Considerable heterogeneity exists in even the simplest of cell systems. With the IncuCyte® S3 and Cell-by-Cell Analysis module, you can quantify the process and effects of cellular heterogeneity in real-time in living cells – inside your incubator. Study the dynamic, phenotypic changes of cell subsets during activation or differentiation, or understand how cell subsets respond to treatments using our unique and accessible approach to live-cell imaging and analysis.
The IncuCyte® S3 Live-Cell Analysis System, Cell-by-Cell Analysis software module, and IncuCyte® reagents provide a new, enabling, end-to-end solution for analyzing heterogeneous cultures at 96-well throughput.
|Identify individual adherent or non-adherent cells with advanced software algorithms in high-contrast phase images||Label-free quantification of the total cell population|
|Classification of cells based on morphology or fluorescence with our purpose-built, guided software workflow||Easily link cell subset phenotype to function or health, providing complementary functional data to research tools, such as single cell genomics analysis|
|Proprietary, non-perturbing reagents detect cell surface marker expression, function, or health||Enable multiplexed, kinetic analysis in living cells|
|Cells are kept stationary while optics move with our unique, mobile optical train, permitting observation of shifts in population dynamics in specific areas of the field.||Cells are maintained in the field of view during image acquisition|
|Uninterrupted incubation provided by your tissue culture incubator||Reduce artifacts with a consistent, physiologically-relevant environment during the entire experiment|
|Automated image acquisition and analysis enables high volume data generation in 96-well formats||Conduct robust pharmacological analysis. Screen therapeutic drug candidates, or study more variables in less time|
|Complete end-to-end solution including instrument, software and reagents||Spend more time investigating by reducing time spent troubleshooting|
Apply IncuCyte® Cell-by-Cell Analysis to heterogeneous populations such as PBMCs, immune or oncology preparations to study the dynamic behavior of individual subsets of cells, then generate powerful insights by relating data back to disease states, progression, and therapeutic efficacy. Observe differentiation or activation processes dynamically to understand subset modulation and transition over time, and identify therapeutic mechanisms of actions on a specific cell type in a mixed population.
Study dynamic changes in cell subpopulations and couple to processes such as activation or differentiation
Quantify cell-specific phenotypic changes in expression markers or morphology within mixed cultures in an unperturbed micro-environment
Perform kinetic phenotyping to identify subpopulations in mixed cultures
Measure fractional changes in number of cells labeled with your cell surface protein of interest
Uncover cell-specific cytotoxic treatment effects on health
Label a population of interest and multiplex with readouts of cell health using non-perturbing detection reagents
Complement your Existing Workflows
Figure 1A. Track changes in cellular parameters associated with T cell activation. Subset classification based on cell enlargement and morphological change in activated T-cells. PBMCs were treated with anti-CD3 and IL-2, or vehicle control, and monitored over time with IncuCyte® S3. (A-D) Activation induces a time-dependent increase in average cell area and eccentricity (all cells). Note the change in eccentricity precedes the increase in area. The cell-by-cell area distribution (E) and density plots (F-H) highlight the increased heterogeneity over time following activation, and the appearance of a population of large cells with high eccentricity. Values shown are the mean ± SEM of 12 wells.
Figure 1B. Analyze subsets of activated T-cells: CD71 upregulation. (A-C) Cell-by-cell density plots shows increase in CD71 (FabFluor-488 labeled) fluorescence as a function of time and cell area (phase) in activated T-cells. (D) Dynamic changes in the proportion of CD71+, but not CD4+ cells, follows activation. (E) Subset analysis shows preferential upregulation of CD71 expression in large (>100 mm2) vs small (<110 mm2) cells. These data demonstrate an activation-induced, time-dependent increase in CD71 expression and a strong linkage between cell size and CD71, with >90% of large cells expressing CD71 after 4 days of activation
Figure 2a. Immunophenotyping validation via cellular identification and classification on the IncuCyte® S3. Freshly isolated PBMCs from three donors were characterized for six CD markers and IgG control using either flow cytometry or live-cell Immunocytochemistry analysis using FabFluor-488 labeled Ab. A strong correlation was observed between two methods when considering the mean values from the three donors (A), or each donor alone (B).
Figure 2b. Phenotyping HER2 expression in various cell types using cell by cell analysis on the IncuCyte S3. A549, SKOV-3 or SkBr3 cells were characterised for HER2 expression using FabFluor-488 labeled Abs. Images (top row) and quantification of fluorescence (bottom row) demonstrated lack of HER2 expression in A549 cells, heterogeneous expression in SKOV-3 cells and homogenous, high expression in SkBr3 cells. Isotype control responses represent the negative population.
Figure 3. Track Cell Health in sub populations of cells: Time course of HT1080 fibrosarcoma apoptosis following Camptothecin (CPT, cytotoxic) or cyclohexamide (CHX, cytostatic) treatment. Cell health was determined with multiplexed readouts of IncuCyte® NucLight Red (nuclear viability marker) and non-perturbing IncuCyte® Caspase 3/7 Green Reagent (apoptotic indicator). Cell images show response at 24 h with associated classification masking (A & E). Cell subsets were classified based on red and green fluorescence using IncuCyte Cell-by-Cell Analysis Software tools (B & F). After CPT treatment, there was a decrease in the red population indicating loss of viable cells, increasing red and green fluorescence indicating early apoptosis, as well as increasing green fluorescence indicating late apoptosis (C). After CHX treatment there was a lack of apoptosis (G). Concentration response time courses of the early apoptotic population are shown (percentage of total cells exhibiting red and green fluorescence, D & H). Values shown are the mean ± SEM of 3 wells.
Combine the power of automated image acquisition and purpose-built cell-by-cell image analysis tools with unique live-cell imaging reagents to easily generate kinetic data from thousands of images. Study functional kinetic data from identified cellular subsets and compare to total population data.
The IncuCyte® S3 and Cell-by-Cell Analysis Module provides insight and productivity that compliments established technology for analysis of single cells:
|Flow Cytometry||High Content Imaging||Time-lapse Microscopy|
|Extraction of features at individual cell level|
|Population, Subset & Heterogeneity analysis tools||Manufacturer dependent|
|Live-cell, 'non-perturbing' protocols||
(for some applications)
|No cell lifting or fixing|
|Long term, full environmental control|
|Single-cell tracking||Manufacturer dependent|
|Spatial/Morphological insight - images & movies|
|Long-term temporal analysis|
|Automated acquisition & analysis||Manufacturer dependent|
Figure 4a. Cells identified in heterogeneous (mixed) cultures and cell by cell analysis. Characterization of a mixed B cell/T cell culture for the CD surface marker CD45 and CD20 using FabFluor-488 labeled Abs. (A) IncuCyte vessel view images (yellow = Ab-labelled cell) of mixed cell populations in the ratios shown. Note the greater proportion of CD20-labeled (Ramos) cells as the ratio of R:J increased in contrast to the CD45 that labels both cell types. (B) IncuCyte cell by cell quantification of the % expression in the mixed culture. (C) Time course of CD20+ cell count showing proliferation of CD20+ cells within the mixed culture. Values shown are the mean ± SEM of 4 wells.
Figure 4b. Label free cell counting of adherent cells using cell by cell analysis. Various densities of A549 NucRed cells were analysed either with cell by cell and red object count to validate label free counting over time. (A) Images demonstrate individual cell masking using the cell by cell software. (B) Time course of phase count and red count across densities shows overlay of data. (C) Correlation of count data over 48 h demonstrates R2 value of 1 with a slope of 1. This has been repeated across a range of cell types. Values show are the mean ± SEM of 4 wells.
|IncuCyte S3 Live-cell Analysis System||1 instrument||4637|
|IncuCyte Cell-by-Cell Analysis Software Module||1 module||9600-0031|
|IncuCyte® Mouse IgG1 FabFluor-488 Antibody Labeling Reagent||1 vial (50 µg)||4745|
|IncuCyte® Mouse IgG2a FabFluor-488 Antibody Labeling Reagent||1 vial (50 µg)||4743|
|IncuCyte® Mouse IgG2b FabFluor-488 Antibody Labeling Reagent||1 vial (50 µg)||4744|
|IncuCyte® Annexin V Red Reagent for Apoptosis||1 vial||4641|
|IncuCyte® Annexin V Green Reagent for Apoptosis||1 vial||4642|
|IncuCyte® Caspase 3/7 Green Reagent for Apoptosis||20 µl||4440|
|IncuCyte® Caspase 3/7 Red Reagent for Apoptosis||20 µl||4704|
|IncuCyte® Cytotox Red Reagent for counting dead cells||5 µl x 5||4632|
|IncuCyte® Cytotox Green Reagent for counting dead cells||5 µl x 5||4633|