Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics
Abstract
Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Matchmore »
- Authors:
-
[2];
[2];
[2];
[2];
[3];
[1];
[1]
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354 United States
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354 United States; Brigham Young Univ., Provo, UT (United States). Dept. of Chemistry and Biochemistry
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Biological and Environmental Research (BER); National Institutes of Health (NIH)
- OSTI Identifier:
- 1673582
- Report Number(s):
- PNNL-SA-152553
Journal ID: ISSN 0003-2700
- Grant/Contract Number:
- AC05-76RL01830; GM103493; U24CA210955
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Analytical Chemistry
- Additional Journal Information:
- Journal Volume: 92; Journal Issue: 15; Journal ID: ISSN 0003-2700
- Publisher:
- American Chemical Society (ACS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; nanoPOTS; proteomics; LC-MS; automation
Citation Formats
Williams, Sarah M., Liyu, Andrey V., Tsai, Chia-Feng, Moore, Ronald J., Orton, Daniel J., Chrisler, William B., Gaffrey, Matthew J., Liu, Tao, Smith, Richard D., Kelly, Ryan T., Pasa-Tolic, Ljiljana, and Zhu, Ying. Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics. United States: N. p., 2020.
Web. doi:10.1021/acs.analchem.0c01551.
Williams, Sarah M., Liyu, Andrey V., Tsai, Chia-Feng, Moore, Ronald J., Orton, Daniel J., Chrisler, William B., Gaffrey, Matthew J., Liu, Tao, Smith, Richard D., Kelly, Ryan T., Pasa-Tolic, Ljiljana, & Zhu, Ying. Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics. United States. https://doi.org/10.1021/acs.analchem.0c01551
Williams, Sarah M., Liyu, Andrey V., Tsai, Chia-Feng, Moore, Ronald J., Orton, Daniel J., Chrisler, William B., Gaffrey, Matthew J., Liu, Tao, Smith, Richard D., Kelly, Ryan T., Pasa-Tolic, Ljiljana, and Zhu, Ying. Wed .
"Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics". United States. https://doi.org/10.1021/acs.analchem.0c01551. https://www.osti.gov/servlets/purl/1673582.
@article{osti_1673582,
title = {Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics},
author = {Williams, Sarah M. and Liyu, Andrey V. and Tsai, Chia-Feng and Moore, Ronald J. and Orton, Daniel J. and Chrisler, William B. and Gaffrey, Matthew J. and Liu, Tao and Smith, Richard D. and Kelly, Ryan T. and Pasa-Tolic, Ljiljana and Zhu, Ying},
abstractNote = {Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.},
doi = {10.1021/acs.analchem.0c01551},
journal = {Analytical Chemistry},
number = 15,
volume = 92,
place = {United States},
year = {Wed Jul 08 00:00:00 EDT 2020},
month = {Wed Jul 08 00:00:00 EDT 2020}
}
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