Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model
Human Proteome Project (HPP) presents a systematic characterization of the protein landscape under different conditions using several complementary-omic techniques (LC-MS/MS proteomics, affinity proteomics, transcriptomics, etc.). In the present study, using a B-cell lymphoma cell line as a model, c...
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| Format: | Article |
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MDPI AG
2021-11-01
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| Series: | Biomolecules |
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| Online Access: | https://www.mdpi.com/2218-273X/11/12/1776 |
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| author | Alicia Landeira-Viñuela Paula Díez Pablo Juanes-Velasco Quentin Lécrevisse Alberto Orfao Javier De Las Rivas Manuel Fuentes |
| author_facet | Alicia Landeira-Viñuela Paula Díez Pablo Juanes-Velasco Quentin Lécrevisse Alberto Orfao Javier De Las Rivas Manuel Fuentes |
| author_sort | Alicia Landeira-Viñuela |
| collection | DOAJ |
| description | Human Proteome Project (HPP) presents a systematic characterization of the protein landscape under different conditions using several complementary-omic techniques (LC-MS/MS proteomics, affinity proteomics, transcriptomics, etc.). In the present study, using a B-cell lymphoma cell line as a model, comprehensive integration of RNA-Seq transcriptomics, MS/MS, and antibody-based affinity proteomics (combined with size-exclusion chromatography) (SEC-MAP) were performed to uncover correlations that could provide insights into protein dynamics at the intracellular level. Here, 5672 unique proteins were systematically identified by MS/MS analysis and subcellular protein extraction strategies (neXtProt release 2020-21, MS/MS data are available via ProteomeXchange with identifier PXD003939). Moreover, RNA deep sequencing analysis of this lymphoma B-cell line identified 19,518 expressed genes and 5707 protein coding genes (mapped to neXtProt). Among these data sets, 162 relevant proteins (targeted by 206 antibodies) were systematically analyzed by the SEC-MAP approach, providing information about PTMs, isoforms, protein complexes, and subcellular localization. Finally, a bioinformatic pipeline has been designed and developed for orthogonal integration of these high-content proteomics and transcriptomics datasets, which might be useful for comprehensive and global characterization of intracellular protein profiles. |
| first_indexed | 2024-03-10T04:32:42Z |
| format | Article |
| id | doaj.art-556d281facd54cecb22447663535af64 |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-10T04:32:42Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-556d281facd54cecb22447663535af642023-11-23T03:58:59ZengMDPI AGBiomolecules2218-273X2021-11-011112177610.3390/biom11121776Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma ModelAlicia Landeira-Viñuela0Paula Díez1Pablo Juanes-Velasco2Quentin Lécrevisse3Alberto Orfao4Javier De Las Rivas5Manuel Fuentes6Department of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainDepartment of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainDepartment of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainDepartment of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainDepartment of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainBioinformatics and Functional Genomics, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, SpainDepartment of Medicine and General Cytometry Service-Nucleus, USAL/IBSAL, 37000 Salamanca, SpainHuman Proteome Project (HPP) presents a systematic characterization of the protein landscape under different conditions using several complementary-omic techniques (LC-MS/MS proteomics, affinity proteomics, transcriptomics, etc.). In the present study, using a B-cell lymphoma cell line as a model, comprehensive integration of RNA-Seq transcriptomics, MS/MS, and antibody-based affinity proteomics (combined with size-exclusion chromatography) (SEC-MAP) were performed to uncover correlations that could provide insights into protein dynamics at the intracellular level. Here, 5672 unique proteins were systematically identified by MS/MS analysis and subcellular protein extraction strategies (neXtProt release 2020-21, MS/MS data are available via ProteomeXchange with identifier PXD003939). Moreover, RNA deep sequencing analysis of this lymphoma B-cell line identified 19,518 expressed genes and 5707 protein coding genes (mapped to neXtProt). Among these data sets, 162 relevant proteins (targeted by 206 antibodies) were systematically analyzed by the SEC-MAP approach, providing information about PTMs, isoforms, protein complexes, and subcellular localization. Finally, a bioinformatic pipeline has been designed and developed for orthogonal integration of these high-content proteomics and transcriptomics datasets, which might be useful for comprehensive and global characterization of intracellular protein profiles.https://www.mdpi.com/2218-273X/11/12/1776affinity-based proteomicshuman proteome projectLC-MS/MStranscriptomicssize-exclusion-chromatography (SEC) |
| spellingShingle | Alicia Landeira-Viñuela Paula Díez Pablo Juanes-Velasco Quentin Lécrevisse Alberto Orfao Javier De Las Rivas Manuel Fuentes Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model Biomolecules affinity-based proteomics human proteome project LC-MS/MS transcriptomics size-exclusion-chromatography (SEC) |
| title | Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model |
| title_full | Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model |
| title_fullStr | Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model |
| title_full_unstemmed | Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model |
| title_short | Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model |
| title_sort | deepening into intracellular signaling landscape through integrative spatial proteomics and transcriptomics in a lymphoma model |
| topic | affinity-based proteomics human proteome project LC-MS/MS transcriptomics size-exclusion-chromatography (SEC) |
| url | https://www.mdpi.com/2218-273X/11/12/1776 |
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