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1.
J Proteome Res ; 17(11): 3914-3922, 2018 11 02.
Artigo em Inglês | MEDLINE | ID: mdl-30300549

RESUMO

Human tissues are known to exhibit interindividual variability, but a deeper understanding of the different factors affecting protein expression is necessary to further apply this knowledge. Our goal was to explore the proteomic variability between individuals as well as between healthy and diseased samples, and to test the efficacy of machine learning classifiers. In order to investigate whether disparate proteomics data sets may be combined, we performed a retrospective analysis of proteomics data from 9 different human tissues. These data sets represent several different sample prep methods, mass spectrometry instruments, and tissue health. Using these data, we examined interindividual and intertissue variability in peptide expression, and analyzed the methods required to build accurate tissue classifiers. We also evaluated the limits of tissue classification by downsampling the peptide data to simulate situations where less data is available, such as clinical biopsies, laser capture microdissection or potentially single-cell proteomics. Our findings reveal the strong potential for utilizing proteomics data to build robust tissue classifiers, which has many prospective clinical applications for evaluating the applicability of model clinical systems.


Assuntos
Variação Biológica Individual , Mineração de Dados/estatística & dados numéricos , Regulação da Expressão Gênica , Peptídeos/química , Proteínas/genética , Proteômica/métodos , Sequência de Aminoácidos , Biópsia , Linhagem Celular , Feminino , Perfilação da Expressão Gênica , Humanos , Microdissecção e Captura a Laser , Fígado/química , Aprendizado de Máquina , Masculino , Monócitos/química , Especificidade de Órgãos , Ovário/química , Pâncreas/química , Peptídeos/isolamento & purificação , Peptídeos/metabolismo , Proteínas/metabolismo , Estudos Retrospectivos , Análise de Célula Única , Substância Negra/química , Lobo Temporal/química
2.
Sci Rep ; 7: 44296, 2017 03 13.
Artigo em Inglês | MEDLINE | ID: mdl-28287158

RESUMO

Compartmentalization of metabolic pathways to particular organelles is a hallmark of eukaryotic cells. Knowledge of the development of organelles and attendant pathways under different metabolic states has been advanced by live cell imaging and organelle specific analysis. Nevertheless, relatively few studies have addressed the cellular localization of pathways for synthesis of fungal secondary metabolites, despite their importance as bioactive compounds with significance to medicine and agriculture. When triggered to produce sesquiterpene (trichothecene) mycotoxins, the endoplasmic reticulum (ER) of the phytopathogenic fungus Fusarium graminearum is reorganized both in vitro and in planta. Trichothecene biosynthetic enzymes accumulate in organized smooth ER with pronounced expansion at perinuclear- and peripheral positions. Fluorescence tagged trichothecene biosynthetic proteins co-localize with the modified ER as confirmed by co-fluorescence and co-purification with known ER proteins. We hypothesize that changes to the fungal ER represent a conserved process in specialized eukaryotic cells such as in mammalian hepatocytes and B-cells.


Assuntos
Retículo Endoplasmático/metabolismo , Fusarium/metabolismo , Micotoxinas/biossíntese , Tricotecenos/biossíntese , Vias Biossintéticas/genética , Retículo Endoplasmático/ultraestrutura , Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismo , Fusarium/genética , Fusarium/fisiologia , Proteínas Luminescentes/genética , Proteínas Luminescentes/metabolismo , Microscopia Eletrônica de Transmissão , Microscopia de Fluorescência , Doenças das Plantas/microbiologia , Metabolismo Secundário/genética , Triticum/microbiologia
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