Mzmine 2		software	http://mzmine.github.io/
LC-MS
Q-Exactive Orbitrap	Thermo	-	Equipped with HESI ionization source
1290 UHPLC	Agilent		Equipped with binary pump, autosampler, column compartment
C18 column	Agilent	959757-902	Eclipse Plus C18 RRHD column (2.1 × 100 mm, 1.8 μm)
Solvents
Optima LC-MS grade Methanol	Fisher	A456-4
OptimaLC-MS grade Acetonitrile	Fisher	A955-4
OptimaLC-MS grade Water	Fisher	W6-4
LC-MS grade Formic Acid	Fisher	A11710X1-AMP
Vortex-Genie 2	Scientific Industries	SI-0236
Centrifuge Sorvall Micro 21	Thermo Scientific	75-772-436
Other
Amber HPLC vials 2 mL/caps	Agilent	5182-0716/5182-0717
0.2-μm PTFE syringe filters	Pall Corp.	4521
Whatman 47mm GF/A glass microfiber filters	Sigma-Aldrich	WHA1820047
Media
MA media (pH 8.6) ( quantity / L)			Watanabe, M. F. & Oishi, S. Effects of environmental factors on toxicity of a cyanobacterium (Microcystis aeruginosa) under culture conditions. Applied and Environmental microbiology. 49 (5), 1342-1344 (1985).
Ca(NO3)·4H2O, 50 mg	Sigma-Aldrich	C2786
KNO3, 100 mg	Sigma-Aldrich	P8291
NaNO3, 50 mg	Sigma-Aldrich	S5022
Na2SO4, 40 mg	Sigma-Aldrich	S5640
MgCl2·6H20, 50 mg	Sigma-Aldrich	M2393
Sodium glycerophosphate, 100 mg	Sigma-Aldrich	G9422
H3BO3, 20 mg	Sigma-Aldrich	B6768
Bicine, 500 mg	Sigma-Aldrich	RES1151B-B7
	P(IV) metal solution, 5 mL
Bring the following to 1 L with ddH2O
NaEDTA·2HO	Sigma-Aldrich	E6635
FeCl3 ·6H2O	Sigma-Aldrich	236489
MnCl2·4H2O	Baker	2540
ZnCl2	Sigma-Aldrich	Z0152
CoCl2·6H2O	Sigma-Aldrich	C8661
Na2MoO4·2H2O	Baker	3764
Cyanobacteria BG-11 50X Freshwater Solution	Sigma-Aldrich	C3061-500mL