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IncuCyte® Applications

IncuCyte® S3 Cell-by-Cell Analysis

Overview

Overview

WHITE PAPER: Live-cell Analysis of Cell Subsets and Heterogeneity Download now

Answer more questions about your non-adherent cell models with IncuCyte® S3’s Cell-by-Cell Analysis

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.

Key Features and Benefits

Feature Benefit
Identify individual 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. Non-adherent 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

Cell-by-cell

Cell-by-Cell Analysis

Gain dynamic insight into the phenotypic biology of subsets of cells

Apply IncuCyte® S3’s Cell-by-Cell Analysis to heterogeneous populations such as PBMC’s or non-adherent immuno-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.

Request an IncuCyte Demo    Request more information

Video Cell-by-cell Subpopluation

Key Advantages

Key Advantages

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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

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Perform kinetic immunophenotyping to identify subpopulations in mixed cultures

Measure fractional changes in number of cells labeled with your cell surface protein of interest

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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

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Complement your Existing Workflows

  • Easily generate kinetic data from thousands of images using unique Cell –by –Cell image analysis tools and live-cell reagents
  • Study functional kinetic data from identified cellular subsets and compare to total population data

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

Cell by Cell Subpupulation Figure 1a - Track changes in cellular parameters associated with T cell activation

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

Cell by Cell Subpopulation Figure 1b - Analyze subsets of activated T-cells: CD71 upregulation


Identify subpopulations in mixed cultures with kinetic immunophenotyping

Measure fractional changes in number of cells labeled with your cell surface protein of interest.

Figure 2. 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).

Cell by Cell Subpopulation Figure 2 - Immunophenotyping validation via cellular identification and classification on the IncuCyte S3


Uncover cell-specific cytotoxic treatment effect on cell health

Label a population of interest and multiplex with readouts of cell health using non-perturbing detection reagents.

Figure 3. Measure cell health in sub population of cells: human CD8+ T-lymphocytes are susceptible to vincristine-induced apoptotic cell death.  (A) Frequency histograms of FabFluor-488-CD8, -CD45 and -IgG-labeled hPBMCs.  (B & C)  IncuCyte® images showing color-coded subsets of healthy and apoptotic (IncuCyte® Annexin V+) CD8+ or CD8- cells (4 groups) following treatment with vincristine (300 nM) or vehicle (48 h). Vincristine induced a concentration- and time-dependent reduction in the proliferation of CD8+ cells (D) and a concomitant increase in apoptosis (E). Concentration-response curves yielded IC50 or EC50 values of 4 nM for anti-proliferation and 8 nM for induction of apoptosis (F). Values shown are the mean ± SEM of 3 wells.

Cell by Cell Subpopulation - Measure cell health in sub population of cells: human CD8+ T-lymphocytes are susceptible to vincristine-induced apoptotic cell death


Complement your existing workflows

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.

Quick guide:

Cell by Cell Subpoulation Quick Guide

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Comparison to traditional technology

The IncuCyte® S3 and Cell-by-Cell Analysis Module provides insight and productivity that compliments established technology for analysis of single cells:

  IncuCyte
Cell-by-Cell
Flow Cytometry High Content Imaging Time-lapse Microscopy
Biological Insight
Extraction of features at individual cell level
Population, Subset & Heterogeneity analysis tools Manufacturer dependent
Live-cell, 'non-perturbing' protocols
(for some applications)
Long term, full environmental control
Single-cell tracking Manufacturer dependent
Spatial/Morphological insight - images & movies
Long-term temporal analysis
Productivity
Microplate throughput
Automated acquisition & analysis Manufacturer dependent

Validation Data

Validation data

Cell by Cell Figure 4 - Cells identified in heterogeneous (mixed) cultures and Cell-by-Cell analysis

Figure 4. Cells identified in heterogeneous (mixed) cultures and Cell-by-Cell analysis: FabFluor-488 coupled anti-CD20 and anti-CD45 labeling of Jurkat & Ramos cells. Characterization of a mixed B cell/T cell culture for the CD surface marker CD45 and CD20. FabFluor-488 labeled Abs were added to the cultures. (A) IncuCyte® Vessel View images (Yellow = Ab-labeled cell) of mixed cell populations in the ratios shown (J=Jurkat, R=Ramos). Note the greater proportion of CD20-labeled (Ramos) cells as the ratio of R:J increases in contrast to CD45 that labels both cell types. (B) IncuCyte® cell-by-cell quantification of % expression in the mixed culture. (C, D) Time-courses of CD20+ cell count and % of population. Note the proliferation (increase in cell count) of CD20 cells, and time-dependent increase in proportion of CD20+ cells within the mixed culture. Values shown are the mean ± SEM of 4 wells.

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