SIMILE enables alignment of tandem mass spectra with statistical significance

Daniel G. C. Treen, Mingxun Wang, Shipei Xing, Katherine B. Louie, Tao Huan, Pieter C. Dorrestein, Trent R. Northen and Benjamin P. Bowen ()
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Daniel G. C. Treen: Environmental Genomics and Systems Biology Division & The Joint Genome Institute Lawrence Berkeley National Laboratory
Mingxun Wang: University of California, San Diego
Shipei Xing: University of British Columbia
Katherine B. Louie: Environmental Genomics and Systems Biology Division & The Joint Genome Institute Lawrence Berkeley National Laboratory
Tao Huan: University of British Columbia
Pieter C. Dorrestein: University of California, San Diego
Trent R. Northen: Environmental Genomics and Systems Biology Division & The Joint Genome Institute Lawrence Berkeley National Laboratory
Benjamin P. Bowen: Environmental Genomics and Systems Biology Division & The Joint Genome Institute Lawrence Berkeley National Laboratory

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: Abstract Interrelating small molecules according to their aligned fragmentation spectra is central to tandem mass spectrometry-based untargeted metabolomics. Current alignment algorithms do not provide statistical significance and compounds that have multiple delocalized structural differences and therefore often fail to have their fragment ions aligned. Here we align fragmentation spectra with both statistical significance and allowance for multiple chemical differences using Significant Interrelation of MS/MS Ions via Laplacian Embedding (SIMILE). SIMILE yields spectral alignment inferred structural connections in molecular networks that are not found with cosine-based scoring algorithms. In addition, it is now possible to rank spectral alignments based on p-values in the exploration of structural relationships between compounds and enhance the chemical connectivity that can be obtained with molecular networking.

Date: 2022
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DOI: 10.1038/s41467-022-30118-9

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