Review of interferometric spectroscopy of scattered light for the quantification of subdiffractional structure of biomaterials

Abstract

Optical microscopy is the staple technique in the examination of microscale material structure in basic science and applied research. Of particular importance to biology and medical research is the visualization and analysis of the weakly scattering biological cells and tissues. However, the resolution of optical microscopy is limited to ? 200 ?? nm due to the fundamental diffraction limit of light. We review one distinct form of the spectroscopic microscopy (SM) method, which is founded in the analysis of the second-order spectral statistic of a wavelength-dependent bright-field far-zone reflected-light microscope image. This technique offers clear advantages for biomedical research by alleviating two notorious challenges of the optical evaluation of biomaterials: the diffraction limit of light and the lack of sensitivity to biological, optically transparent structures. Addressing the first issue, it has been shown that the spectroscopic content of a bright-field microscope image quantifies structural composition of samples at arbitrarily small length scales, limited by the signal-to-noise ratio of the detector, without necessarily resolving them. Addressing the second issue, SM utilizes a reference arm, sample arm interference scheme, which allows us to elevate the weak scattering signal from biomaterials above the instrument noise floor.

Macrogenomic engineering via modulation of the scaling of chromatin packing density

“…This range of structural length scales corresponds to genomic distances from the Kbp to the Mbp range. The produced signal, Σ , is a result of the heterogeneity of the spatial variations in chromatin density within each diffraction-limited voxel, and is proportional to D : Σ ∝ ( D − D 0 ), where D 0 ≈ 1.50 43 . As shown by equation (5), the influence of the change in the packing-density scaling of chromatin on gene expression depends on: (1) the average initial (that is, preceding the perturbation) expression rate $\overline{\epsilon }$ determined by m , (2) the initial D , (3) the upper length-scale of packing-density scaling of chromatin $\left(\frac{M_f}{M_{min}}\right)$, (4) gene length L , and (5) the size of the interaction volume (see Supplementary Section 1 for the derivation).…”

Correlating colorectal cancer risk with field carcinogenesis progression using partial wave spectroscopic microscopy

“…The resulting data are stored in an image cube (x, y, λ), where an interference spectra are stored for each pixel position (x, y) within the field of view. L d is calculated from the fluctuations in the interference spectra as detailed in Cherkezyan et al [20].…”

Nanoscale Chromatin Imaging and Analysis (nano-ChIA) platform bridges 4-D chromatin organization with molecular function

“…PWS directly measures variations in spectral light interference resulting from light scattering due to heterogeneities in chromatin density. This interference signal is then processed to characterize the shape of the autocorrelation function of chromatin density within the coherence volume in both fixed and live cells with sensitivity to structural length scales between 20 and 300 nm (31,32). To investigate the molecular functionality relevant to chromatin structure, nano-ChIA correlates STORM imaging with PWS on the same cells to visualize chromatin packing structure with respect to the spatial distribution of pertinent macromolecules such as active RNA polymerases (Fig.…”

“…Those variations in the refractive index distribution are characterized by the mass scaling or chromatin packing scaling, D. Therefore, D was calculated from maps of ∑ . A detailed description of the relationship between ∑ and D is provided in the SI (27,31).…”