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by claude@2026-07, 2026-07-16
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The study investigated how pyruvate carboxylase (PC) influences metabolite profiles and endometriosis-related progression using human endometriosis stromal cells (IhESCs) exposed to PC knockdown versus a control, analyzed with quasi-targeted metabolomics using methanol extraction followed by LC–MS/MS on a QTRAP 6500+ and bioinformatics in R/MetaboAnalyst (PCA, differential metabolite analysis, and KEGG pathway mapping). PC knockdown altered cellular metabolite signatures in pathways linked to glycolysis, and the paper reports that PC promotes glycolysis and progression of endometriosis by activating the AKT pathway. A stated limitation is that the approach centers on metabolomics and associated pathway analyses, with only three biological replicates reported. This paper is centrally about endometriosis — it specifically links PC-driven glycolysis and AKT pathway activation to endometriosis progression.
Abstract
Quasi-targeted metabolomics was employed to investigate the effects of PC knockdown (si#1) on cellular metabolite profiles, with experimental analysis performed by Novogene. The workflow consisted of four main phases: sample collection, metabolite extraction, mass spectrometry analysis, and bioinformatics processing. IhESCs in NC or siPC group were digested and counted. A total of 5×10⁵ cells were transferred into a centrifuge tube, centrifuged, and washed once with pre-chilled PBS. After another round of centrifugation, 300μL of 80% aqueous methanol solution was added, followed by quick-freezing in liquid nitrogen for 5 minutes. The mixture was thawed on ice, vortexed for 30s, and sonicated for 6 minutes. Subsequently, it was centrifuged at 5000rpm and 4℃ for 1 minute. The supernatant was collected into a new centrifuge tube, lyophilized to a dry powder, and then reconstituted in 300μL of 10% aqueous methanol solution. Metabolite detection was conducted using the SCIEX QTRAP® 6500+ mass spectrometer in multiple reaction monitoring mode, supported by Novogene's proprietary metabolomics database (novoDB). Quantification was based on Q3 (product ion) signals, while qualitative analysis integrated three-dimensional identification: 1) retention time alignment, 2) Q1/Q3 (precursor/product ion) pair matching, and 3) verification through MS/MS spectral library comparison. Three biological replicates were performed, and quality control (QC) samples were prepared by equal-volume mixing of all experimental samples. Data normalization was conducted using the total peak area normalization method. R software and MetaboAnalyst were utilized for bioinformatics analysis of metabolomics data, including principal component analysis (PCA), differential metabolite analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
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Pyruvate carboxylase promotes glycolysis and progression of endometriosis by activating the AKT pathway
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Description
Quasi-targeted metabolomics was employed to investigate the effects of PC knockdown (si#1) on cellular metabolite profiles, with experimental analysis performed by Novogene. The workflow consisted of four main phases: sample collection, metabolite extraction, mass spectrometry analysis, and bioinformatics processing. IhESCs in NC or siPC group were digested and counted. A total of 5×10⁵ cells were transferred into a centrifuge tube, centrifuged, and washed once with pre-chilled PBS. After another round of centrifugation, 300μL of 80% aqueous methanol solution was added, followed by quick-freezing in liquid nitrogen for 5 minutes. The mixture was thawed on ice, vortexed for 30s, and sonicated for 6 minutes. Subsequently, it was centrifuged at 5000rpm and 4℃ for 1 minute. The supernatant was collected into a new centrifuge tube, lyophilized to a dry powder, and then reconstituted in 300μL of 10% aqueous methanol solution.
Metabolite detection was conducted using the SCIEX QTRAP® 6500+ mass spectrometer in multiple reaction monitoring mode, supported by Novogene's proprietary metabolomics database (novoDB). Quantification was based on Q3 (product ion) signals, while qualitative analysis integrated three-dimensional identification: 1) retention time alignment, 2) Q1/Q3 (precursor/product ion) pair matching, and 3) verification through MS/MS spectral library comparison. Three biological replicates were performed, and quality control (QC) samples were prepared by equal-volume mixing of all experimental samples. Data normalization was conducted using the total peak area normalization method. R software and MetaboAnalyst were utilized for bioinformatics analysis of metabolomics data, including principal component analysis (PCA), differential metabolite analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
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