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Title: Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

Abstract

Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow that with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modulesmore » of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Furthermore, our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.« less

Authors:
 [1];  [1];  [2];  [3];  [1];  [1];  [1];  [1];  [1];  [4];  [1];  [3];  [1];  [2];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Univ. of Alabama, Birmingham, AL (United States)
  3. Cincinnati Children’s Hospital Medical Center, Cincinnati, OH (United States)
  4. Univ. of Texas, Austin, TX (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
Sponsoring Org.:
USDOE
OSTI Identifier:
1340766
Report Number(s):
PNNL-SA-119185
Journal ID: ISSN 2045-2322; 48632; 453040220
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; Environmental Molecular Sciences Laboratory

Citation Formats

Clair, Geremy, Piehowski, Paul D., Nicola, Teodora, Kitzmiller, Joseph A., Huang, Eric L., Zink, Erika M., Sontag, Ryan L., Orton, Daniel J., Moore, Ronald J., Carson, James P., Smith, Richard D., Whitsett, Jeffrey A., Corley, Richard A., Ambalavanan, Namasivayam, and Ansong, Charles. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples. United States: N. p., 2016. Web. doi:10.1038/srep39223.
Clair, Geremy, Piehowski, Paul D., Nicola, Teodora, Kitzmiller, Joseph A., Huang, Eric L., Zink, Erika M., Sontag, Ryan L., Orton, Daniel J., Moore, Ronald J., Carson, James P., Smith, Richard D., Whitsett, Jeffrey A., Corley, Richard A., Ambalavanan, Namasivayam, & Ansong, Charles. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples. United States. doi:10.1038/srep39223.
Clair, Geremy, Piehowski, Paul D., Nicola, Teodora, Kitzmiller, Joseph A., Huang, Eric L., Zink, Erika M., Sontag, Ryan L., Orton, Daniel J., Moore, Ronald J., Carson, James P., Smith, Richard D., Whitsett, Jeffrey A., Corley, Richard A., Ambalavanan, Namasivayam, and Ansong, Charles. Thu . "Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples". United States. doi:10.1038/srep39223. https://www.osti.gov/servlets/purl/1340766.
@article{osti_1340766,
title = {Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples},
author = {Clair, Geremy and Piehowski, Paul D. and Nicola, Teodora and Kitzmiller, Joseph A. and Huang, Eric L. and Zink, Erika M. and Sontag, Ryan L. and Orton, Daniel J. and Moore, Ronald J. and Carson, James P. and Smith, Richard D. and Whitsett, Jeffrey A. and Corley, Richard A. and Ambalavanan, Namasivayam and Ansong, Charles},
abstractNote = {Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow that with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Furthermore, our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.},
doi = {10.1038/srep39223},
journal = {Scientific Reports},
number = ,
volume = 6,
place = {United States},
year = {Thu Dec 22 00:00:00 EST 2016},
month = {Thu Dec 22 00:00:00 EST 2016}
}

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Works referenced in this record:

Chemically Etched Open Tubular and Monolithic Emitters for Nanoelectrospray Ionization Mass Spectrometry
journal, November 2006

  • Kelly, Ryan T.; Page, Jason S.; Luo, Quanzhou
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