Biomolecular Component Analysis of Phospholipids Composition in Live HeLa Cells

Utility of 1.5 Tesla MRI Scanner in the Management of Small Sample Sizes Driven from 3D Breast Cell Culture

The aim of this work was to use and optimize a 1.5 Tesla magnetic resonance imaging (MRI) system for three-dimensional (3D) images of small samples obtained from breast cell cultures in vitro. The basis of this study was to design MRI equipment to enable imaging of MCF-7 breast cancer cell cultures (about 1 million cells) in 1.5 and 2 mL glass tubes and/or bioreactors with an external diameter of less than 20 mm. Additionally, the development of software to calculate longitudinal and transverse relaxation times is described. Imaging tests were performed using a clinical MRI scanner OPTIMA 360 manufactured by GEMS. Due to the size of the tested objects, it was necessary to design additional receiving circuits allowing for the study of MCF-7 cell cultures placed in glass bioreactors. The examined sample's volume did not exceed 2.0 mL nor did the number of cells exceed 1 million. This work also included a modification of the sequence to allow for the analysis of T1 and T2 relaxation times. The analysis was performed using the MATLAB package (produced by MathWorks). The created application is based on medical MR images saved in the DICOM3.0 standard which ensures that the data analyzed are reliable and unchangeable in an unintentional manner that could affect the measurement results. The possibility of using 1.5 T MRI systems for cell culture research providing quantitative information from in vitro studies was realized. The scanning resolution for FOV = 5 cm and the matrix was achieved at a level of resolution of less than 0.1 mm/pixel. Receiving elements were built allowing for the acquisition of data for MRI image reconstruction confirmed by images of a phantom with a known structure and geometry. Magnetic resonance sequences were modified for the saturation recovery (SR) method, the purpose of which was to determine relaxation times. An application in MATLAB was developed that allows for the analysis of T1 and T2 relaxation times. The relaxation times of cell cultures were determined over a 6-week period. In the first week, the T1 time value was 1100 ± 40 ms, which decreased to 673 ± 59 ms by the sixth week. For T2, the results were 171 ± 10 ms and 128 ± 12 ms, respectively.

Attempts to Detect Lipid Metabolites from a Single Cell Using Proton-Transfer-Reaction Mass Spectrometry Coupled with Micro-Scale Supercritical Fluid Extraction: A Preliminary Study

Proton-transfer-reaction (PTR) mass spectrometry (MS), a widely used method for detecting trace-levels of volatile organic compounds in gaseous samples, can also be used for the analysis of small non-volatile molecules by using supercritical fluid as a transporter for the molecules. Supercritical fluid extraction (SFE) is a method that permits lipophilic compounds to be rapidly and selectively extracted from complex matrices. The combination of the high sensitivity of PTR MS with the SFE is a potentially novel method for analyzing small molecules in a single cell, particularly for the analysis of lipophilic compounds. We preliminarily evaluated this method for analyzing the components of a single HeLa cell that is fixed on a stainless steel frit and is then directly introduces the SFE extracts into the PTR MS. A total of 200/91 ions were observed in positive/negative ion mode time-of-flight mass spectra, and the masses of 11/10 ions could be matched to chemical formulae obtained from the LipidMaps lipids structure database. Using various authentic lipophilic samples, the method could be used to detect free fatty acids in the sub-femtomole to femtomole order in the negative ion mode, the femtomole to sub-picomole order for fat-soluble vitamins, and the picomole order for poly aromatic hydrocarbons in both the positive and negative ion mode.

Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600-1800 cm-1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey's multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

Surface Plasmon Localization-Based Super-resolved Raman Microscopy

We investigate label-free measurement of molecular distribution by super-resolved Raman microscopy using surface plasmon (SP) localization. Localized SP was formed with plasmonic nanopost arrays (PNAs) for measurement of the molecular distribution in HeLa cells. Compared with conventional Raman microscopy on gold thin films, PNAs induce a localized near-field, which allows for the enhancement of the peak signal-to-noise ratio by as much as 4.5 dB in the Raman shifts. Super-resolved distributions of aromatic amino acids and lipids (C-C stretching and C-H₂ twist mode) as targets in HeLa cells were obtained after image reconstruction. Results show almost 4-fold improvement on average in the lateral precision over conventional diffraction-limited Raman microscopy images. Combined with axial imaging in an evanescent field, the results suggest an improvement in optical resolution due to superlocalized light volume by more than an order of magnitude over that of conventional diffraction-limited Raman microscopy.

Quantitative label-free imaging of iron-bound transferrin in breast cancer cells and tumors

Transferrin (Tf) is an essential serum protein which delivers iron throughout the body via transferrin-receptor (TfR)-mediated uptake and iron release in early endosomes. Currently, there is no robust method to assay the population of iron-bound Tf in intact cells and tissues. Raman hyperspectral imaging detected spectral peaks that correlated with iron-bound Tf in intact cells and tumor xenografts sections (~1270-1300 cm-1). Iron-bound (holo) and iron-free (apo) human Tf forms were endocytosed by MDAMB231 and T47D human breast cancer cells. The Raman iron-bound Tf peak was identified in cells treated with holo-Tf, but not in cells incubated with apo-Tf. A reduction in the Raman peak intensity between 5 and 30 min of Tf internalization was observed in T47D, but not in MDAMB231, suggesting that T47D can release iron from Tf more efficiently than MDAMB231. MDAMB231 may display a disrupted iron homeostasis due to iron release delays caused by alterations in the pH or ionic milieu of the early endosomes. In summary, we have demonstrated that Raman hyperspectral imaging can be used to identify iron-bound Tf in cell cultures and tumor xenografts and detect iron release behavior of Tf in breast cancer cells.