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By combining sample-expansion hydrogel chemistry with label-free chemical-specific stimulated Raman scattering microscopy, the protocol describes how to achieve label-free super-resolution volumetric imaging in biological samples. With an additional machine learning image segmentation algorithm, protein-specific multi-component images in tissues without antibody labeling were obtained.
The universal utilization of fluorescence microscopy, especially super-resolution microscopy, has greatly advanced knowledge about modern biology. Conversely, the requirement of fluorophore labeling in fluorescent techniques poses significant challenges, such as photobleaching and non-uniform labeling of fluorescent probes and prolonged sample processing. In this protocol, the detailed working procedures of vibrational imaging of swelled tissue and analysis (VISTA) are presented. VISTA circumvents obstacles associated with fluorophores and achieves label-free super-resolution volumetric imaging in biological samples with spatial resolution down to 78 nm. The procedure is established by embedding cells and tissues in hydrogel, isotropically expanding the hydrogel sample hybrid, and visualizing endogenous protein distributions by vibrational imaging with stimulated Raman scattering microscopy. The method is demonstrated on both cells and mouse brain tissues. Highly correlative VISTA and immunofluorescence images were observed, validating the protein origin of imaging specificities. Exploiting such correlation, a machine learning-based image-segmentation algorithm was trained to achieve multi-component prediction of nuclei, blood vessels, neuronal cells, and dendrites from label-free mouse brain images. The procedure was further adapted to investigate pathological poly-glutamine (polyQ) aggregates in cells and amyloid-beta (Aβ) plaques in brain tissues with high throughput, justifying its potential for large-scale clinical samples.
The development of optical imaging methods has revolutionized the understanding of modern biology because they provide unprecedented spatial and temporal information of targets across different scales, from subcellular proteins to whole organs1. Among them, fluorescence microscopy is the most well-established, with a large palette of organic dyes with high extinction coefficients and quantum yields2, easy-to-use genetic-encoded fluorescent proteins3, and super-resolution methods such as STED, PALM, and STORM for imaging nanometer-scale structures4,5. In addition, recent advancements in sample engineering and preservation chemistry, which expand specimens embedded in swellable polymer hydrogels6,7,8, enable sub-diffraction limited resolution on conventional fluorescence microscopes. For instance, typical expansion microscopy (ExM) effectively enhances the image resolution by four times with fourfold isotropic sample expansion7.
Despite its advantages, super-resolution fluorescence microscopy shares limitations that originate from fluorophore labeling. First, photobleaching and inactivation of fluorophores compromise the capacity for repetitive and quantitative fluorescence evaluations. Photobleaching is an inevitable event when light keeps pumping electrons into electronically excited states9. Second, labeling the fluorophores to the desired targets is not always a straightforward task. For instance, immunostaining demands a long and laborious sample preparation process and hinders imaging throughput10. It could also introduce artifacts due to inhomogeneous antibody-labeling, especially deep inside tissues11. Moreover, proper labeling strategies that target fluorophores for the desired proteins might be underdeveloped. For example, extensive screenings were required to find effective antibodies for Aβ plaques12. Smaller organic dyes, such as Congo red, often have limited specificity, only staining the core of the Aβ plaque. It is, therefore, highly desirable to develop a label-free super-resolution modality that circumvents the drawbacks of fluorophore-labeling and provides complementary high-resolution imaging from cells to tissues, and even to large-scale human samples.
Raman microscopy provides label-free contrast for chemical-specific structures and maps out the distribution of otherwise invisible chemical bonds by looking at the excited vibrational transitions13. In particular, stimulated Raman scattering (SRS) imaging on label-free or tiny-labeled samples has been demonstrated to have similar speed and resolution to fluorescence microscopy14,15. For example, healthy brain region has been readily differentiated from tumor-infiltrated region in human and mouse tissues16,17. Aβ plaques were also clearly imaged by targeting protein CH3 vibration (2940 cm−1) and amide I (1660 cm−1) on a fresh-frozen brain slice without any labeling18. Raman scattering, therefore, offers robust label-free contrast that overcomes the limitations of fluorophores. The question then became how one can accomplish super-resolution capacity using Raman scattering, which could reveal nanoscale structural details and functional implications in biological samples.
Although extensive efforts have been made to achieve super-resolution for Raman microscopy with elegant optic instrumentations, the resolution enhancement on biological samples has been rather limited19,20,21. Here, based on the recent works22,23, we present a protocol that combines a sample-expansion strategy with stimulated Raman scattering for super-resolution label-free vibrational imaging, named Vibrational Imaging of Swelled Tissues and Analysis (VISTA). First, cells and tissues were embedded in hydrogel matrixes through an optimized protein-hydrogel hybridization protocol. The hydrogel tissue hybrids were then incubated in detergent-rich solutions for delipidation, followed by expansion in water. The expanded samples were then imaged by a regular SRS microscope by targeting CH3 vibrations from retained endogenous proteins. VISTA, owing to its label-free imaging feature, bypasses photobleaching and inhomogeneous labeling arising from fluorophore labeling, with much higher sample processing throughput. This is also the first sub-100 nm (down to 78 nm) label-free imaging reported. No additional optical instrumentation besides typical SRS setup22,24 is required, making it readily applicable. With correlative VISTA and immunofluorescence images, an established machine-learning image-segmentation algorithm was trained25,26 to generate protein-specific multiplex images from single-channel images. The method was further applied to investigate Aβ plaques in mouse brain tissues, providing a holistic image suited for sub-phenotyping based on the fine views of the plaque core and peripheral filaments surrounded by cell nuclei and blood vessels.
All animal procedures performed in this study were approved by the California Institute of Technology Institutional Animal Care and Use Committee (IACUC), and the protocol procedures complied with all relevant ethical regulations.
1. Preparation of stock solutions for fixation and sample expansion
2. Preparation of mammalian cell samples
3. Preparation of mouse brain samples
4. Hydrogel embedding, denaturation, and expansion of cell and tissue samples
5. Label-free imaging of endogenous protein distribution in expanded cell and tissue samples
6. Correlative VISTA and fluorescent imaging of immuno-labeled and expanded tissue samples
7. Construction, training, and validation of U-Net architecture
NOTE: Installation on Linux is recommended. A graphics card with >10 GB of RAM is required.
8. VISTA combined with U-Net predictions for protein-specific multiplexity in label-free images
After establishing the working principle of the imaging and analysis method, image registration was done to evaluate the expansion ratio and to ensure isotropic expansion during sample processing (Figure 1A,B). Both untreated and VISTA samples were imaged while targeting the bond vibration at 2940 cm−1, which originates from CH3 of endogenous proteins. In untreated samples, the protein-rich structures like nuclei were dark due to the overwhelming ...
In summary, we present the protocol for VISTA, which is a label-free modality to image protein-rich cellular and subcellular structures of cells and tissues. By targeting endogenous CH3 from proteins in hydrogel-embedded cell and tissues, the method achieves an effective imaging resolution down to 78 nm in biological samples and resolves minor extrusion in Huntingtin aggregates and fibrils in Aβ plaques. This technique is the first instance to report sub-100 nm resolution for label-free imaging modalities...
The authors declare no competing interests.
We acknowledge the Caltech Biological Imaging Facility for software support. L.W. acknowledges the support of the National Institutes of Health (NIH Director's New Innovator Award, DP2 GM140919-01), Amgen (Amgen Early Innovation Award), and the start-up funds from the California Institute of Technology.
Name | Company | Catalog Number | Comments |
1.0 M Tris pH 8 | Sigma-Aldrich | 648314 | |
16% Paraformaldehyde | Electron microscopy science | 15710 | diluted to 4% in PBS |
25x water immersion objective | Olympus | XLPLN25XWMP2 | NA 1.05 |
5XFAD Mice | Mutant Mouse Resource and Research Centers and the Jackson Laboratory | B6SJL-Tg (APPSwFlLon, PSEN1*M146L*L286 V) 6799Vas/Mmjax | Alzheimer brain |
60x water immersion objective | Olympus | UPLSAPO60XWIR | NA 1.2 |
Acrylamide | Sigma-Aldrich | A9099 | |
ammonium persulfate | Sigma-Aldrich | A3678 | |
anti-MAP2 | Cell Signaling Technology | 8707 | |
anti-NeuN | Cell Signaling Technology | 24307 | |
borosilicate coverslip #1.5 | Fisher Scientific | 1254581 | |
C57BL/6J Mice | Jackson Laboratory (JAX) | 664 | Normal mice |
D2O | Sigma-Aldrich | 151882 | for SRS calibration |
DAPI | Thermo Fisher | D1306 | |
DMEM | GIBCO | 10566-016 | |
FBS | GIBCO | A4766 | |
glass slide 3" x 1" x 1 mm | VWR | 16004-430 | |
goat anti-chicken IgY, Alexa Fluor 647 | Invitrogen | A-21449 | |
goat anti-mouse IgG, Alexa Fluor 647 | Invitrogen | A-21236 | |
goat anti-rabbit IgG, Alexa Fluor 488 | Invitrogen | A-11034 | |
goat anti-rat IgG, Alexa Fluor 568 | Invitrogen | A-11077 | |
Grace Bio-Labs Press-To-Seal silicone isolators | Sigma-Aldrich | GBL664108 | microscope spacer |
Htt-97Q-GFP Plasmid | Gift from Prof. R. Kopito and Prof. F.-U.Hartl. | ||
Laser scanning microscope | Olympus | FV3000 | laser scanning confocal microscope |
lipofectamine 3000 | Thermo Fisher | L3000001 | transfection agent |
Lycopersicon Esculentum Lectin DyLight®594 (lectin) | Vector Laboratories | DL-1177-1 | |
Microscope spacer | Grace Bio-Labs | 621502 | |
N,N′-methylenebisacrylamide (BIS) | Sigma-Aldrich | M1533 | bought as 2% solution in water |
Nuclease free water | Thermo Fisher | 10977-015 | |
Penicillin-Streptomycin | GIBCO | 15140-122 | |
poly-strene beads | Sigma-Aldrich | 43302 | for resolution characterization |
Sodium Acrylate | Sigma-Aldrich | 408220 | |
sodium dodecyl sulfate | Sigma-Aldrich | 71725 | |
soft-wool paint brush #3 | TANIS | 000333 | |
SRS Laser | A.P.E | picoEmerald | 2ps pulse width |
tetramethylethylenediamine | Sigma-Aldrich | T9281 | |
Tissue culture flask 25 cm2 | Corning | 430639 | |
Triton X-100 | Sigma-Aldrich | T8787 | |
Tween-20 | Sigma-Aldrich | P9416 | |
tweezer | Fine Science Tool | 11295-51 | |
Vibrotome | Leica | VT1200S | the vibratome |
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