Fig. 3: AI-powered image identification and sorting of microbial monoclones.
A AI-powered image analysis. The captured images can be used to identify the microchamber in the image by object detection algorithm and the region of interest (ROI) can be segmented based on OpenCV. Subsequently, a semantic segmentation model identifies bacteria inside the microchamber and provides relevant information such as the number of bacteria, gray scale area of the bacterial region. B Different numbers of bacterial samples were used to load into the microchamber. The images were acquired automatically by AI, which also identified the number of bacteria within the microchamber. At least three independent experiments were performed, and similar results were obtained. C The number of bacteria identified by AI was found to be linearly correlated with the number of bacteria loaded into the microchamber, with R2 of 0.993. n = 3 biological replicates. Data are presented as mean +/− SD. Source data are provided as a Source Data file. D AI-powered panoramic image analysis. Starting from one end of the chip, panoramic identification of the chip can be achieved using S-shaped window shifting. The images from each screen were analyzed to form the panoramic image of the chip, and the image and position information of each microchamber was collected and stored. In addition, fluorescence information corresponding to each microchamber of the chip can be obtained based on the coordinate information obtained from the bright field. Through regular monitoring, the image change information of each chamber can be obtained, providing technical support for obtaining the single-cell scale growth phenotype. E Using LIB technology, microscopic monoclones were exported as droplets, which were collected into 96-well plates for incubation with the assistance of the capillary. F The accuracy of droplet recovery was evaluated, and the probability of recovered droplets being re-culturable was assessed based on E. coli monoclonal droplets. n = 3 biological replicates. Data are presented as mean +/− SD. Source data are provided as a Source Data file.
