| Literature DB >> 26410728 |
Nneka Dim1, Maryna Perepelyuk2, Olukayode Gomes3, Chellappagounder Thangavel4, Yi Liu5, Robert Den6, Ashakumary Lakshmikuttyamma7, Sunday A Shoyele8.
Abstract
BACKGROUND: siRNAs have a high potential for silencing critical molecular pathways that are pathogenic. Nevertheless, their clinical application has been limited by a lack of effective and safe nanotechnology-based delivery system that allows a controlled and safe transfection to cytosol of targeted cells without the associated adverse effects. Our group recently reported a very effective and safe hybrid nanoparticle delivery system composing human IgG and poloxamer-188 for siRNA delivery to cancer cells. However, these nanoparticles need to be optimized in terms of particle size, loading capacity and encapsulation efficiency. In the present study, we explored the effects of certain production parameters on particle size, loading capacity and encapsulation efficiency. Further, to make these nanoparticles more specific in their delivery of siRNA, we conjugated anti-NTSR1-mAb to the surface of these nanoparticles to target NTSR1-overexpressing cancer cells. The mechanism of siRNA release from these antiNTSR1-mAb functionalized nanoparticles was also elucidated.Entities:
Mesh:
Substances:
Year: 2015 PMID: 26410728 PMCID: PMC4583992 DOI: 10.1186/s12951-015-0124-2
Source DB: PubMed Journal: J Nanobiotechnology ISSN: 1477-3155 Impact factor: 10.435
Fig. 1Diagrammatic representation and TEM micrograph of the produced nanoparticle. a Nanoparticles at lower magnification. b Nanoparticles at higher magnification to show the internal arrangement of the components
The effects of variable parametes on particle size, PDI, zeta potential, encapsulation efficiency and loading capacity of nanoparticles (Mean ± SD, n = 3)
| Nanoparticle batch | Particle size (NM) | PDI | Zeta potential (mV) | Encapsulation efficiency (%) | Loading capacity (%) |
|---|---|---|---|---|---|
| IP-1 | 672.4 ± 17.9 | 0.08 ± 0.02 | +17.1 ± 0.8 | 41.1 ± 0.2 | 0.71 ± 0.02 |
| IP-2 | 424.6 ± 12.4 | 0.04 ± 0.01 | +17.3 ± 0.4 | 50.2 ± 0.4 | 1.23 ± 0.03 |
| IP-3 | 135.4 ± 5.4 | 0.07 ± 0.03 | +16.7 ± 0.2 | 60 ± 0.4 | 2.04 ± 0.06 |
| IP3-anti-NTSR1-mAb | 140.2 ± 2.4 | 0.2 ± 0.04 | 0.0 ± 0.3 | N/A | N/A |
| IP-4 | 716.1 ± 15.2 | 0.1 ± 0.04 | +17.4 ± 0.4 | 35.4 ± 0.4 | 0.62 ± 0.04 |
| IP-5 | 545.3 ± 14.3 | 0.06 ± 0.03 | +17.9 ± 0.3 | 40.3 ± 0.3 | 0.81 ± 0.03 |
| IP-6 | 389.2 ± 11.4 | 0.06 ± 0.05 | +17.5 ± 0.4 | 48.5 ± 0.5 | 1.21 ± 0.05 |
| IP-7 | 820.5 ± 12.4 | 0.08 ± 0.03 | +17.4 ± 0.5 | 30.3 ± 0.1 | 0.53 ± 0.02 |
| IP-8 | 799.3 ± 11.4 | 0.1 ± 0.04 | +16.9 ± 0.6 | 37.3 ± 0.3 | 0.65 ± 0.03 |
| IP-9 | 589.3 ± 10.4 | 0.09 ± 0.05 | +17.2 ± 0.3 | 42.6 ± 0.4 | 0.82 ± 0.04 |
PDI polydispersity index
Fig. 2-FI-IR spectra showing the conjugation of anti-NTSR1-mAb to hybrid nanoparticles (a) incomparison to non-functionalized nanoparticles (b)
Fluorecent intensities of anti-NTSR1-mAb functionalized hybrid nanoparticles was compared to that of the non-functionalized, PBS solution and free sheep antimurine IgG labelled with FITC (Mean ± SD, n = 3)
| Sample | Fluorescent intensity |
|---|---|
| Anti-NTSR1-mAb functionalized nanoparticles | 2435.1 ± 7.5 |
| Non-functionalized nanoparticles | 436.2 ± 3.4 |
| PBS | 314.3 ± 5.1 |
| Sheep antimurine IgG-FITC | 1134 ± 10.3 |
Fig. 3Comparison of in vitro siRNA release profile from siRNA encapsulated anti-NTSR1-mAb functionalized and non-functionalized nanoparticles at pH 5 and 7. siRNA was more efficiently released at pH 5 due to the superior solubility of human IgG at that pH. Functionalization of the nanoparticles did not seem to affect the release rate at each of the pH values. n = 3 for each sample point
Mathematical models and parameters based on siRNA release data from non-functionalized nanoparticles
| PH | Correlation (R) | n value for Korsmeyer–Peppas | ||||
|---|---|---|---|---|---|---|
| Zero order | First-order | Higuchi | Hixson–Crowell | Korsmeyer–Peppas | ||
| 7.4 | 0.6578 | 0.3456 | 0.6877 | 0.3455 | 0.5456 | 0.35 |
| 5 | 0.4567 | 0.5673 | 0.9856 | 0.4563 | 0.9856 | 0.67 |
Mathematical models and parameters based on siRNA release data from NTSR1-functionalized nanoparticles
| PH | Correlation (R) | n value for Korsmeyer–Peppas | ||||
|---|---|---|---|---|---|---|
| Zero order | First-order | Higuchi | Hixson–Crowell | Korsmeyer–Peppas | ||
| 7.4 | 0.4537 | 0.6784 | 0.4579 | 0.4536 | 0.4563 | 0.34 |
| 5 | 0.4567 | 0.4675 | 0.9754 | 0.5647 | 0.9789 | 0.64 |
Fig. 4Reverse transcriptase PCR showing the expression of neurotensin receptor 1 (NTSR1) in A549 and H23 cell lines
Fig. 5Fluorescence micrograph showing the delivery of siGLO into the cytosol of A549 cells using the NTSR1-mAb-functionalized hybrid nanoparticles. The upper panel shows the inhibition of siGLO delivery following an initial treatment of the cells with neurotensin
Fig. 6Fluorescence micrograph showing the delivery of siGLO into the cytosol of H23 cells using the NTSR1-mAb-functionalized hybrid nanoparticles. The upper panel shows the inhibition of siGLO delivery following an initial treatment of the cells with neurotensin
Fig. 7Probing the effect of inhibition of neurotensin receptor 1 (NTSR1) with neurotensin on the internalization of siRNA-loaded targeted hybrid nanoparticles in A549 and H23 cells using flow cytometry (n = 3)
Fig. 8Reaction schemes for the attachment of anti-NTSR1-mAb to hybrid nanoparticles
Variable parameters used in the formulation of different nanoparticle batches
| Nanoparticle batch | Concentration of human IgG (mg/mL) | Concentration of poloxamer-188 (%w/v) | Magnetic stirring rate (rpm) | Amount of siRNA (µg) |
|---|---|---|---|---|
| IP-1 | 5 | 0.2 | 125 | 187 |
| IP-2 | 5 | 0.2 | 250 | 187 |
| IP-3 | 5 | 0.2 | 350 | 187 |
| IP-4 | 7.5 | 0.2 | 125 | 187 |
| IP-5 | 7.5 | 0.2 | 250 | 187 |
| IP-6 | 7.5 | 0.2 | 350 | 187 |
| IP-7 | 10 | 0.2 | 125 | 187 |
| IP-8 | 10 | 0.2 | 250 | 187 |
| IP-9 | 10 | 0.2 | 350 | 187 |