Micro-Raman spectroscopy study of blood samples from myocardial infarction patients

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review

Raman spectroscopy is a widely developing approach for noninvasive analysis that can provide information on chemical composition and molecular structure. High chemical specificity calls for developing different medical diagnostic applications based on Raman spectroscopy. This review focuses on the Raman-based techniques used in medical diagnostics and provides an overview of such techniques, possible areas of their application, and current limitations. We have reviewed recent studies proposing conventional Raman spectroscopy and surface-enhanced Raman spectroscopy for rapid measuring of specific biomarkers of such diseases as cardiovascular disease, cancer, neurogenerative disease, and coronavirus disease (COVID-19). As a result, we have discovered several most promising Raman-based applications to identify affected persons by detecting some significant spectral features. We have analyzed these approaches in terms of their potentially diagnostic power and highlighted the remaining challenges and limitations preventing their translation into clinical settings.

Understanding the role of membrane cholesterol upon Epstein Barr virus infection in astroglial cells

Background

EBV infection has long been postulated to trigger multiple sclerosis (MS) and anti-EBV antibodies showed a consistent presence in MS patients. Previous reports from our group have shown that the EBV infects different brain cells. Entry of the virus in neuronal cells is assisted by several host factors including membrane cholesterol. By using an inhibitor, methyl-β-cyclodextrin (MβCD), we evaluated the role of membrane cholesterol in EBV infection and pathogenesis.

Methodology

The membrane cholesterol depleted cells were infected with EBV and its latent genes expression were assessed. Further, EBV-mediated downstream signalling molecules namely STAT3, RIP, NF-kB and TNF-α levels was checked at protein level along with spatial (periphery and nucleus) and temporal changes in biomolecular fingerprints with Raman microspectroscopy (RS).

Results

Upon treatment with MβCD, lmp1 and lmp2a suggested significant downregulation compared to EBV infection. Downstream molecules like STAT3 and RIP, exhibited a decrease in protein levels temporally upon exposure to MβCD while NF-kB levels were found to be increased. Further, the intensity of the Raman spectra exhibited an increase in triglycerides and fatty acids in the cytoplasm of EBV-infected LN-229 cells compared to MβCD+EBV. Likewise, the Raman peak width of cholesterol, lipid and fatty acids were found to be reduced in EBV-infected samples indicates elevation in the cholesterol specific moieties. In contrast, an opposite pattern was observed in the nucleus. Moreover, the ingenuity pathway analysis revealed protein molecules such as VLDLR, MBP and APP that are associated with altered profile of cholesterol, fatty acids and triglycerides with infection-related CNS disorders.

Conclusion

Taken together, our results underline the important role of membrane cholesterol over EBV entry/pathogenesis in astroglia cells which further trigger/exacerbate virus-associated neuropathologies. These results likely to aid into the prognosis of neurological disease like MS.

Vibrational spectroscopy identifies myocardial chemical modifications in heart failure with preserved ejection fraction

BACKGROUND

Vibrational spectroscopy can be a valuable tool to monitor the markers of cardiovascular diseases. In the present work, we explored the vibrational spectroscopy characteristics of the cardiac tissue in an experimental model of heart failure with preserved ejection fraction (HFpEF). The goal was to detect early cardiac chemical modifications associated with the development of HFpEF.

METHODS

We used the Fourier-transform infrared (FTIR) and Raman micro-spectroscopic techniques to provide complementary and objective tools for the histological assessment of heart tissues from an animal model of HFpEF. A new sampling technique was adopted (tissue print on a CaF2 disk) to characterize the extracellular matrix.

RESULTS

Several spectroscopic markers (lipids, carbohydrates, and glutamate bands) were recognized in the cardiac ventricles due to the comorbidities associated with the pathology, such as obesity and diabetes. Besides, abnormal collagen cross-linking and a decrease in tryptophan content were observed and related to the stiffening of ventricles and to the inflammatory state which is a favourable condition for HFpEF.

CONCLUSIONS

By the analyses of tissues and tissue prints, FTIR and Raman techniques were shown to be highly sensitive and selective in detecting changes in the chemistry of the heart in experimental HFpEF and its related comorbidities. Vibrational spectroscopy is a new approach that can identify novel biomarkers for early detection of HFpEF.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Monitoring of microbial proteome dynamics using Raman stable isotope probing

Abnormal protein kinetics could be a cause of several diseases associated with essential life processes. An accurate understanding of protein dynamics and turnover is essential for developing diagnostic or therapeutic tools to monitor these changes. Raman spectroscopy in combination with stable isotope probes (SIP) such as carbon-13, and deuterium has been a breakthrough in the qualitative and quantitative study of various metabolites. In this work, we are reporting the utility of Raman-SIP for monitoring dynamic changes in the proteome at the community level. We have used ¹³ C-labeled glucose as the only carbon source in the medium and verified its incorporation in the microbial biomass in a time-dependent manner. A visible redshift in the Raman spectral vibrations of major biomolecules such as nucleic acids, phenylalanine, tyrosine, amide I, and amide III were observed. Temporal changes in the intensity of these bands demonstrating the feasibility of protein turnover monitoring were also verified. Kanamycin, a protein synthesis inhibitor was used to assess the feasibility of identifying effects on protein turnover in the cells. Successful application of this work can provide an alternate/adjunct tool for monitoring proteome-level changes in an objective and nondestructive manner.

Serum protein profile study of myocardial infarction using a LED induced fluorescence based HPLC system

Cardiovascular diseases (CVDs) are the major health conditions for high mortality and morbidity in humans. Delay in the diagnosis of CVDs effect patients long and short-term health condition. In -house assembled UV-light emitting diode (LED) based fluorescence detector for high -performance liquid chromatography (HPLC) (HPLC-LED-IF) system is used to record serum chromatograms of three categories of samples namely, before medicated- myocardial infarction (B-MI), after medicated- MI (A-MI), and normal. The sensitivity and performance of HPLC-LED-IF system is estimated using commercial serum proteins. Statistical analysis tools like, descriptive statistics, principal component analysis (PCA), and Match/ No Match test were applied to visualize the variation in three groups of samples. Statistical analysis of the protein profile data showed fairly good discrimination among the three categories. The receiver operating characteristic (ROC) curve also supported the reliability of the method to diagnose MI.

N, Adigal S, Lukose J, Kartha VB, Chidangil S. Cardiovascular biomarkers in body fluids: progress and prospects in optical sensors

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases.

Expert opinion.

Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient’s short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques.