Optimization of SERS Tag Intensity, Binding Footprint, and Emittance

Nanoparticle surface enhanced Raman scattering (SERS) tags have attracted interest as labels for use in a variety of applications, including biomolecular assays. An obstacle to progress in this area is a lack of standardized approaches to compare the brightness of different SERS tags within and between laboratories. Here we present an approach based on binding of SERS tags to beads with known binding capacities that allows evaluation of the average intensity, the relative binding footprint of particles in a SERS tag preparation, and the size-normalized intensity or emittance. We tested this on four different SERS tag compositions and show that aggregated gold nanorods produce SERS tags that are 2–4 times brighter than relatively more monodisperse nanorods, but that the aggregated nanorods are also correspondingly larger, which may negate the intensity if steric hindrance limits the number of tags bound to a target. By contrast, SERS tags prepared from smaller gold nanorods coated with a silver shell produce SERS tags that are 2–3 times brighter, on a size-normalized basis, than the Au nanorod-based tags, resulting in labels with improved performance in SERS-based image and flow cytometry assays. SERS tags based on red-resonant Ag plates showed similarly bright signals and small footprint. This approach to evaluating SERS tag brightness is general, uses readily available reagents and instruments, and should be suitable for interlab comparisons of SERS tag brightness

Additional file 1 of Serpin-loaded extracellular vesicles promote tissue repair in a mouse model of impaired wound healing

Additional file 1: Figure S1. Statistical analysis of CD marker expression in PVA infiltrates at various time points. In support of the piechart analyses in Fig. 1, immune cells infiltrating PVA sponges were quantified at each time point focusing on: a Macrophages, b Inflammatory monocytes, c Neutrophils, d Dendritic cells, and e T cells (p-value: ***<0.001, **<0.005, *<0.05). Figure S2. Evaluation of EV biogenesis related gene expression in the PVA cells by qRT-PCR depending on the 2, 7, and 14 days. Measurements of changes in gene expression normalized to GAPDH in cells infiltrating PVA sponges focusing on the following canonical biogeneis genes: a Rab5a, b Rab5b, c Rab27, d Rab27b e Rab11a, f VPS4a, g TSG101, and h Rab35 (p-value: **<0.005, *<0.05). Figure S3. Analysis of baseline cell infiltrate in PVA sponges of WT vs. db/db mice, from which EVs were harvested. Flow cytometry analysis of immune cells recruited to the PVA sponge at 14 days post-implantation focusing on : a monoyctes based on CD11b+Ly6Chigh cells as a subset of CD45+ cells, b neutrophils based on Ly6G+Ly6Clow cells as a subset of CD45+ cells, c macrophages based on CD11b+F4/80+ cells as a subset of CD45+ cells, d DCs based on MHCII+ cells as a subest of CD11b+CD11c+ cells, e T cells based on CD4+ cells as a subset of CD3+ cells, f CD8+ T cells as a subset of CD3+ cells, and g Regulatory T cells based on CD4+CD25+ as a subset of CD3+ cells. (p-value: *<0.05). Figure S4. Validation of EVs derived from WT and db/db mice by vFRed analysis. a Size distribution of WT EVs. b Plot diameter data of WT EVs. c Expression of Annexin V-PE on WT EVs. d Expression of tetraspanins CD9, CD63 and CD81 (TS-PE)on WT EVs. e Histogram of Annexin V-PE expression on WT EVs normalized to buffer only (grey filled in). f Histogram of TS-PE on WT EVs normalized to buffer only (grey filled in). g Size distribution of db/db EVs. h Plot diameter data of db/db EVs. i Expression of Annexin V-PE on db/db EVs. j Expression of TS-PE on db/db EVs. k Histogram of Annexin V-PE expression on db/db EVs normalized to buffer only (grey filled in). l Histogram of TS-PE on db/db EVs normalized to buffer only (grey filled in). Figure S5. Validation of lentivirus titer testing using HEK293 cells. a Representative comparison of lentivirus yields b based on titer testing of lentiviral p24 protein using GoStix analysis per manufacturers recommendations. Figure S6. A representative example of the analysis of EVs engineered to express specific proteins. a EVs collected from the conditioned media of parental cells as a negative control (Left, naïve HEK293 donor cells) and enriched by density ultracentrifugation were subjected to vFRED staining to determine EV diameter as described in the Materials and Methods. GFP-loaded EVs (XP-GFP) in absence (Left) or presence (Right) of anti-CD81-PE tetraspanin were analyzed for b GFP fluorescence and c expression of CD81. d and e An overview and quantification of GFP-EV internalization into HEK293 cells (filled in) compared to buffer control (open). Figure S7. Quantification of K14 immunohistochemistry. The fluorescent intensity of ant-K14 stained tissue sections from Figure 5l were quantified using Image J. A minimum of 3 fields were analyzed for each of the EV treated samples (p-value: * <0.05). Table S1. Detail information of primer for extracellular vesicle biogenesis related genes. Table S2. Primer sequences for cloning of XP tag in-frame with SERPINA1, SERPINF2, and SERPING1

Additional file 2 of Serpin-loaded extracellular vesicles promote tissue repair in a mouse model of impaired wound healing

Additional File 2: Proteomic data from the Mass Spectrometry analysis of proteins detected in EVs from wild-type and diabetic db/db mice

Total EV yield as determined by NTA and TRPS.

<p>Total EV yield as determined by NTA and TRPS.</p

EV quantitative analysis.

<p><b>(A)</b> Schematic representation of protocol used for the isolation of CSF microvesicles and exosomes. <b>(B)</b> In nanoparticles tracking analysis, light scattered by EVs is captured by digital camera over a series of frames. The rate of the particle movement is then used to calculate particle size using the Stokes—Einstein equation. <b>(C)</b> In tunable resistive pulse sensing, EVs change the electrical resistance as they pass through a pore-based sensor resulting in a resistive pulse signal. Signals obtained from the measurements can then be used to calculate the size, concentration and charge of each particle by correlating the signal back to a set of known standards. <b>(D)</b> In Vesicle flow cytometry, EVs were stained with an optimized concentration of a fluorogenic lipophilic probe, di-8-ANEPPS, and detected on a custom high sensitivity flow cytometer. Vesicle diameter was estimated by comparison to di-8-stained liposomes.</p

Comparison of EV quantification by NTA and TRPS.

<p>EVs were isolated from CSF collected from glioblastoma patients by differential centrifugation into microvesicle (10,000×g) and exosome (120,000×g) fractions, and resuspended in PBS. Isolated EVs were analyzed by NTA or TRPS. <b>(A)</b> Size profile of CSF exosomes determined by NTA and TRPS. <b>(B)</b> Size profile of CSF microvesicles determined by NTA and TRPS. <b>(C)</b> Comparison of EV yield by size ranges.</p

Total EV as determined by NTA and VFC.

<p>Total EV as determined by NTA and VFC.</p

EV yield by size range as determined by NTA and TRPS.

<p>EV yield by size range as determined by NTA and TRPS.</p

Comparison of EV quantification by NTA and VFC.

<p>CSF EVs isolated by differential centrifugation into microvesicle (10,000×g) and exosome (120,000×g) fractions were analyzed by NTA or VFC. <b>(A)</b> Size profile of CSF exosomes determined by NTA and VFC. <b>(B)</b> Size profile of CSF microvesicles determined by NTA and VFC. <b>(C)</b> Comparison of EV yield by size ranges.</p

Comparison of EV quantification by NTA and TEM.

<p>CSF EVs were fractionated into microvesicles (10,000×g) and exosomes (120,000×g) by differential ultracentrifugation and then analyzed by NTA and TEM. <b>(A)</b> Representative TEM images, scale bar = 200nm. <b>(B)</b> Total EV count as determined by NTA and TEM. Fold difference in particle detected between NTA and TEM is denoted.</p