Antimicrobial Resistant (AMR) fungal pathogens do not respond to conventional treatments, causing lethal infections, especially in immunocompromised people. The urgent need for fast, reliable, and highly specific diagnostic methods to control this silent pandemic is evident. Raman Spectroscopy methods have great potential for the detection and identification of microbial pathogens, either label- free or using specific Raman tags and probes. We are developing carbohydrate-based Raman probes aiming to achieve selective pathogen detection inspired by the first steps of infection, during which pathogens adhere to the surface of host cells via carbohydrateprotein interactions. Previously, our group identified an aromatic-core divalent galactoside, that mimics host cell carbohydrates and recognizes Candida albicans, a critical priority fungal pathogen. We have synthesized thiol-bearing derivatives of this compound, which are attached to the surface of gold nanoparticles to create novel Raman glycoprobes capable of binding C. albicans. These novel glycoprobes will be studied for the capture, detection and chemical imaging of fungal pathogens, such as C. albicans and Aspergillus fumigatus using coherent Raman spectroscopic techniques. Ultimately, we aim to optimize this approach for the capture, imaging and identification of multiple pathogens in a biological sample. Herein, we present our current progress.
The capability of Raman spectroscopy for biological cell classification has been previously reported and is shown to be well suited for research purposes. The implementation in the clinical setting for such tasks as cell counting and pathology is prohibited by the required acquisition time due to the low scattering cross section present. In this work, we present a study on the capability of broadband coherent anti-Stokes Raman scattering (BCARS) using a fiber laser, for white blood cell analysis. The improvements in acquisition time afforded by the coherent process in BCARS could potentially allow for hyperspectral imaging and cell classification or cellomics, but there are known drawbacks in BCARS such as the quadratic concentration dependence and nonresonant background. We provide some initial results on comparing the spontaneous Raman spectrum of a plasmacytoid dendritic cell line, with the corresponding BCARS spectrum. We offer an approach whereby a single BCARS spectrum can be obtained for a single cell from a hyperspectral image, for the purpose of a potential downstream cell classification.
Microplastics contamination in water sources presents a pressing concern for environmental and public health, necessitating accurate detection and quantification methods. We investigate the application of broadband Coherent anti-Stokes Raman Spectroscopy (BCARS) as an innovative, rapid, and label-free spectroscopy method for the detection of microplastics in drinking water. Current methods for detecting microplastics, such as visual inspection, FTIR and spontaneous Raman spectroscopy, and gas chromatography, have limitations in terms of sensitivity, speed, specificity, or destructive analysis. BCARS, however, offers a non-destructive approach with the capability to identify particles smaller than a micron and to discern different types of plastics through chemical analysis. BCARS operates at a significantly faster rate than spontaneous Raman spectroscopy, reducing acquisition time from seconds to milliseconds. BCARS utilizes a dual excitation technique to simultaneously probe both the fingerprint and C-H band regions of the Raman spectrum and allows for the identification of different polymers in a sample, as demonstrated in this study with a mixture of Polystyrene and Poly(methyl methacrylate) (PMMA) micro-beads. Our results highlight the ability of B-CARS to distinguish between different types of polymers in a sample, using resonant peaks at specific wave-numbers to generate a false-color image for easy identification.
Broadband CARS is commonly used to study tissue sections of biological samples utilizing the inherent vibrational contrast present due to molecular vibrations. This technique however, is notably hindered by the ubiquitous non-resonant background (NRB) that plagues the interpretation of images. Nevertheless, a promising avenue is polarization suppression which was previously reported for single frequency CARS and has shown efficacy in NRB removal. Here, we employ polarization suppression using two acquisitions for interferometric NRB rejection, which has previously been applied to polymers and liquids. The spectral interferometric method requires only passive polarization optics, in addition to a BCARS system. The method was applied to the BCARS imaging of fungal spores and compared to the spectra obtained from the Kramers-Kronig phase retrieval algorithm.
The third-order nonlinear nature of Broadband CARS means it has the inherent capability to produce label-free images using vibrational information as contrast. The speed of the technique is several orders of magnitude greater than spontaneous Raman spectroscopy. This has implications for enabling diagnostics in areas such as histology, immunology and cytology. The major drawback in BCARS currently preventing these applications is mainly the nonresonant background, present due to degenerate four-wave mixing. This background can be removed using the tensorial properties of the electronic susceptibility. This technique is known as spectral interferometric polarization CARS (SIP-CARS). We show an implementation of SIP-CARS on highly resonant polymer beads for spectroscopic imaging using two sequential BCARS scans to probe different components of the susceptibility tensor.
The application of Broadband CARS to cell imaging studies has thus far been limited to those where high contrast features are present, such as lipids and exogenously introduced tags. This is due to the inherent low SNR obtained in BCARS from the low density of oscillators in single cells coupled with the non-resonant background present in all media which distorts the measured signal. In this paper, we show that an autoencoder which we named VECTOR2, trained on simulated spectra, can accurately perform NRB removal of recorded BCARS images of unstained biological specimen. This allows cell imaging comparable in time to spontaneous Raman imaging with high bandwidth and resolution. The introduction of standard baseline flattening prior to NRB removal preserves the image structure while removing artefacts from raster scanning and optical noise. This results in a hyperspectral image of the NRB-free BCARS signal which is linear in the sample concentration and has a spectrum that is very similar to the spontaneous Raman spectrum.
MicroRNAs are small ~22 nucleotide RNA sequences that are guided to the 3’ untranslated region (UTR) of protein-coding target mRNA sequences. One particular microRNA, miR155, plays a remarkable role in the immune system, where it is essential for mounting appropriate immune responses. However, its dysregulation has been identified in multiple inflammatory disorders such as Multiple Sclerosis (MS), arthritis, psoriasis and colitis. More specifically, miR-155 has been found to be elevated in the serum and brain lesions of MS patients. Importantly, therapeutic inhibition of miR-155 can inhibit progression of the MS disease model. One of us has identified that macrophages are major contributor to miR-155 elevation in the MS disease model, whilst its inhibition specifically in macrophages can limit the disease. Here macrophages were isolated from the femur and tibia of wild-type (WT) mice and mice with a knock-out (KO) of the gene regulating miR-155 production, and were cultured in-vitro and stimulated with lipopolysaccharide (LPS) to simulate an immune response. Cells were then prepared for spectral analysis by FTIR imaging with a Perkin-Elmer Spotlight 400 imaging microscope. After pre-processing the dimensionality of spectra were reduced using principal components analysis, kernel-PCA and universal manifold application and projection (UMAP) and classified using a support vector machine algorithm, delivering a classification performance approaching F1~0.89. Spectral features differentiating WT and KO classes were observed across the fingerprint region with no single spectral marker being the sole source of differentiation of the downstream molecular events. This study exemplifies the challenge in spectral discrimination of the complexity of molecular events in ex-vivo models of immune dysregulation.
Multi-modal spectroscopic analysis of biological systems may offer an improved overall non-invasive biophotonic metric of the status of the system, further enhancing the diagnostic and prognostic capabilities of these technologies. In the present study macrophages were extracted from wild-type mice and mice with a knock-out of the gene regulating miR-155, which has been observed to occur in patients with various autoimmune disorders, including multiple sclerosis (MS). Macrophages were stimulated in-vitro to produce an immune response and were then screened spectroscopically with FTIR and Raman spectroscopy (at 532nm and 660nm). Low, medium and high level data fusion strategies for classification of response to stimulation and miRNA regulation were piloted, using downstream principal components analysis-support vector machine classifiers to test the impact of these strategies on classification performance. These techniques allowed the development of a combined highlevel data-fusion, classification pipeline with a high level of classification accuracy (F1<0.9), with reduced variability in performance. Our proposed spectroscopic assay-data fusion strategy may provide an adjunct to clinical screening and diagnosis of various autoimmune disorders whose aetiology is associated with genetic dysregulation.
Raman micro-spectroscopy (RMS) is a powerful technique for the identification, classification, and diagnosis of cancer cells and tissues.1 The requirement for long acquisition times of 1-30 s have impeded clinical application. The slow acquisition time can be overcome by the use of coherent Raman scattering (CRS), a class of thirdorder nonlinear optical spectroscopies that employ a sequence of light pulses to set-up a vibrational coherence within the ensemble of molecules inside the laser focus. The two most widely employed CRS techniques are coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS) both of which achieve extremely high acquisition speeds up to the video rate, but traditional architectures are limited in terms of “single frequency” detection resulting from the use of picosecond pump and Stokes pulses with an optical bandwidth of a few wavenumbers. An important breakthrough has been recently achieved by the Cicerone group2 using a femtosecond Er:fiber laser oscillator followed by two erbium doped fiber amplifier arms; one arm is frequency doubled to generate narrow-band pulses at 770 nm with a flat-top 3.8 ps temporal profile, while the other is spectrally broadened in a highly non-linear fiber to generate a broad supercontinuum spanning the 900–1350 nm wavelength region. This pulse combination enables extraction of the CARS response by both the two-color and the three-color mechanism. While all previous broadband CARS systems failed to provide a low-noise spectrum in the fingerprint region, this approach has enabled Raman spectra in the whole biologically relevant frequency region (500–3500 cm-1) to be captured with 10 cm-1 resolution and 3.5 ms acquisition. Here, we provide guidance on the initial setup and optimization of this bCARS micro-spectroscopy system, with specific examples of the common pitfalls encountered during the setup. This is particularly useful for those coming from a background of designing spontaneous Raman spectroscopy systems for biomedical applications.
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