ReDU: a framework to find and reanalyze public mass spectrometry data

Alan K Jarmusch^#^{1

2}, Mingxun Wang^#^{1

2}, Christine M Aceves^#^{1

2}, Rohit S Advani^{1

2}, Shaden Aguirre^{1

2}, Alexander A Aksenov^{1

2}, Gajender Aleti³, Allegra T Aron^{1

2}, Anelize Bauermeister^{1

4}, Sanjana Bolleddu^{1

2}, Amina Bouslimani^{1

2}, Andres Mauricio Caraballo Rodriguez^{1

2}, Rama Chaar^{1

2}, Roxana Coras⁵, Emmanuel O Elijah^{1

2}, Madeleine Ernst^{1

2

6}, Julia M Gauglitz^{1

2}, Emily C Gentry^{1

2}, Makhai Husband^{1

2}, Scott A Jarmusch⁷, Kenneth L Jones 2nd^{1

2}, Zdenek Kamenik⁸, Audrey Le Gouellec⁹, Aileen Lu^{1

2}, Laura-Isobel McCall¹⁰, Kerry L McPhail¹¹, Michael J Meehan^{1

2}, Alexey V Melnik^{1

2}, Riya C Menezes¹², Yessica Alejandra Montoya Giraldo¹³, Ngoc Hung Nguyen^{1

2}, Louis Felix Nothias^{1

2}, Mélissa Nothias-Esposito^{1

2}, Morgan Panitchpakdi^{1

2}, Daniel Petras^{1

2

14}, Robert A Quinn¹⁵, Nicole Sikora^{1

2}, Justin J J van der Hooft^{1

16}, Fernando Vargas^{1

2

17}, Alison Vrbanac¹⁸, Kelly C Weldon^{1

2

19}, Rob Knight^{18

19

20

21}, Nuno Bandeira^{2

19

20}, Pieter C Dorrestein^{22

23

24

25}

Affiliations

¹ Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA.
² Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
³ Department of Psychiatry, Stein Clinical Research, University of California, San Diego, La Jolla, CA, USA.
⁴ Institute of Biomedical Sciences, Universidade de São Paulo, São Paulo, Brazil.
⁵ Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
⁶ Center for Newborn Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark.
⁷ Marine Biodiscovery Centre, Department of Chemistry, University of Aberdeen, Old Aberdeen, UK.
⁸ Institute of Microbiology, Czech Academy of Sciences, Videnska, Czech Republic.
⁹ TIMC-IMAG, Univ. Grenoble Alpes, CNRS, Grenoble INP, CHU Grenoble Alpes, Grenoble, France.
¹⁰ Department of Chemistry and Biochemistry, Department of Microbiology and Plant Biology, and Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA.
¹¹ Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA.
¹² Research Group Mass Spectrometry, Max Planck Institute for Chemical Ecology, Jena, Germany.
¹³ Grupo de Investigación en Ciencias Biológicas y Bioprocesos (CIBIOP), Department of Biological Sciences, Universidad EAFIT, Medellín, Colombia.
¹⁴ Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA.
¹⁵ Department of Biochemistry and Molecular Biology, Michigan State University, Lansing, MI, USA.
¹⁶ Bioinformatics Group, Wageningen University, Wageningen, the Netherlands.
¹⁷ Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
¹⁸ Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
¹⁹ Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA.
²⁰ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
²¹ Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
²² Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²³ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²⁴ Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²⁵ Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.

^# Contributed equally.

PMID: 32807955
PMCID: PMC7968862
DOI: 10.1038/s41592-020-0916-7

ReDU: a framework to find and reanalyze public mass spectrometry data

Alan K Jarmusch et al. Nat Methods. 2020 Sep.

. 2020 Sep;17(9):901-904.

doi: 10.1038/s41592-020-0916-7. Epub 2020 Aug 17.

Authors

Affiliations

¹ Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA.
² Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
³ Department of Psychiatry, Stein Clinical Research, University of California, San Diego, La Jolla, CA, USA.
⁴ Institute of Biomedical Sciences, Universidade de São Paulo, São Paulo, Brazil.
⁵ Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
⁶ Center for Newborn Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark.
⁷ Marine Biodiscovery Centre, Department of Chemistry, University of Aberdeen, Old Aberdeen, UK.
⁸ Institute of Microbiology, Czech Academy of Sciences, Videnska, Czech Republic.
⁹ TIMC-IMAG, Univ. Grenoble Alpes, CNRS, Grenoble INP, CHU Grenoble Alpes, Grenoble, France.
¹⁰ Department of Chemistry and Biochemistry, Department of Microbiology and Plant Biology, and Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA.
¹¹ Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA.
¹² Research Group Mass Spectrometry, Max Planck Institute for Chemical Ecology, Jena, Germany.
¹³ Grupo de Investigación en Ciencias Biológicas y Bioprocesos (CIBIOP), Department of Biological Sciences, Universidad EAFIT, Medellín, Colombia.
¹⁴ Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA.
¹⁵ Department of Biochemistry and Molecular Biology, Michigan State University, Lansing, MI, USA.
¹⁶ Bioinformatics Group, Wageningen University, Wageningen, the Netherlands.
¹⁷ Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
¹⁸ Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
¹⁹ Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA.
²⁰ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
²¹ Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
²² Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²³ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²⁴ Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.
²⁵ Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA. pdorrestein@health.ucsd.edu.

^# Contributed equally.

PMID: 32807955
PMCID: PMC7968862
DOI: 10.1038/s41592-020-0916-7

Abstract

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

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Figures

**Extended Data Fig. 1. Repository-scale molecular cartography enabled by ReDU.**
ReDU samples with latitude and longitude information, n = 34,003, were grouped by latitude and longitude (n = 2068 different locations) and plotted colored by number of annotations per file (log10 scaled).

**Extended Data Fig. 2. Comparison of bacterial cultures using Group Comparator in ReDU.**
Bacterial cultures of 1280|Staphylococcus aureus (n = 49), 1423|Bacillus subtilis (n = 89), and 1883|Streptomyces (n = 7) were compared and chemical differences are illustrated by pyroGlu-Ile, staurosporine, and surfactin-C14.

**Extended Data Fig 3. Repository-scale molecular networking of human blood (n = 711), fecal (n = 5,097), and urine (n = 307) supplemented by MolNetEnhancer.**
(a) MolNetEnhancer enhanced molecular network in which components are colored based on Classyfire chemical class prediction. (b) Number of nodes per Classyfire chemical class prediction. Nodes without a match in Classyfire are not displayed.

**Extended Data Fig 4. Molecular cartography of the distribution of drugs on the human body visualized using ili.**
Descaladinose azithromycin, a drug metabolite of azithromycin, distribution in human (n = 17,117; normalized by the number of files per sample).

**Fig 1.. ReDU Framework and Illustrative Public ReDU Data Analyses.**
(a) ReDU provides users the tools to find public data in the GNPS/MassIVE knowledgebase, explore public data analyses in ReDU, and enable repository-scale co- and re-analyses in GNPS. Contributors are provided a template for sample information and a drag-and-drop validator. (b) 2D Emperor plot displaying the projection of human plasma samples (orange) from rheumatoid arthritis patients (not included in ReDU) onto all files (points) in ReDU colored by UBERON ontology (NCBI taxonomy-based opacity used: projected data, 1.0; 9606|Homo sapiens, 0.7; and all other data, 0.25). (c) Illustrative results from Chemical Explorer for 12-ketodeoxycholic acid, cholic acid, and rosuvastatin annotated in human fecal (n = 5,097) files over different life stages. (d) Group comparator performed on human blood (n = 711), fecal (n = 5,097), and urine (n = 307) samples resulted in different chemical compositions as illustrated by bilirubin, urobilin, and stercobilin.

**Fig 2.. Repository-scale Molecular Networking of Public Data in ReDU.**
(a) Molecular network of human blood (n = 711), fecal (n = 5,097), and urine (n = 307) in ReDU with nodes colored by annotation status, annotated (red) or unannotated (grey). (b) Summary of MS/MS library matching results (level 2 or 3) are displayed for the nodes in the network and all MS/MS spectra considered in the molecular network. (c) A portion of the repository-scale molecular networking containing clindamycin. Nodes are colored by the sample type. Node size reflects the number of MassIVE datasets. Node shape annotation status (annotated, diamond or unannotated, circle). Putatively annotated clindamycin analogs (**2–9**), based on MS/MS interpretation, are indicated using dashed arrows and numbers, blue, corresponding to the proposed structures.

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References

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ReDU: a framework to find and reanalyze public mass spectrometry data

Affiliations

ReDU: a framework to find and reanalyze public mass spectrometry data

Authors

Affiliations

Abstract

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources