Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes
Abstract
Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a “cells-to-peptides” automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography–mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM–MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.
- Authors:
-
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark); Shenzhen Inst. for Advanced Technologies (China)
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Basque Center for Applied Mathematics (BCAM), Bilbao, Bizkaia (Spain)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office
- OSTI Identifier:
- 1592414
- Alternate Identifier(s):
- OSTI ID: 1569459
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Proteome Research
- Additional Journal Information:
- Journal Volume: 18; Journal Issue: 10; Journal ID: ISSN 1535-3893
- Publisher:
- American Chemical Society (ACS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; automation; sample preparation; proteomics; bacteria; fungi; microbes; biotechnology; high-throughput
Citation Formats
Chen, Yan, Guenther, Joel M., Gin, Jennifer W., Chan, Leanne Jade G., Costello, Zak, Ogorzalek, Tadeusz L., Tran, Huu M., Blake-Hedges, Jacquelyn M., Keasling, Jay D., Adams, Paul D., García Martín, Héctor, Hillson, Nathan J., and Petzold, Christopher J. Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes. United States: N. p., 2019.
Web. doi:10.1021/acs.jproteome.9b00455.
Chen, Yan, Guenther, Joel M., Gin, Jennifer W., Chan, Leanne Jade G., Costello, Zak, Ogorzalek, Tadeusz L., Tran, Huu M., Blake-Hedges, Jacquelyn M., Keasling, Jay D., Adams, Paul D., García Martín, Héctor, Hillson, Nathan J., & Petzold, Christopher J. Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes. United States. https://doi.org/10.1021/acs.jproteome.9b00455
Chen, Yan, Guenther, Joel M., Gin, Jennifer W., Chan, Leanne Jade G., Costello, Zak, Ogorzalek, Tadeusz L., Tran, Huu M., Blake-Hedges, Jacquelyn M., Keasling, Jay D., Adams, Paul D., García Martín, Héctor, Hillson, Nathan J., and Petzold, Christopher J. Thu .
"Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes". United States. https://doi.org/10.1021/acs.jproteome.9b00455. https://www.osti.gov/servlets/purl/1592414.
@article{osti_1592414,
title = {Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes},
author = {Chen, Yan and Guenther, Joel M. and Gin, Jennifer W. and Chan, Leanne Jade G. and Costello, Zak and Ogorzalek, Tadeusz L. and Tran, Huu M. and Blake-Hedges, Jacquelyn M. and Keasling, Jay D. and Adams, Paul D. and García Martín, Héctor and Hillson, Nathan J. and Petzold, Christopher J.},
abstractNote = {Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a “cells-to-peptides” automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography–mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM–MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.},
doi = {10.1021/acs.jproteome.9b00455},
journal = {Journal of Proteome Research},
number = 10,
volume = 18,
place = {United States},
year = {Thu Aug 22 00:00:00 EDT 2019},
month = {Thu Aug 22 00:00:00 EDT 2019}
}
Web of Science
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