The combination between the electrochemical sensor and selective specificity of MB modified aptamer(MB-Apt) yielded an electrochemical aptasensor with a high sensitivity and excellent specific recognition ability to STX.

The association between the gut microbiome and the five stages of colorectal cancer (CRC) (healthy, polyposis, nonadvanced adenoma, advanced adenoma, and cancer) remains unclear. We performed 16S rRNA sequencing of the V3-V4 amplicon from 999 samples from subjects at various stages of CRC development and constructed an accurate predictive random forest model for CRC development. In the testing set, our five-category CRC prediction classifier had accuracies of 0.84 and 0.74 using the relative operational taxonomic unit (OTU) abundances and relative genus abundances, respectively. Specifically, the OTU-based classifier had a sensitivity of 0.97 and specificity of 0.97 for CRC samples, and the genus-based classifier had a sensitivity of 0.97 and specificity of 0.95 for CRC samples. Meanwhile, the gut microbiota was found to differ at all stages of CRC development. The differential abundances of closely related bacteria were used to accurately classify the five stages of CRC development. Additionally, both unannotated and annotated OTUs played important roles in classifier modelling. Our work not only provides valuable 16S rRNA sequencing data from patients and healthy individuals on a large scale but also identifies reproducible gut microbiome biomarkers for CRC staging and highlights their potential applications as noninvasive microbiome biomarkers for diagnosis and as predictive CRC screening tests.