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.

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.

Noninvasive detection of macrophage activation with single-cell resolution through machine learning.

We present a method enabling the noninvasive study of minute cellular changes in response to stimuli, based on the acquisition of multiple parameters through label-free microscopy. The retrieved parameters are related to different attributes of the cell. Morphological variables are extracted from quantitative phase microscopy and autofluorescence images, while molecular indicators are retrieved via Raman spectroscopy. We show that these independent parameters can be used to build a multivariate statistical model based on logistic regression, which we apply to the detection at the single-cell level of macrophage activation induced by lipopolysaccharide (LPS) exposure and compare their respective performance in assessing the individual cellular state. The models generated from either morphology or Raman can reliably and independently detect the activation state of macrophage cells, which is validated by comparison with their cytokine secretion and intracellular expression of molecules related to the immune response. The independent models agree on the degree of activation, showing that the features provide insight into the cellular response heterogeneity. We found that morphological indicators are linked to the phenotype, which is mostly related to downstream effects, making the results obtained with these variables dose-dependent. On the other hand, Raman indicators are representative of upstream intracellular molecular changes related to specific activation pathways. By partially inhibiting the LPS-induced activation using progesterone, we could identify several subpopulations, showing the ability of our approach to identify the effect of LPS activation, specific inhibition of LPS, and also the effect of progesterone alone on macrophage cells.

Raman spectroscopy as a tool for label-free lymphocyte cell line discrimination.

Unactivated lymphocytes are morphologically identical and biochemically relatively similar, making them difficult to distinguish from one another with conventional light microscopy. Here, we use Raman spectroscopy to provide biochemical information on the composition of different lymphocyte cell lines. As could be expected, the biochemical differences measured with Raman spectroscopy between lymphocyte cell lines are small, but in combination with partial least squares discriminant analysis it is possible not only to distinguish between T- and B-cells, but also between individual T-cell and B-cell lines.

Label-free Raman imaging of the macrophage response to the malaria pigment hemozoin.

Hemozoin, the 'malaria pigment', is engulfed by phagocytic cells, such as macrophages, during malaria infection. This biocrystalline substance is difficult to degrade and often accumulates in phagocytes. The macrophage response to hemozoin relates to the severity of the disease and the potential for malaria-related disease complications. In this study we have used Raman spectroscopy as a label-free method to investigate the biochemical changes occurring in macrophages during the first few hours of hemozoin uptake. We found a number of distinct spectral groups, spectrally or spatially related to the presence of the hemozoin inside the cell. Intracellular hemozoin was spectrally identical to extracellular hemozoin, regardless of the location in the cell. A small proportion of hemozoin was found to be associated with lipid-based components, consistent with the uptake of hemozoin into vesicles such as phagosomes and lysosomes. The spatial distribution of the hemozoin was observed to be inhomogeneous, and its presence largely excluded that of proteins and lipids, demonstrating that cells were not able to break down the biocrystals on the time scales studied here. These results show that Raman imaging can be used to answer some of the open questions regarding the role of hemozoin in the immune response. How different combinations of hemozoin and other molecules are treated by macrophages, whether hemozoin can be broken down by the cell, and more importantly, which co-factors or products are involved in the subsequent cell reaction are the expected issues to be elucidated by this technique.

Laser-targeted photofabrication of gold nanoparticles inside cells.

Nanoparticle manipulation is of increasing interest, since they can report single molecule-level measurements of the cellular environment. Until now, however, intracellular nanoparticle locations have been essentially uncontrollable. Here we show that by infusing a gold ion solution, focused laser light-induced photoreduction allows in situ fabrication of gold nanoparticles at precise locations. The resulting particles are pure gold nanocrystals, distributed throughout the laser focus at sizes ranging from 2 to 20 nm, and remain in place even after removing the gold solution. We demonstrate the spatial control by scanning a laser beam to write characters in gold inside a cell. Plasmonically enhanced molecular signals could be detected from nanoparticles, allowing their use as nano-chemical probes at targeted locations inside the cell, with intracellular molecular feedback. Such light-based control of the intracellular particle generation reaction also offers avenues for in situ plasmonic device creation in organic targets, and may eventually link optical and electron microscopy.

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.

Deconstructing RNA: optical measurement of composition and structure.

RNA molecules are involved in many pathways within the cell and their sequence composition, structure, conformational transitions and interactions with other molecules are all important factors in determining RNA function. Here we present a method for systematically and quantitatively determining characteristics of RNA using Raman spectroscopy. This method can be used to assess the composition and structure of a given RNA molecule, including ribose-phosphate sugar-pucker conformation, face-to-face base stacking and hydrogen bonding interactions. Three RNA molecules with different sequence and structural features (the exon splicing silencer 3 from HIV-1, an RNA aptamer against Runt-related transcription factor, and the SARS coronaviral stem loop 2) are presented as examples where the structure is crucial to the function of the RNA. We carry out piecewise analysis of the RNA spectra and show that using a nucleotide spectra library helps to unlock the entire ensemble of vibrational information. This analysis demonstrates the extent to which RNA characteristics can be elucidated, using purely optical methods.

Raman spectroscopic analysis of malaria disease progression via blood and plasma samples.

In this study Raman spectroscopy has been used to monitor the changes in erythrocytes and plasma during Plasmodium infection in mice, following malaria disease progression over the course of 7 days. The Raman spectra of both samples are dominated by the spectra of hemoglobin and hemozoin, due to their resonant enhancement. In plasma samples, due to the inherently low heme background, heme-based changes in the Raman spectra could be detected in the very early stages of infection, as little as one day after Plasmodium infection, where parasitemia levels were low, on the order of 0.2%, and typically difficult to detect by existing methods. Further principal component analysis also indicates concurrent erythrocyte membrane changes at around day 4, where parasitemia levels reached 3%. These results show that plasma analysis has significant potential for early, quantitative and automated detection of malaria, and to quantify heme levels in serum which modulate malarial effects on the immune system.

Differentiation of walnut wood species and steam treatment using ATR-FTIR and partial least squares discriminant analysis (PLS-DA).

Wood is a ubiquitous material used in everyday life. Accurate identification of species can be of importance in a historical context enabling appropriate conservation treatment and adequate choice of material to be applied to historic wooden objects, and in a more modern context, in the identification of forgeries. Wood is also often treated to improve certain physical characteristics, often strength and durability. However, determination of whether or not a piece of wood has been treated can be very difficult. Infrared spectroscopy has previously been applied to differentiate between different wood species or between treated and untreated wood, often in conjunction with chemometric analysis techniques. Here, we report the use of mid-IR spectroscopy, coupled with partial least squares discriminant analysis for the discrimination between two walnut wood species and to differentiate between steam-treated and untreated samples of each of these wood species. We show that the discrimination between species and between steam-treated and non-steam-treated wood from Juglans nigra is very clear and, while analysis of the quality of the discrimination between steam-treated and non-steam-treated J. regia samples is not as good, it is, nevertheless, sufficient for discrimination between the two groups with a statistical significance of P < 0.0001.

Raman and Raman optical activity (ROA) analysis of RNA structural motifs in Domain I of the EMCV IRES.

Raman and Raman optical activity (ROA) spectra were collected for four RNA oligonucleotides based on the EMCV IRES Domain I to assess the contributions of helix, GNRA tetraloop, U.C mismatch base pair and pyrimidine-rich bulge structures to each. Both Raman and ROA spectra show overall similarities for all oligonucleotides, reflecting the presence of the same base paired helical regions and GNRA tetraloop in each. Specific bands are sensitive to the effect of the mismatch and asymmetric bulge on the structure of the RNA. Raman band changes are observed that reflect the structural contexts of adenine residues, disruption of A-form helical structure, and incorporation of pyrimidine bases in non-helical regions. The ROA spectra are also sensitive to conformational mobility of ribose sugars, and verify a decrease in A-type helix content upon introduction of the pyrimidine-rich bulge. Several Raman and ROA bands also clearly show cooperative effects between the mismatch and pyrimidine-rich bulge motifs on the structure of the RNA. The complementary nature of Raman and ROA spectra provides detailed and highly sensitive information about the local environments of bases, and secondary and tertiary structures, and has the potential to yield spectral signatures for a wide range of RNA structural motifs.