Fabrication of plasmonic probes for reproducible nanospectroscopic investigation of lipid monolayers - The electrochemical etching with DC-pulsed voltage.

Tip-enhanced Raman spectroscopy (TERS) is a label-free analytical technique that characterizes molecular systems, potentially even with a nanometric resolution. In principle, the metallic plasmonic probe is illuminated with a laser beam generating the localized surface plasmons, which induce a strong local electric field enhancement in close proximity to the probe. Such field enhancement improves the Raman scattering cross-section from the sample volume localized near the probe apex. TERS provides a high spatial resolution and a great sensitivity, however, it is rather rarely used due to technical limitations causing unstable enhancement and the relative lack of data reproducibility. Despite many scientific efforts for the fabrication of effective TER probes providing robust TER enhancement still requires further investigations. In this work, we explore new possibilities based on preparation of scanning tunnelling microscopy (STM) plasmonic probes, since by nature of the tunnelling effect, they potentially could offer a very high spatial resolution in STM guided TERS experiments. Here we compare two methods of STM-TERS probe preparation for effective spectra acquisition. Our results strongly indicate that an application of square pulse voltage upon the etching procedure significantly improves the quality of the TER data over those obtained with a constant voltage one. To demonstrate the efficiency of our probes we present the results of hyperspectral TER mapping of the 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE) monolayer deposited on an ultra-pure and atomically flat gold substrate.

Molecular alterations in metaphase chromosomes induced by bleomycin.

Chromosomes are intranuclear structures, their main function is to store and transmit genetic information during cell division. They are composed of tightly packed DNA in the form of chromatin, which is constantly exposed to various damaging factors. The resulting changes in DNA can have serious consequences (e.g. mutations) if they are not repaired or repaired incorrectly. In this article, we studied chromosomes isolated from human cervical cancer cells (HeLa) exposed to a genotoxic drug causing both single- and double-strand breaks. Specifically, we used bleomycin to induce DNA damage. We followed morphological and chemical changes in chromosomes upon damage induction. Atomic force microscopy was used to visualize the morphology of chromosomes, while Raman microspectroscopy enabled the detection of changes in the chemical structure of chromatin with the resolution close to the diffraction limit. Additionally, we extracted spectra corresponding to chromosome I or chromatin from hyperspectral Raman maps with convolutional neural networks (CNN), which were further analysed with the principal component analysis (PCA) algorithm to reveal molecular markers of DNA damage in chromosomes. The applied multimodal approach revealed simultaneous morphological and molecular changes, including chromosomal aberrations, alterations in DNA conformation, methylation pattern, and increased protein expression upon the bleomycin treatment at the level of the single chromosome.

Combined analytical approach empowers precise spectroscopic interpretation of subcellular components of pancreatic cancer cells.

The lack of specific and sensitive early diagnostic options for pancreatic cancer (PC) results in patients being largely diagnosed with late-stage disease, thus inoperable and burdened with high mortality. Molecular spectroscopic methodologies, such as Raman or infrared spectroscopies, show promise in becoming a leader in screening for early-stage cancer diseases, including PC. However, should such technology be introduced, the identification of differentiating spectral features between various cancer types is required. This would not be possible without the precise extraction of spectra without the contamination by necrosis, inflammation, desmoplasia, or extracellular fluids such as mucous that surround tumor cells. Moreover, an efficient methodology for their interpretation has not been well defined. In this study, we compared different methods of spectral analysis to find the best for investigating the biomolecular composition of PC cells cytoplasm and nuclei separately. Sixteen PC tissue samples of main PC subtypes (ductal adenocarcinoma, intraductal papillary mucinous carcinoma, and ampulla of Vater carcinoma) were collected with Raman hyperspectral mapping, resulting in 191,355 Raman spectra and analyzed with comparative methodologies, specifically, hierarchical cluster analysis, non-negative matrix factorization, T-distributed stochastic neighbor embedding, principal components analysis (PCA), and convolutional neural networks (CNN). As a result, we propose an innovative approach to spectra classification by CNN, combined with PCA for molecular characterization. The CNN-based spectra classification achieved over 98% successful validation rate. Subsequent analyses of spectral features revealed differences among PC subtypes and between the cytoplasm and nuclei of their cells. Our study establishes an optimal methodology for cancer tissue spectral data classification and interpretation that allows precise and cognitive studies of cancer cells and their subcellular components, without mixing the results with cancer-surrounding tissue. As a proof of concept, we describe findings that add to the spectroscopic understanding of PC.

Variabilities in global DNA methylation and ß-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer.

PURPOSE: Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue. METHODS: Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues. RESULTS: The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of ß-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies. CONCLUSIONS: Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and ß-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing.

Raman Research on Bleomycin-Induced DNA Strand Breaks and Repair Processes in Living Cells.

Even several thousands of DNA lesions are induced in one cell within one day. DNA damage may lead to mutations, formation of chromosomal aberrations, or cellular death. A particularly cytotoxic type of DNA damage is single- and double-strand breaks (SSBs and DSBs, respectively). In this work, we followed DNA conformational transitions induced by the disruption of DNA backbone. Conformational changes of chromatin in living cells were induced by a bleomycin (BLM), an anticancer drug, which generates SSBs and DSBs. Raman micro-spectroscopy enabled to observe chemical changes at the level of single cell and to collect hyperspectral images of molecular structure and composition with sub-micrometer resolution. We applied multivariate data analysis methods to extract key information from registered data, particularly to probe DNA conformational changes. Applied methodology enabled to track conformational transition from B-DNA to A-DNA upon cellular response to BLM treatment. Additionally, increased expression of proteins within the cell nucleus resulting from the activation of repair processes was demonstrated. The ongoing DNA repair process under the BLM action was also confirmed with confocal laser scanning fluorescent microscopy.

Revealing local molecular distribution, orientation, phase separation, and formation of domains in artificial lipid layers: Towards comprehensive characterization of biological membranes.

Lipids, together with molecules such as DNA and proteins, are one of the most relevant systems responsible for the existence of life. Selected lipids are able to assembly into various organized structures, such as lipid membranes. The unique properties of lipid membranes determine their complex functions, not only to separate biological environments, but also to participate in regulatory functions, absorption of nutrients, cell-cell communication, endocytosis, cell signaling, and many others. Despite numerous scientific efforts, still little is known about the reason underlying the variability within lipid membranes, and its biochemical significance. In this review, we discuss the structural complexity of lipid membranes, as well as the importance to simplify studied systems in order to understand phenomena occurring in natural, complex membranes. Such systems require a model interface to be analyzed. Therefore, here we focused on analytical studies of artificial systems at various interfaces. The molecular structure of lipid membranes, specifically the nanometric thickens of molecular bilayer, limits in a major extent the choice of highly sensitive methods suitable to study such structures. Therefore, we focused on methods that combine high sensitivity, and/or chemical selectivity, and/or nanometric spatial resolution, such as atomic force microscopy, nanospectroscopy (tip-enhanced Raman spectroscopy, infrared nanospectroscopy), phase modulation infrared reflection-absorption spectroscopy, sum-frequency generation spectroscopy. We summarized experimental and theoretical approaches providing information about molecular structure and composition, lipid spatial distribution (phase separation), organization (domain shape, molecular orientation) of lipid membranes, and real-time visualization of the influence of various molecules (proteins, drugs) on their integrity. An integral part of this review discusses the latest achievements in the field of lipid layer-based biosensors.

Molecular Spectroscopic Markers of Abnormal Protein Aggregation.

Abnormal protein aggregation has been intensively studied for over 40 years and broadly discussed in the literature due to its significant role in neurodegenerative diseases etiology. Structural reorganization and conformational changes of the secondary structure upon the aggregation determine aggregation pathways and cytotoxicity of the aggregates, and therefore, numerous analytical techniques are employed for a deep investigation into the secondary structure of abnormal protein aggregates. Molecular spectroscopies, including Raman and infrared ones, are routinely applied in such studies. Recently, the nanoscale spatial resolution of tip-enhanced Raman and infrared nanospectroscopies, as well as the high sensitivity of the surface-enhanced Raman spectroscopy, have brought new insights into our knowledge of abnormal protein aggregation. In this review, we order and summarize all nano- and micro-spectroscopic marker bands related to abnormal aggregation. Each part presents the physical principles of each particular spectroscopic technique listed above and a concise description of all spectral markers detected with these techniques in the spectra of neurodegenerative proteins and their model systems. Finally, a section concerning the application of multivariate data analysis for extraction of the spectral marker bands is included.