Isotope labeled 3D-Raman confocal imaging and atomic force microscopy study on epithelial cells interacting with the fungus Candida albicans.

The human pathogenic fungus Candida albicans damages epithelial cells during superficial infections. Here we use three-dimensional-sequential-confocal Raman spectroscopic imaging and atomic force microscopy to investigate the interaction of C. albicans wild type cells, the secreted C. albicans peptide toxin candidalysin and mutant cells lacking candidalysin with epithelial cells. The candidalysin is responsible for epithelial cell damage and exhibits in its deuterated form an identifiable Raman signal in a frequency region distinct from the cellular frequency region. Vibration modes at 2100-2200 cm-1 attributed to carbon­deuterium bending and at 477 cm-1, attributed to the nitrogen­deuterium out-of-plane bending, found around the nucleus, can be assigned to deuterated candidalysin. Atomic force microscopy visualized 100 nm deep lesions on the cell and force-distance curves indicate the higher adhesion on pore surrounding after incubation with candidalysin. Candidalysin targets the plasma membrane, but is also found inside of the cytosol of epithelial cells during C. albicans infection.

Selection of ssDNA aptamers and construction of aptameric electrochemical biosensor for the detection of Giardia intestinalis trophozoite protein.

Giardia intestinalis is one of the most widespread intestinal parasites and is considered a major cause of epidemic or sporadic diarrhea worldwide. In this study, we aimed to develop a rapid aptameric diagnostic technique for G. intestinalis infection. First, the SELEX (Systematic Evolution of Ligands by Exponential Enrichment) process generated DNA aptamers specific to a recombinant protein of the parasite's trophozoite. Ten selection rounds were performed; each round, the DNA library was incubated with the target protein conjugated to Sepharose beads. Then, the unbound sequences were removed by washing and the specific sequences were eluted and amplified by Polymerase Chain Reaction (PCR). Two aptamers were selected, and the dissociation constants (Kd), were determined as 2.45 and 16.95 nM, showed their high affinity for the G. intestinalis trophozoite protein. Subsequently, the aptamer sequence T1, which exhibited better affinity, was employed to develop a label-free electrochemical biosensor. A thiolated aptamer was covalently immobilized onto a gold screen-printed electrode (SPGE), and the binding of the targeted protein was monitored using square wave voltammetry (SWV). The developed aptasensor enabled accurate detection of the G. intestinalis recombinant protein within the range of 0.1 pg/mL to 100 ng/mL, with an excellent sensitivity (LOD of 0.35 pg/mL). Moreover, selectivity studies showed a negligible cross-reactivity toward other proteins such as bovine serum albumin, globulin, and G. intestinalis cyst protein.

Comprehensive multi-gas study by means of fiber-enhanced Raman spectroscopy for the investigation of nitrogen cycle processes.

The extensive use of synthetic fertilizers has led to a considerable increase in reactive nitrogen input into agricultural and natural systems, resulting in negative effects in multiple ecosystems, the so-called nitrogen cascade. Since the global population relies on fertilization for food production, synthetic fertilizer use needs to be optimized by balancing crop yield and reactive nitrogen losses. Fiber-enhanced Raman spectroscopy (FERS) is introduced as a unique method for the simultaneous quantification of multiple gases to the study processes related to the nitrogen cycle. By monitoring changes in the headspace gas concentrations, processes such as denitrification, nitrification, respiration, and nitrogen fixation, as well as fertilizer addition were studied. The differences in concentration between the ambient and prepared process samples were evident in the Raman spectra, allowing for differentiation of process-specific spectra. Gas mixture concentrations were quantified within a range of low ppm to 100% for the gases N2, O2, CO2, N2O, and NH3. Compositional changes were attributed to processes of the nitrogen cycle. With help of multivariate curve resolution, it was possible to quantify N2O and CO2 simultaneously. The impact of fertilizers on N-cycle processes in soil was simulated and analyzed for identifying active processes. Thus, FERS was proven to be a suitable technique to optimize fertilizer composition and to quantify N2O and NH3 emissions, all with a single device and without further sample preparation.

Optical photothermal infrared spectroscopy and discrete wavenumber imaging for high content screening of single cells.

Major drawbacks of direct mid-infrared spectroscopic imaging of single cells in an aqueous buffer are strong water absorption, low resolution typically above 10 µm, and Mie scattering effects. This study demonstrates how an indirect detection principle can overcome these drawbacks using the optical photothermal infrared (O-PTIR) technique for high-resolution discrete wavenumber imaging and fingerprint spectroscopy of cultivated cells as a model system in a simple liquid sample chamber. The O-PTIR spectra of six leukemia- and cancer-derived cell lines showed main IR bands near 1648, 1547, 1447, 1400, 1220, and 1088 cm-1. Five spectra of approximately 260 single cells per cell type were averaged, the O-PTIR data set was divided into leukemia-derived cells (THP-1, HL 60, Jurkat, and Raji) and cancer cells (HeLa and HepaRG), and partial least squares linear discriminant analysis (PLS-LDA) was applied in the spectral range 800-1800 cm-1 to train three classification models. A leukemia versus cancer cell model showed an accuracy of 90.0%, the HeLa versus HepaRG cell model had an accuracy of 95.4%, and the model for the distinction of leukemia cells had an accuracy of 75.4%. IR bands in linear discriminants (LDs) of the models were correlated with second derivative spectra that resolved more than 25 subbands. The IR and second derivative spectra of proteins, DNA, RNA and lipids were collected as references to confirm band assignments. O-PTIR images of single cells at a 200 nm step size were acquired at 1086, 1548, and 1746 cm-1 to visualize the nucleic acid, protein, and lipid distribution, respectively. Variations in subcellular features and in the lipid-to-protein and nucleic acid-to-protein ratios were identified that were consistent with biomolecular information in LDs. In conclusion, O-PTIR can provide high-quality spectra and images with submicron resolution of single cells in aqueous buffers that offer prospects in high-content screening applications.

Design and test of a rigid endomicroscopic system for multimodal imaging and femtosecond laser ablation.

Significance: Conventional diagnosis of laryngeal cancer is normally made by a combination of endoscopic examination, a subsequent biopsy, and histopathology, but this requires several days and unnecessary biopsies can increase pathologist workload. Nonlinear imaging implemented through endoscopy can shorten this diagnosis time, and localize the margin of the cancerous area with high resolution. Aim: Develop a rigid endomicroscope for the head and neck region, aiming for in-vivo multimodal imaging with a large field of view (FOV) and tissue ablation. Approach: Three nonlinear imaging modalities, which are coherent anti-Stokes Raman scattering, two-photon excitation fluorescence, and second harmonic generation, as well as the single photon fluorescence of indocyanine green, are applied for multimodal endomicroscopic imaging. High-energy femtosecond laser pulses are transmitted for tissue ablation. Results: This endomicroscopic system consists of two major parts, one is the rigid endomicroscopic tube 250 mm in length and 6 mm in diameter, and the other is the scan-head (10×12×6 cm3 in size) for quasi-static scanning imaging. The final multimodal image accomplishes a maximum FOV up to 650 µm, and a resolution of 1 µm is achieved over 560 µm FOV. The optics can easily guide sub-picosecond pulses for ablation. Conclusions: The system exhibits large potential for helping real-time tissue diagnosis in surgery, by providing histological tissue information with a large FOV and high resolution, label-free. By guiding high-energy fs laser pulses, the system is even able to remove suspicious tissue areas, as has been shown for thin tissue sections in this study.

Raman Spectroscopic Imaging of Human Bladder Resectates towards Intraoperative Cancer Assessment.

Raman spectroscopy offers label-free assessment of bladder tissue for in vivo and ex vivo intraoperative applications. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates. Raman microspectroscopic images were collected from whole tissue samples in a closed chamber at 785 nm laser excitation using a 20× objective lens and 250 µm step size. Without further preprocessing, Raman images were decomposed by the hyperspectral unmixing algorithm vertex component analysis into endmember spectra and their abundancies. Hierarchical cluster analysis distinguished endmember Raman spectra that were assigned to normal bladder, bladder cancer, necrosis, epithelium and lipid inclusions. Interestingly, Raman spectra of microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. In conclusion, our Raman workflow and data processing protocol with minimal user interference offers advantages for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices.

SERS-based detection of 5-S-cysteinyl-dopamine as a novel biomarker of Parkinson's disease in artificial biofluids.

The early detection of Parkinson's disease (PD) can significantly improve treatment and quality of life in patients. 5-S-Cysteinyl-dopamine (CDA) is a key metabolite of high relevance for the early detection of PD. Therefore, its sensitive detection with fast and robust methods can improve its use as a biomarker. In this work we show the potentialities of label-free SERS spectroscopy in detecting CDA in aqueous solutions and artificial biofluids, with a simple, fast and sensitive approach. We present a detailed experimental SERS band assignment of CDA employing silver nanoparticle (AgNP) substrates in aqueous media, which was supported by theoretical calculations and simulated Raman and SERS spectra. The tentative orientation of CDA over the AgNP was also studied, indicating that catechol and carboxylic acid play a key role in the metallic surface adsorption. Moreover, we showed that SERS can allow us to identify CDA in aqueous media at low concentration, leading to the identification of some of its characteristic bands in pure water and in synthetic cerebrospinal fluid (SCSF) below 1 × 10-8 M, while its band identification in simulated urine (SUR) can be reached at 1 × 10-7 M. In conclusion, we show that CDA can be suitably detected by means of label-free SERS spectroscopy, which can significantly improve its sensitive detection for further analytical studies as a novel biomarker and further clinical diagnosis in PD patients.

Tuning the corona-core ratio of polyplex micelles for selective oligonucleotide delivery to hepatocytes or hepatic immune cells.

Targeted delivery of oligonucleotides or small molecular drugs to hepatocytes, the liver's parenchymal cells, is challenging without targeting moiety due to the highly efficient mononuclear phagocyte system (MPS) of the liver. The MPS comprises Kupffer cells and specialized sinusoidal endothelial cells, efficiently clearing nanocarriers regardless of their size and surface properties. Physiologically, this non-parenchymal shield protects hepatocytes; however, these local barriers must be overcome for drug delivery. Nanocarrier structural properties strongly influence tissue penetration, in vivo pharmacokinetics, and biodistribution profile. Here we demonstrate the in vivo biodistribution of polyplex micelles formed by polyion complexation of short interfering (si)RNA with modified poly(ethylene glycol)-block-poly(allyl glycidyl ether) (PEG-b-PAGE) diblock copolymer that carries amino moieties in the side chain. The ratio between PEG corona and siRNA complexed PAGE core of polyplex micelles was chemically varied by altering the degree of polymerization of PAGE. Applying Raman-spectroscopy and dynamic in silico modeling on the polyplex micelles, we determined the corona-core ratio (CCR) and visualized the possible micellar structure with varying CCR. The results for this model system reveal that polyplex micelles with higher CCR, i.e., better PEG coverage, exclusively accumulate and thus allow passive cell-type-specific targeting towards hepatocytes, overcoming the macrophage-rich reticuloendothelial barrier of the liver.

Optical photothermal infrared spectroscopy with simultaneously acquired Raman spectroscopy for two-dimensional microplastic identification.

In recent years, vibrational spectroscopic techniques based on Fourier transform infrared (FTIR) or Raman microspectroscopy have been suggested to fulfill the unmet need for microplastic particle detection and identification. Inter-system comparison of spectra from reference polymers enables assessing the reproducibility between instruments and advantages of emerging quantum cascade laser-based optical photothermal infrared (O-PTIR) spectroscopy. In our work, IR and Raman spectra of nine plastics, namely polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, polycarbonate, polystyrene, silicone, polylactide acid and polymethylmethacrylate were simultaneously acquired using an O-PTIR microscope in non-contact, reflection mode. Comprehensive band assignments were presented. We determined the agreement of O-PTIR with standalone attenuated total reflection FTIR and Raman spectrometers based on the hit quality index (HQI) and introduced a two-dimensional identification (2D-HQI) approach using both Raman- and IR-HQIs. Finally, microplastic particles were prepared as test samples from known materials by wet grinding, O-PTIR data were collected and subjected to the 2D-HQI identification approach. We concluded that this framework offers improved material identification of microplastic particles in environmental, nutritious and biological matrices.

Efficient Gene Delivery of Tailored Amphiphilic Polypeptides by Polyplex Surfing.

Within this study, an amphiphilic and potentially biodegradable polypeptide library based on poly[(4-aminobutyl)-l-glutamine-stat-hexyl-l-glutamine] [P(AB-l-Gln-stat-Hex-l-Gln)] was investigated for gene delivery. The influence of varying proportions of aliphatic and cationic side chains affecting the physicochemical properties of the polypeptides on transfection efficiency was investigated. A composition of 40 mol% Hex-l-Gln and 60 mol % AB-l-Gln (P3) was identified as best performer over polypeptides with higher proportions of protonatable monomers. Detailed studies of the transfection mechanism revealed the strongest interaction of P3 with cell membranes, promoting efficient endocytic cell uptake and high endosomal release. Spectrally, time-, and z-resolved fluorescence microscopy further revealed the crucial role of filopodia surfing in polyplex-cell interaction and particle internalization in lamellipodia regions, followed by rapid particle transport into cells. This study demonstrates the great potential of polypeptides for gene delivery. The amphiphilic character improves performance over cationic homopolypeptides, and the potential biodegradability is advantageous toward other synthetic polymeric delivery systems.

Real-time molecular imaging of near-surface tissue using Raman spectroscopy.

The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.

In Vitro Fiber-Probe-Based Identification of Pathogens in Biofilms by Raman Spectroscopy.

Biofilms are the preferred habitat of microorganisms on living and artificial surfaces. Biofilm-related infections, such as infections of medical implants, are difficult to treat, and due to a reduced cultivability of the included bacteria, difficult to diagnose. Therefore, it is highly important to rapidly identify and investigate biofilms on implant surfaces, e.g., during surgery. In this study, we present fiber-probe-based Raman spectroscopy with an excitation wavelength of 785 nm, which was applied to investigate six different pathogen species involved in biofilm-related infections. Biofilms were cultivated in a drip flow reactor, which can model a biofilm growth environment. The signals collected from a fiber probe allowed us to collect Raman spectra not only from the embedded bacterial and yeast cells but also the surrounding extracellular polymeric substance matrix. This information was used in a classification model. The model consists of a principal component analysis in combination with linear discriminant analysis and was examined by applying a leave-one-batch-out cross-validation. This model achieved a classification accuracy of 93.8%. In addition, the identification accuracy increased up to 97.5% when clinical strains were used for identification. A fiber-probe-based Raman spectroscopy method combined with a chemometric analysis might therefore serve as a fast, accurate, and portable strategy for the species identification of biofilm-related infections, e.g., during surgical procedures.

Activity and electron donor preference of two denitrifying bacterial strains identified by Raman gas spectroscopy.

Human activities have greatly increased the input of reactive nitrogen species into the environment and disturbed the balance of the global N cycle. This imbalance may be offset by bacterial denitrification, an important process in maintaining the ecological balance of nitrogen. However, our understanding of the activity of mixotrophic denitrifying bacteria is not complete, as most research has focused on heterotrophic denitrification. The aim of this study was to investigate substrate preferences for two mixotrophic denitrifying bacterial strains, Acidovorax delafieldii and Hydrogenophaga taeniospiralis, under heterotrophic, autotrophic or mixotrophic conditions. This complex analysis was achieved by simultaneous identification and quantification of H2, O2, CO2, 14N2, 15N2 and 15N2O in course of the denitrification process with help of cavity-enhanced Raman spectroscopic (CERS) multi-gas analysis. To disentangle electron donor preferences for both bacterial strains, microcosm-based incubation experiments under varying substrate conditions were conducted. We found that Acidovorax delafieldii preferentially performed heterotrophic denitrification in the mixotrophic sub-experiments, while Hydrogenophaga taeniospiralis preferred autotrophic denitrification in the mixotrophic incubation. These observations were supported by stoichiometric calculations. The results demonstrate the prowess of advanced Raman multi-gas analysis to study substrate use and electron donor preferences in denitrification, based on the comprehensive quantification of complex microbial gas exchange processes.

Noise Sources and Requirements for Confocal Raman Spectrometers in Biosensor Applications.

Raman spectroscopy probes the biochemical composition of samples in a non-destructive, non-invasive and label-free fashion yielding specific information on a molecular level. Nevertheless, the Raman effect is very weak. The detection of all inelastically scattered photons with highest efficiency is therefore crucial as well as the identification of all noise sources present in the system. Here we provide a study for performance comparison and assessment of different spectrometers for confocal Raman spectroscopy in biosensor applications. A low-cost, home-built Raman spectrometer with a complementary metal-oxide-semiconductor (CMOS) camera, a middle price-class mini charge-coupled device (CCD) Raman spectrometer and a laboratory grade confocal Raman system with a deeply cooled CCD detector are compared. It is often overlooked that the sample itself is the most important "optical" component in a Raman spectrometer and its properties contribute most significantly to the signal-to-noise ratio. For this purpose, different representative samples: a crystalline silicon wafer, a polypropylene sample and E. coli bacteria were measured under similar conditions using the three confocal Raman spectrometers. We show that biosensor applications do not in every case profit from the most expensive equipment. Finally, a small Raman database of three different bacteria species is set up with the middle price-class mini CCD Raman spectrometer in order to demonstrate the potential of a compact setup for pathogen discrimination.

Precise Encoding of Triple-Bond Raman Scattering of Single Polymer Nanoparticles for Multiplexed Imaging Application.

Stimulated Raman scattering (SRS) microscopy in combination with innovative tagging strategies offers great potential as a universal high-throughput biomedical imaging tool. Here, we report rationally tailored small molecular monomers containing triple-bond units with large Raman scattering cross-sections, which can be polymerized at the nanoscale for enhancement of SRS contrast with smaller but brighter optical nanotags with artificial fingerprint output. From this, a class of triple-bond rich polymer nanoparticles (NPs) was engineered by regulating the relative dosages of three chemically different triple-bond monomers in co-polymerization. The bonding strategy allowed for 15 spectrally distinguishable triple-bond combinations. These accurately structured nano molecular aggregates, rather than long-chain macromolecules, could establish a universal method for generating small-sized biological SRS imaging tags with high sensitivity for high-throughput multi-color biomedical imaging.

Surface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients.

Extracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.

Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors.

Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates.

Simple and rapid peptide nanoprobe biosensor for the detection of Legionellaceae.

This study demonstrates the development of a sensitive, specific, and quantitative peptide-based nanoprobe prototype assay for the detection of Legionellaceae in a simple way and in a short time. In this work, proteases present in the culture supernatants of Legionella spp. were used as a biomarker. Fluorogenic peptide substrates, specific to Legionella strains culture supernatant proteases, were identified. Peptidases produced a significant increase in the fluorescence intensity following the cleavage of the dipeptide fluorogenic substrates. The specific substrates were identified and coupled with carboxyl-terminated nano-magnetic particles (NMPs). On the other hand, the C-terminal was conjugated with the cysteine residue to covalently integrate with a gold sensing platform via the Au-S linkage. Four different sensors were fabricated from the four specific substrates, which were treated with the protesase of six different species of Legionella. In the presence of specific protease, the peptide sequence is digested and the magnetic nanobeads moved out of the gold surface, resulting in the apparence of gold color. One of the nanoprobes sensitivity detects as low as 60 CFU mL-1 of Legionella anisa, Legionella micdadei, and Fluoribacter dumoffii. The cross-reactivity of the sensors was tested using other closely associated bacterial species and no significant cross-reactivity of the sensors was found. It is envisaged that this assay could be useful for screening purposes or might be supportive for the fast and easy detection of Legionella protease activity for water monitoring purposes.

Biophotonic technologies for assessment of breast tumor surgical margins-A review.

Breast conserving surgery (BCS) offering similar surgical outcomes as mastectomy while retaining breast cosmesis is becoming increasingly popular for the management of early stage breast cancers. However, its association with reoperation rates of 20% to 40% following incomplete tumor removal warrants the need for a fast and accurate intraoperative surgical margin assessment tool that offers cellular, structural and molecular information of the whole specimen surface to a clinically relevant depth. Biophotonic technologies are evolving to qualify as such an intraoperative tool for clinical assessment of breast cancer surgical margins at the microscopic and macroscopic scale. Herein, we review the current research in the application of biophotonic technologies such as photoacoustic imaging, Raman spectroscopy, multimodal multiphoton imaging, diffuse optical imaging and fluorescence imaging using medically approved dyes for breast cancer detection and/or tumor subtype differentiation toward intraoperative assessment of surgical margins in BCS specimens, and possible challenges in their route to clinical translation.