Imaging transcriptional dynamics

Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells

Single-cell RNA sequencing has revolutionized our understanding of cellular heterogeneity, but routine methods require cell lysis and fail to probe the dynamic trajectories responsible for cellular state transitions, which can only be inferred. Here, we present a nanobiopsy platform that enables the injection of exogenous molecules and multigenerational longitudinal cytoplasmic sampling from a single cell and its progeny. The technique is based on scanning ion conductance microscopy (SICM) and, as a proof of concept, was applied to longitudinally profile the transcriptome of single glioblastoma (GBM) brain tumor cells in vitro over 72 hours. The GBM cells were biopsied before and after exposure to chemotherapy and radiotherapy, and our results suggest that treatment either induces or selects for more transcriptionally stable cells. We envision the nanobiopsy will contribute to transforming standard single-cell transcriptomics from a static analysis into a dynamic assay.

Single-cell transcriptional dynamics in a living vertebrate

The ability to quantify transcriptional dynamics in individual cells via live imaging has revolutionized our understanding of gene regulation. However, such measurements are lacking in the context of vertebrate embryos. We addressed this deficit by applying MS2-MCP mRNA labeling to the quantification of transcription in zebrafish, a model vertebrate. We developed a platform of transgenic organisms, light sheet fluorescence microscopy, and optimized image analysis that enables visualization and quantification of MS2 reporters. We used these tools to obtain the first single-cell, real-time measurements of transcriptional dynamics of the segmentation clock. Our measurements challenge the traditional view of smooth clock oscillations and instead suggest a model of discrete transcriptional bursts that are organized in space and time. Together, these results highlight how measuring single-cell transcriptional activity can reveal unexpected features of gene regulation and how this data can fuel the dialogue between theory and experiment.

Transcriptional activators in the early Drosophila embryo perform different kinetic roles

Combinatorial regulation of gene expression by transcription factors (TFs) may in part arise from kinetic synergy-wherein TFs regulate different steps in the transcription cycle. Kinetic synergy requires that TFs play distinguishable kinetic roles. Here, we used live imaging to determine the kinetic roles of three TFs that activate transcription in the Drosophila embryo-Zelda, Bicoid, and Stat92E-by introducing their binding sites into the even-skipped stripe 2 enhancer. These TFs influence different sets of kinetic parameters, and their influence can change over time. All three TFs increased the fraction of transcriptionally active nuclei; Zelda also shortened the first-passage time into transcription and regulated the interval between transcription events. Stat92E also increased the lifetimes of active transcription. Different TFs can therefore play distinct kinetic roles in activating the transcription. This has consequences for understanding the composition and flexibility of regulatory DNA sequences and the biochemical function of TFs. A record of this paper's transparent peer review process is included in the supplemental information.

Unveiling dynamic enhancer–promoter interactions in Drosophila melanogaster

Proper enhancer–promoter interactions are essential to maintaining specific transcriptional patterns and preventing ectopic gene expression. Drosophila is an ideal model organism to study transcriptional regulation due to extensively characterized regulatory regions and the ease of implementing new genetic and molecular techniques for quantitative analysis. The mechanisms of enhancer–promoter interactions have been investigated over a range of length scales. At a DNA level, compositions of both enhancer and promoter sequences affect transcriptional dynamics, including duration, amplitude, and frequency of transcriptional bursting. 3D chromatin topology is also important for proper enhancer–promoter contacts. By working competitively or cooperatively with one another, multiple, simultaneous enhancer–enhancer, enhancer–promoter, and promoter–promoter interactions often occur to maintain appropriate levels of mRNAs. For some long-range enhancer–promoter interactions, extra regulatory elements like insulators and tethering elements are required to promote proper interactions while blocking aberrant ones. This review provides an overview of our current understanding of the mechanism of enhancer–promoter interactions and how perturbations of such interactions affect transcription and subsequent physiological outcomes.

Real-time imaging of RNA polymerase I activity in living human cells

RNA polymerase I (Pol I) synthesizes about 60% of cellular RNA by transcribing multiple copies of the ribosomal RNA gene (rDNA). The transcriptional activity of Pol I controls the level of ribosome biogenesis and cell growth. However, there is currently a lack of methods for monitoring Pol I activity in real time. Here, we develop LiveArt (live imaging-based analysis of rDNA transcription) to visualize and quantify the spatiotemporal dynamics of endogenous ribosomal RNA (rRNA) synthesis. LiveArt reveals mitotic silencing and reactivation of rDNA transcription, as well as the transcriptional kinetics of interphase rDNA. Using LiveArt, we identify SRFBP1 as a potential regulator of rRNA synthesis. We show that rDNA transcription occurs in bursts and can be altered by modulating burst duration and amplitude. Importantly, LiveArt is highly effective in the screening application for anticancer drugs targeting Pol I transcription. These approaches pave the way for a deeper understanding of the mechanisms underlying nucleolar functions.

Enhancer-Mediated Formation of Nuclear Transcription Initiation Domains

Enhancers in higher eukaryotes and upstream activating sequences (UASs) in yeast have been shown to recruit components of the RNA polymerase II (Pol II) transcription machinery. At least a fraction of Pol II recruited to enhancers in higher eukaryotes initiates transcription and generates enhancer RNA (eRNA). In contrast, UASs in yeast do not recruit transcription factor TFIIH, which is required for transcription initiation. For both yeast and mammalian systems, it was shown that Pol II is transferred from enhancers/UASs to promoters. We propose that there are two modes of Pol II recruitment to enhancers in higher eukaryotes. Pol II complexes that generate eRNAs are recruited via TFIID, similar to mechanisms operating at promoters. This may involve the binding of TFIID to acetylated nucleosomes flanking the enhancer. The resulting eRNA, together with enhancer-bound transcription factors and co-regulators, contributes to the second mode of Pol II recruitment through the formation of a transcription initiation domain. Transient contacts with target genes, governed by proteins and RNA, lead to the transfer of Pol II from enhancers to TFIID-bound promoters.

Dynamics of Drosophila endoderm specification

During early Drosophila embryogenesis, a network of gene regulatory interactions orchestrates terminal patterning, playing a critical role in the subsequent formation of the gut. We utilized CRISPR gene editing at endogenous loci to create live reporters of transcription and light-sheet microscopy to monitor the individual components of the posterior gut patterning network across 90 min prior to gastrulation. We developed a computational approach for fusing imaging datasets of the individual components into a common multivariable trajectory. Data fusion revealed low intrinsic dimensionality of posterior patterning and cell fate specification in wild-type embryos. The simple structure that we uncovered allowed us to construct a model of interactions within the posterior patterning regulatory network and make testable predictions about its dynamics at the protein level. The presented data fusion strategy is a step toward establishing a unified framework that would explore how stochastic spatiotemporal signals give rise to highly reproducible morphogenetic outcomes.

Degree of Freedom of Gene Expression in Saccharomyces cerevisiae

The complexity of genome-wide gene expression has not yet been adequately addressed due to a lack of comprehensive statistical analyses. In the present study, we introduce degree of freedom (DOF) as a summary statistic for evaluating gene expression complexity. Because DOF can be interpreted by a state-space representation, application of the DOF is highly useful for understanding gene activities. We used over 11,000 gene expression data sets to reveal that the DOF of gene expression in Saccharomyces cerevisiae is not greater than 450. We further demonstrated that various degrees of freedom of gene expression can be interpreted by different sequence motifs within promoter regions and Gene Ontology (GO) terms. The well-known TATA box is the most significant one among the identified motifs, while the GO term "ribosome genesis" is an associated biological process. On the basis of transcriptional freedom, our findings suggest that the regulation of gene expression can be modeled using only a few state variables. IMPORTANCE Yeast works like a well-organized factory. Each of its components works in its own way, while affecting the activities of others. The order of all activities is largely governed by the regulation of gene expression. In recent decades, biologists have recognized many regulations for yeast genes. However, it is not known how closely the regulation links each gene together to make all components of the cell work as a whole. In other words, biologists are very interested in how many independent control factors are needed to operate an artificial "cell" that works the same as a real one. In this work, we suggested that only 450 control factors were sufficient to represent the regulation of all 5800 yeast genes.

Epigenetic imprinting alterations as effective diagnostic biomarkers for early-stage lung cancer and small pulmonary nodules

Background

Early lung cancer detection remains a clinical challenge for standard diagnostic biopsies due to insufficient tumor morphological evidence. As epigenetic alterations precede morphological changes, expression alterations of certain imprinted genes could serve as actionable diagnostic biomarkers for malignant lung lesions.

Results

Using the previously established quantitative chromogenic imprinted gene in situ hybridization (QCIGISH) method, elevated aberrant allelic expression of imprinted genes GNAS, GRB10, SNRPN and HM13 was observed in lung cancers over benign lesions and normal controls, which were pathologically confirmed among histologically stained normal, paracancerous and malignant tissue sections. Based on the differential imprinting signatures, a diagnostic grading model was built on 246 formalin-fixed and paraffin-embedded (FFPE) surgically resected lung tissue specimens, tested against 30 lung cytology and small biopsy specimens, and blindly validated in an independent cohort of 155 patients. The QCIGISH diagnostic model demonstrated 99.1% sensitivity (95% CI 97.5–100.0%) and 92.1% specificity (95% CI 83.5–100.0%) in the blinded validation set. Of particular importance, QCIGISH achieved 97.1% sensitivity (95% CI 91.6–100.0%) for carcinoma in situ to stage IB cancers with 100% sensitivity and 91.7% specificity (95% CI 76.0–100.0%) noted for pulmonary nodules with diameters ≤ 2 cm.

Conclusions

Our findings demonstrated the diagnostic value of epigenetic imprinting alterations as highly accurate translational biomarkers for a more definitive diagnosis of suspicious lung lesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01203-5.

TriTag: an integrative tool to correlate chromatin dynamics and gene expression in living cells

A wealth of single-cell imaging studies have contributed novel insights into chromatin organization and gene regulation. However, a comprehensive understanding of spatiotemporal gene regulation requires developing tools to combine multiple monitoring systems in a single study. Here, we report a versatile tag, termed TriTag, which integrates the functional capabilities of CRISPR-Tag (DNA labeling), MS2 aptamer (RNA imaging) and fluorescent protein (protein tracking). Using this tag, we correlate changes in chromatin dynamics with the progression of endogenous gene expression, by recording both transcriptional bursting and protein production. This strategy allows precise measurements of gene expression at single-allele resolution across the cell cycle or in response to stress. TriTag enables capturing an integrated picture of gene expression, thus providing a powerful tool to study transcriptional heterogeneity and regulation.

Nascent RNA analyses: tracking transcription and its regulation

The programmes that direct an organism's development and maintenance are encoded in its genome. Decoding of this information begins with regulated transcription of genomic DNA into RNA. Although transcription and its control can be tracked indirectly by measuring stable RNAs, it is only by directly measuring nascent RNAs that the immediate regulatory changes in response to developmental, environmental, disease and metabolic signals are revealed. Multiple complementary methods have been developed to quantitatively track nascent transcription genome-wide at nucleotide resolution, all of which have contributed novel insights into the mechanisms of gene regulation and transcription-coupled RNA processing. Here we critically evaluate the array of strategies used for investigating nascent transcription and discuss the recent conceptual advances they have provided.

RNA Structure and Cellular Applications of Fluorescent Light-Up Aptamers

The cellular functions of RNA are not limited to their role as blueprints for protein synthesis. In particular, noncoding RNA, such as, snRNAs, lncRNAs, miRNAs, play important roles. With increasing numbers of RNAs being identified, it is well known that the transcriptome outnumbers the proteome by far. This emphasizes the great importance of functional RNA characterization and the need to further develop tools for these investigations, many of which are still in their infancy. Fluorescent light-up aptamers (FLAPs) are RNA sequences that can bind nontoxic, cell-permeable small-molecule fluorogens and enhance their fluorescence over many orders of magnitude upon binding. FLAPs can be encoded on the DNA level using standard molecular biology tools and are subsequently transcribed into RNA by the cellular machinery, so that they can be used as fluorescent RNA tags (FLAP-tags). In this Minireview, we give a brief overview of the fluorogens that have been developed and their binding RNA aptamers, with a special focus on published crystal structures. A summary of current and future cellular FLAP applications with an emphasis on the study of RNA-RNA and RNA-protein interactions using split-FLAP and Förster resonance energy transfer (FRET) systems is given.

Phase Separation and Transcription Regulation: Are Super-Enhancers and Locus Control Regions Primary Sites of Transcription Complex Assembly?

It is proposed that the multiple enhancer elements associated with locus control regions and super-enhancers recruit RNA polymerase II and efficiently assemble elongation competent transcription complexes that are transferred to target genes by transcription termination and transient looping mechanisms. It is well established that transcription complexes are recruited not only to promoters but also to enhancers, where they generate enhancer RNAs. Transcription at enhancers is unstable and frequently aborted. Furthermore, the Integrator and WD-domain containing protein 82 mediate transcription termination at enhancers. Abortion and termination of transcription at the multiple enhancers of locus control regions and super-enhancers provide a large pool of elongation competent transcription complexes. These are efficiently captured by strong basal promoter elements at target genes during transient looping interactions.