Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
July 25th, 2022
4.3K views
We present a protocol to acquire chemical images with broadband stimulated Raman scattering (SRS) microscopy. Based on an SRS microscope that operates with differential multichannel-lock-in detection, the protocol describes the sample preparation, adjustment of the SRS apparatus, and chemometrics to disentangle different constituents of chemically heterogeneous samples.
Overview
This article presents a protocol for acquiring chemical images using broadband stimulated Raman scattering (SRS) microscopy. The method allows for label-free and non-invasive imaging of chemical constituents in biological samples.
Key Study Components
Area of Science
- Neuroscience
- Biochemistry
- Microscopy Techniques
Background
- Stimulated Raman scattering microscopy enables rapid measurement of vibrational spectra.
- It is applicable in imaging cells and tissues.
- The protocol addresses challenges related to broadband optical sources and detection chains.
- Sample preparation involves using PMMA and polystyrene microbeads.
Purpose of Study
- To provide a detailed protocol for SRS microscopy.
- To enable the localization and quantification of chemical constituents.
- To enhance imaging techniques in biological and biomedical sciences.
Methods Used
- Preparation of samples using PMMA and polystyrene microbeads.
- Adjustment of optical components for optimal SRS signal detection.
- Use of a photodiode and oscilloscope for beam profiling.
- Raster scanning of samples to acquire SRS spectra.
Main Results
- Successful acquisition of chemical images from samples.
- Demonstration of the effectiveness of the SRS microscopy protocol.
- Identification of chemical constituents based on spectral profiles.
- Optimization of detection methods for enhanced imaging quality.
Conclusions
- The SRS microscopy protocol is effective for chemical imaging.
- It provides a non-invasive method for analyzing biological samples.
- Future applications may expand into various fields of research.
Frequently Asked Questions
What is stimulated Raman scattering microscopy?
Stimulated Raman scattering microscopy is a technique that allows for label-free imaging of chemical constituents by measuring vibrational spectra.
What are the main applications of this protocol?
The protocol can be applied in biological and biomedical sciences to image cells and tissues.
What challenges does this protocol address?
It addresses challenges related to the broadband optical source and the detection chain in SRS microscopy.
How are samples prepared for SRS microscopy?
Samples are prepared by mixing PMMA and polystyrene microbeads on a microscope cover slip and allowing them to dry.
What is the significance of the SRS signal?
The SRS signal allows for the identification and quantification of chemical constituents in the sample.
Can this method be used for live cell imaging?
Yes, SRS microscopy is a non-invasive technique suitable for live cell imaging.
Executive Industry Relevance
Broadband stimulated Raman scattering (SRS) microscopy enables rapid, label-free chemical imaging with hyperspectral resolution, directly supporting early discovery and mechanistic de-risking in biopharma R&D. By extracting full vibrational spectra per pixel, this approach enhances chemical specificity and quantitative analysis of complex biological samples. Its integration into discovery workflows increases predictive confidence and informs portfolio triage at critical inflection points.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables direct interrogation of molecular composition in cells and tissues for hypothesis-driven research.
- Supports functional target validation by mapping and quantifying chemical constituents without labels.
- Improves mechanistic de-risking by providing multiplexed chemical information at high spatial resolution.
- Facilitates predictive confidence in target engagement and pathway analysis.
Screening & Assay Development
- Prepares validated, label-free biological systems for downstream screening workflows.
- Delivers reproducible, quantitative hyperspectral data for assay standardization.
- Enables high-throughput, multiplexed compound evaluation by capturing multiple chemical signatures simultaneously.
- Supports platform scalability and reuse across diverse sample types.
Translational & Preclinical Research
- Aligns chemical imaging outputs with disease-relevant biomarker discovery when applied to tissue samples.
- Provides continuity from discovery through preclinical validation by enabling quantitative, non-invasive analysis.
- Reduces translational risk by supporting robust chemical characterization of preclinical models.
- Enhances predictive de-risking for candidate advancement decisions.
Pipeline & Workflow Integration
Broadband SRS microscopy fits within the early discovery to lead identification continuum, providing a reusable analytical capability for chemical mapping and quantification.
- Discovery Biology: Supports hypothesis testing and pathway clarification through multiplexed chemical imaging.
- Screening: Delivers reproducible, quantitative outputs for assay readiness and compound evaluation.
- Analytics: Provides hyperspectral measurements and chemometric analysis for robust comparison of sample conditions.
- Translational Research: Enables alignment with biomarker strategies and preclinical model validation when applied to relevant tissues.
- Enterprise Reuse: Functions as a scalable, label-free imaging platform adaptable across multiple R&D programs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in chemical imaging.
- Operational Value: Standardizes workflows with reproducible, high-throughput, label-free analysis.
- Strategic Value: Informs go/no-go decisions and enhances capital efficiency by providing robust chemical data early.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of discovery and preclinical assets.
Implementation Considerations
- Requires expertise in nonlinear optics, spectroscopy, and chemometric data analysis.
- Demands specialized instrumentation, including broadband optical sources and multichannel detection systems.
- Necessitates cross-team standardization for sample preparation and data interpretation.
- Adaptation across different biological models may require protocol optimization.
- Current spectral range may be limited; extension to fingerprint regions depends on optical source optimization.
Biopharma FAQs
Why does null hypothesis testing matter for SRS-based target validation?
Null hypothesis testing in broadband SRS imaging ensures that observed chemical differences between samples are statistically significant, supporting robust target validation. This approach reduces false positives in chemical mapping and strengthens confidence in mechanistic findings. Reliable statistical analysis underpins decision-making for target advancement.
How does independent variable isolation fit in SRS imaging workflows?
Isolating independent variables, such as specific chemical constituents, allows SRS microscopy to attribute spectral changes directly to experimental manipulations. This clarity is essential for dissecting pathway effects and validating biological hypotheses in early discovery. It streamlines mechanistic de-risking and supports reproducible R&D outcomes.
What do quantitative dependent variable measurements enable in hyperspectral SRS?
Quantitative measurements of dependent variables, like constituent concentrations, enable precise mapping and comparison of chemical profiles across samples. This capability supports assay development, compound screening, and translational research by providing actionable, reproducible data. It enhances predictive confidence in both discovery and preclinical phases.
Why are replication requirements critical for SRS data in cross-functional teams?
Replication ensures that SRS-derived chemical maps and spectra are consistent across experiments and operators, facilitating cross-functional collaboration. Standardized, reproducible outputs are essential for integrating chemical imaging data into broader R&D workflows. This reliability supports enterprise-wide adoption and portfolio decision-making.
What statistical analysis capabilities are needed before SRS implementation?
Robust statistical analysis, including chemometric methods and noise quantification, is required to interpret hyperspectral SRS data accurately. These capabilities enable teams to distinguish true chemical signals from background variation and validate findings for downstream applications. Proper analytics are foundational for reliable implementation in biopharma pipelines.
