Refractive index maps and membrane dynamics of human red blood cells parasitized by Plasmodium falciparum

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

Imaging the intracellular refractive index distribution (IRID) for dynamic label-free living colon cancer cells via circularly depolarization decay model (CDDM)

Label-free detection of intracellular substances for living cancer cells remains a significant hurdle in cancer pathogenesis research. Although the sensitivity of light polarization to intracellular substances has been validated, current studies are predominantly focused on tissue lesions, thus label-free detection of substances within individual living cancer cells is still a challenge. The main difficulty is to find specific detection methods along with corresponding characteristic parameters. With refractive index as an endogenous marker of substances, this study proposes a detection method of intracellular refractive index distribution (IRID) for label-free living colon cancer (LoVo) cells. Utilizing the circular depolarization decay model (CDDM) to calculate the degree of circular polarization (DOCP) modulated by the cell allows for the derivation of the IRID on the focal plane. Experiments on LoVo cells demonstrated the refractive index of single cell can be accurately and precisely measured, with precision of 10-3 refractive index units (RIU). Additionally, chromatin content during the interphases (G1, S, G2) of cell cycle was recorded at 56.5%, 64.4%, and 71.5%, respectively. A significantly finer IRID can be obtained compared to the phase measurement method. This method is promising in providing a dynamic label-free intracellular substances detection method in cancer pathogenesis studies.

Deep learning-assisted smartphone-based quantitative microscopy for label-free peripheral blood smear analysis

Hematologists evaluate alterations in blood cell enumeration and morphology to confirm peripheral blood smear findings through manual microscopic examination. However, routine peripheral blood smear analysis is both time-consuming and labor-intensive. Here, we propose using smartphone-based autofluorescence microscopy (Smart-AM) for imaging label-free blood smears at subcellular resolution with automatic hematological analysis. Smart-AM enables rapid and label-free visualization of morphological features of normal and abnormal blood cells (including leukocytes, erythrocytes, and thrombocytes). Moreover, assisted with deep-learning algorithms, this technique can automatically detect and classify different leukocytes with high accuracy, and transform the autofluorescence images into virtual Giemsa-stained images which show clear cellular features. The proposed technique is portable, cost-effective, and user-friendly, making it significant for broad point-of-care applications.

Non-steady state thermometry with optical diffraction tomography

Label-free thermometry is a pivotal tool for many disciplines. However, most current approaches are only suitable for planar heat sources in steady state, thereby restricting the range of systems that can be reliably studied. Here, we introduce pump probe-based optical diffraction tomography (ODT) as a method to map temperature precisely and accurately in three dimensions (3D) at the single-particle level. To do so, we first systematically characterize the thermal landscape in a model system consisting of gold nanorods in a microchamber and then benchmark the results against simulations and quantitative phase imaging thermometry. We then apply ODT thermometry to resolve thermal landscapes inaccessible to other label-free approaches in the form of nonplanar heat sources embedded in complex environments and freely diffusing gold nanorods in a microchamber. Last, we foresee that our approach will find many applications where routine thermal characterization of heterogeneous nanoparticles samples in 3D or in non-steady state is required.

Implementation of a portable diffraction phase microscope for digital histopathology

Quantitative phase imaging (QPI) has a significant advantage in histopathology as it helps in differentiating biological tissue structures and cells without the need for staining. To make this capability more accessible, it is crucial to develop compact and portable systems. In this study, we introduce a portable diffraction phase microscopy (DPM) system that allows the acquisition of phase map images from various organs in mice using a low-NA objective lens. Our findings indicate that the cell and tissue structures observed in portable DPM images are similar to those seen in conventional histology microscope images. We confirmed that the developed system's performance is comparable to the benchtop DPM system. Additionally, we investigate the potential utility of digital histopathology by applying deep learning technology to create virtual staining of DPM images.

Real-time simultaneous refractive index and thickness mapping of sub-cellular biology at the diffraction limit

Mapping the cellular refractive index (RI) is a central task for research involving the composition of microorganisms and the development of models providing automated medical screenings with accuracy beyond 95%. These models require significantly enhancing the state-of-the-art RI mapping capabilities to provide large amounts of accurate RI data at high throughput. Here, we present a machine-learning-based technique that obtains a biological specimen's real-time RI and thickness maps from a single image acquired with a conventional color camera. This technology leverages a suitably engineered nanostructured membrane that stretches a biological analyte over its surface and absorbs transmitted light, generating complex reflection spectra from each sample point. The technique does not need pre-existing sample knowledge. It achieves 10-4 RI sensitivity and sub-nanometer thickness resolution on diffraction-limited spatial areas. We illustrate practical application by performing sub-cellular segmentation of HCT-116 colorectal cancer cells, obtaining complete three-dimensional reconstruction of the cellular regions with a characteristic length of 30 μm. These results can facilitate the development of real-time label-free technologies for biomedical studies on microscopic multicellular dynamics.

Energy spectrum analysis on a red blood cell model

It is important to understand the dynamics of red blood cells (RBCs) in blood flow. This requires the formulation of coarse-grained RBC models that reproduce the hydrodynamic properties of blood accurately. One of the models that successfully reproduces the rheology and morphology of blood has been proposed by Fedosov et al. [Comput. Methods Appl. Mech. Eng. 199, 1937-1948 (2010)]. The proposed RBC model contains several parameters whose values are determined by either various experiments or physical requirements. In this study, we developed a new method of determining parameter values precisely from the fluctuations of the RBC membrane. Specifically, we studied the relationship between the spectra of the fluctuations and model parameters. Characteristic peaks were observed in the spectra, whose peak frequencies were dependent on the parameter values. In addition, we investigated the spectra of the radius of gyration. We identified the peaks originating from the spring potential and the volume-conserving potential appearing in the spectra. These results lead to the precise experimental determination of the parameters used in the RBC model.

Optical Diffraction Tomography and Raman Confocal Microscopy for the Investigation of Vacuoles Associated with Cancer Senescent Engulfing Cells

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retention. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the noninvasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

Influence of Chemical and Genetic Manipulations on Cellular Organelles Quantified by Label-Free Optical Diffraction Tomography

Label-free optical diffraction tomography provides three-dimensional imaging of cells and organelles, along with their refractive index (RI) and volume. These physical parameters are valuable for quantitative and accurate analysis of the subcellular microenvironment and its connections to intracellular biological properties. In biological and biochemical cell analysis, various invasive cell manipulations are used, such as temperature change, chemical fixation, live cell staining with fluorescent dye, and gene overexpression of exogenous proteins. However, it is not fully understood how these various manipulations affect the physicochemical properties of different organelles. In this study, we investigated the impact of these manipulations on the cellular properties of single HeLa cells. We found that after cell fixation and an increase in temperature, the RI value of organelles, such as the nucleus and cytoplasm, significantly decreased overall. Interestingly, unlike the cell nuclei, cytoplasmic RI values were hardly detected after membrane permeation, indicating that only intracytoplasmic components were largely lost. Additionally, our findings revealed that the expression of GFP and GFP-tagged proteins significantly increased the RI values of organelles in living cells compared to the less effective RI changes observed with chemical fluorescence staining for cell organelles. The result demonstrates that distinct types of invasive manipulations can alter the microenvironment of organelles in different ways. Our study sheds new light on how chemical and genetic manipulations affect organelles.

Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography

Resolving three-dimensional morphological features in thick specimens remains a significant challenge for label-free imaging. We report a new speckle diffraction tomography (SDT) approach that can image thick biological specimens with ~500 nm lateral resolution and ~1 μm axial resolution in a reflection geometry. In SDT, multiple-scattering background is rejected through spatiotemporal gating provided by dynamic speckle-field interferometry, while depth-resolved refractive index maps are reconstructed by developing a comprehensive inverse-scattering model that also considers specimen-induced aberrations. Benefiting from the high-resolution and full-field quantitative imaging capabilities of SDT, we successfully imaged red blood cells and quantified their membrane fluctuations behind a turbid medium with a thickness of 2.8 scattering mean-free paths. Most importantly, we performed volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including the mapping of nanoscale topographic features of Dua's and Descemet's membranes that had not been previously visualized.

Label-Free Analysis of Urine Samples with In-Flow Digital Holographic Microscopy

Urinary tract infections are among the most frequent infectious diseases and require screening a great amount of urine samples from patients. However, a high percentage of samples result as negative after urine culture plate tests (CPTs), demanding a simple and fast preliminary technique to screen out the negative samples. We propose a digital holographic microscopy (DHM) method to inspect fresh urine samples flowing in a glass capillary for 3 min, recording holograms at 2 frames per second. After digital reconstruction, bacteria, white and red blood cells, epithelial cells and crystals were identified and counted, and the samples were classified as negative or positive according to clinical cutoff values. Taking the CPT as reference, we processed 180 urine samples and compared the results with those of urine flow cytometry (UFC). Using standard evaluation metrics for our screening test, we found a similar performance for DHM and UFC, indicating DHM as a suitable and fast screening technique retaining several advantages. As a benefit of DHM, the technique is label-free and does not require sample preparation. Moreover, the phase and amplitude images of the cells and other particles present in urine are digitally recorded and can serve for further investigation afterwards.

Label-Free Digital Holotomography Reveals Ibuprofen-Induced Morphological Changes to Red Blood Cells

Understanding the dose-dependent effect of over-the-counter drugs on red blood cells (RBCs) is crucial for hematology and digital pathology. Yet, it is challenging to continuously record the real-time, drug-induced shape changes of RBCs in a label-free manner. Here, we demonstrate digital holotomography (DHTM)-enabled real-time, label-free concentration-dependent and time-dependent monitoring of ibuprofen on RBCs from a healthy donor. The RBCs are segmented based on three-dimensional (3D) and four-dimensional (4D) refractive index tomograms, and their morphological and chemical parameters are retrieved with their shapes classified using machine learning. We directly observed the formation and motion of spicules on the RBC membrane when aqueous solutions of ibuprofen were drop-cast on wet blood, creating rough-membraned echinocyte forms. At low concentrations of 0.25-0.50 mM, the ibuprofen-induced morphological change was transient, but at high concentrations (1-3 mM) the spiculated RBC remained over a period of up to 1.5 h. Molecular simulations confirmed that aggregates of ibuprofen molecules at high concentrations significantly disrupted the RBC membrane structural integrity and lipid order but produced negligible effect at low ibuprofen concentrations. Control experiments on the effect of urea, hydrogen peroxide, and aqueous solutions on RBCs showed zero spicule formation. Our work clarifies the dose-dependent chemical effects on RBCs using label-free microscopes that can be deployed for the rapid detection of overdosage of over-the-counter and prescribed drugs.

Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor

In glioblastoma (GBM) patients, maximal safe resection remains a challenge today due to its invasiveness and diffuse parenchymal infiltration. In this context, plasmonic biosensors could potentially help to discriminate tumor tissue from peritumoral parenchyma based on differences in their optical properties. A nanostructured gold biosensor was used ex vivo to identify tumor tissue in a prospective series of 35 GBM patients who underwent surgical treatment. For each patient, two paired samples, tumor and peritumoral tissue, were extracted. Then, the imprint left by each sample on the surface of the biosensor was individually analyzed, obtaining the difference between their refractive indices. The tumor and non-tumor origins of each tissue were assessed by histopathological analysis. The refractive index (RI) values obtained by analyzing the imprint of the tissue were significantly lower (p = 0.0047) in the peritumoral samples (1.341, Interquartile Range (IQR) 1.339-1.349) compared with the tumor samples (1.350, IQR 1.344-1.363). The ROC (receiver operating characteristic) curve showed the capacity of the biosensor to discriminate between both tissues (area under the curve, 0.8779, p < 0.0001). The Youden index provided an optimal RI cut-off point of 0.003. The sensitivity and specificity of the biosensor were 81% and 80%, respectively. Overall, the plasmonic-based nanostructured biosensor is a label-free system with the potential to be used for real-time intraoperative discrimination between tumor and peritumoral tissue in patients with GBM.

Multi-contrast digital histopathology of mouse organs using quantitative phase imaging and virtual staining

Quantitative phase imaging (QPI) has emerged as a new digital histopathologic tool as it provides structural information of conventional slide without staining process. It is also capable of imaging biological tissue sections with sub-nanometer sensitivity and classifying them using light scattering properties. Here we extend its capability further by using optical scattering properties as imaging contrast in a wide-field QPI. In our first step towards validation, QPI images of 10 major organs of a wild-type mouse have been obtained followed by H&E-stained images of the corresponding tissue sections. Furthermore, we utilized deep learning model based on generative adversarial network (GAN) architecture for virtual staining of phase delay images to a H&E-equivalent brightfield (BF) image analogues. Using the structural similarity index, we demonstrate similarities between virtually stained and H&E histology images. Whereas the scattering-based maps look rather similar to QPI phase maps in the kidney, the brain images show significant improvement over QPI with clear demarcation of features across all regions. Since our technology provides not only structural information but also unique optical property maps, it could potentially become a fast and contrast-enriched histopathology technique.

3D reconstruction of unstained weakly scattering cells from a single defocused hologram

We investigate the problem of 3D complex field reconstruction corresponding to unstained red blood cells (RBCs) with a single defocused off-axis digital hologram. The main challenge in this problem is the localization of cells to the correct axial range. While investigating the volume recovery problem for a continuous phase object like the RBC, we observe an interesting feature of the backpropagated field that it does not show a clear focusing effect. Therefore, sparsity enforcement within the iterative optimization framework using a single hologram data frame cannot effectively restrict the reconstruction to the true object volume. For phase objects, it is known that the amplitude contrast of the backpropagated object field at the focus plane is minimum. We use this information available in the recovered object field in the hologram plane to device depth-dependent weights that are proportional to the inverse of amplitude contrast. This weight function is employed in the iterative steps of the optimization algorithm to assist the object volume localization. The overall reconstruction process is performed using the mean gradient descent (MGD) framework. Experimental illustrations of 3D volume reconstruction of the healthy as well as malaria-infected RBCs are presented. A test sample of polystyrene microsphere bead is also used to validate the axial localization capability of the proposed iterative technique. The proposed methodology is simple to implement experimentally and provides an approximate tomographic solution, which is axially restricted and consistent with the object field data.

Non-Invasive and Minute-Frequency 3D Tomographic Imaging Enabling Long-Term Spatiotemporal Observation of Single Cell Fate

Non-invasive and rapid imaging technique at subcellular resolution is significantly important for multiple biological applications such as cell fate study. Label-free refractive-index (RI)-based 3D tomographic imaging constitutes an excellent candidate for 3D imaging of cellular structures, but its full potential in long-term spatiotemporal cell fate observation is locked due to the lack of an efficient integrated system. Here, a long-term 3D RI imaging system incorporating a cutting-edge white light diffraction phase microscopy module with spatiotemporal stability, and an acoustofluidic device to roll and culture single cells in a customized live cell culture chamber is reported. Using this system, 3D RI imaging experiments are conducted for 250 cells and demonstrate efficient cell identification with high accuracy. Importantly, long-term and frequency-on-demand 3D RI imaging of K562 and MCF-7 cancer cells reveal different characteristics during normal cell growth, drug-induced cell apoptosis, and necrosis of drug-treated cells. Overall, it is believed that the proposed 3D tomographic imaging technique opens up a new avenue for visualizing intracellular structures and will find many applications such as disease diagnosis and nanomedicine.

Dynamic response of red blood cells in health and disease

The viscoelastic response of the red blood cells (RBCs) affected by hematological disorders become severely impaired by the altered biophysical and morphological properties. These include traits like reduced deformability, increased membrane viscosity, and change in cell shape, causing substantial changes in the overall hemodynamics. RBCs, by virtue of their highly elastic membrane and low bending rigidity, exhibit complex dynamics when exposed to cyclic, transient forces in the microcirculation. Here, we employ mesoscopic numerical simulations based on the dissipative particle dynamics (DPD) framework to explore the dynamics of healthy, schizont stage malaria-infected and type 2 diabetes mellitus affected RBCs subjected to external time-dependent loads. The paper focuses on the imposition and cessation of external forcing on the cells of two different typologies, saw-tooth cyclic wave loading and sudden loads in the form of creep and relaxation phenomena. The effects of varying the rate of stress and the applied stress magnitude were investigated. Our simulations disclosed unique shape transitions of the hysteresis curves at varied loading rates. A careful analysis reveals a critical threshold of half cycle time of the from wherein the deformation of all cells observed, healthy or otherwise, falls under the nearly reversible deformation regime displaying minimal energy dissipation. Finally, we also examined the individual effects of the different constitutive and geometric characteristics attributed to the pathological cells and observed interesting recovery dynamics of spherocytes and cells having high shear moduli. The distinguished deformation behaviour of healthy and diseased cells could establish external force as a valuable initial biomarker.

Optical diffraction tomography and image reconstruction to measure host cell alterations caused by divergent Plasmodium species

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium. Understanding the biological features of various parasite forms is important for the optical diagnosis and defining pathological states, which are often constrained by the lack of ambient visualization approaches. Here, we employ a label-free tomographic technique to visualize the host red blood cell (RBC) remodeling process and quantify changes in biochemical properties arising from parasitization. Through this, we provide a quantitative body of information pertaining to the influence of host cell environment on growth, survival, and replication of P. falciparum and P. vivax in their respective host cells: mature erythrocytes and young reticulocytes. These exquisite three-dimensional measurements of infected red cells demonstrats the potential of evolving 3D imaging to advance our understanding of Plasmodium biology and host-parasite interactions.

Multiple-scattering simulator-trained neural network for intensity diffraction tomography

Recovering 3D phase features of complex biological samples traditionally sacrifices computational efficiency and processing time for physical model accuracy and reconstruction quality. Here, we overcome this challenge using an approximant-guided deep learning framework in a high-speed intensity diffraction tomography system. Applying a physics model simulator-based learning strategy trained entirely on natural image datasets, we show our network can robustly reconstruct complex 3D biological samples. To achieve highly efficient training and prediction, we implement a lightweight 2D network structure that utilizes a multi-channel input for encoding the axial information. We demonstrate this framework on experimental measurements of weakly scattering epithelial buccal cells and strongly scattering C. elegans worms. We benchmark the network's performance against a state-of-the-art multiple-scattering model-based iterative reconstruction algorithm. We highlight the network's robustness by reconstructing dynamic samples from a living worm video. We further emphasize the network's generalization capabilities by recovering algae samples imaged from different experimental setups. To assess the prediction quality, we develop a quantitative evaluation metric to show that our predictions are consistent with both multiple-scattering physics and experimental measurements.

Rapid diagnosis of malaria by chemometric peak-free LIBS of trace biometals in blood

Laser Induced Breakdown Spectroscopy (LIBS) trace atomic species of diseased biofluids are subtle (peak-free) in complex spectra. Trace analysis requires a considerable push in analytical strategy. Enabling LIBS with chemometrics can help identify, extract, analyze and interpret the trace species' spectral signatures to give an insight on the biophysiological status of the bodies from which the biofluids originate. We report on the trace quantitative performance of peak-free LIBS enabled by chemometrics modelling using principal components analysis (PCA) for direct artificial neural network (ANN)-based analysis of Cu, Zn, Fe and Mg in Plasmodium falciparum-infected blood in the context of rapid spectral diagnosis of malaria utilizing the biometals as the disease biomarkers. Only one standard is required in this method-to delineate the analyte spectral regions (feature selection) and to test for accuracy. Based on the alteration of the biometal levels and their multivariate and correlational patterns in cultured blood, peripheral finger blood drops dried directly on Nucleopore membrane filters was accurately discriminated as either malaria-infected or healthy. Further the morphological evolution of Plasmodium was accurately predicted using spectral features of the biometals wherein high negative correlations between Fe (- 0.775) and Zn (- 0.881) and high positive correlations between Cu (0.892) and Mg (0.805) with parasitemia were observed. During the first 96 h of malaria infection Cu increases profoundly (from 328 to 1999 ppb) while Fe, Zn and Mg decrease (from 1206 to 674 ppb), (from 1523 to 499 ppb) and (from 23,880 to 19,573 ppb) respectively. Compared with healthy, Plasmodium falciparum-infected blood has high Cu but low levels of Fe, Zn and Mg. Cu and Zn are highly (≥ 0.9) positively correlated while Fe and Cu as well as Zn and Cu are highly (≥ 0.9) negatively correlated. Chemometric peak-free LIBS showed the potential for direct rapid malaria diagnostics in blood based on the levels, alterations and multivariate associations of the trace biometals which are used as biomarkers of the disease.

Ring stage classification of Babesia microti and Plasmodium falciparum using optical diffraction 3D tomographic technique

Background

Babesia is an intraerythrocytic parasite often misdiagnosed as a malaria parasite, leading to inappropriate treatment of the disease especially in co-endemic areas. In recent years, optical diffraction tomography (ODT) has shown great potential in the field of pathogen detection by quantification of three-dimensional (3D) imaging tomograms. The 3D imaging of biological cells is crucial to investigate and provide valuable information about the mechanisms behind the pathophysiology of cells and tissues.

Methods

The early ring stage of P. falciparum were obtained from stored stock of infected RBCs and of B. microti were obtained from infected patients during diagnosis. The ODT technique was applied to analyze and characterize detailed differences between P. falciparum and B. microti ring stage at the single cell level. Based on 3D quantitative information, accurate measurement was performed of morphological, biochemical, and biophysical parameters.

Results

Accurate measurements of morphological parameters indicated that the host cell surface area at the ring stage in B. microti was significantly smaller (140.2 ± 17.1 µm2) than that in P. falciparum (159.0 ± 15.2 µm2), and sphericities showed higher levels in B. microti-parasitized cells (0.66 ± 0.05) than in P. falciparum (0.60 ± 0.04). Based on biochemical parameters, host cell hemoglobin level was significantly higher and membrane fluctuations were respectively more active in P. falciparum-infected cells (30.25 ± 2.96 pg; 141.3 ± 24.68 nm) than in B. microti (27.28 ± 3.52 pg; 110.1 ± 38.83 nm). The result indicates that P. falciparum more actively altered host RBCs than B. microti.

Conclusion

Although P. falciparum and B. microti often show confusable characteristics under the microscope, and the actual three-dimensional properties are different. These differences could be used in differential clinical diagnosis of erythrocytes infected with B. microti and P. falciparum.

Graphical Abstract

Three-dimensional bi-functional refractive index and fluorescence microscopy (BRIEF)

Fluorescence microscopy is a powerful tool for imaging biological samples with molecular specificity. In contrast, phase microscopy provides label-free measurement of the sample's refractive index (RI), which is an intrinsic optical property that quantitatively relates to cell morphology, mass, and stiffness. Conventional imaging techniques measure either the labeled fluorescence (functional) information or the label-free RI (structural) information, though it may be valuable to have both. For example, biological tissues have heterogeneous RI distributions, causing sample-induced scattering that degrades the fluorescence image quality. When both fluorescence and 3D RI are measured, one can use the RI information to digitally correct multiple-scattering effects in the fluorescence image. Here, we develop a new computational multi-modal imaging method based on epi-mode microscopy that reconstructs both 3D fluorescence and 3D RI from a single dataset. We acquire dozens of fluorescence images, each 'illuminated' by a single fluorophore, then solve an inverse problem with a multiple-scattering forward model. We experimentally demonstrate our method for epi-mode 3D RI imaging and digital correction of multiple-scattering effects in fluorescence images.

Refractive Index of Hemoglobin Analysis: A Comparison of Alternating Conditional Expectations and Computational Intelligence Models

Hemoglobin is one of the most important blood elements, and its optical properties will determine all other optical properties of human blood. Since the refractive index (RI) of hemoglobin plays a vital role as a non-invasive indicator of some illnesses, accurate calculation of it would be of great importance. Moreover, measurement of the RI of hemoglobin in the laboratory is time-consuming and expensive; thus, developing a smart approach to estimate this parameter is necessary. In this research, four viable strategies were used to make a quantitative correlation between the RI of hemoglobin and its influencing parameters including the concentration, wavelength, and temperature. First, alternating conditional expectations (ACE), a statistical approach, was employed to generate a correlation to predict the RI of hemoglobin. Then, three different optimized intelligent techniques-optimized neural network (ONN), optimized fuzzy inference system (OFIS), and optimized support vector regression (OSVR)-were used to model the RI. A bat-inspired (BA) algorithm was embedded in the formulation of intelligent models to obtain the optimal values of weights and biases of an artificial neural network, membership functions of the fuzzy inference system, and free parameters of support vector regression. The coefficient of determination, root-mean-square error, average absolute relative error, and symmetric mean absolute percentage error for each of the ACE, ONN, OFIS, and OSVR were found as the measure of each model's accuracy. Results showed that ACE and optimized models (ONN, OFIS, and OSVR) have promising results in the estimation of hemoglobin's RI. Collectively, ACE outperformed ONN, OFIS, and OSVR, while sensitivity analysis indicated that the concentration, wavelength, and, lastly, temperature would have the highest impact on the RI.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Automated wide-field malaria parasite infection detection using Fourier ptychography on stain-free thin-smears

Diagnosis of malaria in endemic areas is hampered by the lack of a rapid, stain-free and sensitive method to directly identify parasites in peripheral blood. Herein, we report the use of Fourier ptychography to generate wide-field high-resolution quantitative phase images of erythrocytes infected with malaria parasites, from a whole blood sample. We are able to image thousands of erythrocytes (red blood cells) in a single field of view and make a determination of infection status of the quantitative phase image of each segmented cell based on machine learning (random forest) and deep learning (VGG16) models. Our random forest model makes use of morphology and texture based features of the quantitative phase images. In order to label the quantitative images of the cells as either infected or uninfected before training the models, we make use of a Plasmodium berghei strain expressing GFP (green fluorescent protein) in all life cycle stages. By overlaying the fluorescence image with the quantitative phase image we could identify the infected subpopulation of erythrocytes for labelling purposes. Our machine learning model (random forest) achieved 91% specificity and 72% sensitivity while our deep learning model (VGG16) achieved 98% specificity and 57% sensitivity. These results highlight the potential for quantitative phase imaging coupled with artificial intelligence to develop an easy to use platform for the rapid and sensitive diagnosis of malaria.

Comparative analysis of Radachlorin accumulation, localization, and photobleaching in three cell lines by means of holographic and fluorescence microscopy

In this paper we compare the response of cells of established lines of different origin: HeLa, A549 and 3T3 to photodynamic treatment with Radachlorin photosensitizer. The analysis was performed on different aspects of the treatment procedure including photosensitizer accumulation, localization and photobleaching in cells and post-treatment dynamics of changes in cellular morphology at different treatment doses. It was shown that in the three cell lines Radachlorin accumulated in lysosomes to much greater extent than in mitochondria. The cells' response to treatment was analyzed by identification of their death pathways and evaluation of average phase shift dynamics using digital holographic microscopy. The analysis performed on the three cell lines allowed us to evaluate treatment doses specific for each pathway in each line. Among the three lines HeLa cells were found to be the most susceptible to treatment while 3T3 cells the most resistant. The comparison of these results with the data on Radachlorin accumulation, localization and photobleaching rates showed that the observed higher sensitivity of HeLa cells to photodynamic treatment correlated with higher photosensitizer uptake and more intensive photobleaching while lower sensitivity of 3T3 cells correlated with lower uptake and less intensive photobleaching.

Lipid Membrane Flexibility in Protic Ionic Liquids

Here, we determine by neutron spin echo spectrometry (NSE) how the flexibility of egg lecithin vesicles depends on solvent composition in two protic ionic liquids (PILs) and their aqueous mixtures. In combination with small-angle neutron scattering (SANS), dynamic light scattering (DLS), and fluorescent probe microscopy, we show that the bending modulus is up to an order of magnitude lower than in water but with no change in bilayer thickness or nonpolar chain composition. This effect is attributed to the dynamic association and exchange of the IL cation between the membrane and bulk liquid, which has the same origin as the underlying amphiphilic nanostructure of the IL solvent itself. This provides a new mechanism by which to tune and control lipid membrane behavior.

Biophysical Tools and Concepts Enable Understanding of Asexual Blood Stage Malaria

Forces and mechanical properties of cells and tissues set constraints on biological functions, and are key determinants of human physiology. Changes in cell mechanics may arise from disease, or directly contribute to pathogenesis. Malaria gives many striking examples. Plasmodium parasites, the causative agents of malaria, are single-celled organisms that cannot survive outside their hosts; thus, thost-pathogen interactions are fundamental for parasite’s biological success and to the host response to infection. These interactions are often combinations of biochemical and mechanical factors, but most research focuses on the molecular side. However, Plasmodium infection of human red blood cells leads to changes in their mechanical properties, which has a crucial impact on disease pathogenesis because of the interaction of infected red blood cells with other human tissues through various adhesion mechanisms, which can be probed and modelled with biophysical techniques. Recently, natural polymorphisms affecting red blood cell biomechanics have also been shown to protect human populations, highlighting the potential of understanding biomechanical factors to inform future vaccines and drug development. Here we review biophysical techniques that have revealed new aspects of Plasmodium falciparum invasion of red blood cells and cytoadhesion of infected cells to the host vasculature. These mechanisms occur differently across Plasmodium species and are linked to malaria pathogenesis. We highlight promising techniques from the fields of bioengineering, immunomechanics, and soft matter physics that could be beneficial for studying malaria. Some approaches might also be applied to other phases of the malaria lifecycle and to apicomplexan infections with complex host-pathogen interactions.

Optical-force-controlled red-blood-cell microlenses for subwavelength trapping and imaging

We demonstrate that red blood cells (RBCs), with an adjustable focusing effect controlled by optical forces, can act as bio-microlenses for trapping and imaging subwavelength objects. By varying the laser power injected into a tapered fiber probe, the shape of a swelled RBC can be changed from spherical to ellipsoidal by the optical forces, thus adjusting the focal length of such bio-microlens in a range from 3.3 to 6.5 µm. An efficient optical trapping and a simultaneous fluorescence detecting of a 500-nm polystyrene particle have been realized using the RBC microlens. Assisted by the RBC microlens, a subwavelength imaging has also been achieved, with a magnification adjustable from 1.6× to 2×. The RBC bio-microlenses may offer new opportunities for the development of fully biocompatible light-driven devices in diagnosis of blood disease.

Quantitative phase velocimetry measures bulk intracellular transport of cell mass during the cell cycle

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of bulk material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle.

A particle-based computational model to analyse remodelling of the red blood cell cytoskeleton during malaria infections

Red blood cells can withstand the harsh mechanical conditions in the vasculature only because the bending rigidity of their plasma membrane is complemented by the shear elasticity of the underlying spectrin-actin network. During an infection by the malaria parasite Plasmodium falciparum, the parasite mines host actin from the junctional complexes and establishes a system of adhesive knobs, whose main structural component is the knob-associated histidine rich protein (KAHRP) secreted by the parasite. Here we aim at a mechanistic understanding of this dramatic transformation process. We have developed a particle-based computational model for the cytoskeleton of red blood cells and simulated it with Brownian dynamics to predict the mechanical changes resulting from actin mining and KAHRP-clustering. Our simulations include the three-dimensional conformations of the semi-flexible spectrin chains, the capping of the actin protofilaments and several established binding sites for KAHRP. For the healthy red blood cell, we find that incorporation of actin protofilaments leads to two regimes in the shear response. Actin mining decreases the shear modulus, but knob formation increases it. We show that dynamical changes in KAHRP binding affinities can explain the experimentally observed relocalization of KAHRP from ankyrin to actin complexes and demonstrate good qualitative agreement with experiments by measuring pair cross-correlations both in the computer simulations and in super-resolution imaging experiments.

Malaria is one of the deadliest infectious diseases and its symptoms are related to the blood stage, when the parasite multiplies within red blood cells. In order to avoid clearance by the spleen, the parasite produces specific factors like the adhesion receptor PfEMP1 and the multifunctional protein KAHRP that lead to the formation of adhesive knobs on the surface of the red blood cells and thus increase residence time in the vasculature. We have developed a computational model for the parasite-induced remodelling of the actin-spectrin network to quantitatively predict the dynamical changes in the mechanical properties of the infected red blood cells and the spatial distribution of the different protein components of the membrane skeleton. Our simulations show that KAHRP can relocate to actin junctions due to dynamical changes in binding affinities, in good qualitative agreement with super-resolution imaging experiments. In the future, our simulation framework can be used to gain further mechanistic insight into the way malaria parasites attack the red blood cell cytoskeleton.

Measurement of Variations in Gas Refractive Index with 10-9 Resolution Using Laser Speckle

Highly resolved determination of refractive index is vital in fields ranging from biosensing through to laser range finding. Laser speckle is known to be a sensitive probe of the properties of the light and the environment, but to date speckle-based refractive index measurements have been restricted to 10^-6 resolution. In this work we identify a strategy to optimize the sensitivity of speckle to refractive index changes, namely, by maximizing the width of the distribution of optical path lengths in the medium. We show that this can be realized experimentally by encapsulating the medium of interest within an integrating sphere. While mitigating against laser-induced heating effects, we demonstrate that variations of the refractive index of air as small as 4.5 × 10^-9 can be resolved with an uncertainty of 7 × 10^-10. This is an improvement of 3 orders of magnitude when compared to previous speckle-based methods.

In-depth biological analysis of alteration in Plasmodium knowlesi-infected red blood cells using a noninvasive optical imaging technique

Background

Imaging techniques are commonly used to understand disease mechanisms and their biological features in the microenvironment of the cell. Many studies have added to our understanding of the biology of the malaria parasite Plasmodium knowlesi from functional in vitro and imaging analysis using serial block-face scanning electron microscopy (SEM). However, sample fixation and metal coating during SEM analysis can alter the parasite membrane.

Methods

In this study, we used noninvasive diffraction optical tomography (DOT), also known as holotomography, to explore the morphological, biochemical, and mechanical alterations of each stage of P. knowlesi-infected red blood cells (RBCs). Each stage of the parasite was synchronized using Nycodenz and magnetic-activated cell sorting (MACS) for P. knowlesi and P. falciparum, respectively. Holotomography was applied to measure individual three-dimensional refractive index tomograms without metal coating, fixation, or additional dye agent.

Results

Distinct profiles were found on the surface area and hemoglobin content of the two parasites. The surface area of P. knowlesi-infected RBCs showed significant expansion, while P. falciparum-infected RBCs did not show any changes compared to uninfected RBCs. In terms of hemoglobin consumption, P. falciparum tended to consume hemoglobin more than P. knowlesi. The observed profile of P. knowlesi-infected RBCs generally showed similar results to other studies, proving that this technique is unbiased.

Conclusions

The observed profile of the surface area and hemoglobin content of malaria infected-RBCs can potentially be used as a diagnostic parameter to distinguish P. knowlesi and P. falciparum infection. In addition, we showed that holotomography could be used to study each Plasmodium species in greater depth, supporting strategies for the development of diagnostic and treatment strategies for malaria.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05182-1.

Acoustofluidic interferometric device for rapid single-cell physical phenotyping

High-throughput single-cell analysis based on physical properties (such as morphology or mechanics) is emerging as a powerful tool to inform clinical research, with a great potential for translation towards diagnosis. Here we present a novel microfluidic approach adopting acoustic waves to manipulate and mechanically stimulate single cells, and interferometry to track changes in the morphology and measure size, deformability, and refractive index of non-adherent cells. The method is based on the integration within the acoustofluidic channel of a low-finesse Fabry-Perot resonator, providing very high sensitivity and a speed potentially suitable to obtain the high-throughput necessary to handle the variability stemming from the biological diversity of single cells. The proposed approach is applied to a set of different samples: reference polystyrene beads, algae and yeast. The results demonstrate the capability of the acoustofluidic interferometric device to detect and quantify optomechanical properties of single cells with a throughput suitable to address label-free single-cell clinical analysis.

Speeding up reconstruction of 3D tomograms in holographic flow cytometry via deep learning

Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us to access high-resolution imaging with high-throughput, the huge amount of time-lapse holographic images to be processed (hundreds of digital holograms per cell) constitutes the actual bottleneck. This prevents the system from being suitable for lab-on-a-chip platforms in real-world applications, where fast analysis of measured data is mandatory. Here we demonstrate a significant speeding-up reconstruction of phase-contrast tomograms by introducing in the processing pipeline a multi-scale fully-convolutional context aggregation network. Although it was originally developed in the context of semantic image analysis, we demonstrate for the first time that it can be successfully adapted to a holographic lab-on-chip platform for achieving 3D tomograms through a faster computational process. We trained the network with input-output image pairs to reproduce the end-to-end holographic reconstruction process, i.e. recovering quantitative phase maps (QPMs) of single cells from their digital holograms. Then, the sequence of QPMs of the same rotating cell is used to perform the tomographic reconstruction. The proposed approach significantly reduces the computational time for retrieving tomograms, thus making them available in a few seconds instead of tens of minutes, while essentially preserving the high-content information of tomographic data. Moreover, we have accomplished a compact deep convolutional neural network parameterization that can fit into on-chip SRAM and a small memory footprint, thus demonstrating its possible exploitation to provide onboard computations for lab-on-chip devices with low processing hardware resources.

Label-free imaging and evaluation of characteristic properties of asthma-derived eosinophils using optical diffraction tomography

Optical diffraction tomography (ODT), an emerging imaging technique that does not require fluorescent staining, can measure the three-dimensional distribution of the refractive index (RI) of organelles. In this study, we used ODT to characterize the pathological characteristics of human eosinophils derived from asthma patients presenting with eosinophilia. In addition to morphological information about organelles appearing in eosinophils, including the cytoplasm, nucleus, and vacuole, we succeeded in imaging specific granules and quantifying the RI values of the granules. Interestingly, ODT analysis showed that the RI (i.e., molecular density) of granules was significantly different between eosinophils from asthma patients and healthy individuals without eosinophilia, and that vacuoles were frequently found in the cells of asthma patients. Our results suggest that the physicochemical properties of eosinophils derived from patients with asthma can be quantitatively distinguished from those of healthy individuals. The method will provide insight into efficient evaluation of the characteristics of eosinophils at the organelle level for various diseases with eosinophilia.

Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for the field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time-consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a solution for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45 and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges.

Characterizing Organelles in Live Stem Cells Using Label-Free Optical Diffraction Tomography

Label-free optical diffraction tomography (ODT), an imaging technology that does not require fluorescent labeling or other pre-processing, can overcome the limitations of conventional cell imaging technologies, such as fluorescence and electron microscopy. In this study, we used ODT to characterize the cellular organelles of three different stem cells-namely, human liver derived stem cell, human umbilical cord matrix derived mesenchymal stem cell, and human induced pluripotent stem cell-based on their refractive index and volume of organelles. The physical property of each stem cell was compared with that of fibroblast. Based on our findings, the characteristic physical properties of specific stem cells can be quantitatively distinguished based on their refractive index and volume of cellular organelles. Altogether, the method employed herein could aid in the distinction of living stem cells from normal cells without the use of fluorescence or specific biomarkers.

Roadmap on Digital Holography-Based Quantitative Phase Imaging

Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups. It also briefly discusses the present and future perspectives of 2D and 3D QPI research based on digital holographic microscopy, holographic tomography, and their applications.

The effect of pupil transmittance on axial resolution of reflection phase microscopy

A reflection phase microscope (RPM) can be equipped with the capability of depth selection by employing a gating mechanism. However, it is difficult to achieve an axial resolution close to the diffraction limit in real implementation. Here, we systematically investigated the uneven interference contrast produced by pupil transmittance of the objective lens and found that it was the main cause of the practical limit that prevents the axial resolution from reaching its diffraction limit. Then we modulated the power of illumination light to obtain a uniform interference contrast over the entire pupil. Consequently, we could achieve an axial resolution fairly close to the diffraction limit set by the experimental conditions.

Application of quantitative cell imaging using label-free optical diffraction tomography

The cell is three-dimensionally and dynamically organized into cellular compartments, including the endoplasmic reticulum, mitochondria, vesicles, and nucleus, which have high relative molecular density. The structure and functions of these compartments and organelles may be deduced from the diffusion and interaction of related biomolecules. Among these cellular components, various protein molecules can freely access the nucleolus or mitotic chromosome through Brownian diffusion, even though they have a densely packed structure. However, physicochemical properties of the nucleolus and chromosomes, such as molecular density and volume, are not yet fully understood under changing cellular conditions. Many studies have been conducted based on high-resolution imaging and analysis techniques using fluorescence. However, there are limitations in imaging only fluorescently labeled molecules, and cytotoxicity occurs during three-dimensional imaging. Alternatively, the recently developed label-free three-dimensional optical diffraction tomography (ODT) imaging technique can divide various organelles in cells into volumes and analyze them by refractive index, although specific molecules cannot be observed. A previous study established an analytical method that provides comprehensive insights into the physical properties of the nucleolus and mitotic chromosome by utilizing the advantages of ODT and fluorescence techniques, such as fluorescence correlation spectroscopy and confocal laser scanning microscopy. This review article summarizes a recent study and discusses the future aspects of the ODT for cellular compartments.

Functionalized supported membranes for quantifying adhesion of P. falciparum-infected erythrocytes

The pathology of Plasmodium falciparum malaria is largely defined by the cytoadhesion of infected erythrocytes to the microvascular endothelial lining. The complexity of the endothelial surface and the large range of interactions available for the infected erythrocyte via parasite-encoded adhesins make analysis of critical contributions during cytoadherence challenging to define. Here, we have explored supported membranes functionalized with two important adhesion receptors, ICAM1 or CD36, as a quantitative biomimetic surface to help understand the processes involved in cytoadherence. Parasitized erythrocytes bound to the receptor-functionalized membranes with high efficiency and selectivity under both static and flow conditions, with infected wild-type erythrocytes displaying a higher binding capacity than do parasitized heterozygous sickle cells. We further show that the binding efficiency decreased with increasing intermolecular receptor distance and that the cell-surface contacts were highly dynamic and increased with rising wall shear stress as the cell underwent a shape transition. Computer simulations using a deformable cell model explained the wall-shear-stress-induced dynamic changes in cell shape and contact area via the specific physical properties of erythrocytes, the density of adhesins presenting knobs, and the lateral movement of receptors in the supported membrane.

Spatial light interference microscopy: principle and applications to biomedicine

In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, and full-field methods. Then, we outline SLIM imaging from theory and instrumentation to diffraction tomography. Zernike's phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that enables high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. We introduce two methods for solving the inverse problem using SLIM, white-light tomography, and Wolf phase tomography. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.

Isotropically resolved label-free tomographic imaging based on tomographic moulds for optical trapping

A major challenge in three-dimensional (3D) microscopy is to obtain accurate spatial information while simultaneously keeping the microscopic samples in their native states. In conventional 3D microscopy, axial resolution is inferior to spatial resolution due to the inaccessibility to side scattering signals. In this study, we demonstrate the isotropic microtomography of free-floating samples by optically rotating a sample. Contrary to previous approaches using optical tweezers with multiple foci which are only applicable to simple shapes, we exploited 3D structured light traps that can stably rotate freestanding complex-shaped microscopic specimens, and side scattering information is measured at various sample orientations to achieve isotropic resolution. The proposed method yields an isotropic resolution of 230 nm and captures structural details of colloidal multimers and live red blood cells, which are inaccessible using conventional tomographic microscopy. We envision that the proposed approach can be deployed for solving diverse imaging problems that are beyond the examples shown here.

Application of digital holographic tomography in antitumor effect of cantharides complex on 4T1 breast cancer cells

The study focuses on a methodology providing noninvasive monitoring and evaluation of the antitumor effect of traditional Chinese medicine, cantharides complex (canth), on 4T1 breast tumor cells. Digital holographic tomography (DHT) and developed data post-processing algorithms were used for quantitative estimation of changes in optical and morphological parameters of cells. We calculated and compared data on the refractive index, thickness, and projected area of 4T1 breast tumor cells in control untreated specimens and those treated with doxorubicin hydrochloride (DOX), canth, and their combinations. Post-treatment changes in cellular morphology recorded by DHT demonstrated that the two drugs led to noticeably different morphological changes in cells that can be presumably associated with different pathways of their death, apoptosis, or necrosis. The effect of combined treatment with these two drugs strongly depended on their relative concentrations and could lead to changes characteristic either for DOX or for canth; however, being more profound than those obtained when using each drug solely. The results obtained by DHT are in a good correspondence with commonly used cell viability analysis and immunofluorescent analysis of changes in cellular cytoskeleton.

More than just a barrier: using physical models to couple membrane shape to cell function

The correct execution of many cellular processes, such as division and motility, requires the cell to adopt a specific shape. Physically, these shapes are determined by the interplay of the plasma membrane and internal cellular driving factors. While the plasma membrane defines the boundary of the cell, processes inside the cell can result in the generation of forces that deform the membrane. These processes include protein binding, the assembly of protein superstructures, and the growth and contraction of cytoskeletal networks. Due to the complexity of the cell, relating observed membrane deformations back to internal processes is a challenging problem. Here, we review cell shape changes in endocytosis, cell adhesion, cell migration and cell division and discuss how by modeling membrane deformations we can investigate the inner working principles of the cell.

Limited-angle tomographic phase microscopy utilizing confocal scanning fluorescence microscopy

We present a multimodal imaging technique, combining tomographic phase microscopy with limited angular projection range and number, and two-channel spinning-disk confocal scanning fluorescence microscopy. This technique allows high-accuracy 3D refractive index (RI) profiling of live cells in spite of the missing projections. The cellular outer shape and its interior organelles measured by the confocal fluorescence imaging not only specify the cell in molecular levels, but also provide the 3D distributions of the whole cell as well as its organelles. We take these additional 3D morphological details as constraints in Gerchberg-Papoulis-based optical diffraction tomography algorithm. We then obtain an accurate 3D RI tomogram, even with a sparse angular range having a small number of perspective projections, otherwise providing low-accuracy RI reconstruction. Then, we obtain both cellular molecular specificity and inner RI values of the cell and its organelles. We compare the reconstructed 3D RI profiles of various samples, demonstrating the superiority of the proposed technique.

Holographic tomography: techniques and biomedical applications [Invited]

Holographic tomography (HT) is an advanced label-free optical microscopic imaging method used for biological studies. HT uses digital holographic microscopy to record the complex amplitudes of a biological sample as digital holograms and then numerically reconstruct the sample's refractive index (RI) distribution in three dimensions. The RI values are a key parameter for label-free bio-examination, which correlate with metabolic activities and spatiotemporal distribution of biophysical parameters of cells and their internal organelles, tissues, and small-scale biological objects. This article provides insight on this rapidly growing HT field of research and its applications in biology. We present a review summary of the HT principle and highlight recent technical advancement in HT and its applications.