Proteomics

Dataset Information

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Multiplexed single cell proteomics of hypoxia in HEK293 expressing PIP-FUCCI


ABSTRACT: This study aimed to characterize temporal proteome dynamics of hypoxia using single-cell mass spectrometry-based proteomics. HEK293 cells expressing PIP-FUCCI cell cycle markers were grown in suspension culture. Cells were exposed to hypoxia and temporally sampled for single-cell sorting into 384-well plates. Samples were processed and multiplexed using TMT labeling according to the SCoPE2 workflow and analyzed using the RETICLE acquisition method. In parallel, single-cell RNA-seq data were also collected. These datasets were used together to disentangle the effects of hypoxia from cell cycle progression and to construct joint transcriptional and translational trajectories along the hypoxia response.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Craig Barry  

LAB HEAD: Craig Barry

PROVIDER: PXD053053 | Pride | 2026-02-16

REPOSITORIES: Pride

Dataset's files

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Action DRS
20220924_T4_001.raw Raw
20220924_T4_002.raw Raw
20220924_T4_003.raw Raw
20220924_T4_004.raw Raw
20220924_T4_005.raw Raw
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Publications

Resolving Single-Cell Gene Expression by Pseudotemporal Integration of Transcriptomic and Proteomic Datasets.

Barry Craig P CP   Talbo Gert H GH   Beauglehole Aiden A   Ovchinnikov Dmitry D   Munro Trent T   Mahler Stephen S   Baker Kym K   Nielsen Lars K LK   Mercer Tim R TR   Marcellin Esteban E  

Molecular & cellular proteomics : MCP 20251127 1


Single-cell omics technologies, such as single-cell RNA-Seq and single-cell proteomics, offer unprecedented insights into cellular heterogeneity and dynamic regulatory processes. However, integrating these data types to construct comprehensive transcription-translation profiles remains challenging because of their distinct and complex behaviors. This study presents a novel approach using pseudotemporal cell ordering to integrate single-cell RNA-Seq and single-cell proteomics by mass spectrometry  ...[more]

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