Label-free Raman microspectral analysis for comparison of cellular uptake and distribution between nontargeted and EGFR-targeted biodegradable polymeric nanoparticles

Chernenko, T. V.; Buyukozturk, Fulden; Miljković, Miloš D.; Carrier, Rebecca L.; Diem, Max; Amiji, Mansoor M.

doi:10.1007/s13346-013-0178-3

Cited by 22 publications

(25 citation statements)

References 33 publications

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“…Chernenko et al . demonstrated the compartmentalisation of PEG-PCL nanoparticles in secondary endosomes of Hela cells by following the vibrational signature of PCL molecules and their released cargo using label-free Raman imaging 46 47 . The ability to distinguish specific routes of cellular uptake would be beneficial in defining the sub-cellular partitioning of either PMs and payload and could be investigated in future experiments, but the quantification of payload released intracellularly is equally important.…”

Section: Resultsmentioning

confidence: 99%

Quantification of intracellular payload release from polymersome nanoparticles

Scarpa

Bailey

Janeczek

et al. 2016

Sci Rep

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Polymersome nanoparticles (PMs) are attractive candidates for spatio-temporal controlled delivery of therapeutic agents. Although many studies have addressed cellular uptake of solid nanoparticles, there is very little data available on intracellular release of molecules encapsulated in membranous carriers, such as polymersomes. Here, we addressed this by developing a quantitative assay based on the hydrophilic dye, fluorescein. Fluorescein was encapsulated stably in PMs of mean diameter 85 nm, with minimal leakage after sustained dialysis. No fluorescence was detectable from fluorescein PMs, indicating quenching. Following incubation of L929 cells with fluorescein PMs, there was a gradual increase in intracellular fluorescence, indicating PM disruption and cytosolic release of fluorescein. By combining absorbance measurements with flow cytometry, we quantified the real-time intracellular release of a fluorescein at a single-cell resolution. We found that 173 ± 38 polymersomes released their payload per cell, with significant heterogeneity in uptake, despite controlled synchronisation of cell cycle. This novel method for quantification of the release of compounds from nanoparticles provides fundamental information on cellular uptake of nanoparticle-encapsulated compounds. It also illustrates the stochastic nature of population distribution in homogeneous cell populations, a factor that must be taken into account in clinical use of this technology.

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Section: Resultsmentioning

confidence: 99%

Quantification of intracellular payload release from polymersome nanoparticles

Scarpa

Bailey

Janeczek

et al. 2016

Sci Rep

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“…Raman microspectroscopy provides high-resolution imaging combined with chemical analysis without destruction of the biological sample and the use of labels [ 126 – 128 ]. Intrinsic chemical bond vibrations can be visualized and characterized combined with optical sectioning with diffraction-limited spatial resolution that can be approximated to 1 µm [ 129 – 130 ]. This technique has been used, for example, in in vivo and diagnostic imaging of various cancers in humans [ 131 ].…”

Section: Reviewmentioning

confidence: 99%

Overview about the localization of nanoparticles in tissue and cellular context by different imaging techniques

Ostrowski¹,

Nordmeyer²,

Boreham³

et al. 2015

Beilstein J. Nanotechnol.

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SummaryThe increasing interest and recent developments in nanotechnology pose previously unparalleled challenges in understanding the effects of nanoparticles on living tissues. Despite significant progress in in vitro cell and tissue culture technologies, observations on particle distribution and tissue responses in whole organisms are still indispensable. In addition to a thorough understanding of complex tissue responses which is the domain of expert pathologists, the localization of particles at their sites of interaction with living structures is essential to complete the picture. In this review we will describe and compare different imaging techniques for localizing inorganic as well as organic nanoparticles in tissues, cells and subcellular compartments. The visualization techniques include well-established methods, such as standard light, fluorescence, transmission electron and scanning electron microscopy as well as more recent developments, such as light and electron microscopic autoradiography, fluorescence lifetime imaging, spectral imaging and linear unmixing, superresolution structured illumination, Raman microspectroscopy and X-ray microscopy. Importantly, all methodologies described allow for the simultaneous visualization of nanoparticles and evaluation of cell and tissue changes that are of prime interest for toxicopathologic studies. However, the different approaches vary in terms of applicability for specific particles, sensitivity, optical resolution, technical requirements and thus availability, and effects of labeling on particle properties. Specific bottle necks of each technology are discussed in detail. Interpretation of particle localization data from any of these techniques should therefore respect their specific merits and limitations as no single approach combines all desired properties.

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“…The VCA algorithm has been used in monitoring cellular uptake [ 30 ], in depicting the distribution of amygdalin in apricot seeds [ 31 ], in giving insights into the plant cell wall structure [ 32 ], in the selection of marker spectra of hyperspectral images of leafs in order to determine the pigment content [ 33 ] or in unmixing optoacoustic data [ 34 ]. VCA assumes that all pixels in the image are in a space (simplex of a determined order depending on the number of endmembers) defined by the purest components (vertices) called endmembers (EM) and that the affine transformation of a simplex is also a simplex.…”

Section: Introductionmentioning

confidence: 99%

Multivariate unmixing approaches on Raman images of plant cell walls: new insights or overinterpretation of results?

et al. 2018

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BackgroundPlant cell walls are nanocomposites based on cellulose microfibrils embedded in a matrix of polysaccharides and aromatic polymers. They are optimized for different functions (e.g. mechanical stability) by changing cell form, cell wall thickness and composition. To reveal the composition of plant tissues in a non-destructive way on the microscale, Raman imaging has become an important tool. Thousands of Raman spectra are acquired, each one being a spatially resolved molecular fingerprint of the plant cell wall. Nevertheless, due to the multicomponent nature of plant cell walls, many bands are overlapping and classical band integration approaches often not suitable for imaging. Multivariate data analysing approaches have a high potential as the whole wavenumber region of all thousands of spectra is analysed at once.ResultsThree multivariate unmixing algorithms, vertex component analysis, non-negative matrix factorization and multivariate curve resolution–alternating least squares were applied to find the purest components within datasets acquired from micro-sections of spruce wood and Arabidopsis. With all three approaches different cell wall layers (including tiny S1 and S3 with 0.09–0.14 µm thickness) and cell contents were distinguished and endmember spectra with a good signal to noise ratio extracted. Baseline correction influences the results obtained in all methods as well as the way in which algorithm extracts components, i.e. prioritizing the extraction of positive endmembers by sequential orthogonal projections in VCA or performing a simultaneous extraction of non-negative components aiming at explaining the maximum variance in NMF and MCR-ALS. Other constraints applied (e.g. closure in VCA) or a previous principal component analysis filtering step in MCR-ALS also contribute to the differences obtained. ConclusionsVCA is recommended as a good preliminary approach, since it is fast, does not require setting many input parameters and the endmember spectra result in good approximations of the raw data. Yet the endmember spectra are more correlated and mixed than those retrieved by NMF and MCR-ALS methods. The latter two give the best model statistics (with lower lack of fit in the models), but care has to be taken about overestimating the rank as it can lead to artificial shapes due to peak splitting or inverted bands. Electronic supplementary materialThe online version of this article (10.1186/s13007-018-0320-9) contains supplementary material, which is available to authorized users.

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Label-free Raman microspectral analysis for comparison of cellular uptake and distribution between nontargeted and EGFR-targeted biodegradable polymeric nanoparticles

Cited by 22 publications

References 33 publications

Quantification of intracellular payload release from polymersome nanoparticles

Quantification of intracellular payload release from polymersome nanoparticles

Overview about the localization of nanoparticles in tissue and cellular context by different imaging techniques

Multivariate unmixing approaches on Raman images of plant cell walls: new insights or overinterpretation of results?

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