Cryo-Structured Illumination Microscopic Data Collection from Cryogenically Preserved Cells
May 28th, 2021
5.7K views
This protocol demonstrates how to image biological cryo-preserved samples using cryo-structured illumination microscopy. We demonstrate the methodology by imaging the cytoskeleton of U2OS cells.
Overview
This article details the use of three-dimensional structured illumination microscopy (3D SIM) under cryogenic conditions (cryoSIM) for super-resolution imaging of fluorescently labeled cellular structures. The protocol enables high-resolution visualization of cellular ultrastructure in whole cells, compatible with correlative workflows involving X-ray microscopy. The method is demonstrated using U2OS cells labeled for mitochondria and tubulin.
Key Study Components
Area of Science
- Super-resolution fluorescence microscopy
- Cryogenic imaging
- Cell biology
- Correlative imaging techniques
Background
- Conventional fluorescence microscopy is limited in resolution for imaging subcellular structures.
- Structured illumination microscopy (SIM) enhances resolution, enabling visualization of molecular processes in cells.
- Cryogenic preservation maintains native cellular ultrastructure and reduces photodamage.
- Correlative workflows combine fluorescence imaging with electron or X-ray microscopy for comprehensive structural and functional analysis.
Purpose of Study
- To provide a detailed protocol for performing 3D SIM imaging at cryogenic temperatures using the cryoSIM microscope.
- To demonstrate the compatibility of cryoSIM with subsequent X-ray microscopy for correlative imaging.
- To offer practical recommendations for sample preparation, fluorophore selection, and imaging parameter optimization.
Methods Used
- Preparation and handling of cryogenically preserved biological samples (U2OS cells labeled for mitochondria and tubulin).
- Operation of the cryoSIM microscope, including sample loading, stage cooling with liquid nitrogen, and imaging setup.
- Acquisition of visible light mosaics and super-resolution fluorescence images using structured illumination.
- Image processing and artifact assessment using software tools such as SIMCheck and stitchEm.
Main Results
- CryoSIM enables rapid, super-resolution imaging of whole cells at cryogenic temperatures using conventional fluorophores and low light doses.
- High-resolution images reveal detailed localization of mitochondria and the arrangement of microtubules within cells.
- The protocol supports identification and marking of regions of interest for targeted imaging.
- SIM reconstruction artifacts can be detected and assessed using dedicated software tools.
Conclusions
- CryoSIM provides significant resolution improvement over standard epifluorescence microscopy for cryopreserved samples.
- The method is compatible with correlative imaging workflows, enabling integration with cryo-soft X-ray tomography.
- Careful sample handling and parameter optimization are critical for data quality and preservation of ultrastructure.
Frequently Asked Questions
What is the main advantage of using cryoSIM over conventional fluorescence microscopy?
CryoSIM offers super-resolution imaging at cryogenic temperatures, providing higher spatial resolution and better preservation of native cellular ultrastructure compared to conventional fluorescence microscopy.
How are samples prepared and maintained during cryoSIM imaging?
Samples are cryogenically preserved and kept submerged or close to liquid nitrogen throughout the process to prevent de-vitrification and maintain structural integrity.
What types of samples and fluorophores are compatible with cryoSIM?
The protocol is compatible with a variety of biological samples and conventional fluorophores, as demonstrated with U2OS cells labeled for mitochondria and tubulin.
How are regions of interest identified and imaged?
Visible light mosaics and fluorescence maps are used to locate and mark biologically interesting cells or structures, which are then targeted for super-resolution imaging.
How are SIM reconstruction artifacts detected?
Artifacts can be identified using the SIMCheck plugin for ImageJ, which highlights areas susceptible to reconstruction errors based on modulation contrast.
Can cryoSIM images be correlated with other imaging modalities?
Yes, cryoSIM is designed for compatibility with correlative workflows, allowing subsequent imaging with techniques such as cryo-soft X-ray tomography.
What precautions are necessary to ensure high-quality cryoSIM data?
Maintaining cryogenic conditions, optimizing exposure times, and monitoring dynamic range are essential to prevent sample damage and ensure high-quality imaging results.
Executive Industry Relevance
Cryo-structured illumination microscopy (cryoSIM) enables super-resolution imaging of cryogenically preserved cells, providing unprecedented insight into cellular ultrastructure while maintaining native biological context. This capability is strategically positioned for correlative workflows, supporting integration with X-ray tomography and facilitating high-confidence target validation in early discovery. The method enhances predictive confidence and de-risks mechanistic hypotheses across the biopharma R&D pipeline.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables high-resolution visualization of subcellular structures for functional target validation.
- Supports mechanistic de-risking by correlating molecular localization with ultrastructural context.
- Facilitates hypothesis-driven interrogation of cellular responses to internal or external cues.
- Improves predictive confidence for portfolio triage and early-stage decision making.
Screening & Assay Development
- Prepares validated, structurally preserved biological systems for downstream screening workflows.
- Delivers quantitative, reproducible imaging outputs for assay standardization.
- Enables reliable identification and marking of regions of interest for targeted compound evaluation.
- Supports scalability and platform reuse in super-resolution imaging pipelines.
Translational & Preclinical Research
- Aligns imaging outputs with disease-relevant cellular models for translational biomarker studies.
- Maintains continuity from discovery through preclinical validation by preserving ultrastructure.
- Reduces biological risk in preclinical advancement decisions through correlative imaging data.
- Provides mechanistic insights that inform risk-adjusted progression of therapeutic candidates.
Pipeline & Workflow Integration
CryoSIM integrates into the discovery-to-preclinical continuum, bridging high-resolution imaging with correlative structural analysis and supporting lead identification and validation workflows.
- Discovery Biology: Enables robust hypothesis testing and pathway clarification by visualizing molecular and structural relationships.
- Screening: Provides reproducible, quantitative imaging data for assay readiness and compound triage.
- Analytics: Generates high-content measurements and supports artifact detection for reliable data interpretation.
- Translational Research: Facilitates biomarker alignment and continuity across model systems when combined with X-ray tomography.
- Enterprise Reuse: Establishes a reusable imaging capability for multi-modal, cross-project applications.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in target validation.
- Operational Value: Standardizes imaging protocols and ensures reproducibility across teams and projects.
- Strategic Value: Enables informed go/no-go decisions and enhances capital efficiency by reducing late-stage biological risk.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of therapeutic programs.
Implementation Considerations
- Requires expertise in cryogenic sample handling and super-resolution microscopy operation.
- Demands specialized instrumentation, including cryo-stages and compatible imaging software.
- Necessitates cross-team standardization of imaging parameters and artifact assessment protocols.
- Must adapt protocols for different cell types and fluorophores to ensure data quality.
- Careful management of cryogenic conditions and exposure settings is critical to avoid sample damage and data artifacts.
Biopharma FAQs
Why does null hypothesis testing matter for cryoSIM-based target validation?
Null hypothesis testing in cryoSIM workflows enables objective assessment of whether observed molecular localizations or structural changes are statistically significant, supporting robust target validation. This reduces the risk of false positives in early discovery and informs confident portfolio decisions.
How does independent variable isolation fit into cryoSIM imaging pipelines?
Isolating independent variables, such as specific fluorophore labeling or controlled environmental cues, ensures that observed ultrastructural changes in cryoSIM images can be attributed to defined experimental conditions. This strengthens mechanistic de-risking and supports reproducible discovery workflows.
What do quantitative dependent variable measurements enable in cryoSIM workflows?
Quantitative measurements of fluorescence intensity, spatial localization, and structural arrangement in cryoSIM images enable precise comparison across experimental groups. These outputs support data-driven decisions in assay development and target prioritization.
Why are replication requirements critical for cross-functional collaboration in cryoSIM imaging?
Replication ensures that cryoSIM imaging results are reproducible across different operators, instruments, and sample batches, facilitating reliable data sharing and interpretation among discovery, screening, and translational teams.
What statistical analysis capabilities are required before implementing cryoSIM in R&D pipelines?
Robust statistical analysis tools are needed to assess image quality, detect reconstruction artifacts, and validate quantitative outputs from cryoSIM data. These capabilities are essential for ensuring data integrity and supporting regulatory or portfolio advancement decisions.
Chapters in this video
0:04
Introduction
1:09
Preparation of the Cryo-Stage
2:08
Transfer of the Sample Storage Box into the Cryo-Stage
3:34
Stage Docking and Focusing
5:03
Brightfield Mosaic Acquisition and Identification of Areas of Interest
6:48
Data Collection
8:59
After Imaging
9:38
Results: Cryo-structured Illumination Microscopic Imaging
11:00
Conclusion
