Structure annotation of full-scan MS data for LC-MS and imaging MS

Full-scan MS data from both LC-MS and imaging MS capture multiple ion forms, including their in/post-source fragments. Here we leverage such fragments to structurally annotate full-scan data from LC-MS or imaging MS by matching against MS/MS spectral libraries.

ms1_id is a Python package that annotates full-scan MS data using tandem MS libraries, specifically:

• annotate pseudo MS/MS spectra: mgf files
• annotate LC-MS data: mzML or mzXML files
• annotate imaging MS data: imzML files
• build indexed MS/MS libraries from mgf or msp files (see Flash entropy for more details)

Workflow

Example annotations

Installation

pip install ms1_id

Python 3.9+ is required. It has been tested on macOS (14.6, M2 Max) and Linux (Ubuntu 20.04).

Usage

Note: Indexed libraries are needed for the workflow. You can download the indexed GNPS library here.

# For LC-MS data
wget https://github.com/Philipbear/ms1_id/releases/latest/download/gnps.zip
unzip gnps.zip -d db

# For MS imaging data (fragments with mz < 100 are removed, as they are not usually included in MS imaging data)
wget https://github.com/Philipbear/ms1_id/releases/latest/download/gnps_minmz100.zip
unzip gnps_minmz100.zip -d db

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Annotate pseudo MS/MS spectra

If you have pseudo MS/MS spectra in mgf format, you can directly annotate them:

ms1_id annotate --input_file pseudo_msms.mgf --libs db/gnps.pkl db/gnps_k10.pkl --min_score 0.7 --min_matched_peak 3

Here, two indexed libraries are searched against, and the result tsv files will be saved in the same directory as the input file.

For more options, run:

ms1_id annotate --help

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Annotate LC-MS data

To annotate LC-MS data, here is an example command:

ms1_id lcms --project_dir lc_ms --sample_dir data --ms1_id_libs db/gnps.pkl db/gnps_k10.pkl --ms2_id_lib db/gnps.pkl

Here, lc_ms is the project directory. Raw mzML or mzXML files are stored in the lc_ms/data folder. Both MS1 and MS/MS annotations will be performed. For MS1 annotation, both gnps.pkl and gnps_k10.pkl libraries are used. For MS/MS annotation, the gnps.pkl library is used. Results can be accessed from aligned_feature_table.tsv.

For more options, run:

ms1_id lcms --help

Expected runtime is ~5-7 min for a single LC-MS file. If it takes longer than 10 min, please increase the --mass_detect_int_tol parameter (default: 2e5 for Orbitraps, 5e2 for QTOFs).

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Annotate MS imaging data

To annotate MS imaging data, here is an example command:

ms1_id msi --input_dir msi --libs db/gnps_minmz100.pkl db/gnps_minmz100_k10.pkl --n_cores 12

Here, msi is the input directory consisting of the imzML and ibd files. All the imzML files in the directory will be annotated individually. Two libraries are used simultaneously, and 12 cores will be used for parallel processing. Annotation results can be accessed from ms1_id_annotations_derep.tsv

For more options, run:

ms1_id msi --help

Expected runtime is ~3-20 min for a single MS imaging dataset if at least 12 cores are available.

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Build indexed MS/MS libraries

To build your own indexed library, run:

ms1_id index --ms2db library.msp --peak_scale_k 10 --peak_intensity_power 0.5

For more options, run:

ms1_id index --help

Demo

We provide a demo script to prepare the environment, download libraries, download LC-MS data and run the annotation workflow.

bash run.sh

Citation

Shipei Xing, Vincent Charron-Lamoureux, Måns Ekelöf, Yasin El Abiead, Huaxu Yu, Oliver Fiehn, Theodore Alexandrov, Pieter C. Dorrestein. Structural annotation of full-scan MS data: A unified solution for LC-MS and MS imaging analyses. bioRxiv 2024.

Data

Data type	Dataset	Link	Instrument
LC-MS	Pooled chemical standards	MSV000095789	Q Exactive
LC-MS	NIST human feces	MSV000095787	Q Exactive
LC-MS	IBD dataset	PR000639	Q Exactive
LC-MS	Mouse feces (lipidomics)	MSV000095868	Q-TOF
LC-MS	Komagataella phaffii (yeast)	MSV000090053	Q Exactive
LC-MS	Bacterial isolates	MSV000085024	Q Exactive
LC-MS	Odontotaenius disjunctus microbe isolates	MSV000090030	Q Exactive
LC-MS	Environmental fungal strains	MSV000090000	Q Exactive
LC-MS	Sea water DOM	MSV000094338	Q Exactive
LC-MS	Foam DOM	MSV000083888	Q Exactive
LC-MS	Ocean DOM	MSV000083632	Q Exactive
LC-MS	Plant extracts	MSV000090975	Q Exactive
LC-MS	32 plant species	MSV000090968	Q Exactive
Imaging MS	Mouse liver with spotted standards	METASPACE	MALDI-Orbitrap
Imaging MS	Mouse brain	MTBLS313	MALDI-FTICR
Imaging MS	Mouse body	METASPACE	MALDI-FTICR
Imaging MS	Human hepatocytes	METASPACE project	MALDI-Orbitrap
Imaging MS	HeLa_NIH3T3	METASPACE project	MALDI-Orbitrap
Imaging MS	Populus trichocarpa root	METASPACE	MALDI-timsTOF
Imaging MS	Human liver tissue	METASPACE	MALDI-TOF
Imaging MS	Human kidney	METASPACE	MALDI-timsTOF
Imaging MS	Mouse kidney	METASPACE	MALDI-FTICR
Imaging MS	Mouse brain (TOF)	METASPACE	MALDI-TOF

License

This project is licensed under the Apache 2.0 License (Copyright 2024 Shipei Xing).