Light scattering characterization of mitochondrial aggregation in single cells

Dynamic light scattering microscopy sensing mitochondria dynamics for label-free detection of triple-negative breast cancer enhanced by deep learning

We established a deep learning-based dynamic light scattering (DLS) microscopy sensing mitochondria dynamic for label-free identification of triple-negative breast cancer (TNBC) cells. The capacity of DLS microscopy to detect the intracellular motility of subcellular scatters was verified with the analysis of the autocorrelation function. We also conducted an in-depth examination of the impact of mitochondrial dynamics on DLS within TNBC cells, employing confocal fluorescent imaging to visualize the morphology of the mitochondria. Furthermore, we applied the DLS microscopy incorporating the two-stream deep learning method to differentiate the TNBC subtype and HER2 positive breast cancer subtype, with the classification accuracy achieving 0.89.

Multi-wavelength multi-direction laser light scattering for cell characterization using machine learning-based methods

Cell identification and analysis play a crucial role in many biology- and health-related applications. The internal and surface structures of a cell are complex and many of the features are sub-micron in scale. Well-resolved images of these features cannot be obtained using optical microscopy. Previous studies have reported that the single-cell angular laser-light scattering patterns (ALSP) can be used for label-free cell identification and analysis. The ALSP can be affected by cell properties and the wavelength of the probing laser. Two cell properties, cell surface roughness and the number of mitochondria, are investigated in this study. The effects of probing laser wavelengths (blue, green, and red) and the directions of scattered light collection (forward, side, and backward) are studied to determine the optimum conditions for distinguishing the two cell properties. Machine learning (ML) analysis has been applied to ALSP obtained from numerical simulations. The results of ML analysis show that the backward scattering is the best direction for characterizing the surface roughness, while the forward scattering is the best direction for differentiating the number of mitochondria. The laser light having red or green wavelength is found to perform better than that having the blue wavelength in differentiating the surface roughness and the number of mitochondria. This study provides important insights into the effects of probing laser wavelength on gaining information about cells from their ALSP.

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry

Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we developed the multi-modal static cytometry that adopted different features to classify the typical human cervical epithelial cells (H8) and cervical cancer cells (HeLa). With the light-sheet static cytometry, we obtain brightfield (BF) images, fluorescence (FL) images and two-dimensional (2D) light scattering (LS) patterns of single cervical cells. Three feature extraction methods are used to extract multi-modal features based on different data characteristics. Analysis and classification of morphological and textural features demonstrate the potential of intracellular mitochondria in cervical cancer cell classification. The deep learning method is used to automatically extract deep features of label-free LS patterns, and an accuracy of 76.16% for the classification of the above two kinds of cervical cells is obtained, which is higher than the other two single modes (BF and FL). Our multi-modal static cytometry uses a variety of feature extraction and analysis methods to provide the mitochondria as promising internal biomarkers for cervical cancer diagnosis, and to show the promise of label-free, automatic classification of early cervical cancer with deep learning-based 2D light scattering.

Scattering angle resolved optical coherence tomography measures morphological changes in Bacillus subtilis colonies

Significance

An unmet need is recognized for early detection and diagnosis of neurological diseases. Many psychological markers emerge years after disease onset. Mitochondrial dysfunction and corresponding neurodegeneration occur before onset of large-scale cell and tissue pathology. Early detection of subcellular morphology changes could serve as a beacon for early detection of neurological diseases. This study is on bacterial colonies, Bacillus subtilis, which are similar in size to mitochondria.

Aim

This study investigates whether morphological changes can be detected in Bacillus subtilis using scattering angle resolved optical coherence tomography (SAR-OCT).

Approach

The SAR-OCT was applied to detect scattering angle distribution changes in Bacillus subtilis. The rod-to-coccus shape transition of the bacteria was imaged, and the backscattering angle was analyzed by recording the distribution of the ratio of low- to medium angle scattering (L/M ratio). Bacillus orientation at different locations in colonies was analytically modeled and compared with SAR-OCT results.

Results

Significant differences in the distribution of backscattering angle were observed in Bacillus subtilis transitioning from rod-to-coccus shapes. In Bacillus subtilis, the C -parameter of the Burr distribution of the SAR-OCT-derived L/M ratio was significantly smaller in coccus compared with rod-shaped bacteria. SAR-OCT-derived L/M ratio varied with bacterial position in the colony and is consistent with predicted orientations from previous studies.

Conclusions

Study results support the potential of utilizing SAR-OCT to detect bacterial morphological changes.

Scattering Inversion Study for Suspended Label-Free Lymphocytes with Complex Fine Structures

Objective and Impact Statement. Distinguishing malignant lymphocytes from normal ones is vital in pathological examination. We proposed an inverse light scattering (ILS) method for label-free suspended lymphocytes with complex fine structures to identify their volumes for pathological state. Introduction. Light scattering as cell's "fingerprint" provides valuable morphology information closely related to its biophysical states. However, the detail relationships between the morphology with complex fine structures and its scattering characters are not fully understood. Methods. To quantitatively inverse the volumes of membrane and nucleus as the main scatterers, clinical lymphocyte morphologies were modeled combining the Gaussian random sphere geometry algorithm by 750 reconstructed results after confocal scanning, which allowed the accurate simulation to solve ILS problem. For complex fine structures, the specificity for ILS study was firstly discussed (to our knowledge) considering the differences of not only surface roughness, posture, but also the ratio of nucleus to the cytoplasm and refractive index. Results. The volumes of membrane and nucleus were proved theoretically to have good linear relationship with the effective area and entropy of forward scattering images. Their specificity deviations were less than 3.5%. Then, our experimental results for microsphere and clinical leukocytes showed the Pearson product-moment correlation coefficients (PPMCC) of this linear relationship were up to 0.9830~0.9926. Conclusion. Our scattering inversion method could be effectively applied to identify suspended label-free lymphocytes without destructive sample pretreatments and complex experimental systems.

Integration of light scattering with machine learning for label free cell detection

Light scattering has been used for label-free cell detection. The angular light scattering patterns from the cells are unique to them based on the cell size, nucleus size, number of mitochondria, and cell surface roughness. The patterns collected from the cells can then be classified based on different image characteristics. We have also developed a machine learning (ML) method to classify these cell light scattering patterns. As a case study we have used this light scattering technique integrated with the machine learning to analyze staurosporine-treated SH-SY5Y neuroblastoma cells and compare them to non-treated control cells. Experimental results show that the ML technique can provide a classification accuracy (treated versus non-treated) of over 90%. The predicted percentage of the treated cells in a mixed solution is within 5% of the reference (ground-truth) value and the technique has the potential to be a viable method for real-time detection and diagnosis.

Assessment of internal refractive index profile of stochastically inhomogeneous nuclear models via analysis of two-dimensional optical scattering patterns

SIGNIFICANCE

Optical scattering signals obtained from tissue constituents contain a wealth of structural information. Conventional intensity features, however, are mostly dictated by the overall morphology and mean refractive index of these constituents, making it very difficult to exclusively sense internal refractive index fluctuations.

AIM

We perform a systematic analysis to elucidate how changes in internal refractive index profile of cell nuclei can best be detected via optical scattering.

APPROACH

We construct stochastically inhomogeneous nuclear models and numerically simulate their azimuth-resolved scattering patterns. We then process these two-dimensional patterns with the goal of identifying features that directly point to subnuclear structure.

RESULTS

Azimuth-dependent intensity variations over the side scattering range provide significant insights into subnuclear refractive index profile. A particular feature we refer to as contrast ratio is observed to be highly sensitive to the length scale and extent of refractive index fluctuations; further, this feature is not susceptible to changes in the overall size and mean refractive index of nuclei, thereby allowing for selective tracking of subnuclear structure that can be linked to chromatin distribution.

CONCLUSIONS

Our analysis will potentially pave the way for scattering-based assessment of chromatin reorganization that is considered to be a key hallmark of precancer progression.

Visible Light Optical Coherence Tomography (OCT) Quantifies Subcellular Contributions to Outer Retinal Band 4

Purpose

To use visible light optical coherence tomography (OCT) to investigate subcellular reflectivity contributions to the outermost (4th) of the retinal hyperreflective bands visualized by current clinical near-infrared (NIR) OCT.

Methods

Visible light OCT, with 1.0 µm axial resolution, was performed in 28 eyes of 19 human subjects (21-57 years old) without history of ocular pathology. Two foveal and three extrafoveal hyperreflective zones were consistently depicted within band 4 in all eyes. The two outermost hyperreflective bands, occasionally visualized by NIR OCT, were presumed to be the retinal pigment epithelium (RPE) and Bruch's membrane (BM). RPE thickness, BM thickness, and RPE interior reflectivity were quantified topographically across the macula.

Results

A method for correcting RPE multiple scattering tails was found to both improve the Gaussian goodness-of-fit for the BM intensity profile and reduce the coefficient of variation of BM thickness in vivo. No major topographical differences in macular BM thickness were noted. RPE thickness decreased with increasing eccentricity. Visible light OCT signal intensity in the RPE was weighted to the apical side and attenuated more across the RPE in the fovea than peripherally.

Conclusions

Morphometry of the presumed RPE and BM bands is consistent with known anatomy. Weighting of RPE reflectivity toward the apical side suggests that melanosomes are the predominant contributors to RPE backscattering and signal attenuation in young eyes.

Translational Relevance

By enabling morphometric analysis of the RPE and BM, visible light OCT deciphers the main reflectivity contributions to outer retinal band 4, commonly visualized by commercial OCT systems.

Supercontinuum-based nondisruptive scattering analyses of mouse fibroblast L929 cells before and after necrosis

The scattering properties of biological tissue are highly dependent on the structure size, refractive index, and wavelength of the incident light. Furthermore, these scattering characteristics are strongly influenced by movements of the scattering objects. A method is developed to determine the angular- and spectral-resolved scattering properties that enabled the characterization of biological nano- and microscaled cell structures. Nanosecond pulses from a spectrally filtered supercontinuum light source are captured and time-resolved to depress background noise and minimize disruptive effects of the biological cells. The scattering characteristics of a monolayer of mouse fibroblast L929 cells are measured at defined wavelengths in a standard cell culture plate. Because of the size and distribution of the scattering structures, a Fourier transform-based Mie scattering scheme is used to analyze the data. The system is tested to detect structural changes of mouse fibroblast L929 cells before and after poisoning with Triton X100. The final result is the development of a contamination-free method to study pathological changes in cell cultures, necrosis, or other cell-damaging effects.

Label-free dynamic segmentation and morphological analysis of subcellular optical scatterers

Imaging without fluorescent protein labels or dyes presents significant advantages for studying living cells without confounding staining artifacts and with minimal sample preparation. Here, we combine label-free optical scatter imaging with digital segmentation and processing to create dynamic subcellular masks, which highlight significantly scattering objects within the cells' cytoplasms. The technique is tested by quantifying organelle morphology and redistribution during cell injury induced by calcium overload. Objects within the subcellular mask are first analyzed individually. We show that the objects' aspect ratio and degree of orientation ("orientedness") decrease in response to calcium overload, while they remain unchanged in untreated control cells. These changes are concurrent with mitochondrial fission and rounding observed by fluorescence, and are consistent with our previously published data demonstrating scattering changes associated with mitochondrial rounding during calcium injury. In addition, we show that the magnitude of the textural features associated with the spatial distribution of the masked objects' orientedness values, changes by more than 30% in the calcium-treated cells compared with no change or changes of less than 10% in untreated controls, reflecting dynamic changes in the overall spatial distribution and arrangement of subcellular scatterers in response to injury. Taken together, our results suggest that our method successfully provides label-free morphological signatures associated with cellular injury. Thus, we propose that dynamically segmenting and analyzing the morphology and organizational patterns of subcellular scatterers as a function of time can be utilized to quantify changes in a given cellular condition or state.

Clinical lymphocytes construction for light scattering inversion study: a three-dimensional morphology constructed method from defective confocal images

Constructing models of cells' realistic internal and external morphology is vital for correlation between light scattering and morphology of the scattering structure. The image stack obtained from fluorescent confocal microscopy is at present used to construct the cell's three-dimensional (3-D) morphology. However, due to the poor labeling quality and unavoidable optical noise present in the image stacks, 3-D morphologies are difficult to construct and are an impediment to the statistical analyses of cell structures. We propose a method called the "area and shape constraint method (ASCM)" for constructing 3-D morphology. Blurred 3-D morphologies constructed by common methods from image stacks considered as defective and which are commonly discarded are well restored by the ASCM. Seventy-four clinical blood samples and a series of standard fluorescent spheres are selected to evaluate the validity and precision of our proposed ASCM. Both the qualitative and quantitative results obtained by ASCM indicate the good performance of the method in constructing the cell's 3-D morphology.

Energetic mitochondrial failing in vitiligo and possible rescue by cardiolipin

Vitiligo is characterized by death or functional defects of epidermal melanocytes through still controversial pathogenic process. Previously, we showed that mitochondria-driven pre-senescent phenotype diminishes the capability of vitiligo melanocytes to cope with stressful stimuli. In the current study, we investigated markers of mitochondrial energy metabolism including the PGC1a axis, and then we determined the index of mitochondrial impairment using a cytomic approach. We found in cultured epidermal vitiligo melanocytes, compared to healthy ones, low ATP, increased proton leakage, and altered expression of several glycolytic enzymes (hexokinase II, pyruvic dehydrogenase kinase 1 and pyruvic kinase M2), We suggest that the low ATP production may be sufficient in steady-state conditions but it is unable to cover further needs. We also found in vitiligo melanocyrtes hyper-activation of the PGC1α axis, finalized to counteract the energy defect. Cytomic analysis, supported by MitoTracker Red pattern and ex-vivo immunohistochemistry, suggested an increased mitochondrial mass, possibly useful to ensure the essential ATP level. Finally, pharmacological cardiolipin stabilization reverted the energetic impairment, confirming the initial mitochondrial role. In conclusion, we report new insight in the pathogenetic mechanism of viitligo and indicate that the mitochondrial failure rescue by cardiolipin manipulation may be a new intriguing target in treatment development.

Angular-dependent light scattering from cancer cells in different phases of the cell cycle

Cancer cells in different phases of the cell cycle result in significant differences in light scattering properties. In order to harvest cancer cells in particular phases of the cell cycle, we cultured cancer cells through the process of synchronization. Flow cytometric analysis was applied to check the results of cell synchronization and prepare for light scattering measurements. Angular-dependent light scattering measurements of cancer cells arrested in the G1, S, and G2 phases have been performed. Based on integral calculations for scattering intensities from 5° to 10° and from 110° to 150°, conclusions have been reached. Clearly, the sizes of the cancer cells in different phases of the cell cycle dominated the forward scatter. Accompanying the increase of cell size with the progression of the cell cycle, the forward scattering intensity also increased. Meanwhile, the DNA content of cancer cells in every phase of the cell cycle is responsible for light scattering at large scatter angles. The higher the DNA content of cancer cells was, the greater the positive effect on the high-scattering intensity. As expected, understanding the relationships between the light scattering from cancer cells and cell cycles will aid in the development of cancer diagnoses. Also, it may assist in the guidance of antineoplastic drugs clinically.

Light scattering from normal and cervical cancer cells

The light scattering characteristic plays a very important role in optic imaging and diagnostic applications. For optical detection of the cell, cell scattering characteristics have an extremely vital role. In this paper, we use the finite-difference time-domain (FDTD) algorithm to simulate the propagation and scattering of light in biological cells. The two-dimensional scattering cell models were set up based on the FDTD algorithm. The cell models of normal cells and cancerous cells were established, and the shapes of organelles, such as mitochondria, were elliptical. Based on these models, three aspects of the scattering characteristics were studied. First, the radar cross section (RCS) distribution curves of the corresponding cell models were calculated, then corresponding relationships between the size and the refractive index of the nucleus and light scattering information were analyzed in the three periods of cell canceration. The values of RCS increase positively with the increase of the nucleo-cytoplasmic ratio in the cancerous process when the scattering angle ranges from 0° to 20°. Second, the effect of organelles in the scattering was analyzed. The peak value of the RCS of cells with mitochondria is higher than the cells without mitochondria when the scattering angle ranges from 20° to 180°. Third, we demonstrated that the influence of cell shape is important, and the impact was revealed by the two typical ideal cells: round cells and oval cells. When the scattering angle ranges from 0° to 80°, the peak values and the frequencies of the appearance of the peaks from the two models are roughly similar. It can be concluded that: (1) the size of the nuclei and the change of the refractive index of cells have a certain impact on light scattering information of the whole cell; (2) mitochondria and other small organelles contribute to the cell light scattering characteristics in the larger scattering angle area; and (3) the change of the cell shape significantly influences the value of scattering peak and the deviation of scattering peak position. The results of the numerical simulation will guide subsequent experiments and early diagnosis of cervical cancer.

Relation between clinical mature and immature lymphocyte cells in human peripheral blood and their spatial label free scattering patterns

A single living cell's light scattering pattern (LSP) in the horizontal plane, which has been denoted as the cell's "2D fingerprint," may provide a powerful label-free detection tool in clinical applications. We have recently studied the LSP in spatial scattering planes, denoted as the cell's "3D fingerprint," for mature and immature lymphocyte cells in human peripheral blood. The effects of membrane size, morphology, and the existence of the nucleus on the spatial LSP are discussed. In order to distinguish clinical label-free mature and immature lymphocytes, the special features of the spatial LSP are studied by statistical method in both the spatial and frequency domains. Spatial LSP provides rich information on the cell's morphology and contents, which can distinguish mature from immature lymphocyte cells and hence ultimately it may be a useful label-free technique for clinical leukemia diagnosis.

Simulation of cellular changes on Optical Coherence Tomography of human retina

We present a methodology to assess cell level alterations on the human retina responsible for functional changes observable in the Optical Coherence Tomography data in healthy ageing and in disease conditions, in the absence of structural alterations. The methodology is based in a 3D multilayer Monte Carlo computational model of the human retina. The optical properties of each layer are obtained by solving the Maxwell's equations for 3D domains representative of small regions of those layers, using a Discontinuous Galerkin Finite Element Method (DG-FEM). Here we present the DG-FEM Maxwell 3D model and its validation against Mie's theory for spherical scatterers. We also present an application of our methodology to the assessment of cell level alterations responsible for the OCT data in Diabetic Macular Edema. It was possible to identify which alterations are responsible for the changes observed in the OCT scans of the diseased groups.

In situ detection of laser-induced slip initiation on the silicon wafer surface

We propose a real-time in situ method to detect slip initiation on the surface of silicon wafers during high-power laser beam irradiation. In this method, light is collected from the surface of a silicon wafer subjected to laser irradiation. When the slip is initiated, it strongly scatters the laser beam, allowing detection of the time of the slip initiation based on the resulting sudden increase in the scattering signal. To demonstrate the performance of this method, a silicon wafer specimen was illuminated by a near-infrared continuous-wave fiber laser beam (of wavelength 1070 nm) at four different laser powers, and the scattered light was detected. The scattering signal increased suddenly at the time of slip initiation. To confirm the occurrence of slip, the surface morphologies of the silicon specimens after laser irradiation were analyzed using an optical microscope; surface slips were observed only in the specimens for which the sudden increase in scattering had been detected. Thus, the proposed method is shown to be very effective for the real-time in situ detection of surface slip initiation induced by high-power laser beam irradiation on silicon wafers.

Simulation of diffuse photon migration in tissue by a Monte Carlo method derived from the optical scattering of spheroids

A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.

Label-free and noninvasive optical detection of the distribution of nanometer-size mitochondria in single cells

A microfluidic flow cytometric technique capable of obtaining information on nanometer-sized organelles in single cells in a label-free, noninvasive optical manner was developed. Experimental two-dimensional (2D) light scattering patterns from malignant lymphoid cells (Jurkat cell line) and normal hematopoietic stem cells (cord blood CD34+ cells) were compared with those obtained from finite-difference time-domain simulations. In the simulations, we assumed that the mitochondria were randomly distributed throughout a Jurkat cell, and aggregated in a CD34+ cell. Comparison of the experimental and simulated light scattering patterns led us to conclude that distinction from these two types of cells may be due to different mitochondrial distributions. This observation was confirmed by conventional confocal fluorescence microscopy. A method for potential cell discrimination was developed based on analysis of the 2D light scattering patterns. Potential clinical applications using mitochondria as intrinsic biological markers in single cells were discussed in terms of normal cells (CD34+ cell and lymphocytes) versus malignant cells (THP-1 and Jurkat cell lines).

Wide-angle light-scattering differentiation of organelle-size particle distributions in whole cells

A finite-difference time-domain (FDTD) method is used to study the multiple scattering from many organelle-size particles distributed in a biological cell. Conventional flow cytometry, where the small-angle forward scatter (FSC) intensity and side scatter (SSC) intensity are used for cell characterizations, may have difficulties to differentiate the organelle distributions in biological cells. Based on the FDTD simulations, a light-scattering methodology is proposed here to overcome such a problem. This method differentiates the dense and sparse distributions of organelle-size particles in a cell, by counting the peak numbers in both large-angle FSC and wide-angle SSC, with the multiple scattering effects being considered. Implemented with a wide-angle microfluidic cytometer, the approach demonstrated in this theoretical study may find potential applications in clinics for label-free cell physiological study.