Mammalian cell and tissue imaging using Raman and coherent Raman microscopy

Alpha-synuclein aggregation induces prominent cellular lipid changes as revealed by Raman spectroscopy and machine learning analysis

The aggregation of α-synuclein is a central neuropathological hallmark in neurodegenerative disorders known as Lewy body diseases, including Parkinson's disease and dementia with Lewy bodies. In the aggregation process, α-synuclein transitions from its native disordered/α-helical form to a β-sheet-rich structure, forming oligomers and protofibrils that accumulate into Lewy bodies, in a process that is thought to underlie neurodegeneration. Lipids are thought to play a critical role in this process by facilitating α-synuclein aggregation and contributing to cell toxicity, possibly through ceramide production. This study aimed to investigate biochemical changes associated with α-synuclein aggregation, focusing on lipid changes, using Raman spectroscopy coupled with machine learning. HEK293, Neuro2a and SH-SY5Y expressing increased levels of α-synuclein were treated with sonicated α-synuclein pre-formed fibrils, to model seeded aggregation. Raman spectroscopy, complemented by an in-house lipid spectral library, was used to monitor the aggregation process and its effects on cellular viability over 14 days. We detected α-synuclein aggregation by assessing β-sheet peaks at 1045 cm⁻1, in cells treated with α-synuclein pre-formed fibrils, using machine learning (principal component analysis and uniform manifold approximation and projection) analysis based on Raman spectral features. Changes in lipid profiles, and especially sphingolipids, including a decrease in sphingomyelin and increase in ceramides, were observed, consistent with oxidative stress and apoptosis. Altogether, our study informs on biochemical alterations that can be considered for the design of therapeutic strategies for Parkinson's disease and related synucleinopathies.

Synthetic Lipid Biology

Cells contain thousands of different lipids. Their rapid and redundant metabolism, dynamic movement, and many interactions with other biomolecules have justly earned lipids a reputation as a vexing class of molecules to understand. Further, as the cell's hydrophobic metabolites, lipids assemble into supramolecular structures─most commonly bilayers, or membranes─from which they carry out myriad biological functions. Motivated by this daunting complexity, researchers across disciplines are bringing order to the seeming chaos of biological lipids and membranes. Here, we formalize these efforts as "synthetic lipid biology". Inspired by the idea, central to synthetic biology, that our abilities to understand and build biological systems are intimately connected, we organize studies and approaches across numerous fields to create, manipulate, and analyze lipids and biomembranes. These include construction of lipids and membranes from scratch using chemical and chemoenzymatic synthesis, editing of pre-existing membranes using optogenetics and protein engineering, detection of lipid metabolism and transport using bioorthogonal chemistry, and probing of lipid-protein interactions and membrane biophysical properties. What emerges is a portrait of an incipient field where chemists, biologists, physicists, and engineers work together in proximity─like lipids themselves─to build a clearer description of the properties, behaviors, and functions of lipids and membranes.

Noninvasive Optical Sensing of Aging and Diet Preferences Using Raman Spectroscopy

Effective dietary strategies and interventions for monitoring dietary exposures require accurate and noninvasive methods to understand how diet modulates health and risk of obesity; advances in technology are transforming the landscape and enabling more specific tailored approaches to nutritional guidance. This study explores the use of Raman spectroscopy (RS), a noninvasive and nondestructive analytical technique, to identify changes in the mice skin in response to constant dietary exposures. We found that RS is highly accurate to determine body composition as a result of habitual dietary patterns, specifically Vegan, Typical American, and Ketogenic diets, all very common in the US context. RS is based on major differences in the intensities of vibrational bands that originate from collagen. Moreover, RS could be used to predict folate deficiency and identify the sex of the animals. Finally, we found that RS could be used to track the chronological age of the mice. Considering the hand-held nature of the utilized spectrometer, one can expect that RS could be used to monitor and, consequently, personalize effects of diet on the body composition.

Trends and Challenges of the Modern Pathology Laboratory for Biopharmaceutical Research Excellence

Pathology, a fundamental discipline that bridges basic scientific discovery to the clinic, is integral to successful drug development. Intrinsically multimodal and multidimensional, anatomic pathology continues to be empowered by advancements in molecular and digital technologies enabling the spatial tissue detection of biomolecules such as genes, transcripts, and proteins. Over the past two decades, breakthroughs in spatial molecular biology technologies and advancements in automation and digitization of laboratory processes have enabled the implementation of higher throughput assays and the generation of extensive molecular data sets from tissue sections in biopharmaceutical research and development research units. It is our goal to provide readers with some rationale, advice, and ideas to help establish a modern molecular pathology laboratory to meet the emerging needs of biopharmaceutical research. This manuscript provides (1) a high-level overview of the current state and future vision for excellence in research pathology practice and (2) shared perspectives on how to optimally leverage the expertise of discovery, toxicologic, and translational pathologists to provide effective spatial, molecular, and digital pathology data to support modern drug discovery. It captures insights from the experiences, challenges, and solutions from pathology laboratories of various biopharmaceutical organizations, including their approaches to troubleshooting and adopting new technologies.

Current research status of Raman spectroscopy in glioma detection

Glioma is the most common primary tumor of the nervous system. Conventional diagnostic methods for glioma often involve time-consuming or reliance on externally introduced materials. Consequently, there is an urgent need for rapid and reliable diagnostic techniques. Raman spectroscopy has emerged as a promising tool, offering rapid, accurate, and label-free analysis with high sensitivity and specificity in biomedical applications. In this review, the fundamental principles of Raman spectroscopy have been introduced, and then the progress of applying Raman spectroscopy in biomedical studies has been summarized, including the identification and typing of glioma. The challenges encountered in the clinical application of Raman spectroscopy for glioma have been discussed, and the prospects have also been envisioned.

Artificial Intelligence-Assisted Stimulated Raman Histology: New Frontiers in Vibrational Tissue Imaging

Frozen section biopsy, introduced in the early 1900s, still remains the gold standard methodology for rapid histologic evaluations. Although a valuable tool, it is labor-, time-, and cost-intensive. Other challenges include visual and diagnostic variability, which may complicate interpretation and potentially compromise the quality of clinical decisions. Raman spectroscopy, with its high specificity and non-invasive nature, can be an effective tool for dependable and quick histopathology. The most promising modality in this context is stimulated Raman histology (SRH), a label-free, non-linear optical process which generates conventional H&E-like images in short time frames. SRH overcomes limitations of conventional Raman scattering by leveraging the qualities of stimulated Raman scattering (SRS), wherein the energy gets transferred from a high-power pump beam to a probe beam, resulting in high-energy, high-intensity scattering. SRH's high resolution and non-requirement of preprocessing steps make it particularly suitable when it comes to intrasurgical histology. Combining SRH with artificial intelligence (AI) can lead to greater precision and less reliance on manual interpretation, potentially easing the burden of the overburdened global histopathology workforce. We review the recent applications and advances in SRH and how it is tapping into AI to evolve as a revolutionary tool for rapid histologic analysis.

Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma

BACKGROUND

Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the background coming from embedding media.

METHODS

Spontaneous Raman spectroscopy was used for molecular fingerprinting of FFPE tissue from 46 patient samples with known methylation subtypes. Spectra were used to construct tumor/non-tumor, IDH1WT/IDH1mut, and methylation-subtype classifiers. Support vector machine and random forest were used to identify the most discriminatory Raman frequencies. Stimulated Raman spectroscopy was used to validate the frequencies identified. Mass spectrometry of glioma cell lines and TCGA were used to validate the biological findings.

RESULTS

Here, we develop APOLLO (rAman-based PathOLogy of maLignant gliOma)-a computational workflow that predicts different subtypes of glioma from spontaneous Raman spectra of FFPE tissue slides. Our novel APOLLO platform distinguishes tumors from nontumor tissue and identifies novel Raman peaks corresponding to DNA and proteins that are more intense in the tumor. APOLLO differentiates isocitrate dehydrogenase 1 mutant (IDH1mut) from wild-type (IDH1WT) tumors and identifies cholesterol ester levels to be highly abundant in IDHmut glioma. Moreover, APOLLO achieves high discriminative power between finer, clinically relevant glioma methylation subtypes, distinguishing between the CpG island hypermethylated phenotype (G-CIMP)-high and G-CIMP-low molecular phenotypes within the IDH1mut types.

CONCLUSIONS

Our results demonstrate the potential of label-free Raman spectroscopy to classify glioma subtypes from FFPE slides and to extract meaningful biological information thus opening the door for future applications on these archived tissues in other cancers.

Label-free Raman imaging for screening of anti-inflammatory function food

Natural bioactive compounds and plant constituents are considered to have a positive anti-inflammatory effect. This study aimed to establish a screening technique for anti-inflammatory function in foods based on label-free Raman imaging. A visible anti-inflammatory analysis method based on coherent anti-Stokes Raman scattering (CARS) was established with an LPS-induced RAW264.7 cell model. Dynamic changes in proteins and lipids were determined at laser pump light wavelengths of 2956 cm-1 and 2856 cm-1, respectively. The method was applied to a plant-based formula (JC) with anti-inflammatory activity. Q-TOF-MS and HPLC analyses revealed the main active constituents of JC as quercetin, kaempferol, l-glutamine, and sodium copper chlorophyllin. In in vitro and in vivo verification experiments, JC showed significant anti-inflammatory activity by regulating the TLR4/NF-κB pathway. In conclusion, this study successfully established a label-free and visible method for screening anti-inflammatory constituents in plant-based food products, which will facilitate the evaluation of functional foods.

Programmable hyperspectral coherent anti-Stokes Raman scattering microscopy

Hyperspectral coherent Raman scattering microscopy provides a significant improvement in acquisition time compared to spontaneous Raman scattering yet still suffers from the time required to sweep through individual wavenumbers. To address this, we present the use of a pulse shaper with a 2D spatial light modulator for phase- and amplitude-based shaping of the Stokes beam to create programmable spectrally tailored excitation envelopes. This enables collection of useful spectral information in a more rapid and efficient manner.

Multi-molecular hyperspectral PRM-SRS microscopy

Lipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.

Femtosecond optical Kerr effect in normal and grades of cancerous breast tissues as a new optical biopsy method

This study reports on the first use of the optical Kerr effect (OKE) in breast cancer tissue. This proposed optical biopsy method utilizes a Femtosecond Optical Kerr Gate to detect changes in dielectric relaxation and conductivity created by a cancerous infection. Here, the temporal behavior of the OKE is tracked in normal and cancerous samples of human and mouse breast. These tissues display a double peaked temporal structure and its decay rate changes depending on the tissue's infection status. The decay of the secondary peak, attributed to ultrafast plasma response, indicates that the tissue's conductivity has doubled once infected. A slower molecular contribution to the Kerr effect can also be observed in healthy tissues. These findings suggest two possible biomarkers for the use of OKE in optical biopsy. Both markers arise from alterations in the infected tissue's cellular structure, which changes the rate at which electronic and molecular processes occur.

Optical Imaging in Human Lymph Node Specimens for Detecting Breast Cancer Metastases: A Review

Assessment of regional lymph node status in breast cancer is of important staging and prognostic value. Even though formal histological examination is the currently accepted standard of care, optical imaging techniques have shown promising results in disease diagnosis. In the present article, we review six spectroscopic techniques and focus on their use as alternative tools for breast cancer lymph node assessment. Elastic scattering spectroscopy (ESS) seems to offer a simple, cost-effective, and reproducible method for intraoperative diagnosis of breast cancer lymph node metastasis. Optical coherence tomography (OCT) provides high-resolution tissue scanning, along with a short data acquisition time. However, it is relatively costly and experimentally complex. Raman spectroscopy proves to be a highly accurate method for the identification of malignant axillary lymph nodes, and it has been further validated in the setting of head and neck cancers. Still, it remains time-consuming. Near-infrared fluorescence imaging (NIRF) and diffuse reflectance spectroscopy (DFS) are related to significant advantages, such as deep tissue penetration and efficiency. Fourier-transform infrared spectroscopy (FTIR) is a promising method but has significant drawbacks. Nonetheless, only anecdotal reports exist on their clinical use for cancerous lymph node detection. Our results indicate that optical imaging methods can create informative and rapid tools to effectively guide surgical decision-making.

Coherent Raman scattering microscopy of lipid droplets in cells and tissues

Lipid droplets (LDs) play a key role as the hub for lipid metabolism to maintain cellular metabolic homeostasis. Understanding the functions and changes of LDs in different pathological conditions is crucial for identifying new markers for diagnosis and discovering new targets for treatment. In recent years, coherent Raman scattering (CRS) microscopy has been popularized for the imaging and quantification of LDs in live cells. Compared to spontaneous Raman scattering microscopy, CRS microscopy offers a much higher imaging speed while maintaining similar chemical information. Due to the high lipid density, LDs usually have strong CRS signals and therefore are the most widely studied organelle in the CRS field. In this review, we discuss recent achievements using CRS to study the quantity, distribution, composition, and dynamics of LDs in various systems.

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.

Bioorthogonal Chemical Imaging of Cell Metabolism Regulated by Aromatic Amino Acids

Essential aromatic amino acids (AAAs) are building blocks for synthesizing new biomasses in cells and sustaining normal biological functions. For example, an abundant supply of AAAs is important for cancer cells to maintain their rapid growth and division. With this, there is a rising demand for a highly specific, noninvasive imaging approach with minimal sample preparation to directly visualize how cells harness AAAs for their metabolism in situ. Here, we develop an optical imaging platform that combines deuterium oxide (D2O) probing with stimulated Raman scattering (DO-SRS) and integrates DO-SRS with two-photon excitation fluorescence (2PEF) into a single microscope to directly visualize the metabolic activities of HeLa cells under AAA regulation. Collectively, the DO-SRS platform provides high spatial resolution and specificity of newly synthesized proteins and lipids in single HeLa cell units. In addition, the 2PEF modality can detect autofluorescence signals of nicotinamide adenine dinucleotide (NADH) and Flavin in a label-free manner. The imaging system described here is compatible with both in vitro and in vivo models, which is flexible for various experiments. The general workflow of this protocol includes cell culture, culture media preparation, cell synchronization, cell fixation, and sample imaging with DO-SRS and 2PEF modalities.

Femtosecond Optical Kerr Gates in Cancerous Breast Tissue for a New Optical Biopsy Method

The Optical Kerr Effect was demonstrated for the first time as a new optical biopsy method to detect normal and grades of cancer of human breast tissues. The technique works by temporally tracking the various electronic and molecular processes that give rise to the nonlinear index of refraction (n2). The rate at which these processes populate and dissipate varies depending on the internal properties of the sample. It is shown here that in tissues, the variances in the ultrafast plasma Kerr responses that relates to the dielectric relaxation can be used as a biomarker for cancer. The relaxation of this response changes significantly between healthy and different grades of triple negative breast cancer tissues. This change can be attributed to a doubling or tripling of the tissue's conductivity depending on the cancer grade.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer

Colorectal cancer is the second most common cause of cancer-related deaths worldwide. To follow up on the progression of the disease, tumor markers are commonly used. Here, we report serum analysis based on Raman spectroscopy to provide a rapid cancer diagnosis with tumor markers and two new cell adhesion molecules measured using the ELİSA method. Raman spectra showed higher Raman intensities at 1447 cm^-1 1560 cm^-1, 1665 cm^-1, and 1769 cm^-1, which originated from CH₂ proteins and lipids, amide II and amide I, and CO lipids vibrations. Furthermore, the correlation test showed, that only the CEA colon cancer marker correlated with the Raman spectra. Importantly, machine learning methods showed, that the accuracy of the Raman method in the detection of colon cancer was around 95 %. Obtained results suggest, that Raman shifts at 1302 cm^-1 and 1306 cm^-1 can be used as spectroscopy markers of colon cancer.

Sub-micrometric spatial distribution of amorphous and crystalline carbonates in biogenic crystals using coherent Raman microscopy

In living organisms, calcium carbonate biomineralization combines complex bio-controlled physical and chemical processes to produce crystalline hierarchical hard tissues (usually calcite or aragonite) typically from an amorphous precursor phase. Understanding the nature of the successive transient amorphous phases potentially involved in the amorphous-to-crystalline transition requires characterization tools, which are able to provide a spatial and spectroscopic analysis of the biomineral structure. In this work, we present a highly sensitive coherent Raman microscopy approach, which allows one to image molecular bond concentrations in post mortem shells and living animals, by exploiting the vibrational signature of the different carbonates compounds. To this end, we target the ν₁ calcium carbonate vibration mode and produce spatially and spectroscopically resolved images of the shell border of a mollusk shell, the Pinctada margaritifera pearl oyster. A novel approach is further presented to efficiently compare the amount of amorphous carbonate with respect to its crystalline counterpart. Finally, the whole microscopy method is used to image in vivo the shell border and demonstrate the feasibility and the reproducibility of the technique. These findings open chemical imaging perspectives for the study of biogenic and bio-inspired crystals.

Imaging approaches for monitoring three-dimensional cell and tissue culture systems

The past decade has seen an increasing demand for more complex, reproducible and physiologically relevant tissue cultures that can mimic the structural and biological features of living tissues. Monitoring the viability, development and responses of such tissues in real-time are challenging due to the complexities of cell culture physical characteristics and the environments in which these cultures need to be maintained in. Significant developments in optics, such as optical manipulation, improved detection and data analysis, have made optical imaging a preferred choice for many three-dimensional (3D) cell culture monitoring applications. The aim of this review is to discuss the challenges associated with imaging and monitoring 3D tissues and cell culture, and highlight topical label-free imaging tools that enable bioengineers and biophysicists to non-invasively characterise engineered living tissues.

Dynamic Progress in Technological Advances to Study Lipids in Aging: Challenges and Future Directions

Lipids participate in all cellular processes. Diverse methods have been developed to investigate lipid composition and distribution in biological samples to understand the effect of lipids across an organism’s lifespan. Here, we summarize the advanced techniques for studying lipids, including mass spectrometry-based lipidomics, lipid imaging, chemical-based lipid analysis and lipid engineering and their advantages. We further discuss the limitation of the current methods to gain an in-depth knowledge of the role of lipids in aging, and the possibility of lipid-based therapy in aging-related diseases.

Towards Raman-Based Screening of Acute Lymphoblastic Leukemia-Type B (B-ALL) Subtypes

Simple Summary

Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy originating from abnormal lymphoid progenitor cells. Since ALL is genetically highly heterogenous, more sensitive and rapid methods for identifying the molecular subtype of ALL are still being searched, and Raman spectroscopy (RS) has a chance of becoming a valuable tool for this purpose. Herein, the RS was applied to analyze normal B cells and three subtypes of B-ALL, characterized by the presence of the product of gene fusion, i.e., BCR-ABL1, TEL-AML1, and TCF3-PBX1. The classification and discrimination of normal and neoplastic cells were carried out with the chemometric approach. Normal B cells were characterized mostly by bands assigned to nucleic acids and proteins, whereas three subtypes of ALL appeared to contain a higher lipid content. Spectral differences between particular ALL subtypes were modest. The results lead to the conclusion that RS has the potential as a diagnostic tool in clinical practice.

Abstract

Acute lymphoblastic leukemia (ALL) is the most common type of malignant neoplasms in the pediatric population. B-cell precursor ALLs (BCP-ALLs) are derived from the progenitors of B lymphocytes. Traditionally, risk factors stratifying therapy in ALL patients included age at diagnosis, initial leukocytosis, and the response to chemotherapy. Currently, treatment intensity is modified according to the presence of specific gene alterations in the leukemic genome. Raman imaging is a promising diagnostic tool, which enables the molecular characterization of cells and differentiation of subtypes of leukemia in clinical samples. This study aimed to characterize and distinguish cells isolated from the bone marrow of patients suffering from three subtypes of BCP-ALL, defined by gene rearrangements, i.e., BCR-ABL1 (Philadelphia-positive, t(9;22)), TEL-AML1 (t(12;21)) and TCF3-PBX1 (t(1;19)), using single-cell Raman imaging combined with multivariate statistical analysis. Spectra collected from clinical samples were compared with single-cell spectra of B-cells collected from healthy donors, constituting the control group. We demonstrated that Raman spectra of normal B cells strongly differ from spectra of their malignant counterparts, especially in the intensity of bands, which can be assigned to nucleic acids. We also showed that the identification of leukemia subtypes could be automated with the use of chemometric methods. Results prove the clinical suitability of Raman imaging for the identification of spectroscopic markers characterizing leukemia cells.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.