Label-free Quantitative Imaging Research Articles

Quantitative Label-Free Chemical Imaging of PLGA Nanoparticles in Cells and Tissues with Single-Particle Sensitivity.

Nanomedicine has brought significant advancements to healthcare by utilizing nanotechnology in medicine. Despite much promise, the further development of nanocarriers for clinical use has been hindered by a lack of understanding and visualization of nano-bio interactions. Conventional imaging methods have limitations in resolution, sensitivity, and specificity. This study introduces a label-free optical approach using stimulated Raman scattering (SRS) microscopy to image poly(lactic-co-glycolic acid) (PLGA) nanocarriers, the most widely used polymeric nanocarrier for delivery therapeutic agents, with single-particle sensitivity and quantification capabilities. A unique Raman peak was identified for PLGA ester, enabling generalized bio-orthogonal bond imaging. We demonstrated quantitative SRS imaging of PLGA nanocarriers across different biological systems from cells to animal tissues. This label-free imaging method provides a powerful tool for studying this prevalent nanocarrier and quantitatively visualizing their distribution, interaction, and clearance in vivo.

Quantifying Intracellular Nanoparticle Distributions with Three-Dimensional Super-Resolution Microscopy.

Super-resolution microscopy can transform our understanding of nanoparticle-cell interactions. Here, we established a super-resolution imaging technology to visualize nanoparticle distributions inside mammalian cells. The cells were exposed to metallic nanoparticles and then embedded within different swellable hydrogels to enable quantitative three-dimensional (3D) imaging approaching electron-microscopy-like resolution using a standard light microscope. By exploiting the nanoparticles' light scattering properties, we demonstrated quantitative label-free imaging of intracellular nanoparticles with ultrastructural context. We confirmed the compatibility of two expansion microscopy protocols, protein retention and pan-expansion microscopy, with nanoparticle uptake studies. We validated relative differences between nanoparticle cellular accumulation for various surface modifications using mass spectrometry and determined the intracellular nanoparticle spatial distribution in 3D for entire single cells. This super-resolution imaging platform technology may be broadly used to understand the nanoparticle intracellular fate in fundamental and applied studies to potentially inform the engineering of safer and more effective nanomedicines.

Progress of Three-Dimensional, Label-Free Quantitative Imaging of Refractive Index in Biological Samples

Progress of Three-Dimensional, Label-Free Quantitative Imaging of Refractive Index in Biological Samples

Single cell capture, isolation, and long-term in-situ imaging using quantitative self-interference spectroscopy.

Single cell research with microfluidic chip is of vital importance in biomedical studies and clinical medicine. Simultaneous microfluidic cell manipulations and long-term cell monitoring needs further investigations due to the lack of label-free quantitative imaging techniques and systems. In this work, single cell capture, isolation and long-term in-situ monitoring was realized with a microfluidic cell chip, compact cell incubator and quantitative self-interference spectroscopy. The proposed imaging method could obtain quantitative and dynamic refractive index distribution in living cells. And the designed microfluidic chip could capture and isolate single cells. The customized incubator could support cell growth conditions when single cell was captured in microfluidic chip. According to the results, single cells could be trapped, transferred and pushed into the culture chamber with the microfluidic chip. The incubator could culture single cells in the chip for 120 h. The refractive index sensitivity of the proposed quantitative imaging method was 0.0282 and the relative error was merely 0.04%.

Quantifying Intracellular Particle Flows by DIC Object Tracking

Label-free imaging techniques such as differential interference contrast (DIC) allow the observation of cells and large subcellular structures in their native, unperturbed states with minimal exposure to light. The development of robust computational image-analysis routines is vital to quantitative label-free imaging. The reliability of quantitative analysis of time-series microscopy data based on single-particle tracking relies on accurately detecting objects as distinct from the background, i.e., segmentation. Typical approaches to segmenting DIC images either involve converting images to those resembling phase contrast, mimicking the optics of DIC object formation, or using the morphological properties of objects. Here, we describe MATLAB based, single-particle tracking tool with a GUI for mobility analysis of objects from in vitro and in vivo DIC time-series microscopy. The tool integrates contrast enhancement with multiple modified Gaussian filters, automated threshold detection for segmentation and minimal distance-based two-dimensional single-particle tracking. We compare the relative performance of multiple filters and demonstrate the utility of the tool for DIC object tracking (DICOT). We quantify subcellular dynamics of a time series of Caenorhabditis elegans embryos in the one-celled stage by detecting birefringent yolk granules in the cytoplasm with high precision. The resulting two-dimensional map of oscillatory dynamics of granules quantifies the cytoplasmic flows driven by anaphasic spindle oscillations. The frequency of oscillations across the anterior-posterior (A-P) and transverse axes of the embryo correspond well with the reported frequency of spindle oscillations. We validate the quantitative accuracy of our method by tracking the in vitro diffusive mobility of micron-sized beads in glycerol solutions. Estimates of the diffusion coefficients of the granules are used to measure the viscosity of a dilution series of glycerol. Thus, our computational method is likely to be useful for both intracellular mobility and in vitro microrheology.

Quantitative Label-Free Imaging of Lipid Domains in Single Bilayers by Hyperspectral Coherent Raman Scattering.

Lipid phase separation in cellular membranes is thought to play an important role in many biological functions. This has prompted the development of synthetic membranes to study lipid–lipid interactions in vitro, alongside optical microscopy techniques aimed at directly visualizing phase partitioning. In this context, there is a need to overcome the limitations of fluorescence microscopy, where added fluorophores can significantly perturb lipid packing. Raman-based optical imaging is a promising analytical tool for label-free chemically specific microscopy of lipid bilayers. In this work, we demonstrate the application of hyperspectral coherent Raman scattering microscopy combined with a quantitative unsupervised data analysis methodology developed in-house to visualize lipid partitioning in single planar membrane bilayers exhibiting liquid-ordered and liquid-disordered domains. Two home-built instruments were utilized, featuring coherent anti-Stokes Raman scattering and stimulated Raman scattering modalities. Ternary mixtures of dioleoylphosphatidylcholine, sphingomyelin, and cholesterol were used to form phase-separated domains. We show that domains are consistently resolved, both chemically and spatially, in a completely label-free manner. Quantitative Raman susceptibility spectra of the domains are provided alongside their spatially resolved concentration maps.

Label-free discrimination and selection of cancer cells from blood during flow using holography-induced dielectrophoresis.

We present a method for label-free imaging and sorting of cancer cells in blood, which is based on a dielectrophoretic microfluidic chip and label-free interferometric phase microscopy. The chip used for imaging has been embedded with dielectrophoretic electrodes, and therefore it can be used to sort the cells based on the decisions obtained during the cell flow by the label-free quantitative imaging method. Hence, we obtained a real-time, automatic, label-free imaging flow cytometry with the ability to sort the cells during flow. To validate our model, we combined into the label-free imaging interferometer a fluorescence imaging channel that indicated the correctness of the label-free sorting. We have achieved above 98% classification success and 69% sorting accuracy at flow rates of 4 to 7 μL hr-1 . In the future, this method is expected to help in label-free sorting of circulating tumor cells in blood following an initial state-of-the-art cell enrichment.

Revealing architectural order with quantitative label-free imaging and deep learning.

We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to predict fluorescence images of diverse cell and tissue structures. QLIPP images reveal anatomical regions and axon tract orientation in prenatal human brain tissue sections that are not visible using brightfield imaging. We report a variant of U-Net architecture, multi-channel 2.5D U-Net, for computationally efficient prediction of fluorescence images in three dimensions and over large fields of view. Further, we develop data normalization methods for accurate prediction of myelin distribution over large brain regions. We show that experimental defects in labeling the human tissue can be rescued with quantitative label-free imaging and neural network model. We anticipate that the proposed method will enable new studies of architectural order at spatial scales ranging from organelles to tissue.

Quantitative label-free imaging of iron-bound transferrin in breast cancer cells and tumors

Transferrin (Tf) is an essential serum protein which delivers iron throughout the body via transferrin-receptor (TfR)-mediated uptake and iron release in early endosomes. Currently, there is no robust method to assay the population of iron-bound Tf in intact cells and tissues. Raman hyperspectral imaging detected spectral peaks that correlated with iron-bound Tf in intact cells and tumor xenografts sections (~1270-1300 cm−1). Iron-bound (holo) and iron-free (apo) human Tf forms were endocytosed by MDAMB231 and T47D human breast cancer cells. The Raman iron-bound Tf peak was identified in cells treated with holo-Tf, but not in cells incubated with apo-Tf. A reduction in the Raman peak intensity between 5 and 30 min of Tf internalization was observed in T47D, but not in MDAMB231, suggesting that T47D can release iron from Tf more efficiently than MDAMB231. MDAMB231 may display a disrupted iron homeostasis due to iron release delays caused by alterations in the pH or ionic milieu of the early endosomes. In summary, we have demonstrated that Raman hyperspectral imaging can be used to identify iron-bound Tf in cell cultures and tumor xenografts and detect iron release behavior of Tf in breast cancer cells.

Multiplex Stimulated Raman Scattering Imaging Cytometry Reveals Lipid-Rich Protrusions in Cancer Cells under Stress Condition.

SummaryIn situ measurement of cellular metabolites is still a challenge in biology. Conventional methods, such as mass spectrometry or fluorescence microscopy, would either destroy the sample or introduce strong perturbations to target molecules. Here, we present multiplex stimulated Raman scattering (SRS) imaging cytometry as a label-free single-cell analysis platform with chemical specificity and high-throughput capabilities. Using SRS imaging cytometry, we studied the metabolic responses of human pancreatic cancer cells under stress by starvation and chemotherapeutic drug treatments. We unveiled protrusions containing lipid droplets as a metabolic marker for stress-resistant cancer cells. Furthermore, by spectroscopic SRS mapping, we unveiled that triglyceride in lipid droplets are used for local energy production through lipolysis, autophagy, and β-oxidation. Our findings demonstrate the potential of targeting lipid metabolism for selective treatment of stress-resistant cancers. Collectively, these results highlight SRS imaging cytometry as a powerful label-free tool for biological discoveries with a high-throughput, high-content capacity.

Saturated Stimulated-Raman-Scattering Microscopy for Far-Field Superresolution Vibrational Imaging

Superresolution microscopy based on stimulated Raman scattering (SRS) is appealing for label-free quantitative imaging of biological and biomedical systems with higher resolution than conventional SRS microscopy, which is diffraction-limited. This study experimentally demonstrates a saturated SRS (SSRS) technique to break the diffraction limit for vibrational imaging of biological samples, such as chloroplasts and Hela cells. The technique holds great promise for studying living cells.

Adaptive frequency filtering based on convolutional neural networks in off-axis digital holographic microscopy.

Digital holographic microscopy (DHM) as a label-free quantitative imaging tool has been widely used to investigate the morphology of living cells dynamically. In the off-axis DHM, the spatial filtering in the frequency spectrum of the hologram is vital to the quality of the reconstructed images. In this paper, we propose an adaptive spatial filtering approach based on convolutional neural networks (CNN) to automatically extracts the optimal shape of frequency components. For achieving robust and precise recognition performance, the net model is trained by using the tens of thousands of frequency spectrums with a variety of specimens and imaging conditions. The experimental results demonstrate that the trained network produce an adaptive spatial filtering window which can accurately select the frequency components of the object term and eliminate the frequency components of the interference terms, especially the coherent noise that overlaps with the object term in the spatial frequency domain. We find that the proposed approach has a fast, robust, and outstanding frequency filtering capability without any manual intervention and initial input parameters compared to previous techniques. Furthermore, the applicability of the proposed method in off-axis DHM for dynamic analysis is demonstrated by real-time monitoring the morphologic changes of living MLO-Y4 cells that are constantly subject to Fluid Shear Stress (FSS).

Quantitative Label-Free Imaging of 3D Vascular Networks Self-Assembled in Synthetic Hydrogels.

Vascularization is an important strategy to overcome diffusion limits and enable the formation of complex, physiologically relevant engineered tissues and organoids. Self-assembly is a technique to generate in vitro vascular networks, but engineering the necessary network morphology and function remains challenging. Here, autofluorescence multiphoton microscopy (aMPM), a label-free imaging technique, is used to quantitatively evaluate in vitro vascular network morphology. Vascular networks are generated using human embryonic stem cell-derived endothelial cells and primary human pericytes encapsulated in synthetic poly(ethylene glycol)-based hydrogels. Two custom-built bioreactors are used to generate distinct fluid flow patterns during vascular network formation: recirculating flow or continuous flow. aMPM is used to image these 3D vascular networks without the need for fixation, labels, or dyes. Image processing and analysis algorithms are developed to extract quantitative morphological parameters from these label-free images. It is observed with aMPM that both bioreactors promote formation of vascular networks with lower network anisotropy compared to static conditions, and the continuous flow bioreactor induces more branch points compared to static conditions. Importantly, these results agree with trends observed with immunocytochemistry. These studies demonstrate that aMPM allows label-free monitoring of vascular network morphology to streamline optimization of growth conditions and provide quality control of engineered tissues.

Integration of diffraction phase microscopy and Raman imaging for label-free morpho-molecular assessment of live cells.

Label-free quantitative imaging is highly desirable for studying live cells by extracting pathophysiological information without perturbing cell functions. Here, we demonstrate a novel label-free multimodal optical imaging system with the capability of providing comprehensive morphological and molecular attributes of live cells. Our morpho-molecular microscopy (3M) system draws on the combined strength of quantitative phase microscopy (QPM) and Raman microscopy to probe the morphological features and molecular fingerprinting characteristics of each cell under observation. While the commonr-path geometry of our QPM system allows for highly sensitive phase measurement, the Raman microscopy is equipped with dual excitation wavelengths and utilizes the same detection and dispersion system, making it a distinctive multi-wavelength system with a small footprint. We demonstrate the applicability of the 3M system by investigating nucleated and nonnucleated cells. This integrated label-free platform has a promising potential in preclinical research, as well as in clinical diagnosis in the near future.

Partially coherent illumination engineering for enhanced refractive index tomography.

Optical diffraction tomography based on partially coherent illumination (PC-ODT) is a quantitative label-free imaging technique that allows reconstructing of the object's 3D refractive index from measured through-focus intensity images. PC illumination provides advantages such as speckle noise-free imaging and inherent compatibility with conventional wide-field microscopes. Here we experimentally demonstrate that a proper design of the PC illumination, different from the familiar bright-field one, and the use of more realistic optical transfer functions (OTFs) have crucial importance in PC-ODT to significantly increase the accuracy in 3D refractive index reconstruction. While realistic OTFs properly account for the real experimental illumination conditions, the proposed PC illumination design allows for gathering the object spatial-frequency content attenuated when bright-field illumination is used.

Optical diffraction tomography with fully and partially coherent illumination in high numerical aperture label-free microscopy [Invited

Quantitative label-free imaging is an important tool for the study of living microorganisms that, during the last decade, has attracted wide attention from the optical community. Optical diffraction tomography (ODT) is probably the most relevant technique for quantitative label-free 3D imaging applied in wide-field microscopy in the visible range. The ODT is usually performed using spatially coherent light illumination and specially designed holographic microscopes. Nevertheless, the ODT is also compatible with partially coherent illumination and can be realized in conventional wide-field microscopes by applying refocusing techniques, as it has been recently demonstrated. Here, we compare these two ODT modalities, underlining their pros and cons and discussing the optical setups for their implementation. In particular, we pay special attention to a system that is compatible with a conventional wide-field microscope that can be used for both ODT modalities. It consists of two easily attachable modules: the first for sample illumination engineering based on digital light processing technology; the other for focus scanning by using an electrically driven tunable lens. This hardware allows for a programmable selection of the wavelength and the illumination design, and provides fast data acquisition as well. Its performance is experimentally demonstrated in the case of ODT with partially coherent illumination providing speckle-free 3D quantitative imaging.

Fast label-free microscopy technique for 3D dynamic quantitative imaging of living cells.

The refractive index (RI) is an important optical characteristic that is often exploited in label-free microscopy for analysis of biological objects. A technique for 3D RI reconstruction of living cells has to be fast enough to capture the cell dynamics and preferably needs to be compatible with standard wide-field microscopes. To solve this challenging problem, we present a technique that provides fast measurement and processing of data required for real-time 3D visualization of the object RI. Specifically, the 3D RI is reconstructed from the measurement of bright-field intensity images, axially scanned by a high-speed focus tunable lens mounted in front of a sCMOS camera, by using a direct deconvolution approach designed for partially coherent light microscopy in the non-paraxial regime. Both the measurement system and the partially coherent illumination, that provides optical sectioning and speckle-noise suppression, enable compatibility with wide-field microscopes resulting in a competitive and affordable alternative to the current holographic laser microscopes. Our experimental demonstrations show video-rate 3D RI visualization of living bacteria both freely swimming and optically manipulated by using freestyle laser traps allowing for their trapping and transport along 3D trajectories. These results prove that is possible to conduct simultaneous 4D label-free quantitative imaging and optical manipulation of living cells, which is promising for the study of the cell biophysics and biology.

Colorimetric imaging of layer-by-layer molecular deposition on nanoplasmonic lycurgus cup array

A quantitative label-free colorimetric imaging of biochemical molecular thin film deposition at a single molecule layer (2nm thickness) resolution was demonstrated on a nanoplasmonic sensor substrate known as nano Lycurgus Cup array (nanoLCA) and the penetration depth of the nanoplasmonic sensor was accordingly determined. Colorimetric nanoplasmonic imaging technique provides significant advantages in direct visualization and quick identification of surface deposited molecules. We implement layer by layer deposition of alternating polyelectrolyte layers with controlled thickness on the nanoLCA device to show surface color changes and determine the decay length of the device derived from the sensor spectral response to the molecular layer thickness. The calculated decay length of the nanoLCA device is 193 nanometers which corresponds well with the decay length of other known surface plasmon sensors. In addition micro contact molecular printing and transferring on the nanoLCA surface is used to selectively deposit poly-l-lysine and different alkanethiol molecules to demonstrate direct colorful visualization of surface patterned unlabeled molecules.

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

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

Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy.

Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures.