Dataset Information

Live Electrophoresis-Correlative AI Democratizes Single-cell Mass Spectrometry Proteomics

ABSTRACT: The goal of this project was to deepen proteome coverage on broadly accessible mass spectrometers. We developed electrophoresis-correlative (Eco) ion sorting mass spectrometry (MS) on a decade-old quadrupole orbitrap mass spectrometer (Q Exactive Plus, Thermo). Artificial intelligence (AI) was adapted (CHIMERYS, Thermo) to process the chimeric tandem mass spectra . The strategy was tested, configured, and validated on 1 ng to 250 pg of the HeLa proteome digest. Within a 15-min effective separation window, 1,758 proteins were identified cumulatively from single-cell equivalent proteome amounts (~250 pg). As demonstration, Eco-AI was deployed to profile the proteomic state of dorsal and ventral cell lineages in blastula stage (stage 8) Xenopus laevis embryos. 1,524 proteins were identified from n = 16 single cells. The quantitative protein profiles revealed emerging cell heterogeneity during differentiation.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human) Xenopus Laevis (african Clawed Frog)

TISSUE(S): Embryo, Early Embryonic Cell

SUBMITTER: Peter Nemes

LAB HEAD: Peter Nemes

PROVIDER: PXD062702 | Pride | 2025-08-16

REPOSITORIES: Pride

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			Action	DRS
	2023_12_04_BS01_DDAtop20_1ngHeLa_rep1.RAW	Raw
	2023_12_04_BS03_DDAtop20_1ngHeLa_rep2.RAW	Raw
	2023_12_05_BS01_DDAtop20_1ngHeLa_rep3.RAW	Raw
	2023_12_05_BS02_WWA4_1ngHeLa_rep1.RAW	Raw
	2023_12_05_BS03_WWA4_1ngHeLa_rep2.RAW	Raw

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Project description:Background: Sepsis-associated encephalopathy (SAE) is a common and severe complication of sepsis. While several studies have reported the proteomic alteration in plasma, urine, heart, etc. of sepsis, few research focused on the brain tissue. This study aims at discovering the differentially abundant proteins in the brains of septic rats to identify biomarkers of SAE. Methods: The Prague-Dawley rats were randomly divided into sepsis (n = 6) or sham (n = 6) groups, and then the whole brain tissue was dissected at 24 h after surgery for further protein identification by TMT-LC–MS/MS-based proteomics. Ingenuity pathway analysis, Gene ontology knowledgebase, and STRING database are used to explore the biological significance of proteins with altered concentration. Results: Among the total of 3163 proteins identified in the brain tissue, 57 were increased while 38 were decreased in the sepsis group compared to the sham group. Bioinformatic analyses suggest that the differentially abundant proteins are highly related to cellular microtubule metabolism, energy production, nucleic acid metabolism, neurological disease, etc. Additionally, acute phase response signaling was possibly activated and PI3K/AKT signaling was suppressed during sepsis. An interaction network established by IPA revealed that Akt1, Gc-globulin, and ApoA1 were the core proteins. The increase of Gc-globulin and the decrease of Akt1 were confirmed by Western blot. Conclusions: Based on the multifunction of these proteins in several brain diseases, we first propose that Gc-globulin, ApoA1, PI3K/AKT pathway, and acute phase response proteins (hemopexin and cluster of alpha-2-macroglobulin) can potentially be diagnosis biomarkers, therapeutic targets, and prognosis indicators of SAE. These results may provide new insights into the pathologic mechanism of SAE, yet further research is required to explore the functional implications and clinical applications of the differentially abundant proteins in the brains of sepsis group.

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Live Electrophoresis-Correlative AI Democratizes Single-cell Mass Spectrometry Proteomics

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