Cellular analysis of the action of epigenetics drugs and probes

Small molecule drugs and probes are important tools in drug discovery, pharmacology, and cell biology. This is of course also true for epigenetic inhibitors. Important examples for the use of established epigenetic inhibitors are the study of the mechanistic role of a certain target in a cellular setting or the modulation of a certain phenotype in an approach that aims towards therapeutic application. Alternatively, cellular testing may aim at the validation of a new epigenetic inhibitor in drug discovery approaches. Cellular and eventually animal models provide powerful tools for these different approaches but certain caveats have to be recognized and taken into account. This involves both the selectivity of the pharmacological tool as well as the specificity and the robustness of the cellular system. In this article, we present an overview of different methods that are used to profile and screen for epigenetic agents and comment on their limitations. We describe not only diverse successful case studies of screening approaches using different assay formats, but also some problematic cases, critically discussing selected applications of these systems

Phospho-Seq: Integrated, Multi-Modal Profiling of Intracellular Protein Dynamics in Single Cells

Cell signaling plays a critical role in regulating cellular behavior and fate. While multimodal single-cell sequencing technologies are rapidly advancing, scalable and flexible profiling of cell signaling states alongside other molecular modalities remains challenging. Here we present Phospho-seq, an integrated approach that aims to quantify phosphorylated intracellular and intranuclear proteins, and to connect their activity with cis-regulatory elements and transcriptional targets. We utilize a simplified benchtop antibody conjugation method to create large custom antibody panels for simultaneous protein and scATAC-seq profiling on whole cells, and integrate this information with scRNA-seq datasets via bridge integration. We apply our workflow to cell lines, induced pluripotent stem cells, and 3-month-old brain organoids to demonstrate its broad applicability. We demonstrate that Phospho-seq can define cellular states and trajectories, reconstruct gene regulatory relationships, and characterize the causes and consequences of heterogeneous cell signaling in neurodevelopment

Phospho-seq: Integrated, multi-modal profiling of intracellular protein dynamics in single cells

&lt;p&gt;&nbsp;&lt;/p&gt;&lt;p&gt;Datasets to go along with the publication listed:&lt;/p&gt;&lt;p&gt;full_object.rds: Brain Organoid Phospho-Seq dataset with ATAC, Protein and imputed RNA data&lt;/p&gt;&lt;p&gt;rna_object.rds: Reference whole cell scRNA-Seq object on Brain organoids&lt;/p&gt;&lt;p&gt;multiome_object.rds: Bridge dataset containing RNA and ATAC modalities for Brain organoids&lt;/p&gt;&lt;p&gt;metacell_allnorm.rds: Metacell object for finding gene-peak-protein linkages in Brain organoid dataset&lt;/p&gt;&lt;p&gt;fullobject_fragments.tsv.gz: fragment file to go with the full object&lt;/p&gt;&lt;p&gt;fullobject_fragments.tsv.gz.tbi:index file for the full object fragment file&lt;/p&gt;&lt;p&gt;multiome_fragments.tsv.gz: fragment file to go with the multiome&nbsp;object&lt;/p&gt;&lt;p&gt;multiome_fragments.tsv.gz.tbi:index file for the multiome object fragment file&lt;/p&gt;&lt;p&gt;K562_Stem.rds : object corresponding to the pilot experiment including K562 cells and iPS cells&lt;/p&gt;&lt;p&gt;K562_stem_fragments.tsv.gz:&nbsp; fragment file to go with the K562_stem object&lt;/p&gt;&lt;p&gt;K562_stem_fragments.tsv.gz.tbi: index file for the K562_stem object fragment file&lt;/p&gt;&lt;p&gt;retina.rds : object corresponding to the retinal organoid phospho-seq experiment&lt;/p&gt;&lt;p&gt;retina_fragments.tsv.gz:&nbsp; fragment file to go with the retina object&lt;/p&gt;&lt;p&gt;retina_fragments.tsv.gz.tbi: index file for the retina object fragment file&lt;/p&gt;&lt;p&gt;retina_multi.rds : object corresponding to the retinal organoid phospho-seq-multiome experiment&lt;/p&gt;&lt;p&gt;retina_multi_fragments.tsv.gz:&nbsp; fragment file to go with the retina_multi object&lt;/p&gt;&lt;p&gt;retina_multi_fragments.tsv.gz.tbi: index file for the retina_multi object fragment file&lt;/p&gt;&lt;p&gt;To use the K562, multiome,&nbsp;retina and retina_multiome datasets provided, please use these lines of code to import the object into Signac/Seurat&nbsp;and change the fragment&nbsp;file path to the corresponding downloaded fragment file:&lt;/p&gt;&lt;p&gt;obj &lt;- readRDS("obj.rds") # remove fragment file information Fragments(obj) &lt;- NULL # Update the path of the fragment file Fragments(obj) &lt;- CreateFragmentObject(path = "download/obj_fragments.tsv.gz", cells = Cells(obj))&lt;/p&gt;&lt;p&gt;To use the K562 and multiome&nbsp;datasets provided, please use these lines of code to import the object into Signac/Seurat&nbsp;and change the fragment&nbsp;file path to the corresponding downloaded fragment file:&lt;/p&gt;&lt;p&gt;obj &lt;- readRDS("obj.rds") # remove fragment file information Fragments(obj) &lt;- NULL # Update the path of the fragment file Fragments(obj) &lt;- CreateFragmentObject(path = "download/obj_fragments.tsv.gz", cells = Cells(obj))&lt;/p&gt;&lt;p&gt;To use the "fullobject" dataset&nbsp;provided, please use these lines of code to import the object into Signac/Seurat&nbsp;and change the fragment&nbsp;file path to the corresponding downloaded fragment file:&nbsp;&lt;/p&gt;&lt;p&gt;#load the stringr package library(stringr) #load the object obj &lt;- readRDS("obj.rds") # remove fragment file information Fragments(obj) &lt;- NULL #Remove unwanted residual information and rename cells obj@reductionsnorm.adt.pca <- NULL obj@reductionsnorm.pca &lt;- NULL obj &lt;- RenameCells(obj, new.names = str_remove(Cells(obj), "atac_")) # Update the path of the fragment file Fragments(obj) &lt;- CreateFragmentObject(path = "download/obj_fragments.tsv.gz", cells = Cells(obj))&lt;/p&gt;&lt;p&gt;&nbsp;&lt;/p&gt;&lt;p&gt;&nbsp;&lt;/p&gt

Analysis of the Microprocessor in Dictyostelium: The Role of RbdB, a dsRNA Binding Protein

We identified the dsRNA binding protein RbdB as an essential component in miRNA processing in Dictyostelium discoideum. RbdB is a nuclear protein that accumulates, together with Dicer B, in nucleolar foci reminiscent of plant dicing bodies. Disruption of rbdB results in loss of miRNAs and accumulation of primary miRNAs. The phenotype can be rescued by ectopic expression of RbdB thus allowing for a detailed analysis of domain function. The lack of cytoplasmic dsRBD proteins involved in miRNA processing, suggests that both processing steps take place in the nucleus thus resembling the plant pathway. However, we also find features e.g. in the domain structure of Dicer which suggest similarities to animals. Reduction of miRNAs in the rbdB- strain and their increase in the Argonaute A knock out allowed the definition of new miRNAs one of which appears to belong to a new non-canonical class

The protein domains of the <i>Dictyostelium</i> microprocessor that are required for correct subcellular localization and for microRNA maturation

<p>The maturation pathways of microRNAs (miRNAs) have been delineated for plants and several animals, belonging to the evolutionary supergroups of Archaeplastida and Opisthokonta, respectively. Recently, we reported the discovery of the microprocessor complex in <i>Dictyostelium discoideum</i> of the Amoebozoa supergroup. The complex is composed of the Dicer DrnB and the dsRBD (double-stranded RNA binding domain) containing protein RbdB. Both proteins localize at nucleoli, where they physically interact, and both are required for miRNA maturation. Here we show that the miRNA phenotype of a Δ<i>drnB</i> gene deletion strain can be rescued by ectopic expression of a series of DrnB GFP fusion proteins, which consistently showed punctate perinucleolar localization in fluorescence microscopy. These punctate foci appear surprisingly stable, as they persist both disintegration of nucleoli and degradation of cellular nucleic acids. We observed that DrnB expression levels influence the number of microprocessor foci and alter RbdB accumulation. An investigation of DrnB variants revealed that its newly identified nuclear localization signal is necessary, but not sufficient for the perinucleolar localization. Biogenesis of miRNAs, which are RNA Pol II transcripts, is correlated with that localization. Besides its bidentate RNase III domains, DrnB contains only a dsRBD, which surprisingly is dispensable for miRNA maturation. This dsRBD can, however, functionally replace the homologous domain in RbdB. Based on the unique setup of the <i>Dictyostelium</i> microprocessor with a subcellular localization similar to plants, but a protein domain composition similar to animals, we propose a model for the evolutionary origin of RNase III proteins acting in miRNA maturation.</p

Inferring and perturbing cell fate regulomes in human cerebral organoids

Self-organizing cerebral organoids grown from pluripotent stem cells combined with single-cell genomic technologies provide opportunities to explore gene regulatory networks (GRNs) underlying human brain development. Here we acquire single-cell transcriptome and accessible chromatin profiling data over a dense time course covering multiple phases of organoid development including neuroepithelial formation, patterning, brain regionalization, and neurogenesis. We identify temporally dynamic and brain region-specific regulatory regions, and cell interaction analysis reveals emergent patterning centers associated with regionalization. We develop Pando, a flexible linear model-based framework that incorporates multi-omic data and transcription binding site predictions to infer a global GRN describing organoid development. We use pooled genetic perturbation with single-cell transcriptome readout to assess transcription factor requirement for cell fate and state regulation in organoid. We find that certain factors regulate the abundance of cell fates, whereas other factors impact neuronal cell states after differentiation. We show that the zinc finger protein GLI3 is required for cortical fate establishment in humans, recapitulating previous work performed in mammalian model systems. We measure transcriptome and chromatin accessibility in normal or GLI3-perturbed cells and identify a regulome central to the dorsoventral telencephalic fate decision. This regulome suggests that Notch effectors HES4/5 are direct GLI3 targets, which together coordinate cortex and ganglionic eminence diversification. Altogether, we provide a framework for how multi-brain region model systems and single-cell technologies can be leveraged to reconstruct human brain developmental biology

Histone variant H2A.Z regulates zygotic genome activation

International audienceAbstract During embryogenesis, the genome shifts from transcriptionally quiescent to extensively active in a process known as Zygotic Genome Activation (ZGA). In Drosophila , the pioneer factor Zelda is known to be essential for the progression of development; still, it regulates the activation of only a small subset of genes at ZGA. However, thousands of genes do not require Zelda, suggesting that other mechanisms exist. By conducting GRO-seq, HiC and ChIP-seq in Drosophila embryos, we demonstrate that up to 65% of zygotically activated genes are enriched for the histone variant H2A.Z. H2A.Z enrichment precedes ZGA and RNA Polymerase II loading onto chromatin. In vivo knockdown of maternally contributed Domino, a histone chaperone and ATPase, reduces H2A.Z deposition at transcription start sites, causes global downregulation of housekeeping genes at ZGA, and compromises the establishment of the 3D chromatin structure. We infer that H2A.Z is essential for the de novo establishment of transcriptional programs during ZGA via chromatin reorganization

Inferring and perturbing cell fate regulomes in human brain organoids

Self-organizing neural organoids grown from pluripotent stem cells combined with single-cell genomic technologies provide opportunities to examine gene regulatory networks underlying human brain development. Here we acquire single-cell transcriptome and accessible chromatin data over a dense time course in human organoids covering neuroepithelial formation, patterning, brain regionalization and neurogenesis, and identify temporally dynamic and brain-region-specific regulatory regions. We developed Pando—a flexible framework that incorporates multi-omic data and predictions of transcription-factor-binding sites to infer a global gene regulatory network describing organoid development. We use pooled genetic perturbation with single-cell transcriptome readout to assess transcription factor requirement for cell fate and state regulation in organoids. We find that certain factors regulate the abundance of cell fates, whereas other factors affect neuronal cell states after differentiation. We show that the transcription factor GLI3 is required for cortical fate establishment in humans, recapitulating previous research performed in mammalian model systems. We measure transcriptome and chromatin accessibility in normal or GLI3-perturbed cells and identify two distinct GLI3 regulomes that are central to telencephalic fate decisions: one regulating dorsoventral patterning with HES4/5 as direct GLI3 targets, and one controlling ganglionic eminence diversification later in development. Together, we provide a framework for how human model systems and single-cell technologies can be leveraged to reconstruct human developmental biology.ISSN:0028-0836ISSN:1476-468

Subcellular localization of RbdB GFP and co-localization with DrnB.

<p>AX2 cells were transformed with the integrating plasmid pDneo2a RbdB GFP and subcellular localization was analyzed by fluorescence microscopy. A: Living cells were analyzed in low fluorescence axenic medium showing a diffuse distribution of the fusion proteins in the nucleoplasm and distinct foci at the periphery of the nuclei. Scale bar represents 5 μm. B: To better localize the subnuclear foci, cells were fixed with methanol and analyzed by an OptiGrid microscope (Leica DM 5500). Genomic DNA was stained by DAPI (red). The nucleoli showed no or only a very weak staining. Merging GFP (green) and DAPI (red) signals indicated that RbdB-GFP foci were enriched adjacent to areas with weak or no DAPI staining. Scale bar represents 2.5 μm. C: Co-localization of GFP DrnB and RbdB mRFP in nucleoli associated foci was monitored by fluorescence microscopy using methanol fixed cells. Shown is a single nucleus. Fusion proteins were expressed from extrachromosomally replicating plasmids. Scale bar represents 2.5 μm.</p