Lessons learned in label free single cell proteomics on a TIMSTOF SCP system
Ontology highlight
ABSTRACT:
INSTRUMENT(S): timsTOF SCP
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Benjamin C Orsburn
PROVIDER: MSV000095633 | MassIVE | Sat Aug 17 11:46:00 BST 2024
REPOSITORIES: MassIVE
Similar Datasets
Project description:Bulk and single human primary hepatocytes were obtained from a commercial source from a single human donor. Cells were grown according to vendor protocols and treated with DMSO control or acetaminophen at the IC50 dose previously determined by R. Bruderer et al., 2015. Single cells were isolated using a Tecan UNO system using vendor protocols. 400 nanogram of bulk cell lysates from each condition were analyzed using diaPASEF using a TIMSTOF Flex system coupled to an EvoSep One system and using a 44 minute total gradient (30SPD). Single isolated cells were ran with a method with a compable run to run time and diaPASEF method using an EasyNLC 1200 system coupled to a TIMSTOF SCP system. In the case of the latter, cells were separated on a PepSep C-18 75 um column operating at 200 nL/min. Bulk cell lysates were used to create a library in SpectroNaut 18 from which was used for the analysis of all single cells.
2024-04-19 | MSV000094572 | MassIVE
Project description:Major advancements in single-cell proteomics (SCP) methodologies have been introduced in recent years, providig highly sensitive sample preparation methods and mass spectrometric technologies. However, most studies present limited throughput and mainly focus on the analysis of cultured cells. To enhance the depth, accuracy, and throughput of SCP for tumor analysis, we developed an automated, high-throughput pipeline that enables the analysis of 1,536 single cells in a single experiment. This approach integrates low-volume sample preparation, automated sample purification, and LC-MS analysis with the Slice-PASEF method. Integration of these methodologies into a streamlined pipeline led to a robust and reproducible identification of more than 3000 proteins per cell. We applied this pipeline to analyze tumor macrophages in a murine lung metastasis model. We identified over 1,800 proteins per cell, including key macrophage markers and ~500 differentially expressed proteins between tumor and control macrophages. PCA analysis successfully separated these populations, revealing the utility of SCP in capturing biologically relevant signals in the tumor microenvironment. Our results demonstrate a robust and scalable pipeline poised to advance single-cell proteomics in cancer research.
2025-07-09 | PXD058457 | Pride
Project description:Proteomics of human primary blood brain barrier cells and hepatocytes analyzed by diaPASEF as described in HN Wilkins 2024.
2024-05-07 | MSV000094702 | MassIVE
Project description:Single cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables and reagents for sample processing and separations, which limits accessibility of SCP to a small number of specialized laboratories. Commercial platforms have become available for SCP cell isolation and sample preparation, but the high cost of these platforms and the technical expertise required for their operation place them out of reach of many interested laboratories. Here, we assessed the new HP D100 Single Cell Dispenser for label-free SCP. The low-cost instrument proved highly accurate and reproducible for dispensing reagents in the 200 nL to 2 µL range. We used the HP D100 to isolate and prepare single cells for SCP within 384-well PCR plates. When the well plates were immediately centrifuged following cell dispensing and again after reagent dispensing, we found that ~97% of wells that were identified in the instrument software as containing a single cell indeed provided proteome coverage expected of a single cell. The D100 Single Cell Dispenser combined with one-step sample processing provides a very rapid easy-to-use workflow for SCP with no reduction in proteome coverage relative to a nanowell-based workflow. The commercial well plates also facilitate autosampling with commercial instrumentation. Single cell samples were analyzed using home-packed 30-µm-i.d. nanoLC columns as well as commercially available 50-µm-i.d. columns. The commercial columns led to identification of ~35% fewer identified proteins. However, combined with the well plate-based preparation platform the presented workflow provides fully commercial and relatively low cost alternative for SCP sample preparations and separations, which should greatly broaden accessibility of SCP to other laboratories.
2023-10-09 | PXD043355 | Pride
Project description:NCI-H-358 cancer cells were treated with the HDAC inhibitor mocetinostat for 24 hours. Single cells were isolated by FACs and prepared in a single well prior to diaPASEF analysis on a TIMSTOF SCP. A 40cm column was used for all analysis using a 200nL/min active gradient of 180 minutes. Library runs were created by pooling 16 single control and treated cells and running on the same gradient (separately) and processed with SpectroNaut 18.
2024-05-05 | MSV000094678 | MassIVE
Project description:NIST1950 SRM samples analyzed on timsTOF Pro in Parallel-Accumulation Serial Fragmentation (PASEF) mode. Data provided by Bruker's team.
2019-10-01 | MSV000084402 | GNPS
Project description:Even with recent improvements in sample preparation and instrumentation, single-cell proteomics (SCP) analyses mostly measure protein abundances, making the field unidimensional. In this study, we employ a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ~4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Lastly, correlating the abundance of individual proteins from cells displaying a wide range of diameters show that histones and some proteins involved in the cell cycle do not scale with cell size confirming previous observations in yeast. Our study represents the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional post-translational measurements beyond protein abundance. This method not only distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner but also showcase the discovery potential of SCP in fundamental biology.
2025-03-30 | PXD054083 | Pride
Project description:Even with recent improvements in sample preparation and instrumentation, single-cell proteomics (SCP) analyses mostly measure protein abundances, making the field unidimensional. In this study, we employ a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ~4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Lastly, correlating the abundance of individual proteins from cells displaying a wide range of diameters show that histones and some proteins involved in the cell cycle do not scale with cell size confirming previous observations in yeast. Our study represents one of the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional post-translational measurements beyond protein abundance. This method not only distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner but also showcase the discovery potential of SCP in fundamental biology.
2025-03-30 | PXD051942 | Pride
Project description:Single-cell proteomics (SCP) has advanced significantly, yet it remains largely unidimensional, focusing primarily on protein abundances. This limitation hinders our understanding of the dynamic processes occurring within individual cells, particularly protein turnover, which is crucial for cellular function and regulation. In this study, we employed a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ~4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects using protein synthesis and degradation inhibitors on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Lastly, correlating the abundance of individual proteins from cells displaying a wide range of diameters show that histones and some proteins involved in the cell cycle do not scale with cell size confirming previous observations in yeast. Our study represents the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional post-translational measurements beyond protein abundance. This method not only distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner but also showcase the discovery potential of SCP in fundamental biology.
2025-03-28 | PXD058753 | Pride
Project description:The HepG2 cell line is a model for exploring hepatotoxicity, drug metabolism and cell cycle status. Single cells were isolated in this stage of the study using a Tecan UNO system with single stage lysis/digestion in microwell plates. The resulting tryptic digests were analyzed using an EvoSep One system with peptides analyzed using diaPASEF on a TIMSTOF Ultra2 system. Please note that due to the size of this study and challenges in both size and accessioning data from novel mass analyzers, each stage of the study will be accessioned separately. This repository only contains cells analyzed using the default EvoSep 40SPD zoom method and a custom EvoSep 80SPD method where separation occurs on a 10cm x 75um x `1.9um ReproSil column.
2025-05-04 | MSV000097789 | MassIVE