Metabolite annotation

Ion Identity Molecular Networking (IIMN)

A strategy extending feature-based molecular networking with MS1-derived ion relationships, linking candidate ion species of the same molecule alongside MS/MS spectral-similarity edges.

Nature Communications · 2021 · 10.1038/s41467-021-23953-9

LC-MSUntargeted metabolomicsMetabolite profilingMetabolite annotation

What does this strategy enable?

Ion Identity Molecular Networking adds a second evidence layer to an FBMN network: relationships between candidate adducts, multimers and other ion species supported by chromatographic behavior and mass differences. MS1 ion-identity edges and MS/MS similarity edges have different meanings and should be interpreted separately. The published GNPS implementation can also collapse ion groups for visualization. These groupings are hypotheses about ion origin, not proof of a molecular structure.

Transferable workflow

Workflow

  1. 1

    Detect and align LC-MS/MS features

    Generate an aligned feature table with representative MS/MS spectra using a compatible preprocessing tool.

  2. 2

    Annotate ion identities

    In a documented ion-identity workflow, group chromatographic features and annotate plausible ion species using retention behavior, peak-shape correlation and expected mass relationships.

  3. 3

    Export FBMN and ion-identity edges

    Export the quantification table, representative MS/MS spectra and supplementary ion-identity pairs with matching feature identifiers. Follow the specific GNPS and preprocessing version documentation.

  4. 4

    Build the ion identity molecular network

    Run FBMN in GNPS with supplementary ion-identity relationships so that MS1 ion relationships and MS/MS spectral-similarity relationships are represented together.

  5. 5

    Inspect compound-level ion groups and molecular families

    Distinguish ion-identity edges from spectral-similarity edges and review collapsed groups against the uncollapsed network. Check ambiguous assignments before propagating annotations.

Connected resources

Tools used in this strategy

Strategy profile

Related objectives

Molecular-family discovery, Unknown identification, Molecular discovery

Components

Preprocessing and feature extraction, Annotation or identification, Molecular networking, Spectral search, Data and workflow sharing

Biological context

Broadly applicable

Ion mobility

Ion mobility not required

Scope and considerations

Designed for

  • LC-MS/MS datasets in which multiple ion species from the same molecule create redundant nodes or obscure molecular-family interpretation.
  • Combining chromatographic ion relationships with fragmentation-spectral relationships.

Important requirements

  • Feature-level chromatographic information, MS/MS spectra, and an ion-identity/supplementary-pairs export from a compatible preprocessing workflow.

Considerations

  • Ion-identity assignments rely on chromatographic correlation and expected mass relationships and should be reviewed, particularly for crowded or poorly resolved chromatographic regions.
  • The original paper also describes MS-DIAL and XCMS with CAMERA export routes. Their version-specific scripts and formats must be checked before substituting them for the MZmine route shown here.
  • Features without MS/MS can participate through ion-identity edges when supported by the implementation; they do not thereby acquire an observed fragmentation spectrum.
  • Ion identity networking is not ion mobility networking and does not require ion mobility acquisition.

Reusable resources

✓ Code available✓ Published method available

Publication

Schmid R, Petras D, Nothias L-F, et al. Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment. Nature Communications 12, 3832 (2021).

doi:10.1038/s41467-021-23953-9

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