What determines accuracy of chemical identification when using microspectroscopy for the analysis of microplastics?

Fourier transform infrared (FTIR) and Raman microspectroscopy are methods applied in microplastics research to determine the chemical identity of microplastics. These techniques enable quantification of microplastic particles across various matrices. Previous work has highlighted the benefits and limitations of each method and found these to be complimentary. Within this work, metadata collected within an interlaboratory method validation study was used to determine which variables most influenced successful chemical identification of un-weathered microplastics in simulated drinking water samples using FTIR and Raman microspectroscopy. No variables tested had a strong correlation with the accuracy of chemical identification (r = ≤0.63). The variables most correlated with accuracy differed between the two methods, and include both physical characteristics of particles (color, morphology, size, polymer type), and instrumental parameters (spectral collection mode, spectral range). Based on these results, we provide technical recommendations to improve capabilities of both methods for measuring microplastics in drinking water and highlight priorities for further research. For FTIR microspectroscopy, recommendations include considering the type of particle in question to inform sample presentation and spectral collection mode for sample analysis. Instrumental parameters should be adjusted for certain particle types when using Raman microspectroscopy. For both instruments, the study highlighted the need for harmonization of spectral reference libraries among research groups, including the use of libraries containing reference materials of both weathered plastic and natural materials that are commonly found in environmental samples.

Fused Raman spectroscopic analysis of blood and saliva delivers high accuracy for head and neck cancer diagnostics.

As a rapid, label-free, non-destructive analytical measurement requiring little to no sample preparation, Raman spectroscopy shows great promise for liquid biopsy cancer detection and diagnosis. We carried out Raman analysis and mass spectrometry of plasma and saliva from more than 50 subjects in a cohort of head and neck cancer patients and benign controls (e.g., patients with benign oral masses). Unsupervised data models were built to assess diagnostic performance. Raman spectra collected from either biofluid provided moderate performance to discriminate cancer samples. However, by fusing together the Raman spectra of plasma and saliva for each patient, subsequent analytical models delivered an impressive sensitivity, specificity, and accuracy of 96.3%, 85.7%, and 91.7%, respectively. We further confirmed that the metabolites driving the differences in Raman spectra for our models are among the same ones that drive mass spectrometry models, unifying the two techniques and validating the underlying ability of Raman to assess metabolite composition. This study bolsters the relevance of Raman to provide additive value by probing the unique chemical compositions across biofluid sources. Ultimately, we show that a simple data augmentation routine of fusing plasma and saliva spectra provided significantly higher clinical value than either biofluid alone, pushing forward the potential of clinical translation of Raman spectroscopy for liquid biopsy cancer diagnostics.

Laser Tweezers Raman Microspectroscopy of Single Cells and Biological Particles.

Laser tweezers Raman spectroscopy (LTRS) is a variation of micro-Raman spectroscopy that is used to analyze single cells and biological particles suspended in an aqueous environment. The Raman spectrum of the cell/particle reflects its intrinsic biochemical composition and molecular structures. The technique utilizes a laser trap generated by a tightly focused Gaussian laser beam to physically manipulate individual cells and immobilize them in the laser focal volume. The same laser that is used for optical trapping also simultaneously excites Raman signals from the trapped cell, which are detected using a spectrometer and a confocal detection setup. LTRS offers unique capabilities not commonly found in other optical cytometry methods, such as label-free chemical analysis, multi-parametric chemical detection with a single excitation laser, and a non-photobleaching signal that can be used to quantitate and monitor dynamic chemical changes. This chapter provides guidelines on the design of a single beam LTRS microscope and methods for building and aligning the system. Operating procedures for trapping particles and acquiring spectra and a summary of data analysis techniques are provided.

Nanoparticles for live cell microscopy: A surface-enhanced Raman scattering perspective.

Surface enhanced Raman scattering (SERS) nanoparticles are an attractive alternative to fluorescent probes for biological labeling because of their photostability and multiplexing capabilities. However, nanoparticle size, shape, and surface properties are known to affect nanoparticle-cell interactions. Other issues such as the formation of a protein corona and antibody multivalency interfere with the labeling properties of nanoparticle-antibody conjugates. Hence, it is important to consider these aspects in order to validate such conjugates for live cell imaging applications. Using SERS nanoparticles that target HER2 and CD44 in breast cancer cells, we demonstrate labeling of fixed cells with high specificity that correlates well with fluorescent labels. However, when labeling live cells to monitor surface biomarker expression and dynamics, the nanoparticles are rapidly uptaken by the cells and become compartmentalized into different cellular regions. This behavior is in stark contrast to that of fluorescent antibody conjugates. This study highlights the impact of nanoparticle internalization and trafficking on the ability to use SERS nanoparticle-antibody conjugates to monitor cell dynamics.

Microbial Transformation of Multiwalled Carbon Nanotubes by Mycobacterium vanbaalenii PYR-1.

Carbonaceous nanomaterials are widely used in industry and consumer products, but concerns have been raised regarding their release into the environment and subsequent impacts on ecosystems and human health. Although many efforts have been devoted to understanding the environmental fate of carbonaceous nanomaterials, information about their microbial transformation is still rare. In this study, we found that within 1 month a polycyclic aromatic hydrocarbon-degrading bacterium, Mycobacterium vanbaalenii PYR-1, was able to degrade both pristine and carboxyl-functionalized multiwalled carbon nanotubes (p-MWCNT and c-MWCNT), as demonstrated by consistent results from high resolution transmission electron microscopy, Raman spectroscopy, and confocal Raman microspectroscopy. Statistical analysis of Raman spectra identified a significant increase in the density of disordered or amorphous carbon in p-MWCNT and c-MWCNT after biodegradation. Microbial respiration further suggested potential mineralization of MWCNTs within about 1 month. All of our analyses consistently showed higher degradation or mineralization of c-MWCNT compared to p-MWCNT. These results highlight the potential of using bacteria in engineered systems to remove residual carbonaceous nanomaterials and reduce risk of human exposure and environmental impact. Meanwhile, our finding suggests possible transformation of carbonaceous nanomaterials by polycyclic aromatic hydrocarbon-degrading bacteria in the natural environment, which should be accounted for in predicting the environmental fate of these emerging contaminants and in nanotechnology risk regulation.

Improving the imaging speed of 1064 nm dispersive Raman microscopy with multifocal patterned detection.

We demonstrate the compatibility of a Hadamard-coded multifocal array approach with a 1064 nm dispersive Raman microscope for improving the imaging speed. The system uses a galvomirror to generate a one-dimensional (1-D) multifocal array at the sample, and the Raman signals from the multiple foci are simultaneously detected by an InGaAs linear detector array. The superimposed spectra are deconvolved to retrieve the individual spectra at each focus. Using a silicon wafer as a test sample, we demonstrate that the method is ideal for the high noise detection conditions encountered when using 1064 nm excitation, InGaAs detectors, and high readout rates. An improvement in the imaging speed by as much as 14 times is achieved with this multifocal method.

Fast Confocal Raman Imaging Using a 2-D Multifocal Array for Parallel Hyperspectral Detection.

We present the development of a novel confocal hyperspectral Raman microscope capable of imaging at speeds up to 100 times faster than conventional point-scan Raman microscopy under high noise conditions. The microscope utilizes scanning galvomirrors to generate a two-dimensional (2-D) multifocal array at the sample plane, generating Raman signals simultaneously at each focus of the array pattern. The signals are combined into a single beam and delivered through a confocal pinhole before being focused through the slit of a spectrometer. To separate the signals from each row of the array, a synchronized scan mirror placed in front of the spectrometer slit positions the Raman signals onto different pixel rows of the detector. We devised an approach to deconvolve the superimposed signals and retrieve the individual spectra at each focal position within a given row. The galvomirrors were programmed to scan different focal arrays following Hadamard encoding patterns. A key feature of the Hadamard detection is the reconstruction of individual spectra with improved signal-to-noise ratio. Using polystyrene beads as test samples, we demonstrated not only that our system images faster than a conventional point-scan method but that it is especially advantageous under noisy conditions, such as when the CCD detector operates at fast read-out rates and high temperatures. This is the first demonstration of multifocal confocal Raman imaging in which parallel spectral detection is implemented along both axes of the CCD detector chip. We envision this novel 2-D multifocal spectral detection technique can be used to develop faster imaging spontaneous Raman microscopes with lower cost detectors.