Surface-enhanced Raman scattering (SERS) and tip-enhanced Raman scattering (TERS) in label-free characterization of erythrocyte membranes and extracellular vesicles at the nano-scale and molecular level.
Tetiana StepanenkoKamila SofińskaNatalia WilkoszJakub DybaśEwelina WiercigrochKatarzyna BulatEwa Szczesny-MalysiakKatarzyna Skirlińska-NosekSara SewerynJoanna G ChwiejEwelina LipiecKatarzyna Maria MarzecPublished in: The Analyst (2024)
The manuscript presents the potential of surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS) for label-free characterization of extracellular microvesicles (EVs) and their isolated membranes derived from red blood cells (RBCs) at the nanoscale and at the single-molecule level, providing detection of a few individual amino acids, protein and lipid membrane compartments. The study shows future directions for research, such as investigating the use of the mentioned techniques for the detection and diagnosis of diseases. We demonstrate that SERS and TERS are powerful techniques for identifying the biochemical composition of EVs and their membranes, allowing the detection of small molecules, lipids, and proteins. Furthermore, extracellular vesicles released from red blood cells (REVs) can be broadly classified into exosomes, microvesicles, and apoptotic bodies, based on their size and biogenesis pathways. Our study specifically focuses on microvesicles that range from 100 to 1000 nanometres in diameter, as presented in AFM images. Using SERS and TERS spectra obtained for REVs and their membranes, we were able to characterize the chemical and structural properties of microvesicle membranes with high sensitivity and specificity. This information may help better distinguish and categorize different types of EVs, leading to a better understanding of their functions and potential biomedical applications.
Keyphrases
- label free
- raman spectroscopy
- red blood cell
- single molecule
- atomic force microscopy
- amino acid
- stem cells
- cell death
- gold nanoparticles
- healthcare
- deep learning
- risk assessment
- sensitive detection
- bone marrow
- machine learning
- mass spectrometry
- convolutional neural network
- small molecule
- molecular dynamics
- high speed
- protein protein
- anti inflammatory
- quantum dots
- real time pcr