PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Bilbao, Aivett; Munoz, Nathalie; Kim, Joonhoon; Orton, Daniel J.; Gao, Yuqian; Poorey, Kunal; Pomraning, Kyle R.; Weitz, Karl; Burnet, Meagan; Nicora, Carrie D.; Wilton, Rosemarie; Deng, Shuang; Dai, Ziyu; Oksen, Ethan; Gee, Aaron; Fasani, Rick A.; Tsalenko, Anya; Tanjore, Deepti; Gardner, James; Smith, Richard D.; Michener, Joshua K.; Gladden, John M.; Baker, Erin S.; Petzold, Christopher J.; Kim, Young-Mo; Apffel, Alex; Magnuson, Jon K.; Burnum-Johnson, Kristin E.

doi:10.1038/s41467-023-37031-9

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Journal Article · Fri Apr 28 04:00:00 EDT 2023 · Nature Communications

DOI:https://doi.org/10.1038/s41467-023-37031-9· OSTI ID:1973113

^[1]; ^[1]; ^[1]; ^[2]; ^[1]; Poorey, Kunal ^[3]; ^[1]; ^[2]; Burnet, Meagan ^[2]; ^[2]; Wilton, Rosemarie ^[4]; Deng, Shuang ^[1]; Dai, Ziyu ^[1]; ^[5]; Gee, Aaron ^[6]; Fasani, Rick A. ^[6]; Tsalenko, Anya ^[6]; Tanjore, Deepti ^[7]; Gardner, James ^[7]; ^[2] more »

Pacific Northwest National Lab. (PNNL), Richland, WA (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Argonne National Lab. (ANL), Argonne, IL (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Agilent Technologies, Santa Clara, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)
Sandia National Lab. (SNL-CA), Livermore, CA (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)
University of North Carolina, Chapel Hill, NC (United States)

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO); National Institutes of Health (NIH)

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1973113

Alternate ID(s):: OSTI ID: 1994378
OSTI ID: 1996726

Report Number(s):: PNNL-SA-174727

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 14; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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PeakDecoder enables machine learning-1 based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements Yuqian, Gao,; Yuqian, Gao, Panorama Public https://doi.org/10.6069/6j7y-t592	dataset	January 2023
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PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

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