Single Cell Picking
Single Cell Picking - Related Videos
10:16
Automated and High-throughput Microbial Monoclonal Cultivation and Picking Using the Single-cell Microliter-droplet Culture Omics System
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2025
This protocol describes how to use the Single-cell Microliter-droplet Culture Omics System (MISS cell) to perform microbial monoclonal isolation, cultivation, and picking. The MISS cell achieves an integrated workflow based on droplet microfluidic technology, which offers excellent droplet monodispersity, high parallel cultivation, and high-throughput biomass detection.
07:28
Transfection, Selection, and Colony-picking of Human Induced Pluripotent Stem Cells TALEN-targeted with a GFP Gene into the AAVS1 Safe Harbor
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Cited by 12 •
2015
TALEN-mediated gene editing at the safe harbor AAVS1 locus enables high-efficiency transgene addition in human iPSCs. This protocol describes the procedures for preparing iPSCs for TALEN and donor vector delivery, transfecting iPSCs, and selecting and isolating iPSC clones to achieve targeted integration of a GFP gene to generate reporter lines.
08:06
Laparoscopic Ovum Pick-up For In Vivo Oocyte Retrieval In Alpacas
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2026
This protocol describes a reproducible method for in vivo oocyte recovery in alpacas using hormonal synchronization, FSH superstimulation, and laparoscopic ovum pick-up (LOPU). The procedure yields consistent follicular responses and efficient oocyte recovery, supporting applications for in vitro embryo production and advanced reproductive biotechnologies.
11:45
Three-Dimensional Kinematic Characterization of an Object Pick-Up Task Using Motion Capture
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2026
This protocol presents a standardized full-body motion capture approach for assessing the object pick-up task, illustrating how distinct movement strategies and compensatory patterns can be quantitatively characterized during this common functional activity.
09:45
Detection of Copy Number Alterations Using Single Cell Sequencing
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Cited by 9 •
2017
Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.
FAQs
The selection process can rely on microscopy-guided micromanipulation or automated cell-handling systems. In either case, researchers identify a target within a mixed population, use a micropipette or related tool to capture it, and transfer it separately. The distinction lies in how target recognition and handling are performed, while both approaches support focused analysis of individual cells.
Tumors can contain cells with different genomic, transcriptomic, phenotypic, or drug-response characteristics. Bulk assays combine these populations, which can obscure uncommon or contrasting cellular behaviors. Examining separated cells instead allows researchers to associate specific properties with individual cells, providing a clearer view of heterogeneity and clonal variation within a tumor sample.
An isolated cell can be directed toward culture or molecular testing, depending on the research objective. Molecular analyses may examine genomic or transcriptomic characteristics, while other evaluations can focus on phenotype or drug response. These measurements help connect the properties of a single cell with disease progression or treatment sensitivity rather than averaging signals across the entire population.
A typical workflow begins with a mixed cell population and identification of a target cell using microscopy or an automated handling system. The selected cell is captured with a micropipette or related tool, transferred away from the original population, and deposited into a separate container. That isolated material can then undergo culture or molecular testing.
Single Cell Picking is particularly useful when a cancer sample contains rare cell populations or substantial clonal variation. Separating cells makes it possible to examine less abundant groups that may be difficult to interpret in bulk measurements. The approach therefore supports focused studies of tumor heterogeneity and comparisons among individual cells within the same broader sample.
After separation, individual cancer cells can support phenotypic or drug-response analyses. Comparing these results across isolated cells can reveal variation in treatment sensitivity that a population-level measurement might conceal. When combined with genomic or transcriptomic information, the findings can help relate cellular characteristics to differences in response and provide a more resolved view of cancer behavior.