Detection and comparison of tumor cell-associated microbiota from different compartments of colorectal cancer.

Introduction: Intratumoral microbes play an important role in the development of colorectal cancer (CRC). However, studying intratumoral microbes in CRC faces technical challenges, as tumor microbe communities are often contaminated by fecal microbes due to the structure of the gut folds and villi. The present study aimed to develop a new method for isolating tumor cell-associated microbiota and comparing microbial populations from different compartments. Materials and methods: The distribution of intestinal bacteria was detected using immunohistochemistry combined with 5R-16s rRNA gene sequencing to explore the effects of the sampling site and number of washes on the detection of microbiota. The 5R-16s rRNA gene sequencing was performed using 44 samples from 11 patients with CRC, including CRC tumor tissues (TT), normal tissues adjacent to CRC (NT), tumor cells (TC), and normal cells (NC). TC and NC were obtained from the TT and NT using an enzymatic digestion method. The microbiota and their potential functions in the four groups were analyzed and compared to determine the differential microbiota related to CRC. Results: Bacteria were mainly distributed in the feces covering intestinal tissues and in the epithelial cells and macrophages within the tissues. Different sampling sites and number of washes led to detection of different microbiota distributions. Although the cleaning method could be controlled, sampling sites varied and led to different microbiota distributions. The phyla of Firmicutes and Bacteroidetes were highly abundant in the conventionally used tissue samples, whereas Proteobacteria was the most abundant phyla in the cell samples isolated with the new method (i.e., after cell enzymatic hydrolysis). Detection of CRC cell-associated microbiota using a cell enzymatic digestion method showed that some bacteria, such as Conclusion: The cell enzymatic digestion method reduced fecal bacterial contamination, enabling low biomass intratumoral microbiota to be detected and allowing prediction of bacterial distributions.