JaeHwang Jung

Quantitative Phase Imaging Techniques for the Study of Cell Pathophysiology: From Principles to Applications

A cellular-level study of the pathophysiology is crucial for understanding the mechanisms behind human diseases. Recent advances in quantitative phase imaging (QPI) techniques show promises for the cellular-level understanding of the pathophysiology of diseases. To provide important insight on how the QPI techniques potentially improve the study of cell pathophysiology, here we present the principles of QPI and highlight some of the recent applications of QPI ranging from cell homeostasis to infectious diseases and cancer.

Spectro-refractometry of individual microscopic objects using swept-source quantitative phase imaging.

We present a novel spectroscopic quantitative phase imaging technique with a wavelength swept-source, referred to as swept-source diffraction phase microscopy (ssDPM), for quantifying the optical dispersion of microscopic individual samples. Employing the swept-source and the principle of common-path interferometry, ssDPM measures the multispectral full-field quantitative phase imaging and spectroscopic microrefractometry of transparent microscopic samples in the visible spectrum with a wavelength range of 450-750 nm and a spectral resolution of less than 8 nm. With unprecedented precision and sensitivity, we demonstrate the quantitative spectroscopic microrefractometry of individual polystyrene beads, 30% bovine serum albumin solution, and healthy human red blood cells.

Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering.

Two-dimensional angle-resolved light scattering maps of individual rod-shaped bacteria are measured at the single-cell level. Using quantitative phase imaging and Fourier transform light scattering techniques, the light scattering patterns of individual bacteria in four rod-shaped species (Bacillus subtilis, Lactobacillus casei, Synechococcus elongatus, and Escherichia coli) are measured with unprecedented sensitivity in a broad angular range from −70° to 70°. The measured light scattering patterns are analyzed along the two principal axes of rod-shaped bacteria in order to systematically investigate the species-specific characteristics of anisotropic light scattering. In addition, the cellular dry mass of individual bacteria is calculated and used to demonstrate that the cell-to-cell variations in light scattering within bacterial species is related to the cellular dry mass and growth.

Label-free identification of individual bacteria using Fourier transform light scattering

Rapid identification of bacterial species is crucial in medicine and food hygiene. In order to achieve rapid and label-free identification of bacterial species at the single bacterium level, we propose and experimentally demonstrate an optical method based on Fourier transform light scattering (FTLS) measurements and statistical classification. For individual rod-shaped bacteria belonging to four bacterial species (Listeria monocytogenes, Escherichia coli, Lactobacillus casei, and Bacillus subtilis), two-dimensional angle-resolved light scattering maps are precisely measured using FTLS technique. The scattering maps are then systematically analyzed, employing statistical classification in order to extract the unique fingerprint patterns for each species, so that a new unidentified bacterium can be identified by a single light scattering measurement. The single-bacterial and label-free nature of our method suggests wide applicability for rapid point-of-care bacterial diagnosis.

Hyperspectral optical diffraction tomography.

Here, we present a novel microscopic technique for measuring wavelength-dependent three-dimensional (3-D) distributions of the refractive indices (RIs) of microscopic samples in the visible wavelengths. Employing 3-D quantitative phase microscopy techniques with a wavelength-swept source, 3-D RI tomograms were obtained in the range of 450 - 700 nm with a spectral resolution of a few nanometers. The capability of the technique was demonstrated by measuring the hyperspectral 3-D RI tomograms of polystyrene beads, human red blood cells, and hepatocytes. The results demonstrate the potential for label-free molecular specific 3-D tomography of biological samples.

Label-free optical quantification of structural alterations in Alzheimer's disease.

We present a wide-field quantitative label-free imaging of mouse brain tissue slices with sub-micrometre resolution, employing holographic microscopy and an automated scanning platform. From the measured light field images, scattering coefficients and anisotropies are quantitatively retrieved by using the modified the scattering-phase theorem, which enables access to structural information about brain tissues. As a proof of principle, we demonstrate that these scattering parameters enable us to quantitatively address structural alteration in the brain tissues of mice with Alzheimer’s disease.

Holographic deep learning for rapid optical screening of anthrax spores

A synergistic application of holography and deep learning enables rapid optical screening of anthrax spores and other pathogens. Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique “representation learning” capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens.

Implementation of automatic gain controlled bidirectional EDFA in WDM networks

Wavelength-division-multiplexing (WDM) techniques combined with n erbium-doped fiber amplifier (EDFA) is essential for realizing high capacity lightwave transmission and flexible optical networks. Compared with unidirectional transmission, bidirectional transmission over a single fiber has the advantage of reducing not only the number of fiber link, but also the number of passive components such as splitters and WDM multiplexers. Recently, lots of problems in bidirectional EDFAs were investigated, and various structure schemes of the EDFA were reported to overcome the problems, such as back reflections. An automatic gain control (AGC) function for bidirectional EDFAs, however, has been rarely reported. In a bidirectional EDFA, optical gains of survival channels are subject to change with the input variations of both directions, such as the addition or dropping of channels. To preserve the system performance, these gain changes should be suppressed by using thee AGC function. For the unidirectional EDFA, several AGC functions demonstrated such as optical clamping methods, link control laser methods and pump control methods. Nowadays, the AGC method by using the pump control is attractive because the implementation is simple and less costs. It may be modified for the bidirectional EDFA, which shares the same port for input and output. In the paper, we propose and demonstrate an AGC scheme for the bidirectional EDFA by means of pump control.

Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

Optical characterization of red blood cells from individuals with sickle cell trait and disease in Tanzania using quantitative phase imaging

Sickle cell disease (SCD) is common across Sub-Saharan Africa. However, the investigation of SCD in this area has been significantly limited mainly due to the lack of research facilities and skilled personnel. Here, we present optical measurements of individual red blood cells from healthy individuals and individuals with SCD and sickle cell trait in Tanzania using the quantitative phase imaging technique. By employing a quantitative phase imaging unit, an existing microscope in a clinic is transformed into a powerful quantitative phase microscope providing measurements on the morphological, biochemical, and biomechanical properties of individual cells. The present approach will open up new opportunities for cost-effective investigation and diagnosis of several diseases in low resource environments.