Background

Hepatotoxicity is one of the leading causes for withdrawal of drugs from the market or limitationsin their use1. The design of cell-based assays to identify toxic effects early in discovery shouldreduce late-stage attrition. One potential indicator of hepatotoxicity is phospholipidosis, anincreased uptake of phospholipid in multi-lamellar vesicles.

Here we present data from cultured primary hepatocytes treated with phospholipidosis-inducingcompounds, followed byanalysis with the DefiniensEnterprise ImageIntelligenceTM Suite. Thismethod not only identifiesglobal changes but can alsoreveal subtle differences incellular physiology,potentially leading to moreinformed decisions whentaking compounds forward.

Methods

Rat primary hepatocytes were cultured in 96 wellplates, treated with control and test compoundsand labelled with synthetic phospholipid coupledto a fluorescent marker. Cellular DNA was labelledwith Hoechst 33342 (Fig. 1).

Images from the plates were captured with a GEINCell Analyzer 3000.

The images were analysed using DefiniensEnterprise Image IntelligenceTM platform. Thisuses Definiens Cognition Network Technology2 tobuild a topological hierarchical network of imageobjects (fig 2A).

Modules derived from the High Content Analysisapplication plug-in Definiens Cellenger® were usedto identify cells, nuclei and phospholpipidoticvesicles, while customised modules to addressother tasks were written in Definiens Developerand plugged into the solution (fig. 2B).

Results

1. Cellular Segmentation

Due to heterogeneity in the phospholipid (red)channel across treatments, information in theHoechst channel was used to generate bothnucleus and cell boundary information. This wasaccomplished despite very low signals at cellboundaries (fig. 3).

2. Live/Dead Cellular Classification

Four distinct cellular phenotypes were observed, basedon cellular and nuclear morphology. Healthy cellspossessed large, round nuclei, while dead cells eithershowed large, granular nuclei, small, bright nuclei, or nonuclei (enucleated). These phenotypes were reflectedin the class hierarchy, allowing extraction of informationat different levels of detail (fig. 4).

3. Standard readout: drug toxicity

Cells were classified as aliveor dead based on theclassification criteria above.

Toxicity-response curves of arepresentative plate’s data areshown below. Onecompound (C1) exhibitedsignificant toxicity at higherdoses of drug, from which theLD50 could be calculated (fig.5).

4. Standard readout: Phospholipidosis

The mean integrated intensity of phospholipid dye is one of the standard readouts to measurephospholipidosis. Only vesicles in viable cells were considered for this response.

For the compounds examined, C1 exhibited a strong phospholipidotic response, C2, C3 and C6exhibited weak responses, while C4and C5 were negative.

The maximal phospholipidoticresponse occurs at concentrationsaround 7 times lower than the toxicdose of drug (see compound 1,figure 6).

5. Subtle effects: vesicle location and clustering

Examination of many of the images, it would appear that there is a very strong bias forphospholipidotic vesicles to align themselves with membranes bordering other adjacent cells, asopposed to “naked” cell borders, bordering background. We examined whether this was the caseby sub-classifying vesicles according to their locations relative to the two different categories ofmembrane.

Analysis of total numbersof vesicles demonstrateover 80% are classified asbeing aligned tomembranes associatedwith other cells; however,when normalised to thelength of cellular orbackground membrane,the response was far lessmarked (fig 7).

6. Probing toxicity: nuclear phenotype

We then examined in more detail the mechanism of death due to toxic compounds. The overallproportion (and number) of enucleated cells remains relatively constant across the wells,demonstrating that thisphenotype appears to bedue to natural attrition,independent of treatment.However, at high doses,compound 1 causes a shiftin nuclear phenotype awayfrom the small/brightirregular (typical apoptotic)phenotype to the large,granular phenotype. Thiseffect was not seen in cellstreated with 80µMamiodarone, the cytotoxiccontrol (fig. 8), indicatingthat different mechanismsof death are associatedwith different compounds.

7. Responses of mono-vs multinucleated cells

It is not clear whether mono- or multinucleated hepatocytes behave differently with drugtreatments. Below we examine the average integrated vesicle intensity for the phospholipidoticcontrol and test compounds at the concentration exhibiting maximal phospholipidotic response.For rigorous examination individual intensities are normalised the area of the individual cells.

Multinucleated cells are onaverage larger thanmononucleated cells, the spotintensity values were normalisedto the area of each individual cell.While there appeared to be asmall difference between singleand multinucleated cells inresponse to compound C1, thisdifference was not statisticallysignificant (fig. 9).

Summary

� Automated, object-based image analysis was used to investigate phospholipidosis.

� Accurate and robust cellular classification was achieved despite low signal: background ratios.

� Straightforward readouts gave basic information on phospholipidotic and toxic cellularresponses.

� Hierarchical segmentation and classification of cellular constituents allows extensive, multivariateanalysis of subtle biological effects.

� These can be used to obtain deeper insights into assay systems and make more informeddecisions when progressing candidate compounds.

References1. Fung M; et al (2001). Drug Information Journal 35, 293–3172. Baatz M, et al. (2006). Cytometry Analysis (2006) 69, 652-658

AUTOMATED MULTIVARIATE ANALYSIS OFPHOSPHOLIPIDOSIS IN PRIMARYHEPATOCYTES USING DEFINIENSCELLENGER® AND DEFINIENS DEVELOPEREdward Ainscow, James Pilling, Nick Brown, Elaine Sullivan, Mike Sullivan.Advanced Science and Technology Laboratory, AstraZeneca, Charnwood, Loughborough LE11 5RH, UK.Nick Arini, Bettina Linssen, Barbara Zenger-Landolt, René Korn, Thomas Harberichter, Andrzej Cholewinski, Colin Blackmore.Definiens AG, Trappentreustrasse 1, 80339 Muenchen, Germany

www.definiens.com

Deeper

insights.Fasterresults.Betterdecisions.

Figure 1: Phospholipidosis Assay. Primary rat hepatocytes labelled with synthetic phospholipid (red) and Hoechst (blue). A = negative control; B = toxic control; C = phospholipidosis.

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Figure 1: Phospholipidosis Assay. Primary rat hepatocytes labelled with synthetic phospholipid (red) and Hoechst (blue). A = negative control; B = toxic control; C = phospholipidosis.

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Figure 1: Phospholipidosis Assay. Primary rat hepatocytes labelled with synthetic phospholipid (red) and Hoechst (blue). A = negative control; B = toxic control; C = phospholipidosis.

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Figure 3: Cellular segmentation. The Hoechst channel (A = shown with gamma correction) was used for cellular segmentation, despite low contrast between cells (B). Segmentation, showing mononuclear and multi-nucleated hepatocytes is shown in (C).

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Figure 3: Cellular segmentation. The Hoechst channel (A = shown with gamma correction) was used for cellular segmentation, despite low contrast between cells (B). Segmentation, showing mononuclear and multi-nucleated hepatocytes is shown in (C).

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Figure 3: Cellular segmentation. The Hoechst channel (A = shown with gamma correction) was used for cellular segmentation, despite low contrast between cells (B). Segmentation, showing mononuclear and multi-nucleated hepatocytes is shown in (C).

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Figure 5: Drug Toxicity Curves. A = Heatmap, with positive, negative and phospholipidosis controls in columns 2 and 11, and dose responses (decreasing col. 3 to col. 10) for 6 compounds. B = Toxicity curves for 6 compounds (C1-C6).

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Figure 5: Drug Toxicity Curves. A = Heatmap, with positive, negative and phospholipidosis controls in columns 2 and 11, and dose responses (decreasing col. 3 to col. 10) for 6 compounds. B = Toxicity curves for 6 compounds (C1-C6).

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Figure 6: Phospholipidosis dose responses. Dose responses of 6 compounds, with EC50 calculations for compounds 1 and 6.

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Figure 6: Phospholipidosis dose responses. Dose responses of 6 compounds, with EC50 calculations for compounds 1 and 6.

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CFigure 7: Location of phospholipidoticvesicles. The majority of vesicles appear to be preferentially aligned with membranes adjacent to other cells (A, B). Normalisation to the length of cell-to-cell or cell-to-background membrane indicates that the effect exists, but is more subtle than visual inspection.

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Figure 8: Dead cell phenotype. The profile of profile of dead nuclei shifts towards the large,granular phenotype with increasing doses of compound 1. This behaviour is different from treatment with cytotoxic controls, indicating different mechanisms of cell death occur at higher doses.

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Figure 8: Dead cell phenotype. The profile of profile of dead nuclei shifts towards the large,granular phenotype with increasing doses of compound 1. This behaviour is different from treatment with cytotoxic controls, indicating different mechanisms of cell death occur at higher doses.

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Figure 9: Comparison of mono-and multinucleated cells. Mean integrated spot intensity normalised to cell area. Error bars, ± sem.

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Figure 2: Definiens Cognition Network Technology - Topology and Modules.The technology builds a network of image objects to describe elements in the image (A). Pre-defined and customised analysis modules were configured to perform the analysis task (B).

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Figure 2: Definiens Cognition Network Technology - Topology and Modules.The technology builds a network of image objects to describe elements in the image (A). Pre-defined and customised analysis modules were configured to perform the analysis task (B).

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Figure 4: Nucleus and Cellular Classification. Images (left) show different phenotypes recognised and classified during the analysis, while the class hierarchy (right) enables multivariate data reporting of different object classes.

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Figure 4: Nucleus and Cellular Classification. Images (left) show different phenotypes recognised and classified during the analysis, while the class hierarchy (right) enables multivariate data reporting of different object classes.

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Figure 4: Nucleus and Cellular Classification. Images (left) show different phenotypes recognised and classified during the analysis, while the class hierarchy (right) enables multivariate data reporting of different object classes.

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