2021
DOI: 10.1038/s41467-021-27110-0
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Author Correction: High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip

Abstract: In this article the author name Chia-Feng Tsai was incorrectly written as Chai-Feng Tsai.The grant number U01 HL148860 relating to NIH grants for Joshua N. Adkins and Geremy C. Clair was omitted. The original article has been corrected.

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Cited by 11 publications
(10 citation statements)
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“…In contrast to the label-free analysis, the TMT-based boosting strategy can increase not only sample throughput (up to 18 channels) 48 but also detection sensitivity with the use of the carrier proteome in the boosting channel for significantly improved MS1 signal. This boosting strategy has recently been demonstrated for effective single-cell proteomics analysis 1 , 15 , 17 . It has also been applied to study low abundant PTMs such as phosphotyrosine peptides 19 or secreted glycoproteins 49 .…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In contrast to the label-free analysis, the TMT-based boosting strategy can increase not only sample throughput (up to 18 channels) 48 but also detection sensitivity with the use of the carrier proteome in the boosting channel for significantly improved MS1 signal. This boosting strategy has recently been demonstrated for effective single-cell proteomics analysis 1 , 15 , 17 . It has also been applied to study low abundant PTMs such as phosphotyrosine peptides 19 or secreted glycoproteins 49 .…”
Section: Discussionmentioning
confidence: 99%
“…Sensitive and nanoscale phosphoproteomic methods have the potential to make such cell type-specific applications more feasible in clinical settings, and also enable more precise phenotypic analysis of cell (sub)types in a time-and/or dose-dependent fashion. Indeed, mass spectrometry (MS)-based single-cell proteomics has recently made significant advancements in detection sensitivity and high-throughput measurements [1][2][3][4] . A remaining technical challenge for nanoscale proteomics is the comprehensive quantitative profiling of post-translational modifications (PTMs), particularly protein phosphorylation states 5 , key indicators for signaling pathways and network activations essential for many physiological functions 6,7 .…”
mentioning
confidence: 99%
“… 11 , 12 , 15 The performance of NanoPOTS has improved over time in terms of versatility, sensitivity, and reproducibility by combining a nested nano-well chip with a cellenONE commercial liquid dispensing instrument. 15 The cellenONE system has also been used in proteoCHIP-based single-cell proteomics. 16 In this method, the sample solution—in the nanoliter range—is covered with hexadecane to prevent evaporation.…”
Section: Introductionmentioning
confidence: 99%
“…The nanoPOTS method uses a specially fabricated nano-well chip and a liquid handling system for digestion. These devices were designed to process the sample in a small volume to reduce protein and peptide adsorption loss. ,, The performance of NanoPOTS has improved over time in terms of versatility, sensitivity, and reproducibility by combining a nested nano-well chip with a cellenONE commercial liquid dispensing instrument . The cellenONE system has also been used in proteoCHIP-based single-cell proteomics .…”
Section: Introductionmentioning
confidence: 99%
“…Sensitive and nanoscale phosphoproteomic methods have the potential to make such cell type-specific applications more feasible in clinical settings, and also enable more precise phenotypic analysis of cell (sub)types in a time-and/or dose-dependent fashion. Indeed, mass spectrometry (MS)-based single-cell proteomics has recently made significant advancements in detection sensitivity and highthroughput measurements [1][2][3][4] . A remaining technical challenge for nanoscale proteomics is the comprehensive quantitative profiling of post-translational modifications (PTMs), particularly protein phosphorylation states 5 , key indicators for signaling pathways and network activations essential for many physiological functions 6,7 .…”
Section: Introductionmentioning
confidence: 99%