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Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity

Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of prot...

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Autores principales: Senavirathna, Lakmini, Ma, Cheng, Chen, Ru, Pan, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368228/
https://www.ncbi.nlm.nih.gov/pubmed/35954294
http://dx.doi.org/10.3390/cells11152450
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author Senavirathna, Lakmini
Ma, Cheng
Chen, Ru
Pan, Sheng
author_facet Senavirathna, Lakmini
Ma, Cheng
Chen, Ru
Pan, Sheng
author_sort Senavirathna, Lakmini
collection PubMed
description Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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spelling pubmed-93682282022-08-12 Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity Senavirathna, Lakmini Ma, Cheng Chen, Ru Pan, Sheng Cells Article Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications. MDPI 2022-08-07 /pmc/articles/PMC9368228/ /pubmed/35954294 http://dx.doi.org/10.3390/cells11152450 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Senavirathna, Lakmini
Ma, Cheng
Chen, Ru
Pan, Sheng
Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title_full Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title_fullStr Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title_full_unstemmed Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title_short Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity
title_sort spectral library-based single-cell proteomics resolves cellular heterogeneity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368228/
https://www.ncbi.nlm.nih.gov/pubmed/35954294
http://dx.doi.org/10.3390/cells11152450
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