Rapid visualization of macromolecular orientation by discrete frequency mid-infrared spectroscopic imaging

Ignited competition: Impact of bioactive extracellular compounds on organelle functions and photosynthetic systems in harmful algal blooms

Prevalent interactions among marine phytoplankton triggered by long-range climatic stressors are well-known environmental disturbers of community structure. Dynamic response of phytoplankton physiology is likely to come from interspecies interactions rather than direct climatic effect on single species. However, studies on enigmatic interactions among interspecies, which are induced by bioactive extracellular compounds (BECs), especially between related harmful algae sharing similar shellfish toxins, are scarce. Here, we investigated how BECs provoke the interactions between two notorious algae, Alexandrium minutum and Gymnodinium catenatum, which have similar paralytic shellfish toxin (PST) profiles. Using techniques including electron microscopy and transcriptome analysis, marked disruptions in G. catenatum intracellular microenvironment were observed under BECs pressure, encompassing thylakoid membrane deformations, pyrenoid matrix shrinkage and starch sheaths disappearance. In addition, the upregulation of gene clusters responsible for photosystem-I Lhca1/4 and Rubisco were determined, leading to weaken photon captures and CO2 assimilation. The redistribution of lipids and proteins occurred at the subcellular level based on in situ focal plane array FTIR imaging approved the damages. Our findings illuminated an intense but underestimated interspecies interaction triggered by BECs, which is responsible for dysregulating photosynthesis and organelle function in inferior algae and may potentially account for fitness alteration in phytoplankton community.

Scattering correction for samples with cylindrical domains measured with polarized infrared spectroscopy

Scattering artifacts are one of the most common effects distorting transmission spectra in Fourier-Transform Infrared spectroscopy. Their increased impact, strongly diminishing the quantitative and qualitative power of IR spectroscopy, is especially observed for structures with a size comparable to the radiation wavelength. To tackle this problem, a wide range of preprocessing techniques based on the Extended Multiplicative Scattering Correction method was developed, using physical properties to remove scattering presence in the spectra. However, until recently those algorithms were mostly focused on spherically shaped samples, for example, cells. Here, an algorithm for samples with cylindrical domains is described, with additional implementation of a linearly polarized light case, which is crucial for the growing field of polarized IR imaging and spectroscopy. An open-source code with GPU based implementation is provided, with a calculation time of several seconds per spectrum. Optimizations done to improve the throughput of this algorithm allow the application of this method into the standard preprocessing pipeline of small datasets.

Digital Histopathology by Infrared Spectroscopic Imaging

Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. First, this review summarizes IR imaging instrumentation especially suited to histopathology, analyses of its performance, and major trends. Second, an overview of data processing methods and application of machine learning is given, with an emphasis on the emerging use of deep learning. Third, a discussion on workflows in pathology is provided, with four categories proposed based on the complexity of methods and the analytical performance needed. Last, a set of guidelines, termed experimental and analytical specifications for spectroscopic imaging in histopathology, are proposed to help standardize the diversity of approaches in this emerging area.

Super-Resolved 3D Mapping of Molecular Orientation Using Vibrational Techniques

When a sample has an anisotropic structure, it is possible to obtain additional information controlling the polarization of incident light. With their straightforward instrumentation approaches, infrared (IR) and Raman spectroscopies are widely popular in this area. Single-band-based determination of molecular in-plane orientation, typically used in materials science, is here extended by the concurrent use of two vibration bands, revealing the orientational ordering in three dimension. The concurrent analysis was applied to IR spectromicroscopic data to obtain orientation angles of a model polycaprolactone spherulite sample. The applicability of this method spans from high-resolution, diffraction-limited Fourier transform infrared (FT-IR) and Raman imaging to super-resolved optical photothermal infrared (O-PTIR) imaging. Due to the nontomographic experimental approach, no image distortion is visible and nanometer scale orientation domains can be observed. Three-dimensional (3D) bond orientation maps enable in-depth characterization and consequently precise control of the sample’s physicochemical properties and functions.

Resolution Limit in Infrared Chemical Imaging

Chemical imaging combines the spatial specificity of optical microscopy with the spectral selectivity of vibrational spectroscopy. Mid-infrared (IR) absorption imaging instruments are now able to capture high-quality spectra with microscopic spatial detail, but the limits of their ability to resolve spatial and spectral objects remain less understood. In particular, the sensitivity of measurements to chemical and spatial changes and rules for optical design have been presented, but the influence of spectral information on spatial sensitivity is as yet relatively unexplored. We report an information theory-based approach to quantify the spatial localization capability of spectral data in chemical imaging. We explicitly consider the joint effects of the signal-to-noise ratio and spectral separation that have significance in experimental settings to derive resolution limits in IR spectroscopic imaging.

Targeted Analysis of Microplastics Using Discrete Frequency Infrared Imaging

An analytical strategy to improve sample throughput with discrete frequency infrared image-based targeted analysis of microplastics using a laser direct infrared chemical imaging system was successfully developed and implemented. Leveraging a quantum cascade laser as a light source, the system could lock the frequency at predetermined wavelengths and use a discrete frequency infrared imaging technique to identify particles with absorption at desired wavelengths. In this way, targeted analysis can be achieved by selectively characterizing these particles. In the concept demonstration study, the targeted analysis was able to identify 87.7% of spiked polyethylene particles by scanning only 20% of the particles in the sample. The technique substantially improves sample throughput by at least a factor of 4 under conditions used. In the tests performed with real environmental samples, the targeted analysis workflow correctly identified eight types of common microplastics by only investigating around 60% of the particles and less than 30% of the sample area. Results obtained demonstrated that this scanning strategy is a game changer to enhance sample throughput in microplastic analysis. The technique has the potential of being applied to other infrared-based analytical platforms.

Design Considerations for Discrete Frequency Infrared Microscopy Systems

Discrete frequency infrared chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument's performance mathematically. Finally, we provide a validation approach by enumerating performance metrics that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.

Application of 2D IR Bioimaging: Hyperspectral Images of Formalin-Fixed Pancreatic Tissues and Observation of Slow Protein Degradation

We used two-dimensional IR bioimaging to study the structural heterogeneity of formalin-fixed mouse pancreas. Images were generated from the hyperspectral data sets by plotting quantities associated with the amide I vibrational mode, which is created by the backbone carbonyl stretch. Images that measure the fundamental vibrational frequencies, cross peaks, and anharmonic shifts are presented. Histograms are generated for each quantity, providing averaged values and distributions around the mean that serve as metrics for protein structures. Images were generated from tissue that had been stored in a formalin fixation for 3, 8, and 48 weeks. Over this period, all three metrics show that that the β-sheet content of the samples increased, consistent with protein aggregation. Our results indicate that formalin fixation does not entirely arrest the degradation of a protein structure in pancreas tissue.

The Impact of Preprocessing Methods for a Successful Prostate Cell Lines Discrimination Using Partial Least Squares Regression and Discriminant Analysis Based on Fourier Transform Infrared Imaging

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer research lies in its capability of monitoring the biochemical status of cells, which undergo malignant transformation and further examination of spectral features that differentiate normal and cancerous ones using proper mathematical approaches. Such examination can be performed with the use of chemometric tools, such as partial least squares discriminant analysis (PLS-DA) classification and partial least squares regression (PLSR), and proper application of preprocessing methods and their correct sequence is crucial for success. Here, we performed a comparison of several state-of-the-art methods commonly used in infrared biospectroscopy (denoising, baseline correction, and normalization) with the addition of methods not previously used in infrared biospectroscopy classification problems: Mie extinction extended multiplicative signal correction, Eiler’s smoothing, and probabilistic quotient normalization. We compared all of these approaches and their effect on the data structure, classification, and regression capability on experimental FT-IR spectra collected from five different prostate normal and cancerous cell lines. Additionally, we tested the influence of added spectral noise. Overall, we concluded that in the case of the data analyzed here, the biggest impact on data structure and performance of PLS-DA and PLSR was caused by the baseline correction; therefore, much attention should be given, especially to this step of data preprocessing.

Macromolecular Orientation in Biological Tissues Using a Four-Polarization Method in FT-IR Imaging

Fourier transform infrared spectroscopy has emerged as a powerful tool for tissue specimen investigation. Its nondestructive and label-free character enables direct determination of biochemical composition of samples. Furthermore, the introduction of polarization enriches this technique by the possibility of molecular orientation study apart from purely quantitative analysis. Most of the molecular orientation studies focused on polymer samples with a well-defined molecular axis. Here, a four-polarization approach for Herman’s in-plane orientation function and azimuthal angle determination was applied to a human tissue sample investigation for the first time. Attention was focused on fibrous tissues rich in collagen because of their cylindrical shape and established amide bond vibrations. Despite the fact that the tissue specimen contains a variety of molecules, the presented results of molecular ordering and orientation agree with the theoretical prediction based on sample composition and vibration directions.

Translation of an esophagus histopathological FT-IR imaging model to a fast quantum cascade laser modality

The technical progress in fast quantum cascade laser (QCL) microscopy offers a platform where chemical imaging becomes feasible for clinical diagnostics. QCL systems allow the integration of previously developed FT-IR-based pathology recognition models in a faster workflow. The translation of such models requires a systematic approach, focusing only on the spectral frequencies that carry crucial information for discrimination of pathologic features. In this study, we optimize an FT-IR-based histopathological method for esophageal cancer detection to work with a QCL system. We explore whether the classifier's performance is affected by paraffin presence from tissue blocks compared to removing it chemically. Working with paraffin-embedded samples reduces preprocessing time in the lab and allows samples to be archived after analysis. Moreover, we test, whether the creation of a QCL model requires a preestablished FTIR model or can be optimized using solely QCL measurements.

Comparison between high definition FT-IR, Raman and AFM-IR for subcellular chemical imaging of cholesteryl esters in prostate cancer cells

The family of vibrational spectroscopic imaging techniques grows every few years and there is a need to compare and contrast new modalities with the better understood ones, especially in the case of demanding biological samples. Three vibrational spectroscopy techniques (high definition Fourier-transform infrared [FT-IR], Raman and atomic force microscopy infrared [AFM-IR]) were applied for subcellular chemical imaging of cholesteryl esters in PC-3 prostate cancer cells. The techniques were compared and contrasted in terms of image quality, spectral pattern and chemical information. All tested techniques were found to be useful in chemical imaging of cholesterol derivatives in cancer cells. The results obtained from FT-IR and Raman imaging showed to be comparable, whereas those achieved from AFM-IR study exhibited higher spectral heterogeneity. It confirms AFM-IR method as a powerful tool in local chemical imaging of cells at the nanoscale level. Furthermore, due to polarization effect, p-polarized AFM-IR spectra showed strong enhancement of lipid bands when compared to FT-IR.

Analysis of molecular orientation in polymeric spherulite using polarized micro attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic imaging

Micro ATR-FTIR spectroscopic imaging enables the visualization of two-dimensional chemical distribution at a higher spatial resolution than macro-transmission FTIR imaging approach. In this study, micro ATR-FTIR imaging was applied for analysis of a specific morphology in a spherulite of poly(3-hydroxybutyrate) (PHB). The PHB spherulites crystallized at an isothermal condition, showed the fine band structure due to the twisting lamellar crystals during the spherulite growth under the polarized optical microscope (POM). In addition, the band structure observed in the PHB spherulite was the double band pattern in which the higher and lower birefringence banded areas alternatively appear due to the three-dimensional orientation of crystallographic axes and the biaxial refractive index ellipsoid of PHB crystalline structure. Micro ATR-FTIR spectroscopic imaging was employed for detecting the double band structure in the PHB spherulite. However, the obtained spectral images did not indicate any band structures. To detect the difference of molecular orientation among the double band structures, the micro ATR-FTIR imaging was performed with a linear polarizer at four different angles. The mean values of absorbance in each measured area changed depending on the polarizer angle. The in-plane molecular orientation to the tangential direction of spherulite, caused by the dependence of the average absorbance on the polarizer angles, was determined by the position of measured area in the spherulite and the linear dicroism of each of the spectral band used. To visualize the small difference of molecular orientation in the double band structure, micro ATR-FTIR images of the dichroic differences at three spectral bands were calculated from two different sets of polarizer angles. The micro ATR-FTIR images representing the dichroic differences displayed their corresponding distributions among three spectral bands. The complementary distributions of the dichroic difference were caused by the crystallographic orientation of b- and c-axes and were successfully visualized to reveal the pattern with the features less than 10 μm in size. The results achieved in this study were due to two advantages of the polarized micro ATR-FTIR imaging: the high spatial resolution of micro ATR-FTIR imaging technique, and the high sensitivity of polarization measurements. Thus, this work demonstrates the power of this spectroscopic approach for such analytical investigation.

Biomedical applications of mid-infrared quantum cascade lasers - a review

Mid-infrared spectroscopy has been applied to research in biology and medicine for more than 20 years and conceivable applications have been identified. More recently, these applications have been shown to benefit from the use of quantum cascade lasers due to their specific properties, namely high spectral power density, small beam parameter product, narrow emission spectrum and, if needed, tuning capabilities. This review provides an overview of the achievements and illustrates some applications which benefit from the key characteristics of quantum cascade laser-based mid-infrared spectroscopy using examples such as breath analysis, the investigation of serum, non-invasive glucose monitoring in bulk tissue and the combination of spectroscopy and microscopy of tissue thin sections for rapid histopathology.

Denoising influence on discrete frequency classification results for quantum cascade laser based infrared microscopy

Currently, there is great interest in bringing the application of IR spectroscopy into the clinic. This however will require a significant reduction in measurement time as Fourier Transform Infrared (FT-IR) imaging takes hours to days to scan a clinically relevant specimen. A potential remedy for this issue is the use of Quantum Cascade Laser Infrared (QCL IR) microscopy performed in Discrete Frequency (DF) mode for maximum speed gain. This gain could be furthermore improved by applying a proper denoising algorithm that takes into account the specific data structure. We have recently compared spectral and spatial denoising techniques in the context of Fourier Transform IR (FT-IR) imaging and showed that the optimal methods depend heavily on the exact data structure. In general multivariate denoising methods such as Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) are the most effective for a dataset containing multiple bands. Histologic classification of QCL IR images of pancreatic tissue using Random Forest was therefore performed to investigate which denoising schemes are the most optimal for such experimental data structure. This work is the first to show the effects of denoising on classification accuracy of QCL data and is likely to be transferable to other QCL microscopes and other modalities using DF imaging, e.g. AFM-IR or CARS/SRS imaging.

Comparison of spectral and spatial denoising techniques in the context of High Definition FT-IR imaging hyperspectral data

The recent emergence of High Definition (HD) FT-IR and Quantum Cascade Laser (QCL) Microscopes elevated the IR imaging field very close to clinical timescales. However, the speed of acquisition and data quality are still the critical factors in reaching the clinic. Denoising offers aide in both aspects if performed properly. However, there is a lack of a direct comparison of the efficiency of denoising techniques in IR imaging in general. To achieve such comparison within a rigorous framework and obtaining the critical information about signal loss, a simulated dataset strongly bound by experimental parameters was created. Using experimental structural and spectral information and experimental noise levels data as an input for the simulation, a direct comparison of spatial (Fourier transform, Mean Filter, Weighted Mean Filter, Gauss Filter, Median Filter, spatial Wavelets and Deep Neural Networks) and spectral (Savitzky-Golay, Fourier transform, Principal Component Analysis, Minimum Noise Fraction and spectral Wavelets) denoising schemes was enabled. All of these techniques were compared on the simulated dataset, taking into account SNR gain, signal distortion and sensitivity to tuning parameters as comparison metrics. Later, the best techniques were applied to experimental data for validation. The results presented here clearly show the benefit of using hyperspectral denoising schemes such as PCA and MNF which outperform other methods.

Concurrent polarization IR analysis to determine the 3D angles and the order parameter for molecular orientation imaging

A non-tomographic analysis method is proposed to determine the 3D angles and the order parameter of molecular orientation using polarization-dependent infrared (IR) spectroscopy. Conventional polarization-based imaging approaches provide only 2D-projected orientational information of single vibrational modes. The newly proposed method concurrently analyses polarization angle-dependent absorptance of two non-parallel transition dipole moments. The relative phase angle and the maximum-to-minimum ratios observed from the two polarization profiles are used to calculate the 3D angles of the mean molecular orientation and the order parameter of the orientational distribution. Usage of those relative observables as intermediate input parameters makes the analysis results robust against variations in concentration, thickness, absorption peak, and absorption cross-section, which can occur in typical imaging conditions. This analysis is based on a single-step, non-iterative calculation that does not require any analytical model function of an orientational distribution function. This concurrent polarization analysis method is demonstrated using two simulation data examples, followed by associated error propagation analysis and discussion on the effect of absorption strength. Application of this robust spectral analysis method to polarization IR microscopy will provide a full molecular orientation image without tilting that tomographies require.

Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

Mapping Solvation Environments in Porous Metal-Organic Frameworks with Infrared Chemical Imaging

We report here the first mesoscale characterization of solvent environments in the metal-organic framework (MOF) Cu₃(BTC)₂ using infrared imaging. Two characteristic populations of the MOF structures corresponding to the carboxylate binding to the Cu(II) (metal) ions were observed, which reflect a regular solvated MOF structure with axial solvents in the binuclear copper paddlewheel and an unsolvated defect mode that lacks axial solvent coordination. Infrared imaging also shows strong correlation between solvent localization and the spatial distribution of the solvated population within the MOF. This is a vital result as any remnant solvent molecules adsorbed inside of MOFs can render them less effective. We propose fast IR imaging as a potential characterization technique that can measure adsorbate and defect distributions in MOFs.