Hyperspectral imaging and microscopy identifies nanoparticles in biological tissue
SUNY Polytechnic researchers and collaborators demonstrated a new method to view nanoparticles in tissues.
IMAGE: Porcine skin tissue exposed to engineered nano material (ENM)-containing solution is mapped against the reference spectral library (RSL).Rows correspond to porcine skin tissue exposed to ceria and alumina ENMs, respectively. Each column shows the same field of view imaged with different techniques. The first column corresponds to a brightfield image of a hematoxylin and eosin stained sample (40X magnification). The area enclosed in a red square was magnified to 100X and viewed using EDFM (column 2) and HSI (column 3), where ENMs appear as high contrast elements (arrows). Column 4 shows the HSI image mapped against the RSL, where the positive matches are shown in blue for ceria and in magenta for alumina. From top to bottom, the rows correspond to: stratum corneum, dermis, and subcutaneous tissue, respectively.
Researchers at SUNY Polytechnic Institute (SUNY Poly), the George Washington School of Medicine and Health Sciences, and Stony Brook University have demonstrated a new method for the rapid visualization and identification of engineered nanoparticles in tissues. This research, published in Microscopy Research and Technique, presents a method for using enhanced darkfield microscopy (EDFM) and hyperspectral imaging (HSI) to easily and rapidly image nanoparticles in tissues from toxicology studies and map the distribution of nanoparticles throughout biological samples based on elemental composition.
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As nanoparticles are increasingly incorporated into industrial processes and consumer products, studying the potential effects of exposure is critical to ensure the health and safety of workers, consumers, and the environment. In particular, the semiconductor industry utilizes metal oxide nanoparticles in a fabrication process, which has been identified by the industry as a critical area for health and safety research due to the potential for worker exposure. In their recent publication, the researchers were able to detail how they located metal oxide nanoparticles in an ex vivo porcine skin tissue model of cutaneous exposure.
"The current gold standard for visualization of nanoparticles in tissue samples is electron microscopy, which is highly time- and resource-intensive," said Sara Brenner, assistant professor of Nanobioscience and Assistant VP for NanoHealth Initiatives at SUNY Poly and corresponding author of the study. "Availability of an alternative, rapid, and cost-effective method would relieve this analytical bottleneck, not only in nanotoxicology, but in many fields where nanoscale visualization is critical. New and emerging analytical methods and tools for nanomaterial detection, visualization, and characterization must keep pace with innovation in terms of nanomaterial development, use, and commercialization. Therefore, forms of higher-throughput screening and direct visualization technology, such as this one, must be leveraged for studying not only nanomaterial behavior in biological systems, but also applied in the context of exposure assessment. The system has great versatility and high practical utility--we've only begun to scratch the surface of what it can do," said Brenner.
The research team utilized a CytoViva HSI system, which incorporates an enhanced darkfield microscope that has improved contrast and a high signal-to-noise ratio for easy visualization of nanoparticles, as well as a hyperspectral imaging camera, which combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400-1000 nm at each pixel in a hyperspectral image. Hyperspectral data can then be used to identify materials of interest in a sample without the need for fluorescent labeling or other destructive sample preparation techniques.
"Nanomaterials have been used for decades in the dermatology consumer space, ranging from sunscreens to anti-aging cosmetics to antimicrobial dressings. Our ability to dispel concerns regarding safety has been limited due to the constraints of our imaging approaches, which is why the publication of this now validated technique is so important," said Adam Friedman, associate professor of Dermatology and Director of Translational Research at the George Washington School of Medicine and Health Sciences.
Not only did the researchers demonstrate the capability of EDFM-HSI to identify and map metal oxide nanoparticles in a porcine skin tissue model of exposure, but they also confirmed this method using traditional methods: Raman spectroscopy (RS) and scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS) for elemental analysis. After identifying areas within positive control tissue samples that were known to contain nanoparticles of interest, the same areas were analyzed via SEM-EDS and RS, which confirmed the identity of the materials. Once these areas were confirmed to be the nanoparticles of interest, reference spectral libraries (RSLs) containing hyperspectral data were created from these areas. RSLs were then used to map the experimental samples to assess the presence and distribution of nanoparticles in those tissues, using the spectral angle mapper (SAM) algorithm in the hyperspectral imaging and analysis software (ENVI 4.8).