Mass Spectrometry for Metabolomics

EMSL leverages its cross-disciplinary expertise and unique suite of state-of-the-art and advanced mass spectrometry platforms to perform a full range of metabolomics studies, such as conventional targeted and untargeted metabolomics and lipidomics. This includes volatile compounds and soil and dissolved organic matter, as well as advanced measurements, such as mass spectrometry imaging and ultra-high resolution mass spectrometry based on Fourier transform ion cyclotron resonance (FTICR). Users of EMSL’s facilities receive support from experts in all stages of the analysis pipeline: from sample preparation to data analysis, including the one-pot biomolecule extraction method, MPLEx.

Research Application

Identification and quantification of metabolites and lipids are critical for understanding biological and environmental systems. EMSL’s mass spectrometry-based metabolomics capabilities provide high-quality data due to unique technical advances, including high mass resolution and increased sensitivity. The resulting metabolomics and lipidomics data provide key components for success across the three research integrated systems below.

• Supporting the Biomolecular Pathways Integrated Research Platform, high-quality metabolomics and lipidomics data help researchers understand biomolecular changes at the cellular level based on an organism’s genetic potential. The data are integrated with other omics data to be collectively interpreted for entire metabolic pathways and used to validate existing or develop new computational metabolic models. Metabolic flux measurements—measuring isotope incorporation into metabolites—provides additional critical information to understand how metabolic pathways temporally respond to changes in external and internal environments.
• Supporting the Cell Signaling and Communication Integrated Research Platform, these resources provide information on metabolite and lipid levels between cells as they interact across heterogenous tissues and communities. They can be single cells or multi-cellular systems of natural and synthetic origin, including plant, fungal, algal, bacterial, archaeal, viral, and mammalian. Example studies include species-resolved characterization of biological functions, behavior driven by inter-cellular signaling, and communication through metabolite exchange.
• Supporting the Rhizosphere Function Integrated Research Platform, metabolomics and lipidomics analyses contribute to deciphering complicated interacting systems in nature, especially plant-microbe interactions in the rhizosphere, to reveal molecular mechanisms. Metabolites and lipids are key components to isolate the major regulators of biomass productivity in bioenergy crops (including grasses and trees), to identify systems biology approaches for enhanced spatiotemporal understanding of crop responses to abiotic stresses (drought, heat, salinity, elevated CO₂), and to develop bioenergy crops with improved biomass productivity and enhanced water and nutrient use efficiency.

Available Instruments

Users who want to focus on a limited number of analytes can take a targeted metabolomics approach. This is a hypothesis-driven approach to address specific scientific questions. EMSL researchers are well equipped to answer these questions using various instrumentation and methods, including a suite of nine triple-quadrupole mass spectrometers used for extremely sensitive and specific assays to quantify specific molecules of interest or in metabolic flux measurements. Those who desire to perform a comprehensive analysis of their sample, including measurement of both known and unknown metabolites and lipids, can use an untargeted metabolomics or lipidomics approach. Gas chromatography-mass spectrometry instrumentation provides untargeted measurements of volatile, semi-volatile molecules, fatty acids and chemically derivatized metabolites.

Twenty-four instruments are available to comprehensively measure metabolites and lipids with no intended bias. These include:

• Three gas chromatography-mass spectrometry instruments
• Sixteen diverse Orbitrap instruments (including hybrid quadrupole-Orbitrap and Tribrid)
• Three ion mobility quadrupole-time of flight mass spectrometry instruments
• Four FTICR-mass spectrometry instruments, including a 21 Tesla FTICR (one of two in the world).

Our mass spectrometers can be coupled with various liquid or gas chromatography systems for separations of complex mixtures or for direct analysis without separation. 

Proper identification of unknown metabolites is challenging. To face this challenge, EMSL collaborates with Pacific Northwest National Laboratory (PNNL) researchers who are creating a variety of tools for standards-free identification of small molecules in complex systems. As only a small percentage of molecules are available as pure standards, PNNL scientists built—leveraging EMSL’s computational chemistry NWChem software and EMSL’s mid-range computing infrastructure—comprehensive metabolite reference libraries.

The tools include:

• ISiCLE workflow, a quantum chemistry-based tool that provides in silico calculations or predictions
• DarkChem, an artificial intelligence/machine learning-based tool
• DEIMoS, a data extraction tool for multidimensional spectrometry
• MAME, a chemical property matching software.

These tools can be used to identify unknown metabolites based on multiple experimental data types, including liquid chromatography coupled with ion mobility spectrometry and tandem mass spectrometry where retention times, collision cross sections, accurate masses, isotopic distributions, and tandem mass spectra are measured. Metabolites are identified by comparing experimental data with the appropriate in-silico library without the need for a reference standard. Three ion mobility quadrupole-time-of-flight mass spectrometers are available to EMSL users, along dedicated preprocessing software actively developed and maintained at PNNL.

Contributing Teams and Resources 

EMSL develops and deploys capabilities for the user program by conducting original research independently or in partnership with others and by adapting/advancing science and technologies developed outside of EMSL. In some instances, EMSL directly deploys mature capabilities developed by others where there is value for the EMSL user community. The following grants/activities, PI’s and teams contributed to the development of this capability: 

Agile BioFoundry

• Kristin Burnum-Johnson, Young-Mo Kim, Nathalie Munoz, Yuqian Gao, Aivett Bilbao. Agile BioFoundry, a national lab consortium for biomanufacturing; DOE EERE BETO award: DE-NL0030038.

MPLEx

• Tom Metz, BER Genome Science Program (GSP);  GSP-funded PNNL Foundational Scientific Focus Area; NIH NIAID grant U19AI106772; and NIH NIDDK grant DP3 DK094343

ISiCLE, DarkChem, DEIMoS, MAME

• Tom Metz, Justin Teeguarden, Ryan Renslow, BER Genomics Science Program-funded PNNL Metabolic and Spatial Interactions in Communities Scientific Focus Area; PNNL LDRD Global Forensic Chemical Exposure Assessment for the Environmental Exposome project, Biomedical Resilience & Readiness in Adverse Operating Environments Agile project, and the Microbiomes in Transition Initiative; NIH NIEHS grant U2CES030170; NCI grant R03CA222443; EPA (Interagency Agreement DW-089–92452001-0 in support of DOE Project No. 68955A)

Related Publications

Agile BioFoundry

• Bilbao A, Munoz N, Kim J, Orton DJ, Gao Y, Poorey K, Pomraning KR, Weitz K, Burnet M, Nicora CD, Wilton R, Deng S, Dai Z, Oksen E, Gee A, Fasani RA, Tsalenko A, Tanjore D, Gardner J, Smith RD, Michener JK, Gladden JM, Baker ES, Petzold CJ, Kim YM, Apffel A, Magnuson JK, Burnum-Johnson KE. 2023. “PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements” Nat Commun. 28;14(1):2461. doi: 10.1038/s41467-023-37031-9.
• Ling C, Peabody GL, Salvachúa D, Kim YM, Kneucker CM, Calvey CH, Monninger MA, Munoz NM, Poirier BC, Ramirez KJ, St John PC, Woodworth SP, Magnuson JK, Burnum-Johnson KE, Guss AM, Johnson CW, Beckham GT. 2022. “Muconic acid production from glucose and xylose in Pseudomonas putida via evolution and metabolic engineering”. Nat Commun. 2022 Aug 22;13(1):4925. doi: 10.1038/s41467-022-32296-y.

MPLEx

Nakayasu ES, Nicora CD, Sims AC, Burnum-Johnson KE, Kim YM, Kyle JE, Matzke MM, Shukla AK, Chu RK, Schepmoes AA, Jacobs JM, Baric RS, Webb-Robertson BJ, Smith RD, Metz TO.  2016. "MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses." mSystems. 1(3):e00043-16. doi: 10.1128/mSystems.00043-16

ISiCLE, DarkChem, DEIMoS, MAME

• Colby SM, Thomas DG, Nuñez JR, Baxter DJ, Glaesemann KR, Brown JM, Pirrung MA, Govind N, Teeguarden JG, Metz TO, Renslow RS. 2019. "ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries". Anal Chem. 91(7):4346-4356. doi: 10.1021/acs.analchem.8b04567
• Colby SM, Nuñez JR, Hodas NO, Corley CD, Renslow RR. 2020. "Deep Learning to Generate in Silico Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples". Anal Chem. 92(2):1720-1729. doi: 10.1021/acs.analchem.9b02348
• Nuñez JR, Colby SM, Thomas DG, Tfaily MM, Tolic N, Ulrich EM, Sobus JR, Metz TO, Teeguarden JG, Renslow RS. 2019. "Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples." J Chem Inf Model. 59 (9):4052-4060. doi: 10.1021/acs.jcim.9b00444
• Colby SM, Chang CH, Bade JL, Nunez JR, Blumer MR, Orton DJ, Bloodsworth KJ, Nakayasu ES, Smith RD, Ibrahim YM, Renslow RS, Metz TO. 2022. "DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data." Anal Chem. 94(16):6130-6138. doi: 10.1021/acs.analchem.1c05017