Raman spectroscopy combined with comprehensive gas chromatography for label-free characterization of plasma-derived extracellular vesicle subpopulations

Raman spectroscopy in extracellular vesicles analysis: Techniques, applications and advancements

Raman spectroscopy provides a robust approach for detailed analysis of the chemical and molecular profiles of extracellular vesicles (EVs). Recent advancements in Raman techniques have significantly enhanced the sensitivity and accuracy of EV characterization, enabling precise detection and profiling of molecular components within EV samples. This review introduces and compares various Raman-based techniques for EV characterization. These include Raman spectroscopy (RS), which provides fundamental molecular information; Raman trapping analysis (RTA), which combines optical trapping with Raman scattering for the manipulation and analysis of individual EVs; surface-enhanced Raman spectroscopy (SERS), which enhances the Raman signal through the use of metallic nanostructures, significantly improving sensitivity; and microfluidic SERS, which integrates SERS with microfluidic platforms to allow high-throughput, label-free analysis of EVs in biological fluids. In addition to comparing various Raman techniques, this review provides a comprehensive analysis that includes comparisons of machine learning methods, EV isolation techniques, and characterization strategies. By integrating these approaches, the review presents a holistic perspective on Raman-based EV analysis, covering profiling, purity, heterogeneity and size analysis as well as imaging. The combined assessment of Raman technologies with advanced computational and experimental methodologies supports the development of more robust diagnostic and therapeutic applications involving EVs.

Multi-omics analysis identified extracellular vesicles as biomarkers for cardiovascular diseases

Cell-derived extracellular vesicles (EVs) have emerged as a promising non-invasive liquid biopsy technique due to their accessibility and their ability to encapsulate and transport diverse biomolecules. EVs have garnered substantial research interest, notably in cardiovascular diseases (CVDs), where their roles in pathophysiology and as diagnostic and prognostic biomarkers are increasingly recognized. This review provides a comprehensive overview of EVs, starting with their origins, followed by the techniques used for their isolation and characterization. We explore the diverse cargo of EVs, including nucleic acids, proteins, lipids, and metabolites, highlighting their roles in intercellular communication and as potential biomarkers. We then delve into the application of genomics, transcriptomics, proteomics, and metabolomics in the analysis of EVs, particularly within the context of CVDs. Finally, we discuss how integrated multi-omics approaches are unveiling novel biomarkers, offering fresh insights into the diagnosis and prognosis of CVDs. This review underscores the growing importance of EVs in clinical diagnostics and the potential of multi-omics to propel future advancements in CVD biomarker discovery.

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.

Toward the nanoscale chemical and physical probing of milk-derived extracellular vesicles using Raman and tip-enhanced Raman spectroscopy

Tip-enhanced Raman spectroscopy (TERS) is an advanced technique to perform local chemical analysis of the surface of a sample through the improvement of the sensitivity and the spatial resolution of Raman spectroscopy by plasmonic enhancement of the electromagnetic signal in correspondence with the nanometer-sized tip of an atomic force microscope (AFM). In this work, TERS is demonstrated to represent an innovative and powerful approach for studying extracellular vesicles, in particular bovine milk-derived extracellular vesicles (mEVs), which are nanostructures with considerable potential in drug delivery and therapeutic applications. Raman spectroscopy has been used to analyze mEVs at the micrometric and sub-micrometric scales to obtain a detailed Raman spectrum in order to identify the 'signature' of mEVs in terms of their characteristic molecular vibrations and, therefore, their chemical compositions. With the ability to improve lateral resolution, TERS has been used to study individual mEVs, demonstrating the possibility of investigating a single mEV selected on the surface of the sample and, moreover, analyzing specific locations on the selected mEV with nanometer lateral resolution. TERS potentially allows one to reveal local differences in the composition of mEVs providing new insights into their structure. Also, thanks to the intrinsic properties of TERS to acquire the signal from only the first few nanometers of the surface, chemical investigation of the lipid membrane in correspondence with the various locations of the selected mEV could be performed by analyzing the peaks of the Raman shift in the relevant range of the spectrum (2800-3000 cm-1). Despite being limited to mEVs, this work demonstrates the potential of TERS in the analysis of extracellular vesicles.

Exosomal Cargo in Ovarian Cancer Dissemination

Ovarian cancer (OC) has the highest mortality rate among all gynecologic cancers and is characterized by early peritoneal spread. The growth and development of OC are associated with the formation of ascitic fluid, creating a unique tumor microenvironment. Understanding the mechanisms of tumor progression is crucial in identifying new diagnostic biomarkers and developing novel therapeutic strategies. Exosomes, lipid bilayer vesicles measuring 30-150 nm in size, are known to establish a crucial link between malignant cells and their microenvironment. Additionally, the confirmed involvement of exosomes in carcinogenesis enables them to mediate the invasion, migration, metastasis, and angiogenesis of tumor cells. Functionally active non-coding RNAs (such as microRNAs, long non-coding RNAs, circRNAs), proteins, and lipid rafts transported within exosomes can activate numerous signaling pathways and modify gene expression. This review aims to expand our understanding of the role of exosomes and their contents in OC carcinogenesis processes such as epithelial-mesenchymal transition (EMT), angiogenesis, vasculogenic mimicry, tumor cell proliferation, and peritoneal spread. It also discusses the potential for utilizing exosomal cargo to develop novel "liquid biopsy" biomarkers for early OC diagnosis.

Detection of micro-plasma-induced exosomes secretion in a fibroblast-melanoma co-culture model

BACKGROUND

Melanoma is a highly aggressive tumor and a significant cause of skin cancer-related death. Timely diagnosis and treatment require identification of specific biomarkers in exosomes secreted by melanoma cells. In this study, label-free surface-enhanced Raman spectroscopy (SERS) method with size-matched selectivity was used to detect membrane proteins in exosomes released from a stimulated environment of fibroblasts (L929) co-cultured with melanoma cells (B16-F10). To promote normal secretion of exosomes, micro-plasma treatment was used to gently induce the co-cultured cells and slightly increase the stress level around the cells for subsequent detection using the SERS method.

RESULTS AND DISCUSSION

Firstly, changes in reactive oxygen species/reactive nitrogen species (ROS/RNS) concentrations in the cellular microenvironment and the viability and proliferation of healthy cells are assessed. Results showed that micro-plasma treatment increased extracellular ROS/RNS levels while modestly reducing cell proliferation without significantly affecting cell survival. Secondly, the particle size of secreted exosomes isolated from the culture medium of L929, B16-F10, and co-cultured cells with different micro-plasma treatment time did not increase significantly under single-cell conditions at short treatment time but might be changed under co-culture condition or longer treatment time. Third, for SERS signals related to membrane protein biomarkers, exosome markers CD9, CD63, and CD81 can be assigned to significant Raman shifts in the range of 943-1030 and 1304-1561 cm-1, while the characteristics SERS peaks of L929 and B16-F10 cells are most likely located at 1394/1404, 1271 and 1592 cm-1 respectively.

SIGNIFICANCE AND NOVELTY

Therefore, this micro-plasma-induced co-culture model provides a promising preclinical approach to understand the diagnostic potential of exosomes secreted by cutaneous melanoma/fibroblasts. Furthermore, the label-free SERS method with size-matched selectivity provides a novel approach to screen biomarkers in exosomes secreted by melanoma cells, aiming to reduce the use of labeling reagents and the processing time traditionally required.

Evaluation of VOCs from fungal strains, building insulation materials and indoor air by solid phase microextraction arrow, thermal desorption-gas chromatography-mass spectrometry and machine learning approaches

Solid phase microextraction Arrow and thermal desorption-gas chromatography-mass spectrometry allowed the collection and evaluation of volatile organic compounds (VOCs) emitted by fungal cultures from building insulation materials and in indoor air. Principal component analysis, linear discriminant analysis and supported vector machine were used for visualization and statistical assessment of differences between samples. In addition, a screening tool based on the soft independent modelling of class analogies (SIMCA) was developed for identification of fungal contamination of indoor air. Ten different fungal strains, incubated under ambient and microaerophilic conditions, were analyzed for time period ranging from 5 to 29 days after inoculation resulting in a total of 140 samples. In addition, the effect of additives on the fungal growing media was studied. The total number of compounds and concentration values were used for the evaluation of the results. Clear differences were observed for VOC profiles emitted by different fungal strains by exploiting long chain alcohols (3-octanol, 1-hexanol and 2-octen-1-ol) and sesquiterpenes (farnesene, cuprene). The analysis of glass-wool and cellulose based building insulation materials (3 samples) gave clear differences, mainly for oxygenated compounds (ethyl acetate and hexanal) and benzenoids (benzaldehyde). Moreover, the comparison of indoor air and insulation materials collected from a house with fungal indoor air problems indicated that 42% of the VOCs were found in both samples. The analysis of 52 indoor air samples demonstrated clear differences in their VOC profiles, especially for hydrocarbons, and between control (44 samples) and indoor air problem houses (8 samples). Finally, the SIMCA model enabled to recognize differences between control and fungi contaminated houses with a prediction capacity over 84%.

Macroporous Epoxy-Based Monoliths Functionalized with Anti-CD63 Nanobodies for Effective Isolation of Extracellular Vesicles in Urine

Extracellular vesicles (EVs) have enormous potential for the implementation of liquid biopsy and as effective drug delivery means, but the fulfilment of these expectations requires overcoming at least two bottlenecks relative to their purification, namely the finalization of reliable and affordable protocols for: (i) EV sub-population selective isolation and (ii) the scalability of their production/isolation from complex biological fluids. In this work, we demonstrated that these objectives can be achieved by a conceptually new affinity chromatography platform composed of a macroporous epoxy monolith matrix functionalized with anti-CD63 nanobodies with afflux of samples and buffers regulated through a pump. Such a system successfully captured and released integral EVs from urine samples and showed negligible unspecific binding for circulating proteins. Additionally, size discrimination of eluted EVs was achieved by different elution approaches (competitive versus pH-dependent). The physical characteristics of monolith material and the inexpensive production of recombinant nanobodies make scaling-up the capture unit feasible and affordable. Additionally, the availability of nanobodies for further specific EV biomarkers will allow for the preparation of monolithic affinity filters selective for different EV subclasses.

Automated On-Line Isolation and Fractionation Method for Subpopulations of Extracellular Vesicles

Immunoaffinity chromatography (IAC) with selective antibodies immobilized on polymeric monolithic disk columns enables selective isolation of biomacromolecules from human plasma, while asymmetrical flow field-flow fractionation (AsFlFFF or AF4) can be used for further fractionation of relevant subpopulations of biomacromolecules (e.g., small dense low-density lipoproteins, exomeres, and exosomes) from the isolates. Here we describe how the isolation and fractionation of subpopulations of extracellular vesicles can be achieved without the presence of lipoproteins using on-line coupled IAC-AsFlFFF. With the developed methodology, it is possible to have fast, reliable, and reproducible automated isolation and fractionation of challenging biomacromolecules from human plasma with a high purity and high yields of subpopulations.

Comparison of Different Isolation Methods for Plasma-Derived Extracellular Vesicles in Patients with Hyperlipidemia

Extracellular vesicles are commonly found in human body fluids and can reflect current physiological conditions of human body and act as biomarkers of disease. The quality of isolated extracellular vesicles facilitates the early diagnosis of various diseases accompanied by hyperlipidemia. Nonetheless, there are no reports on which special methods are suitable for isolating extracellular vesicles from the plasma of patients with hyperlipidemia. Thus, this study compared three different research-based extracellular vesicle isolation approaches, namely ultracentrifugation (UC), polyethylene glycol (PEG) precipitation, and size exclusion chromatography (SEC), and determined which of them was the most effective method. We selected blood samples from 12 patients with clinically diagnosed hyperlipidemia and isolated plasma-derived extracellular vesicles using three methods. The morphology of the isolated extracellular vesicles was observed using transmission electron microscopy, while the concentration was detected by asymmetric flow field-flow fractionation and multi-angle light scattering. Marker proteins were identified by Western blotting, and protein composition was evaluated by silver staining. Both determined the contaminations in the extracellular vesicle samples. The results showed that the three methods can be successfully used for the isolation of extracellular vesicles. The extracellular vesicles isolated by UC were larger in size, and the yield was much lower. Although the yield of extracellular vesicles isolated by PEG precipitation was greatly improved, the contamination was increased. Of the three methods, only the SEC-isolated extracellular vesicles were characterized by high yield and low contamination. Therefore, our data suggested that the SEC was a more ideal method for isolating extracellular vesicles from the plasma of patients with hyperlipidemia.