A self-seeding microwell chip is introduced for the isolation and interrogation of single cells. A cell suspension is transferred to a microwell chip containing 6400 microwells, each microwell with a single 5 μm pore in the bottom. The fluid enters the microwell and drags a cell onto the pore. After a cell has landed onto the pore, it will stop the fluid flow through this microwell. The remaining fluid and cells will be diverted to the next available microwell. This results in a fast and efficient distribution of single cells in individual microwells. After identification by fluorescence microscopy, the cells of interest are isolated from the microwell by punching the bottom together with the cell. The overall single cell recovery of seeding followed by isolation of the single cell, is >70% with a specificity of 100% as confirmed by the genetic make-up of the isolated cells.

Here we present the Puncher technology for the isolation of single cells. This technology combines a silicon chip with microwells, fluorescence imaging, and a punching method to isolate and transfer the single cells to standard reaction tubes. The technology is compatible with commercially available downstream workflows and instrumentation. Here we focus on the isolation of CTC but the Puncher technology can be applied to isolate single cells from liquid biopsies and more general from cell suspensions. It is especially suited for cell suspensions that contain: • Cells of interest at a frequency of 1 per 10,000 or less • A low total number of cells ranging from 1 to 100,000, that are present in a volume of 0.01 to 50 mL.The frequency of appearance of CTC in blood is in the order of the 1 per 10 6 leukocytes.To be able to isolate the single CTC with the Puncher technology, enrichment of the CTC by a 3 logs reduction of the leukocytes is required. Here we describe the use of Rosettesep and Parsortix as examples of pre-enrichment methods that are compatible with the Puncher technology and further downstream applications.

Self-seeding microwell chips can sort single cells into 6400 wells based on cell size and their identity verified by immunofluorescence staining. Here, we developed a microfluidic device in which these single cells can be placed, lysed and their DNA amplified for further interrogation. Whole blood spiked with MCF7 tumor cells was passed through the microwell chips after leukocyte depletion and 37% of the MCF7 cells were identified by epithelial cell adhesion molecule (EpCAM) staining in the microwells. Identified single cells were punched into the reaction chamber of the microfluidic device and reagents for cell lysis and DNA amplification introduced sequentially by peristaltic pumping of micro-valves. On-chip lysis and amplification was performed in 8 parallel chambers yielding a 10,000 fold amplification of DNA. Accessibility of the sample through the reaction chamber allowed for easy retrieval and interrogation of target-specific genes to characterize the tumor cells.

After a CellSearch-processed circulating tumor cell (CTC) sample is imaged, a segmentation algorithm selects nucleic acid positive (DAPI+), cytokeratin-phycoerythrin expressing (CK-PE+) events for further review by an operator. Failures in this segmentation can result in missed CTCs. The CellSearch segmentation algorithm was not designed to handle samples with high cell density, such as diagnostic leukapheresis (DLA) samples. Here, we evaluate deep-learning-based segmentation method StarDist as an alternative to the CellSearch segmentation. CellSearch image archives from 533 whole blood samples and 601 DLA samples were segmented using CellSearch and StarDist and inspected visually. In 442 blood samples from cancer patients, StarDist segmented 99.95% of CTC segmented by CellSearch, produced good outlines for 98.3% of these CTC, and segmented 10% more CTC than CellSearch. Visual inspection of the segmentations of DLA images showed that StarDist continues to perform well when the cell density is very high, whereas CellSearch failed and generated extremely large segmentations (up to 52% of the sample surface). Moreover, in a detailed examination of seven DLA samples, StarDist segmented 20% more CTC than CellSearch. Segmentation is a critical first step for CTC enumeration in dense samples and StarDist segmentation convincingly outperformed CellSearch segmentation.

Here the feasibility is demonstrated that by combining Surface Plasmon Resonance Imaging (SPRi) and self-sorting microwell technology product secretion of individual cells can be monitored. Additionally isolation of the selected cells can be performed by punching the cells from the microwells using coordinates of the positions of microwells obtained with SPRi. Cells of interest can be retrieved sterile from the microwell array for further cultivation.