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Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors
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| Zeitschriftentitel: | Scientific Data |
|---|---|
| Personen und Körperschaften: | , , , , , |
| In: | Scientific Data, 6, 2019, 1 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Springer Science and Business Media LLC
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| Schlagwörter: |
| author_facet |
Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. |
|---|---|
| author |
Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. |
| spellingShingle |
Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. Scientific Data Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability |
| author_sort |
dwivedi, pankaj |
| spelling |
Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. 2052-4463 Springer Science and Business Media LLC Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability http://dx.doi.org/10.1038/s41597-019-0015-8 <jats:title>Abstract</jats:title><jats:p>Granulocyte colony stimulating factor receptor (G-CSFR) plays an important role in the production of neutrophil granulocytes. Mutated G-CSFRs have been directly associated with two distinct malignant phenotypes in patients, e.g. acute myeloid leukemia (AML) and chronic neutrophilic leukemia (CNL). However, the signaling mechanism of the mutated G-CSFRs is not well understood. Here, we present a comprehensive SILAC-based quantitative phosphoserine and phosphothreonine dataset of the normal and mutated G-CSFRs signaling using the BaF3 cell-line-based <jats:italic>in vitro</jats:italic> model system. High pH reversed phase concatenation and Titanium Dioxide Spin Tip column were utilized to increase the dynamic range and detection of the phosphoproteome of G-CSFRs. The dataset was further analyzed using several computational tools to validate the quality of the dataset. Overall, this dataset is the first global phosphoproteomics analysis of both normal and disease-associated-mutant G-CSFRs. We anticipate that this dataset will have a strong potential to decipher the phospho-signaling differences between the normal and malignant G-CSFR biology with therapeutic implications. The phosphoproteomic dataset is available via the PRIDE partner repository.</jats:p> Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors Scientific Data |
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Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_unstemmed |
Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_full |
Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_fullStr |
Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_full_unstemmed |
Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_short |
Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_sort |
phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| topic |
Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability |
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http://dx.doi.org/10.1038/s41597-019-0015-8 |
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2019 |
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|
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<jats:title>Abstract</jats:title><jats:p>Granulocyte colony stimulating factor receptor (G-CSFR) plays an important role in the production of neutrophil granulocytes. Mutated G-CSFRs have been directly associated with two distinct malignant phenotypes in patients, e.g. acute myeloid leukemia (AML) and chronic neutrophilic leukemia (CNL). However, the signaling mechanism of the mutated G-CSFRs is not well understood. Here, we present a comprehensive SILAC-based quantitative phosphoserine and phosphothreonine dataset of the normal and mutated G-CSFRs signaling using the BaF3 cell-line-based <jats:italic>in vitro</jats:italic> model system. High pH reversed phase concatenation and Titanium Dioxide Spin Tip column were utilized to increase the dynamic range and detection of the phosphoproteome of G-CSFRs. The dataset was further analyzed using several computational tools to validate the quality of the dataset. Overall, this dataset is the first global phosphoproteomics analysis of both normal and disease-associated-mutant G-CSFRs. We anticipate that this dataset will have a strong potential to decipher the phospho-signaling differences between the normal and malignant G-CSFR biology with therapeutic implications. The phosphoproteomic dataset is available via the PRIDE partner repository.</jats:p> |
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| author | Dwivedi, Pankaj, Muench, David E., Wagner, Michael, Azam, Mohammad, Grimes, H. Leighton, Greis, Kenneth D. |
| author_facet | Dwivedi, Pankaj, Muench, David E., Wagner, Michael, Azam, Mohammad, Grimes, H. Leighton, Greis, Kenneth D., Dwivedi, Pankaj, Muench, David E., Wagner, Michael, Azam, Mohammad, Grimes, H. Leighton, Greis, Kenneth D. |
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| description | <jats:title>Abstract</jats:title><jats:p>Granulocyte colony stimulating factor receptor (G-CSFR) plays an important role in the production of neutrophil granulocytes. Mutated G-CSFRs have been directly associated with two distinct malignant phenotypes in patients, e.g. acute myeloid leukemia (AML) and chronic neutrophilic leukemia (CNL). However, the signaling mechanism of the mutated G-CSFRs is not well understood. Here, we present a comprehensive SILAC-based quantitative phosphoserine and phosphothreonine dataset of the normal and mutated G-CSFRs signaling using the BaF3 cell-line-based <jats:italic>in vitro</jats:italic> model system. High pH reversed phase concatenation and Titanium Dioxide Spin Tip column were utilized to increase the dynamic range and detection of the phosphoproteome of G-CSFRs. The dataset was further analyzed using several computational tools to validate the quality of the dataset. Overall, this dataset is the first global phosphoproteomics analysis of both normal and disease-associated-mutant G-CSFRs. We anticipate that this dataset will have a strong potential to decipher the phospho-signaling differences between the normal and malignant G-CSFR biology with therapeutic implications. The phosphoproteomic dataset is available via the PRIDE partner repository.</jats:p> |
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| spelling | Dwivedi, Pankaj Muench, David E. Wagner, Michael Azam, Mohammad Grimes, H. Leighton Greis, Kenneth D. 2052-4463 Springer Science and Business Media LLC Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability http://dx.doi.org/10.1038/s41597-019-0015-8 <jats:title>Abstract</jats:title><jats:p>Granulocyte colony stimulating factor receptor (G-CSFR) plays an important role in the production of neutrophil granulocytes. Mutated G-CSFRs have been directly associated with two distinct malignant phenotypes in patients, e.g. acute myeloid leukemia (AML) and chronic neutrophilic leukemia (CNL). However, the signaling mechanism of the mutated G-CSFRs is not well understood. Here, we present a comprehensive SILAC-based quantitative phosphoserine and phosphothreonine dataset of the normal and mutated G-CSFRs signaling using the BaF3 cell-line-based <jats:italic>in vitro</jats:italic> model system. High pH reversed phase concatenation and Titanium Dioxide Spin Tip column were utilized to increase the dynamic range and detection of the phosphoproteome of G-CSFRs. The dataset was further analyzed using several computational tools to validate the quality of the dataset. Overall, this dataset is the first global phosphoproteomics analysis of both normal and disease-associated-mutant G-CSFRs. We anticipate that this dataset will have a strong potential to decipher the phospho-signaling differences between the normal and malignant G-CSFR biology with therapeutic implications. The phosphoproteomic dataset is available via the PRIDE partner repository.</jats:p> Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors Scientific Data |
| spellingShingle | Dwivedi, Pankaj, Muench, David E., Wagner, Michael, Azam, Mohammad, Grimes, H. Leighton, Greis, Kenneth D., Scientific Data, Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors, Library and Information Sciences, Statistics, Probability and Uncertainty, Computer Science Applications, Education, Information Systems, Statistics and Probability |
| title | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_full | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_fullStr | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_full_unstemmed | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_short | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_sort | phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| title_unstemmed | Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors |
| topic | Library and Information Sciences, Statistics, Probability and Uncertainty, Computer Science Applications, Education, Information Systems, Statistics and Probability |
| url | http://dx.doi.org/10.1038/s41597-019-0015-8 |