Interferometric Spectroscopy of Scattered Light Can Quantify the Statistics of Subdiffractional Refractive-Index Fluctuations

Cherkezyan, Lusik; Capoglu, Ilker; Subramanian, Hariharan; Rogers, Jeremy D.; Damania, Dhwanil; Taflove, Allen; Backman, Vadim

doi:10.1103/physrevlett.111.033903

Cited by 71 publications

(91 citation statements)

References 17 publications

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“…Optical interference of the backpropagating light results in wavelength-dependent fluctuations in the acquired spectrally resolved microscope image. The standard deviation of these spectra (Σ) quantifies the internal structure of the sample with nanometer sensitivity (22,23). In cells, there are numerous variations in macromolecular density due to the spatial organization of macromolecules.…”

Section: Resultsmentioning

confidence: 99%

“…Σ, and the disorder strength (L d , which is Σ normalized by sample thickness), are proportional to two crucial characteristics of molecular organization at deeply subdiffractional length scales: the characteristic length scale of macromolecular organization (L c ), and the standard deviation (δn) of the density (22,23). In a fractal media, such as chromatin, the characteristic length scale of macromolecules can be alternatively evaluated through the fractal dimension, D, which is proportional to Σ.…”

Section: Resultsmentioning

confidence: 99%

“…In cells, there are numerous variations in macromolecular density due to the spatial organization of macromolecules. Quantification of this nanomolecular density distribution is given by the statistical parameter, Σ, at each diffraction-limited pixel (22,23).…”

Section: Resultsmentioning

confidence: 99%

“…Likewise, although PWS cannot resolve the structures directly, it provides information about their subdiffractional organization. To demonstrate sensitivity to these structures, Σ is computed directly as described by the work of Cherkezyan et al (22,23) accounting for the physical properties of the live-cell system. As is shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…In early carcinogenesis, we have previously applied a fixed-cell-imaging technique, partial-wave spectroscopic (PWS) microscopy and transmission electron microscopy (TEM), to detect physical changes in the chromatin nanoarchitecture, indicating that the topology of chromatin is a critical component in cellular function at the earliest stages of tumor formation (21). PWS microscopy allows examination of the intracellular organization concealed by the diffraction limit with length scale sensitivity in the range of 20-200 nm, the range at which existing label-free live-cell imaging techniques are deficient, due to the relationship between the nanoscale spatial variations of macromolecular density and the resulting variance in the spectrum of backscattered light (22,23). The novelty is grounded in a previously overlooked difference between resolution and detectability.…”

Section: Significancementioning

confidence: 99%

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Label-free imaging of the native, living cellular nanoarchitecture using partial-wave spectroscopic microscopy

Almassalha

Bauer

Chandler

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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The organization of chromatin is a regulator of molecular processes including transcription, replication, and DNA repair. The structures within chromatin that regulate these processes span from the nucleosomal (10-nm) to the chromosomal (>200-nm) levels, with little known about the dynamics of chromatin structure between these scales due to a lack of quantitative imaging technique in live cells. Previous work using partial-wave spectroscopic (PWS) microscopy, a quantitative imaging technique with sensitivity to macromolecular organization between 20 and 200 nm, has shown that transformation of chromatin at these length scales is a fundamental event during carcinogenesis. As the dynamics of chromatin likely play a critical regulatory role in cellular function, it is critical to develop live-cell imaging techniques that can probe the real-time temporal behavior of the chromatin nanoarchitecture. Therefore, we developed a livecell PWS technique that allows high-throughput, label-free study of the causal relationship between nanoscale organization and molecular function in real time. In this work, we use live-cell PWS to study the change in chromatin structure due to DNA damage and expand on the link between metabolic function and the structure of higherorder chromatin. In particular, we studied the temporal changes to chromatin during UV light exposure, show that live-cell DNA-binding dyes induce damage to chromatin within seconds, and demonstrate a direct link between higher-order chromatin structure and mitochondrial membrane potential. Because biological function is tightly paired with structure, live-cell PWS is a powerful tool to study the nanoscale structure-function relationship in live cells.E very cellular and extracellular structure has a complex nanoscale organization ranging from individual macromolecules that are a few nanometers in size (e.g., protein and DNA) to macromolecular assemblies that are tens to hundreds of nanometers in size (e.g., cell membranes, higher-order chromatin structure, cytoskeleton, and extracellular matrix fibers). A major scientific challenge is to understand these macromolecular structures, specifically their function and interactions in structurally and dynamically complex living cellular systems. To meet these goals, the ideal live-cell imaging technology would satisfy six key requirements: being (i) nanoscale sensitive (<200 nm), (ii) label free, (iii) nonperturbing, (iv) quantitative, (v) high throughput, and (vi) molecularly informative.Current approaches are unable to meet all of these criteria alone. The breakthroughs in superresolution fluorescence microscopy (SRM) have enabled new imaging technologies capable of providing unprecedented molecular identification at the highest resolutions currently available in live cells, but require the use of exogenous fluorophores to visualize macromolecular structures (1-3). For some applications, these labels are indispensable to achieve molecular specificity. However, there are significant drawbacks to the exclusive use of molec...

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Significancementioning

confidence: 99%

See 3 more Smart Citations

Label-free imaging of the native, living cellular nanoarchitecture using partial-wave spectroscopic microscopy

Almassalha

Bauer

Chandler

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Finite‐Difference Time‐Domain Solution of Maxwell's Equations

Taflove

Hagness

2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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For over 100 years after the publication of Maxwell's equations in 1865, essentially all solution techniques for electromagnetic fields and waves were based on Fourier‐domain concepts, assuming a priori a time‐harmonic (sinusoidal steady‐state) field variation and possibly the existence of a particular Green's function or a set of spatial modes. In 1966, Kane Yee's seminal paper introduced a complete paradigm shift in how to solve Maxwell's equations, reporting a field evolution‐in‐time technique that subsequently evolved into the finite‐difference time‐domain (FDTD) method. In the decades since the publication of Yee's paper, there has been an explosion of interest in FDTD and related grid‐based time‐marched solutions of Maxwell's equations among scientists and engineers. During this period, FDTD modeling has evolved to an advanced stage enabling large‐scale simulations of full‐wave time‐domain electromagnetic wave interactions with volumetrically complex structures over large frequency ranges, spatial scales, and timescales. Currently, FDTD modeling spans the electromagnetic spectrum from ultralow frequencies to visible light. FDTD modeling is routinely conducted as an invaluable virtual laboratory bench in scientific inquiry and exploration in electrodynamics; as an integral part of the electromagnetic engineering design and optimization process; and as a powerful forward solver in imaging and sensing inverse problems. This article reviews the technical basis of the key features of FDTD solution techniques for Maxwell's equations and provides 18 modeling examples spanning the electromagnetic spectrum to illustrate the power, flexibility, and robust nature of FDTD computational electrodynamics simulations.

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