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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Endothelial cell heterogeneity in pathological angiogenesis characterized by metabolic transcriptome diversity

ABSTRACT: Endothelial cell (EC) metabolism regulates angiogenesis and is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV). In contrast to tumor ECs (TECs), CNV-ECs cannot be isolated for unbiased metabolic target discovery. Here we used scRNA-sequencing to profile 28,337 choroidal ECs (CECs) from mice to in silico distinguish healthy CECs from CNV-ECs. Trajectory inference suggested that CNV-ECs plastically upregulate genes in central carbon metabolism and collagen biosynthesis during differentiation from quiescent postcapillary venous ECs. CEC-tailored genome scale metabolic modeling predicted essentiality of SQLE and ALDH18A1 for proliferation and collagen production, respectively. Comparative analysis in TECs revealed more outspoken metabolic transcriptome heterogeneity in subtypes and consistent upregulation of SQLE and ALDH18A1 across tumor types. Inhibition of SQLE and ALDH18A1 reduced sprouting angiogenesis in vitro. These findings demonstrate the potential of integrated scRNA-seq analysis to identify angiogenic metabolic targets in disease ECs.

INSTRUMENT(S): Illumina HiSeq 4000

ORGANISM(S): Mus musculus

SUBMITTER: Shawez Khan

PROVIDER: E-MTAB-8119 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Endothelial cell heterogeneity in pathological angiogenesis characterized by metabolic transcriptome diversity

Project description:Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcrip-tomes. Here, by scRNA-sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference of CNV-ECs revealed that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. EC phenotypes displayed metabolic transcriptome heterogeneity. Hypothesizing that conserved genes are more important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome scale metabolic modeling, and gene expression me-ta-analysis in multiple cross-species datasets, followed by functional validation, to identify the top-ranking metabolic targets SQLE and ALDH18A1, involved in EC proliferation and collagen production, respectively, as novel angiogenic targets.

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Endothelial metabolic transcriptome plasticity in pathological angiogenesis

Project description:Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcriptomes. Here, by scRNA-sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference of CNV-ECs revealed that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. EC phenotypes displayed metabolic transcriptome heterogeneity. Hypothesizing that conserved genes are more important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome scale metabolic modeling, and gene expression meta-analysis in multiple cross-species datasets, followed by functional validation, to identify the top-ranking metabolic targets SQLE and ALDH18A1, involved in EC proliferation and collagen production, respectively, as novel angiogenic targets. The effect of SQLE and ALDH18A1 silencing in ECs was investigated by transcriptomics and proteomics analysis.

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