Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise

Nature ◽  
2006 ◽  
Vol 441 (7095) ◽  
pp. 840-846 ◽  
Author(s):  
John R. S. Newman ◽  
Sina Ghaemmaghami ◽  
Jan Ihmels ◽  
David K. Breslow ◽  
Matthew Noble ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
Biological Noise

scholarly journals IMMU-68. SINGLE-CELL PROTEOMIC ANALYSIS OF IMMUNE CELL RESPONSE TO CHECKPOINT BLOCKADE USING 30-PARAMETER FLOW CYTOMETRY

2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi137-vi137
Author(s):  
Amber Giles ◽  
Leonard Nettey ◽  
Thomas Liechti ◽  
Margaret Beddall ◽  
Elizabeth Vera ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Cell Response ◽  
Proteomic Analysis ◽  
Immune Cell ◽  
Checkpoint Blockade ◽  
Immune Cell Response

Abstract PR03: Single-cell proteomic analysis of the tumoral heterogeneity in response to PARP inhibitor

2020 ◽  
Author(s):  
Nicholas D. Kendsersky ◽  
Hongli Ma ◽  
Yong Fang ◽  
Lydia G. Campbell ◽  
Jenny Eng ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
Parp Inhibitor

scholarly journals Optimized Data-Independent Acquisition Approach for Proteomic Analysis at Single-Cell Level

2021 ◽  
Author(s):  
Yuefan Wang ◽  
Tung-Shing Mamie Lih ◽  
Lijun Chen ◽  
Yuanwei Xu ◽  
Morgan D. Kuczler ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
Single Cell Analysis ◽  
Cancer Cell Line ◽  
Cellular Heterogeneity ◽  
Single Cell Level ◽  
Cell Level ◽  
Data Independent Acquisition ◽  
Peptide Precursors ◽  
Proteomic Study

Abstract Background: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. Methods: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. Results: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1,500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. Conclusions: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

CHAPTER 5. Microfluidic Applications in Single-cell Genomic, Transcriptomic and Proteomic Analysis

2020 ◽  
pp. 122-146
Author(s):  
Dalia Dhingra ◽  
Aik Ooi ◽  
Pedro Mendez ◽  
Shu Wang ◽  
Saurabh Gulati ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis

AML-354: High-Dimensional Single-Cell Proteomic Analysis Reveals Therapeutic Vulnerabilities in Patients with Relapsed/Refractory AML

2020 ◽  
Vol 20 ◽  
pp. S206-S207
Author(s):  
Muharrem Muftuoglu ◽  
Zoe Alaniz ◽  
Duncan Mak ◽  
Angelique Lin ◽  
Jared Burks ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
High Dimensional ◽  
Refractory Aml

scholarly journals Functional Role of Second Heart Field-derived Smooth Muscle Cells in Thoracic Aortopathies in Mice

2020 ◽  
Author(s):  
Hisashi Sawada ◽  
Hideyuki Higashi ◽  
Chen Zhang ◽  
Yanming Li ◽  
Yuriko Katsumata ◽  
...  
Keyword(s):  
Smooth Muscle ◽  
Angiotensin Ii ◽  
Smooth Muscle Cells ◽  
Neural Crest ◽  
Single Cell ◽  
Proteomic Analysis ◽  
Ascending Aorta ◽  
Second Heart Field ◽  
Heart Field

AbstractBackgroundThe ascending aorta is a common location for thoracic aortopathies. Pathology predominates in the aortic media with disease severity being most apparent in outer laminar layers. In the ascending aorta, smooth muscle cells (SMCs) are derived from two embryonic origins: cardiac neural crest and second heart field (SHF). SMCs of these origins have distinct distributions, and the localization of SHF coincides with the regional specificity in some forms of thoracic aortopathies. However, the role of SHF-derived SMCs in maintaining the structural and functional integrity of the ascending aorta remains unclear.MethodsMass spectrometry assisted proteomic and single cell transcriptomic analyses were performed in mouse aortas to discriminate molecular features of SHF-derived SMCs in maintaining the aortic homeostasis. Genetic deletion of low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-β receptor 2 (Tgfbr2) in SHF-derived SMCs was conducted to examine impact of SHF-derived SMCs on the development of thoracic aortopathies.ResultsProteomic analysis did not detect differences in protein profiles between ascending (disease prone) and descending (disease resistant) thoracic aortas in saline-infused mice. However, angiotensin II infusion altered these profiles in a region-specific manner. Angiotensin II evoked differential expression of multiple LRP1 ligands. Histological analysis demonstrated that angiotensin II-induced medial disruptions were detected mainly in outer laminar layers derived from the SHF. Single cell RNA sequencing using normal mouse aortas revealed lower abundance of elastin mRNA in SHF-derived SMCs compared to SMCs from the cardiac neural crest. In addition, Lrp1 and Tgfbr2 mRNA were abundant in SHF-derived SMCs. To examine biological effects of SHF-derived cells, Lrp1 or Tgfbr2 was deleted in SHF-derived cells in mice. SHF-specific Lrp1 deletion augmented angiotensin II-induced aortic aneurysm and rupture in the ascending region. Proteomic analysis discerned regulation of protein abundances related to TGF-β signaling pathways by Lrp1 deletion in SHF-derived cells. Deletion of Tgfbr2, a key regulator of TGF-β signaling, in SHF-derived cells led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage in mice.ConclusionThese results demonstrate that SMCs derived from the SHF play a critical role in the integrity of the ascending aortic wall.

scholarly journals Single-cell proteomic analysis

2020 ◽  
pp. e1503 ◽  
Author(s):  
Thai Pham ◽  
Ankush Tyagi ◽  
Yu-Sheng Wang ◽  
Jia Guo
Keyword(s):  
Single Cell ◽  
Proteomic Analysis

scholarly journals Optimized Data-Independent Acquisition Approach for Proteomic Analysis at Single-Cell Level

2021 ◽  
Author(s):  
Yuefan Wang ◽  
Tung-Shing Mamie Lih ◽  
Lijun Chen ◽  
Yuanwei Xu ◽  
Morgan D Kuczler ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
Single Cell Analysis ◽  
Cancer Cell Line ◽  
Cellular Heterogeneity ◽  
Single Cell Level ◽  
Cell Level ◽  
Data Independent Acquisition ◽  
Peptide Precursors ◽  
Proteomic Study

Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. Herein, we report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1,500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. Our results demonstrates that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

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