Raman and infrared spectroscopy of carbohydrates: A review

Raman spectroscopy in lung cancer diagnostics: Can an in vivo setup compete with ex vivo applications?

Lung carcinoma remains the leading cause of cancer death worldwide. The tactic to change this unfortunate rate may be a timely and rapid diagnostic, which may in many cases improve patient prognosis. In our study, we focus on the comparison of two novel methods of rapid lung carcinoma diagnostics, label-free in vivo and ex vivo Raman spectroscopy of the epithelial tissue, and assess their feasibility in clinical practice. As these techniques are sensitive not only to the basic molecular composition of the analyzed sample but also to the secondary structure of large biomolecules, such as tissue proteins, they represent suitable candidate methods for epithelial cancer diagnostics. During routine bronchoscopy, we collected 78 in vivo Raman spectra of normal and cancerous lung tissue and 37 samples of endobronchial pathologies, which were subsequently analyzed ex vivo. Using machine learning techniques, namely principal component analysis (PCA) and support vector machines (SVM), we were able to reach 87.2% (95% CI, 79.8-94.6%) and 100.0% (95% CI, 92.1-100.0%) of diagnostic accuracy for in vivo and ex vivo setup, respectively. Although the ex vivo approach provided superior results, the rapidity of in vivo Raman spectroscopy might become unmatchable in the acceleration of the diagnostic process.

Mapping lipid species remodeling in high fat diet-fed mice: Unveiling adipose tissue dysfunction with Raman microspectroscopy

Dysregulated lipid metabolism in obesity leads to adipose tissue expansion, a major contributor to metabolic dysfunction and chronic disease. Lipid metabolism and fatty acid changes play vital roles in the progression of obesity. In this proof-of-concept study, Raman techniques combined with histochemical imaging methods were utilized to analyze the impact of a high-fat diet (HFD) on different types of adipose tissue in mice, using a small sample size (n = 3 per group). After six weeks of high-fat diet (HFD) feeding, our findings showed hypertrophy, elevated collagen levels, and increased macrophage presence in the adipose tissues of the HFD group compared to the low-fat diet (LFD) group. Statistical analysis of Raman spectra revealed significantly lower unsaturated lipid levels and higher lipid to protein content in different fat pads (brown adipose tissue (BAT), subcutaneous white adipose tissue (SWAT), and visceral white adipose tissue (VWAT)) with HFD. Raman images of adipose tissues were analyzed using Empty modeling and DCLS methods to spatially profile unsaturated and saturated lipid species in the tissues. It revealed elevated levels of ω-3, ω-6, cholesterol, and triacylglycerols in BAT adipose tissues of HFD compared to LFD tissues. These findings indicated that while cholesterol, ω-6/ω-3 ratio, and triacylglycerol levels have risen in the SWAT and VWAT adipose tissues of the HFD group, the levels of ω-3 and ω-6 have decreased following the HFD. The study showed that Raman spectroscopy provided invaluable information at the molecular level for investigating lipid species remodeling and spatial mapping of adipose tissues during HFD.

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.

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time

With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibrational molecular spectroscopy and machine learning (ML) detect biomolecular changes consistent with the presence of viral infection. Saliva samples were collected from 470 individuals, including 65 that were infected with COVID-19 (28 from hospitalized patients and 37 from a walk-in testing clinic) and 251 that had a negative polymerase chain reaction (PCR) test. A further 154 were collected from healthy volunteers. Saliva measurements were achieved in 6 minutes or less and led to machine learning models predicting COVID-19 infection with sensitivity and specificity reaching 90%, depending on volunteer symptoms and disease severity. Machine learning models were based on linear support vector machines (SVM). This platform could be deployed to manage future pandemics using the same hardware but using a tunable machine learning model that could be rapidly updated as new viral strains emerge.

Analytical tools to assess polymer biodegradation: A critical review and recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer's properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Cervical cancer diagnosis model using spontaneous Raman and Coherent anti-Stokes Raman spectroscopy with artificial intelligence

Cervical cancer is the fourth most common cancer worldwide. Histopathology, which is currently considered the gold standard for cervical cancer diagnosis, can be time-consuming and subjective. Therefore, there is an urgent need for a rapid, objective, and non-destructive cervical cancer detection technique. In this study, high-wavenumber spontaneous Raman spectroscopy was used to detect cervical squamous cell carcinoma and normal tissues. The levels of lipids, fatty acids, and proteins in cervical cancerous tissues were found to be higher than those in normal tissues. Raman difference spectroscopy revealed the most significant difference at 2928 cm-1. Additionally, a Coherent anti-Stokes Raman spectroscopy (CARS) instrument was employed to enhance the wavenumber signal intensity and sensitivity. The intrinsic relationship between CARS imaging and cervical lesions was established. The CARS images indicated that the intensity of normal cervical squamous cells was zero, whereas the intensities of keratinized and non-keratinized cervical squamous cell carcinoma tissues were significantly higher. Consequently, diagnostic outcomes could be obtained by observing CARS images with the naked eye. Furthermore, the characteristic structure of keratin pearls in keratinized cervical cancer could serve as a marker for subdividing cervical cancer types. Finally, a ConvNeXt network, a machine-learning model built from CARS images, was utilized to classify different types of tissue images. The results indicated a verification accuracy of 100 %, with a loss function of 0.0927. These findings suggest that the diagnostic model established using CARS images could efficiently diagnose cervical cancer, providing novel insights into the pathological diagnosis of this disease.

Raman imaging for monitoring deuterated squalene-gemcitabine nanomedicines in single living breast cancer cells

We have investigated the impact of gemcitabine (Gem) and deuterated gemcitabine-squalene (GemSQ-d6) nanoparticles (NPs) on MCF7 and MDA-MB-231 breast cancer cell lines by Raman spectroscopy. Quantification of LDL expression levels in both cell lines revealed a four-fold increase in MDA-MB-231 cells compared to MCF7 cells. In in vitro antitumor assessments, Gem displayed 13.5 times more effectiveness than GemSQ NPs against MCF7 cells, whereas GemSQ NPs induced a 14-fold increase in cytotoxicity compared to Gem for MDA-MB-231 cells. Oil Red O staining revealed that the treatment with GemSQ-d6 NPs induced a higher accumulation of lipid droplets at the periphery of the nucleus in MDA-MB-231 cells compared to MCF7 cells. Raman spectroscopy was employed to assess the impact of these drugs (50 µM, 24 h) on these breast cancer cell lines. By using the silent region (2000-2400 cm-1), we demonstrated that the accumulation of the GemSQ-d6 bioconjugate was higher in the cytoplasm of MDA-MB-231 cells than in MCF7 cells. This difference in drug accumulation is likely correlated with their expression levels of LDL receptors (LDLR) However, no information was obtained on Gem in this spectral region. We identified Raman features of squalene (SQ) in 700-1800 cm-1 fingerprint region that allowed us to observe almost the same distribution of GemSQ as that observed in the silent region for both cell lines treated with GemSQ-d6 or SQ-d6. Subsequently, the effects of Gem and GemSQ-d6 on cellular components such as proteins, nucleic acids, and cytochrome C were monitored within the fingerprint spectral region. Our results revealed distinct features in the subcellular accumulation of these biomolecules in response to Gem and GemSQ treatments.

Heterogeneity of Endothelial Cells Impacts the Functionality of Human Pancreatic In Vitro Models

Endothelial cells (ECs) play a crucial role in maintaining tissue homeostasis and functionality. Depending on their tissue of origin, ECs can be highly heterogeneous regarding their morphology, gene and protein expression, functionality, and signaling pathways. Understanding the interaction between organ-specific ECs and their surrounding tissue is therefore critical when investigating tissue homeostasis, disease development, and progression. In vitro models often lack organ-specific ECs, potentially limiting the translatability and validity of the obtained results. The goal of this study was to assess the differences between commonly used EC sources in tissue engineering applications, including human umbilical vein ECs (HUVECs), human dermal microvascular ECs (hdmvECs), and human foreskin microvascular ECs (hfmvECs), and organ-specific human pancreatic microvascular ECs (hpmvECs), and test their impact on functionality within an in vitro pancreas test system used for diabetes research. Utilizing high-resolution Raman microspectroscopy and Raman imaging in combination with established protein and gene expression analyses and exposure to defined physical signals within microfluidic cultures, we identified that ECs exhibit significant differences in their biochemical composition, relevant protein expression, angiogenic potential, and response to the application of mechanical shear stress. Proof-of-concept results showed that the coculture of isolated human islets of Langerhans with hpmvECs significantly increased the functionality when compared with control islets and islets cocultured with HUVECs. Our study demonstrates that the choice of EC type significantly impacts the experimental results, which needs to be considered when implementing ECs into in vitro models.

Hyperspectral oblique plane microscopy enables spontaneous, label-free imaging of biological dynamic processes in live animals

Spontaneous Raman imaging has emerged as powerful label-free technique for investigating the molecular composition of medicines and biological specimens. Although Raman imaging can facilitate understanding of complex biological phenomena in vivo, current imaging modalities are limited in speed and sample compatibility. Here, we introduce a single-objective line-scanning light-sheet microscope, named [Formula: see text]-OPM, which records Raman images on a timescale of minutes to seconds. To demonstrate its function, we use [Formula: see text]-OPM to map and identify microplastic particles based on their Raman spectral characteristics. In live zebrafish embryos, we show that [Formula: see text]-OPM can capture wound dynamics at five-minute intervals, revealing rapid changes in cellular and extracellular matrix composition in the wounded region. Finally, we use [Formula: see text]-OPM to synchronize and average 36,800 individual frames to obtain hyperspectral videos of a zebrafish embryo's beating heart at an effective 28 frames per second, recording compositional changes throughout the cardiac cycle.

Metabolic Response to Small Molecule Therapy in Colorectal Cancer Tracked with Raman Spectroscopy and Metabolomics

Despite numerous screening tools for colorectal cancer (CRC), 25 % of patients are diagnosed with advanced disease. Novel diagnostic technologies that are early, accurate, and rapid are imperative to assess the therapeutic efficacy of clinical drugs and identify new biomarkers of treatment response. Here Raman spectroscopy (RS) was used to track metabolic reprogramming in KRAS-mutant HCT116 and SW837 cells, and KRAS wild-type CC cells. RS combined with multivariate analysis methods distinguished nonresponsive, partially responsive, and responsive cells treated with cetuximab, a monoclonal antibody for EGFR inhibition, sotorasib, a clinically approved KRAS inhibitor, and various doses of trametinib, an inhibitor of the MAPK pathway. Cells treated with a combination of subtoxic doses of trametinib and BKM120, an inhibitor of the PI3K pathway, showed a synergistic response between the two pathways. Using a supervised machine learning regression model, we established a scoring methodology trained to a priori predict therapeutic response to new treatment combinations. RS metabolites were verified with mass spectrometry, and enrichment pathways were identified, including amino acid, purine, and nicotinate and nicotinamide metabolism that differentiated monotherapy from combination therapy. Our approach may ultimately be applicable to patient-derived primary cells and cultures of patient tumors to predict effective drugs for individualized care.

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Carotenoids dispersed in gypsum rock as a result of algae adaptation to the extreme conditions of the Atacama Desert

The high-altitude pre-Andean region of the Atacama Desert is characterized by its stark volcanic rock formations and unique hydrothermal gypsum outcrops (gypcrete) that it hosts. This study delves into the biomolecular composition of the endolithic phototrophic microbes that thrive within these gypcretes. Using advanced Raman spectroscopy techniques, including Raman imaging (complemented by microscopic and 3D microscopic observations), herein we unveil new insights into the adaptive strategies of these gypsum-inhabiting algae. Our Raman imaging results provide a detailed chemical map of carotenoids associated with microbial colonization. This map reveals a significant gradient in pigment content, highlighting a critical survival mechanism for algae and cyanobacteria in this polyextreme environment. Intriguingly, we detected signals for carotenoids not only in the algae-colonized layer, but also deeper within the gypsum matrix - indicating pigment migration following cell disruption. In addition, we conducted an in-depth analysis of individual algal cells from the Trebouxiaceae family, noting their color variations from green to orange, plus describing the spectral differences in detail. This investigation identified in-vivo pigments (carotenoids, chlorophyll) and lipids at the cellular level, offering a comprehensive view of the molecular adaptations enabling life in one of the Earth's most extreme habitats.

Protein-metal interactions due to fretting corrosion at the taper junction of hip implants: An in vitro investigation using Raman spectroscopy

Modular hip implants are a clinically successful and widely used treatment for patients with arthritis. Despite ongoing retrieval studies the understanding of the fundamental physico-chemical mechanisms of friction and wear within the head-taper interface is still limited. Here, we Raman-spectroscopically analyze structural features of the biotribological material which is formed within the taper joint between Ti6Al4V and low-carbon cobalt alloy or high-nitrogen steel surfaces in in vitro gross-slip fretting corrosion tests with bovine calf serum. As a function of the fretting duration, we investigate short and long aliphatic chains and their adsorption behavior on the cobalt- and steel-type surfaces. Using the intensity and frequency shifts of the amide I and III Raman bands, we furthermore identify progressive protein folding and unfolding including the secondary structures of α-helix, β-sheet, and random-coil configuration as well as the formation of proteinaceous clusters depending on the hydrophilicity of the metallic surfaces. We additionally find a mixture of chromates and iron oxides with tryptophan and tyrosine at the worn cobalt alloy and high-nitrogen steel surfaces, respectively. Also, for long fretting duration, sp2 hybridized amorphous carbon is formed due to fretting-induced cleavage of proteins. STATEMENT OF SIGNIFICANCE: Despite efforts enhancing the biomedical tribology of hip implants, the impact of the organic environment on friction and wear at the femoral head-stem taper interface is limitedly understood. Using Raman spectroscopy we resolve structural changes within the biotribological material agglomerated at biomedical-grade metal alloys due to metal-organic interactions during in vitro fretting corrosion tests. Adsorption of short and long aliphatic chains, progressive protein (un)folding and proteinaceous cluster formation depend to a distinguishable extent on the fretting duration and type of alloy. Chromates and iron oxides are mixed with tryptophan and tyrosine, and amorphous carbon is formed resulting from a fretting-induced cleavage of serum proteins. Such information spectroscopically gleaned from biotribological material are vital to improve the design and performance of taper junctions.

Focused ion beam-fabricated nanorod substrate for label-free surface-enhanced Raman spectroscopy and enabling dual virus detection

The COVID-19 pandemic presents global challenges, notably with co-infections in respiratory tract involving SARS-CoV-2 variants and influenza strains. Detecting multiple viruses simultaneously is crucial for accurate diagnosis, effective tracking infectious sources, and containment of the epidemic. This study uses a label-free surface-enhanced Raman spectroscopy (SERS) method using Au NPs/pZrO2 (250) and FIB-made Au NRs (100) to detect dual viruses, including SARS-CoV-2 Delta variant (D) and influenza A (A) or B (B) virus. Results demonstrate distinct peaks facilitating virus differentiation, especially between D and A or B, with clear disparities between substrates; specific peaks at 950 and 1337 cm-1 are pivotal for discerning viruses using Au NPs/pZrO2 (250), while those at 1050, 1394, and 1450 cm-1 and 1033, 1165, 1337, and 1378 cm-1 are key for validation using Au NRs (100). Differences in substrate surface morphology and spatial disposition of accommodating viruses significantly influence hotspot formation and Raman signal amplification efficiency, thereby affecting the ability to distinguish various viruses. Furthermore, both substrates offer insights, even in the presence of oxymetazoline hydrochloride (an interfering substance), with practical implications in viral diagnosis. The customized design and reproducibility underscore efficient Raman signal amplification, even in challenging environments, highlighting potential for widespread virus detection.

The impact of transmembrane peptides on lipid bilayer structure and mechanics: A study of the transmembrane domain of the influenza A virus M2 protein

Transmembrane peptides play important roles in many biological processes by interacting with lipid membranes. This study investigates how the transmembrane domain of the influenza A virus M2 protein, M2TM, affects the structure and mechanics of model lipid bilayers. Atomic force microscopy (AFM) imaging revealed small decreases in bilayer thickness with increasing peptide concentrations. AFM-based force spectroscopy experiments complemented by theoretical model analysis demonstrated significant decreases in bilayer's Young's modulus (E) and lateral area compressibility modulus (KA). This suggests that M2TM disrupts the cohesive interactions between neighboring lipid molecules, leading to a decrease in both the bilayer's resistance to indentation (E) and its ability to resist lateral compression/expansion (KA). The large decreases in bilayer elastic parameters (i.e., E and KA) contrast with small changes in bilayer thickness, implying that bilayer mechanics are not solely dictated by bilayer thickness in the presence of transmembrane peptides. The observed significant reduction in bilayer mechanical properties suggests a softening effect on the bilayer, potentially facilitating membrane curvature generation, a crucial step for M2-mediated viral budding. In parallel, our Raman spectroscopy revealed small but statistically significant changes in hydrocarbon chain vibrational dynamics, indicative of minor disordering in lipid chain conformation. Our findings provide useful insights into the complex interplay between transmembrane peptides and lipid bilayers, highlighting the significance of peptide-lipid interactions in modulating membrane structure, mechanics, and molecular dynamics.

Feasibility of a Fiber-Dispersive Raman Spectrometer for Biomarker Detection

Raman spectroscopy is among the top analytical techniques for ultra-low-dense organic matter, crucial to the search for life and analysis of celestial body surfaces in space exploration missions. Achieving the ultimate sensitivity of in-situ Raman spectroscopy necessitates a breakthrough in detecting inelastically scattered light. Single-photon detectors (SPDs) operating in photon counting mode, which can differentiate between Raman and luminescence responses, are promising candidates for the challenging scientific requirements. Since large SPD arrays are not yet commercially available, a dispersive element can be adapted to a single-pixel detector. By exploiting chromatic dispersion in optical fibers and picosecond-pulsed excitation, we delay the arrivals of different spectral components onto a single-pixel SPD. This method also separates weak Raman signals from stronger luminescence through correlated time-domain measurements. We study the impact of fiber properties and the excitation wavelength of a pulsed laser on the spectral resolution of the fiber-dispersive Raman spectrometer (FDRS). Additionally, we demonstrate the FDRS's potential for studying biomarkers and discuss its feasibility for analyzing inclusions in ice matrices.

Increased obesogenic action of palmitic acid during early stage of adipogenesis

The functional differences between preadipocytes and fully differentiated mature adipocytes derived from stromal vascular fraction stem cells, as well as primary adipocytes have been analysed by evaluating their response to the obesogenic factor (a saturated fatty acid) and TNF-triggered inflammation. The analysis of single adipocytes shows that the saturated fatty acid (palmitic acid) accumulation is accompanied by inflammation and considerably dependent on the stage of the adipogenesis. In particular, preadipocytes show the exceptional potential for palmitic acid uptake resulting in their hypertrophy and the elevated cellular expression of the inflammation marker (ICAM-1). Our research provides new information on the impact of obesogenic factors on preadipocytes that is important in the light of childhood obesity prevention.

Fundamentals and Applications of Raman-Based Techniques for the Design and Development of Active Biomedical Materials

Raman spectroscopy is an analytical method based on light-matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided.

Unveiling Microbial Diversity: Raman Spectroscopy's Discrimination of Clostridium and Related Genera

In the clinical environment, the identification of phylogenetic closely related genera and species like Clostridium and Bacillus spp. is challenging. Both genera contain representatives of pathogenic and nonpathogenic species that need to be distinguished for a proper diagnostic read-out. Therefore, reliable and accurate detection methods must be employed for the correct identification of these genera and species. Despite their high pathogenicity, clostridial infections and food contaminations present significant challenges due to their unique cultivation conditions and developmental needs. Therefore, in many diagnostic protocols, the toxins are used for microbiological documentation. However, the applied laboratory methods suffer in accuracy, sometimes require large bacterial loads to provide reliable results, and cannot differentiate pathogenic from nonpathogenic strains. Here, Raman spectroscopy was employed to create an extensive Raman database consisting of pathogenic and nonpathogenic Bacillus and Clostridium species. These genera, as well as representatives of Paraclostridium and Clostridioides were specifically selected for their phylogenetic relation, cultivation conditions, and metabolic activity. A chemometric evaluation of the Raman spectra of single vegetative cells revealed a high discriminating power at the genus level. However, bacilli are considerably easier to classify at the species level than clostridia. The discrimination between the genera and species was based on their phylogeny and not their aerobic and anaerobic cultivation conditions. These encouraging results demonstrated that Raman spectroscopy coupled with chemometrics is a robust and helpful method for differentiating Clostridium species from Bacillus, Clostridioides, and Paraclostridium species. This approach has the potential to be a valuable tool in clinical diagnostics.

Combining Multiple Spectroscopic Techniques to Reveal the Effects of Staphylococcus aureus Infection on Human Bone Tissues

Osteomyelitis (OM) and periprosthetic joint infections (PJIs) are major public health concerns in Western countries due to increased life expectancy. Infections usually occur due to bacterial spread through fractures, implants, or blood-borne transmission. The pathogens trigger an inflammatory response that hinders bone tissue regeneration. Treatment requires surgical intervention, which involves the precise removal of infected tissue, wound cleansing, and local and systemic antibiotic administration. Staphylococcus aureus (SA) is one of the most common pathogens causing infection-induced OM and PJIs. It forms antimicrobial-resistant biofilms and is frequently found in healthcare settings. In this proof-of-concept, we present an approach based on multiple spectroscopic techniques aimed at investigating the effects of SA infection on bone tissue, as well as identifying specific markers useful to detect early bacterial colonization on the tissue surface. A cross-section of a human femoral diaphysis, with negative-culture results, was divided into three parts, and the cortical and trabecular regions were separated from each other. Two portions of each bone tissue type were infected with SA for one and seven days, respectively. Multiple techniques were used to investigate the impact of the infection on bone tissue, Brillouin-Raman microspectroscopy and attenuated total reflection Fourier transform infrared spectroscopy were employed to assess and develop a new noninvasive diagnostic method to detect SA by targeting the bone of the host. The results indicate that exposure to SA infection significantly alters the bone structure, especially in the case of the trabecular type, even after just one day. Moreover, Raman spectral markers of the tissue damage were identified, indicating that this technique can detect the effect of the pathogens' presence in bone biopsies and pave the way for potential application during surgery, due to its nondestructive and contactless nature.

Cholesterol Conformational Structures in Phospholipid Membranes

Cholesterol is a major component of biomembranes that impacts membrane order, permeability, and lateral organization, but the precise molecular mechanisms of cholesterol's actions are still under investigation. Density functional theory (DFT) calculations have opened the fingerprint vibration bands of large molecules to detailed spectral analysis. For cholesterol, Raman spectral interpretation for conformational structure and hydrogen bonding is now possible. Here, DFT calculations of cholesterol conformers identify 10 structure types that also have unique low-frequency Raman spectra. By fitting experimental spectra to these types, the distribution of cholesterol structures present in phospholipid (PL) membrane vesicles was measured. The distributions reveal that the cholesterol iso-octyl chain tends to align with saturated PL chains and shifts to a thermal distribution for unsaturated PL chains. The results agree with the templating effect of cholesterol on PL membranes and show that the top of the iso-octyl chain is rigid like the rings. It is also shown that the inclusion of water molecules hydrogen bonded to the cholesterol hydroxy group in the DFT calculations may improve the spectral fitting for future studies.

Comparison of biochemical changes induced in radioresistant prostate cancer cells by X-rays, radiosensitizing drugs, and a combined therapy using Raman microspectroscopy

Cancer radioresistance is a major problem in radiotherapy. Many strategies have been proposed to overcome this process including the use of radiosensitizing drugs such as C75 or silibinin. The overall result of all treatments (radiotherapy, chemotherapy, and combined treatment) is cancer cell death. On the other hand, each treatment affects cancer cells differently at the molecular level. However, little is known about biochemical changes induced in cancer cells by these treatments (especially in combined therapy) at the submicroscale. In this study, Raman microspectroscopy was applied to follow such changes induced in radioresistant prostate cancer cells by X-rays, radiosensitizing drugs (C75, silibinin), and a combined treatment. The analysis was supported by the Partial Least Squares Regression method to reveal spectral changes induced by an increasing dose of X-rays and concentrations of the drugs. The obtained regression coefficient (β) plots were compared to each other using a correlation coefficient (R). Our results show that PC-3 cells exhibit dose- and concentration-dependent responses to the treatment with different biochemical changes induced by X-rays in the presence of C75 and silibinin. Moreover, both drugs affect the cells differently at the submicroscale and independently from the X-ray's presence. Finally, C75 shows significant efficiency in the reduction of cell radioresistance.

Exploring pH-Triggered Lamellar to Cubic Phase Transition in 2-Hydroxyoleic Acid/Monoolein Nanodispersions: Insights into Membrane Physicochemical Properties

Self-assembled lipid nanoparticles (LNPs) are essential nanocarriers for drug delivery. Functionalization of LNPs with ionizable lipids creates pH-responsive nanoparticles that change structures under varying pH conditions, enabling pH-triggered drug release. Typically, bicontinuous cubic phase nanoparticles (Cubosomes) and lamellar structured vesicles (Liposomes) differ in lipid packing statuses, affecting drug release and cellular uptake. However, most research predominantly focuses on elucidating lattice structure changes of these LNPs without a deep investigation of lipid-membrane properties. Addressing this gap, our study delves into the lipid-membrane physicochemical property variations during the lamellar-to-cubic phase transition. Here, we prepared pH-responsive LNPs using 2-hydroxyoleic acid/monoolein (2-OHOA/MO) binary components. Small-angle X-ray scattering (SAXS) revealed a phase transition from lamellar vesicles (Lα) to cubosomes (Im3m/Pn3m) with pH reduction. Laurdan and 1,6-diphenyl-1,3,5-hexatriene (DPH) fluorescence probes tracked the lipid-water interfacial polarity and lipid-membrane fluidity variations during the phase transition. Raman spectroscopy provided further insights into lipid-membrane lipid chain packing and chain torsion. We observed that the changes in lipid-membrane properties coincided with the lamellar-to-cubic phase transition, emphasizing the interplay between the phase structure and lipid-membrane behaviors in the 2-OHOA/MO system. This study provides insights into the lipid-membrane properties variation during the pH-triggered phase transition in the 2-OHOA/MO system, guiding future research toward more effective and reliable pH-responsive drug delivery platforms.

Cisplatin-Induced Metabolic Responses Measured with Raman Spectroscopy in Cancer Cells, Spheroids, and Canine-Derived Organoids

Ex vivo assessment of drug response with conventional cell viability assays remains the standard practice for guiding initial therapeutic choices. However, such ensemble approaches fail to capture heterogeneities in treatment response and cannot identify early markers of response. Here, we leverage Raman spectroscopy (RS) as an accurate, low-cost, extraction-free, and label-free approach to track metabolic changes in cancer cells, spheroids, and organoids in response to cisplatin treatment. We identified 12 statistically significant metabolites in cells and 19 metabolites in spheroids and organoids as a function of depth. We show that the cisplatin treatment of 4T1 cells and spheroids results in a shift in metabolite levels; metabolites including nucleic acids such as DNA, 783 cm-1 with p = 0.00021 for cells; p = 0.02173 for spheroids, major amino acids such as threonine, 1338 cm-1 with p = 0.00045 for cells; p = 0.01022 for spheroids, proteins such as amide III, 1248 cm-1 with p = 0.00606 for cells; p = 0.00511 for spheroids serve as early predictors of response. Our RS findings were also applicable to canine-derived organoids, showing spatial variations in metabolic changes as a function of organoid depth in response to cisplatin. Further, the metabolic pathways such as tricarboxylic acid (TCA)/citric acid cycle and glyoxylate and dicarboxylate metabolism that drive drug response showed significant differences based on organoid depth, replicating the heterogeneous treatment response seen in solid tumors where there is a difference from the periphery to the tumor core. Our study showcases the versatility of RS as a predictive tool for treatment response applicable from cells to organotypic cultures, that has the potential to decrease animal burden and readout time for preclinical drug efficacy.

Multimodal Molecular Imaging Reveals a Novel Membrane Component in Sporangia of the Rare Actinomycete Actinoplanes missouriensis

The bacterium Actinoplanes missouriensis belongs to the genus Actinoplanes, a prolific source of useful natural products. This microbe forms globular structures called sporangia, which contain many dormant spores. Recent studies using transmission electron microscopy have shown that the A. missouriensis sporangium membrane has an unprecedented three-layer structure, but its molecular components remain unclear. Here, we present multimodal (spontaneous Raman scattering, coherent anti-Stokes Raman scattering, second harmonic generation, sum frequency generation, and third-order sum frequency generation) label-free molecular imaging of intact A. missouriensis sporangia. Spontaneous Raman imaging assisted with multivariate curve resolution-alternating least-squares analysis revealed a novel component in the sporangium membrane that exhibits unique Raman bands at 1550 and 1615 cm-1 in addition to those characteristic of lipids. A plausible candidate for this component is an unsaturated carbonyl compound with an aliphatic moiety derived from fatty acid. Furthermore, second harmonic generation imaging revealed that a layer(s) of the sporangium membrane containing this unknown component has an ordered, noncentrosymmetric structure like fibrillar proteins and amylopectin. Our results suggest that the sporangium membrane is a new type of biological membrane, not only in terms of architecture but also in terms of components. We demonstrate that multimodal molecular imaging with Raman scattering as the core technology will provide a promising platform for interrogating the chemical components, whether known or unknown, of diverse biological structures produced by microbes.

Oxidative Stability of Fish Oil-Loaded Nanocapsules Produced by Electrospraying Using Kafirin or Zein Proteins as Wall Materials

The encapsulation of fish oil by monoaxial electrospraying using kafirin or zein proteins as hydrophobic wall materials was investigated. Kafirin resulted in spherical fish oil-loaded nanocapsules (>50% of capsules below 1 µm), whereas zein led to fish oil-loaded nanocapsules with non-spherical morphology (>80% of capsules below 1 µm). Both hydrophobic encapsulating materials interacted with fish oil, successfully entrapping the oil within the protein matrix as indicated by Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy results. FTIR also suggested hydrogen bonding between fish oil and the proteins. Trapped radicals in the encapsulation matrix that were detected by electron paramagnetic resonance (EPR), indicated oxidation during electrospraying and storage. Results from isothermal (140 °C) differential scanning calorimetry (DSC) denoted that the encapsulation of fish oil by electrospraying using both kafirin or zein as wall materials protected fish oil from oxidation. In particular, the zein-based nanocapsules were 3.3 times more oxidatively stable than the kafirin-based nanocapsules, which correlates with the higher oil encapsulation efficiency found for zein-based capsules. Thus, this study shows that kafirin might be considered a hydrophobic wall material for the encapsulation of fish oil by electrospraying, although it prevented lipid oxidation to a lower extent when compared to zein.

In Situ Raman Hyperspectral Analysis of Microbial Colonies for Secondary Metabolites Screening

Since the discovery of penicillin, a vast array of microbial antibiotics has been identified and applied in the medical field. Globally, the search for drug candidates via microbial screening is ongoing. Traditional screening methods, however, are time-consuming and require labor-intensive sample processing, significantly reducing throughput. This research introduces a Raman spectroscopy-based screening system tailored to the in situ analysis of microbial colonies on solid culture media. Employing multivariate curve resolution-alternating least-squares (MCR-ALS) for spectral decomposition, our approach reveals the production of secondary metabolites at the single colony level. We enhanced the microbial culture method, enabling direct, high signal-to-noise (S/N) ratio Raman spectroscopic measurements of colonies of Escherichia coli and actinomycetes species. Through semisupervised MCR analysis using the known spectra of actinorhodin and undecylprodigiosin as references, we accurately assessed the production of these compounds by Streptomyces coelicolor A3(2). Furthermore, we herein successfully detected the production of amphotericin B by Streptomyces nodosus, even in the absence of prior spectral information. This demonstrates the potential of our technique in the discovery of secondary metabolites. In addition to enabling the detection of the above-mentioned compounds, this analysis revealed the heterogeneity of the spatial distribution of their production in each colony. Our technique makes a significant contribution to the advancement of microbial screening, offering a rapid, efficient alternative to conventional methods and opening avenues for secondary metabolites discovery.

New insights into lipid and fatty acid metabolism from Raman spectroscopy

One of the challenges facing biology is to understand metabolic events at a single cellular level. While approaches to examine dynamics of protein distribution or report on spatiotemporal location of signalling molecules are well-established, tools for the dissection of metabolism in single living cells are less common. Advances in Raman spectroscopy, such as stimulated Raman scattering (SRS), are beginning to offer new insights into metabolic events in a range of experimental systems, including model organisms and clinical samples, and across a range of disciplines. Despite the power of Raman imaging, it remains a relatively under-used technique to approach biological problems, in part because of the specialised nature of the analysis. To raise the profile of this method, here we consider some key studies which illustrate how Raman spectroscopy has revealed new insights into fatty acid and lipid metabolism across a range of cellular systems. The powerful and non-invasive nature of this approach offers a new suite of tools for biomolecular scientists to address how metabolic events within cells informs on or underpins biological function. We illustrate potential biological applications, discuss some recent advances, and offer a direction of travel for metabolic research in this area.

Raman imaging unveils heme uptake in endothelial cells

Heme released from damaged and senescent red blood cells (RBCs) may contribute to oxidant-mediated cell injury. One of the recently investigated physiological processes, essential in preventing the inflammatory impact of labile heme, is its uptake from the bloodstream by endothelial cells (ECs). In this study, we investigated heme uptake by ECs starting from the model studies on the in vitro cellular level, through the endothelium layer on the ex vivo murine aortic tissues. As the cellular model, Human Aortic Endothelial Cells (HAECs) were chosen, and the concentration of labile heme was adjusted so to avoid the excessive toxic effect of the labile heme. We utilized label-free Raman imaging with two different excitation wavelengths to capture the uptake process in situ and characterize the oxidation state of the iron ion in the intercalated heme. The phenomenon of heme uptake was demonstrated in both, the healthy control C57Bl/6J and FVB animals, as well as in mice with developed atherosclerosis (ApoE/LDLR-/- mice). In the presented work, we presented for the first time Raman-based evidence on the heme uptake process by endothelial cells in both, in vitro and ex vivo systems.

Raman Spectral Analysis in the CHx-Stretching Region as a Guiding Beacon for Non-Targeted, Disruption-Free Monitoring of Germination and Biofilm Formation in the Green Seaweed Ulva

Raman spectroscopy was used to study the complex interactions and morphogenesis of the green seaweed Ulva (Chlorophyta) and its associated bacteria under controlled conditions in a reductionist model system. Integrating multiple imaging techniques contributes to a more comprehensive understanding of these biological processes. Therefore, Raman spectroscopy was introduced as a non-invasive, label-free tool for examining chemical information of the tripartite community Ulva mutabilis-Roseovarius sp.-Maribacter sp. The study explored cell differentiation, cell wall protrusion, and bacterial-macroalgae interactions of intact algal thalli. Using Raman spectroscopy, the analysis of the CHx-stretching wavenumber region distinguished spatial regions in Ulva germination and cellular malformations under axenic conditions and upon inoculation with a specific bacterium in bipartite communities. The spectral information was used to guide in-depth analyses within the fingerprint region and to identify substance classes such as proteins, lipids, and polysaccharides, including evidence for ulvan found in cell wall protrusions.

Application of in-line Raman spectroscopy to monitor crystallization and melting processes in milk fat

Anhydrous milk fat (AMF) and its fractions are used as ingredients in a wide range of food applications. Obtaining the appropriate solid fat content (SFC) is essential to achieve the desired product texture. At present, in-line monitoring techniques to control milk fat crystallization and melting are largely unavailable. The thermal behaviour of milk fat (AMF and four of its fractions) was monitored in a temperature-controlled vessel using an in-line Raman analyser and compared with thermograms generated using differential scanning calorimetry (DSC). The major stages of milk fat crystallization and melting were identified using the in-line Raman analyser. Thermal data from DSC showed excellent linear correlations with Raman spectral data (R2 value of 0.97 for the onset of milk fat crystallisation). Partial least squares regression (PLSR) models were developed using Raman spectra to predict SFC with coefficient of determination (R2Cs) from 0.929 to 0.992 and root mean standard error of calibration (RMSECs) ranging from 3.20 to 10.36%. Results demonstrated Raman spectroscopy has significant potential as a way of monitoring milk fat crystallization and melting processes.

Spontaneous-stimulated Raman co-localization dual-modal analysis approach for efficient identification of tumor cells

The study of highly heterogeneous tumor cells, especially acute myeloid leukemia (AML) cells, usually relies on invasive analytical methods such as morphology, immunology, cytogenetics, and molecular biology classification, which are complex and time-consuming to perform. Mortality is high if patients are not diagnosed in a timely manner, so rapid label-free analysis of gene expression and metabolites within single-cell substructures is extremely important for clinical diagnosis and treatment. As a label-free and non-destructive vibrational detection technique, spontaneous Raman scattering provides molecular information across the full spectrum of the cell but lacks rapid imaging localization capabilities. In contrast, stimulated Raman scattering (SRS) provides a high-speed, high-resolution imaging view that can offer real-time subcellular localization assistance for spontaneous Raman spectroscopic detection. In this paper, we combined multi-color SRS microscopy with spontaneous Raman to develop a co-localized Raman imaging and spectral detection system (CRIS) for high-speed chemical imaging and quantitative spectral analysis of subcellular structures. Combined with multivariate statistical analysis methods, CRIS efficiently differentiated AML from normal leukocytes with an accuracy of 98.1 % and revealed the differences in the composition of nuclei and cytoplasm of AML relative to normal leukocytes. Compared to conventional Raman spectroscopy blind sampling without imaging localization, CRIS increased the efficiency of single-cell detection by at least three times. In addition, using the same approach for further identification of AML subtypes M2 and M3, we demonstrated that intracytoplasmic differential expression of proteins is a marker for their rapid and accurate classifying. CRIS analysis methods are expected to pave the way for clinical translation of rapid tumor cell identification.

Rapid profiling of fish cell nitrogen metabolism with single-cell Raman spectroscopy: Unveiling enzyme's role in ammonia detoxification

Ammonia is a prevalent aquatic pollutant that disrupts cellular functions and energy metabolism in fish, posing significant environmental and health threats. This research investigates the critical role of arginase 2 (ARG2) in mitigating ammonia toxicity in fish cells and its implications in adapting to nitrogen metabolism under high ammonia exposure. Through a CRISPR-Cas9 engineered ARG2 knockdown (KD) in the Epithelioma Papulosum Cyprini (EPC) cell line, we first investigated the biochemical responses of ARG2 KD and wild-type (WT) EPC cells to ammonia stress (NH4Cl treatment), showing diminished urea production and decreased cell viability in ARG2 KD cells. Subsequently, single-cell Raman spectroscopy analysis revealed that ARG2 KD cells exhibited profound metabolic shifts, including changes in protein, nucleic acids, lipid and sugar levels, showing the adjusting role of ARG2 in the balance of carbohydrate and nitrogen metabolism. Furthermore, the upregulated responses of various amino acids, such as glutamine, arginine, alanine, glutamic acid, glycine, histidine, phenylalanine and valine, in WT cells after NH4Cl treatment diminished in ARG2 KD cells except for the decrease in aspartic acid, indicating a switching effect of ARG2 in nitrogen metabolism under ammonia stress. This study highlights ARG2's essential role in ammonia detoxification and emphasizes ARG2's protective function and its importance in metabolism, shedding light on the adaptive mechanisms fish cells deploy against high ammonia environments. These insights contribute to deep understanding of aquatic organisms' molecular responses to environmental ammonia pollution, offering potential strategies for their protection.

Fine-tuning of membrane permeability by reversible photoisomerization of aryl-azo derivatives of thymol embedded in lipid nanoparticles

Responsiveness of liposomes to external stimuli, such as light, should allow a precise spatial and temporal control of release of therapeutic agents or ion transmembrane transport. Here, some aryl-azo derivatives of thymol are synthesized and embedded into liposomes from 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine to obtain light-sensitive membranes whose photo-responsiveness, release behaviour, and permeability towards Cl- ions are investigated. The hybrid systems are in-depth characterized by dynamic light scattering, atomic force microscopy and Raman spectroscopy. In liposomal bilayer the selected guests undergo reversible photoinduced isomerization upon irradiation with UV and visible light, alternately. Non-irradiated hybrid liposomes retain entrapped 5(6)-carboxyfluorescein (CF), slowing its spontaneous leakage, whereas UV-irradiation promotes CF release, due to guest trans-to-cis isomerization. Photoisomerization also influences membrane permeability towards Cl- ions. Data processing, according to first-order kinetics, demonstrates that Cl- transmembrane transport is enhanced by switching the guest from trans to cis but restored by back-switching the guest from cis to trans upon illumination with blue light. Finally, the passage of Cl- ions across the bilayer can be fine-tuned by irradiation with light of longer λ and different light-exposure times. Fine-tuning the photo-induced structural response of the liposomal membrane upon isomerization is a promising step towards effective photo-dynamic therapy.

FABP4 Enhances Lipidic and Fibrotic Cardiac Structural and Ca2+ Dynamic Changes

BACKGROUND

Adipocyte FABP4 (fatty acid-binding protein 4) is augmented in the epicardial stroma of patients with long-standing persistent atrial fibrillation. Because this molecule is released mainly by adipocytes, our objective was to study its role in atrial cardiomyopathy, focusing our attention on fibrosis, metabolism, and electrophysiological changes. These results might clarify the role of adiposity as a mediator of atrial cardiomyopathy.

METHODS

We used several preclinical cellular models, epicardial and subcutaneous stroma primary cell cultures from patients undergoing open heart surgery, human atrial fibroblasts, atrial cardiomyocytes derived from human induced pluripotent stem cells and isolated from adult mice, and Nav1.5 transfected Chinese hamster ovary cells. Fibrosis, glucose, mitochondrial and adipogenesis activity, gene expression, and proteomics were determined by wound healing, enzymatic, colorimetric, fluorescence assays, real-time quantitative polymerase chain reaction, and TripleTOF proteomics. Molecular changes were analyzed by Raman confocal microspectroscopy, calcium dynamics by confocal microscopy, and ion currents by patch clamp. Epicardial, subcutaneous, and atrial fibroblasts and cardiomyocytes were incubated with FABP4 at 100 ng/mL.

RESULTS

Our results showed that FABP4 induced fibrosis, glucose metabolism, and lipid accumulation on epicardial and subcutaneous stroma cells and atrial fibroblasts. Besides, it modified lipid content and calcium dynamics in atrial cardiomyocytes without effects on INa.

CONCLUSIONS

FABP4 exerts fibrotic and metabolic changes on epicardial stroma and modifies lipid content and calcium dynamic on atrial cardiomyocytes. These results suggest its possible role as an atrial cardiomyopathy mediator.

Investigation of etravirine uptake and distribution in single aortic endothelial cells in vitro using Raman imaging

Etravirine (ETV) is an antiretroviral agent that belongs to the class of non-nucleoside reverse transcriptase inhibitors. This study explores the uptake and distribution of ETV in human aortic endothelial cells (HAECs) using Raman spectroscopy combined with chemometrics. The distinctive chemical structure of ETV facilitates tracking of its uptake by observing the Raman band at 2225 cm-1 in the Raman-silent region. The perinuclear distribution pattern in HAECs depends on drug concentration and incubation time. The uptake of ETV is observed within 5 minutes at a concentration of 10 μM, as evidenced by Raman images. Lower ETV concentrations, reflective of those found in human plasma, are detectable in HAECs by applying chemometric methods to Raman spectra from the perinuclear region. The ETV accumulation process is crucial in advancing our understanding of the drug's impact on biochemical alterations within endothelial cells. Additionally, ETV emerges as a promising Raman reporter for marking subcellular compartments, leveraging the 2225 cm-1 band in the cellular Raman silent region. This research contributes valuable insights into the behavior of ETV at the subcellular level, shedding light on its potential applications and impact on subcellular dynamics.

Alkyne-tagged imidazolium-based membrane cholesterol analogs for Raman imaging applications

Cholesterol is an important lipid playing a crucial role in mediating essential cellular processes as well as maintaining the basic structural integrity of biological membranes. Given its vast biological importance, there is an unabated need for sophisticated strategies to investigate cholesterol-mediated biological processes. Raman-tagged sterol analogs offer the advantage of being visualizable without the need for a bulky dye that potentially affects natural membrane integration and cellular interactions as it is the case for many conventionally used fluorescent analogs. Herein, we report a series of alkyne-tagged imidazolium-based cholesterol analogs (CHIMs) with large Raman scattering cross-sections that readily integrate into HEK cells and primary monocyte-derived macrophages and allow (multiplexed) cellular Raman imaging. We envision Raman-tagged CHIM analogs to be a powerful platform for the investigation of cholesterol-mediated cellular processes complementary to other established methods, such as the use of fluorescent analogs.

Fabrication of plasmonic probes for reproducible nanospectroscopic investigation of lipid monolayers - The electrochemical etching with DC-pulsed voltage

Tip-enhanced Raman spectroscopy (TERS) is a label-free analytical technique that characterizes molecular systems, potentially even with a nanometric resolution. In principle, the metallic plasmonic probe is illuminated with a laser beam generating the localized surface plasmons, which induce a strong local electric field enhancement in close proximity to the probe. Such field enhancement improves the Raman scattering cross-section from the sample volume localized near the probe apex. TERS provides a high spatial resolution and a great sensitivity, however, it is rather rarely used due to technical limitations causing unstable enhancement and the relative lack of data reproducibility. Despite many scientific efforts for the fabrication of effective TER probes providing robust TER enhancement still requires further investigations. In this work, we explore new possibilities based on preparation of scanning tunnelling microscopy (STM) plasmonic probes, since by nature of the tunnelling effect, they potentially could offer a very high spatial resolution in STM guided TERS experiments. Here we compare two methods of STM-TERS probe preparation for effective spectra acquisition. Our results strongly indicate that an application of square pulse voltage upon the etching procedure significantly improves the quality of the TER data over those obtained with a constant voltage one. To demonstrate the efficiency of our probes we present the results of hyperspectral TER mapping of the 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE) monolayer deposited on an ultra-pure and atomically flat gold substrate.

Pasture feeding improves the nutritional, textural, and techno-functional characteristics of butter

There is an increasing consumer desire for pasture-derived dairy products, as outdoor pasture-based feeding systems are perceived as a natural environment for animals. Despite this, the number of grazing animals globally has declined as a result of the higher milk yields achieved by indoor TMR feeding systems, in addition to the changing climatic conditions and lower grazing knowledge and infrastructure. This has led to the development of pasture-fed standards, stipulating the necessity of pasture and its minimum requirements as the primary feed source for products advertising such claims, with various requirements depending on the region for which it was produced. This work investigates the differences in the composition and techno-functional properties of butters produced from high, medium and no pasture allowance diets during early, mid, and late lactation. Butters were produced using milks collected from 3 feeding systems: outdoor pasture grazing (high pasture allowance); indoor TMR (no pasture allowance); and a partial mixed ration (medium pasture allowance) system, which involved outdoor pasture grazing during the day and indoor TMR feeding at night. Butters were manufactured during early, mid, and late lactation. Creams derived from TMR feeding systems exhibited the highest milk fat globule size. The fatty acid profiles of butters also differed significantly as a function of diet and could be readily discriminated by partial least squares analysis. The most important fatty acids in such an analysis, as indicated by their highest variable importance projection scores, were CLA C18:2 cis-9,trans-11 (rumenic acid), C16:1n-7 trans (trans-palmitoleic acid), C18:1 trans (elaidic acid), C18:3n-3 (α-linolenic acid), and C18:2n-6 (linoleic acid). Increasing pasture allowances resulted in reduced crystallization temperatures and hardness of butters and concurrently increasing the "yellow" color. Yellow color was strongly correlated with Raman peaks commonly associated with carotenoids. The milk fat globule size of cream decreased with advancing stage of lactation and churning time of cream was lowest in early lactation. Differences in the fatty acid and triglyceride contents of butter as a result of lactation and dietary effects demonstrated significant correlations with the hardness, rheological, melting, and crystallization profiles of the butters. This work highlighted the improved nutritional profile and functional properties of butter with increasing dietary pasture allowance, primarily as a result of increasing proportions of unsaturated fatty acids. Biomarkers of pasture feeding (response in milk proportionate to the pasture allowance) associated with the pasture-fed status of butters were also identified as a result of the significant changes in the fatty acid profile with increasing pasture allowance. This was achieved through the use of 3 authentic feeding systems with varying pasture allowances, commonly operated by farmers around the world and conducted across 3 stages of lactation.

Label-Free Identification of AML1-ETO Positive Acute Myeloid Leukemia Using Single-Cell Raman Spectroscopy

Acute myeloid leukemia (AML) is a malignant hematological tumor disease. Chromosomal abnormality is an independent prognostic factor in AML. AML with t(8:21) (q22; q22)/AML1-ETO (AE) is an independent disease group. In this research, a new method based on Raman spectroscopy is reported for label-free single-cell identification and analysis of AE fusion genes in clinical AML patients. Raman spectroscopy reflects the intrinsic vibration information of molecules in a label-free and non-destructive manner, and the fingerprint Raman spectrum of cells characterizes intracellular molecular types and relative concentration information, so as to realize the identification and molecular metabolism analysis of different kinds of cells. We collected the Raman spectra of bone marrow cells from clinically diagnosed AML M2 patients with and without the AE fusion gene. Through comparison of the average spectra and identification analysis based on multivariate statistical methods such as principal component analysis and linear discriminant analysis, the distinction between AE positive and negative sample cells in M2 AML patients was successfully achieved, and the single-cell identification accuracy was more than 90%. At the same time, the Raman spectra of the two types of cells were analyzed by the multivariate curve resolution alternating least squares decomposition method. It was found that the presence of the AE fusion gene may lead to the metabolic changes of lipid and nucleic acid in AML cells, which was consistent with the results of genomic and metabolomic multi-omics studies. The above results indicate that single-cell Raman spectroscopy has the potential for early identification of AE-positive AML.

Chlamydia psittaci infected cell studies by 4Pi Raman and atomic force microscopy

Chlamydia psittaci is an avian bacterial pathogen that can cause atypical pneumonia in humans via zoonotic transmission. It is a Gram-negative intracellular bacterium that proliferates inside membrane bound inclusions in the cytoplasm of living eukaryotic cells. The study of such cells with C. psittaci inside without destroying them poses a significant challenge. We demonstrated in this work the utility of a combined multitool approach to analyze such complex samples. Atomic force microscopy was applied to obtain high-resolution images of the surface of infected cells upon entrance of bacteria. Atomic force microscopy scans revealed the morphological changes of the cell membrane of Chlamydia infected cells such as changes in roughness of cell membrane and the presence of micro vesicles. 4Pi Raman microscopy was used to image and probe the molecular composition of intracellular bacteria inside intact cells. Information about the structure of the inclusion produced by C. psittaci was obtained and it was found to have a similar molecular fingerprint as that of an intracellular lipid droplet but with less proteins and unsaturated lipids. The presented approach demonstrates complementarity of various microscopy-based approaches and might be useful for characterization of intracellular bacteria.

The impact of repeated temperature cycling on cryopreserved human iPSC viability stems from cytochrome redox state changes

Human induced pluripotent stem cells (hiPSCs) are an attractive cell source for regenerative medicine. For its widespread use as a starting material, a robust storage and distribution system in the frozen state is necessary. For this system, managing transient warming during storage and transport is essential, but how transient warming affects cells and the mechanisms involved are not yet fully understood. This study examined the influence of temperature cyclings (from -80°C to -150°C) on cryopreserved hiPSCs using a custom-made cryo Raman microscope, flow cytometry, and performance indices to assess viability. Raman spectroscopy indicated the disappearance of mitochondrial cytochrome signals after thawing. A reduction in the mitochondrial membrane potential was detected using flow cytometry. The performance indices indicated a decrease in attachment efficiency with an increase in the number of temperature cycles. This decrease was observed in the temperature cycle range above the glass transition temperature of the cryoprotectant. Raman observations captured an increase in the signal intensity of intracellular dimethyl sulfoxide (DMSO) during temperature cycles. Based on these results, we proposed a schematic illustration for cellular responses to temperature fluctuations, suggesting that temperature fluctuations above the glass-transition temperature trigger the movement of DMSO, leading to cytochrome c oxidation, mitochondrial damage, and caspase-mediated cell death. This enhances our understanding of the key events during cryopreservation and informs the development of quality control strategies for hiPSC storage and transport.

Inline Raman Spectroscopy Provides Versatile Molecular Monitoring for Platelet Extracellular Vesicle Purification with Anion-Exchange Chromatography

Extracellular vesicles (EVs) are relatively recently discovered biological nanoparticles that mediate intercellular communication. The development of new methods for the isolation and characterization of EVs is crucial to support further studies on these small and structurally heterogenous vesicles. New scalable production methods are also needed to meet the needs of future therapeutic applications. A reliable inline detection method for the EV manufacturing process is needed to ensure reproducibility and to identify any possible variations in real time. Here, we demonstrate the use of an inline Raman detector in conjunction with anion exchange chromatography for the isolation of EVs from human platelets. Anion-exchange chromatography can be easily coupled with multiple inline detectors and provides an alternative to size-based methods for separating EVs from similar-sized impurities, such as lipoprotein particles. Raman spectroscopy enabled us to identify functional groups in EV samples and trace EVs and impurities in different stages of the process. Our results show a notable separation of impurities from the EVs during anion-exchange chromatography and demonstrate the power of inline Raman spectroscopy. Compared to conventional EV analysis methods, the inline Raman approach does not require hands-on work and can provide detailed, real-time information about the sample and the purification process.

In situ single-droplet analysis of emulsified fat using confocal Raman microscopy: insights into crystal network formation within spatial resolution

Fat crystallization is one of the predominant factors influencing the structure and properties of fat-containing emulsions. In the present study, the role of emulsifiers on fat crystallization dynamics within droplet multiphase systems was evaluated via single-droplet analysis, taking advantage of the non-destructive properties of confocal Raman microscopy. Palm oil droplets dispersed in water were used as a model system, due to palm oil's well-known crystallization properties. Emulsion droplets of the same size were generated using two different emulsifiers (Whey Protein Isolate and Tween 60), at various concentrations. Fast and slow cooling treatments were applied to affect fat crystallisation and network formation as well as droplet morphology, and crystallization dynamics. Raman imaging analysis demonstrated that the chemical structure and concentration of the emulsifier significantly influenced both crystal nucleation within the droplets, as well as the spatial distribution and morphology of the fat crystal network. Additionally, analysis of the spectra of the crystallized phase provided essential information regarding the impact of the emulsifiers on the microstructure, degree of structural order, and structural arrangements of the fat crystal networks. Furthermore, by performing single droplet analysis during cooling it was possible to observe shape distortions in Tween 60 stabilized droplets, as a consequence of the formation of a three-dimensional network of fat crystals that strongly interacted with the interface. On the other hand, the droplets retained their shape when whey proteins were absorbed at the interface. Confocal Raman microscopy, in combination with polarized light microscopy, is, therefore, a well-suited tool for in situ, single-droplet analysis of emulsified oil systems, providing essential information about emulsified fat crystallization dynamics, contributing to better understanding and designing products with enhanced structure and function.

Multi-Wavelength Raman Differentiation of Malignant Skin Neoplasms

Raman microspectroscopy has become an effective method for analyzing the molecular appearance of biomarkers in skin tissue. For the first time, we acquired in vitro Raman spectra of healthy and malignant skin tissues, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), at 532 and 785 nm laser excitation wavelengths in the wavenumber ranges of 900-1800 cm-1 and 2800-3100 cm-1 and analyzed them to find spectral features for differentiation between the three classes of the samples. The intensity ratios of the bands at 1268, 1336, and 1445 cm-1 appeared to be the most reliable criteria for the three-class differentiation at 532 nm excitation, whereas the bands from the higher wavenumber region (2850, 2880, and 2930 cm-1) were a robust measure of the increased protein/lipid ratio in the tumors at both excitation wavelengths. Selecting ratios of the three bands from the merged (532 + 785) dataset made it possible to increase the accuracy to 87% for the three classes and reach the specificities for BCC + SCC equal to 87% and 81% for the sensitivities of 95% and 99%, respectively. Development of multi-wavelength excitation Raman spectroscopic techniques provides a versatile non-invasive tool for research of the processes in malignant skin tumors, as well as other forms of cancer.

Toward noncontact macroscopic imaging of multiple cancers using multi-spectral inelastic scattering detection

Here we introduce a Raman spectroscopy approach combining multi-spectral imaging and a new fluorescence background subtraction technique to image individual Raman peaks in less than 5 seconds over a square field-of-view of 1-centimeter sides with 350 micrometers resolution. First, human data is presented supporting the feasibility of achieving cancer detection with high sensitivity and specificity - in brain, breast, lung, and ovarian/endometrium tissue - using no more than three biochemically interpretable biomarkers associated with the inelastic scattering signal from specific Raman peaks. Second, a proof-of-principle study in biological tissue is presented demonstrating the feasibility of detecting a single Raman band - here the CH2/CH3 deformation bands from proteins and lipids - using a conventional multi-spectral imaging system in combination with the new background removal method. This study paves the way for the development of a new Raman imaging technique that is rapid, label-free, and wide field.

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.

Adipose-derived mesenchymal stem cells' adipogenesis chemistry analyzed by FTIR and Raman metrics

The full understanding of molecular mechanisms of cell differentiation requires a holistic view. Here we combine label-free FTIR and Raman hyperspectral imaging with data mining to detect the molecular cell composition enabling noninvasive monitoring of cell differentiation and identifying biochemical heterogeneity. Mouse adipose-derived mesenchymal stem cells (AD-MSCs) undergoing adipogenesis were followed by Raman and FT-IR imaging, Oil Red, and immunofluorescence. A workflow of the data analysis (IRRSmetrics4stem) was designed to identify spectral predictors of adipogenesis and test machine-learning (ML) methods (hierarchical clustering, PCA, PLSR) for the control of the AD-MSCs differentiation degree. IRRSmetrics4stem provided insights into the chemism of adipogenesis. With single-cell tracking, we established IRRS metrics for lipids, proteins, and DNA variations during AD-MSCs differentiation. The over 90% predictive efficiency of the selected ML methods proved the high sensitivity of the IRRS metrics. Importantly, the IRRS metrics unequivocally recognize a switch from proliferation to differentiation. This study introduced a new bioassay identifying molecular markers indicating molecular transformations and delivering rapid and machine learning-based monitoring of adipogenesis that can be relevant to other differentiation processes. Thus, we introduce a novel, rapid, machine learning-based bioassay to identify molecular markers of adipogenesis. It can be relevant to identification of differentiation-related molecular processes in other cell types, and beyond the cell differentiation including progression of different cellular pathophysiologies reconstituted in vitro.

Specific discrimination of pathogenic bacteria causing septic arthritis using Raman spectroscopy: In-vitro study

In this study we performed preliminary experiments using Raman spectroscopy as an evolving technology in biofluid and microbial characterization, to explore its potential for rapid diagnosis of pathogenic bacteria in an in-vitro synovial fluid infection model. Normal human synovial fluids samples were collected from patients undergoing knee surgery and the three most common pathogenic bacteria introduced in-vitro into the samples. The bacterial growth was systematically monitored using a Raman spectroscopy. Multivariate regression analysis of acquired spectra showed bacterial characteristic Raman bands related to bacterial cell membranes and DNA structures to increase continuously as the incubation period was increased. Spectra signature recorded from cultured synovial fluid samples showed a significant loss in synovial quality and protein morphology over time compared to control samples. In this study, Raman spectroscopy shows promise for rapid pathogenic bacteria identification in synovial fluid. Marker peaks distinguished inoculated bacteria, while chemical changes reveal infection dynamics.

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.