Making colourful sense of Raman images of single cells

In order to understand biological systems it is important to gain pertinent information on the spatial localisation of chemicals within cells. With the relatively recent advent of high-resolution chemical imaging this is being realised and one rapidly developing area of research is the Raman mapping of single cells, an approach whose success has vast potential for numerous areas of biomedical research. However, there is a danger of undermining the potential routine use of Raman mapping due to a lack of consistency and transparency in the way false-shaded Raman images are constructed. In this study we demonstrate, through the use of simulated data and real Raman maps of single human keratinocyte (HaCaT) cells, how changes in the application of colour shading can dramatically alter the final Raman images. In order to avoid ambiguity and potential subjectivity in image interpretation we suggest that data distribution plots are used to aid shading approaches and that extreme care is taken to use the most appropriate false-shading for the biomedical question under investigation

Raman spectroscopy:an evolving technique for live cell studies

One of the most exciting developments in Raman spectroscopy in the last decade has been its application to cells and tissues for diagnostic and pharmaceutical applications, and in particular its use in the analysis of cellular dynamics. Raman spectroscopy is rapidly advancing as a cell imaging method that overcomes many of the limitations of current techniques and is earning its place as a routine tool in cell biology. In this review we focus on important developments in Raman spectroscopy that have evolved into the exciting technique of live-cell Raman microscopy and highlight some of the most recent and significant applications to cell biology

Two-dimensional codistribution spectroscopy applied to UVRR and ROA investigations of biomolecular transitions

The first Raman optical activity (ROA) two-dimensional correlation spectroscopy (2DCOS) study in 2006, monitoring the temperature-induced α-helix-to-β-sheet transition in poly(l-lysine), demonstrated the versatility of 2DCOS. The combination of ROA and 2DCOS provided new ROA band assignments, enabled a direct comparison between the simultaneously collected Raman and ROA data using heterocorrelations and probed sequential information. This study also confirmed that 2DCOS can be successfully used with bisignate data, although specific care is needed when interpreting the results. However, as time has passed, doubts have been raised about not only the sequential orders reported in the study but also the general reliability of sequential data. This issue has now been addressed with the introduction of 2D codistribution (2DCDS) which is specifically designed to provide the sequence of the distributed presence of species along the perturbation variable axis. In light of these new developments in 2D correlation techniques we have revisited the original ROA data and we present our updated results. Furthermore, we demonstrate how 2DCDS can be successfully applied to bisignate data using new spectral data sets of perturbation-induced transitions in polynucleotides

Determination of Phosphorylation and Deprotonation Induced Higher Order Structural Transitions in αs‑Caseins

One extremely sensitive and highly successful application of Raman spectroscopy is the structural characterization of proteins. Understanding higher order structure and its effect on protein stability is essential not only for biopharmaceutical and food manufacturing but also for the understanding of diseases that result from the misfolding of proteins including diabetes type II, Alzheimer's, and Parkinson's disease. Due to the large amount of structural information available in Raman spectra, even small alterations in protein conformations including increased exposure of binding regions or changes in geometry of secondary structural elements can be identified. In this study, we demonstrate the unique sensitivity of Raman spectroscopy to subtle structural transitions in an intrinsically open, flexible protein, α s-casein, in response to phosphorylation and deprotonation. Through the application of 2D correlation analysis two separate transition phases have been identified from pH 6-9 and pH 10-12 for both phosphorylated and dephosphorylated α s-casein. However, the actual structural changes observed in each pH range differed considerably between the phosphorylated and dephosphorylated α s-casein. Furthermore, the presence of the phosphorylated serine residues is demonstrated to have a shielding effect during deprotonation of the protein

Illuminating disease and enlightening biomedicine:Raman spectroscopy as a diagnostic tool

The discovery of the Raman effect in 1928 not only aided fundamental understanding about the quantum nature of light and matter but also opened up a completely novel area of optics and spectroscopic research that is accelerating at a greater rate during the last decade than at any time since its inception. This introductory overview focuses on some of the most recent developments within this exciting field and how this has enabled and enhanced disease diagnosis and biomedical applications. We highlight a small number of stimulating high-impact studies in imaging, endoscopy, stem cell research, and other recent developments such as spatially offset Raman scattering amongst others. We hope this stimulates further interest in this already exciting field, by 'illuminating' some of the current research being undertaken by the latest in a very long line of dedicated experimentalists interested in the properties and potential beneficial applications of light

Analysis and monitoring of single HaCaT cells using volumetric Raman mapping and machine learning

No explorer reached a pole without a map, no chef served a meal without tasting, and no surgeon implants untested devices. Higher accuracy maps, more sensitive taste buds, and more rigorous tests increase confidence in positive outcomes. Biomedical manufacturing necessitates rigour, whether developing drugs or creating bioengineered tissues [1]–[4]. By designing a dynamic environment that supports mammalian cells during experiments within a Raman spectroscope, this project provides a platform that more closely replicates in vivo conditions. The platform also adds the opportunity to automate the adaptation of the cell culture environment, alongside spectral monitoring of cells with machine learning and three-dimensional Raman mapping, called volumetric Raman mapping (VRM). Previous research highlighted key areas for refinement, like a structured approach for shading Raman maps [5], [6], and the collection of VRM [7]. Refining VRM shading and collection was the initial focus, k-means directed shading for vibrational spectroscopy map shading was developed in Chapter 3 and exploration of depth distortion and VRM calibration (Chapter 4). “Cage” scaffolds, designed using the findings from Chapter 4 were then utilised to influence cell behaviour by varying the number of cage beams to change the scaffold porosity. Altering the porosity facilitated spectroscopy investigation into previously observed changes in cell biology alteration in response to porous scaffolds [8]. VRM visualised changed single human keratinocyte (HaCaT) cell morphology, providing a complementary technique for machine learning classification. Increased technical rigour justified progression onto in-situ flow chamber for Raman spectroscopy development in Chapter 6, using a Psoriasis (dithranol-HaCaT) model on unfixed cells. K-means-directed shading and principal component analysis (PCA) revealed HaCaT cell adaptations aligning with previous publications [5] and earlier thesis sections. The k-means-directed Raman maps and PCA score plots verified the drug-supplying capacity of the flow chamber, justifying future investigation into VRM and machine learning for monitoring single cells within the flow chamber

Detection of Protein Glycosylation Using Tip-Enhanced Raman Scattering

The correct glycosylation of biopharmaceutical glycoproteins and their formulations is essential for them to have the desired therapeutic effect on the patient. It has recently been shown that Raman spectroscopy can be used to quantify the proportion of glycosylated protein from mixtures of native and glycosylated forms of bovine pancreatic ribonuclease (RNase). Here we show the first steps toward not only the detection of glycosylation status but the characterization of glycans themselves from just a few protein molecules at a time using tip-enhanced Raman scattering (TERS). While this technique generates complex data that are very dependent on the protein orientation, with the careful development of combined data preprocessing, univariate and multivariate analysis techniques, we have shown that we can distinguish between the native and glycosylated forms of RNase. Many glycoproteins contain populations of subtly different glycoforms; therefore, with stricter orientation control, we believe this has the potential to lead to further glycan characterization using TERS, which would have use in biopharmaceutical synthesis and formulation research

19F Solid-State NMR and Vibrational Raman Characterization of Corticosteroid Drug-Lipid Membrane Interactions

Drug interactions with phospholipid bilayers underpin their behaviour in cell membranes and in liposomal delivery formulations. Liposomal drug delivery in ocular medicine can overcome the physical barriers of the eye and better enable the active molecule to reach its target. Here, Raman and 19F solid-state NMR spectroscopy are used to characterise the interactions of two ocular corticosteroid drugs, difluprednate (DFP) and fluorometholone (FML), with multilamellar vesicles of phosphatidylcholine (PC). 31P NMR confirms that the lipid bilayer tolerates a high drug concentration (a drug: lipid molar ratio of 1 : 10). The 19F NMR spectra of the drugs in lipid bilayers reveal that FML and DFP have different average orientations within the lipid bilayer. Raman spectra of dried lipid films reveal that PC separates from DFP but not from FML, the less lipophilic of the two drugs. This combined approach will assist the design of, and inform the development of, improved liposomal preparations

Raman Spectroscopy with 2D Perturbation Correlation Moving Windows for the Characterization of Heparin–Amyloid Interactions

It has been shown extensively that glycosaminoglycan (GAG)–protein interactions can induce, accelerate, and impede the clearance of amyloid fibrils associated with systemic and localized amyloidosis. Obtaining molecular details of these interactions is fundamental to our understanding of amyloid disease. Consequently, there is a need for analytical approaches that can identify protein conformational transitions and simultaneously characterize heparin interactions. By combining Raman spectroscopy with two-dimensional (2D) perturbation correlation moving window (2DPCMW) analysis, we have successfully identified changes in protein secondary structure during pH- and heparin-induced fibril formation of apolipoprotein A-I (apoA-I) associated with atherosclerosis. Furthermore, from the 2DPCMW, we have identified peak shifts and intensity variations in Raman peaks arising from different heparan sulfate moieties, indicating that protein–heparin interactions vary at different heparin concentrations. Raman spectroscopy thus reveals new mechanistic insights into the role of GAGs during amyloid fibril formation