MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

Method Abstract

MPLEx Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

Mass Spectrometry Experimental Protocol (SIO:001043) | Standard Operating Procedure (SIO:000964)

The Metabolite, Protein and Lipid Extraction (MPLEx) method protocol is a robust and applicable approach for sample processing covering a breadth of diverse sample types, including cell cultures, microbial communities, and tissues. Integrative multi-omics analyses can empower more effective and complete understandings of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still very challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Herein, PNNL staff have adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements.


Method Name:             MPLEx Mass Spectrometry Experimental Protocol

Method Type:              Experimental Protocol (SIO:001043) > Standard Operating Procedure (SIO:000964)

Data Source Taxon:      Mass SpectrometryLiquid Chromatography-Mass SpectrometryGas Chromatography Mass Spectrometry

Topic Areas:                  OmicsProteomicsLipidomicsMetabolomicsPhenomics


Explore PNNL DataHub projects utilizing data source acquisition methods related to published data from integrated research platforms using high-resolution Mass Spectrometry method technologies. Instrument capabilities are linked to published project datasets, publications, analyses and externally related database resources from a suite of cross-discipline data science domain investigations. For more information about capabilities utilizing this method type, visit EMSL's Omics & Mass Spectrometer (MS) resource pages bulleted below.

Multimedia Resources

Nicora, C. D., Burnum-Johnson, K. E., Nakayasu, E. S., Casey, C. P., White III, R. A., Roy Chowdhury, T., Kyle, J. E., Kim, Y. M., Smith, R. D., Metz, T. O., Jansson, J. K., Baker, E. S. The MPLEx Protocol for Multi-omic Analyses of Soil Samples. J. Vis. Exp. (135), e57343, doi: 10.3791/57343 (2018). url:

Copyright © 2018, Journal of Visualized Experiments (JoVE)


Acknowledgment of Federal Funding

The data described here was funded in whole or in part by the National Institute of Allergy and Infectious Diseases, of the National Institutes of Health under award number U19AI106772, and is a contribution of the "Modeling Host Responses to Understand Severe Human Virus Infections" Project at Pacific Northwest National Laboratory. Data generated by the Omics-LHV Core for proteomics, metabolomics, and lipidomics analyses for were performed at Pacific Northwest National Laboratory in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy’s (DOE) Office, operating under the Battelle Memorial Institute for the DOE under contract number DE-AC05-76RLO1830. 

Cite as: 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. MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses. mSystems. 2016 May 10;1(3):e00043-16. doi: 10.1128/mSystems.00043-16.

Projects (2)

Omics-Lethal Human Virus Computational Modeling & Omics Core Processed Data Collection The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" (U19AI106772) program project was a comprehensive and interactive systems...

  1. Datasets


The Phenotypic Response of the Soil Microbiome to Environmental Perturbations Project (Soil Microbiome) at Pacific Northwest National Laboratory is a Genomic Sciences Program Science Focus Area (SFA) Project operating under the Environmental Microbiome Science Research Area. The Soil Microbiome SFA...

  1. Datasets

Datasets (10)
Publications (2)
People (1)

Lindsey Anderson’s research has been dedicated to the identification and characterization of novel, targeted and non-targeted, functional metabolic interactions using a high-throughput systems biology and computational biology approach. Her expertise in functional metabolism and multidisciplinary...

Data Sources (3)