RESUMEN
Nucleosomes help structure chromosomes by compacting DNA into fibers. To gain insight into how nucleosomes are arranged in vivo, we combined quantitative super-resolution nanoscopy with computer simulations to visualize and count nucleosomes along the chromatin fiber in single nuclei. Nucleosomes assembled in heterogeneous groups of varying sizes, here termed "clutches," and these were interspersed with nucleosome-depleted regions. The median number of nucleosomes inside clutches and their compaction defined as nucleosome density were cell-type-specific. Ground-state pluripotent stem cells had, on average, less dense clutches containing fewer nucleosomes and clutch size strongly correlated with the pluripotency potential of induced pluripotent stem cells. RNA polymerase II preferentially associated with the smallest clutches while linker histone H1 and heterochromatin were enriched in the largest ones. Our results reveal how the chromatin fiber is formed at nanoscale level and link chromatin fiber architecture to stem cell state.
Asunto(s)
Cromatina/química , Nucleosomas/química , Nucleosomas/ultraestructura , Animales , Diferenciación Celular , Cromatina/metabolismo , Simulación por Computador , Células Madre Embrionarias/química , Células Madre Embrionarias/metabolismo , Estudio de Asociación del Genoma Completo , Histonas/metabolismo , Humanos , Interfase , Ratones , Mutación , Nucleosomas/metabolismo , Células Madre Pluripotentes/química , Células Madre Pluripotentes/metabolismo , ARN Polimerasa II/metabolismoRESUMEN
50 years ago, Vincent Allfrey and colleagues discovered that lymphocyte activation triggers massive acetylation of chromatin. However, the molecular mechanisms driving epigenetic accessibility are still unknown. We here show that stimulated lymphocytes decondense chromatin by three differentially regulated steps. First, chromatin is repositioned away from the nuclear periphery in response to global acetylation. Second, histone nanodomain clusters decompact into mononucleosome fibers through a mechanism that requires Myc and continual energy input. Single-molecule imaging shows that this step lowers transcription factor residence time and non-specific collisions during sampling for DNA targets. Third, chromatin interactions shift from long range to predominantly short range, and CTCF-mediated loops and contact domains double in numbers. This architectural change facilitates cognate promoter-enhancer contacts and also requires Myc and continual ATP production. Our results thus define the nature and transcriptional impact of chromatin decondensation and reveal an unexpected role for Myc in the establishment of nuclear topology in mammalian cells.
Asunto(s)
Linfocitos B/metabolismo , Ciclo Celular , Núcleo Celular/metabolismo , Ensamble y Desensamble de Cromatina , Cromatina/metabolismo , Histonas/metabolismo , Activación de Linfocitos , Proteínas Proto-Oncogénicas c-myc/metabolismo , Acetilcoenzima A/metabolismo , Acetilación , Adenosina Trifosfato/metabolismo , Animales , Linfocitos B/inmunología , Línea Celular , Cromatina/química , Cromatina/genética , Metilación de ADN , Epigénesis Genética , Genotipo , Histonas/química , Inmunidad Humoral , Metilación , Ratones Endogámicos C57BL , Ratones Noqueados , Conformación de Ácido Nucleico , Fenotipo , Dominios y Motivos de Interacción de Proteínas , Procesamiento Proteico-Postraduccional , Proteínas Proto-Oncogénicas c-myc/química , Proteínas Proto-Oncogénicas c-myc/genética , Imagen Individual de Molécula , Relación Estructura-Actividad , Factores de Tiempo , Transcripción GenéticaRESUMEN
Systems biology approaches are extensively used to model and reverse engineer gene regulatory networks from experimental data. Conversely, synthetic biology allows "de novo" construction of a regulatory network to seed new functions in the cell. At present, the usefulness and predictive ability of modeling and reverse engineering cannot be assessed and compared rigorously. We built in the yeast Saccharomyces cerevisiae a synthetic network, IRMA, for in vivo "benchmarking" of reverse-engineering and modeling approaches. The network is composed of five genes regulating each other through a variety of regulatory interactions; it is negligibly affected by endogenous genes, and it is responsive to small molecules. We measured time series and steady-state expression data after multiple perturbations. These data were used to assess state-of-the-art modeling and reverse-engineering techniques. A semiquantitative model was able to capture and predict the behavior of the network. Reverse engineering based on differential equations and Bayesian networks correctly inferred regulatory interactions from the experimental data.
Asunto(s)
Redes Reguladoras de Genes , Técnicas Genéticas , Modelos Genéticos , Saccharomyces cerevisiae/genética , Biología de Sistemas/métodos , Biología Computacional/métodos , Galactosa/metabolismo , Perfilación de la Expresión Génica , Regulación Fúngica de la Expresión Génica , Glucosa/metabolismo , Saccharomyces cerevisiae/metabolismoRESUMEN
Chromatin fiber organization is essential for gene function in all cell types. Moreover it helps to determine cell fate in embryonic/adult stem cells and in somatic cells undergoing reprogramming to pluripotency. Until now the diffraction limit of light has limited the inspection of the chromatin fiber organization to a level sufficient to understand how it impacts gene function. The development of advanced microscopy methods, such as single molecule localization microscopy, has largely opened a new field of research providing us with the tools to visualize and quantitatively analyze chromatin fiber organization and thus gene activity at nanoscale resolution in single cells.
Asunto(s)
Diferenciación Celular/genética , Reprogramación Celular/genética , Cromatina/genética , Análisis de la Célula Individual/métodos , Células Madre Embrionarias/citología , Humanos , MicroscopíaRESUMEN
Systems and Synthetic Biology use computational models of biological pathways in order to study in silico the behaviour of biological pathways. Mathematical models allow to verify biological hypotheses and to predict new possible dynamical behaviours. Here we use the tools of non-linear analysis to understand how to change the dynamics of the genes composing a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-engineering and Modelling Assessment (IRMA). Guided by previous theoretical results that make the dynamics of a biological network depend on its topological properties, through the use of simulation and continuation techniques, we found that the network can be easily turned into a robust and tunable synthetic oscillator or a bistable switch. Our results provide guidelines to properly re-engineering in vivo the network in order to tune its dynamics.