Dataset Information

Precise quantification of nanoparticle internalization.

ABSTRACT: Nanoparticles have opened new exciting avenues for both diagnostic and therapeutic applications in human disease, and targeted nanoparticles are increasingly used as specific drug delivery vehicles. The precise quantification of nanoparticle internalization is of importance to measure the impact of physical and chemical properties on the uptake of nanoparticles into target cells or into cells responsible for rapid clearance. Internalization of nanoparticles has been measured by various techniques, but comparability of data between different laboratories is impeded by lack of a generally accepted standardized assay. Furthermore, the distinction between associated and internalized particles has been a challenge for many years, although this distinction is critical for most research questions. Previously used methods to verify intracellular location are typically not quantitative and do not lend themselves to high-throughput analysis. Here, we developed a mathematical model which integrates the data from high-throughput flow cytometry measurements with data from quantitative confocal microscopy. The generic method described here will be a useful tool in biomedical nanotechnology studies. The method was then applied to measure the impact of surface coatings of vesosomes on their internalization by cells of the reticuloendothelial system (RES). RES cells are responsible for rapid clearance of nanoparticles, and the resulting fast blood clearance is one of the major challenges in biomedical applications of nanoparticles. Coating of vesosomes with long chain polyethylene glycol showed a trend for lower internalization by RES cells.

SUBMITTER: Gottstein C

PROVIDER: S-EPMC3767576 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Precise quantification of nanoparticle internalization.

Gottstein Claudia C Wu Guohui G Wong Benjamin J BJ Zasadzinski Joseph Anthony JA

ACS nano 20130603 6

Nanoparticles have opened new exciting avenues for both diagnostic and therapeutic applications in human disease, and targeted nanoparticles are increasingly used as specific drug delivery vehicles. The precise quantification of nanoparticle internalization is of importance to measure the impact of physical and chemical properties on the uptake of nanoparticles into target cells or into cells responsible for rapid clearance. Internalization of nanoparticles has been measured by various technique ...[more]

PMID: 23706031

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Project description:BackgroundMass spectrometry based quantification of peptides can be performed using the iTRAQ reagent in conjunction with mass spectrometry. This technology yields information about the relative abundance of single peptides. A method for the calculation of reliable quantification information is required in order to obtain biologically relevant data at the protein expression level.ResultsA method comprising sound error estimation and statistical methods is presented that allows precise abundance analysis plus error calculation at the peptide as well as at the protein level. This yields the relevant information that is required for quantitative proteomics. Comparing the performance of our method named Quant with existing approaches the error estimation is reliable and offers information for precise bioinformatic models. Quant is shown to generate results that are consistent with those produced by ProQuant, thus validating both systems. Moreover, the results are consistent with that of Mascot 2.2. The MATLAB scripts of Quant are freely available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/, each under the GNU Lesser General Public License.ConclusionThe software Quant demonstrates improvements in protein quantification using iTRAQ. Precise quantification data can be obtained at the protein level when using error propagation and adequate visualization. Quant integrates both and additionally provides the possibility to obtain more reliable results by calculation of wise quality measures. Peak area integration has been replaced by sum of intensities, yielding more reliable quantification results. Additionally, Quant allows the combination of quantitative information obtained by iTRAQ with peptide and protein identifications from popular tandem MS identification tools. Hence Quant is a useful tool for the proteomics community and may help improving analysis of proteomic experimental data. In addition, we have shown that a lognormal distribution fits the data of mass spectrometry based relative peptide quantification.

Dataset Information

Precise quantification of nanoparticle internalization.

Publications

Precise quantification of nanoparticle internalization.

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