Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH
September 20th, 2020
Single molecule RNA fluorescence in situ hybridization (smFISH) is a method to accurately quantify levels and localization of specific RNAs at the single cell level. Here, we report our validated lab protocols for wet-bench processing, imaging and image analysis for single cell quantification of specific RNAs.
Overview
Single molecule RNA fluorescence in situ hybridization (smFISH) is a powerful technique for quantifying RNA levels and localization at the single cell level. This method enables the analysis of cell-to-cell and allele-by-allele variation in RNA, providing insights into gene transcription and RNA response to external stimuli.
Key Study Components
Area of Science
- Neuroscience
- Cell Biology
- Molecular Biology
Background
- smFISH allows for the investigation of RNA content in individual cells.
- It provides spatial information about RNA distribution.
- This method is crucial for understanding gene expression dynamics.
- It can reveal variations in RNA levels due to external factors.
Purpose of Study
- To validate lab protocols for smFISH.
- To enable accurate quantification of specific RNAs.
- To facilitate imaging and analysis of RNA at the single cell level.
Methods Used
- Cells are treated with an estrogen receptor agonist.
- Cells are fixed using a fixation buffer.
- Washing steps are performed with cold sterile PBS.
- Cells are incubated in 70% ethanol for preservation.
Main Results
- smFISH accurately quantifies RNA levels.
- It reveals spatial localization of specific RNAs.
- Variations in RNA content can be analyzed effectively.
- Results provide insights into cellular responses to stimuli.
Conclusions
- smFISH is a validated method for single cell RNA analysis.
- It enhances understanding of gene transcription processes.
- This technique is valuable for studying RNA dynamics in response to external factors.
Frequently Asked Questions
Executive Industry Relevance
Single molecule FISH (smFISH) enables precise quantification of transcriptionally active alleles and RNA localization at the single cell level, addressing the challenge of cellular heterogeneity in gene expression analysis. This capability enhances predictive confidence in early discovery and target validation by revealing cell-to-cell and allele-specific transcriptional responses to stimuli. Integrating smFISH into discovery pipelines supports risk-adjusted decision-making and portfolio prioritization by providing high-resolution, quantitative data on gene regulation dynamics.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables direct visualization and quantification of nascent and mature RNA at the single cell and allele level.
- Supports mechanistic de-risking by distinguishing transcriptional activity in response to specific treatments.
- Improves predictive confidence for target engagement and pathway modulation.
- Facilitates functional validation of gene targets through spatial and quantitative RNA analysis.
Screening & Assay Development
- Provides validated, quantitative readouts for assay standardization and reproducibility.
- Enables high-content screening of transcriptional responses across diverse cell populations.
- Supports development of scalable imaging and analysis pipelines for downstream workflows.
- Delivers robust data for compound evaluation based on transcriptional modulation.
Translational & Preclinical Research
- Aligns single cell transcriptional data with disease-relevant models for translational biomarker discovery.
- Ensures continuity from early discovery through preclinical validation by tracking gene expression changes.
- Reduces biological ambiguity in preclinical models by resolving cell-to-cell variability.
- Supports risk-adjusted advancement decisions with quantitative, spatially resolved RNA data.
Pipeline & Workflow Integration
smFISH integrates into the discovery continuum from early hypothesis testing through lead identification and preclinical research, providing a reusable platform for quantitative single cell analysis.
- Discovery Biology: Enables hypothesis testing and pathway clarification by quantifying transcriptional activity at single cell and allele resolution.
- Screening: Delivers reproducible, quantitative outputs for assay development and compound screening.
- Analytics: Provides spatial and quantitative measurements of nascent and mature RNA for robust data comparison.
- Translational Research: Connects single cell gene expression data to disease models and biomarker strategies.
- Enterprise Reuse: Establishes a standardized, scalable workflow for ongoing R&D applications across programs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in target validation.
- Operational Value: Standardizes single cell RNA quantification and imaging for reproducibility and scalability.
- Strategic Value: Informs go/no-go decisions and enhances capital efficiency by providing high-resolution data early in the pipeline.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of discovery programs.
Implementation Considerations
- Requires expertise in single cell imaging, probe design, and quantitative image analysis.
- Demands advanced microscopy platforms and computational infrastructure for data processing.
- Necessitates cross-team standardization of sample preparation and analysis protocols.
- Adaptation may be needed for different cell types or tissue models.
- High-quality image acquisition and signal-to-noise optimization are critical for accurate quantification.
Biopharma FAQs
Chapters in this video
0:04
Introduction
0:34
RNA Fluorescence In Situ Hybridization (FISH) Fixation
1:14
RNA FISH Hybridization
2:16
Imaging Preparation
3:08
High Resolution Microscopy and Image Processing
4:05
Image Analysis
4:45
Results: Representative Image Segmentation and E2-Induced GREB1 Quantification
5:56
Conclusion
