Project description:Phase separation is an important mechanism to generate certain biomolecular condensates and organize the cell interior. Condensate formation and function remain incompletely understood due to difficulties in visualizing the condensate interior at high resolution. Here we analyzed the structure of biochemically reconstituted chromatin condensates through cryo-electron tomography. We found that traditional blotting methods of sample preparation were inadequate, and high-pressure freezing plus focused ion beam milling was essential to maintain condensate integrity. To identify densely packed molecules within the condensate, we integrated deep learning-based segmentation with novel context-aware template matching. Our approaches were developed on chromatin condensates, and were also effective on condensed regions of in situ native chromatin. Using these methods, we determined the average structure of nucleosomes to 6.1 and 12 Å resolution in reconstituted and native systems, respectively, and found that nucleosomes have a nearly random orientation distribution in both cases. Our methods should be applicable to diverse biochemically reconstituted biomolecular condensates and to some condensates in cells.
Project description:Chromatin organization is highly dynamic and regulates transcription. Upon transcriptional activation, chromatin is remodeled and referred to as "open," but quantitative and dynamic data of this decompaction process are lacking. Here, we have developed a quantitative high resolution-microscopy assay in living yeast cells to visualize and quantify chromatin dynamics using the GAL7-10-1 locus as a model system. Upon transcriptional activation of these three clustered genes, we detect an increase of the mean distance across this locus by >100 nm. This decompaction is linked to active transcription but is not sensitive to the histone deacetylase inhibitor trichostatin A or to deletion of the histone acetyl transferase Gcn5. In contrast, the deletion of SNF2 (encoding the ATPase of the SWI/SNF chromatin remodeling complex) or the deactivation of the histone chaperone complex FACT lead to a strongly reduced decompaction without significant effects on transcriptional induction in FACT mutants. Our findings are consistent with nucleosome remodeling and eviction activities being major contributors to chromatin reorganization during transcription but also suggest that transcription can occur in the absence of detectable decompaction.
Project description:BackgroundChromatin remodeling, histone modifications and other chromatin-related processes play a crucial role in gene regulation. A very useful technique to study these processes is chromatin immunoprecipitation (ChIP). ChIP is widely used for a few model systems, including Arabidopsis, but establishment of the technique for other organisms is still remarkably challenging. Furthermore, quantitative analysis of the precipitated material and normalization of the data is often underestimated, negatively affecting data quality.ResultsWe developed a robust ChIP protocol, using maize (Zea mays) as a model system, and present a general strategy to systematically optimize this protocol for any type of tissue. We propose endogenous controls for active and for repressed chromatin, and discuss various other controls that are essential for successful ChIP experiments. We experienced that the use of quantitative PCR (QPCR) is crucial for obtaining high quality ChIP data and we explain why. The method of data normalization has a major impact on the quality of ChIP analyses. Therefore, we analyzed different normalization strategies, resulting in a thorough discussion of the advantages and drawbacks of the various approaches.ConclusionHere we provide a robust ChIP protocol and strategy to optimize the protocol for any type of tissue; we argue that quantitative real-time PCR (QPCR) is the best method to analyze the precipitates, and present comprehensive insights into data normalization.
Project description:The structure of chromatin is critical for many aspects of cellular physiology and is considered to be the primary medium to store epigenetic information. It is defined by the histone molecules that constitute the nucleosome, the positioning of the nucleosomes along the DNA and the non-histone proteins that associate with it. These factors help to establish and maintain a largely DNA sequence-independent but surprisingly stable structure. Chromatin is extensively disassembled and reassembled during DNA replication, repair, recombination or transcription in order to allow the necessary factors to gain access to their substrate. Despite such constant interference with chromatin structure, the epigenetic information is generally well maintained. Surprisingly, the mechanisms that coordinate chromatin assembly and ensure proper assembly are not particularly well understood. Here, we use label free quantitative mass spectrometry to describe the kinetics of in vitro assembled chromatin supported by an embryo extract prepared from preblastoderm Drosophila melanogaster embryos. The use of a data independent acquisition method for proteome wide quantitation allows a time resolved comparison of in vitro chromatin assembly. A comparison of our in vitro data with proteomic studies of replicative chromatin assembly in vivo reveals an extensive overlap showing that the in vitro system can be used for investigating the kinetics of chromatin assembly in a proteome-wide manner.
Project description:Chromatin immunoprecipitation (ChIP) analysis is widely used to identify the locations in genomes occupied by transcription factors (TFs). The approach involves chemical cross-linking of DNA with associated proteins, fragmentation of chromatin by sonication or enzymatic digestion, immunoprecipitation of the fragments containing the protein of interest, and then PCR or hybridization analysis to characterize and quantify the genomic sequences enriched. We developed a computational model of quantitative ChIP analysis to elucidate the factors contributing to the method's resolution. The most important variables identified by the model were, in order of importance, the spacing of the PCR primers, the mean length of the chromatin fragments, and, unexpectedly, the type of fragment width distribution, with very small DNA fragments and smaller amplicons providing the best resolution of TF binding. One of the major predictions of the model was also validated experimentally.
Project description:Accurate genome duplication requires a tightly regulated DNA replication program that relies on the fine regulation of origin firing. While the molecular steps involved in origin firing have been determined predominantly in budding yeast, the complexity of this process in human cells has yet to be fully elucidated. Here, we describe a straightforward proteomics approach to systematically analyze protein recruitment to the chromatin during induced origin firing in human cells. Using a specific inhibitor against CHK1 kinase, we induced a synchronized wave of dormant origin firing (DOF) and assessed the S phase chromatin proteome at different time points. We provide time-resolved loading dynamics of 3269 proteins, including the core replication machinery and origin firing factors. This dataset accurately represents known temporal dynamics of proteins on the chromatin during the activation of replication forks and the subsequent DNA damage due to the hyperactivation of excessive replication forks. Finally, we used our dataset to identify the condensin II subunit NCAPH2 as a novel factor required for efficient origin firing and replication. Overall, we provide a comprehensive resource to interrogate the protein recruitment dynamics of replication origin firing events in human cells.
Project description:To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated micro-plates. Under these conditions, cells spread and divide in all directions resulting in an inherent variability in cell shape, morphology and behavior. The high cell-to-cell variance of the overall population impedes the success of HCA, especially for drug development. The ability of micropatterns to normalize the shape and internal polarity of every individual cell provides a tremendous opportunity for solving this critical bottleneck (1-2). To facilitate access and use of the micropatterning technology, CYTOO has developed a range of ready to use micropatterns, available in coverslip and microwell formats. In this video article, we provide detailed protocols of all the procedures from cell seeding on CYTOOchip micropatterns, drug treatment, fixation and staining to automated acquisition, automated image processing and final data analysis. With this example, we illustrate how micropatterns can facilitate cell-based assays. Alterations of the cell cytoskeleton are difficult to quantify in cells cultured on homogenous substrates, but culturing cells on micropatterns results in a reproducible organization of the actin meshwork due to systematic positioning of the cell adhesion contacts in every cell. Such normalization of the intracellular architecture allows quantification of even small effects on the actin cytoskeleton as demonstrated in these set of protocols using blebbistatin, an inhibitor of the actin-myosin interaction.
Project description:Eukaryotic nuclear DNA wraps around histone proteins to form a nucleosome, a basic unit of chromatin. Posttranslational modification of histones plays an important role in gene regulation and chromosome duplication. Some modifications are quite stable to be an epigenetic memory, and others exhibit rapid turnover or fluctuate during the cell cycle. Histone H4 Lys20 monomethylation (H4K20me1) has been shown to be involved in chromosome condensation, segregation, replication and repair. H4K20 methylation is controlled through a few methyltransferases, PR-Set7/Set8, SUV420H1, and SUV420H2, and a demethylase, PHF8. In cycling cells, the level of H4K20me1 increases during G2 and M phases and decreases during G1 phase. To monitor the local concentration and global fluctuation of histone modifications in living cells, we have developed a genetically encoded probe termed mintbody (modification-specific intracellular antibody; Sato et al., 2013 and 2016). By measuring the nuclear to cytoplasmic intensity ratio, the relative level of H4K20me1 in individual cells can be monitored. This detailed protocol allows the semi-quantitative analysis of the effects of methyltransferases on H4K20me1 levels in living cells based on H4K20me1-mintbody described by Sato et al. (2016).
Project description:Sequencing chromatin-associated RNA using libraries from the chromatin fraction makes it possible to characterize RNA processing driven by disassociated subunits. Here, we present an experimental strategy and computational pipeline for processing chromatin-associated RNA-seq data to detect and quantify readthrough transcripts. We describe steps for constructing degron mouse embryonic stem cells, detecting readthrough genes, data processing, and data analysis. This protocol can be adapted to various biological scenarios and other types of nascent RNA-seq, such as TT-seq. For complete details on the use and execution of this protocol, please refer to Li et al. (2023).1.
Project description:mRNA positioning in the cell is important for diverse cellular functions and proper development of multicellular organisms. Single-molecule RNA FISH (smFISH) enables quantitative investigation of mRNA localization and abundance at the level of individual molecules in the context of cellular features. Details about spatial mRNA patterning at various times, in different genetic backgrounds, at different developmental stages, and under varied environmental conditions provide invaluable insights into the mechanisms and functions of spatial regulation. Here, we describe detailed methods for performing smFISH along with immunofluorescence for two large, multinucleate cell types: the fungus Ashbya gossypii and cultured mouse myotubes. We also put forward a semi-automated image processing tool that systematically detects mRNAs from smFISH data and statistically analyzes the spatial pattern of mRNAs using a customized MATLAB code. These protocols and image analysis tools can be adapted to a wide variety of transcripts and cell types for systematically and quantitatively analyzing mRNA distribution in three-dimensional space.