Cognitive analysis of metabolomics data for systems biology

Majumder, Erica L.-W.; Billings, Elizabeth M.; Benton, H. Paul; Martin, Richard L.; Palermo, Amelia; Guijas, Carlos; Rinschen, Markus M.; Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Tagtow, Bradley A.; Plumb, Robert S.; Siuzdak, Gary

doi:10.1038/s41596-020-00455-4

Cognitive analysis of metabolomics data for systems biology

Journal Article · Fri Jan 22 00:00:00 EST 2021 · Nature Protocols

DOI:https://doi.org/10.1038/s41596-020-00455-4· OSTI ID:1774918

^[1]; ^[1]; ^[1]; ^[2]; Palermo, Amelia ^[1]; ^[1]; ^[1]; ^[1]; ^[1]; Tagtow, Bradley A. ^[2]; ^[3]; ^[1]

The Scripps Research Inst., La Jolla, CA (United States). Center for Mass Spectrometry and Metabolomics
IBM Watson Health, Cambridge, MA (United States)
Waters Corp., Milford, MA (United States)

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: National Institutes of Health (NIH); USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1774918

Journal Information:: Nature Protocols, Journal Name: Nature Protocols Journal Issue: 3 Vol. 16; ISSN 1754-2189

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Metabolomics Analysis for Biomarker Discovery: Advances and Challenges Monteiro, M. S.; Carvalho, M.; Bastos, M. L. Current Medicinal Chemistry, Vol. 20, Issue 2 https://doi.org/10.2174/092986713804806621	journal	January 2013
COL4A3 Gene Variants and Diabetic Kidney Disease in MODY Wang, Yiting; Zhang, Junlin; Zhao, Yingwang Clinical Journal of the American Society of Nephrology, Vol. 13, Issue 8 https://doi.org/10.2215/CJN.09100817	journal	July 2018
The Pathogenic Role of the Adaptive Immune Response to Modified LDL in Diabetes Virella, Gabriel; Lopes-Virella, Maria F. Frontiers in Endocrinology, Vol. 3 https://doi.org/10.3389/fendo.2012.00076	journal	January 2012
Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources Eicher, Tara; Kinnebrew, Garrett; Patt, Andrew Metabolites, Vol. 10, Issue 5 https://doi.org/10.3390/metabo10050202	journal	May 2020
Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS Zarate, Erica; Boyle, Veronica; Rupprecht, Udo Metabolites, Vol. 7, Issue 1 https://doi.org/10.3390/metabo7010001	journal	December 2016
Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics Blaženović, Ivana; Kind, Tobias; Ji, Jian Metabolites, Vol. 8, Issue 2 https://doi.org/10.3390/metabo8020031	journal	May 2018
MetaboAnalystR 2.0: From Raw Spectra to Biological Insights Chong, Jasmine; Yamamoto, Mai; Xia, Jianguo Metabolites, Vol. 9, Issue 3 https://doi.org/10.3390/metabo9030057	journal	March 2019
Cleavage of Transaldolase by Granzyme B Causes the Loss of Enzymatic Activity with Retention of Antigenicity for Multiple Sclerosis Patients Niland, Brian; Miklossy, Gabriella; Banki, Katalin The Journal of Immunology, Vol. 184, Issue 7 https://doi.org/10.4049/jimmunol.0804174	journal	March 2010
Human Transaldolase and Cross-Reactive Viral Epitopes Identified by Autoantibodies of Multiple Sclerosis Patients Esposito, Maria; Venkatesh, Vijay; Otvos, Laszlo The Journal of Immunology, Vol. 163, Issue 7 https://doi.org/10.4049/jimmunol.163.7.4027	journal	October 1999
Semantic Scholar Fricke, Suzanne Journal of the Medical Library Association, Vol. 106, Issue 1 https://doi.org/10.5195/JMLA.2018.280	journal	January 2018
SciFinder Gabrielson, Stephen Walter Journal of the Medical Library Association, Vol. 106, Issue 4 https://doi.org/10.5195/JMLA.2018.515	journal	October 2018
Semantic Scholar Fricke, Suzanne Journal of the Medical Library Association, Vol. 106, Issue 1 https://doi.org/10.5195/jmla.2018.280	journal	January 2018
SciFinder Gabrielson, Stephen Walter Journal of the Medical Library Association, Vol. 106, Issue 4 https://doi.org/10.5195/jmla.2018.515	journal	October 2018
Transcriptional profiling and biomarker identification reveal tissue specific effects of expanded ataxin-3 in a spinocerebellar ataxia type 3 mouse model Toonen, Lodewijk; Overzier, Maurice; Evers, Melvin figshare https://doi.org/10.6084/m9.figshare.c.4142210	collection	January 2018
One-year follow-up of B vitamin and Iron status in patients with phenylketonuria provided tetrahydrobiopterin (BH4) Brantley, Kristen; Douglas, Teresa; Singh, Rani Figshare https://doi.org/10.6084/m9.figshare.c.4283867	collection	January 2018

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