Raman spectra of biomarkers of relevance to analytical astrobiological exploration: hopanoids, sterols and steranes

Raman Metabolomics of Candida auris Clades: Profiling and Barcode Identification

This study targets on-site/real-time taxonomic identification and metabolic profiling of seven different Candida auris clades/subclades by means of Raman spectroscopy and imaging. Representative Raman spectra from different Candida auris samples were systematically deconvoluted by means of a customized machine-learning algorithm linked to a Raman database in order to decode structural differences at the molecular scale. Raman analyses of metabolites revealed clear differences in cell walls and membrane structure among clades/subclades. Such differences are key in maintaining the integrity and physical strength of the cell walls in the dynamic response to external stress and drugs. It was found that Candida cells use the glucan structure of the extracellular matrix, the degree of α-chitin crystallinity, and the concentration of hydrogen bonds between its antiparallel chains to tailor cell walls’ flexibility. Besides being an effective ploy in survivorship by providing stiff shields in the α–1,3–glucan polymorph, the α–1,3–glycosidic linkages are also water-insoluble, thus forming a rigid and hydrophobic scaffold surrounded by a matrix of pliable and hydrated β–glucans. Raman analysis revealed a variety of strategies by different clades to balance stiffness, hydrophobicity, and impermeability in their cell walls. The selected strategies lead to differences in resistance toward specific environmental stresses of cationic/osmotic, oxidative, and nitrosative origins. A statistical validation based on principal component analysis was found only partially capable of distinguishing among Raman spectra of clades and subclades. Raman barcoding based on an algorithm converting spectrally deconvoluted Raman sub-bands into barcodes allowed for circumventing any speciation deficiency. Empowered by barcoding bioinformatics, Raman analyses, which are fast and require no sample preparation, allow on-site speciation and real-time selection of appropriate treatments.

Raman Spectroscopy of Oral Candida Species: Molecular-Scale Analyses, Chemometrics, and Barcode Identification

Oral candidiasis, a common opportunistic infection of the oral cavity, is mainly caused by the following four Candida species (in decreasing incidence rate): Candida albicans, Candida glabrata, Candida tropicalis, and Candida krusei. This study offers in-depth Raman spectroscopy analyses of these species and proposes procedures for an accurate and rapid identification of oral yeast species. We first obtained average spectra for different Candida species and systematically analyzed them in order to decode structural differences among species at the molecular scale. Then, we searched for a statistical validation through a chemometric method based on principal component analysis (PCA). This method was found only partially capable to mechanistically distinguish among Candida species. We thus proposed a new Raman barcoding approach based on an algorithm that converts spectrally deconvoluted Raman sub-bands into barcodes. Barcode-assisted Raman analyses could enable on-site identification in nearly real-time, thus implementing preventive oral control, enabling prompt selection of the most effective drug, and increasing the probability to interrupt disease transmission.

Use of Raman microspectroscopy to predict malting barley husk adhesion quality

Good quality husk-caryopsis adhesion is essential for malting barley, but that quality is influenced by caryopsis surface lipid composition. Raman spectroscopy was applied to lipid extracts from barley caryopses of cultivars with differential adhesion qualities. Principal component regression indicated that Raman spectroscopy can distinguish among cultivars with good and poor quality adhesion due to differences in compounds associated with adhesion quality.

On the Stability of Deinoxanthin Exposed to Mars Conditions during a Long-Term Space Mission and Implications for Biomarker Detection on Other Planets

Outer space, the final frontier, is a hostile and unforgiving place for any form of life as we know it. The unique environment of space allows for a close simulation of Mars surface conditions that cannot be simulated as accurately on the Earth. For this experiment, we tested the resistance of Deinococcus radiodurans to survive exposure to simulated Mars-like conditions in low-Earth orbit for a prolonged period of time as part of the Biology and Mars experiment (BIOMEX) project. Special focus was placed on the integrity of the carotenoid deinoxanthin, which may serve as a potential biomarker to search for remnants of life on other planets. Survival was investigated by evaluating colony forming units, damage inflicted to the 16S rRNA gene by quantitative PCR, and the integrity and detectability of deinoxanthin by Raman spectroscopy. Exposure to space conditions had a strong detrimental effect on the survival of the strains and the 16S rRNA integrity, yet results show that deinoxanthin survives exposure to conditions as they prevail on Mars. Solar radiation is not only strongly detrimental to the survival and 16S rRNA integrity but also to the Raman signal of deinoxanthin. Samples not exposed to solar radiation showed only minuscule signs of deterioration. To test whether deinoxanthin is able to withstand the tested parameters without the protection of the cell, it was extracted from cell homogenate and exposed to high/low temperatures, vacuum, germicidal UV-C radiation, and simulated solar radiation. Results obtained by Raman investigations showed a strong resistance of deinoxanthin against outer space and Mars conditions, with the only exception of the exposure to simulated solar radiation. Therefore, deinoxanthin proved to be a suitable easily detectable biomarker for the search of Earth-like organic pigment-containing life on other planets.

Recent advances in hopanoids analysis: Quantification protocols overview, main research targets and selected problems of complex data exploration

Pentacyclic triterpenoids, particularly hopanoids, are organism-specific compounds and are generally considered as useful biomarkers that allow fingerprinting and classification of biological, environmental and geological samples. Simultaneous quantification of various hopanoids together with battery of related non-polar and low-molecular mass compounds may provide principal information for geochemical and environmental research focusing on both modern and ancient investigations. Target compounds can be derived from microbial biomass, water columns, sediments, coals, crude fossils or rocks. This create number of analytical problems due to different composition of the analytical matrix and interfering compounds and therefore, proper optimization of quantification protocols for such biomarkers is still the challenge. In this work we summarizing typical analytical protocols that were recently applied for quantification of hopanoids like compounds from different samples. Main steps including components of interest extraction, pre-purification, fractionation, derivatization and quantification involving gas (1D and 2D) as well as liquid separation techniques (liquid-liquid extraction, solid-phase extraction, planar and low resolution column chromatography, high-performance liquid chromatography) are described and discussed from practical point of view, mainly based on the experimental papers that were published within last two years, where significant increase in hopanoids research was noticed. The second aim of this review is to describe the latest research trends concerning determination of hopanoids and related low-molecular mass lipids analyzed in various samples including sediments, rocks, coals, crude oils and plant fossils as well as stromatolites and microbial biomass cultivated under different conditions. It has been found that majority of the most recent papers are based on uni- or bivariate approach for complex data analysis. Data interpretation involves number of physicochemical parameters and hopanoids quantities or given biomarkers mass ratios derived from high-throughput separation and detection systems, typically GC-MS and HPLC-MS. Based on quantitative data reported in recently published experimental works it has been demonstrated that multivariate data analysis using e.g. principal components computations may significantly extend our knowledge concerning proper biomarkers selection and samples classification by means of hopanoids and related non-polar compounds.

Fourier transform infrared spectroscopy and Raman spectroscopy as tools for identification of steryl ferulates

Steryl ferulates are a mixture of minor bioactive compounds, possessing well-established health benefits. However, individual steryl ferulate species show structural differences, which seem to substantially influence their health-promoting potential. In this study, we tested Fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy, as potential tools in the identification of steryl ferulates. On the basis of our spectral data obtained from various individual steryl ferulates and steryl ferulate mixtures extracted from rice (γ-oryzanol), corn bran, and wheat bran, we provide comprehensive peak assignment tables for both FTIR and Raman. With the help of FTIR spectroscopy, structural differences between individual steryl ferulates were possible to identify, such as the presence of the cyclopropane ring and additional differences in the side chain of the sterane skeleton. Data obtained with Raman spectroscopy provided us with a control for FTIR peak assignment and also with some additional information on the samples. However, detecting structural differences between steryl ferulates was not possible with this method. We consider that FTIR spectroscopy alone or combined with Raman provides detailed data on the structures of steryl ferulates. Moreover, thorough peak assignment tables presented in this study could prove to be helpful tools when identifying steryl ferulates, especially as a group, in future studies.

On the origin of the 1602 cm-1 Raman band of yeasts; contribution of ergosterol

The 1602 cm(-1) Raman signature, which we call the "Raman spectroscopic signature of life" in yeasts, is a marker Raman band for cell metabolic activity. Despite the established fact that its intensity sensitively reflects the metabolic status of the cell, its molecular origin remained unclear. In this work, we propose ergosterol as the major contributor of the 1602 cm(-1) Raman signature. The theoretical isotope shift calculation for ergosterol agreed with previous observations. Furthermore, experiments showed that the Raman spectrum of ergosterol corresponds very well with the depleting spectral component in yeast that behaves together with the 1602 cm(-1) signature when the cells are under stress. This work implies that the 1602 cm(-1) Raman signature could serve as an intrinsic ergosterol marker in yeasts for the study of sterol metabolism in vivo and in a label-free manner, which could not be done by any other techniques at the current stage.