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Annotator: postprocessing software for generating function-based signatures from quantitative mass spectrometry

Sylvester, JE;Bray, TS;Kron, SJ;
Product: LPS from Escherichia coli O111:B4

Mass spectrometry is used to investigate global changes in protein abundance in cell lysates. Increasingly powerful methods of data collection have emerged over the past decade, but this has left researchers with the task of sifting through mountains of data for biologically significant results. Often, the end result is a list of proteins with no obvious quantitative relationships to define the larger context of changes in cell behavior. Researchers are often forced to perform a manual analysis from this list or to fall back on a range of disparate tools, which can hinder the communication of results and their reproducibility. To address these methodological problems, we developed Annotator, an application that filters validated mass spectrometry data and applies a battery of standardized heuristic and statistical tests to determine significance. To address systems-level interpretations, we incorporated UniProt and Gene Ontology keywords as statistical units of analysis, yielding quantitative information about changes in abundance for an entire functional category. This provides a consistent and quantitative method for formulating conclusions about cellular behavior, independent of network models or standard enrichment analyses. Annotator allows for bottom-up annotations that are based on experimental data and not inferred by comparison to external or hypothetical models. Annotator was developed as an independent postprocessing platform that runs on all common operating systems, thereby providing a useful tool for establishing the inherently dynamic nature of functional annotations, which depend on results from ongoing proteomic experiments. Annotator is available for download at http://people.cs.uchicago.edu/∼tyler/annotator/annotator_desktop_0.1.tar.gz .

PubMed ID: 22224429
230623062017-06-052017-06-0511:03:0111:03:012018-03-082018-03-0816:32:1716:32:17Sylvester, JE;Bray, TS;Kron, SJ;Sylvester, JE;Bray, TS;Kron, SJ;20122012Annotator: postprocessing software for generating function-based signatures from quantitative mass spectrometryAnnotator: postprocessing software for generating function-based signatures from quantitative mass spectrometryJournal Of Proteome ResearchJournal Of Proteome Research1521-361521-361111332222442922224429

Mass spectrometry is used to investigate global changes in protein abundance in cell lysates. Increasingly powerful methods of data collection have emerged over the past decade, but this has left researchers with the task of sifting through mountains of data for biologically significant results. Often, the end result is a list of proteins with no obvious quantitative relationships to define the larger context of changes in cell behavior. Researchers are often forced to perform a manual analysis from this list or to fall back on a range of disparate tools, which can hinder the communication of results and their reproducibility. To address these methodological problems, we developed Annotator, an application that filters validated mass spectrometry data and applies a battery of standardized heuristic and statistical tests to determine significance. To address systems-level interpretations, we incorporated UniProt and Gene Ontology keywords as statistical units of analysis, yielding quantitative information about changes in abundance for an entire functional category. This provides a consistent and quantitative method for formulating conclusions about cellular behavior, independent of network models or standard enrichment analyses. Annotator allows for bottom-up annotations that are based on experimental data and not inferred by comparison to external or hypothetical models. Annotator was developed as an independent postprocessing platform that runs on all common operating systems, thereby providing a useful tool for establishing the inherently dynamic nature of functional annotations, which depend on results from ongoing proteomic experiments. Annotator is available for download at http://people.cs.uchicago.edu/∼tyler/annotator/annotator_desktop_0.1.tar.gz .

Mass spectrometry is used to investigate global changes in protein abundance in cell lysates. Increasingly powerful methods of data collection have emerged over the past decade, but this has left researchers with the task of sifting through mountains of data for biologically significant results. Often, the end result is a list of proteins with no obvious quantitative relationships to define the larger context of changes in cell behavior. Researchers are often forced to perform a manual analysis from this list or to fall back on a range of disparate tools, which can hinder the communication of results and their reproducibility. To address these methodological problems, we developed Annotator, an application that filters validated mass spectrometry data and applies a battery of standardized heuristic and statistical tests to determine significance. To address systems-level interpretations, we incorporated UniProt and Gene Ontology keywords as statistical units of analysis, yielding quantitative information about changes in abundance for an entire functional category. This provides a consistent and quantitative method for formulating conclusions about cellular behavior, independent of network models or standard enrichment analyses. Annotator allows for bottom-up annotations that are based on experimental data and not inferred by comparison to external or hypothetical models. Annotator was developed as an independent postprocessing platform that runs on all common operating systems, thereby providing a useful tool for establishing the inherently dynamic nature of functional annotations, which depend on results from ongoing proteomic experiments. Annotator is available for download at http://people.cs.uchicago.edu/∼tyler/annotator/annotator_desktop_0.1.tar.gz .

5.0015.001

Sample Preparation:

To provide a source of data that was rich in content for functional annotation, we prepared a complex sample of soluble proteins from neutrophils activated by lipopolysaccharide (LPS). The human promyelocytic HL-60 cell line (ATCC) was differentiated in culture using 1 μM alltrans retinoic acid (Sigma-Aldrich), 6 pM 1α,25-Dihydroxyvitamin D3 (Sigma-Aldrich), and 30 ng/mL granulocyte-colony stimulatory factor (Invitrogen) in Iscove's Modified Dulbecco's medium (Mediatech, Inc.) supplemented with 20% FBS and 4 mM L-glutamine.31 Cells were activated via treatment with 100 ng/mL of lipopolysaccharide (LPS) from E. coli O111:B4 (List Biological Laboratories) for 30 minutes. ...

Sample Preparation:

To provide a source of data that was rich in content for functional annotation, we prepared a complex sample of soluble proteins from neutrophils activated by lipopolysaccharide (LPS). The human promyelocytic HL-60 cell line (ATCC) was differentiated in culture using 1 μM alltrans retinoic acid (Sigma-Aldrich), 6 pM 1α,25-Dihydroxyvitamin D3 (Sigma-Aldrich), and 30 ng/mL granulocyte-colony stimulatory factor (Invitrogen) in Iscove's Modified Dulbecco's medium (Mediatech, Inc.) supplemented with 20% FBS and 4 mM L-glutamine.31 Cells were activated via treatment with 100 ng/mL of lipopolysaccharide (LPS) from E. coli O111:B4 (List Biological Laboratories) for 30 minutes. ...

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3292622/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3292622/2012-03-022012-03-0210.1021/pr200460s10.1021/pr200460sLPS from Escherichia coli O111:B4LPS from Escherichia coli O111:B4skron@uchicago.eduskron@uchicago.edu100;Activated;Analysis;Application;Biological;Cell;Cellular;E. coli;Experimental;Factor;Function;Gene;Lipopolysaccharide;List;List Biological;LPS;Modified;O111:B4;Protein;Quantitative;Tools;Treatment;Journal Of Proteome Research100;Activated;Analysis;Application;Biological;Cell;Cellular;E. coli;Experimental;Factor;Function;Gene;Lipopolysaccharide;List;List Biological;LPS;Modified;O111:B4;Protein;Quantitative;Tools;Treatment;Journal Of Proteome Research201201annotator-postprocessing-software-for-generatingannotator-postprocessing-software-for-generating