The CellRaft® Technology is powered by our innovative software that controls the automated imaging and CellRaft isolation functions of the platform. Most importantly, the CellRaft Cytometry™ feature allows for software-driven decision-making to identify CellRafts of interest. User-defined attributes ranging from cell shape to colony size to fluorescence intensity allow for precise identification of exactly the desired cells or colonies.
The CellRaft AIR® System and software provide a seamless workflow for research, allowing biologists to engage with their engineered cells as they develop into colonies. This powerful tool enables diverse applications to be run on the system to capture the cell of choice from the CellRaft Array.
Software features include:
Track and trace capability for image-based record keeping
User-defined multiparameter analysis (e.g., time, morphology, phenotype)
Easy template creation for defining desired CellRafts
Custom population subsetting to assess cell behavior over time
Software-guided CellRaft selection
Automated CellRaft mapping from population gates for isolation
Monitor Cells Over Time
Easily identify cells of interest for automated isolation based on multiple parameters.
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Take a tour through our software and explore how it can work for your application.Â
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Multiparameter Analysis
Users can create unique sub-populations for CellRaft classification using a variety of user-defined parameters. In the example below, the user is looking for single cell derived colonies. The parameters can be created to identify CellRafts that have: a) single cells at timepoint one, b) cells that doubled at timepoint two, and c) contain a confluent colony at timepoint three.
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Image Over Time and Analyze at Each Time Point
The system captures snapshot images of cells dividing over time, and provides a curated list of CellRafts that meet experimental criteria. The user can define specific cell characteristics and identify overlapping subsets of CellRafts. Using CellRaft Cytometry, the user was able to locate CellRafts containing single cells at timepoint one, dividing cells at timepoint two, and rafts containing cells with a certain confluence at timepoint three. Using the population subset feature, the three populations can be overlayed in the Venn Diagram to identify the intersect of the three groups (green center). In the example below illustrating a cell line development workflow, the user is looking for single cell derived colonies.
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Set User Defined Criteria in Real-Time
The histogram plots the pixel size of every area of interest (AOI) identified on all of the CellRafts of the array scanned. Users can easily define the desired area for the AOI by toggling the sliders along the X-axis of the histogram. The green area in the curve highlights the selected area range.Â
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Easy Detection of Single Cells
A single cell on a CellRaft can be readily identified using CellRaft Cytometry (the white contour defines the boundaries of the area of interest).
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Image Based Phenotyping
Using fluorescence intensity, CellRafts containing clonal colonies that were gene induced were able to be easily identified. The software was also able to eliminate leaky cells that were expressing red fluorescence before being induced, ensuring the isolation of optimal clones for downstream experiments.
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Rare Population Detection
3T3 cells were engineered with blue fluorescent protein (BFP). The polyclonal population of cells also expressed human HER-2 cell surface receptor. Staining with a directly conjugated anti-HER-2 antibody was performed on Array (green). Using the software, the user was able to set up single cell populations along with blue and green fluorescence gates to determine which rafts contained single-cell derived colonies that were dually positive for HER-2 and BFP. The software was able to locate the few double-positive clones, as there were only 30 clones that were both positive for BFP and HER-2 in the bulk population seeded. For more information, see RaftNote.
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On-array Live Staining
Hepatic organoid stained with (blue) NucBlue nuclear and (green) EpCAM membrane. 2,500 organoid fragments were seeded on a 3D CellRaft Array. The software was able to locate organoids of a certain size to be used for z-stacking and isolation.Â
