pH-induced conformational transitions in α-lactalbumin investigated with two-dimensional Raman correlation variance plots and moving windows

Non-invasive detection of regulatory T cells with Raman spectroscopy

Regulatory T cells (Tregs) are a type of lymphocyte that is key to maintaining immunological self-tolerance, with great potential for therapeutic applications. A long-standing challenge in the study of Tregs is that the only way they can be unambiguously identified is by using invasive intracellular markers. Practically, the purification of live Tregs is often compromised by other cell types since only surrogate surface markers can be used. We present here a non-invasive method based on Raman spectroscopy that can detect live unaltered Tregs by coupling optical detection with machine learning implemented with regularized logistic regression. We demonstrate the validity of this approach first on murine cells expressing a surface Foxp3 reporter, and then on peripheral blood human T cells. By including methods to account for sample purity, we could generate reliable models that can identify Tregs with an accuracy higher than 80%, which is already comparable with typical sorting purities achievable with standard methods that use proxy surface markers. We could also demonstrate that it is possible to reliably detect Tregs in fully independent donors that are not part of the model training, a key milestone for practical applications.

Imaging vs Nonimaging Raman Spectroscopy for High-Throughput Single-Cell Phenotyping

Raman spectroscopy can provide nonbiased single-cell analysis based on the endogenous ensemble of biomolecules, with alterations in cellular content indicative of cell state and disease. The measurements themselves can be performed in a variety of modes: generally, full imaging takes the most time but can provide the most information. By reducing the imaging resolution and generating the most characteristic single-cell Raman spectrum in the shortest time, we optimize the utility of the Raman measurement for cell phenotyping. Here, we establish methods to compare these different measurement approaches and assess what, if any, undesired effects occur in the cell. Assuming that laser-induced damage should be apparent as a change in molecular spectra across sequential measurements, and by defining the information content as the Raman-based separability of two cell lines, we thereby establish a parameter range for optimum measurement sensitivity and single-cell throughput in single-cell Raman spectroscopic analysis. While the work here uses 532 nm irradiation, the same approach can be generalized to Raman analysis at other wavelengths.

Single-cell Raman microscopy with machine learning highlights distinct biochemical features of neutrophil extracellular traps and necrosis

The defining biology that distinguishes neutrophil extracellular traps (NETs) from other forms of cell death is unresolved, and techniques which unambiguously identify NETs remain elusive. Raman scattering measurement provides a holistic overview of cell molecular composition based on characteristic bond vibrations in components such as lipids and proteins. We collected Raman spectra from NETs and freeze/thaw necrotic cells using a custom built high-throughput platform which is able to rapidly measure spectra from single cells. Principal component analysis of Raman spectra from NETs clearly distinguished them from necrotic cells despite their similar morphology, demonstrating their fundamental molecular differences. In contrast, classical techniques used for NET analysis, immunofluorescence microscopy, extracellular DNA, and ELISA, could not differentiate these cells. Additionally, machine learning analysis of Raman spectra indicated subtle differences in lipopolysaccharide (LPS)-induced as opposed to phorbol myristate acetate (PMA)-induced NETs, demonstrating the molecular composition of NETs varies depending on the stimulant used. This study demonstrates the benefits of Raman microscopy in discriminating NETs from other types of cell death and by their pathway of induction.

Non-invasive monitoring of T cell differentiation through Raman spectroscopy

The monitoring of dynamic cellular behaviors remains a technical challenge for most established techniques used nowadays for single-cell analysis, as most of them are either destructive, or rely on labels that can affect the long-term functions of cells. We employ here label-free optical techniques to non-invasively monitor the changes that occur in murine naive T cells upon activation and subsequent differentiation into effector cells. Based on spontaneous Raman single-cell spectra, we develop statistical models that allow the detection of activation, and employ non-linear projection methods to delineate the changes occurring over a several day period spanning early differentiation. We show that these label-free results have very high correlation with known surface markers of activation and differentiation, while also providing spectral models that allow the identification of the underlying molecular species that are representative of the biological process under study.

Evaluation of a Raman Chemometric Method for Detecting Protein Structural Conformational Changes in Solution

Raman scattering shows promise as a powerful routine tool, to determine both secondary and the smaller tertiary structural changes that precede aggregation in both solutions and solids. A method was developed utilizing principal component analysis (PCA) of Raman spectra for detection of small, but meaningful, pH induced changes in tertiary protein structure linked to aggregate formation using α-lactalbumin solutions as a model. The sample preparation and spectral parameters, were optimized for a bulk Raman probe. Analysis of large regions (600-1850 cm^-1) yielded principal component (PC) scores useful for semi-quantitative comparison of protein conformation between formulations. PC loadings corresponded to specific structural peaks known to change with solution pH. PCA of circular dichroism (CD) spectra of dilute solutions yielded similar results. Sucrose is a common formulation excipient with a Raman spectrum that overlaps many protein peaks. With sucrose in the protein solution, the ability of PCA to discern protein structural changes from the Raman spectra was somewhat reduced. Analysis of a more limited spectral region (1530-1780 cm^-1) with negligible sucrose spectral contribution improved the discrimination of protein conformational states. The new Raman method accurately distinguished differences in protein structure in concentrated solutions. The long-term goal is to explore Raman characterization as a routine monitoring tool of protein stability in both solution and solid states.

Determination of lentiviral titer by surface enhanced Raman scattering

Lentiviruses are commonly used to deliver genetic code into host cells for biomedical applications, such as gene therapy, pharmaceuticals, and vaccine development. Knowing the infectious titer of these virus particles is critical for development in these areas. Current methods of determining viral titer often require cell culture, where a cell is infected and the inserted genetic code is expressed in a known number of cells, which can require days or weeks to prepare and analyze samples. To provide a more rapid method of determining viral titer, the use of surface enhanced Raman spectroscopy (SERS) was explored. SERS provides both chemical and structural information by using plasmonic metallic nanostructures to amplify the Raman signal. Two different lentiviruses, one with a vector encoding a GFP gene and the same virus without the GFP gene included, were analyzed by SERS in viral production media at various concentrations. The SERS response was demonstrated to be sensitive to the incorporation of the GFP gene into the viral vector. Chemometric analysis using multivariate curve resolution (MCR) was able to identify a component in the observed SERS spectra that correlated with the concentration of GFP containing virus particles. Using the MCR model and the SERS response, the viral titer of lentivirus encoding for GFP was determined. The viral titer determined by SERS agreed well with expression of the GFP in infected cells. The SERS response using different metals and excitation wavelengths was also explored. Overall, this work demonstrates the utility of SERS for rapid determination of lentiviral titer.

Synthesis of gold nanoparticles@reduced porous graphene-modified ITO electrode for spectroelectrochemical detection of SARS-CoV-2 spike protein

Here, we reported the synthesis of reduced porous graphene oxide (rPGO) decorated with gold nanoparticles (Au NPs) to modify the ITO electrode. Then we used this highly uniform Au NPs@rPGO modified ITO electrode as a surface-enhanced Raman spectroscopy-active surface and a working electrode. The uses of the Au nanoparticles and porous graphene enhance the Raman signals and the electrochemical conductivity. COVID-19 protein-based biosensor was developed based on immobilization of anti-COVID-19 antibodies onto the modified electrode and its uses as a probe for capturing the COVID-19 protein. The developed biosensor showed the capability of monitoring the COVID-19 protein within a concentration range from 100 nmol/L to 1 pmol/L with a limit of detection (LOD) of 75 fmol/L. Furthermore, COVID-19 protein was detected based on electrochemical techniques within a concentration range from 100 nmol/L to 500 fmol/L that showed a LOD of 39.5 fmol/L. Finally, three concentrations of COVID-19 protein spiked in human serum were investigated. Thus, the present sensor showed high efficiency towards the detection of COVID-19.

Electrochemical Microbiosensor for Detecting COVID-19 in a Patient Sample Based on Gold Microcuboids Pattern

As continues increasing the COVID-19 infections, there is an urgent need for developing fast, simple, selective, and accurate COVID-19 biosensors. A highly uniform gold (Au) microcuboid pattern was used as a microelectrode that allowed monitoring a small analyte. The electrochemical biosensor was used to monitor the COVID-19 S protein within a concentration range from 100 to 5 pmol L⁻¹; it showed a lower detection limit of 276 fmol L⁻¹. Finally, the developed COVID-19 sensor was used to detect a positive sample from a human patient obtained through a nasal swab; the results were confirmed using the PCR technique. The results showed that the SWV technique showed high sensitivity towards detecting COVID-19 and good efficiency for detecting COVID-19 in a positive human sample.

Label-free Raman mapping of saturated and unsaturated fatty acid uptake, storage, and return toward baseline levels in macrophages

Macrophage uptake and metabolism of fatty acids is involved in a large number of important biological pathways including immune activation and regulation of macrophages, as well as pathological conditions including obesity, atherosclerosis, and others lifestyle diseases. There are few methods available to directly probe both the uptake and later redistribution/metabolism of fatty acids within living cells as well as the potential changes induced within the cells themselves. We use Raman imaging and analysis to evaluate the effects of different fatty acids following their uptake in macrophages. The label-free nature of the methods means that we can evaluate the fatty acid dynamics without modifying endogenous cellular behavior and metabolism.

The molecular chaperone β-casein prevents amorphous and fibrillar aggregation of α-lactalbumin by stabilisation of dynamic disorder

Deficits in protein homeostasis (proteostasis) are typified by the partial unfolding or misfolding of native proteins leading to amorphous or fibrillar aggregation, events that have been closely associated with diseases including Alzheimer's and Parkinson's diseases. Molecular chaperones are intimately involved in maintaining proteostasis, and their mechanisms of action are in part dependent on the morphology of aggregation-prone proteins. This study utilised native ion mobility–mass spectrometry to provide molecular insights into the conformational properties and dynamics of a model protein, α-lactalbumin (α-LA), which aggregates in an amorphous or amyloid fibrillar manner controlled by appropriate selection of experimental conditions. The molecular chaperone β-casein (β-CN) is effective at inhibiting amorphous and fibrillar aggregation of α-LA at sub-stoichiometric ratios, with greater efficiency against fibril formation. Analytical size-exclusion chromatography demonstrates the interaction between β-CN and amorphously aggregating α-LA is stable, forming a soluble high molecular weight complex, whilst with fibril-forming α-LA the interaction is transient. Moreover, ion mobility–mass spectrometry (IM-MS) coupled with collision-induced unfolding (CIU) revealed that α-LA monomers undergo distinct conformational transitions during the initial stages of amorphous (order to disorder) and fibrillar (disorder to order) aggregation. The structural heterogeneity of monomeric α-LA during fibrillation is reduced in the presence of β-CN along with an enhancement in stability, which provides a potential means for preventing fibril formation. Together, this study demonstrates how IM-MS and CIU can investigate the unfolding of proteins as well as examine transient and dynamic protein–chaperone interactions, and thereby provides detailed insight into the mechanism of chaperone action and proteostasis mechanisms.

Tandem fluorescence and Raman (fluoRaman) characterisation of a novel photosensitiser in colorectal cancer cell line SW480

A novel photosensitiser, DC473, designed with solvatochromatic fluorescence and distinct Raman signal, is detected with tandem fluoRaman in SW480 cells.

The development of new imaging tools, molecules and modalities is crucial to understanding biological processes and the localised cellular impact of bioactive compounds. A small molecule photosensitiser, DC473, has been designed to be both highly fluorescent and to exhibit a strong Raman signal in the cell-silent region of the Raman spectrum due to a diphenylacetylene structure. DC473 has been utilised to perform a range of novel tandem fluorescence and Raman (fluoRaman) imaging experiments, enabling a thorough examination of the compound's cellular localisation, exemplified in colorectal cancer cells (SW480). This multifunctional fluoRaman imaging modality revealed the presence of the compound in lipid droplets and only a weak signal in the cytosol, by both Raman and fluorescence imaging. In addition, Raman microscopy detected the compound in a cell compartment we labelled as the nucleolus, whereas fluorescence microscopy did not detect the fluoRaman probe due to solvatochromatic effects in a local polar environment. This last finding was only possible with the use of tandem confocal Raman and fluorescence methods. By following the approach detailed herein, incorporation of strong Raman functional groups into fluorophores can enable a plethora of fluoRaman experiments, shedding further light on potential drug compound's cellular behaviour and biological activity.

Engaging with Raman Spectroscopy to Investigate Antibody Aggregation

In the last decade, a number of studies have successfully demonstrated Raman spectroscopy as an emerging analytical technique for monitoring antibody aggregation, especially in the context of drug development and formulation. Raman spectroscopy is a robust method for investigating protein conformational changes, even in highly concentrated antibody solutions. It is non-destructive, reproducible and can probe samples in an aqueous environment. In this review, we focus on the application and challenges associated with using Raman spectroscopy as a tool to study antibody aggregates.

Advancements of two dimensional correlation spectroscopy in protein researches

The developments of two-dimensional correlation spectroscopy (2DCOS) applications in protein studies are discussed, especially for the past two decades. The powerful utilities of 2DCOS combined with various analytical techniques in protein studies are summarized. The emphasis is on the vibration spectroscopic techniques including IR, NIR, Raman and optical activity (ROA), as well as vibration circular dichroism (VCD) and fluorescence spectroscopy. In addition, some new developments, such as hetero-spectral 2DCOS, moving-window correlation, and model based correlation, are also reviewed for their utility in the investigation of the secondary structure, denaturation, folding and unfolding changes of protein. Finally, the new possibility and challenges of 2DCOS in protein research are highlighted as well.

Two-dimensional correlation spectroscopy in protein science, a summary for past 20years

Two-dimensional correlation spectroscopy (2DCOS) has been widely used to Infrared, Raman, Near IR, Optical Activity (ROA), Vibrational Circular Dichroism (VCD) and Fluorescence spectroscopy. In addition, several new developments, such as 2D hetero-correlation analysis, moving-window two-dimensional (MW2D) correlation, model based correlation (βν and kν correlation analyses) have also well incorporated into protein research. They have been used to investigate secondary structure, denaturation, folding and unfolding changes of protein, and have contributed greatly to the field of protein science. This review provides an overview of the applications of 2DCOS in the field of protein science for the past 20 year, especially to memory our old friend, Dr. Boguslawa Czarnik-Matusewicz, for her great contribution in this research field. The powerful utility of 2DCOS combined with various analytical techniques in protein studies is summarized. The noteworthy developments and perspective of 2DCOS in this field are highlighted finally.

Least Squares Moving-Window Spectral Analysis

Least squares regression is proposed as a moving-windows method for analysis of a series of spectra acquired as a function of external perturbation. The least squares moving-window (LSMW) method can be considered an extended form of the Savitzky-Golay differentiation for nonuniform perturbation spacing. LSMW is characterized in terms of moving-window size, perturbation spacing type, and intensity noise. Simulation results from LSMW are compared with results from other numerical differentiation methods, such as single-interval differentiation, autocorrelation moving-window, and perturbation correlation moving-window methods. It is demonstrated that this simple LSMW method can be useful for quantitative analysis of nonuniformly spaced spectral data with high frequency noise.

Analytical and Numerical Characterization of Autocorrelation and Perturbation-Correlation Moving-Window Methods

Moving-window (MW) approaches to two-dimensional correlation spectroscopy (2D-COS) make it possible to characterize spectral changes occurring in a narrow range of perturbation variable (e.g., time, temperature, and concentration). Despite the wide range of application, the physical meanings of MW correlation intensities have been only qualitatively associated with the direction and curvature of spectral intensity change with regard to a perturbation variable. Here are full and simplified analytical expressions of autocorrelation moving-window (ACMW) and synchronous and asynchronous perturbation-correlation moving-window ( s-PCMW and as-PCMW) intensities. When the window is set sufficiently narrower than the bandwidth of spectral change, the square root of ACMW intensity and s-PCMW intensity becomes proportional to the first order derivative, and as-PCMW intensity becomes proportional to the negative of the second order derivative. This paper demonstrates that both ACMW and PCMW profiles can be significantly altered by non-uniform perturbation spacing. It is also found that intensity noise can cause ACMW to display a false offset drift. This analytical and numerical characterization of the two MW correlation intensities elucidates their physical meanings and ascertains the analysis conditions for reliable interpretation.

Monitoring antibody aggregation in early drug development using Raman spectroscopy and perturbation-correlation moving windows

In this study, we demonstrate the sensitivity of two-dimensional perturbation-correlation moving windows (PCMW) to characterize conformational transitions in antibodies. An understanding of how physiochemical properties affect protein stability and instigate aggregation is essential for the engineering of antibodies. In order to establish the potential of PCMW as a technique for early identification of aggregation mechanisms during antibody development, five antibodies with varying propensity to aggregate were compared. Raman spectra were acquired, using a 532 nm excitation wavelength as the protein samples were heated from 56 to 78 °C and analyzed with PCMW. Initial principal component analysis confirmed a trend between the observed spectral variations and increasing temperature for all five samples. Analysis using PCMW revealed that when spectral variations were directly related to temperature, distinct differences in conformational changes could be determined between samples related to protein stability, providing a greater understanding of the aggregation mechanisms of problematic antibody variants.

Investigation of DMSO-induced conformational transitions in human serum albumin using two-dimensional raman optical activity spectroscopy

Recent Raman and Raman optical activity (ROA) results have demonstrated that dimethyl sulfoxide (DMSO) induces the selective conversion of α-helix motifs into the poly(L-proline) II (PPII) helix conformation in an array of proteins, while β-sheets remain mostly unaffected. Human serum albumin (HSA), a highly α-helical protein, underwent the most dramatic changes and, therefore, was selected as a model for further investigations into the mechanism of this conformational change. Herein we report the use of two-dimensional ROA correlation analysis applying synchronous, autocorrelation, and moving windows approaches in order to understand the conformational transitions in HSA as a function of DMSO concentration. Our results indicate that the destabilization of native α-helix starts at DMSO concentrations as little as 20% in water (v/v), with the transition to PPII helix being complete at ~80% DMSO. These results clearly indicate that any protein preparation containing relatively low concentrations of DMSO should consider possible disruptions in α-helical domains.

Cell optical density and molecular composition revealed by simultaneous multimodal label-free imaging

We show how Raman imaging can be combined with independent but simultaneous phase measurements of unlabeled cells, with the resulting data providing information on how the light is retarded and/or scattered by molecules in the cell. We then show, for the first time to our knowledge, how the chemistry of the cell highlighted in the Raman information is related to the cell quantitative phase information revealed in digital holographic microscopy by quantifying how the two sets of spatial information are correlated. The results show that such a multimodal implementation is highly useful for the convenience of having video rate imaging of the cell during the entire Raman measurement time, allowing us to observe how the cell changes during Raman acquisition. More importantly, it also shows that the two sets of label-free data, which result from different scattering mechanisms, are complementary and can be used to interpret the composition and dynamics of the cell, where each mode supplies label-free information not available from the other mode.

The transition from the native to the acid-state characterized by multi-spectroscopy approach: study for the holo-form of bovine α-lactalbumin

The transition of the holo-form of bovine α-lactalbumin from the native (N) to the pH-generated acidic-state (A-state) was analyzed by probing its tertiary and secondary structure using a concerted spectroscopic approach combining near- and far-UV circular dichroism (CD), electrospray ionization ion mobility mass spectrometry (ESI-IM-MS), vibrational circular dichroism (VCD), and Fourier transform infrared spectroscopy (FTIR) in the attenuated total reflection (ATR) and transmission (TR) modes. The spectroscopic results, which relied on the interaction of an electromagnetic field with different molecular targets, confirmed the decay of extensive rigid side-chain packing interactions during the pH-induced N→A-state transition and revealed the targets' dependence on secondary structural changes. Independent analyses of the spectral changes using two methods of multivariate analysis, such as principal component analysis and two-dimensional correlation spectroscopy, revealed small but significant differences in the secondary structure as a result of the all-or-none transition. The cooperativity of the transition was quantitatively described using values corresponding to the mid-point (tm) and width of the transition (Δtm). The averages of the two parameters, calculated using the data collected by the different probes, were equal to 3.5±0.2 and 0.6±0.1(SE), respectively. The variable two-state nature of the cooperative N→A-state transition confirmed that the protonation of the side chain carboxyl groups on the Asp and Glu residues and that the release of a Ca(2+) ion induced structural changes on both the secondary and tertiary levels. The changes have been confirmed by results obtained from the concerted spectroscopic approach.

Honey bee odorant-binding protein 14: effects on thermal stability upon odorant binding revealed by FT-IR spectroscopy and CD measurements

In the present work, we study the effect of odorant binding on the thermal stability of honey bee (Apis mellifera L.) odorant-binding protein 14. Thermal denaturation of the protein in the absence and presence of different odorant molecules was monitored by Fourier transform infrared spectroscopy (FT-IR) and circular dichroism (CD). FT-IR spectra show characteristic bands for intermolecular aggregation through the formation of intermolecular β-sheets during the heating process. Transition temperatures in the FT-IR spectra were evaluated using moving-window 2D correlation maps and confirmed by CD measurements. The obtained results reveal an increase of the denaturation temperature of the protein when bound to an odorant molecule. We could also discriminate between high- and low-affinity odorants by determining transition temperatures, as demonstrated independently by the two applied methodologies. The increased thermal stability in the presence of ligands is attributed to a stabilizing effect of non-covalent interactions between odorant-binding protein 14 and the odorant molecule.

Investigation of the structure of alpha-lactalbumin protein nanotubes using optical spectroscopy

Alpha-lactalbumin (α-la) is one of the major proteins in whey. When partially hydrolysed with Bacillus licheniformis protease, it produces nanotubular structures in the presence of calcium ions by a self-assembly process. This study presents investigation of α-la protein structure during hydrolysis and nanotube formation using optical spectroscopy. Before spectroscopic measurements, nanotubes were examined with microscopy. The observed α-la nanotubes (α-LaNTs) were in the form of regular hollow strands with a diameter of about 20 nm and the average length of 1 μm. Amide and backbone vibration bands of the Raman spectra displayed remarkable conformational changes in α and β domains in the protein structure during nanotube growth. This was confirmed by the Fourier-transform infrared (FTIR) spectroscopy data. Also, FTIR analysis revealed certain bands at calcium (Ca++) binding sites of COO− groups in hydrolysed protein. These sites might be critical in nanotube elongation.

The importance of protonation in the investigation of protein phosphorylation using Raman spectroscopy and Raman optical activity

The effect of protonation on amino acid monomers and protein phosphorylation was studied by means of a combination of Raman scattering and Raman optical activity (ROA). In the past, identifying spectral variations in phosphorylated proteins arising from either the phosphate stretch or amide vibrational modes has proven to be challenging mainly due to the loss of amide and P═O band intensity in the presence of phosphate. By contrast, we have developed a novel strategy based on the careful monitoring of the sample pH and thereby modified the protonation state, such that these difficulties can be overcome and phosphate-derived vibrations are readily visualized with both Raman and ROA. Variations in pH-dependent spectral sets of phosphorylated amino acid monomers serine and threonine demonstrated that the protonation state could be determined by the intensity of the monobasic (-OPO(3)H(-)) phosphate stretch band occurring at ~1080 cm(-1) versus the dibasic (-OPO(3)(2-)) band measured at ~980 cm(-1) in both Raman and ROA. Furthermore, by adjustment of the pH of aqueous samples of the phosphoprotein α-casein and comparing this result with dephosphorylated α-casein, spectral variations in phosphate stretch bands and amide bands could be easily determined. Consequently, structural variations due to both protonation and dephosphorylation could be distinguished, demonstrating the potential of Raman and ROA for future investigations of phosphoprotein structure and interactions.