An enabling capability for proteomics would be the ability to study protein expression on a global scale. While several different separation and analysis options are being investigated to advance the practice of proteomics, mass spectrometry (MS) is rapidly becoming the core instrumental technology used to characterize the large number of proteins that constitute a proteome. To be most effective, proteomic measurements must be high-throughput, ideally allowing thousands of proteins to be identified on a time scale of hours. Most strategies of identification by MS rely on the analysis of enzymatically produced peptides originating from an isolated protein followed by either peptide mapping or tandem MS (MS/MS) to obtain sequence information for a single peptide. In the case of peptide mapping, several peptide masses are needed to unambiguously identify a protein with the typically achieved mass measurement accuracies (MMA). The ability to identify proteins based on the mass of a single peptide (i.e., an accurate mass tag; AMT) is proposed and is largely dependent on the MMA that can be achieved. To determine the MMA necessary to enable the use of AMTs for proteome-wide protein identification, we analyzed the predicted proteins and their tryptic fragments from Saccharomyces cerevisiae and Caenorhabditis elegans. The results show that low ppm (i.e., approximately 1 ppm) level measurements have practical utility for analysis of small proteomes. Additionally, up to 85% of the peptides predicted from these organisms can function as AMTs at sub-ppm MMA levels attainable using Fourier transform ion cyclotron resonance MS. Additional information, such as sequence constraints, should enable even more complex proteomes to be studied at more modest mass measurement accuracies. Once AMTs are established, subsequent high-throughput measurements of proteomes (e.g., after perturbations) will be greatly facilitated.
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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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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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