The hyperspectral, interferometric microscopy technique, PWS has demonstrated the ability to measure variance in the nanoscale refractive index (Σ) of chromatin – the macromolecular assembly containing most of a cell’s genetic material. However, the question arises: how does Σ relate to the physical distribution of mass in chromatin, and specifically the organization of chromatin packing. We developed an analytical framework to relate Σ to the mass-density autocorrelation function – which can fully describe the distribution of mass and is characterized by D. This relationship was validated numerically using the rigorous modelling technique FDTD and experimentally with PWS and Chromatin Electron Microscopy (ChromEM).
Fluorescence photo-switching of native, unmodified DNA using visible light enables label-free, nanoscale, single-molecule photon localization microscopy (PLM) of chromatin structure. Compared with conventional label-based super resolution imaging techniques, the label-free DNA-PLM has the advantage of faithfully resolving the native nucleotides under non-perturbing conditions, thus allowing a reliable analysis of the chromatin organization. Recently, we have developed an algorithm to quantify the chromatin spatial distribution based on label-free DNA-PLM images by calculating the fractal dimension from the chromatin cluster size and the number of photon emission events. For demonstration, we employed label-free DNA-PLM with TIRF illumination, and imaged the nuclei of ovarian cancer cells with three descending chromatin heterogeneities: the P53 mutation (M248), the wild type (A2780), and the wild type treated with a commonly-used chemotherapeutic drug celecoxib (Cele). Using the algorithm, we extracted the fractal dimensions for nuclear chromatin. We found that the fractal dimension is between 2 to 3 for all cells, which lies in the range of reported values from other techniques (e.g., TEM). We also observed that M248 has the highest fractal dimension while Cele has the lowest, a perfect match with the experimental expectations. We believe this study can provide a new approach to quantify label-free super-resolution imaging of macromolecular structures and could contribute to our knowledge of native in-vitro nuclear chromatin configurations.
We demonstrate a multimodal imaging methodology to probe the nanoscale environment of cells. The system combines partial-wave spectroscopic (PWS) microscopy and spectroscopic photon localization microscopy (SPLM). PWS quantifies the nanoarchitecture of cells with sensitivity to structures between 20 and 200 nm. SPLM is a newly developed super-resolution imaging technique based upon the principles of single-molecule localization microscopy and spectroscopy. In addition to allowing super-resolution imaging, SPLM provides inherent molecular-specific spectroscopic information of targeted structures visualized when dyes are used. Combining both of these modalities into a single instrument allows nanoscale characterization of the super-resolution molecular imaging provided by SPLM as it relates to nanoscale structural information provided by PWS. As an example, we labeled RNA polymerase in HeLa cells and showed correlations between the locations of the RNA polymerase visualized by SPLM and the nanoscale structure of the chromatin measured by PWS. Such information is crucial in understanding the role of specific molecules in regulating the chromatin structure and gene expression. More broadly, this instrument can give insight into the molecular pathways of diseases and therapeutic treatments of those diseases, while simultaneously showing the effects on chromatin topology.
Our group had previously established that nanoscale three-dimensional refractive index (RI) fluctuations of a linear, dielectric, label-free medium can be sensed in the far field through spectroscopic microscopy, regardless of the diffraction limit of optical microscopy. Adopting this technique, Partial Wave Spectroscopic (PWS) Microscopy was able to sense nanoarchitectural alterations in early-stage cancers. With the success of PWS on detecting cancer from healthy clinical samples, we further investigated whether and how histological staining can enhance the performance of PWS by both finite difference time domain (FDTD) simulations and experiments.
In this investigation, the dispersion models of hematoxylin and eosin were extracted from the absorption spectra of H and E stained cells. Using these models, the effect of staining were studied via FDTD simulations of unstained versus stained samples with various nanostructures. We observed that, the spectral variance was increased and the spectral variance difference between two samples with distinct nanostructures was enhanced in stained samples by over 200%. Furthermore, we investigated with FDTD whether molecule-specific staining can be used to enhance signals from a medium composing of the desired molecule. Samples with two mixed random media were created and the desired medium was either stained or unstained. Our results showed that the difference between the nanostructures of only the desired medium was enhanced in stained samples. We concluded that, with molecule-specific staining, PWS can selectively target the nanoarchitecture of a desired molecule. Lastly, these results were validated by experiments using human buccal cells from healthy or lung cancer patients.
This study has significant impact in improving the performance of PWS on quantifying nanoarchitectural alterations during cancer.
Structural and biological origins of light scattering in cells and tissue are still poorly understood. We demonstrate how this problem might be addressed through the use of transmission electron microscopy (TEM). For biological samples, TEM image intensity is proportional to mass-density, and thus proportional to refractive index (RI). By calculating the autocorrelation function (ACF) of TEM image intensity of a thin-section of cells, we essentially maintain the nanoscale ACF of the 3D cellular RI distribution, given that the RI distribution is statistically isotropic. Using this nanoscale 3D RI ACF, we can simulate light scattering through biological samples, and thus guiding many optical techniques to quantify specific structures. In this work, we chose to use Partial Wave Spectroscopy (PWS) microscopy as a one of the nanoscale-sensitive optical techniques. Hela cells were prepared using standard protocol to preserve nanoscale ultrastructure, and a 50-nm slice was sectioned for TEM imaging at 6 nm resolution. The ACF was calculated for chromatin, and the PWS mean sigma was calculated by summing over the power spectral density in the visible light frequency of a random medium generated to match the ACF. A 1-µm slice adjacent to the 50-nm slice was sectioned for PWS measurement to guarantee identical chromatin structure. For 33 cells, we compared the calculated PWS mean sigma from TEM and the value measured directly, and obtained a strong correlation of 0.69. This example indicates the great potential of using TEM measured RI distribution to better understand the quantification of cellular nanostructure by optical methods.
Combining finite-difference time-domain (FDTD) methods and modeling of optical microscopy modalities, we previously developed an open-source software package called Angora, which is essentially a “microscope in a computer.” However, the samples being simulated were limited to nondispersive media. Since media dispersions are common in biological samples (such as cells with staining and metallic biomarkers), we have further developed a module in Angora to simulate samples having complicated dispersion properties, thereby allowing the synthesis of microscope images of most biological samples. We first describe a method to integrate media dispersion into FDTD, and we validate the corresponding Angora dispersion module by applying Mie theory, as well as by experimentally imaging gold microspheres. Then, we demonstrate how Angora can facilitate the development of optical imaging techniques with a case study.
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