Dec 17, 2022

Public workspaceNucleoside analysis with liquid chromatography–tandem mass spectrometry (LC–MS/MS) 

DOI
dx.doi.org/10.17504/protocols.io.q26g7yrq1gwz/v1
  • 1Arcadia Science
Arcadia Science
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DOI: dx.doi.org/10.17504/protocols.io.q26g7yrq1gwz/v1
Protocol Citation: Peter Thuy-Boun 2022. Nucleoside analysis with liquid chromatography–tandem mass spectrometry (LC–MS/MS) . protocols.io https://dx.doi.org/10.17504/protocols.io.q26g7yrq1gwz/v1
Manuscript citation:
Borges A, Radkov A, Thuy-Boun PS. (2022). A workflow to isolate phage DNA and identify nucleosides by HPLC and mass spectrometry. https://doi.org/10.57844/arcadia-1ey9-j808
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: September 19, 2022
Last Modified: January 29, 2024
Protocol Integer ID: 70255
Keywords: LC–MS, LC-MS, LS-MS/MS, MS/MS, nucleosides, dna, chemical modification, modification, modified, phage, genome, phages, mass spec
Abstract
This protocol details the detection of modified nucleosides using LC–MS/MS
Chromatography
Chromatography
Perform online separation of nucleoside mixtures using a liquid chromatography (LC) setup paired to a mass spectrometer.
Note
The gradient described here was not optimized. We used this approach to crudely survey the elution profile of our analytes of interest. The injection volume and analyte concentrations were also not optimized and realistically can be reduced several fold in subsequent runs. Nucleosides of interest eluted within the first 5–7 min, providing a reasonable starting point for future gradient optimization.

Prepare 20 µL of nucleoside digest containing approximately 1 µg of nucleoside mixture. Inject 10 µL of digest per run.
Separate nucleosides using a C18 column and binary solvent gradient of HPLC-grade water + 0.1% formic acid (A) and acetonitrile + 0.1% formic acid (B).
Set LC flow rate at 150 µL/min.
Note
We used an Agilent 1100 quaternary LC system.

Create a chromatography method using the following 30 min gradient as a guide:

  • 0–0.5% B over 2 min
  • 0.5–30% B over 4 min
  • 30–95% B over 0.5 min
  • Hold at 95% B for 4 min
  • 95–0.5% B over 0.5 min
  • Hold at 0.5% B over 19 min
Note
This gradient has not been optimized.


Enable column heater at a constant 45 °C.
Mass spectrometry
Mass spectrometry
Acquire data using a mass spectrometer capable of MS/MS experiments (we used a Thermo LTQ Orbitrap XL outfitted with an API source, below are recommended settings).

Note
These experiments can also be run on qToF-type instruments to yield similar high-resolution data but parameters will need to be adjusted accordingly. These experiments can also be run on triple quadrupole and ion trap instruments — however, doing so will yield low-resolution data.

Acquire data in positive mode with lock-mass enabled (targets: 391.284290, 413.266230).
Adjust MS1 scan settings to target ions in the 200–800 m/z range at 100,000 resolution selecting for charge states +1 and +2 for MS/MS.
Follow each MS1 scan with 7 data-dependent MS2 scans collected also at 100,000 resolution. Set ion isolation window at 4 m/z.
Activate ions by CID at NCE of 35% with a minimum signal threshold of 3e4.
Enable dynamic exclusion with a maximum repeat count of three times within 30 s with an exclusion duration of 30 s.
Data processing
Data processing
Convert Thermo .raw files obtained after tandem mass spectrometry analysis to .mgf format using MSConvert 3.0.22031 (a component of the Proteowizard open source mass spectrometry bioinformatics software package) under generic default presets for .mgf file extraction.
Analyte identification
Analyte identification
Use the Jupyter notebook linked below to identify candidate nucleosides based on .mgf files extracted during the previous step.
Note
We manually inspected mass spectrometry data and noticed a consistent pattern of −116 m/z differences between probable nucleoside precursor ions and their most prominent fragmentation product ions, suggesting a pattern of deoxyribose neutral mass loss during fragmentation. Based on this pattern, we wrote Python scripts in the following Jupyter notebooks to automate nucleoside identification within our accurate mass high resolution dataset.

Our GitHub repository with "nucleoside finder" script is available here: https://github.com/Arcadia-Science/nucleoside-finder/tree/v1.0