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Surface enhanced Raman scattering (SERS) is a powerful tool for vibrational spectroscopy, providing orders of magnitude increase in chemical sensitivity compared to spontaneous Raman scattering. Yet it remains a challenge to synthesize robust, uniform SERS substrates quickly and easily. Lithographic approaches to produce substrates can achieve high, uniform sensitivity but are expensive and complex, thus difficult to scale. Facile solution-phase chemical approaches often result in unreliable SERS substrates due to heterogeneous arrangement of "hot spots" throughout the material. Here we demonstrate the synthesis and characterization of a homogeneous gold nanofoam (AuNF) substrate produced by a rapid, one-pot, four-ingredient synthetic approach. AuNFs are rapidly nucleated with macroscale porosity and then chemically roughened to produce nanoscale features that confer homogeneous and high signal enhancement (~109) across large areas, a comparable performance to lithographically produced substrates.

Immune checkpoint blockade (ICB) therapy has revolutionized clinical oncology. However, the efficacy of ICB therapy is limited by the ineffective infiltration of T effector (Teff) cells to tumors and the immunosuppressive tumor microenvironment (TME). Here, we report a programmable tumor cells/Teff cells bispecific nano-immunoengager (NIE) that can circumvent these limitations to improve ICB therapy. The peptidic nanoparticles (NIE-NPs) bind tumor cell surface α3β1 integrin and undergo in situ transformation into nanofibrillar network nanofibers (NIE-NFs). The prolonged retained nanofibrillar network at the TME captures Teff cells via the activatable α4β1 integrin ligand and allows sustained release of resiquimod for immunomodulation. This bispecific NIE eliminates syngeneic 4T1 breast cancer and Lewis lung cancer models in mice, when given together with anti-PD-1 antibody. The in vivo structural transformation-based supramolecular bispecific NIE represents an innovative class of programmable receptor-mediated targeted immunotherapeutics to greatly enhance ICB therapy against cancers.

Given the emerging diagnostic utility of extracellular vesicles (EVs), it is important to account for non-EV contaminants. Lipoprotein present in EV-enriched isolates may inflate particle counts and decrease sensitivity to biomarkers of interest, skewing chemical analyses and perpetuating downstream issues in labeling or functional analysis. Using label free surface enhanced Raman scattering (SERS), we confirm that three common EV isolation methods (differential ultracentrifugation, density gradient ultracentrifugation, and size exclusion chromatography) yield variable lipoprotein content. We demonstrate that a dual-isolation method is necessary to isolate EVs from the major classes of lipoprotein. However, combining SERS analysis with machine learning assisted classification, we show that the disease state is the main driver of distinction between EV samples, and largely unaffected by choice of isolation. Ultimately, this study describes a convenient SERS assay to retain accurate diagnostic information from clinical samples by overcoming differences in lipoprotein contamination according to isolation method., SERS can “see through” varying lipoprotein contamination present in extracellular vesicles isolated from cancer patient samples for accurate diagnostic classification.

[Image: see text] For more effective early-stage cancer diagnostics, there is a need to develop sensitive and specific, non- or minimally invasive, and cost-effective methods for identifying circulating nanoscale extracellular vesicles (EVs). Here, we report the utilization of a simple plasmonic scaffold composed of a microscale biosilicate substrate embedded with silver nanoparticles for surface-enhanced Raman scattering (SERS) analysis of ovarian and endometrial cancer EVs. These substrates are rapidly and inexpensively produced without any complex equipment or lithography. We extensively characterize the substrates with electron microscopy and outline a reproducible methodology for their use in analyzing EVs from in vitro and in vivo biofluids. We report effective chemical treatments for (i) decoration of metal surfaces with cysteamine to nonspecifically pull down EVs to SERS hotspots and (ii) enzymatic cleavage of extraluminal moieties at the surface of EVs that prevent localization of complementary chemical features (lipids/proteins) to the vicinity of the metal-enhanced fields. We observe a major loss of sensitivity for ovarian and endometrial cancer following enzymatic cleavage of EVs’ extraluminal domain, suggesting its critical significance for diagnostic platforms. We demonstrate that the SERS technique represents an ideal tool to assess and measure the high heterogeneity of EVs isolated from clinical samples in an inexpensive, rapid, and label-free assay.

Immune checkpoint blockade (ICB) therapy has revolutionized clinical oncology. However, the efficacy of ICB therapy is limited by the ineffective homing of T effector (Teff) cells to tumours and the immunosuppressive tumour microenvironment (TME). Here, we report a programmable tumour cells/Teff cells bispecific nano-immuno-engager (NIE) that can circumvent these limitations to improve ICB therapy. We have developed 28 nm non-toxic peptidic micellar nanoparticles (NIE-NPs) that bind α3β1 integrin on tumour cells membrane and undergo in situ transformation on surface of tumour cells into nanofibrillar network (NIE-NFs). The nanofibrillar network persistently facilitates cytotoxic T cells’ homing to the proximity of tumour cells via activatable α4β1 integrin ligands, and also allows sustained release of resiquimod to reprogram the TME. This bispecific NIE eliminates syngeneic 4T1 breast cancer and Lewis lung cancer models in mice, when given together with anti-PD-1 antibody. The in vivo structural transformation-based supramolecular bispecific NIE represents an innovative class of programmable receptor-mediated targeted immunotherapeutics to greatly enhance ICB therapy against cancers.

Using a regular CMOS sensor as a template, we are able to fabricate a simple but highly effective superhydrophobic SERS substrate. Specifically, we decorated the microlens layer of the sensor with 7 μm polystyrene beads to obtain a PDMS patterned replica. The process resulted in a uniform pattern of voids in the PDMS (denoted nanobowls) that are intercalated with a few larger voids (denoted here microbowls). The voids act as superhydrophobic substrates with analyte concentration capabilities in bigger bowl-like structures. Silver nanoparticles were directly grown on the patterned PDMS substrate inside both the nano- and microbowls, and serve as strong electromagnetic field enhancers for the SERS substrate. After systematic characterization of the fabricated SERS substrate by atomic force microscopy and scanning electron microscopy, we demonstrated its SERS performance using 4-aminothiophenol as a reporter molecule. Finally, we employed this innovative substrate to concentrate and analyze extracellular vesicles (EVs) isolated from an MC65 neural cell line in an ultralow sample volume. This substrate can be further exploited for the investigation of various EV biomarkers for early diagnosis of different diseases using liquid biopsy.

Surface-enhanced Raman scattering (SERS) is a powerful technique for sensitive label-free analysis of chemical and biological samples. While much recent work has established sophisticated automation routines using machine learning and related artificial intelligence methods, these efforts have largely focused on downstream processing (e.g., classification tasks) of previously collected data. While fully automated analysis pipelines are desirable, current progress is limited by cumbersome and manually intensive sample preparation and data collection steps. Specifically, a typical lab-scale SERS experiment requires the user to evaluate the quality and reliability of the measurement (i.e., the spectra) as the data are being collected. This need for expert user-intuition is a major bottleneck that limits applicability of SERS-based diagnostics for point-of-care clinical applications, where trained spectroscopists are likely unavailable. While application-agnostic numerical approaches (e.g., signal-to-noise thresholding) are useful, there is an urgent need to develop algorithms that leverage expert user intuition and domain knowledge to simplify and accelerate data collection steps. To address this challenge, in this work, we introduce a machine learning-assisted method at the acquisition stage. We tested six common algorithms to measure best performance in the context of spectral quality judgment. For adoption into future automation platforms, we developed an open-source python package tailored for rapid expert user annotation to train machine learning algorithms. We expect that this new approach to use machine learning to assist in data acquisition can serve as a useful building block for point-of-care SERS diagnostic platforms.

Background Tetraspanin expression of extracellular vesicles (EVs) is often used as a surrogate for their detection and classification, a practice that typically assumes their consistent expression across EV sources. Results Here we demonstrate that there are distinct patterns in colocalization of tetraspanin expression of EVs enriched from a variety of in vitro and in vivo sources. We report an optimized method for the use of single particle antibody-capture and fluorescence detection to identify subpopulations according to tetraspanin expression and compare our findings with nanoscale flow cytometry. We found that tetraspanin profile is consistent from a given EV source regardless of isolation method, but that tetraspanin profiles are distinct across various sources. Tetraspanin profiles measured by flow cytometry do not totally agree, suggesting that limitations in subpopulation detection significantly impact apparent protein expression. We further analyzed tetraspanin expression of single EVs captured non-specifically, revealing that tetraspanin capture can bias the apparent multiplexed tetraspanin profile. Finally, we demonstrate that this bias can have significant impact on diagnostic sensitivity for tumor-associated EV surface markers. Conclusion Our findings may reveal key insights into protein expression heterogeneity of EVs that better inform EV capture and detection platforms for diagnostic or other downstream use. Graphical abstract

One of the hallmarks of Alzheimer's disease (AD) pathogenesis is believed to be the production and deposition of amyloid-beta (Aβ) peptide into extracellular plaques. Existing research indicates that extracellular vesicles (EVs) can carry Aβ associated with AD. However, characterization of the EVs-associated Aβ and its conformational variants has yet to be realized. Raman spectroscopy is a label-free and non-destructive method that is able to assess the biochemical composition of EVs. This study reports for the first time the Raman spectroscopic fingerprint of the Aβ present in the molecular cargo of small extracellular vesicles (sEVs). Raman spectra were measured from sEVs isolated from Alzheimer's disease cell culture model, where secretion of Aβ is regulated by tetracycline promoter, and from midbrain organoids. The averaged spectra of each sEV group showed considerable variation as a reflection of the biochemical content of sEVs. Spectral analysis identified more intense Raman peaks at 1650 cm−1 and 2930 cm−1 attributable to the Aβ peptide incorporated in sEVs produced by the Alzheimer's cell culture model. Subsequent analysis of the spectra by principal component analysis differentiated the sEVs of the Alzheimer's disease cell culture model from the control groups of sEVs. Moreover, the results indicate that Aβ associated with secreted sEVs has a α-helical secondary structure and the size of a monomer or small oligomer. Furthermore, by analyzing the lipid content of sEVs we identified altered fatty acid chain lengths in sEVs that carry Aβ that may affect the fluidity of the EV membrane. Overall, our findings provide evidence supporting the use of Raman spectroscopy for the identification and characterization of sEVs associated with potential biomarkers of neurological disorders such as toxic proteins., Extracellular vesicles can carry Aβ associated with Alzheimer's disease. In this article we identify specific Raman spectroscopic features that can be associated with Aβ present in the molecular cargo of small extracellular vesicles.

Tetraspanin expression of extracellular vesicles (EVs) is often used as a surrogate for their general detection and classification from background contaminants. This common practice typically assumes a consistent expression of tetraspanins across EV sources, thus obscuring subpopulations of variable or limited tetraspanin expression. While some recent studies indicate differential expression of tetraspanins across bulk isolated EVs, here we present analysis of single EVs isolated using various field-standard methods from a variety of in vitro and in vivo sources to identify distinct patterns in colocalization of tetraspanin expression. We report an optimized method for the use of antibodycapture single particle interferometric reflectance imaging sensing (SP-IRIS) and fluorescence detection to identify subpopulations according to tetraspanin expression and compare our findings with nanoscale flow cytometry. Using SP-IRIS and immunofluorescence, we report that tetraspanin profile is consistent from a given EV source regardless of isolation method, but that tetraspanin profiles are distinct across various sources. Tetraspanin profiles as measured by flow cytometry do not share similar trends, suggesting that limitations in subpopulation detection significantly impact apparent protein expression. We further analyzed tetraspanin expression of single EVs captured non-specifically, revealing that tetraspanin capture can bias the apparent multiplexed tetraspanin profile. Finally, we demonstrate that this bias can have significant impact on diagnostic sensitivity for tumor-associated EV surface markers. Our findings may reveal key insights into the complexities of the EV biogenesis and signaling pathways and better inform EV capture and detection platforms for diagnostic or other downstream use.

To be clinically efficacious, nanotherapeutic drugs need to reach disease tissues reliably and cause limited side effects to normal organs and tissues. Here, we report a proof-of-concept study on the development of a smart peptidic nanophototherapeutic agent in line with clinical requirements, which can transform its morphology from nanoparticles to nanofibrils at the tumor sites. This in vivo receptor-mediated transformation process resulted in the formation and prolonged tumor-retention of highly ordered (J-aggregate type of photosensitizer) photosensitive peptide nanofibrillar network with greatly enhanced photothermal and photodynamic properties. This strategy of "multiple daily low-intensity laser radiation after each intravenous injection of significantly low-dose of nanomaterials" demonstrated effective elimination of 4T1 orthotopic syngeneic breast cancer in mice. The technology for nanomaterial modulation based on living cell surface receptors, in this case tumor-associated α3β1 integrin, has great potential for clinical translation and is expected to improve the therapeutic efficacy against many cancers.

The soluble oligomeric form of the amyloid beta (Aβ) peptide is the major causative agent in the molecular pathogenesis of Alzheimer's disease (AD). We have previously developed a pyrroline-nitroxyl fluorene compound (SLF) that blocks the toxicity of Aβ. Here we introduce the multi-parametric surface plasmon resonance (MP-SPR) approach to quantify SLF binding and effect on the self-association of the peptide via a label-free, real-time approach. Kinetic analysis of SLF binding to Aβ and measurements of layer thickness alterations inform on the mechanism underlying the ability of SLF to inhibit Aβ toxicity and its progression towards larger oligomeric assemblies. Depending on the oligomeric state of Aβ, distinct binding affinities for SLF are revealed. The Aβ monomer and dimer uniquely possess sub-nanomolar affinity for SLF via a non-specific mode of binding. SLF binding is weaker in oligomeric Aβ, which displays an affinity for SLF on the order of 100 μM. To complement these experiments we carried out molecular docking and molecular dynamics simulations to explore how SLF interacts with the Aβ peptide. The MP-SPR results together with in silico modeling provide affinity data for the SLF-Aβ interaction and allow us to develop a new general method for examining protein aggregation.

Two nonlinear imaging modalities, coherent anti-Stokes Raman scattering (CARS) and sum-frequency generation (SFG), were successfully combined for sensitive multimodal imaging of multiple solid-state forms and their changes on drug tablet surfaces. Two imaging approaches were used and compared: (i) hyperspectral CARS combined with principal component analysis (PCA) and SFG imaging and (ii) simultaneous narrowband CARS and SFG imaging. Three different solid-state forms of indomethacin-the crystalline gamma and alpha forms, as well as the amorphous form-were clearly distinguished using both approaches. Simultaneous narrowband CARS and SFG imaging was faster, but hyperspectral CARS and SFG imaging has the potential to be applied to a wider variety of more complex samples. These methodologies were further used to follow crystallization of indomethacin on tablet surfaces under two storage conditions: 30 °C/23% RH and 30 °C/75% RH. Imaging with (sub)micron resolution showed that the approach allowed detection of very early stage surface crystallization. The surfaces progressively crystallized to predominantly (but not exclusively) the gamma form at lower humidity and the alpha form at higher humidity. Overall, this study suggests that multimodal nonlinear imaging is a highly sensitive, solid-state (and chemically) specific, rapid, and versatile imaging technique for understanding and hence controlling (surface) solid-state forms and their complex changes in pharmaceuticals.

Extracellular vesicles (EVs) have the ability to function as molecular vehicles and could therefore be harnessed to deliver drugs to target cells in diseases such as cancer. The composition of EVs determines their function as well as their interactions with cells, which consequently affects the cell uptake efficacy of EVs. In this study, we present two novel label-free approaches for studying EVs; characterization of EV composition by time-gated surface-enhanced Raman spectroscopy (TG-SERS) and monitoring the kinetics and amount of cellular uptake of EVs by surface plasmon resonance (SPR) in real-time. Using these methods, we characterized the most abundant EVs of human blood, red blood cell (RBC)- and platelet (PLT)-derived EVs and studied their interactions with prostate cancer cells. Complementary studies were performed with nanoparticle tracking analysis for concentration and size determinations of EVs, zeta potential measurements for surface charge analysis, and fluorophore-based confocal imaging and flow cytometry to confirm EV uptake. Our results revealed distinct biochemical features between the studied EVs and demonstrated that PLT-derived EVs were more efficiently internalized by PC-3 cells than RBC-derived EVs. The two novel label-free techniques introduced in this study were found to efficiently complement conventional techniques and paves the way for further use of TG-SERS and SPR in EV studies.

Human epidermal growth factor receptor 2 (HER2) is overexpressed in over 20% of breast cancers. The dimerization of HER2 receptors leads to the activation of down-stream signals enabling proliferation and survival of malignant phenotypes. Owing to the high expression levels of HER2, combination therapies are currently required for the treatment of HER2-positive breast cancer. Here, we designed non-toxic transformable peptides that self-assemble into micelles in aqueous conditions, but, upon binding to HER2 on cancer cells, transform into nanofibers, which disrupt HER2 dimerization and subsequent downstream signalling events, leading to apoptosis of cancer cells. The phase transformation of the peptides enables specific HER2-targeting and inhibition of HER2 dimerization blocks the expression of proliferation and survival genes in the nucleus. We demonstrate that these transformable peptides can be used as a monotherapy for the treatment of HER2+ breast cancer in mouse xenograft models.

Oral squamous cancers (OSC) are hallmarked by poor prognosis, delayed clinical detection, and a lack of defined, characteristic biomarkers. By screening combinatorial one-bead one-compound (OBOC) peptide libraries against oral squamous cancer cell lines, two cyclic peptide ligands, LLY12 and LLY13 were previously identified. These ligands are capable of specific binding to the oral cancer cell lines (MOK-101, HSC-3, SCC-4 and SCC-10a) but not non-cancerous keratinocytes, leukocytes, fibroblast, and endothelial cells. These two peptides were synthesized and evaluated for their binding property, cytotoxicity and cell permeability. In vitro studies indicate that both LLY12 and LLY13 were able to bind to oral cancer cells with high specificity but did not show any cytotoxicity against human keratinocytes. Biotinylated LLY13, in complex with streptavidin-alexa488 was taken up by live oral cancer cells, thus rendering it as an excellent candidate vehicle for efficient delivery of drug loaded-nanoparticles. In vivo and ex vivo near infra-red fluorescence imaging studies confirmed the in vivo targeting efficiency and specificity of LLY13 in oral cancer orthotopic murine xenograft model. In vivo studies also showed that LLY13 was able to accumulate in the OSC tumors and demarcate the tumor margins in orthotopic xenograft model. Together, our data supports LLY13 as a promising theranostic agent against OSC.

We recently found that subsequent treatments of hardwood kraft pulps with a tertiary amine (DABCO; 1,4-diazabicyclo[2.2.2]octane) catalyzed hypochlorous acid (Hcat), ozone (Z) and hydrogen peroxide (P) may provide full brightness with low chemical dosages in a short overall reaction time. Here we report chemical characteristics and stability of Hcat–Z–P bleached eucalyptus kraft pulps. In comparison with a normal ECF (elementary chlorine free) bleached pulp the Hcat–Z–P bleached pulps had low carbonyl group content while the degree of polymerization of cellulose remained at high level. However, the brightness of the Hcat–Z–P bleached pulps was reversed more easily under humid ageing conditions in comparison with the ECF bleached pulp. The discoloration was accompanied by an increase in Raman emission at 1560 cm−1 which is indicative of formation of highly conjugated chromophores. The brightness reversion did not correlate with the carbonyl content that is often considered to be the main origin of the brightness loss under humid conditions. In contrast, the brightness instability of the catalytically bleached pulps possibly resulted from the relatively high organochlorine content.

In response to physiological and artificial stimuli, cells generate nano-scale extracellular vesicles (EVs) by encapsulating biomolecules in plasma membrane-derived phospholipid envelopes. These vesicles are released to bodily fluids, hence acting as powerful endogenous mediators in intercellular signaling. EVs provide a compelling alternative for biomarker discovery and targeted drug delivery, but their kinetics and dynamics while interacting with living cells are poorly understood. Here we introduce a novel method, fluorescence lifetime imaging microscopy (FLIM) to investigate these interaction attributes. By FLIM, we show distinct cellular uptake mechanisms of different EV subtypes, exosomes and microvesicles, loaded with anti-cancer agent, paclitaxel. We demonstrate differences in intracellular behavior and drug release profiles of paclitaxel-containing EVs. Exosomes seem to deliver the drug mostly by endocytosis while microvesicles enter the cells by both endocytosis and fusion with cell membrane. This research offers a new real-time method to investigate EV kinetics with living cells, and it is a potential advancement to complement the existing techniques. The findings of this study improve the current knowledge in exploiting EVs as next-generation targeted drug delivery systems. publishedVersion

In this work, we utilize a short-wavelength, 532-nm picosecond pulsed laser coupled with a time-gated complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) detector to acquire Raman spectra of several drugs of interest. With this approach, we are able to reveal previously unseen Raman features and suppress the fluorescence background of these drugs. Compared to traditional Raman setups, the present time-resolved technique has two major improvements. First, it is possible to overcome the strong fluorescence background that usually interferes with the much weaker Raman spectra. Second, using the high photon energy excitation light source, we are able to generate a stronger Raman signal compared to traditional instruments. In addition, observations in the time domain can be performed, thus enabling new capabilities in the field of Raman and fluorescence spectroscopy. With this system, we demonstrate for the first time the possibility of recording fluorescence-suppressed Raman spectra of solid, amorphous and crystalline, and non-photoluminescent and photoluminescent drugs such as caffeine, ranitidine hydrochloride, and indomethacin (amorphous and crystalline forms). The raw data acquired by utilizing only the picosecond pulsed laser and a CMOS SPAD detector could be used for identifying the compounds directly without any data processing. Moreover, to validate the accuracy of this time-resolved technique, we present density functional theory (DFT) calculations for a widely used gastric acid inhibitor, ranitidine hydrochloride. The obtained time-resolved Raman peaks were identified based on the calculations and existing literature. Raman spectra using non-time-resolved setups with continuous-wave 785- and 532-nm excitation lasers were used as reference data. Overall, this demonstration of time-resolved Raman and fluorescence measurements with a CMOS SPAD detector shows promise in diverse areas, including fundamental chemical research, the pharmaceutical setting, process analytical technology (PAT), and the life sciences. Graphical abstract Time-resolved Raman measurement of a pharmaceutical sample using the complementary metal-oxide semiconductor (CMOS) single photon avalanche diode (SPAD) detector technology Electronic supplementary material The online version of this article (doi:10.1007/s00216-015-9156-6) contains supplementary material, which is available to authorized users.

All cells expel a variety of nanosized extracellular vesicles (EVs), including exosomes, with composition reflecting the cells' biological state. Cancer pathology is dramatically mediated by EV trafficking via key proteins, lipids, metabolites, and microRNAs. Recent proteomics evidence suggests that tumor-associated exosomes exhibit distinct expression of certain membrane proteins, rendering those proteins as attractive targets for diagnostic or therapeutic application, yet it is not currently feasible to distinguish circulating EVs in complex biofluids according to their tissue of origin or state of disease. Here, peptide binding to tumor-associated EVs via overexpressed membrane protein is demonstrated. It is found that SKOV-3 ovarian tumor cells and their released EVs express alpha(3)beta(1) integrin, which can be targeted by the in-house cyclic nonapeptide, LXY30. After measuring bulk SKOV-3 EV association with LXY30 by flow cytometry, Raman spectral analysis of laser-trapped single exosomes with LXY30-dialkyne conjugate enables the differentiation of cancer-associated exosomes from noncancer exosomes. Furthermore, the foundation for a highly specific detection platform for tumor-EVs in solution with biosensor surface-immobilized LXY30 is introduced. LXY30 not only exhibits high specificity and affinity to alpha(3)beta(1) integrin-expressing EVs, but also reduces EV uptake into SKOV-3 parent cells, demonstrating the possibility for therapeutic application.

The aim of this work is to develop a platform for characterizing extracellular vesicles (EV) by using gold-polymer nanopillar SERS arrays simultaneously circumventing the photoluminescence-related disadvantages of Raman with a time-resolved approach. EVs are rich of biochemical information reporting of, for example, diseased state of the biological system. Currently, straightforward, label-free and fast EV characterization methods with low sample consumption are warranted. In this study, SERS spectra of red blood cell and platelet derived EVs were successfully measured and their biochemical contents analyzed using multivariate data analysis techniques. The developed platform could be conveniently used for EV analytics in general.

When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the “protein corona” associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-of-concept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent “hard” and “soft” coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (KD) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation. When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the "protein corona" associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-ofconcept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent "hard" and "soft" coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (K-D) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation.

Exosomes are small (~100nm) membrane bound vesicles excreted by cells as part of their normal biological processes. These extracellular vesicles are currently an area of intense research, since they were recently found to carry functional mRNA that allows transfer of proteins and other cellular instructions between cells. Exosomes have been implicated in a wide range of diseases, including cancer. Cancer cells are known to have increased exosome production, and may use those exosomes to prepare remote environments for metastasis. Therefore, there is a strong need to develop characterization methods to help understand the structure and function of these vesicles. However, current techniques, such as proteomics and genomics technologies, rely on aggregating a large amount of exosome material and reporting on chemical content that is averaged over many millions of exosomes. Here we report on the use of laser-tweezers Raman spectroscopy (LTRS) to probe individual vesicles, discovering distinct heterogeneity among exosomes both within a cell line, as well as between different cell lines. Through principal components analysis followed by hierarchical clustering, we have identified four “subpopulations” of exosomes shared across seven cell lines. The key chemical differences between these subpopulations, as determined by spectral analysis of the principal component loadings, are primarily related to membrane composition. Specifically, the differences can be ascribed to cholesterol content, cholesterol to phospholipid ratio, and surface protein expression. Thus, we have shown LTRS to be a powerful method to probe the chemical content of single extracellular vesicles.

In a recent paper by Su [ACS Photonics 2015 2, 1241–1245], a microtoroid resonator was demonstrated that is capable of detecting binding events of single exosomes, as well as providing other physical parameters such as size and mass. While we feel the method presented by Su is likely to find significant application in the basic study of exosomes, the clinical significance of this result is overstated in the article. As discussed below, the proof-of-concept results presented depend critically on a xenograft model that is not readily translated into a clinical setting.