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Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

ABSTRACT: Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

SUBMITTER: Bittremieux W

PROVIDER: S-EPMC10733301 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

Bittremieux Wout W Avalon Nicole E NE Thomas Sydney P SP Kakhkhorov Sarvar A SA Aksenov Alexander A AA Gomes Paulo Wender P PWP Aceves Christine M CM Caraballo-Rodríguez Andrés Mauricio AM Gauglitz Julia M JM Gerwick William H WH Huan Tao T Jarmusch Alan K AK Kaddurah-Daouk Rima F RF Kang Kyo Bin KB Kim Hyun Woo HW Kondić Todor T Mannochio-Russo Helena H Meehan Michael J MJ Melnik Alexey V AV Nothias Louis-Felix LF O'Donovan Claire C Panitchpakdi Morgan M Petras Daniel D Schmid Robin R Schymanski Emma L EL van der Hooft Justin J J JJJ Weldon Kelly C KC Yang Heejung H Xing Shipei S Zemlin Jasmine J Wang Mingxun M Dorrestein Pieter C PC

Nature communications 20231220 1

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this libr ...[more]

PMID: 38123557

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Project description:IntroductionThe Metabolomics Workbench Data Repository is a public repository of mass spectrometry and nuclear magnetic resonance data and metadata derived from a wide variety of metabolomics studies. The data and metadata for each study is deposited, stored, and accessed via files in the domain-specific 'mwTab' flat file format.ObjectivesIn order to improve the accessibility, reusability, and interoperability of the data and metadata stored in 'mwTab' formatted files, we implemented a Python library and package. This Python package, named 'mwtab', is a parser for the domain-specific 'mwTab' flat file format, which provides facilities for reading, accessing, and writing 'mwTab' formatted files. Furthermore, the package provides facilities to validate both the format and required metadata elements of a given 'mwTab' formatted file.MethodsIn order to develop the 'mwtab' package we used the official 'mwTab' format specification. We used Git version control along with Python unit-testing framework as well as continuous integration service to run those tests on multiple versions of Python. Package documentation was developed using sphinx documentation generator.ResultsThe 'mwtab' package provides both Python programmatic library interfaces and command-line interfaces for reading, writing, and validating 'mwTab' formatted files. Data and associated metadata are stored within Python dictionary- and list-based data structures, enabling straightforward, 'pythonic' access and manipulation of data and metadata. Also, the package provides facilities to convert 'mwTab' files into a JSON formatted equivalent, enabling easy reusability of the data by all modern programming languages that implement JSON parsers. The 'mwtab' package implements its metadata validation functionality based on a pre-defined JSON schema that can be easily specialized for specific types of metabolomics studies. The library also provides a command-line interface for interconversion between 'mwTab' and JSONized formats in raw text and a variety of compressed binary file formats.ConclusionsThe 'mwtab' package is an easy-to-use Python package that provides FAIRer utilization of the Metabolomics Workbench Data Repository. The source code is freely available on GitHub and via the Python Package Index. Documentation includes a 'User Guide', 'Tutorial', and 'API Reference'. The GitHub repository also provides 'mwtab' package unit-tests via a continuous integration service.

Dataset Information

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

Publications

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

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