Study On Label-free Multimodal Profiling Of Individual Functionalized Nanoparticles And Extracellular Vesicles

Extracellular vesicles(EVs)and functional nanoparticles,such as drug-loaded liposomes,are playing an increasingly important role in fields of nano-medicine and nano-biology.Studies have shown that biomolecule information and morphological characteristics carried by functionalized nanoparticles are heavily implicated in their functions and biogenesis.However,heterogeneity is always expected to be present within diverse nanoparticle populations,since the limitation of single-modality characterization and only providing "averaged" information of bulk of samples,current gold standard characterizations are not capable of accurately profiling heterogeneity.Fluorescent labelling techniques including high resolution flow-cytometry,can simultaneously profile chemical and morphological information on single-particle basis,but labeling of nanoparticles is quite challenging,and profiling capability is limited by the number of fluorescence channel and priori fluorescence library,making it difficult to profiling multiple-biomolecule information of functional nanoparticles with unknown makeup.Laser-tweezer Raman Spectroscopy(LTRS),which integrates laser tweezer and non-destructive,label-free Raman spectroscopy together,has demonstrated potential for studying individual nanoparticles such as EVs and liposomes.While some effort has been placed on improvement of measurement sensitivity,throughput and trying to extract size information based on traditional LTRS,these methods also cannot distinguish between single particles or multiple particles/aggregates within the trap.To address this challenge,we present a label-free morpho-chemical characterization method that combines LTRS with an elastic scattering measurement channel,records Raman spectra and tracks trapped particle motion to identify chemical composition,size and refractive index.Based on constrained Brownian motion model and Mie scattering model,the profiling principles of particle size and refractive index is derived;in addition,according to linear superposition model and confocal configuration of Raman spectroscopy.Once the particle size is obtained,quantitative chemical concentration of nanoparticle was also extracted.Highlights of the technique is its unique capacity to characterize aggregation status and absolute chemical concentration at the single-particle level.Subsequently,we designed and built this multi-modal profiling system with the development of controlled automated data collecting process.By using NIST standard nano-spheres of different materials and particle sizes,we validated and optimized the system's characterization performance and accuracy.Meanwhile,the comparison of our technique with commercial "gold standard" methods verifies the well satisfaction of research requirements.Further,combining morpho-chemical information together allows unique information to be extracted,such as encapsulation efficiency and lamellarity of drug loaded liposomes,which has not been demonstrated previously on a single-particle basis without labels or laborious EM imaging.When applied to EVs,quantitative characterization of multiple chemical components was achieved by utilizing pure components Raman spectral library and asymmetric least squares model.Through principal component analysis and hierarchical clustering analysis,we also reveal the compositional and size differences between single exosomes derived from laryngeal cancerous(HN4)and normal epithelial(NP69)cell lines,along with a HN4 cells where TRPP2 channel was knocked down.The comparison reveals that after knocking-down the TRPP2 protein,the chemical makeup of EVs derived from laryngeal cancerous cells becomes closer to EVs derived from normal epithelial cells.Intriguingly,the differences in EV content are found in small subpopulations of EVs,highlighting the importance of single-particle measurements.Thus,our technique provides a novel,quantitative way for characterizing the diversity of nanoparticles,which could be applied to standardization of drug content in nano-delivery systems,and studying the relationship between biogenesis,composition,and function of exosomes.