We present an approach for an autonomous system that detects a particular state of interest in a living cell and can govern cell fate accordingly. Cell states could be better identified by the expression pattern of several genes than of a single one. Therefore, autonomous identification can be achieved by a system that measures the expression of these several genes and integrates their activities into a single output. We have constructed a system that diagnoses a unique state in yeast, in which two independent pathways, methionine anabolism and galactose catabolism, are active. Our design is based on modifications of the yeast two-hybrid system. We show that cells could autonomously report on their state, identify the state of interest, and inhibit their growth accordingly. The system's sensitivity is adjustable to detect states with limited dynamic range of inputs. The system's output depends only on the activity of input pathways, not on their identity; hence it is straightforward to diagnose any pair of inputs. A simple model is presented that accounts for the data and provides predictive power. We propose that such systems could handle real-life states-of-interest such as identification of aberrant versus normal growth.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Increase the total number of rows showing on this page by using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details about experiment type and any other genes involved in the interaction.
Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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