Within cells, the spatial compartmentalization of thousands of distinct proteins serves a multitude of diverse biochemical needs. Correlative super-resolution (SR) fluorescence and electron microscopy (EM) can elucidate protein spatial relationships to global ultrastructure, but has suffered from tradeoffs of structure preservation, fluorescence retention, resolution, and field of view. We developed a platform for three-dimensional cryogenic SR and focused ion beam–milled block-face EM across entire vitreously frozen cells. The approach preserves ultrastructure while enabling independent SR and EM workflow optimization. We discovered unexpected protein-ultrastructure relationships in mammalian cells including intranuclear vesicles containing endoplasmic reticulum–associated proteins, web-like adhesions between cultured neurons, and chromatin domains subclassified on the basis of transcriptional activity. Our findings illustrate the value of a comprehensive multimodal view of ultrastructural variability across whole cells.

words):Living cells function through the spatial compartmentalization of thousands of distinct proteins serving a multitude of diverse biochemical needs. Correlative super-resolution (SR) fluorescence and electron microscopy (EM) has emerged as a pathway to directly view nanoscale protein relationships to the underlying global ultrastructure, but has traditionally suffered from tradeoffs of structure preservation, fluorescence retention, resolution, and field of view. We developed a platform for three-dimensional correlative cryogenic SR and focused ion beam milled block-face EM across entire vitreously frozen cells that addresses these issues by preserving native ultrastructure and enabling independent SR and EM workflow optimization. Application to a variety of biological systems revealed a number of unexpected protein-ultrastructure relationships and underscored the value of a comprehensive multimodal view of ultrastructural variability across whole cells. modalities (supplementary note 1, table S1), allowing specific molecular components to be visualized at nanoscale resolution in the context of the crowded intracellular environment.However, SR/EM correlation often involves tradeoffs in sample preparation between the retention of fluorescent labels, sufficiently dense heavy metal staining for high contrast EM, and faithful preservation of ultrastructure, particularly when chemical fixation is used (19)(20)(21)(22).Here we describe a pipeline ( fig. S1) for correlative cryo-SR/FIB-SEM imaging of whole cells designed to address these issues. Specifically, cryogenic, as opposed to room temperature, SR performed after high pressure freezing (HPF), allowed us to use a standard EM sample preparation protocol without compromise. We used cryogenic 3D structured illumination (SIM) and single molecule localization (SMLM) microscopy for SR protein specific contrast with 3D FIB-SEM for global contrast of subcellular ultrastructure. The SR modality highlights features not readily apparent from the EM data alone, such as exceptionally long or convoluted endosomes, and permits unique classification of vesicles of like morphology, such as lysosomes, peroxisomes, and mitochondrial-derived vesicles. Cell-wide 3D correlation also reveals unexpected localization patterns of proteins, including intranuclear vesicles positive for an ER marker, intricate web-like structures of adhesion proteins at cell-cell junctions, and heterogeneity in euchromatin or heterochromatin recruitment of transcriptionally-associated histone H3.3 and heterochromatin protein 1α (HP1α) in the nuclei of neural progenitor cells as they transition into differentiated neurons). More generally, whole cell cryo-SR/FIB-SEM can reveal compartmentalized proteins within known subcellular components, help discover new subcellular components, and classify unknown EM morphologies and their roles in cell biology. Cryogenic SR below 10K: motivations and photophysical characterization

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83–91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.

Extensive remodeling of the extracellular matrix (ECM) occurs in many epithelial cancers. For example, in ovarian cancer, upregulation of collagen isoform type III has been linked to invasive forms of the disease, and this change may be a potential biomarker. To examine this possibility, we implemented wavelength-dependent second harmonic generation circular dichroism (SHG-CD) imaging microscopy to quantitatively determine changes in chirality in ECM models comprised of different Col I/Col III composition. In these models, Col III was varied between 0 and 40%, and we found increasing Col III results in reduced net chirality, consistent with structural biology studies of Col I and III in tissues where the isoforms comingle in the same fibrils. We further examined the wavelength dependence of the SHG-CD to both optimize the response and gain insight into the underlying mechanism. We found using shorter SHG excitation wavelengths resulted in increased SHG-CD sensitivity, where this is consistent with the electric-dipole-coupled oscillator model suggested previously for the nonlinear chirality response from thin films. Moreover, the sensitivity is further consistent with the wavelength dependency of SHG intensity fit to a two-state model of the two-photon absorption in collagen. We also provide experimental calibration protocols to implement the SHG-CD modality on a laser scanning microscope. We last suggest that the technique has broad applicability in probing a wide range of diseased states with changes in collagen molecular structure.

BackgroundOvarian cancer remains the most deadly gynecological cancer with a poor aggregate survival rate; however, the specific rates are highly dependent on the stage of the disease upon diagnosis. Current screening and imaging tools are insufficient to detect early lesions and are not capable of differentiating the subtypes of ovarian cancer that may benefit from specific treatments.MethodAs an alternative to current screening and imaging tools, we utilized wavelength dependent collagen-specific Second Harmonic Generation (SHG) imaging microscopy and optical scattering measurements to probe the structural differences in the extracellular matrix (ECM) of normal stroma, benign tumors, endometrioid tumors, and low and high-grade serous tumors.ResultsThe SHG signatures of the emission directionality and conversion efficiency as well as the optical scattering are related to the organization of collagen on the sub-micron size scale and encode structural information. The wavelength dependence of these readouts adds additional characterization of the size and distribution of collagen fibrils/fibers relative to the interrogating wavelengths. We found a strong wavelength dependence of these metrics that are related to significant structural differences in the collagen organization and are consistent with the dualistic classification of type I and II serous tumors. Moreover, type I endometrioid tumors have strongly differing ECM architecture than the serous malignancies. The SHG metrics and optical scattering measurements were used to form a linear discriminant model to classify the tissues, and we obtained high accuracy (>90%) between high-grade serous tumors from the other tissue types. High-grade serous tumors account for ~70% of ovarian cancers, and this delineation has potential clinical applications in terms of supplementing histological analysis, understanding the etiology, as well as development of an in vivo screening tool.ConclusionsSHG and optical scattering measurements provide sub-resolution information and when combined provide superior diagnostic power over clinical imaging modalities. Additionally the measurements are able to delineate the different subtypes of ovarian cancer and may potentially assist in treatment protocols. Understanding the altered collagen assembly can supplement histological analysis and provide new insight into the etiology. These methods could become an in vivo screening tool for earlier detection which is important since ovarian malignancies can metastasize while undetectable by current clinical imaging resolution.