Bessel-Beam Hyperspectral CARS Microscopy with Sparse Sampling: Enabling High-Content High-Throughput Label-Free Quantitative Chemical Imaging

Label-Free Screening of Drug-Induced Liver Injury Using Stimulated Raman Scattering Microscopy and Spectral Phasor Analysis

Hepatic toxicity is a leading cause of the termination of clinical trials and the withdrawal of therapeutics following regulatory approval. The detection of drug-induced liver injury (DILI) is therefore of importance to ensure patient safety and the effectiveness of novel small molecules and drugs. DILI encompasses drug-induced steatosis (DIS) and drug-induced phospholipidosis (DIPL) which involve the accumulation of excess intracellular lipids. Here, we develop hyperspectral stimulated Raman scattering (SRS) microscopy as a label-free methodology for discriminating DIS and DIPL in mammalian cell culture. We demonstrate that hyperspectral SRS imaging in tandem with spectral phasor analysis is capable of discriminating DIS and DIPL based on the nature and distribution of intracellular lipids resulting from each process. To demonstrate the practical application of this methodology, we develop a panel of alkyne-tagged propranolol analogues that display varying DILI effects. Using hyperspectral SRS imaging together with spectral phasor analysis, our label-free methodology corroborated the standard fluorescence-based assay for DILI. As a label-free screening method, it offers a convenient and expedient methodology for visualizing hepatotoxicity in cell cultures which could be integrated into the early stages of the drug development process for screening new chemical entities for DILI.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

Pollution effects on retinal health: A review on current methodologies and findings

In our daily life, we are exposed to numerous industrial chemicals that may be harmful to the retina, which is a delicate and sensitive part of our eyes. This could lead to irreversible changes and cause retinal diseases or blindness. Current retinal environmental health studies primarily utilize animal models, isolated mammalian retinas, animal- or human-derived retinal cells, and retinal organoids, to address both pre- and postnatal exposure. However, as there is limited toxicological information available for specific populations, human induced pluripotent stem cell (hiPSC)-induced models could be effective tools to supplement such data. In order to obtain more comprehensive and reliable toxicological information, we need more appropriate models, novel evaluation methods, and computational technologies to develop portable equipment. This review mainly focused on current toxicology models with particular emphasis on retinal organoids, and it looks forward to future models, analytical methods, and equipment that can efficiently and accurately evaluate retinal toxicity.

Bessel Beam Coherent Anti-Stokes Raman Scattering Spectroscopy for Turbulent Flow Diagnosis

Coherent anti-Stokes Raman scattering (CARS) spectroscopy plays an important role in chemical analysis for transient flow dynamics. Due to the turbulent ambient conditions, the CARS spectrum often suffers from a poor signal-to-noise ratio (SNR) and cannot provide a convincing measurement. Here, we report on a CARS spectroscopic method using a Bessel beam to enhance the spectral fidelity and SNR in a quasi-turbulent environment. Compared with traditional CARS, the measurement accuracy is significantly improved by taking advantage of the anti-scattering and self-healing characteristics of the Bessel beam. Our preliminary results indicate that Bessel beam CARS could be a promising method for high precision turbulent flow measurement fields.

Nonlinear Optical Microscopy and Plasmon Enhancement

Improving nonlinear optics efficiency is currently one of the hotspots in modern optical research. Moreover, with the maturity of nonlinear optical microscope systems, more and more biology, materials, medicine, and other related disciplines have higher imaging resolution and detection accuracy requirements for nonlinear optical microscope systems. Surface plasmons of metal nanoparticle structures could confine strong localized electromagnetic fields in their vicinity to generate a new electromagnetic mode, which has been widely used in surface-enhanced Raman scattering, surface-enhanced fluorescence, and photocatalysis. In this review, we summarize the mechanism of nonlinear optical effects and surface plasmons and also review some recent work on plasmon-enhanced nonlinear optical effects. In addition, we present some latest applications of nonlinear optical microscopy system research.

In situ Plasmon-Enhanced CARS and TPEF for Gram staining identification of non-fluorescent bacteria

In this work, we report in situ nonlinear microscopic images on plasmon-enhanced coherent anti-Stokes Raman scattering (CARS) and plasmon-Induced two-photon excited fluorescence （TPEF)of non-fluorescent microorganism. Our unique synthesized Au@Ag nanorods provide with two distinct surface-plasmon resonance (SPR) at 400 and 800 nm, respectively, which can efficiently induce linear fluorescence signals of E. coli but also enhance the nonlinear optical spectroscopy signals of TPEF, and coherent anti-Stokes Raman scattering (CARS) imaging of E. coli and S. aureus. Furthermore, calculations with complete active space self-consistent field (CASSCF) reveals the hot electrons of SPs can efficiently induce the biological fluorescence of non-fluorescent flavin nucleotides on the surface of E. coli. This novel mechanism is expected to guide the development and application of new microbial detection reagents. Gram-negative and Gram-positive bacteria can be well distinguished by nonlinear microscopic imaging of the CARS signal at 1589 cm^-1. Benefit by the strong penetrability of non-linear optical signals, it is expected to realize in situ real-time detection and classification of pathogenic microbial infections in vivo.

Hyperspectral CARS microscopy and quantitative unsupervised analysis of deuterated and non-deuterated fatty acid storage in human cells

Coherent anti-Stokes Raman scattering (CARS) implemented as a vibrational micro-spectroscopy modality eradicates the need for potentially perturbative fluorescent labeling while still providing high-resolution, chemically specific images of biological samples. Isotopic substitution of hydrogen atoms with deuterium introduces minimal change to molecular structures and can be coupled with CARS microscopy to increase chemical contrast. Here, we investigate HeLa cells incubated with non-deuterated or deuterium-labeled fatty acids, using an in-house-developed hyperspectral CARS microscope coupled with an unsupervised quantitative data analysis algorithm, to retrieve Raman susceptibility spectra and concentration maps of chemical components in physically meaningful units. We demonstrate that our unsupervised analysis retrieves the susceptibility spectra of the specific fatty acids, both deuterated and non-deuterated, in good agreement with reference Raman spectra measured in pure lipids. Our analysis, using the cell-silent spectral region, achieved excellent chemical specificity despite having no prior knowledge and considering the complex intracellular environment inside cells. The quantitative capabilities of the analysis allowed us to measure the concentration of deuterated and non-deuterated fatty acids stored within cytosolic lipid droplets over a 24 h period. Finally, we explored the potential use of deuterium-labeled lipid droplets for non-invasive cell tracking, demonstrating an effective application of the technique for distinguishing between cells in a mixed population over a 16 h period. These results further demonstrate the chemically specific capabilities of hyperspectral CARS microscopy to characterize and distinguish specific lipid types inside cells using an unbiased quantitative data analysis methodology.

Quantification of the nonlinear susceptibility of the hydrogen and deuterium stretch vibration for biomolecules in coherent Raman micro-spectroscopy

Deuterium labelling is increasingly used in coherent Raman imaging of complex systems, such as biological cells and tissues, to improve chemical specificity. Nevertheless, quantitative coherent Raman susceptibility spectra for deuterated compounds have not been previously reported. Interestingly, it is expected theoretically that -D stretch vibrations have a Raman susceptibility lower than -H stretch vibrations, with the area of their imaginary part scaling with their wavenumber, which is shifted from around 2900 cm-1 for C-H into the silent region around 2100 cm-1 for C-D. Here, we report quantitative measurements of the nonlinear susceptibility of water, succinic acid, oleic acid, linoleic acid and deuterated isoforms. We show that the -D stretch vibration has indeed a lower area, consistent with the frequency reduction due to the doubling of atomic mass from hydrogen to deuterium. This finding elucidates an important trade-off between chemical specificity and signal strength in the adoption of deuterium labelling as an imaging strategy for coherent Raman microscopy.

Identifying subpopulations in multicellular systems by quantitative chemical imaging using label-free hyperspectral CARS microscopy

Quantitative hyperspectral coherent Raman scattering microscopy merges imaging with spectroscopy and utilises quantitative data analysis algorithms to extract physically meaningful chemical components, spectrally and spatially-resolved, with sub-cellular resolution. This label-free non-invasive method has the potential to significantly advance our understanding of the complexity of living multicellular systems. Here, we have applied an in-house developed hyperspectral coherent anti-Stokes Raman scattering (CARS) microscope, combined with a quantitative data analysis pipeline, to imaging living mouse liver organoids as well as fixed mouse brain tissue sections xenografted with glioblastoma cells. We show that the method is capable of discriminating different cellular sub-populations, on the basis of their chemical content which is obtained from an unsupervised analysis, i.e. without prior knowledge. Specifically, in the organoids, we identify sub-populations of cells at different phases in the cell cycle, while in the brain tissue, we distinguish normal tissue from cancer cells, and, notably, tumours derived from transplanted cancer stem cells versus non-stem glioblastoma cells. The ability of the method to identify different sub-populations was validated by correlative fluorescence microscopy using fluorescent protein markers. These examples expand the application portfolio of quantitative chemical imaging by hyperspectral CARS microscopy to multicellular systems of significant biomedical relevance, pointing the way to new opportunities in non-invasive disease diagnostics.

Mammalian cell and tissue imaging using Raman and coherent Raman microscopy

Direct imaging of metabolism in cells or multicellular organisms is important for understanding many biological processes. Raman scattering (RS) microscopy, particularly, coherent Raman scattering (CRS) such as coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS), has emerged as a powerful platform for cellular imaging due to its high chemical selectivity, sensitivity, and imaging speed. RS microscopy has been extensively used for the identification of subcellular structures, metabolic observation, and phenotypic characterization. Conjugating RS modalities with other techniques such as fluorescence or infrared (IR) spectroscopy, flow cytometry, and RNA-sequencing can further extend the applications of RS imaging in microbiology, system biology, neurology, tumor biology and more. Here we overview RS modalities and techniques for mammalian cell and tissue imaging, with a focus on the advances and applications of CARS and SRS microscopy, for a better understanding of the metabolism and dynamics of lipids, protein, glucose, and nucleic acids in mammalian cells and tissues. This article is categorized under: Laboratory Methods and Technologies > Imaging Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.

Review of high-content screening applications in toxicology

High-content screening (HCS) technology combining automated microscopy and quantitative image analysis can address biological questions in academia and the pharmaceutical industry. Various HCS experimental applications have been utilized in the research field of in vitro toxicology. In this review, we describe several HCS application approaches used for studying the mechanism of compound toxicity, highlight some challenges faced in the toxicological community, and discuss the future directions of HCS in regards to new models, new reagents, data management, and informatics. Many specialized areas of toxicology including developmental toxicity, genotoxicity, developmental neurotoxicity/neurotoxicity, hepatotoxicity, cardiotoxicity, and nephrotoxicity will be examined. In addition, several newly developed cellular assay models including induced pluripotent stem cells (iPSCs), three-dimensional (3D) cell models, and tissues-on-a-chip will be discussed. New genome-editing technologies (e.g., CRISPR/Cas9), data analyzing tools for imaging, and coupling with high-content assays will be reviewed. Finally, the applications of machine learning to image processing will be explored. These new HCS approaches offer a huge step forward in dissecting biological processes, developing drugs, and making toxicology studies easier.

Label-Free Volumetric Quantitative Imaging of the Human Somatic Cell Division by Hyperspectral Coherent Anti-Stokes Raman Scattering

Quantifying the chemical composition of unstained intact tissue and cellular samples with high spatio-temporal resolution in three dimensions would provide a step change in cell and tissue analytics critical to progress the field of cell biology. Label-free optical microscopy offers the required resolution and noninvasiveness, yet quantitative imaging with chemical specificity is a challenging endeavor. In this work, we show that hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy can be used to provide quantitative volumetric imaging of human osteosarcoma cells at various stages through cell division, a fundamental component of the cell cycle progress resulting in the segregation of cellular content to produce two progeny. We have developed and applied a quantitative data analysis method to produce volumetric three-dimensional images of the chemical composition of the dividing cell in terms of water, proteins, DNAP (a mixture of proteins and DNA, similar to chromatin), and lipids. We then used these images to determine the dry masses of the corresponding organic components. The attribution of proteins and DNAP components was validated using specific well-characterized fluorescent probes, by comparison with correlative two-photon fluorescence microscopy of DNA and mitochondria. Furthermore, we map the same chemical components under perturbed conditions, employing a drug that interferes directly with cell division (Taxol), showing its influence on cell organization and the masses of proteins, DNAP, and lipids.

Hyperspectral analysis applied to micro-Brillouin maps of amyloid-beta plaques in Alzheimer's disease brains

A recent investigation on the architecture and chemical composition of amyloid-β (Aβ) plaques in ex vivo histological sections of an Aβ-overexpressing transgenic mouse hippocampus has shed light on the infrared light signature of cell-activation related biomarkers of Alzheimer's disease. A correlation was highlighted between the biomechanical properties detected by Brillouin microscopy and the molecular make-up of Aβ plaques provided by FTIR spectroscopic imaging and Raman microscopy (with correlative immunofluorescence imaging) in this animal model of the disease. In the Brillouin spectra of heterogeneous materials such as biomedical samples, peaks are likely the result of multiple contributions, more or less overlaid on a spatial and spectral scale. The ability to disentangle these contributions is very important as it may give access to discrete components that would otherwise be buried within the Brillouin peak envelope. Here, we applied an unsupervised non-negative matrix factorization method to analyse the spontaneous Brillouin microscopy maps of Aβ plaques in transgenic mouse hippocampal sections. The method has already been proven successful in decomposing chemical images and is applied here for the first time to acoustic maps acquired with a Fabry-Perot Brillouin microscope. We extracted and visualised a decrease in tissue rigidity from the core through to the periphery of the plaque, with spatially distinct components that we assigned to specific entities. This work demonstrates that it is possible to reveal the structure and mechanical properties of Aβ plaques, with details visualized by the projection of the mechanical contrast into a few relevant channels.