Inferring secretory and metabolic pathway activity from omic data with secCellFie
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ABSTRACT:
PROVIDER: PRJNA1043633 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26901289_1.fastq.gz | Fastqsanger.gz | |||
| SRR26901289_2.fastq.gz | Fastqsanger.gz | |||
| SRR26901290_1.fastq.gz | Fastqsanger.gz | |||
| SRR26901290_2.fastq.gz | Fastqsanger.gz | |||
| SRR26901291_1.fastq.gz | Fastqsanger.gz |
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Project description:Understanding protein secretion has considerable importance in the biotechnology industry and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer protein secretion capabilities from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can be used to predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.
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Project description:Understanding protein secretion has considerable importance in the biotechnology industry and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer protein secretion capabilities from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can be used to predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.
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Project description:Abstract: Secretion occurs in all cells, with relatively low levels in most cells and extremely high levels in specialized secretory cells, such as those of the pancreas, salivary and mammary glands. Here, we report that the CrebA/Creb3-like family of bZip transcription factors functions to upregulate expression of both the general protein machinery required in all cells for secretion and of cell-type specific secreted proteins. Drosophila CrebA directly binds the enhancers of secretory pathway genes and is both necessary and sufficient to activate expression of every secretory pathway component gene examined thus far. Microarray profiling reveals that CrebA also upregulates expression of genes encoding cell type specific secreted components. Finally, we find that the human CrebA orthologues, Creb3L1 and Creb3L2, have the ability to upregulate the secretory pathway in non-secretory cell types. Goals: Creb3L1 is the closest related human orthologue of Drosophila CrebA. CrebA is required to upregulate genes encoding the protein machinery and cargo in specialized secretory cells. To determine if the human orthologues of CrebA, Creb3L1 and Creb3L2, perform the same function, we expressed the truncated active form of Creb3L1 in non-secretory HeLa cells. We then performed microarray experiments and found that active Creb3L1 is sufficient to upregulate genes encoding the protein machinery of the secretory pathway, as observed with Drosophila CrebA.
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