A nuclear architecture screen in Drosophila identifies Stonewall as a link between chromatin position at the nuclear periphery and germline stem cell fate.

The association of genomic loci to the nuclear periphery is proposed to facilitate cell type-specific gene repression and influence cell fate decisions. However, the interplay between gene position and expression remains incompletely understood, in part because the proteins that position genomic loci at the nuclear periphery remain unidentified. Here, we used an Oligopaint-based HiDRO screen targeting ∼1000 genes to discover novel regulators of nuclear architecture in Drosophila cells. We identified the heterochromatin-associated protein Stonewall (Stwl) as a factor promoting perinuclear chromatin positioning. In female germline stem cells (GSCs), Stwl binds and positions chromatin loci, including GSC differentiation genes, at the nuclear periphery. Strikingly, Stwl-dependent perinuclear positioning is associated with transcriptional repression, highlighting a likely mechanism for Stwl's known role in GSC maintenance and ovary homeostasis. Thus, our study identifies perinuclear anchors in Drosophila and demonstrates the importance of gene repression at the nuclear periphery for cell fate.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are nonrandom, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization. Here, we describe two methods for the detection of DNA and RNA of individual gene alleles by fluorescence in situ hybridization (FISH) in a high-throughput format. We have optimized combined DNA/RNA FISH approaches either using simultaneous or sequential detection of DNA and nascent RNA. These optimized DNA and RNA FISH protocols were implemented in a 384-well plate format alongside automated image and data analysis and enable accurate detection of individual gene alleles and their gene expression status across a large cell population. We successfully visualized MYC and EGFR DNA and nascent RNA with allele-level resolution in multiple cell types, and we determined the radial position of active and inactive MYC and EGFR alleles. These optimized DNA/RNA detection approaches are versatile and sensitive tools for mapping of chromatin features and gene activity at the single-allele level and at high throughput.

High-Throughput RNA-HCR-FISH Detection of Endogenous Pre-mRNA Splice Variants.

RNA-fluorescence in situ hybridization (RNA-FISH) is an essential and widely used tool for visualizing RNA molecules in intact cells. Recent advances have increased RNA-FISH sensitivity, signal detection efficiency, and throughput. However, detection of endogenous mRNA splice variants has been challenging due to the limits of visualization of RNA-FISH fluorescence signals and due to the limited number of RNA-FISH probes per target. HiFENS (high-throughput FISH detection of endogenous pre-mRNA splicing isoforms) is a method that enables visualization and relative quantification of mRNA splice variants at single-cell resolution in an automated high-throughput manner. HiFENS incorporates HCR (hybridization chain reaction) signal amplification strategies to enhance the fluorescence signal generated by low abundance transcripts or a small number of FISH probes targeting short stretches of RNA, such as single exons. The technique offers a significant advance in high-throughput FISH-based RNA detection and provides a powerful tool that can be used as a readout in functional genomics screens to discover and dissect cellular pathways regulating gene expression and alternative pre-mRNA splicing events.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are non-random, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization. Here, we describe two methods for the detection of DNA and RNA of individual gene alleles by fluorescence in situ hybridization (FISH) in a high-throughput format. We have optimized combined DNA/RNA FISH approaches either using simultaneous or sequential detection. These optimized DNA and RNA FISH protocols, implemented in a 384-well plate format alongside automated image and data analysis, enable accurate detection of chromatin loci and their gene expression status across a large cell population with allele-level resolution. We successfully visualized MYC and EGFR DNA and RNA in multiple cell types, and we determined the radial position of active and inactive MYC and EGFR alleles. These optimized DNA/RNA detection approaches are versatile and sensitive tools for mapping of chromatin features and gene activity at the single-allele level and at high throughput.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are non-random, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization. Here, we describe two methods for the detection of DNA and RNA of individual gene alleles by fluorescence in situ hybridization (FISH) in a high-throughput format. We have optimized combined DNA/RNA FISH approaches either using simultaneous or sequential detection. These optimized DNA and RNA FISH protocols, implemented in a 384-well plate format alongside automated image and data analysis, enable accurate detection of chromatin loci and their gene expression status across a large cell population with allele-level resolution. We successfully visualized MYC and EGFR DNA and RNA in multiple cell types, and we determined the radial position of active and inactive MYC and EGFR alleles. These optimized DNA/RNA detection approaches are versatile and sensitive tools for mapping of chromatin features and gene activity at the single-allele level and at high throughput.

Native FISH: A low- and high-throughput assay to analyze the alternative lengthening of telomere (ALT) pathway.

Alternative lengthening of telomeres (ALT) is a telomerase-independent and recombination-based mechanism used by approximately 15% of human cancers to maintain telomere length and to sustain proliferation. ALT-positive cells display unique features that could be exploited for tailored cancer therapies. A key limitation for the development of ALT-specific treatments is the lack of an assay to detect ALT-positive cells that is easy to perform and that can be scaled up. One of the most broadly used assays for ALT detection, CCA (C-circle assay), does not provide single-cell information and it is not amenable to High-Throughput Screening (HTS). To overcome these limitations, we developed Native-FISH (N-FISH) as an alternative method to visualize ALT-specific single-stranded telomeric DNA. N-FISH produces single-cell data, can be applied to fixed tissues, does not require DNA isolation or amplification steps, and it can be miniaturized in a 384-well format. This protocol details the steps to perform N-FISH protocol both in a low- and high-throughput format to analyze ALT. While low-throughput N-FISH is useful to assay the ALT state of cell lines, we expect that the miniaturized N-FISH assay coupled with high-throughput imaging will be useful in functional genomics and chemical screens to identify novel cellular factors that regulate ALT and potential ALT therapeutic targets for cancer therapies directed against ALT-positive tumors, respectively.

Novel biosensor for high-throughput detection of progesterone receptor-interacting endocrine disruptors.

Progesterone receptor (PR)-interacting compounds in the environment are associated with serious health hazards. However, methods for their detection in environmental samples are cumbersome. We report a sensitive activity-based biosensor for rapid and reliable screening of progesterone receptor (PR)-interacting endocrine disrupting chemicals (EDCs). The biosensor is a cell line which expresses nuclear mCherry-NF1 and a green fluorescent protein (GFP)-tagged chimera of glucocorticoid receptor (GR) N terminus fused to the ligand binding domain (LBD) of PR (GFP-GR-PR). As this LBD is shared by the PRA and PRB, the biosensor reports on the activation of both PR isoforms. This GFP-GR-PR chimera is cytoplasmic in the absence of hormone and translocates rapidly to the nucleus in response to PR agonists or antagonists in concentration- and time-dependent manner. In live cells, presence of nuclear NF1 label eliminates cell fixation and nuclear staining resulting in efficient screening. The assay can be used in screens for novel PR ligands and PR-interacting contaminants in environmental samples. A limited screen of river water samples indicated a widespread, low-level contamination with PR-interacting contaminants in all tested samples.

hcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells.

Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

High-throughput image processing software for the study of nuclear architecture and gene expression.

High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software programs for image analysis workflows typically do not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities. HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, nucleus registration, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new analysis modules for existing analysis pipelines and to adding new analysis modules. To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI software platform for a variety of cell biology applications.