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Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics
[Image: see text] The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strat...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996606/ https://www.ncbi.nlm.nih.gov/pubmed/36802514 http://dx.doi.org/10.1021/acs.analchem.2c05022 |
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author | Matzinger, Manuel Müller, Elisabeth Dürnberger, Gerhard Pichler, Peter Mechtler, Karl |
author_facet | Matzinger, Manuel Müller, Elisabeth Dürnberger, Gerhard Pichler, Peter Mechtler, Karl |
author_sort | Matzinger, Manuel |
collection | PubMed |
description | [Image: see text] The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 μL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination. |
format | Online Article Text |
id | pubmed-9996606 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99966062023-03-10 Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics Matzinger, Manuel Müller, Elisabeth Dürnberger, Gerhard Pichler, Peter Mechtler, Karl Anal Chem [Image: see text] The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 μL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination. American Chemical Society 2023-02-20 /pmc/articles/PMC9996606/ /pubmed/36802514 http://dx.doi.org/10.1021/acs.analchem.2c05022 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Matzinger, Manuel Müller, Elisabeth Dürnberger, Gerhard Pichler, Peter Mechtler, Karl Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics |
title | Robust and
Easy-to-Use One-Pot Workflow for Label-Free
Single-Cell Proteomics |
title_full | Robust and
Easy-to-Use One-Pot Workflow for Label-Free
Single-Cell Proteomics |
title_fullStr | Robust and
Easy-to-Use One-Pot Workflow for Label-Free
Single-Cell Proteomics |
title_full_unstemmed | Robust and
Easy-to-Use One-Pot Workflow for Label-Free
Single-Cell Proteomics |
title_short | Robust and
Easy-to-Use One-Pot Workflow for Label-Free
Single-Cell Proteomics |
title_sort | robust and
easy-to-use one-pot workflow for label-free
single-cell proteomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996606/ https://www.ncbi.nlm.nih.gov/pubmed/36802514 http://dx.doi.org/10.1021/acs.analchem.2c05022 |
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