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1.
Nature ; 590(7847): 649-654, 2021 02.
Artículo en Inglés | MEDLINE | ID: mdl-33627808

RESUMEN

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.


Asunto(s)
Ciclo Celular , Proteogenómica/métodos , Análisis de la Célula Individual/métodos , Transcriptoma , Proteínas de Ciclo Celular/metabolismo , Línea Celular Tumoral , Linaje de la Célula , Proliferación Celular , Humanos , Interfase , Mitosis , Proteínas Oncogénicas/metabolismo , Fosforilación , Proteínas Quinasas/metabolismo , Proteoma/metabolismo , Factores de Tiempo
3.
Science ; 356(6340)2017 05 26.
Artículo en Inglés | MEDLINE | ID: mdl-28495876

RESUMEN

Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map of subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of the proteomes of 13 major organelles. Exploration of the proteomes revealed single-cell variations in abundance or spatial distribution and localization of about half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.


Asunto(s)
Imagen Molecular , Orgánulos/química , Orgánulos/metabolismo , Mapas de Interacción de Proteínas , Proteoma/análisis , Proteoma/metabolismo , Análisis de la Célula Individual , Línea Celular , Conjuntos de Datos como Asunto , Femenino , Humanos , Masculino , Espectrometría de Masas , Microscopía Fluorescente , Mapeo de Interacción de Proteínas , Proteoma/genética , Reproducibilidad de los Resultados , Fracciones Subcelulares , Transcriptoma
4.
Science ; 347(6220): 1260419, 2015 Jan 23.
Artículo en Inglés | MEDLINE | ID: mdl-25613900

RESUMEN

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.


Asunto(s)
Bases de Datos de Proteínas , Proteoma/metabolismo , Empalme Alternativo , Línea Celular , Femenino , Genes , Código Genético , Humanos , Internet , Masculino , Proteínas de la Membrana/genética , Proteínas de la Membrana/metabolismo , Proteínas Mitocondriales/genética , Proteínas Mitocondriales/metabolismo , Neoplasias/genética , Neoplasias/metabolismo , Análisis por Matrices de Proteínas , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismo , Proteoma/genética , Distribución Tisular , Transcripción Genética
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