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1.
Analyst ; 145(11): 3983-3995, 2020 Jun 07.
Article in English | MEDLINE | ID: mdl-32322872

ABSTRACT

The design of nanoparticles for application in medical diagnostics and therapy requires a thorough understanding of various aspects of nanoparticle-cell interactions. In this work, two unconventional methods for the study of nanoparticle effects on cells, Raman spectroscopy and atomic force microscopy (AFM), were employed to track the molecular and morphological changes that are caused by the interaction between cervical carcinoma-derived HeLa cells and two types of cerium dioxide (CeO2) nanoparticles, ones with dextran coating and the others with no coating. Multivariate statistical analyses of Raman spectra, such as principal component analysis and partial least squares regression, were applied in order to extract the variations in the vibrational features of cell biomolecules and through them, the changes in biomolecular content and conformation. Both types of nanoparticles induced changes in DNA, lipid and protein contents of the cell and variations of the protein secondary structure, whereas dextran-coated CeO2 affected the cell-growth rate to a higher extent. Atomic force microscopy showed changes in cell roughness, cell height and nanoparticle effects on surface molecular layers. The method differentiated between the impact of dextran-coated and uncoated CeO2 nanoparticles with higher precision than performed viability tests. Due to the holistic approach provided by vibrational information on the overall cell content, accompanied by morphological modifications observed by high-resolution microscopy, this methodology offers a wider picture of nanoparticle-induced cell changes, in a label-free single-cell manner.


Subject(s)
Cell Membrane/drug effects , Metal Nanoparticles/chemistry , Pseudopodia/drug effects , Cell Membrane/chemistry , Cerium/chemistry , Dextrans/chemistry , HeLa Cells , Humans , Microscopy, Atomic Force , Principal Component Analysis , Pseudopodia/chemistry , Regression Analysis , Spectrum Analysis, Raman , Surface Properties
2.
Sci Rep ; 9(1): 12653, 2019 09 02.
Article in English | MEDLINE | ID: mdl-31477762

ABSTRACT

Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.


Subject(s)
Spectrum Analysis, Raman , Cell Differentiation/drug effects , Cell Survival/drug effects , Doxorubicin/pharmacology , Humans , Principal Component Analysis , Support Vector Machine , THP-1 Cells
3.
Analyst ; 144(15): 4488-4492, 2019 Aug 07.
Article in English | MEDLINE | ID: mdl-31287453

ABSTRACT

High-throughput screening Raman spectroscopy (HTS-RS) with automated localization algorithms offers unsurpassed speed and sensitivity to investigate the effect of dithiothreitol on the diatom Phaedactylum tricornutum. The HTS-RS capability that was demonstrated for this model system can be transferred to unmet analytical applications such as kinetic in vivo studies of microalgal assemblages.


Subject(s)
Diatoms/drug effects , Dithiothreitol/pharmacology , Algorithms , Diatoms/radiation effects , High-Throughput Screening Assays/methods , Light , Spectrum Analysis, Raman/methods , Xanthophylls/chemistry , Xanthophylls/metabolism
4.
Analyst ; 144(7): 2367-2374, 2019 Mar 25.
Article in English | MEDLINE | ID: mdl-30793720

ABSTRACT

Caenorhabditis elegans is an animal model frequently used in research on the effects of metabolism on organismal aging. This comes with a requirement for methods to investigate metabolite content, turnover, and distribution. The aim of our study was to assess the use of a label-free approach to determine both content and distribution of glycogen, the storage form of glucose, in C. elegans. To this end, we grew C. elegans worms under three different dietary conditions for 24-48 h, representing starvation, regular diet and a high glucose diet, followed by analysis of glycogen content. Glycogen analysis was performed on fixed individual whole worms using Raman micro-spectroscopy (RMS). Results were confirmed by comparison with two conventional assays, i.e. iodine staining of worms and enzymatic determination of glycogen. RMS was further used to assess overall lipid and protein content and distribution in the same samples used for glycogen analysis. Expectedly, both glycogen and lipid content were highest in worms grown on a high glucose diet, lower in regularly fed, and lowest in starved nematodes. In summary, RMS is a method suitable for analysis of glycogen content in C. elegans that has the advantage over established methods that (i) individual worms (rather than hundreds per sample) can be analyzed, (ii) glycogen distribution can be assessed at subcellular resolution and (iii) the distribution patterns of other macromolecules can be assessed from the same worms. Thus, RMS has the potential to be used as a sensitive, accurate, cost-effective and high throughput method to evaluate glycogen stores in C. elegans.


Subject(s)
Caenorhabditis elegans/metabolism , Glycogen/metabolism , Spectrum Analysis, Raman , Animals , Caenorhabditis elegans Proteins/metabolism , Iodides/metabolism , Iodine/metabolism , Lipid Metabolism
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