Detergent-Insoluble Proteome Analysis Revealed Aberrantly Aggregated Proteins in Human Preeclampsia Placentas.
Wanling ZhangXing ChenZiqi YanYang ChenYizhi CuiBingjun ChenChujun HuangWeiwen ZhangXingfeng YinQing-Yu HeFang HeTong WangPublished in: Journal of proteome research (2017)
Preeclampsia (PE) is a placenta disease, featured by hypertension, proteinuria, and other multiorgan dysfunctions, and its etiology is unclear. We and others have shown that intensive endoplasmic reticulum (ER) stress and unfolded protein response (UPR) occur in the PE placenta. In this study, we isolated detergent-insoluble proteins (DIPs) from human placenta tissues, which were enriched with protein aggregates, to characterize the placenta UPR in PE. With data-independent acquisition (DIA) mass spectrometry, we identified 2066 DIPs across all normal (n = 10) and PE (n = 10) placenta samples, among which 110 and 108 DIPs were significantly up- and down-regulated in PE, respectively. Per clustering analysis, differential DIPs could generally distinguish PE from normal placentas. We verified the MS quantitation of endoglin and vimentin by immunoblotting. In addition, we observed that PE placenta tissues have remarkably more endoglin in the cytoplasm. Furthermore, we found that DIPs were evenly distributed across different chromosomes and could be enriched in diversified gene ontology terms, while differential DIPs avoided to distribute on X-chromosome. Significantly up-regulated DIPs in PE were focused on the top functions of lipid metabolism, while 23 of these DIPs could form the top network regulating cellular movement, development, growth, and proliferation. Our results implicate that human PE placentas have disease-relevant differential DIPs, which reflect aberrantly aggregated proteins of placental tissues. The mass spectrometry proteomics data have been deposited to ProteomeXchange consortium with the data set identifier PXD006654, and iProX database (accession number: IPX0000948000).
Keyphrases
- mass spectrometry
- endothelial cells
- liquid chromatography
- gene expression
- electronic health record
- big data
- high performance liquid chromatography
- blood pressure
- pregnant women
- machine learning
- multiple sclerosis
- gas chromatography
- emergency department
- small molecule
- deep learning
- amino acid
- liquid chromatography tandem mass spectrometry
- tandem mass spectrometry
- solid phase extraction
- pregnancy outcomes