Rare Events Detection
App Notes
App Notes
In this document, we demonstrate how LiveDrop’s ModaFlow provides a high-quality detection system, effectively reducing both false-positive and false-negative events, thereby enhancing overall detection reliability. Flow cytometry is pivotal in critical clinical applications, enabling the detection of rare events. These range from identifying Minimal Residual Disease in cancer patients' blood to enumerating rare cell populations and detecting rare enzyme variants. However, conventional flow cytometry faces challenges in accurately detecting rare events, mainly due to false-positive and false-negative occurrences, which can compromise experiment reliability.
Cell sorting is a fundamental technique in biological research and clinical applications, allowing the isolation and purification of specific cell populations from heterogeneous samples. This ability to segregate cells based on intrinsic properties like size, morphology, surface markers, or molecular signatures has transformed fields such as immunology, cancer research, regenerative medicine, and drug discovery. In recent decades, advancements in cell sorting technologies have enhanced efficiency, sensitivity, and versatility. While Fluorescent-Activated Cell Sorting (FACS) is the gold standard, it's limited to sorting cells based on emitted fluorescence or fluorescence from bound fluorophores, restricting study of cell secretome and interactions. Additionally, FACS imposes significant mechanical stress on cells during sorting, potentially affecting viability and functionality.
By detecting events in droplets and providing a direct visual verification of the sorted droplets.The ModaFlow can easily distinguish true events from false events caused by sub-cellular debris, dead cells, dust clumps, particle aggregates and cell clusters.
In a first experiment depicted in Figure 1, samples containing both fluorescent beads and cells, were sorted and screened by the ModaFlow. In 9 independent experiments, the ModaFlow successfully detected 16 out of 17 beads in a total of 3,4 million cells!
Ina second experiment, beads and cells were prepared in an un-purified solution containing auto-fluorescent debris, potentially being detected as false-positive. As demonstrated in Figure 2, beads containing droplets are easily detected and distinguished from the droplets containing contaminants.
The ModaFlow excels in detecting rare events and distinguishing true positives from false positives by systematically capturing images of each detected droplet. The compartmentalization of samples into hundreds of thousands of micro-scale droplets, coupled with image acquisition, simplifies, accelerates, and enhances the reliability of object enumeration, detection, and quantification.
