Towards 3D modelling and imaging of infection scenarios at the single cell level using holographic optical tweezers and digital holographic microscopy

3D integral imaging of acoustically trapped objects

3D imaging provides crucial details about the objects and scenes that may not be obtained via 2D imaging methods. However, there are several applications in which the object to be 3D-imaged requires to be immobilized. The integrated digital holographic microscopy (DHM) and optical trapping (OT) system is a useful solution for such a task, but both DHM and OT are mostly suitable for microscopic specimens. Here, for the first time to the best of our knowledge and as an analogy to the DHM-OT system, we introduce integral imaging (InIm) and acoustic trapping (AT) integrated system for 3D imaging of immobilized mesoscopic and macroscopic objects. Post-processing of InIm data enables reconstructing the scene at any arbitrary plane, therefore, it re-focuses any particular depth of the object, which is a curtail task, especially when the object is trapped by AT. We demonstrate the capability of our system by simultaneous trapping and 3D imaging of single and multiple irregularly shaped objects with mm sizes.

Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network

The healthcare industry is in dire need of rapid microbial identification techniques for treating microbial infections. Microbial infections are a major healthcare issue worldwide, as these widespread diseases often develop into deadly symptoms. While studies have shown that an early appropriate antibiotic treatment significantly reduces the mortality of an infection, this effective treatment is difficult to practice. The main obstacle to early appropriate antibiotic treatments is the long turnaround time of the routine microbial identification, which includes time-consuming sample growth. Here, we propose a microscopy-based framework that identifies the pathogen from single to few cells. Our framework obtains and exploits the morphology of the limited sample by incorporating three-dimensional quantitative phase imaging and an artificial neural network. We demonstrate the identification of 19 bacterial species that cause bloodstream infections, achieving an accuracy of 82.5% from an individual bacterial cell or cluster. This performance, comparable to that of the gold standard mass spectroscopy under a sufficient amount of sample, underpins the effectiveness of our framework in clinical applications. Furthermore, our accuracy increases with multiple measurements, reaching 99.9% with seven different measurements of cells or clusters. We believe that our framework can serve as a beneficial advisory tool for clinicians during the initial treatment of infections.

Patch-Based U-Net Model for Isotropic Quantitative Differential Phase Contrast Imaging

Quantitative differential phase-contrast (qDPC) imaging is a label-free phase retrieval method for weak phase objects using asymmetric illumination. However, qDPC imaging with fewer intensity measurements leads to anisotropic phase distribution in reconstructed images. In order to obtain isotropic phase transfer function, multiple measurements are required; thus, it is a time-consuming process. Here, we propose the feasibility of using deep learning (DL) method for isotropic qDPC microscopy from the least number of measurements. We utilize a commonly used convolutional neural network namely U-net architecture, trained to generate 12-axis isotropic reconstructed cell images (i.e. output) from 1-axis anisotropic cell images (i.e. input). To further extend the number of images for training, the U-net model is trained with a patch-wise approach. In this work, seven different types of living cell images were used for training, validation, and testing datasets. The results obtained from testing datasets show that our proposed DL-based method generates 1-axis qDPC images of similar accuracy to 12-axis measurements. The quantitative phase value in the region of interest is recovered from 66% up to 97%, compared to ground-truth values, providing solid evidence for improved phase uniformity, as well as retrieved missing spatial frequencies in 1-axis reconstructed images. In addition, results from our model are compared with paired and unpaired CycleGANs. Higher PSNR and SSIM values show the advantage of using the U-net model for isotropic qDPC microscopy. The proposed DL-based method may help in performing high-resolution quantitative studies for cell biology.

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.

Three-dimensional label-free observation of individual bacteria upon antibiotic treatment using optical diffraction tomography

Measuring alterations in bacteria upon antibiotic application is important for basic studies in microbiology, drug discovery, clinical diagnosis, and disease treatment. However, imaging and 3D time-lapse response analysis of individual bacteria upon antibiotic application remain largely unexplored mainly due to limitations in imaging techniques. Here, we present a method to systematically investigate the alterations in individual bacteria in 3D and quantitatively analyze the effects of antibiotics. Using optical diffraction tomography, in-situ responses of Escherichia coli and Bacillus subtilis to various concentrations of ampicillin were investigated in a label-free and quantitative manner. The presented method reconstructs the dynamic changes in the 3D refractive-index distributions of living bacteria in response to antibiotics at sub-micrometer spatial resolution.

Quantitative phase imaging of cells in a flow cytometry arrangement utilizing Michelson interferometer-based off-axis digital holographic microscopy

We combined Michelson-interferometer-based off-axis digital holographic microscopy (DHM) with a common flow cytometry (FCM) arrangement. Utilizing object recognition procedures and holographic autofocusing during the numerical reconstruction of the acquired off-axis holograms, sharply focused quantitative phase images of suspended cells in flow were retrieved without labeling, from which biophysical cellular features of distinct cells, such as cell radius, refractive index and dry mass, can be subsequently retrieved in an automated manner. The performance of the proposed concept was first characterized by investigations on microspheres that were utilized as test standards. Then, we analyzed two types of pancreatic tumor cells with different morphology to further verify the applicability of the proposed method for quantitative live cell imaging. The retrieved biophysical datasets from cells in flow are found in good agreement with results from comparative investigations with previously developed DHM methods under static conditions, which demonstrates the effectiveness and reliability of our approach. Our results contribute to the establishment of DHM in imaging FCM and prospect to broaden the application spectrum of FCM by providing complementary quantitative imaging as well as additional biophysical cell parameters which are not accessible in current high-throughput FCM measurements.

3D dynamics of bacteria wall entrapment at a water-air interface

Swimming bacteria can be trapped for prolonged times at the surface of an impenetrable boundary. The subsequent surface confined motility is found to be very sensitive to the physico-chemical properties of the interfaces which determine the boundary conditions for the flow. The quantitative understanding of this complex dynamics requires detailed and systematic experimental data to validate theoretical models for both flagellar propulsion and interfacial dynamics. Using a combination of optical trapping and holographic imaging we study the 3D dynamics of wall entrapment of swimming bacteria that are sequentially released towards a surfactant-covered liquid-air interface. We find that an incompressible surfactant model for the interface quantitatively accounts for the observed normal and tangential speed of bacteria as they approach the boundary. Surprisingly we also find that, although bacteria circulate over the air phase in counterclockwise circular trajectories, typical of free-slip interfaces, the body axis is still tilted "nose down" as found for no-slip interfaces.

Optical excitation and detection of neuronal activity

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical contact or fluorescent imaging at target locations, which is often limited by photobleaching and phototoxicity. In this paper, we show that phase imaging can report the intracellular transport induced by optogenetic stimulation. We developed a multimodal instrument that can both stimulate cells with subcellular spatial resolution and detect optical pathlength (OPL) changes with nanometer scale sensitivity. We found that OPL fluctuations following stimulation are consistent with active organelle transport. Furthermore, the results indicate a broadening in the transport velocity distribution, which is significantly higher in stimulated cells compared to optogenetically inactive cells. It is likely that this label-free, contactless measurement of optogenetic response will provide an enabling approach to neuroscience.

Isotropic differential phase contrast microscopy for quantitative phase bio-imaging

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi-axis intensity measurements in wide-field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high-speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin-film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro-lens array, as well as label-free live human cell samples.

Synchronization in pairs of rotating active biomotors

Although synchronization is a well-known physical phenomenon, experimental studies of its emergence in living bacterial cells are still scarce. The difficulty in generating a controlled scenario to detect synchronization has limited the experimental outcomes so far. We present a realization based on holographic optical tweezers in which adhered pairs of self-propelled bacteria rotate in a plane. The separation distance between the bacteria determines the strength of the hydrodynamic coupling. Despite the noisy environment and autonomous dynamics of the living bacteria, we find evidence of phase locking and frequency entrainment in their rotation. The observation of higher order frequency synchronization is also discussed.

The Role of Nanomechanics in Healthcare

Nanomechanics has played a vital role in pushing our capability to detect, probe, and manipulate the biological species, such as proteins, cells, and tissues, paving way to a deeper knowledge and superior strategies for healthcare. Nanomechanical characterization techniques, such as atomic force microscopy, nanoindentation, nanotribology, optical tweezers, and other hybrid techniques have been utilized to understand the mechanics and kinetics of biospecies. Investigation of the mechanics of cells and tissues has provided critical information about mechanical characteristics of host body environments. This information has been utilized for developing biomimetic materials and structures for tissue engineering and artificial implants. This review summarizes nanomechanical characterization techniques and their potential applications in healthcare research. The principles and examples of label-free detection of cancers and myocardial infarction by nanomechanical cantilevers are discussed. The vital importance of nanomechanics in regenerative medicine is highlighted from the perspective of material selection and design for developing biocompatible scaffolds. This review interconnects the advancements made in fundamental materials science research and biomedical technology, and therefore provides scientific insight that is of common interest to the researchers working in different disciplines of healthcare science and technology.

Quantitative phase imaging for medical diagnosis

Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter- and intra-observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label-free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date. [Image adapted from Y. Park, M. Diez-Silva, G. Popescu, G. Lykotrafitis, W. Choi, M. S. Feld, and S. Suresh, Proc. Natl. Acad. Sci. 105, 13730-13735 (2008).].

Holographic intravital microscopy for 2-D and 3-D imaging intact circulating blood cells in microcapillaries of live mice

Intravital microscopy is an essential tool that reveals behaviours of live cells under conditions close to natural physiological states. So far, although various approaches for imaging cells in vivo have been proposed, most require the use of labelling and also provide only qualitative imaging information. Holographic imaging approach based on measuring the refractive index distributions of cells, however, circumvent these problems and offer quantitative and label-free imaging capability. Here, we demonstrate in vivo two- and three-dimensional holographic imaging of circulating blood cells in intact microcapillaries of live mice. The measured refractive index distributions of blood cells provide morphological and biochemical properties including three-dimensional cell shape, haemoglobin concentration, and haemoglobin contents at the individual cell level. With the present method, alterations in blood flow dynamics in live healthy and sepsis-model mice were also investigated.

Tomographic phase microscopy with 180° rotation of live cells in suspension by holographic optical tweezers

We present a new tomographic phase microscopy (TPM) approach that allows capturing the three-dimensional refractive index structure of single cells in suspension without labeling, using 180° rotation of the cells. This is obtained by integrating an external off-axis interferometer for wide-field wave front acquisition with holographic optical tweezers (HOTs) for trapping and micro-rotation of the suspended cells. In contrast to existing TPM approaches for cell imaging, our approach does not require anchoring the sample to a rotating stage, nor is it limited in angular range as is the illumination rotation approach. Thus, it allows noninvasive TPM of suspended live cells in a wide angular range. The proposed technique is experimentally demonstrated by capturing the three-dimensional refractive index map of yeast cells, while collecting interferometric projections at an angular range of 180° with 5° steps. The interferometric projections are processed by both the filtered back-projection method and the diffraction theory method. The experimental system is integrated with a spinning disk confocal fluorescent microscope for validation of the label-free TPM results.

Optically trapped bacteria pairs reveal discrete motile response to control aggregation upon cell-cell approach

Aggregation of bacteria plays a key role in the formation of many biofilms. The critical first step is cell-cell approach, and yet the ability of bacteria to control the likelihood of aggregation during this primary phase is unknown. Here, we use optical tweezers to measure the force between isolated Bacillus subtilis cells during approach. As we move the bacteria towards each other, cell motility (bacterial swimming) initiates the generation of repulsive forces at bacterial separations of ~3 μm. Moreover, the motile response displays spatial sensitivity with greater cell-cell repulsion evident as inter-bacterial distances decrease. To examine the environmental influence on the inter-bacterial forces, we perform the experiment with bacteria suspended in Tryptic Soy Broth, NaCl solution and deionised water. Our experiments demonstrate that repulsive forces are strongest in systems that inhibit biofilm formation (Tryptic Soy Broth), while attractive forces are weak and rare, even in systems where biofilms develop (NaCl solution). These results reveal that bacteria are able to control the likelihood of aggregation during the approach phase through a discretely modulated motile response. Clearly, the force-generating motility we observe during approach promotes biofilm prevention, rather than biofilm formation.

Identification of meat-associated pathogens via Raman microspectroscopy

The development of fast and reliable sensing techniques to detect food-borne microorganisms is a permanent concern in food industry and health care. For this reason, Raman microspectroscopy was applied to rapidly detect pathogens in meat, which could be a promising supplement to currently established methods. In this context, a spectral database of 19 species of the most important harmful and non-pathogenic bacteria associated with meat and poultry was established. To create a meat-like environment the microbial species were prepared on three different agar types. The whole amount of Raman data was taken as a basis to build up a three level classification model by means of support vector machines. Subsequent to a first classifier that differentiates between Raman spectra of Gram-positive and Gram-negative bacteria, two decision knots regarding bacterial genus and species follow. The different steps of the classification model achieved accuracies in the range of 90.6%-99.5%. This database was then challenged with independently prepared test samples. By doing so, beef and poultry samples were spiked with different pathogens associated with food-borne diseases and then identified. The test samples were correctly assigned to their genus and for the most part down to the species-level i.e. a differentiation from closely-related non-pathogenic members was achieved.