Mounting evidence suggests that distinct microbial communities reside in tumors and play important roles in tumor physiology. Recently, a previous study profiled the composition and localization of intratumoral bacteria using 16S ribosomal DNA (rDNA) sequencing and histological visualization methods across seven tumor types, including human glioblastoma. However, their results based on traditional histological examinations should be further validated considering potential sources of contamination originating from sample collection and processing. Here, we aim to propose a three-dimensional (3D) in situ intratumoral microbiota visualization and quantification protocol avoiding surface contamination and provide a comprehensive histological investigation on local bacteria within human glioma samples. We develop a 3D quantitative in situ intratumoral microbiota imaging strategy, combining tissue clearing, immunofluorescent labeling, optical sectioning microscopy, and image processing, to visualize bacterial lipopolysaccharide (LPS) within gliomas in a direct, contaminant-free, and unambiguous manner. Through an automated statistical algorithm, reliable signals can be distinguished for further analysis of their sizes, distribution, and fluorescence intensities. In tandem, we also combined 2D images obtained from thin-section histological methods, including immunohistochemistry and fluorescence in situ hybridization, to provide comprehensive histological imaging for local bacterial components within human glioma samples. We have, for the first time, achieved 3D quantitative imaging of bacterial LPS colonized in gliomas in a contamination-free manner within human glioma samples. We also built the multiple histological evidence chain demonstrating the irregular shapes and sparse distribution of bacterial components within human glioma samples, mostly localized near nuclear membranes or in the intercellular space. This study provides favorable evidence for the presence of microbiota in human gliomas and provides information on the feature and distribution of bacterial components. The results, along with the integrated 3D quantitative intratumoral microbiota imaging method, are promising to provide insightful information into the direct interactions between the microbial community and the host in the tumor microenvironment.
Keywords: fluorescent labeling; glioma; image processing; microbiota; three-dimensional visualization; tissue clearing.
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