Label-free Chemical Imaging of Fungal Spore Walls by Raman Microscopy and Multivariate Curve Resolution Analysis

Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy

Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment. Current methods have limitations that can delay interventions and increase the risk of morbidity and mortality. Raman spectroscopy is a promising alternative to identify capsular serotypes in hypermucoviscous K. pneumoniae isolates. It provides rapid and in situ measurements with minimal sample preparation. Moreover, its combination with machine learning tools demonstrates high accuracy and reproducibility. This study analyzed the viability of combining Raman spectroscopy with one-dimensional convolutional neural networks (1-D CNN) to classify four capsular serotypes of hypermucoviscous K. pneumoniae: K1, K2, K54 and K57. Our approach involved identifying the most relevant Raman features for classification to prevent overfitting in the training models. Simplifying the dataset to essential information maintains accuracy and reduces computational costs and training time. Capsular serotypes were classified with 96 % accuracy using less than 30 Raman features out of 2400 contained in each spectrum. To validate our methodology, we expanded the dataset to include both hypermucoviscous and non-mucoid isolates and distinguished between them. This resulted in an accuracy rate of 94 %. The results obtained have significant potential for practical healthcare applications, especially for enabling the prompt prescription of the appropriate antibiotic treatment against infections.

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Machine learning-assisted SERS approach enables the biochemical discrimination in Bcl-2 and Mcl-1 expressing yeast cells treated with ketoconazole and fluconazole antifungals

Antifungal medications are important due to their potential application in cancer treatment either on their own or with traditional treatments. The mechanisms that prevent the effects of these medications and restrict their usage in cancer treatment are not completely understood. The evaluation and discrimination of the possible protective effects of the anti-apoptotic members of the Bcl-2 family of proteins, critical regulators of mitochondrial apoptosis, against antifungal drug-induced cell death has still scientific uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. However, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time, we investigated the probable protective activities of Bcl-2 and Mcl-1 proteins against cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal drugs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-noise ratio. The analysis of SERS spectral data via advanced unsupervised and supervised machine learning methods enabled unquestionable differentiation (100 %) in samples and biomolecular identification. Various SERS bands related to lipids and proteins observed in the analyses suggest that the expression of these anti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifungals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurements. We strongly believe that the proposed approach paves the way for the evaluation of various biochemical structures/changes in various cells.

In situ monitoring of the shikimate pathway: a combinatorial approach of Raman reverse stable isotope probing and hyperspectral imaging

Sensing and visualization of metabolites and metabolic pathways in situ are significant requirements for tracking their spatiotemporal dynamics in a non-destructive manner. The shikimate pathway is an important cellular mechanism that leads to the de novo synthesis of many compounds containing aromatic rings of high importance such as phenylalanine, tyrosine, and tryptophan. In this work, we present a cost-effective and extraction-free method based on the principles of stable isotope-coupled Raman spectroscopy and hyperspectral Raman imaging to monitor and visualize the activity of the shikimate pathway. We also demonstrated the applicability of this approach for nascent aromatic amino acid localization and tracking turnover dynamics in both prokaryotic and eukaryotic model systems. This method can emerge as a promising tool for both qualitative and semi-quantitative in situ metabolomics, contributing to a better understanding of aromatic ring-containing metabolite dynamics across various organisms.

Regulation of sexual differentiation initiation in Schizosaccharomyces pombe

The fission yeast Schizosaccharomyces pombe is an excellent model organism to explore cellular events owing to rich tools in genetics, molecular biology, cellular biology, and biochemistry. Schizosaccharomyces pombe proliferates continuously when nutrients are abundant but arrests in G1 phase upon depletion of nutrients such as nitrogen and glucose. When cells of opposite mating types are present, cells conjugate, fuse, undergo meiosis, and finally form 4 spores. This sexual differentiation process in S. pombe has been studied extensively. To execute sexual differentiation, the glucose-sensing cAMP-PKA (cyclic adenosine monophosphate-protein kinase A) pathway, nitrogen-sensing TOR (target of rapamycin) pathway, and SAPK (stress-activating protein kinase) pathway are crucial, and the MAPK (mitogen-activating protein kinase) cascade is essential for pheromone sensing. These signals regulate ste11 at the transcriptional and translational levels, and Ste11 is modified in multiple ways. This review summarizes the initiation of sexual differentiation in S. pombe based on results I have helped to obtain, including the work of many excellent researchers.

Competition of Cd(II) and Pb(II) on the bacterial cells: a new insight from bioaccumulation based on NanoSIMS imaging

Polymetallic exposure causes complex toxicity to microorganisms. In this study, we investigated the responses of Escherichia coli under co-existence of cadmium (Cd) and lead (Pb), primarily based on biochemical analysis and RNA sequencing. Cd completely inhibited bacterial growth at a concentration of 2.41 mmol/L, with its removal rate as low as <10%. In contrast, the Pb removal rate was >95% under equimolar sole Pb stress. In addition, the Raman analysis confirmed the loss of proteins for the bacterial cells. Under the co-existence of Cd and Pb, the Cd toxicity to E. coli was alleviated. Meanwhile, the biosorption of Pb cations was more intense during the competitive sorption with Cd. Transmission electron microscopy images showed that a few cells were elongated during incubation, i.e., the average cellular length increased from 1.535 ± 0.407 to 1.845 ± 0.620 µm. Moreover, NanoSIMS imaging showed that the intracellular distribution of Cd and Pb was coupled with sulfur. Genes regulating sulfate transporter were also upregulated to promote sulfate assimilation. Then, the subsequent production of biogenic sulfide and sulfur-containing amino acids was enhanced. Although this strategy based on S enrichment could resist the polymetallic stress, not all related genes were induced to upregulate under sole Cd stress. Therefore, the S metabolism might remodel the microbial resistance to variable occurrence of heavy metals. Furthermore, the competitive sorption (in contrast to sole Cd stress) could prevent microbial cells from strong Cd toxicity.IMPORTANCEMicrobial tolerance and resistance to heavy metals have been widely studied under stress of single metals. However, the polymetallic exposure seems to prevail in the environment. Though microbial resistance can alleviate the effects of exogenous stress, the taxonomic or functional response to polymetallic exposure is still not fully understood. We determined the strong cytotoxicity of cadmium (Cd) on growth, and cell elongation would be driven by Cd stress. The addition of appropriate lead (Pb) showed a stimulating effect on microbial bioactivity. Meanwhile, the biosorption of Pb was more intense during co-existence of Pb and Cd. Our work also revealed the spatial coupling of intracellular S and Cd/Pb. In particular, the S assimilation was promoted by Pb stress. This work elucidated the microbial responses to polymetallic exposure and may provide new insights into the antagonistic function during metal stresses.

Machine learning enabled multiplex detection of periodontal pathogens by surface-enhanced Raman spectroscopy

Periodontitis is a chronic inflammation of the periodontium caused by a persistent bacterial infection, resulting in destruction of the supporting structures of teeth. Analysis of microbial composition in saliva can inform periodontal status. Actinobacillus actinomycetemcomitans (Aa), Porphyromonas gingivalis (Pg), and Streptococcus mutans (Sm) are among reported periodontal pathogens, and were used as model systems in this study. Our atomic force microscopic (AFM) study revealed that these pathogens are biological nanorods with dimensions of 0.6-1.1 μm in length and 500-700 nm in width. Current bacterial detection methods often involve complex preparation steps and require labeled reporting motifs. Employing surface-enhanced Raman spectroscopy (SERS), we revealed cell-type specific Raman signatures of these pathogens for label-free detection. It overcame the complexity associated with spectral overlaps among different bacterial species, relying on high signal-to-noise ratio (SNR) spectra carefully collected from pure species samples. To enable simple, rapid, and multiplexed detection, we harnessed advanced machine learning techniques to establish predictive models based on a large set of raw spectra of each bacterial species and their mixtures. Using these models, given a raw spectrum collected from a bacterial suspension, simultaneous identification of all three species in the test sample was achieved at 95.6 % accuracy. This sensing modality can be applied to multiplex detection of a broader range and a larger set of periodontal pathogens, paving the way for hassle-free detection of oral bacteria in saliva with little to no sample preparation.

Single-Cell Level Raman Molecular Profiling Reveals the Classification of Growth Phases of Chaetoceros tenuissimus

Harmful algal blooms (HABs) are a natural phenomenon caused by outbreaks of algae, resulting in serious problems for aquatic ecosystems and the coastal environment. Chaetoceros tenuissimus (C. tenuissimus) is one of the diatoms responsible for HABs. The growth curve of C. tenuissimus can be observed from beginning to end of HABs: therefore, detailed analysis is necessary to characterize each growth phase of C. tenuissimus. It is important to examine the phenotype of each diatom cell individually, as they display heterogeneity even in the same growth phase. Raman spectroscopy is a label-free technique to elucidate biomolecular profiles and spatial information at the cellular level. Multivariate data analysis (MVA) is an efficient method for the analysis of complicated Raman spectra, to identify molecular features. Here, we utilized Raman microspectroscopy to identify the molecular information of each diatom cell, at the single-cell level. The MVA, together with a support vector machine, which is a machine learning technique, allowed the classification of proliferating and nonproliferating cells. The classification includes polyunsaturated fatty acids such as linoleic acid, eicosapentaenoic acid, and docosahexaenoic acid. This study indicated that Raman spectroscopy is an appropriate technique to examine C. tenuissimus at the single-cell level, providing relevant data to assess the correlation between the molecular details obtained from the Raman analysis, at each growth phase.

Exploring dynamic changes of fungal cellular components during nanoemulsion treatment by multivariate microRaman imaging

Recently, essential oils (EO) have gained a lot of interest for use as antifungal agent in food and agricultural industry and extensive research is ongoing to understand their mode of action. However, the exact mechanism is not yet elucidated. Here, we integrated spectral unmixing and Raman microspectroscopy imaging to unveil the antifungal mechanism of green tea EO based nanoemulsion (NE) against Magnaporthe oryzae. The dramatic change in protein, lipid, adenine, and guanine bands indicate that NE has a significant impact on the protein, lipid and metabolic processes of purine. The results also demonstrated that the NE treatment caused damage to fungal hyphae by inducing a physical injury leading to cell wall damage and loss of integrity. Our study shows that MCR-ALS (Multivariate Curve Resolution-Alternating Least Squares) and N-FINDR (N-finder algorithm) Raman imaging could serve as a suitable complementary package to the traditional methods, for revealing the antifungal mechanism of action of EO/NE.

Automatic classification of Candida species using Raman spectroscopy and machine learning

One of the problems that most affect hospitals is infections by pathogenic microorganisms. Rapid identification and adequate, timely treatment can avoid fatal consequences and the development of antibiotic resistance, so it is crucial to use fast, reliable, and not too laborious techniques to obtain quick results. Raman spectroscopy has proven to be a powerful tool for molecular analysis, meeting these requirements better than traditional techniques. In this work, we have used Raman spectroscopy combined with machine learning algorithms to explore the automatic identification of eleven species of the genus Candida, the most common cause of fungal infections worldwide. The Raman spectra were obtained from more than 220 different measurements of dried drops from pure cultures of each Candida species using a Raman Confocal Microscope with a 532 nm laser excitation source. After developing a spectral preprocessing methodology, a study of the quality and variability of the measured spectra at the isolate and species level, and the spectral features contributing to inter-class variations, showed the potential to discriminate between those pathogenic yeasts. Several machine learning and deep learning algorithms were trained using hyperparameter optimization techniques to find the best possible classifier for this spectral data, in terms of accuracy and lowest possible overfitting. We found that a one-dimensional Convolutional Neural Network (1-D CNN) could achieve above 80 % overall accuracy for the eleven classes spectral dataset, with good generalization capabilities.

Surface-enhanced Raman spectral characterization of antifungal activity of selenium and zinc based organometallic compounds

Surface-enhanced Raman spectroscopy (SERS) is used to identify the biochemical changes associated with the antifungal activities of selenium and zinc organometallic complexes against Aspergillus niger fungus. These biochemical changes identified in the form of SERS peaks can help to understand the mechanism of action of these antifungal agents which is important for development of new antifungal drugs. The SERS spectral changes indicate the denaturation and conformational changes of proteins and fungal cell wall decomposition in complex exposed fungal samples. The SERS spectra of these organometallic complexes exposed fungi are analyzed by using statistical tools like principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). PCA is employed to differentiate the SERS spectra of fungal samples exposed to ligands and complexes. The PLS-DA discriminated different groups of spectra with 99.8% sensitivity, 100% specificity, 98% accuracy and 86 % area under receiver operating characteristic (AUROC) curve.

Raman microscopy tracks maturity of melanin intermediates in Botrytis cinerea, a plant pathogen

We use Raman microscopy to describe the structure and chemical composition of both conidiophore and hyphae of Botrytis cinerea, a common plant pathogen. To interpret experimental data, we use density functional theory (DFT) to compute Raman tensors specific to an important fungal glycopeptide, a segment of α-chitin, and several naphthalene-based precursors of increasing complexity, which we propose play a role in the melanin synthesis pathway. Using spectral interpretations based on quantum chemical validation, we review microscopy images reconstructed for specific Raman activities and describe differences in distributions of structural components, photo-protective secondary naphthalene-based pigments, and proteins in both spores and hyphal filaments. Comparison of our results with literature data on other fungi suggests an example of convergent evolution expressed at the level of secondary metabolites specific to plant pathogenic fungi. Our results indicate that pre-resonant Raman monitoring of melanin precursors may help assessment of local Botrytis population biology to aid agricultural production.

SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms

The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (Lactobacillus spp. and Bifidobacterium spp.) and vaginal pathogens: bacteria (e.g., Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae), fungi (e.g., Candida albicans, Candida glabrata), and protozoa (Trichomonas vaginalis). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of Candida spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between Lactobacillus spp. and Bifidobacterium spp. (natural flora) and pathogen (e.g., Candida glabrata) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for Lactobacillus spp. 1400 cm⁻¹, for fungi 905 and 1209 cm⁻¹, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm⁻¹. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.

Raman Microspectroscopy Imaging Analysis of Extracellular Vesicles Biogenesis by Filamentous Fungus Penicilium chrysogenum

The mechanism of production of extracellular vesicles (EVs) and their molecular contents are of great interest due to their diverse roles in biological systems and are far from being completely understood. Even though cellular cargo releases mediated by EVs have been demonstrated in several cases, their role in secondary metabolite production and release remains elusive. In this study, this aspect is investigated in detail using Raman microspectroscopic imaging. Considerable evidence is provided to suggest that the release of antibiotic penicillin by the filamentous fungus Penicillium chrysogenum involves EVs. Further, the study also reveals morphological modifications of the fungal body during biogenesis, changes in cell composition at the locus of biogenesis, and major molecular contents of the released EVs. The results suggest a possible general role of EVs in the release of antibiotics from the producing organisms.

Surface Chemical and Morphological Analysis of Chitosan/1,3-β-d-Glucan Polysaccharide Films Cross-Linked at 90 °C

The cross-linking temperature of polymers may affect the surface characteristics and molecular arrangement, which are responsible for their mechanical and physico-chemical properties. The aim of this research was to determine and explain in detail the mechanism of unit interlinkage of two-component chitosan/1,3-β-d-glucan matrices gelled at 90 °C. This required identifying functional groups interacting with each other and assessing surface topography providing material chemical composition. For this purpose, various spectroscopic and microscopic approaches, such as attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM), were applied. The results indicate the involvement mainly of the C-C and C-H groups and C=O⋯HN moieties in the process of biomaterial polymerization. Strong chemical interactions and ionocovalent bonds between the N-glucosamine moieties of chitosan and 1,3-β-d-glucan units were demonstrated, which was also reflected in the uniform surface of the sample without segregation. These unique properties, hybrid character and proper cell response may imply the potential application of studied biomaterial as biocompatible scaffolds used in regenerative medicine, especially in bone restoration and/or wound healing.

Development of multi-frequency impedance scanning electron microscopy

Nanometre-scale observation of specimens in water is indispensable in many scientific fields like biology, chemistry, material science and nanotechnology. Scanning electron microscopy (SEM) allows high-resolution images of biological samples to be obtained under high vacuum conditions but requires specific sample-preparation protocols. Therefore, there is a need for convenient and minimally invasive methods of observing samples in solution. We have developed a new type of impedance microscopy, namely multi-frequency impedance SEM (IP-SEM), which allows nanoscale imaging of various specimens in water while minimising radiation damage. By varying the frequency of the input voltage signal of the sine wave, the present system can detect dielectric properties of the sample’s composition at nanometre resolution. It also enables examination of unstained biological specimens and material samples in water. Furthermore, it can be used for diverse samples in liquids across a broad range of scientific subjects such as nanoparticles, nanotubes and organic and catalytic materials.

Raman Micro-spectroscopy and Imaging of Filamentous Fungi

Filamentous fungi grow by the elongation of tubular cells called hyphae and form mycelia through repeated hyphal tip growth and branching. Since hyphal growth is closely related to the ability to secrete large amounts of enzymes or invade host cells, a more detailed understanding and the control of its growth are important in fungal biotechnology, ecology, and pathogenesis. Previous studies using fluorescence imaging revealed many of the molecular mechanisms involved in hyphal growth. Raman microspectroscopy and imaging methods are now attracting increasing attention as powerful alternatives due to their high chemical specificity and label-free, non-destructive properties. Spatially resolved information on the relative abundance, structure, and chemical state of multiple intracellular components may be simultaneously obtained. Although Raman studies on filamentous fungi are still limited, this review introduces recent findings from Raman studies on filamentous fungi and discusses their potential use in the future.

Raman Imaging of Pathogenic Candida auris: Visualization of Structural Characteristics and Machine-Learning Identification

Invasive fungal infections caused by yeasts of the genus Candida carry high morbidity and cause systemic infections with high mortality rate in both immunocompetent and immunosuppressed patients. Resistance rates against antifungal drugs vary among Candida species, the most concerning specie being Candida auris, which exhibits resistance to all major classes of available antifungal drugs. The presently available identification methods for Candida species face a severe trade-off between testing speed and accuracy. Here, we propose and validate a machine-learning approach adapted to Raman spectroscopy as a rapid, precise, and labor-efficient method of clinical microbiology for C. auris identification and drug efficacy assessments. This paper demonstrates that the combination of Raman spectroscopy and machine learning analyses can provide an insightful and flexible mycology diagnostic tool, easily applicable on-site in the clinical environment.

Hybrid material based on subgleba of mosaic puffball mushroom (Handkea utriformis) as an adsorbent for heavy metal removal from aqueous solutions

The alkali treated subglebal tissue of the mosaic puffball (Handkea utriformis) (Sa) and Sa modified with hydroxyapatite (Sa-HAp), obtained by successive ionic layer adsorption and reaction (SILAR) method, were used for the removal of Pb²⁺, Cd²⁺ and Ni²⁺ from aqueous solution. The materials were characterized by FT-IR, Raman, SEM and EDS analysis and by determination of pH_PZC. The adsorption performances of Sa and Sa-HAp were assessed in batch experiments at different pH, contact times, temperatures and mass of the adsorbent. Different models of adsorption isotherms were used, and the best fit was obtained with the Langmuir model. Maximum adsorption capacities of Sa towards Pb²⁺, Cd²⁺ and Ni²⁺ were 44.82, 15.54 and 17.21 mg g^-1, while for Sa-HAp were 79.55, 52.59 and 45.01 mg g^-1, respectively. Kinetic data were well fitted by a pseudo second-order model, while thermodynamic studies disclose spontaneous and endothermic adsorption process. The Sa-Hap was successfully regenerated with 1 M NaCl and after the fifth desorption cycle and 10 h achieved 82.9, 69.7 and 60.4 %, while for 0.5 M NaCl + 0.5 M NaOH and 1 h was 78.3, 64.1, 57.5 % of desorbed Pb²⁺, Cd²⁺ and Ni²⁺, respectively. The competitive study and results from a column system confirmed good applicability of Sa-HAp adsorbent.

DNA Fingerprint Analysis of Raman Spectra Captures Global Genomic Alterations in Imatinib-Resistant Chronic Myeloid Leukemia: A Potential Single Assay for Screening Imatinib Resistance

Monitoring the development of resistance to the tyrosine kinase inhibitor (TKI) imatinib in chronic myeloid leukemia (CML) patients in the initial chronic phase (CP) is crucial for limiting the progression of unresponsive patients to terminal phase of blast crisis (BC). This study for the first time demonstrates the potential of Raman spectroscopy to sense the resistant phenotype. Currently recommended resistance screening strategy include detection of BCR-ABL1 transcripts, kinase domain mutations, complex chromosomal abnormalities and BCR-ABL1 gene amplification. The techniques used for these tests are expensive, technologically demanding and have limited availability in resource-poor countries. In India, this could be a reason for more patients reporting to clinics with advanced disease. A single method which can identify resistant cells irrespective of the underlying mechanism would be a practical screening strategy. During our analysis of imatinib-sensitive and -resistant K562 cells, by array comparative genomic hybridization (aCGH), copy number variations specific to resistant cells were detected. aCGH is technologically demanding, expensive and therefore not suitable to serve as a single economic test. We therefore explored whether DNA finger-print analysis of Raman hyperspectral data could capture these alterations in the genome, and demonstrated that it could indeed segregate imatinib-sensitive and -resistant cells. Raman spectroscopy, due to availability of portable instruments, ease of spectrum acquisition and possibility of centralized analysis of transmitted data, qualifies as a preliminary screening tool in resource-poor countries for imatinib resistance in CML. This study provides a proof of principle for a single assay for monitoring resistance to imatinib, available for scrutiny in clinics.

Effect of slug mycophagy on Tuber aestivum spores

Truffles in the genus Tuber produce subterranean fruiting bodies that are not able to actively discharge their spores in the environment. For this reason, truffles depend on mycophagous animals for reproduction. Fungus consumption (mycophagy) is a behaviour typical of both vertebrates and invertebrates. Mammals, especially rodents, are the most studied group of mycophagists and have been found to consume a great variety of fungi. Among invertebrates, mycophagy is documented in arthropods, but rarely in molluscs. In our study we assessed the effect on the morphology and mycorrhizal colonization of Tuber aestivum spores after passage through the gut of slugs (Deroceras invadens) and, for comparison, of a house mouse (Mus musculus). Light, scanning electron and atomic force microscopy revealed that the digestion, especially by slugs, freed spores from the asci and modified their morphology. These are believed to be the reasons why we observed an improvement in oak mycorrhization with the slug and rodent ingested spores in comparison to a fresh spore inoculation. We also demonstrated by molecular barcoding that slugs' guts sampled on a Tuber melanosporum truffle ground contain spores from this species and Tuber brumale, further suggesting that some invertebrates are efficient Tuber spore dispersers.

Deconstruction of Obscure Features in SVD-Decomposed Raman Images from P. chrysogenum Reveals Complex Mixing of Spectra from Five Cellular Constituents

Raman imaging has transcended in recent times from being an analytical tool to a molecular profiling technique. Biomedical applications of this technique often rely on singular-value decomposition (SVD), principal component analysis (PCA), etc. for data analysis. These methods, however, obliterate the molecular information contained in the original Raman data leading to speculative interpretations based on relative intensities. In the present study, SVD analysis of the Raman images from Penicillium chrysogenum resulted in 11 spectral components and corresponding images with highly distorted spectral features and complex image contrast, respectively. To interpret the SVD results in molecular terms, we have developed a combined multivariate approach. By applying this methodology, we have successfully extracted the contribution of five biomolecular constituents of the P. chrysogenum filamentous cell to the SVD vectors. Molecular interpretability will help SVD/PCA surpass the realm of variance-based classification to a more meaningful molecular domain.

Non-invasive diagnosis of colorectal cancer by Raman spectroscopy: Recent developments in liquid biopsy and endoscopy approaches

Colorectal cancer (CRC) is the third most common cancer diagnosed globally and is also one of the leading causes of cancer deaths in both men and women. The progression of CRC is slow and is often contained in colon but the risk increases with age. Based on the high certainty that the net benefit of screening in an age group is substantial, screening for CRC is recommended beginning at the age of 50. Currently, most of the incidence is concentrated in developed countries but the rate is increasing rapidly in developing geographies. Detecting CRC at an early stage is critical to reduce morbidity and mortality. Colonoscopy is the most preferred screening method but not very widely implemented due to practical considerations such as cost involved, lack of personnel and facility. To address these concerns, Raman spectroscopy (RS) has been suggested as a viable alternative due to its potential as a rapid non-invasive diagnostic tool. Recently, several studies have been reported but many variations of RS applications in CRC exists and are not well understood by non-specialists. This review focuses particularly on developments of Raman based liquid biopsy and endoscopic studies in order to throw light on each of their significance and limitations. Necessary developments in the future to translate RS into a clinical tool for screening and diagnosis of CRC are also briefly presented.

Resonance Raman Spectra for the In Situ Identification of Bacteria Strains and Their Inactivation Mechanism

The resonance Raman spectra of bacterial carotenoids have been employed to identify bacterial strains and their intensity changes as a function of ultraviolet (UV) radiation dose have been used to differentiate between live and dead bacteria. In addition, the resonance-enhanced Raman spectra enabled us to detect bacteria in water at much lower concentrations (∼10⁸ cells/mL) than normally detected spectroscopically. A handheld spectrometer capable of recording resonance Raman spectra in situ was designed, constructed, and was used to record the spectra. In addition to bacteria, the method presented in this paper may also be used to identify fungi, viruses, and plants, in situ, and detect infections within a very short period of time.

Preparation and characterization of a novel green tea essential oil nanoemulsion and its antifungal mechanism of action against Magnaporthae oryzae

Blast is one of the most devastating fungal diseases of rice caused by Magnaporthe oryzae. Plant essential oil (EO) can function as antifungal agents and are regarded as a safe and acceptable method for plant disease control. However, EOs are unstable and hydrophobic, which limits its use. In the present study, we aimed for the preparation and characterization of a nanoemulsion (NE) from green tea essential oil (GTO) by ultrasonication method and determined the antifungal activity of NE onM. oryzae. The particle size and zeta potential of the NE were 86.98 nm and -15.1 mV, respectively. The chemical composition and functional groups of GTO and NE were studied by using GC-MS analysis, portable Raman spectroscopy, and FTIR coupled with chemometric analysis. GC-MS analysis showed the major components in GTO and NE were n-Hexyl cinnamaldehyde and L-α-Terpineol. Both GTO and NE showed good antioxidant activity and total phenol content. Moreover, the NE showed good antifungal activity againstM. oryzae which was further confirmed by scanning electron microscopy (SEM) examination. Also, confocal Raman micro-spectroscopy (CRM) revealed the antifungal mechanism of GTO and NE on M. oryzae which proves the cell damage. To the best of our knowledge, this is the first study on the antifungal activity of GTO and NE against M. oryzae and also the use of CRM for the evaluation of the chemical changes in single fungal hyphae in a holistic approach. This study suggests that the prepared NE could be a potential candidate for use as a substitute for synthetic fungicides.

Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy

Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.

Responses of Rhodotorula mucilaginosa under Pb(II) stress: carotenoid production and budding

Rhodotorula mucilaginosa resists heavy metal (HM) stress because of its abundant extracellular polymeric substances and functional vesicles. In this study, we provided new insights into its survival strategies at both biochemical and genetic levels. After lead exposure, carotenoid biosynthesis was initiated within 24 h incubation and then increased to the maximum after 96 h of incubation. Raman analysis confirmed that carotenoids (primarily β-carotene) were the major identifiable chemical substances on the cell surface. Moreover, the increased carotenoid production was accompanied by a rising budding rate, ~40% higher than that in the cultures without Pb. During the 96 h of incubation, the driving force for Pb accumulation was assigned to this elevated budding rate. After 96 h, biosorption was primarily attributed to the enhanced antioxidant ability of the single cells during carotenoid production. Furthermore, the yeast budding cells demonstrated an evidently heterogeneous biosorption of Pb, i.e., the rejuvenated daughters had a relatively lower Pb level than the mother cells. This resulted in the protection of the buds from Pb stress. After investigating phosphorus uptake and the RNA sequencing data, we finally confirmed two tightly correlated pathways that resist HM stress, i.e., biochemical (carotenoid production) and reproductive (healthy buds) pathways.

Ultraviolet-C inactivation and hydrophobicity of Bacillus subtilis and Bacillus velezensis spores isolated from extended shelf-life milk

Bacterial spores are important in food processing due to their ubiquity, resistance to high temperature and chemical inactivation. This work aims to study the effect of ultraviolet C (UVC) on the spores of Bacillus subtilis and Bacillus velezensis at a molecular and individual level to guide in deciding on the right parameters that must be applied during the processing of liquid foods. The spores were treated with UVC using phosphate buffer saline (PBS) as a suspension medium and their lethality rate was determined for each sample. Purified spore samples of B. velezensis and B. subtilis were treated under one pass in a UVC reactor to inactivate the spores. The resistance pattern of the spores to UVC treatment was determined using dipicolinic acid (Ca-DPA) band of spectral analysis obtained from Raman spectroscopy. Flow cytometry analysis was also done to determine the effect of the UVC treatment on the spore samples at the molecular level. Samples were processed for SEM and the percentage spore surface hydrophobicity was also determined using the Microbial Adhesion to Hydrocarbon (MATH) assay to predict the adhesion strength to a stainless-steel surface. The result shows the maximum lethality rate to be 6.5 for B. subtilis strain SRCM103689 (B47) and highest percentage hydrophobicity was 54.9% from the sample B. velezensis strain LPL-K103 (B44). The difference in surface hydrophobicity for all isolates was statistically significant (P < 0.05). Flow cytometry analysis of UVC treated spore suspensions clarifies them further into sub-populations unaccounted for by plate counting on growth media. The Raman spectroscopy identified B4002 as the isolate possessing the highest concentration of Ca-DPA. The study justifies the critical role of Ca-DPA in spore resistance and the possible sub-populations after UVC treatment that may affect product shelf-life and safety. UVC shows a promising application in the inactivation of resistant spores though there is a need to understand the effects at the molecular level to design the best parameters during processing.

Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis

Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis–alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells.

Non-traditional intrinsic luminescence from non-conjugated polymer dots: designing a hybrid biomaterial

Herein, an eco-friendly and facile synthesis of nitrogen-containing non-conjugated polymer dots (NCPD) with optimal blue emission is reported from the biopolymer β-glucan with a peptide–polysaccharide linkage (namely NH2-β-glucan).

Activity and Mechanism of Action of the Bioceramic Silicon Nitride as an Environmentally Friendly Alternative for the Control of the Grapevine Downy Mildew Pathogen Plasmopara viticola

Downy mildew of grapevine, caused by Plasmopara viticola (Berk. and Curt.) Berl. and de Toni, is one of the most devastating diseases of grapevine, severely affecting grape and wine production and quality worldwide. Infections are usually controlled by the intensive application of synthetic fungicides or by copper-based products in organic farming, rising problems for soil contamination and adverse impacts on environment and human health. While strict regulations attempt to minimize their harmful consequences, the situation calls for the development of alternative fungicidal strategies. This study presents the unprecedented case of a bioceramic, silicon nitride, with antimicrobial properties against P. viticola, but without adverse effects on human cells and environment, opening the way to the possible extension of silicon nitride applications in agriculture. Raman spectroscopic assessments of treated sporangia in conjunction with microscopic observations mechanistically showed that the nitrogen-chemistry of the bioceramic surface affects pathogen's biochemical components and cell viability, thus presenting a high potential for host protection from P. viticola infections.

Evaluation of the Cultivated Mushroom Pleurotus ostreatus Basidiocarps Using Vibration Spectroscopy and Chemometrics

Fruiting bodies (basidiocarps) of the cultivated mushroom Pleurotus ostreatus (16 strains) were characterized by vibration spectroscopy and chemometrics. According to organic elemental analysis and Megazyme assay, the basidiocarps contained ~6.2–17.5% protein and ~18.8–58.2% total glucans. The neutral sugar analysis confirmed that glucose predominated in all the samples (~71.3–94.4 mol%). Fourier-transformed (FT) mid- and near-infrared (FT MIR, FT NIR) and FT Raman spectra of the basidiocarps were recorded, and the characteristic bands of proteins, glucans and chitin were assigned. The samples were discriminated based on principal component analysis (PCA) of the spectroscopic data in terms of biopolymeric composition. The partial least squares regression (PLSR) models based on first derivatives of the vibration spectra were obtained for the prediction of the macromolecular components, and the regression coefficients R2 and root mean square errors (RMSE) were calculated for the calibration (cal) of proteins (R2cal 0.981–0.994, RMSEcal ~0.3–0.5) and total glucans (R2cal 0.908–0.996, RMSEcal ~0.6–3.0). According to cross-validation (CV) diagnosis, the protein models were more precise and accurate (R2cv 0.901–0.970, RMSEcv ~0.6–1.1) than the corresponding total glucan models (R2cv 0.370–0.804, RMSEcv ~4.7–8.5) because of the wide structural diversity of these polysaccharides. Otherwise, the Raman band of phenylalanine ring breathing vibration at 1004 cm−1 was used for direct quantification of proteins in P. ostreatus basidiocarps (R ~0.953). This study showed that the combination of vibration spectroscopy with chemometrics is a powerful tool for the evaluation of culinary and medicinal mushrooms, and this approach can be proposed as an alternative to common analytical methods.

Multiscale Analysis of Metal Oxide Nanoparticles in Tissue: Insights into Biodistribution and Biotransformation

Metal oxide nanoparticles have emerged as exceptionally potent biomedical sensors and actuators due to their unique physicochemical features. Despite fascinating achievements, the current limited understanding of the molecular interplay between nanoparticles and the surrounding tissue remains a major obstacle in the rationalized development of nanomedicines, which is reflected in their poor clinical approval rate. This work reports on the nanoscopic characterization of inorganic nanoparticles in tissue by the example of complex metal oxide nanoparticle hybrids consisting of crystalline cerium oxide and the biodegradable ceramic bioglass. A validated analytical method based on semiquantitative X-ray fluorescence and inductively coupled plasma spectrometry is used to assess nanoparticle biodistribution following intravenous and topical application. Then, a correlative multiscale analytical cascade based on a combination of microscopy and spectroscopy techniques shows that the topically applied hybrid nanoparticles remain at the initial site and are preferentially taken up into macrophages, form apatite on their surface, and lead to increased accumulation of lipids in their surroundings. Taken together, this work displays how modern analytical techniques can be harnessed to gain unprecedented insights into the biodistribution and biotransformation of complex inorganic nanoparticles. Such nanoscopic characterization is imperative for the rationalized engineering of safe and efficacious nanoparticle-based systems.

Organelle specific simultaneous Raman/green fluorescence protein microspectroscopy for living cell physicochemical studies

We demonstrate a novel bio-spectroscopic technique, "simultaneous Raman/GFP microspectroscopy". It enables organelle specific Raman microspectroscopy of living cells. Fission yeast, Schizosaccharomyces pombe, whose mitochondria are green fluorescence protein (GFP) labeled, is used as a test model system. Raman excitation laser and GFP excitation light irradiate the sample yeast cells simultaneously. GFP signal is monitored in the anti-Stokes region where interference from Raman scattering is negligibly small. Of note, 13 568 Raman spectra measured from different points of 19 living yeast cells are categorized according to their GFP fluorescence intensities, with the use of a two-component multivariate curve resolution with alternate least squares (MCR-ALS) analysis in the anti-Stokes region. This categorization allows us to know whether or not Raman spectra are taken from mitochondria. Raman spectra specific to mitochondria are obtained by an MCR-ALS analysis in the Stokes region of 1389 strongly GFP positive spectra. Two mitochondria specific Raman spectra have been obtained. The first one is dominated by protein Raman bands and the second by lipid Raman bands, being consistent with the known molecular composition of mitochondria. In addition, the second spectrum shows a strong band of ergosterol at 1602 cm^-1 , previously reported as "Raman spectroscopic signature of life of yeast."

Raman Scattering: From Structural Biology to Medical Applications

This is a review of relevant Raman spectroscopy (RS) techniques and their use in structural biology, biophysics, cells, and tissues imaging towards development of various medical diagnostic tools, drug design, and other medical applications. Classical and contemporary structural studies of different water-soluble and membrane proteins, DNA, RNA, and their interactions and behavior in different systems were analyzed in terms of applicability of RS techniques and their complementarity to other corresponding methods. We show that RS is a powerful method that links the fundamental structural biology and its medical applications in cancer, cardiovascular, neurodegenerative, atherosclerotic, and other diseases. In particular, the key roles of RS in modern technologies of structure-based drug design are the detection and imaging of membrane protein microcrystals with the help of coherent anti-Stokes Raman scattering (CARS), which would help to further the development of protein structural crystallography and would result in a number of novel high-resolution structures of membrane proteins—drug targets; and, structural studies of photoactive membrane proteins (rhodopsins, photoreceptors, etc.) for the development of new optogenetic tools. Physical background and biomedical applications of spontaneous, stimulated, resonant, and surface- and tip-enhanced RS are also discussed. All of these techniques have been extensively developed during recent several decades. A number of interesting applications of CARS, resonant, and surface-enhanced Raman spectroscopy methods are also discussed.

Spectral counterstaining in luminescence-enhanced biological Raman microscopy

Cell imaging heavily depends on fluorescent labels typically incompatible with Raman microscopy. The europium(iii) complex based on dipicolinic acid (DPA) presented here is an exception from this rule. Although its luminescence bands are very narrow, their intensity is comparable to the background Raman bands. This makes it complementary to less luminous compounds referred to as Raman tags. Through several examples we show that the complex provides a morphological context in otherwise unstained cells, thus acting as a spectral-counterstaining agent.

Whole-Organism Analysis by Vibrational Spectroscopy

Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

Visualizing wax ester fermentation in single Euglena gracilis cells by Raman microspectroscopy and multivariate curve resolution analysis

BACKGROUND

Global demand for energy is on the rise at a time when limited natural resources are fast depleting. To address this issue, microalgal biofuels are being recommended as a renewable and eco-friendly substitute for fossil fuels. Euglena gracilis is one such candidate that has received special interest due to their ability to synthesize wax esters that serve as precursors for production of drop-in jet fuel. However, to realize economic viability and achieve industrial-scale production, development of novel methods to characterize algal cells, evaluate its culture conditions, and construct appropriate genetically modified strains is necessary. Here, we report a Raman microspectroscopy-based method to visualize important metabolites such as paramylon and ester during wax ester fermentation in single Euglena gracilis cells in a label-free manner.

RESULTS

We measured Raman spectra to obtain intracellular biomolecular information in Euglena under anaerobic condition. First, by univariate approach, we identified Raman markers corresponding to paramylon/esters and constructed their time-lapse chemical images. However, univariate analysis is severely limited in its ability to obtain detailed information as several molecules can contribute to a Raman band. Therefore, we further employed multivariate curve resolution analysis to obtain chain length-specific information and their abundance images of the produced esters. Accumulated esters in Euglena were particularly identified to be myristyl myristate (C28), a wax ester candidate suitable to prepare drop-in jet fuel. Interestingly, we found accumulation of two different forms of myristyl myristate for the first time in Euglena through our exploratory multivariate analysis.

CONCLUSIONS

We succeeded in visualizing molecular-specific information in Euglena during wax ester fermentation by Raman microspectroscopy. It is obvious from our results that simple univariate approach is insufficient and that multivariate curve resolution analysis is crucial to extract hidden information from Raman spectra. Even though we have not measured any mutants in this study, our approach is directly applicable to other systems and is expected to deepen the knowledge on lipid metabolism in microalgae, which eventually leads to new strategies that will help to enhance biofuel production efficiency in the future.

Multiphoton fluorescence lifetime imaging microscopy (FLIM) and super-resolution fluorescence imaging with a supramolecular biopolymer for the controlled tagging of polysaccharides

A new supramolecular polysaccharide complex, comprising a functionalised coumarin tag featuring a boronic acid and β-d-glucan (a natural product extract from barley, Hordeum Vulgare) was assembled based on the ability of the boronate motif to specifically recognise and bind to 1,2- or 1,3-diols in water. The complexation ratio of the fluorophore : biopolymer strand was determined from fluorescence titration experiments in aqueous environments and binding isotherms best described this interaction using a 2 : 1 model with estimated association constants of K2:1a1 = 5.0 × 104 M-1 and K2:1a2 = 3.3 × 1011 M-1. The resulting hybrid (denoted 5@β-d-glucan) was evaluated for its cellular uptake as an intact functional biopolymer and its distribution compared to that of the pinacol-protected coumarin boronic acid derivative using two-photon fluorescence lifetime imaging microscopy (FLIM) in living cells. The new fluorescent β-d-glucan conjugate has a high kinetic stability in aqueous environments with respect to the formation of the free boronic acid derivative compound 5 and retains fluorescence emissive properties both in solution and in living cells, as shown by two-photon fluorescence spectroscopy coupled with time-correlated single photon counting (TCSPC). Super-resolution fluorescence imaging using Airyscan detection as well as TM AFM and Raman spectroscopy investigations confirmed the formation of fluorescent and nano-dimensional aggregates of up to 20 nm dimensions which self-assemble on several different inert surfaces, such as borosilicate glass and mica surfaces, and these aggregates can also be observed within living cells with optical imaging techniques. The cytoplasmic distribution of the 5@β-d-glucan complex was demonstrated in several different cancer cell lines (HeLa and PC-3) as well as in healthy cells (J774.2 macrophages and FEK-4). Both new compounds (pinacol protected boronated coumarin) 5-P and its complex hybrid 5@β-d-glucan successfully penetrate cellular membranes with the minimum morphological alterations to cells and distribute evenly in the cytoplasm. The glucan biopolymer retains its activity towards macrophages in the presence of the coumarin tag functionality, demonstrating the potential of this natural β-d-glucan to act as a functional self-assembled theranostic scaffold capable of mediating the delivery of anchored small organic molecules with imaging and drug delivery applications.

Fibril formation and therapeutic targeting of amyloid-like structures in a yeast model of adenine accumulation

The extension of the amyloid hypothesis to include non-protein metabolite assemblies invokes a paradigm for the pathology of inborn error of metabolism disorders. However, a direct demonstration of the assembly of metabolite amyloid-like structures has so far been provided only in vitro. Here, we established an in vivo model of adenine self-assembly in yeast, in which toxicity is associated with intracellular accumulation of the metabolite. Using a strain blocked in the enzymatic pathway downstream to adenine, we observed a non-linear dose-dependent growth inhibition. Both the staining with an indicative amyloid dye and anti-adenine assemblies antibodies demonstrated the accumulation of adenine amyloid-like structures, which were eliminated by lowering the supplied adenine levels. Treatment with a polyphenol inhibitor reduced the occurrence of amyloid-like structures while not affecting the dramatic increase in intracellular adenine concentration, resulting in inhibition of cytotoxicity, further supporting the notion that toxicity is triggered by adenine assemblies.

Small molecule metabolites like phenylalanine can form amyloid-like structures but so far this has only been demonstrated in vitro. Here the authors generate a yeast in vivo model of adenine self-assembly and characterize the adenine assemblies in cells by indicative amyloid dye and anti-adenine assemblies antibodies.

Resistance and Raman spectroscopy analysis of Parageobacillus thermantarcticus spores after γ-ray exposure

Spores of the genus Bacillus are able to resist ionizing radiations and therefore they are a suitable biological model for studies in Astrobiology, i.e. the multidisciplinary approach to the study of the origin and evolution of life on Earth and in the universe. The resistance to γ-radiation is an important issue in Astrobiology in relation to the search for bacterial species that could adapt to life in space. This study investigates the resistance of spores of the thermophilic bacteria Parageobacillus thermantarcticus to γ-rays. The analysis of spores' response to irradiation at a molecular level is performed by means of Raman spectroscopy that allows to get insights in the sequence of events taking place during inactivation. The role of the γ-rays' dose in the inactivation of spores is also investigated, allowing to highlight the mechanism(s) of inactivation including DNA damage, protein denaturation and calcium dipicolinate levels.

Biological and Medical Applications of Multivariate Curve Resolution Assisted Raman Spectroscopy

Biological specimens such as cells, tissues and biofluids (urine, blood) contain mixtures of many different biomolecules, all of which contribute to a Raman spectrum at any given point. The separation and identification of pure biochemical components remains one of the biggest challenges in Raman spectroscopy. Multivariate curve resolution, a matrix factorization method, is a powerful, yet flexible, method that can be used with constraints, such as non-negativity, to decompose a complex spectroscopic data matrix into a small number of physically meaningful pure spectral components along with their relative abundances. This paper reviews recent applications of multivariate curve resolution by alternating least squares analysis to Raman spectroscopic and imaging data obtained either in vivo or in vitro from biological and medical samples.

Single cell assessment of yeast metabolic engineering for enhanced lipid production using Raman and AFM-IR imaging

BACKGROUND

Biodiesel is a valuable renewable fuel made from derivatized fatty acids produced in plants, animals, and oleaginous microbes. Of the latter, yeasts are of special interest due to their wide use in biotechnology, ability to synthesize fatty acids and store large amounts of triacylglycerols while utilizing non-food carbon sources. While yeast efficiently produce lipids, genetic modification and indeed, lipid pathway metabolic engineering, is usually required for cost-effective production. Traditionally, gas chromatography (GC) is used to measure fatty acid production and to track the success of a metabolic engineering strategy in a microbial culture; here we have employed vibrational spectroscopy approaches at population and single cell level of engineered yeast while simultaneously investigating metabolite levels in subcellular structures.

RESULTS

Firstly, a strong correlation (r² > 0.99) was established between Fourier transform infrared (FTIR) lipid in intact cells and GC analysis of fatty acid methyl esters in the differently engineered strains. Confocal Raman spectroscopy of individual cells carrying genetic modifications to enhance fatty acid synthesis and lipid accumulation revealed changes to the lipid body (LB), the storage organelle for lipids in yeast, with their number increasing markedly (up to tenfold higher); LB size was almost double in the strain that also expressed a LB stabilizing gene but considerable variation was also noted between cells. Raman spectroscopy revealed a clear trend toward reduced unsaturated fatty acid content in lipids of cells carrying more complex metabolic engineering. Atomic force microscopy-infrared spectroscopy (AFM-IR) analysis of individual cells indicated large differences in subcellular constituents between strains: cells of the most highly engineered strain had elevated lipid and much reduced carbohydrate in their cytoplasm compared with unmodified cells.

CONCLUSIONS

Vibrational spectroscopy analysis allowed the simultaneous measurement of strain variability in metabolite production and impact on cellular structures as a result of different gene introductions or knockouts, within a lipid metabolic engineering strategy and these inform the next steps in comprehensive lipid engineering. Additionally, single cell spectroscopic analysis measures heterogeneity in metabolite production across microbial cultures under genetic modification, an emerging issue for efficient biotechnological production.

Genus- and species-level identification of dermatophyte fungi by surface-enhanced Raman spectroscopy

This paper demonstrates that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) can serve as a fast and reliable technique for detection and identification of dermatophyte fungi at both genus and species level. Dermatophyte infections are the most common mycotic diseases worldwide, affecting a quarter of the human population. Currently, there is no optimal method for detection and identification of fungal diseases, as each has certain limitations. Here, for the first time, we have achieved with a high accuracy, differentiation of dermatophytes representing three major genera, i.e. Trichophyton, Microsporum, and Epidermophyton. Two first principal components (PC), namely PC-1 and PC-2, gave together 97% of total variance. Additionally, species-level identification within the Trichophyton genus has been performed. PC-1 and PC-2, which are the most diagnostically significant, explain 98% of the variance in the data obtained from spectra of: Trichophyton rubrum, Trichophyton menatgrophytes, Trichophyton interdigitale and Trichophyton tonsurans. This study offers a new diagnostic approach for the identification of dermatophytes. Being fast, reliable and cost-effective, it has the potential to be incorporated in the clinical practice to improve diagnostics of medically important fungi.

Developing Raman spectroscopy as a diagnostic tool for label-free antigen detection

For several decades, a multitude of studies have documented the ability of Raman spectroscopy (RS) to differentiate between tissue types and identify pathological changes to tissues in a range of diseases. Furthermore, spectroscopists have illustrated that the technique is capable of detecting disease-specific alterations to tissue before morphological changes become apparent to the pathologist. This study draws comparisons between the information that is obtainable using RS alongside immunohistochemistry (IHC), since histological examination is the current GOLD standard for diagnosing a wide range of diseases. Here, Raman spectral maps were generated using formalin-fixed, paraffin-embedded colonic tissue sections from healthy patients and spectral signatures from principal components analysis (PCA) were compared with several IHC markers to confirm the validity of their localizations. PCA loadings identified a number of signatures that could be assigned to muscle, DNA and mucin glycoproteins and their distributions were confirmed with antibodies raised against anti-Desmin, anti-Ki67 and anti-MUC2, respectively. The comparison confirms that there is excellent correlation between RS and the IHC markers used, demonstrating that the technique is capable of detecting compositional changes in tissue in a label-free manner, eliminating the need for antibodies.

Imaging phospholipid conformational disorder and packing in giant multilamellar liposome by confocal Raman microspectroscopy

Liposomes are closed phospholipid bilayer systems that have profound applications in fundamental cell biology, pharmaceutics and medicine. Depending on the composition (pure or mixture of phospholipids, presence of cholesterol) and preparation protocol, intra- and inter-chain molecular interactions vary leading to changes in the quality (order and packing) of liposomes. So far it is not possible to image conformational disorders and packing densities within a liposome in a straightforward manner. In this study, we utilized confocal Raman microspectroscopy to visualize structural disorders and packing efficiency within a giant multilamellar liposome model by focusing mainly on three regions in the vibrational spectrum (CC stretching, CH deformation and CH stretching). We estimated properties such as trans/gauche isomers and lateral packing probability. Interestingly, our Raman imaging studies revealed gel phase rich domains and heterogeneous lateral packing within the giant multilamellar liposome.