Nonresonant Raman imaging of protein distribution in single human cells

Raman spectroscopy of lymphocytes from patients with the Epstein-Barr virus infection

In this study, Raman spectroscopy is applied to trace lymphocytes activation following contact with the Epstein-Barr virus (EBV) of the herpesvirus family. The biomarker of cell activation is found to be the 520 cm-1 band, indicating formation of immunoglobulins. The blood samples are obtained from patients diagnosed with infectious mononucleosis and treated at the University Hospital in Kraków. The lymphocytes' Raman spectra are collected using a mapping technique, exciting samples with a 514.5 nm line of Ar + laser. Measurements are performed on the 1st, 4th, 6th, 12th and 30th day of hospitalization, until the patient has recovered. The highest intensity of the immunoglobulin marker is observed on the 4th day of hospitalization, while the results of the blood count of patients show the greatest increase in the number of lymphocytes at the beginning of hospitalization. No activated lymphocytes were observed in the blood of healthy volunteers. Some information is provided by the evaluation of B-cell activation by estimating the activated areas in the cells, which are determined by the presence of the Ig marker. The 900 cm-1 band and band around 1450 cm-1 are also analyzed as markers of the presence of the latent membrane protein, LMP2A (and 2B), of the EBV viral protein. The anomalous degree of depolarization observed in B-cells in the course of EBV infection appears to be due to the influence of a virus protein, disrupting BCR signal transduction.

Stable SERS Detection of Lactobacillus fermentum Using Optical Tweezers in a Microfluidic Environment

Rapid identification of fermented lactic acid bacteria has long been a challenge in the brewing industry. This study combined label-free surface-enhanced Raman scattering (SERS) and optical tweezer technology to construct a test platform within a microfluidic environment. Six kinds of lactic acid bacteria common in industry were tested to prove the stability of the SERS spectra. The results demonstrated that the utilization of optical tweezers to securely hold the bacteria significantly enhanced the stability of the SERS spectra. Furthermore, SVM and XGBoost machine learning algorithms were utilized to analyze the obtained Raman spectra for identification, and the identification accuracies exceeded 95% for all tested lactic acid bacteria. The findings of this study highlight the crucial role of optical tweezers in improving the stability of SERS spectra by capturing bacteria in a microfluidic environment, prove that this technology could be used in the rapid identification of lactic acid bacteria, and show great significance in expanding the applicability of the SERS technique for other bacterial testing purposes.

Single-cell phenotypes revealed as a key biomarker in bacterial-fungal interactions: a case study of Staphylococcus and Malassezia

IMPORTANCE

Evaluating bacterial-fungal interactions is important for understanding ecological functions in a natural habitat. Many studies have defined bacterial-fungal interactions according to changes in growth rates when co-cultivated. However, the current literature lacks detailed studies on phenotypic changes in single cells associated with transcriptomic profiles to understand the bacterial-fungal interactions. In our study, we measured the single-cell phenotypes of bacteria co-cultivated with fungi using Raman spectroscopy with its transcriptomic profiles and determined the consequence of these interactions in detail. This rapid and reliable phenotyping approach has the potential to provide new insights regarding bacterial-fungal interactions.

Harnessing the power of Raman spectroscopic imaging for ophthalmology

Eye diseases can cause great inconvenience to people's daily life; therefore, it is necessary to study the causes of ocular diseases and related physiological processes. Raman spectroscopic imaging (RSI) is a non-destructive, non-contact detection technique with the advantages of label-free, non-invasive and highly specific. Compared with other mature imaging technologies, RSI can provide real-time molecular information and high-resolution imaging at relatively low cost, making it very suitable for quantitative detection of biological molecules. RSI can reflect the overall situation of the sample, revealing the content distribution of the same substance in different areas of the sample. This review focuses on the recent advances in ophthalmology, with particular emphasis on the powerful use of RSI techniques, as well as its combination with other imaging techniques. Finally, we prospect the wider application and future potential of RSI approaches in ophthalmology.

Reliable cell preparation protocol for Raman imaging to effectively differentiate normal leukocytes and leukemic blasts

Leukemias are a remarkably diverse group of malignancies originating from abnormal progenitor cells in the bone marrow. Leukemia subtypes are classified according to the cell type that has undergone neoplastic transformation using demanding and time-consuming methods. Alternative is Raman imaging that can be used both for living and fixed cells. However, considering the diversity of leukemic cell types and normal leukocytes, and the availability of different sample preparation protocols, the main objective of this work was to verify them for leukemia and normal blood cell samples for Raman imaging. The effect of glutaraldehyde (GA) fixation in a concentration gradient (0.1 %, 0.5 %, and 2.5 % GA) on the molecular structure of T-cell acute lymphoblastic leukemia (T-ALL) and peripheral blood mononuclear cells (PBMCs) was verified. Changes in the secondary structure of proteins within cells were indicated as the main effect of fixation, as shown by an increase in band intensity at 1041 cm^-1, characteristic for in-plane δ(CH) deformation in phenylalanine (Phe). Different sensitivity of mononuclear and leukemic cells to fixation was observed. While the 0.1 % concentration of GA was too low to preserve the cell structure for an extended period of time, a GA concentration of 0.5 % seemed optimal for both normal and malignant cells. Chemical changes in PBMCs samples stored for 11 days were also investigated, which manifested in numerous modifications in the secondary structure of proteins and the content of nucleic acids. The impact of cell preculturing for 72 h after unbanking was verified, and there was no significant effect on the molecular structure of cells fixed with 0.5 % GA. In summary, the developed protocol for the preparation of samples for Raman imaging allows for the effective differentiation of fixed normal leukocytes from malignant T lymphoblasts.

Leveraging single-cell Raman spectroscopy and single-cell sorting for the detection and identification of yeast infections

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics.

Preparation of inhalable N-acetylcysteine-loaded magnetite chitosan microparticles for nitrate adsorption in particulate matter

Airborne particulate matter has been designated as a class 1 carcinogen by the World Health Organization. Nitrate is a toxic substance that accounts for a large proportion of particulate matter, and nitrate toxicity has long been reported. In this study, we aimed to optimize the adsorption and removal of particulate matter containing nitrate for effective elimination by the lungs. To this end, particles were designed to optimize the inhalation and removal efficiencies. These particles were prepared as chitosan-based particles containing N-acetylcysteine by using emulsion diffusion methods. Chitosan adsorbs nitrate, while N-acetylcysteine dissolves mucus. This removal mechanism has been found to occur in various in vitro models that mimic respiratory environments and in vivo models. In particular, the removal of exogenous substances, such as particulate matter, by the motility of respiratory cilia through mucolytic effect was investigated. This new approach for the adsorption and elimination of toxic substances entering the lungs represents an alternative defense mechanism against exposure to nitrates from air pollution.

Stain-free Gram staining classification of pathogens via single-cell Raman spectroscopy combined with machine learning

Gram staining (GS) is one of the routine microbiological operations to classify bacteria based on the cell wall structure. Accurate GS classification of pathogens is of great significance since it helps correct administration of antimicrobial treatment. The laborious procedure and low sensitivity results related to conventional GS have resulted in reluctance among clinicians. In this study, we integrate confocal Raman spectroscopy and machine learning techniques to distinguish Gram-negative (GN) or Gram-positive (GP) bacteria. A single-cell Raman database including seven most common clinical pathogens (three GP strains and four GN strains) was constructed. Machine learning algorithms including the support-vector machine (SVM), k-nearest neighbors' algorithm (k-NN), gradient boosting machine (GBM), linear discriminant analysis (LDA), and t-distributed stochastic neighbor embedding (t-SNE) were trained to achieve the binary classification for GS. With such a relatively small database, the SVM model achieved the highest accuracy of 98.1%. The molecular signatures of GN and GP embedded in their Raman fingerprints were identified with hierarchical cluster analysis (HCA). The results indicated that Raman peaks for peptidoglycan and teichoic acid were the most significant factors that contributed to accurate classification. The Raman machine learning approach could greatly enhance the diagnosis of pathogenic infections.

Dielectrophoresis-Based SERS Sensors for the Detection of Cancer Cells in Microfluidic Chips

The detection of freely circulating cancer cells (CTCs) is one of the greatest challenges of modern medical diagnostics. For several years, there has been increased attention on the use of surface-enhanced Raman spectroscopy (SERS) for the detection of CTCs. SERS is a non-destructive, accurate and precise technique, and the use of special SERS platforms even enables the amplification of weak signals from biological objects. In the current study, we demonstrate the unique arrangement of the SERS technique combined with the deposition of CTCs cells on the surface of the SERS platform via a dielectrophoretic effect. The appropriate frequencies of an alternating electric field and a selected shape of the electric field can result in the efficient deposition of CTCs on the SERS platform. The geometry of the microfluidic chip, the type of the cancer cells and the positive dielectrophoretic phenomenon resulted in the trapping of CTCs on the surface of the SERS platform. We presented results for two type of breast cancer cells, MCF-7 and MDA-MB-231, deposited from the 0.1 PBS solution. The limit of detection (LOD) is 20 cells/mL, which reflects the clinical potential and usefulness of the developed approach. We also provide a proof-of-concept for these CTCs deposited on the SERS platform from blood plasma.

Bacterial Resuscitation from Starvation-Induced Dormancy Results in Phenotypic Diversity Coupled with Translational Activity Depending on Carbon Substrate Availability

Dormancy is a survival strategy of stressed bacteria inhabiting a various environment. Frequent dormant-active transitions owing to environmental changes play an important role in functional redundancy. However, a proper understanding of the phenotypic changes in bacteria during these transitions remains to be clarified. In this study, orthogonal approaches, such as electron microscopy, flow cytometry, and Raman spectroscopy, which can evaluate phenotypic heterogeneity at the single-cell level, were used to observe morphological and molecular phenotypic changes in resuscitated cells, and RNA sequencing (RNASeq) was used to determine the genetic characteristics associated with phenotypes. Within 12 h of the resuscitation process, morphological (cell size and shape) and physiological (growth and viability) characteristics as well as molecular phenotypes (cellular components) were found to be recovered to the extent that they were similar to those in active cells. The recovery rate and detailed phenotypic properties of the resuscitated cells differed significantly depending on the type or concentration of carbon sources. RNASeq analysis revealed that genes related to translation were significantly upregulated under all resuscitation conditions. The simpler the carbon source (e.g., glucose), the higher the expression of genes involved in cellular repair, and the more complex the carbon source (e.g., beef extract), the higher the expression of genes associated with increased energy production associated with cellular aerobic respiration. This study of phenotypic plasticity of resuscitated cells provides fundamental insight into understanding the adaptive fine-tuning of the microbiome in response to environmental changes and the functional redundancy resulting from phenotype heterogeneity.

Label-free differentiation of clinical E. coli and Klebsiella isolates with Raman spectroscopy

Raman spectroscopy is a promising spectroscopic technique for microbiological diagnostics. In routine diagnostic, the differentiation of pathogens of the Enterobacteriaceae family remain challenging. In this study, Raman spectroscopy was applied for the differentiation of 24 clinical E. coli, Klebsiella pneumoniae and Klebsiella oxytoca isolates. Spectra were collected with two spectroscopic approaches: UV-Resonance Raman spectroscopy (UVRR) and single-cell Raman microspectroscopy with 532 nm excitation. A description of the different biochemical profiles provided by the different excitation wavelengths was performed followed by machine-learning models for the classification at the genus and species levels. UVRR was shown to outperform 532 nm excitation, enabling correct classification at the genus level of 23/24 isolates. Furthermore, for the first time, Klebsiella species were correctly classified at the species level with 92% accuracy, classifying all three K. oxytoca isolates correctly. These findings should guide future applicative studies, increasing the scope of Raman spectroscopy's suitability for clinical applications.

In situ identification of environmental microorganisms with Raman spectroscopy

Microorganisms in natural environments are crucial in maintaining the material and energy cycle and the ecological balance of the environment. However, it is challenging to delineate environmental microbes' actual metabolic pathways and intraspecific heterogeneity because most microorganisms cannot be cultivated. Raman spectroscopy is a culture-independent technique that can collect molecular vibration profiles from cells. It can reveal the physiological and biochemical information at the single-cell level rapidly and non-destructively in situ. The first part of this review introduces the principles, advantages, progress, and analytical methods of Raman spectroscopy applied in environmental microbiology. The second part summarizes the applications of Raman spectroscopy combined with stable isotope probing (SIP), fluorescence in situ hybridization (FISH), Raman-activated cell sorting and genomic sequencing, and machine learning in microbiological studies. Finally, this review discusses expectations of Raman spectroscopy and future advances to be made in identifying microorganisms, especially for uncultured microorganisms.

Raman-Deuterium Isotope Probing and Metagenomics Reveal the Drought Tolerance of the Soil Microbiome and Its Promotion of Plant Growth

Drought has become a major agricultural threat leading crop yield loss. Although a few species of rhizobacteria have the ability to promote plant growth under drought, the drought tolerance of the soil microbiome and its relationship with the promotion of plant growth under drought are scarcely studied. This study aimed to develop a novel approach for assessing drought tolerance in agricultural land by quantitatively measuring microbial phenotypes using stable isotopes and Raman spectroscopy. Raman spectroscopy with deuterium isotope probing was used to identify the Raman signatures of drought effects from drought-tolerant bacteria. Counting drought-tolerant cells by applying these phenotypic properties to agricultural samples revealed that 0% to 52.2% of all measured single cells had drought-tolerant properties, depending on the soil sample. The proportions of drought-tolerant cells in each soil type showed similar tendencies to the numbers of revived pea plants cultivated under drought. The phenotype of the soil microbiome and plant behavior under drought conditions therefore appeared to be highly related. Studying metagenomics suggested that there was a reliable link between the phenotype and genotype of the soil microbiome that could explain mechanisms that promote plant growth in drought. In particular, the proportion of drought-tolerant cells was highly correlated with genes encoding phytohormone production, including tryptophan synthase and isopentenyl-diphosphate delta-isomerase; these enzymes are known to alleviate drought stress. Raman spectroscopy with deuterium isotope probing shows high potential as an alternative technology for quantitatively assessing drought tolerance through phenotypic analysis of the soil microbiome. IMPORTANCE Soil microbiome has played a critical role in the plant survival during drought. However, the drought tolerance of soil microbiome and its ability to promote plant growth under drought is still scarcely studied. In this study, we identified the Raman signature (i.e., phenotype) of drought effects from drought-tolerant bacteria in agricultural soil samples using Raman-deuterium isotope probing (Raman-DIP). Moreover, the number of drought-tolerant cells measured by Raman-DIP was highly related to the survival rate of plant cultivation under drought and the abundance of genes encoding phytohormone production alleviating drought stress in plant. These results suggest Raman-DIP is a promising technology for measuring drought tolerance of soil microbiome. This result give us important insight into further studies of a reliable link between phenotype and genotype of soil microbiome for future plant-bacteria interaction research.

Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy

In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli. Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health.

Raman spectroscopy for the differentiation of Enterobacteriaceae: a comparison of two methods

A comprehensive dataset of bacteria of the family Enterobacteriaceae was collected and measured with Raman spectroscopy. Fiber-probe based Raman spectroscopy enabled classification with 100% accuracy and remained robust with a validation dataset.

Correlation and Difference Between Raman Spectral Characteristic and Feature Evaluation for Leukocytes and Tumor Cells

Tumor detection supported by Raman spectroscopy is becoming increasingly popular, yet the relevance of spectral variation and feature selection retains unclear. Here we determined the correlation and difference between spectral characteristic and feature evaluation for leukocytes and tumor cells. Some peaks were found to show noticeable spectral differences, and their intensity distributions were investigated, finding using log-normal distribution to describe Raman intensity pattern may be more appropriate. Further the importance of all Raman features was calculated, where some other peak features occupied the top status. By surveying the intensity variation and feature evaluation for those peaks, we concluded the peak with the highest importance does not correspond to the peak location with the most noticeable intensity difference in spectra. Moreover, the peak intensity ratio of I₁₅₁₇/I₇₁₉ associated with protein to nucleic acid level presented the maximum separation, thus, it can be recognized as a special indicator to develop an alternative cancer detection. It is inspiring to introduce advanced statistical models into bio-spectroscopic fields but those intrinsic spectral variations rather than classification performance should be valued. Our explorations can provide possibilities to reveal the essences within tumor carcinogenesis based on Raman spectroscopy, further overwhelming the obstacles during the translation into clinical applications.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Targeting acute myeloid leukemia cells by CD33 receptor-specific MoS2-based nanoconjugates

Acute myeloid leukemia (AML) is a highly aggressive type of cancer caused by the uncontrolled proliferation of undifferentiated myeloblasts, affecting the bone marrow and blood. Systemic chemotherapy is considered the primary treatment strategy; unfortunately, healthy cells are also affected to a large extent, leading to severe side effects of this treatment. Targeted drug therapies are becoming increasingly popular in modern medicine, as they bypass normal tissues and cells. Two-dimensional MoS₂-based nanomaterials have attracted attention in the biomedical field as promising agents for cancer diagnosis and therapy. Cancer cells typically (over)express distinctive cytoplasmic membrane-anchored or -spanning protein-based structures (e.g., receptors, enzymes) that distinguish them from healthy, non-cancerous cells. Targeting cancer cells via tumor-specific markers using MoS₂-based nanocarriers loaded with labels or drugs can significantly improve specificity and reduce side effects of such treatment. SKM-1 is an established AML cell line that has been employed in various bio-research applications. However, to date, it has not been used as the subject of studies on selective cancer targeting by inorganic nanomaterials. Here, we demonstrate an efficient targeting of AML cells using MoS₂nanoflakes prepared by a facile exfoliation route and functionalized with anti-CD33 antibody that binds to CD33 receptors expressed by SKM-1 cells. Microscopic analyses by confocal laser scanning microscopy supplemented by label-free confocal Raman microscopy proved that (anti-CD33)-MoS₂conjugates were present on the cell surface and within SKM-1 cells, presumably having been internalized via CD33-mediated endocytosis. Furthermore, the cellular uptake of SKM-1 specific (anti-CD33)-MoS₂conjugates assessed by flow cytometry analysis was significantly higher compared with the cellular uptake of SKM-1 nonspecific (anti-GPC3)-MoS₂conjugates. Our results indicate the importance of appropriate functionalization of MoS₂nanomaterials by tumor-recognizing elements that significantly increase their specificity and hence suggest the utilization of MoS₂-based nanomaterials in the diagnosis and therapy of AML.

In vitro Label Free Raman Microspectroscopic Analysis to Monitor the Uptake, Fate and Impacts of Nanoparticle Based Materials

The continued emergence of nanoscale materials for nanoparticle-based therapy, sensing and imaging, as well as their more general adoption in a broad range of industrial applications, has placed increasing demands on the ability to assess their interactions and impacts at a cellular and subcellular level, both in terms of potentially beneficial and detrimental effects. Notably, however, many such materials have been shown to interfere with conventional in vitro cellular assays that record only a single colorimetric end-point, challenging the ability to rapidly screen cytological responses. As an alternative, Raman microspectroscopy can spatially profile the biochemical content of cells, and any changes to it as a result of exogenous agents, such as toxicants or therapeutic agents, in a label free manner. In the confocal mode, analysis can be performed at a subcellular level. The technique has been employed to confirm the cellular uptake and subcellular localization of polystyrene nanoparticles (PSNPs), graphene and molybdenum disulfide micro/nano plates (MoS₂), based on their respective characteristic spectroscopic signatures. In the case of PSNPs it was further employed to identify their local subcellular environment in endosomes, lysosomes and endoplasmic reticulum, while for MoS₂ particles, it was employed to monitor subcellular degradation as a function of time. For amine functionalized PSNPs, the potential of Raman microspectroscopy to quantitatively characterize the dose and time dependent toxic responses has been explored, in a number of cell lines. Comparing the responses to those of poly (amidoamine) nanoscale polymeric dendrimers, differentiation of apoptotic and necrotic pathways based on the cellular spectroscopic responses was demonstrated. Drawing in particular from the experience of the authors, this paper details the progress to date in the development of applications of Raman microspectroscopy for in vitro, label free analysis of the uptake, fate and impacts of nanoparticle based materials, in vitro, and the prospects for the development of a routine, label free high content spectroscopic analysis technique.

High accuracy detection of malignant pleural effusion based on label-free surface-enhanced Raman spectroscopy and multivariate statistical analysis

The present study aims to diagnose malignant pleural effusion (MPE) based on the identification of distinctive Raman spectra bands. The tests on 83 pleural effusion (PE) samples including 32 benign PE (BPE) and 51 MPE were performed based on rapid and label-free surface-enhanced Raman spectroscopy (SERS). The TiO₂ photo-catalyzed Ag NPs were used as SERS substrate. And the SERS spectra of BPE and MPE were compared and diagnosed through orthogonal partial least squares discriminant analysis (OPLS-DA). The diagnosis results showed that the sensitivity and specificity can reach 92.2% and 93.8%, respectively, based on leave-one-out cross validation. And the area under curve values of MPE was 0.985. This study demonstrated an accurate way of combining Raman spectra of PE with OPLS-DA to identify MPE and BPE.

Silicon Nitride: A Bioceramic with a Gift

In the closing decades of the 20th century, silicon nitride (Si₃N₄) was extensively developed for high-temperature gas turbine applications. Technologists attempted to take advantage of its superior thermal and mechanical properties to improve engine reliability and fuel economy. Yet, this promise was never realized in spite of the worldwide research, which was conducted at that time. Notwithstanding this disappointment, its use in medical applications in the early 21st century has been an unexpected gift. While retaining all of its engineered mechanical properties, it is now recognized for its peculiar surface chemistry. When immersed in an aqueous environment, the slow elution of silicon and nitrogen from its surface enhances healing of soft and osseous tissue, inhibits bacterial proliferation, and eradicates viruses. These benefits permit it to be used in a wide array of different disciplines inside and outside of the human body including orthopedics, dentistry, virology, agronomy, and environmental remediation. Given the global public health threat posed by mutating viruses and bacteria, silicon nitride offers a valid and straightforward alternative approach to fighting these pathogens. However, there is a conundrum behind these recent discoveries: How can this unique bioceramic be both friendly to mammalian cells while concurrently lysing invasive pathogens? This unparalleled characteristic can be explained by the pH-dependent kinetics of two ammonia species-NH₄⁺ and NH₃-both of which are leached from the wet Si₃N₄ surface.

Detection of circulating tumor cells in blood by shell-isolated nanoparticle - enhanced Raman spectroscopy (SHINERS) in microfluidic device

Isolation and detection of circulating tumor cells (CTCs) from human blood plays an important role in non- invasive screening of cancer evolution and in predictive therapeutic treatment. Here, we present the novel tool utilizing: (i) the microfluidic device with (ii) incorporated photovoltaic (PV) based SERS-active platform, and (iii) shell-isolated nanoparticles (SHINs) for simultaneous separation and label-free analysis of circulating tumour cells CTCs in the blood specimens with high specificity and sensitivity. The proposed microfluidic chip enables the efficient size - based inertial separation of circulating cancer cells from the whole blood samples. The SERS-active platform incorporated into the microfluidic device permits the label-free detection and identification of isolated cells through the insight into their molecular and biochemical structure. Additionally, the silver nanoparticles coated with an ultrathin shell of silica (Ag@SiO2) was used to improve the detection accuracy and sensitivity of analysed tumor cells via taking advantages of shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS). The empirical analysis of SHINERS spectra revealed that there are some differences among studied (HeLa), renal cell carcinoma (Caki-1), and blood cells. Unique SHINERS features and differences in bands intensities between healthy and cancer cells might be associated with the variations in the quantity and quality of molecules such as lipid, protein, and DNA or their structure during the metastasis cancer formation. To demonstrate the statistical efficiency of the developed method and improve the differentiation for circulating tumors cells detection the principal component analysis (PCA) has been performed for all SHINERS data. PCA method has been applied to recognize the most significant differences in SHINERS data among the three analyzed cells: Caki-1, HeLa, and blood cells. The proposed approach challenges the current multi-steps CTCs detection methods in the terms of simplicity, sensitivity, invasiveness, destructivity, time and cost of analysis, and also prevents the defragmentation/damage of tumor cells and thus leads to improving the accuracy of analysis. The results of this research work show the potential of developed SERS based tool for the separation of tumor cells from whole blood samples in a simple and minimally invasive manner, their detection and molecular characterization using one single technology.

Detection of Circulating Tumor Cells Using Membrane-Based SERS Platform: A New Diagnostic Approach for 'Liquid Biopsy'

The detection and monitoring of circulating tumor cells (CTCs) in blood is an important strategy for early cancer evidence, analysis, monitoring of therapeutic response, and optimization of cancer therapy treatments. In this work, tailor-made membranes (MBSP) for surface-enhanced Raman spectroscopy (SERS)-based analysis, which permitted the separation and enrichment of CTCs from blood samples, were developed. A thin layer of SERS-active metals deposited on polymer mat enhanced the Raman signals of CTCs and provided further insight into CTCs molecular and biochemical composition. The SERS spectra of all studied cells—prostate cancer (PC3), cervical carcinoma (HeLa), and leucocytes as an example of healthy (normal) cell—revealed significant differences in both the band positions and/or their relative intensities. The multivariate statistical technique based on principal component analysis (PCA) was applied to identify the most significant differences (marker bands) in SERS data among the analyzed cells and to perform quantitative analysis of SERS data. Based on a developed PCA algorithm, the studied cell types were classified with an accuracy of 95% in 2D PCA to 98% in 3D PCA. These results clearly indicate the diagnostic efficiency for the discrimination between cancer and normal cells. In our approach, we exploited the one-step technology that exceeds most of the multi-stage CTCs analysis methods used and enables simultaneous filtration, enrichment, and identification of the tumor cells from blood specimens.

Intuitive Label-Free SERS Detection of Bacteria Using Aptamer-Based in Situ Silver Nanoparticles Synthesis

The characteristic of an ideal bacteria-detection method should have high sensitivity and specificity, be easy to operate, and not have a time-consuming culture process. In this study, we report a new bacteria-detection strategy that can recognize bacteria quickly and directly by surface-enhanced Raman scattering (SERS) with the formation of well-defined bacteria-aptamer@AgNPs. SERS signals generated by bacteria-aptamer@AgNPs exhibited a linear dependence on bacteria (R² = 0.9671) concentration ranging from 10¹ to 10⁷ cfu/mL. The detection limit is sensitive down to 1.5 cfu/mL. Meanwhile, the bacteria SERS signal was dramatically enhanced by its specifically recognized aptamer, and the bacteria could be identified directly and visually through the SERS spectrum. This strategy eliminates the puzzling data analysis of previous studies and offers significant advantages over existing approaches, getting a critical step toward the creation of SERS-based biochips for rapid in situ bacteria detection in mixture samples.

The use of a genetically encoded molecular crowding sensor in various biological phenomena

We evaluated usability of a previously developed genetically encoded molecular crowding sensor in various biological phenomena. Molecular crowding refers to intracellular regions that are occupied more by proteins and nucleotides than by water molecules and is thought to have a strong effect on protein function. To evaluate intracellular molecular crowding, usually the diffusion coefficient of a probe is used because it is related to mobility of the surrounding molecular crowding agents. Recently, genetically encoded molecular crowding sensors based on Förster resonance energy transfer were reported. In the present study, to evaluate the usability of a genetically encoded molecular crowding sensor, molecular crowding was monitored during several biological events. Changes in molecular crowding during stem cell differentiation, cell division, and focal adhesion development and difference in molecular crowding in filopodia locations were examined. The results show usefulness of the genetically encoded molecular crowding sensor for understanding the biological phenomena relating to molecular crowding.

Accurate and Rapid Differentiation of Acinetobacter baumannii Strains by Raman Spectroscopy: a Comparative Study

In recent years, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become the standard for routine bacterial species identification due to its rapidity and low costs for consumables compared to those of traditional DNA-based methods. However, it has been observed that strains of some bacterial species, such as Acinetobacter baumannii strains, cannot be reliably identified using mass spectrometry (MS). Raman spectroscopy is a rapid technique, as fast as MALDI-TOF, and has been shown to accurately identify bacterial strains and species. In this study, we compared hierarchical clustering results for MS, genomic, and antimicrobial susceptibility test data to hierarchical clustering results from Raman spectroscopic data for 31 A. baumannii clinical isolates labeled according to their pulsed-field gel electrophoresis data for strain differentiation. In addition to performing hierarchical cluster analysis (HCA), multiple chemometric methods of analysis, including principal-component analysis (PCA) and partial least-squares discriminant analysis (PLSDA), were performed on the MS and Raman spectral data, along with a variety of spectral preprocessing techniques for best discriminative results. Finally, simple HCA algorithms were performed on all of the data sets to explore the relationships between, and natural groupings of, the strains and to compare results for the four data sets. To obtain numerical comparison values of the clustering results, the external cluster evaluation criteria of the Rand index of the HCA dendrograms were calculated. With a Rand index value of 0.88, Raman spectroscopy outperformed the other techniques, including MS (with a Rand index value of 0.58).

A machine learning framework to analyze hyperspectral stimulated Raman scattering microscopy images of expressed human meibum

We develop and discuss a methodology for batch-level analysis of hyperspectral stimulated Raman scattering (hsSRS) data sets of human meibum in the CH-stretching vibrational range. The analysis consists of two steps. The first step uses a training set (n=19) to determine chemically meaningful reference spectra that jointly constitute a basis set for the sample. This procedure makes use of batch-level vertex component analysis (VCA), followed by unsupervised k-means clustering to express the data set in terms of spectra that represent lipid and protein mixtures in changing proportions. The second step uses a random forest classifier to rapidly classify hsSRS stacks in terms of the pre-determined basis set. The overall procedure allows a rapid quantitative analysis of large hsSRS data sets, enabling a direct comparison among samples using a single set of reference spectra. We apply this procedure to assess 50 specimens of expressed human meibum, rich in both protein and lipid, and show that the batch-level analysis reveals marked variation among samples that potentially correlate with meibum health quality.

Structural Changes of Amyloid Beta in Hippocampus of Rats Exposed to Ozone: A Raman Spectroscopy Study

The aim of this work was to study the effect of oxidative stress on the structural changes of the secondary peptide structure of amyloid beta 1-42 (Aβ 1-42), in the dentate gyrus of hippocampus of rats exposed to low doses of ozone. The animals were exposed to ozone-free air (control group) and 0.25 ppm ozone during 7, 15, 30, 60, and 90 days, respectively. The samples were studied by: (1) Raman spectroscopy to detect the global conformational changes in peptides with α-helix and β-sheet secondary structure, following the deconvolution profile of the amide I band; and (2) immunohistochemistry against Aβ 1-42. The results of the deconvolutions of the amide I band indicate that, ozone exposure causes a progressively decrease in the abundance percentage of α-helix secondary structure. Furthermore, the β-sheet secondary structure increases its abundance percentage. After 60 days of ozone exposure, the β-sheet band is identified in a similar wavenumber of the Aβ 1-42 peptide standard. Immunohistochemistry assays show an increase of Aβ 1-42 immunoreactivity, coinciding with the conformational changes observed in the Raman spectroscopy of Aβ 1-42 at 60 and 90 days. In conclusion, oxidative stress produces changes in the folding process of amyloid beta peptide structure in the dentate gyrus, leading to its conformational change in a final β-sheet structure. This is associated to an increase in Aβ 1-42 expression, similar to the one that happens in the brain of Alzheimer's Disease (AD) patients.

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

Plasmonic nanocone arrays for rapid and detailed cell lysate surface enhanced Raman spectroscopy analysis

A plasmonic nanocone SERS substrate with a uniform enhancement factor is developed and applied for cell lysate studies.

Detection of Genomic DNA Damage from Radiated Nasopharyngeal Carcinoma Cells Using Surface-Enhanced Raman Spectroscopy (SERS)

Structural changes and chemical modifications in DNA during interactions with X-ray radiation are still not clear within 48 h of incubation. We investigate genomic DNA from the radiated CNE2 cell line within 48 h of incubation using surface-enhanced Raman spectroscopy (SERS). Multivariate methods including principal component analysis (PCA) and random forest are proposed to explore the statistical significance before and after radiation. Our results show that intensities of several bands change after radiation, which indicates backbone damage and base-unstacking. Biological effects from DNA damage repairing process may be simultaneously stimulated and different from incubation time. Under doses of 10 Gy (with 24 and 48 h of incubation) and 20 Gy (with 48 h of incubation), the relative contents of C against T and A against G deviate obviously from the control level. Statistical results strengthen significantly the idea that modification in DNA bases is associated with the disruption of base-stacking in the DNA duplex. Our findings provide vital information for radiation-induced the DNA damage at the molecular level, which may provide insight into the effect and mechanism of anticarcinogens in tumor therapy.

Protein clustering in chemically stressed HeLa cells studied by infrared nanospectroscopy

Photo-Thermal Induced Resonance (PTIR) nanospectroscopy, tuned towards amide-I absorption, was used to study the distribution of proteic material in 34 different HeLa cells, of which 18 were chemically stressed by oxidative stress with Na₃AsO₃. The cell nucleus was found to provide a weaker amide-I signal than the surrounding cytoplasm, while the strongest PTIR signal comes from the perinuclear region. AFM topography shows that the cells exposed to oxidative stress undergo a volume reduction with respect to the control cells, through an accumulation of the proteic material around and above the nucleus. This is confirmed by the PTIR maps of the cytoplasm, where the pixels providing a high amide-I signal were identified with a space resolution of ∼300 × 300 nm. By analyzing their distribution with two different statistical procedures we found that the probability to find protein clusters smaller than 0.6 μm in the cytoplasm of stressed HeLa cells is higher by 35% than in the control cells. These results indicate that it is possible to study proteic clustering within single cells by label-free optical nanospectroscopy.

Redox State of Cytochromes in Frozen Yeast Cells Probed by Resonance Raman Spectroscopy

Cryopreservation is a well-established technique used for the long-term storage of biological materials whose biological activity is effectively stopped under low temperatures (suspended animation). Since most biological methods do not work in a low-temperature frozen environment, the mechanism and details of the depression of cellular activity in the frozen state remain largely uncharacterized. In this work, we propose, to our knowledge, a new approach to study the downregulation of the redox activity of cytochromes b and c in freezing yeast cells in a contactless, label-free manner. Our approach is based on cytochrome photobleaching effects observed in the resonance Raman spectra of live cells. Photoinduced and native redox reactions that contributed to the photobleaching rate were studied over a wide temperature range (from -173 to +25 °C). We found that ice formation influences both the rate of cytochrome redox reactions and the balance between the reduced and oxidized cytochromes. We demonstrate that the temperature dependence of native redox reaction rates can be well described by the thermal activation law with an apparent energy of 32.5 kJ/mol, showing that the redox reaction rate is ∼10(15) times slower at liquid nitrogen temperature than at room temperature.

Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy

The present study aims to identify distinctive Raman spectrum metabolic peaks to predict hepatocellular carcinoma (HCC). We performed a label-free, non-invasive surface-enhanced Raman spectroscopy (SERS) test on 230 serum samples including 47 HCC, 60 normal controls (NC), 68 breast cancer (BC) and 55 lung cancer (LC) by mixing Au@AgNRs with serum directly. Based on the observed SERS spectra, discriminative metabolites including tryptophan, phenylalanine, and etc. were found in HCC, when compared with BC, LC, and NC (P<0.05 in all). Common metabolites-proline, valine, adenine and thymine were found in HCC, BC and LC with compared to NC group (P<0.05). Importantly, Raman spectra of HCC serum biomarker AFP were firstly detected to analyze the HCC prominent peak. Orthogonal partial least squares discriminant analysis was adopted to assess the diagnostic accuracy; area under curve value of HCC is 0.991. This study provides new insights into the HCC metabolites detection through Raman spectroscopy.

Resonance Raman Probes for Organelle-Specific Labeling in Live Cells

Raman microspectroscopy provides for high-resolution non-invasive molecular analysis of biological samples and has a breakthrough potential for dissection of cellular molecular composition at a single organelle level. However, the potential of Raman microspectroscopy can be fully realized only when novel types of molecular probes distinguishable in the Raman spectroscopy modality are developed for labeling of specific cellular domains to guide spectrochemical spatial imaging. Here we report on the design of a next generation Raman probe, based on BlackBerry Quencher 650 compound, which provides unprecedentedly high signal intensity through the Resonance Raman (RR) enhancement mechanism. Remarkably, RR enhancement occurs with low-toxic red light, which is close to maximum transparency in the biological optical window. The utility of proposed RR probes was validated for targeting lysosomes in live cultured cells, which enabled identification and subsequent monitoring of dynamic changes in this organelle by Raman imaging.

Raman spectroscopy of endoscopic colonic biopsies from patients with ulcerative colitis to identify mucosal inflammation and healing

Raman spectroscopy was used to differentiate between mucosally healed (or quiescent) and inflamed colon tissue, as assessed endoscopically, in patients with ulcerative colitis. From the analysis of the Raman spectra of 60 biopsy tissue samples, clear differences were identified between the spectra of the quiescent and inflamed tissue. Three carotenoid peaks were found to be approximately twice as intense in the inflamed tissue. Two phospholipid peaks were found to be significantly lower in the inflamed tissue. Using multivariate statistical analysis, we show that these five peaks can be used to discriminate between endoscopically quiescent and inflamed tissue. We also correlated the Raman data with a histological assessment of the tissue. Four of the five peaks were found to be significantly different between the spectra of histologically healed (or quiescent) and histologically inflamed tissue. These findings indicate the ability of Raman spectroscopy to accurately classify colon tissue as either quiescent or inflamed, irrespective of whether an endoscopic or histological grading scheme is followed. We thus demonstrate that Raman spectroscopy could potentially be used as an early diagnosis tool for assessing the presence of mucosal healing or inflammation in patients with ulcerative colitis.

Raman spectroscopy: an evolving technique for live cell studies

One of the most exciting developments in Raman spectroscopy in the last decade has been its application to cells and tissues for diagnostic and pharmaceutical applications, and in particular its use in the analysis of cellular dynamics. Raman spectroscopy is rapidly advancing as a cell imaging method that overcomes many of the limitations of current techniques and is earning its place as a routine tool in cell biology. In this review we focus on important developments in Raman spectroscopy that have evolved into the exciting technique of live-cell Raman microscopy and highlight some of the most recent and significant applications to cell biology.

Dependence of fluorescent protein brightness on protein concentration in solution and enhancement of it

Fluorescent proteins have been widely used in biology because of their compatibility and varied applications in living specimens. Fluorescent proteins are often undesirably sensitive to intracellular conditions such as pH and ion concentration, generating considerable issues at times. However, harnessing these intrinsic sensitivities can help develop functional probes. In this study, we found that the fluorescence of yellow fluorescent protein (YFP) depends on the protein concentration in the solution and that this dependence can be enhanced by adding a glycine residue in to the YFP; we applied this finding to construct an intracellular protein-crowding sensor. A Förster resonance energy transfer (FRET) pair, involving a cyan fluorescent protein (CFP) insensitive to protein concentration and a glycine-inserted YFP, works as a genetically encoded probe to evaluate intracellular crowding. By measuring the fluorescence of the present FRET probe, we were able to detect dynamic changes in protein crowding in living cells.

Structured line illumination Raman microscopy

In the last couple of decades, the spatial resolution in optical microscopy has increased to unprecedented levels by exploiting the fluorescence properties of the probe. At about the same time, Raman imaging techniques have emerged as a way to image inherent chemical information in a sample without using fluorescent probes. However, in many applications, the achievable resolution is limited to about half the wavelength of excitation light. Here we report the use of structured illumination to increase the spatial resolution of label-free spontaneous Raman microscopy, generating highly detailed spatial contrast from the ensemble of molecular information in the sample. Using structured line illumination in slit-scanning Raman microscopy, we demonstrate a marked improvement in spatial resolution and show the applicability to a range of samples, including both biological and inorganic chemical component mapping. This technique is expected to contribute towards greater understanding of chemical component distributions in organic and inorganic materials.

Direct label-free measurement of the distribution of small molecular weight compound inside thick biological tissue using coherent Raman microspectroscopy

Distributions of small molecular weight (less than 300 Da) compounds inside biological tissue have been obscure because of the lack of appropriate methods to measure them. Although fluorescence techniques are widely used to characterise the localisation of large biomolecules, they cannot be easily applied to the cases with small molecule compounds. We used CARS spectroscopy to detect and identify a label-free small molecule compound. To facilitate detection in aqueous environment, we utilised time-resolved and phase-sensitive techniques to reduce non-resonant background generated from water. We applied this technique to detect small molecular weight compound, taurine, inside mouse cornea tissue immersed in taurine solution as an initial model experiment. We detected a Raman peak of taurine near wavenumber 1033 cm⁻¹ inside cornea and successfully characterised its depth profile in the tissue. Our CARS spectra measurement can be a promising method to measure and visualise the distribution of small bio-related compounds in biological background without using any labeling, paving the way for new cell biological analysis in various disciplines.

Raman microscopy for cellular investigations--From single cell imaging to drug carrier uptake visualization

Progress in advanced therapeutic concepts requires the development of appropriate carrier systems for intracellular drug delivery. Consequently, analysis of interaction between carriers, drugs and cells as well as their uptake and intracellular fate is a current focus of research interest. In this context, Raman spectroscopy recently became an emerging analytical technique, due to its non-destructive, chemically selective and label-free working principle. In this review, we briefly present the state-of-the-art technologies for cell visualization and drug internalization. Against this background, Raman microscopy is introduced as a versatile analytical technique. An overview of various Raman spectroscopy investigations in this field is given including interactions of cells with drug molecules, carrier systems and other nanomaterials. Further, Raman instrumentations and sample preparation methods are discussed. Finally, as the analytical limit is not reached yet, a future perspective for Raman microscopy in pharmaceutical and biomedical research on the single cell level is given.

The use of wavelength modulated Raman spectroscopy in label-free identification of T lymphocyte subsets, natural killer cells and dendritic cells

Determining the identity of cells of the immune system usually involves destructive fixation and chemical staining, or labeling with fluorescently labeled antibodies recognising specific cell surface markers. Completely label-free identification would be a significant advantage in conditions where untouched cells are a priority. We demonstrate here the use of Wavelength Modulated Raman Spectroscopy, to achieve label-free identification of purified, unfixed and untouched populations of major immune cell subsets isolated from healthy human donors. Using this technique we have been able to distinguish between CD4⁺ T lymphocytes, CD8⁺ T lymphocytes and CD56⁺ Natural Killer cells at specificities of up to 96%. Additionally, we have been able to distinguish between CD303⁺ plasmacytoid and CD1c⁺ myeloid dendritic cell subsets, the key initiator and regulatory cells of many immune responses. This demonstrates the ability to identify unperturbed cells of the immune system, and opens novel opportunities to analyse immunological systems and to develop fully label-free diagnostic technologies.

Applications of Raman micro-spectroscopy to stem cell technology: label-free molecular discrimination and monitoring cell differentiation

Stem cell therapy is widely acknowledged as a key medical technology of the 21st century which may provide treatments for many currently incurable diseases. These cells have an enormous potential for cell replacement therapies to cure diseases such as Parkinson's disease, diabetes and cardiovascular disorders, as well as in tissue engineering as a reliable cell source for providing grafts to replace and repair diseased tissues. Nevertheless, the progress in this field has been difficult in part because of lack of techniques that can measure non-invasively the molecular properties of cells. Such repeated measurements can be used to evaluate the culture conditions during differentiation, cell quality and phenotype heterogeneity of stem cell progeny. Raman spectroscopy is an optical technique based on inelastic scattering of laser photons by molecular vibrations of cellular molecules and can be used to provide chemical fingerprints of cells or organelles without fixation, lysis or use of labels and other contrast enhancing chemicals. Because differentiated cells are specialized to perform specific functions, these cells produce specific biochemicals that can be detected by Raman micro-spectroscopy. This mini-review paper describes applications of Raman micro-scpectroscopy to measure moleculare properties of stem cells during differentiation in-vitro. The paper focuses on time- and spatially-resolved Raman spectral measurements that allow repeated investigation of live stem cells in-vitro.