EP2171443A1

EP2171443A1 - Method for predicting biological systems responses in hepatocytes

Info

Publication number: EP2171443A1
Application number: EP08779870A
Authority: EP
Inventors: William Irwin; Lawrence Vernetti; Patricia A. Johnston; D. Lansing Taylor
Original assignee: Cellumen Inc
Current assignee: Cellumen Inc
Priority date: 2007-06-26
Filing date: 2008-06-26
Publication date: 2010-04-07
Also published as: CN101784895A; WO2009002565A1

Abstract

The inventive method employs a 'systems biology' approach to predicting hepatotoxicity and other biological hepatocyte responses resulting from exposure to the test substance. In one embodiment, the invention provides an automated method for predicting the hepatocyte biological systems effect of a test substance. In another embodiment, the invention provides a method for constructing a knowledgebase (or database) of cellular systems biology response profiles for reference substances with known biological systems effects. In another embodiment, the invention provides a set of protocols and software tools used to carry out the profiling. Another embodiment of the invention is a panel of reagents. In another embodiment, the invention provides a set of protocols and software tools used to carry out the profiling. Another embodiment of the invention is a panel of reagents and protocols required for generating cellular systems biology response profiles, either to create a knowledgebase, or to use with an existing knowledgebase and informatics software to profile substance physiological effects. Another embodiment of the invention is a database of physiological profiles.

Description

METHOD FOR PREDICTING BIOLOGICAL SYSTEMS RESPONSES IN

HEPATOCYTES

RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No. 60/946, 186, filed on June 26, 2007.

The entire teachings of the above application are incorporated herein by reference.

BACKGROUND OF THE INVENTION

Ultimately, many candidate drugs fail because hepatocellular toxicity is discovered during animal drug safety trials, or even in late stage clinical trials in humans. Yet, even after drug approval there is still a substantial risk for hepatotoxicity in marketed drugs. Despite occasional drug withdrawal owing to non- hepatic toxicities, liver toxicity is the most common reason cited for withdrawal or significantly limiting the use of approved drugs. Overall, hepatotoxicity results in inefficiency and costs that could be reduced by the use of earlier-stage assays with high predictive value to identifying in vivo liver toxicity.

Considering that the human liver is highly sensitive to all kinds of environmental toxicants, the challenge in environmental toxicology is to develop highly predictive and rapid screening methods to assess the impact of substances on 2 human health, including potential toxicity to the liver.

Several factors complicate the problem, such as increasingly large numbers of substances to be tested; the complexities of environmental exposure require testing over a broad range of exposure mechanism, concentration and time; and uncertainties regarding the influence of age and genetic variability on the results. Reliable means to improve the efficiency of environmental toxicology testing, and to reduce the number of animal tests required, are actively being sought by the National Toxicology Program at the United States National Institutes of Health and other governmental and private sector entities worldwide. In these areas, and others in which cellular assays are central, progress is limited by assays that are typically focused on a single cellular process, as there are limited tools available for analyzing complex, multi-component system responses. A recent comparison of the performance of a panel of cytotoxicity assays, including DNA synthesis, protein synthesis, glutathione depletion, superoxide induction, Caspase-3 induction, membrane integrity and cell viability found that these assays on average had only half the predictive power of animal studies (Xu et al., Chem Biol Interact, 2004. 150(1): p. 1 15-28.). These assays were carried out independently, and no attempt was made to combine the readouts in any quantitative way, to improve the overall predictivity. In addition, other studies have shown that the multidimensional cellular responses from cell-based assays can be clustered using standard methods, to identify compounds with similar activities (Taylor et al., Drug Discov Today, 2005, 2(2): p. 149-154; Mitchison, Chembiochem, 2005. 6(1): p. 33-9; Perlman, Science, 2004. 306(5699): p. 1194-8). Taken together, these studies have demonstrated proof of principle for clustering compound responses, but have not attempted to correlate these identified clusters with specific response profiles and then use the response to predict the physiological impact of unknown substances.

A simple automated classifier has been developed for use with some commercially available assays. This classifier allows the use of Boolean operations to combine the outputs from several assay features into a single result (Abraham et al., Preclinica, 2004. 2(5): p. 349-355). These Boolean operations allow the assay developer to define an output that combines several feature measurements. This is very useful in expanding the scope of some high content screening (HCS) assays, but has limited features, and is certainly not designed for, nor would it be easy to use with multidimensional feature sets. Accordingly, a recent study describes a multidimensional cytotoxicity assay using human Hep G2 that has 80% correlation to clinical hepatotoxicity (P. J. O'Brien et al, Arch Toxicol, 2006, 80(9), p. 580- 604). However, HepG2 cells lack many functions of differentiated hepatocytes. Consistent with the importance for early detection of hepatotoxicity liabilities, there is a need to develop a multidimensional cellular systems biology screening method in primary hepatocytes for predicting mechanism-based hepatotoxicity. SUMMARY OF THE INVENTION

The invention provides methods and system for cellular systems biology profiling and analysis that comprise multicolor fluorescence of five or more (e.g., multiplexed) biomarkers coupled with searchable databases. The invention provides methods for analyzing and cellular systems biology (CSB) (also sometimes referred to herein as "systems cell biology") profiling of hepatocyte responses. Cellular systems biology is the investigation of the integrated and interacting networks of genes, proteins, and metabolites that are responsible for normal and abnormal cell functions. One embodiment of the invention provides a method for predicting the biological systems effect of a test substance on hepatocytes (e.g., primary hepatocytes, stem cell-derived hepatocytes, hepatocytes within a liver section, hepatocyte explant culture, or a hepatocyte-derived cell line). The method comprises providing hepatocytes, e.g., hepatocytes in a high density plate format, in an overlay culture, encapsulated, or grown on flexible 3D support matrices. The hepatocytes have metabolically active cytochrome P450 (the hepatocytes are sometimes referred to as "metabolically active"), such that the hepatocytes can metabolize compounds, e.g., drugs. The hepatocytes are contacted with a test substance and six or more cellular features in at least two cellular functional classes are measured, wherein at least one cellular functional class is phospholipidosis or steatosis, to produce a response profile of the hepatocytes contacted with the test substance. Cellular features can be measured using standard techniques, e.g., by acquiring at least one image of the hepatocytes contacted with the test substance using at least one optical mode and analyzing the image to measure the six or more cellular features. The combination of the six or more cellular features produces a biological systems effect profile of the test substance on the hepatocytes. This response profile is compared to other response profiles, which may be, for example, in a database, of known biological systems effects of one or more substances on cells (e.g., hepatocytes), such that if the response profile of the hepatocytes contacted with the test substance is the same as, or is similar to, a response profile in the database, then the test substance is predicted to have the same or similar biological systems effect as the substance that produced the known biological systems effect on cells (e.g., hepatocytes) in the database.

One embodiment of the invention provides a method for profiling a hepatocyte response state. The method comprises obtaining one or more hepatocytes that are labeled with a panel of fluorescently labeled reagents, thereby producing one or more fluorescently labeled cells. Each fluorescently labeled reagent is specific for a biomarker, and the panel of fluorescently labeled reagents detects at least about five or more different biomarkers. The detection of a biomarker provides a read-out of one or more features of the one or more cells. In one embodiment, the invention provides an automated method using high density plates (such as, for example, 384 well microtiter plates) for predicting the hepatocellular systems effects of a test substance. In accordance with one aspect, hepatocytes can be isolated from any species (such as, for example, rat, mouse, human, dog, pig, and/or rabbit), the hepatocytes to be treated with the test substance are provided, and the hepatocytes to be treated contain a unique combination of fluorescent or luminescent reporters or manipulations. The reporters respond to and indicate a functional response, whereas the manipulations produce a functional response in the hepatocytes. Either before or after addition of the reporters or performing the manipulations, the hepatocytes are contacted with (incubated with) the test substance. After the addition of the reporters or performing the manipulations and contacting the hepatocytes with the test substance, hepatocytes are imaged or scanned to obtain fluorescence images of the reporters. Thereafter, images of the hepatocytes are analyzed to measure or detect biomarkers. Thereafter, these features obtained from the biomarker measurements are combined to produce a cellular systems biology response profile for the test substance. In accordance with another aspect, a battery of hepatocytes to be treated is provided, which is similarly incubated with the test substance.

Then, images of hepatocytes within the battery are acquired and analyzed to measure or detect biomarkers indicative of cellular functional classes. In a next step, these features from the hepatocytes are combined to produce a cellular systems biology response profile for the test substance. In either aspect, the method involves finally comparing the cellular systems biology response profile of the test substance to a database (or knowledgebase) of cellular systems biology response profiles for reference substances with known biological systems effects on the liver. As a result of such comparison, the extent of correlation between the response profiles of the test substance to the database of cellular systems biology response profiles for substances with known hepatocellular systems effects indicates the probability that the test substance will exhibit an effect in a living hepatocyte or liver.

Another embodiment of the invention provides a method for constructing a knowledgebase (or database) of cellular systems biology response profiles for reference substances. Such substances can have known hepatocellular biological systems effects. In one embodiment is a method for constructing a database of cellular systems biology response profiles for hepatocytes contacted with one or more reference substances. The method comprises contacting hepatocytes having metabolically active cytochrome P450 with a first reference substance. The hepatocytes are labelled with a panel of fluorescently labeled reagents to produce one or more fluorescently labeled hepatocytes. Each fluorescently labeled reagent is specific for a biomarker and the panel of fluorescently labeled reagents detects at least five different biomarkers. The detection of a biomarker provides a read-out of one or more features. In a particular embodiment, at least one feature is related to at least one cellular functional class selected from the group consisting of phospholipidosis and steatosis. The one or more fluorescently labeled hepatocytes can be imaged with at least one optical mode to produce a set of data that can be analyzed for one or more features of each of the five or more biomarkers. The combination of the features of the five or more biomarkers generates a cellular systems biology profile of the hepatocytes for the first reference substance. This cellular systems biology profile can be added to a database of cellular systems biology profiles for reference substances. Further reference substances (e.g., second, third, fourth, etc. substances) can be similarly analyzed and added to the database thereby constructing a database of cellular systems biology response profiles for hepatocytes contacted with one or more reference substances. In accordance another aspect, a battery of hepatocytes to be treated with the test substance is provided, and the hepatocytes to be treated contain a unique combination of fluorescent or luminescent reporters or manipulations. Either before or after addition of the reporters or performing the manipulations, the hepatocytes are contacted with (incubated with) a reference substance. After the addition of the reporters or performing the manipulations and contacting the hepatocytes with the reference substance, hepatocytes are imaged or scanned to obtain fluorescence images of the reporters. Then, images of the hepatocytes are analyzed to measure or detect biomarkers. In a next step, these features from the hepatocytes are combined to produce a cellular systems biology response profile for the reference substance. In accordance with another aspect, a battery of hepatocytes to be treated is provided, which is similarly incubated with the reference substance. Thereafter, images of hepatocytes within the battery are acquired and analyzed to measure or detect biomarker indicative of cellular functional classes. In a next step, these features from the hepatocytes are combined to produce a cellular systems biology response profile for the test substance. In either aspect, the method involves comparing the cellular systems biology response profile of the test substance to a database (or knowledgebase) of cellular systems biology response profiles for reference substances with known hepatocellular biological systems effects. The cellular systems biology response profile for the reference substance then is added to the database. The steps can be repeated using different reference substances (e.g., first reference substance, second reference substance, etc.) to increase the database. The invention also provides a knowledgebase (or database) of cellular systems biology response profiles.

The method can result in the identification and classification of predicted in vivo hepatocellular effects in hepatocyte cells, the liver, and effect on an organism as a whole, and other functional responses for applications in drug discovery, environmental toxicology, biomedical research and in other fields (e.g., environmental health and industrial safety).

In another embodiment, the invention provides a set of protocols and software tools used to carry out the profiling. Another embodiment of the invention comprises a panel of reagents and protocols for generating cellular systems biology response profiles, either to create a knowledgebase, or to use with an existing knowledgebase and informatics software to profile substance physiological effects. Another embodiment of the invention is a database of physiological profiles. Also provided are kits comprising reagents and instructions for practicing the methods described herein.

Yet another embodiment of the invention provides a business method wherein one or more candidate drug compounds are sent from a first drug discovery company to a second toxicity screening company and the second toxicity screening company performs toxicity screening on the one or more compounds utilizing one or more of the aspects of the invention described above and returns to first drug discovery company a cellular systems biology toxicity report. These aspects, and other inventive features, will be apparent from the accompanying drawings and following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. Figures IA and IB presents a flowchart of one embodiment of the inventive method. Figure IA concerns construction of the database or knowledgebase and Figure IB concerns assessing a test compound using the database or knowledgebase.

Figure 2 depicts exemplary images from multiplexed HCS assays in rat hepatocytes. Figure 3 illustrates the sample flow while processing plates to produce profiles in accordance with the inventive method.

Figures 4A, 4B and 4C illustrate a hepatocyte map revealing DNA content changes in at two cell populations that differ in nuclear size.

Figures 5A, 5B and 5C illustrate some graphical display methods to display cellular responses that contribute to creating a cellular systems biology response profile.

Figure 6 illustrates a combination often toxicity related functional classes associated with toxicity assessment and corresponding hepatocellular biomarkers.

Figure 7 illustrates standard plate layouts for Hepatotoxicity Profiling Multiplex Plates 1 and 2 described in Example 2. Figures 8A and 8B present data generated by the hepatotoxicity analysis based on dose response described in Example 2.

Figure 9 presents data demonstrating CellCipher profile clustering analysis of a 30 compound test set evaluated in Hep G2 cells as described. Figure 10 demonstrates CellCipher profile principal component analysis of a

30 compound test set evaluated in Hep G2 cells.

Figures 1 IA-C are graphs demonstrating metabolism dependent toxicity in isolated rat hepatocytes. FIG. 1 IA illustrates time dependent decrease in metabolic capacity in demonstrated in hepatocytes. Three hours after plating Cytochrome P450 metabolism is approximately 70% the level of freshly isolated cells but falls to 30% and 20% after 16 or 24 hr, respectively. FIG. 1 IB illustrates that the toxic product from diclofenac metabolism is required to produce overt cytotoxicity and is demonstrated as dose and time-dependent cell loss at 24 and 48 hr. However, no toxicity is evident after 72 hr exposure to a cell line that lacks metabolic capacity (HepG2 cells). FIG. HC illustrates the importance of timing compound exposure to metabolic activity is demonstrated in hepatocytes. When diclofenac is treated in hepatocytes 16 hr after plating, the toxicity is reduced as compared to those treated at 3 hr.

Figures 12A-C illustrate hepatocytes regaining polarized bile canalicular transport functions after 4 days in overlay cultures. Figure 12A is an image demonstrating normal transport in control cells and showing increased fluorescence in bile canalicular spaces formed between adjacent hepatocytes. Figure 12B is an image showing that normal transport function can be inhibited by compounds such as troglitazone as shown by decreased fluorescence into bile canalicular spaces. Figure 12C is a graph of image analysis processing that can be used to quantify the transport of fluorescent dye by normalizing the either the intensity or the area of fluorescence in-between adjacent hepatocytes to the total hepatocyte intensity or area, respectively.

DETAILED DESCRIPTION OF THE INVENTION A description of example embodiments of the invention follows. The present invention is directed toward extending a cell systems biology approach into isolated hepatocytes. The cell is the simplest living system. Tissues are collections of specific cell types forming interacting colonies of cells. Although cells and tissues are less complex than a complete organism, they posses significant functional complexity allowing a detailed understanding of many aspects affecting a whole organism, such as the cellular basis of disease, treatment efficacy and potential toxicity of treatments.

The inventive method employs a "systems biology" approach in high density format to predicting hepatotoxicity responses resulting from exposure to the test substance. The method is based on integrating cell-based assays of multiple components of a hepatocyte cell system to generate cellular systems biology response profiles that are predictive of higher level cell and cell system and liver functions and responses. Embodiments of the inventive method are presented in a flow chart in Figures IA and IB. For building such a database or knowledgebase, the cellular systems biology response profile of a reference substance is determined and added to the database (Figure IA).

For assessing a test substance, the cellular systems biology response profile of the test substance is compared to a database (or knowledgebase) of cellular systems biology response profiles for reference substances with known biological systems effects (Figure 1 B).

The inventive method can be conducted using competent, liver-derived cells comprising hepatocytes to be treated with the test or reference substance. In a particular embodiment, the hepatocytes have metabolically active cytochrome P450. The hepatocytes within the battery to be tested can be from a single cell type or multiple cell types. The use of multiple cell types can, however, more broadly indicate tissue associated responses. Cell types can include any mammalian or non- mammalian source material containing intact, living hepatocytes that function wholly or partially with differentiated hepatocyte functions. The source material can include but is not limited to: specific primary hepatocytes (e.g., isolated by standard enzymatic-dispersal, ex-vivo or other outgrowth methods), intact, ex-vivo functional liver sections (e.g., liver tissue) or host organs containing hepatocytes (i.e., spleen) (e.g., collected by mechanical excising); hepatocytes passaged and grown in culture derived from hepatocellular sources or progenitor sources (i.e., stem hepatocytes), and any cell genetically engineered to express one or more hepatocyte cell functions. Furthermore, the hepatocytes or hepatocellular source materials can be maintained in 2D and 3D culture on solid or flexible substrates with specialized coating (e.g. matrigel, collagen sandwich) or encapsulated using synthetic or natural proteins, fibers or other substrates intended to support hepatocellular functions or provide mechanical support. Finally, the hepatocytes within a battery can contain non- hepatic cells that are normally associated with liver such as Kupffer cells and other inflammatory cells, endothelial cells, stellate cells, bile duct epithelial cells, fibroblasts and liver neuronal cells.

Such cellular materials can be primary cultures or established hepatocellular lines (e.g., HepG2), as desired, and are commercially available from a variety of sources (e.g., Cambrex, CellzDirect, In Vitro Technologies, Xenotech, Zivic Laboratories). The hepatocytes or hepatocellular derived cells within the battery can be selected for one type or a mixture of cell types, as desired.

The hepatocytes can optionally contain one or more hepatocyte specific reporters and/or manipulations. In some embodiments, each hepatocyte can contain a unique combination of reporters and/or manipulations. In other embodiments, populations of hepatocytes contain unique combinations of reporters and/or manipulations. The hepatocytes should contain a number of reporters and/or manipulations suitable to approximate a biological system. Typically, the hepatocytes contain a unique combination of at least 5 or more (such as, for example, at least about 6 or more, or at least about 7 or more, at least about 8 or more, at least about 9 or more, at least about 10 or more, at least about 1 1 or more, at least about 12 or more, at least about 13 or more, at least about 14 or more, or at least about 15 or more) unique combinations of reporters and/or manipulations.

"Cellular systems biology" (also referred to herein as "CSB"), is the investigation of the integrated and interacting networks of genes, proteins, and metabolites that are responsible for normal and abnormal cell functions. Thus, a "cellular systems biology profile" is a systemic characterization of the interactions, relationships, and/or state of the constituents of cells as indicated by at least about five or more biomarkers that give rise to the cellular systems biology features that are used to construct the profile. The interrelationships within a cellular systems biology profile are defined, for example, either arithmetically (e.g., ratios, sums, or differences between cellular systems biology feature values) or statistically (e.g., hierarchical clustering methods or principal component analyses of combinations of cellular systems biology feature values).

Cellular systems biology harnesses technologies such as the higher throughput capacity of automated microscopy technologies while avoiding the expense and potential confounding species related problems (e.g., worms, flies, fish, rodents, etc.) associated with traditional organism-based systems biology. A cellular systems biology profile is a systemic characterization of cells in the context defined as the study of the living cell, the basic "unit of life"; an integrated and interacting network of genes, proteins and a myriad of metabolic reactions that give rise to function. Thus, a "cellular systems biology profile" is a systemic characterization of the interactions, relationships, and/or state of the constituents of cells as indicated by at least about five or more biomarkers that give rise to the cellular systems biology features that are used to construct the profile. The interrelationships within a cellular systems biology profile are defined, for example, either arithmetically (e.g., ratios, sums, or differences between cellular systems biology feature values) or statistically (e.g., hierarchical clustering methods or principal component analyses of combinations of cellular systems biology feature values).

A "cellular systems biology response profile" (also referred to herein as a "response profile") is the cellular systems biology profile that is the result (e.g., response) of a cell or cells to treatment with an agent, substance, environmental condition, etc. as described in more detail herein. The response profile can identify particular cellular functions (e.g., as described more fully below, one, two, three, four, five, six, seven, eight, nine, ten, or more) of any of the following: toxic responses, apoptosis, cell proliferation, stress pathway activation, organelle function, morphological changes, drug metabolism activity, and the like) that are affected by the treatment. As used herein, a "biomarker" is a cellular constituent and/or activity (e.g., protein or other macromolecules, organelles, ions, metabolites, etc.) that can be specifically "labeled" e.g., with a reporter or a fluorescence based reagent (fluorescently labeled antibodies, fluorescently labeled peptides, fluorescently labeled polypeptides, fluorescent protein biosensors, fluorescently labeled aptamers, fluorescently labeled nucleic acid probes, fluorescently labeled chemicals, and fluorescent chemicals). In one embodiment of the invention, a panel of fluorescently labeled reagents that detect at least about five different biomarkers is used. In another embodiment, the panel of fluorescently labeled reagents detects at least about six, at least about seven, at least about eight, at least about nine, at least about ten, at least about eleven, at least about twelve, at least about thirteen, at least about fourteen, or at least about fifteen or more different biomarkers. Each fluorescently labeled reagent can be identified by its particular fluorescence characteristics (e.g., wavelength for excitation and/or emission, intensity, fluorescence anisotropy, fluorescence lifetime, and the like). Thus, two or more fluorescently labeled reagents or biomarkers can be distinctly labeled and thus they can be distinguished from each other. The detection of a biomarker in one or more cells is a read-out of one or more features of the cells or tissue. As used herein, a "feature" (also referred to herein as a "cellular feature") is a measurement (e.g., an image-based measurement) or series of measurements of a particular biomarker that can include measurements of, inter alia, morphometry, intensity, localization, and ratios or differences of the biomarker, that can indicate a biological function or activity of the hepatocyte. Biological functions or activities indicated by biomarkers include, but are not limited to: protein posttranslational modifications such as phosphorylation, proteolytic cleavage, methylation, myristoylation, and attachment of carbohydrates; translocations of ions, metabolites, and macromolecules between compartments within or between cells; changes in the structure and activity of organelles; and alterations in the expression levels of macromolecules such as coding and non- coding RNAs and proteins, morphology, state of differentiation, and the like. A single biomarker can provide a read-out of more than one feature. For example, Hoechst dye can be used to detect DNA (e.g., a biomarker), and a number of features of the cells (e.g., nucleus size, cell cycle stage, number of nuclei, presence of apoptotic nuclei, etc.). In the context of the inventive method, a "reporter" is a fluorescent or luminescent molecule, such as a physiological indicator, a label, a protein, a biosensor, etc. The reporter can be a protein or non-proteinaceous. Where a reporter is proteinaceous, however, the hepatocytes can express one or more of the reporter molecules. Alternatively or additionally, one or more of the reporter molecules can be delivered into the cell, e.g., by attaching a protein sequence tag facilitating importation across the plasma membrane. In embodiments where the hepatocytes are fixed prior to imaging, a reporter can be provided by standard labeling technology. Examples of labels that are suitable reporters for use in the context of the inventive method include, for example, probes available to label sub-cellular compartments, localize proteins, label membranes, respond to membrane potentials, sense the local chemical environment, read out molecular mobility, respond to hepatocellular metabolic and conjugation capabilities and provide many other measurements (see, e.g., Waggoner, A., "Fluorescence probes for analysis of cell structure, function and health by flow and imaging cytometry.," in Applications of Fluorescence in the Biomedical Sciences, D. Taylor, et al., Editors. 1986, Alan R. Liss, Inc.: New York. p. 3-28, herein incorporated by reference in its entirety). Coupled with antibodies, immunofluorescence labeling provides an easy method for detecting and localizing proteins, hepatocyte specific proteins (e.g., albumin) protein variants such as phosphorylated proteins or phospholipids. Hepatocytes or cells of hepatic origin also can be engineered to express proteins tagged with any of the color variants of fluorescent proteins (Chalfie et al., Science, 1994. 263(5148): p. 802-5; Chudakov, et al. Trends Biotechnol, 2005. 23(12): p. 605-13), and these fluorescent proteins can be further engineered to create biosensors, indicators of specific cellular functions (see, e.g., Conway et al., Receptors Channels, 2002. 8(5- 6): p. 331-41 ; Umezawa, et al., Biosens Bioelectron, 2005. 20(12): p. 2504-1 1 ; Giuliano et al., Trends Biotechnol, 1998. 16(3): p. 135-40; Giuliano et al., Curr Opin Cell Biol, 1995. 7(1): p. 4-12). Biosensors can detect one or more protein-protein interactions in hepatocytes (see, e.g., PCT/US2005/027919, published as WO2006/017751). An example of a toxicologically significant, simple protein- protein interaction is keap-1 , a cytoplasmic protein and nfr2, a nuclear transcription regulator. Under normal conditions, the genes responsible for antioxidant activity are not expressed due to the binding between Keap- 1 protein and nrf2 within the cytoplasm of cells. When appropriately stressed, the transcriptional regulator nfr2 is released from keap-1 and translocates to the nucleus of the cell where it induces expression of antioxidant stress proteins and phase 2-detoxifying enzymes. Thus, appropriately labeled biosensors can be used to detect changes in protein-protein interactions, such as between keap-1 and nfr2.

A variety of labels can be combined in a single sample preparation to provide for the measurement of many features in each individual hepatocyte in a population, as well as in the population as a whole (Zhang et al., Cell, 2004. 1 19(1): p. 137-44; Taylor et al., Drug Discov. Today, 2005. 2(2): p. 149-154). Quantum dots, with their single excitation wavelength and narrow emission bands, provide the potential for even higher degrees of multiplexing within an assay (Michalet, et al., Science, 2005. 307(5709): p. 538-44). In addition to the rainbow of fluorescent probes, a number of bioluminescent and chemiluminescent reagents can be effectively used in cell based assays (Hemmila et al., J Fluoresc, 2005, 15(4): p. 529-42; Roda et al., Trends Biotechnol, 2004. 22(6): p. 295-303).

The hepatocytes can be plated on substrates such as microplates, microscope slides or other labware typically used for cell based assays. In addition, hepatocytes can be maintained in flexible support matrices such as polymer foams or gels and hydrogels used for 3D cell culturing. Generally, such labware and flexible supports are transparent to facilitate subsequent imaging analysis. Multiwell microplates are preferred as they facilitate multiple iterative assays to be conducted simultaneously and can be readily handled using automated equipment. Multiwell plates are commercially available and can be 8 well, 12 well, 96 well, 384 well, 1536 well, etc. The hepatocytes can be plated at any desired density to facilitate subsequent imaging analysis. For higher density multiwell microplates, several hundred to several thousand hepatocytes can be introduced into each well (e.g., 200-30,000 cells per 40 μl well).

In the context of the inventive method, a "manipulation" is a treatment of one or more hepatocytes to affect a functional response (or change) in the cell.

Hepatocytes can be manipulated by exposure to or contact with chemical, biological, environmental, or genetic treatments. These treatments can be used to alter the activity of cellular ions, metabolites, macromolecules, and organelles, which, in turn, effect phenotypic changes that can be further altered by treatment with additional substances. Examples of manipulations using standard techniques are known to the skilled artisan and include expression or heightened expression of a protein, knockdown of the expression of a protein, addition of a stimulus of known response or addition of a substance which induce or inhibit metabolic capacities, conjugation reactions, transporter functions, albumin protein synthesis or release, ammonia detoxification, carbohydrate and lipid regulation, and differentiation of hepatocytes or progenitor hepatocytes. In a particular embodiment, the manipulation of hepatocytes is the contacting of hepatocytes with a test or reference substance. For example, once plated, the hepatocytes manipulated by contacting with a test substance or a reference substance for a given period of time. In the context of the present invention, the "test substance" or "reference substance" is any substance for which a cellular systems biology response profile is to be obtained. For example, a manipulation can be contact with an infective biological article (parasite, bacteria, mycoplasma, virus, prion, ) small molecule (such as a "drug" or drug candidate), a biomolecule (such as a protein, polypeptide, nucleic acid (e.g., DNA, RNA, or hybrid polynucleotides)), or exposure to a condition e.g., an environmental condition (such as osmolality, pH, temperature or a combination thereof), electromagnetic radiation (e.g., light frequency, intensity, or duration), or other types of radiation (e.g., alpha, beta, gamma radiation, etc.) or any substances engineered for uniformity of size and shape (e.g., nanoparticles). A substance is treated as a test substance when its effect on the biological system in question is being probed. A substance is a reference substance when its effect on the biological system is known and where its effect on the battery of hepatocytes is desired to be added to the database or knowledgebase.

In performing the inventive method, a test or reference substance is exposed to the hepatocytes in a manner suitable for the test or reference substance to come into contact with the hepatocytes and interact with the hepatocytes. Typically, where the test or reference substance is a molecule or infective biological article, it can be introduced into the location of the hepatocytes (e.g., a well of a culture plate into which the hepatocytes are placed). The molecule or biological article then can interact with the cell at its outer surface or permeate the cell and interact with its internal workings. Other types of test or reference substances (e.g., temperature, radiation, etc.) are exposed to the hepatocytes in a manner suitable to the type of substance. The hepatocytes are incubated with the test or reference substance for a suitable time, which can vary from one or a few minutes, to several minutes, several hours, to several days. For example, the length of time can be selected based on whether immediate or chronic activity is desired. In one embodiment, the hepatocytes are incubated with the test or reference substance for 1 minute, 3 minutes, 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 8 hours, 10 hours, 12 hours, 16 hours, 20 hours, 24 hours, 28 hours, 32 hours, 36 hours, 48 hours and/or 72 hours.

In alternative embodiments, iterative batteries of hepatocytes (i.e., similar batteries) can be treated in parallel employing differing test substance or reference substance concentrations so that a cellular systems biology response profile can be constructed for each concentration. For example, 6-10 point log concentration series can be employed for compounds ranging in concentrations from about 1 nM or less to about 1 mM or greater. Similarly, different batteries of hepatocytes (e.g., having a different set of reporters or manipulations) can be exposed to the test substance. Employing iterative batteries of either different cell type and/or concentration can thus be conducted in parallel (e.g., in different wells of the same multi-well plate; in different wells of a different multi-well plate) and analyzed concurrently or in parallel. Also, negative and positive control hepatocytes (e.g., untreated wells or wells treated with a substance with a known activity) can be assayed along with the test substance or reference substance(s). After the test or reference substance is exposed to the hepatocytes, cellular features are measured. For example, in one embodiment, images of the hepatocytes can be acquired. Where the hepatocytes contain one or more reporters, images are obtained using frequencies (channels) appropriate for each of the fluorescent or luminescent reporters to be imaged. An example of such multiplex images is presented in Figure 2. Additionally or alternatively, the hepatocytes can be stained with dyes, fluorescent or luminescent labels (e.g., antibodies, ligands, etc.) that bind to desired proteins or cellular structures, and then imaged at frequencies (channels) appropriate for each of the dyes, fluorescent or luminescent labels to be imaged. Thus, in one embodiment, the hepatocytes are imaged with at least one optical mode to produce a first set of data. Imaging can be performed using any suitable means, for example, wide field microscopy or confocal microscopy. In one embodiment, at least one optical mode is fluorescence light microscopy. Data that are produced from imaging can be visual or digital. In one embodiment, the set of data are digital data.

The images of the hepatocytes are analyzed to measure or detect biomarkers, which are selected to be indicative of the functional classes appropriate to the property (such as toxicity, clinical pathology, histopathology, etc.) to be assayed. Thus, the reporters (labels, dyes, etc.) can be selected to target (e.g., bind to) biomarkers or features appropriate for assaying classes of cellular function. Within each of these cellular function classes, one or more assays are used to measure one or more of the biomarkers or features as an indication of a response in that assay functional class. In some embodiments, a single biomarker or reporter corresponds to a single feature. In other embodiments, a biomarker or reporter can be used to assess more than one feature (multiple features).

As described herein, cellular features in at least two cellular functional classes are measured to produce a response profile. In a particular embodiment, at least one cellular functional class is phospholipidosis or steatosis. Any suitable cellular functional classes can be selected, depending on the aim of the assay. The number of cellular functional classes selected for assaying can be one, two or more, depending on the number needed to produce a response profile, as will be appreciated by the skilled artisan. Examples of biomarkers, features and function classes suitable for assessing hepatotoxicity are presented in Example 1. Features include nuclear size, shape and location as indices of cell cycle or state of cell health; measurements of metabolic capabilities (phase I and Phase II metabolism reactions), detoxification capabilities (urea biosynthesis), carbohydrate regulation (glycogen biosynthesis), measurements of fat (e.g., triglyceride) storage as indicators of steatosis, measurements of lysosomal number, size, shape, location as indices of phospholipidosis or other abnormal lysosomal function; measurements of mitochondria number, size, shape and locations as indices of mitochondrial dysregulation or hepatocellular health; and measurements of peroxisome number, size, shape, location as indices of peroxisomal proliferation and other dysregulation of peroxisomal function. In a preferred embodiment, the hepatocellular biomarkers measure features of two or more functional response classes selected from cell proliferation, metabolic capabilities, detoxification capabilities, lipid and carbohydrate regulation, stress pathways, organelle function including but not limited to indices of phospholipidosis and peroxisomal proliferation, cell cycle state, morphology, apoptosis, DNA damage, metabolism, mitochondrial function, cell differentiation and cell-cell or cell-non-cellular compartment interaction. In another preferred embodiment, the hepatocellular biomarkers measure features of two or more functional response classes selected from cell proliferation, cell cycle, apoptosis, morphology, cytoskeletal perturbations, mitochondrial function, stress kinase activation, DNA damage, and cell-cell or cell-non-cellular compartment interaction. In a preferred embodiment, at least one functional response class is steatosis or phospholipidosis, or a combination thereof. Biomarkers (e.g., triglycerides, DGAT, MGAT, and combinations thereof) can measure features such as increased fat storage as tryglycerides, regulation of enzymatic processes of lipid regulation, which indicate steatosis. Biomarkers (e.g., LAMPl) can measure features such as increases in lysosomal size or increased lysosomal specific proteins, which indicate phospholipidosis.

Features indicating hepatocyte proliferation include nuclear count, cell count, total cell mass, total DNA, the phosphorylation state of cell cycle regulatory proteins, or the post-translational modification state of any protein involved in cell growth or division. Features indicating stress pathway activation include transcription factor activation (e.g., c-jun, NRF2, NF-B, Pl , ATF2, MSKl , CREB, or NFAT), or kinase activation (e.g., p38, INK, ERK, RSK90 or MEK). Features indicating organelle function include cytoskeletal organization, mitochondrial mass or membrane potential, peroxisome mass, golgi organization, lysosomal mass or plasma membrane permeability. Features indicating cell cycle state include DNA content, Rb phosphorylation, cyclin Bl (CDKl) biosynthesis, cyclin Dl (CDK4) biosynthesis, cyclin E (CDK2 biosynthesis and histone H3 phosphorylation state. Features indicating morphology include motility, cell spreading, adhesion, ruffling, blebbing or colony formation. Features indicating apoptosis include nuclear size and shape, DNA content, gluthatione content, measure of reactive oxygen species, caspase activation, cytochrome C release, PARP cleavage, Bax translocation and degradation. Features indicating DNA damage include, repair protein (APE) expression, GADD 153 induction, tumor suppressor p53 activation, Rb expression, oxidative activity (8-oxoguanine), or transcription activity (Octl). Features indicating metabolism and metabolic activity include glutathione content, reactive oxygen species, cAMP concentration, P-glycoprotein activity, CYP450 induction/inhibition, or the time-dependent clearance or concentration of an added substance. Features indicating signal transduction include Ca++ ion concentration (e.g., intracellular Ca++ ion concentration), pH, expression of a protein, activation of a protein, modification of a protein, translocation of a protein, or interaction between proteins known to be associated with a specific pathway. Features indicating cell differentiation include a tissue specific protein or exhibiting a tissue specific morphology such as glucagon receptor or cytokeratin 8,18 expression. Features indicating cell-cell interactions include concentration of tight junction proteins at a cell-cell interface, or transfer of material from one cell to another or into a non-cellular compartment such as reformed bile canalicular spaces.

Further features indicating metabolic capabilities include oxidative and conjugation metabolism, ureagenesis, lipid storage, glycogenesis, gylcogenolysis and albumin synthesis. Preferred features include microtubule stability, microfilament stability, c-jun phosphorylation state, mitochondrial mass, mitochondrial membrane potential, cytochrome C release, lysosomal mass, peroxisomal mass, nuclear size, cell cycle arrest, DNA degradation, and cell loss. The imaging used to assay the desired hepatocellular biomarkers can be conducted using fixed (e.g., chemically fixed) or live cells. For live cell assays, labeling reagents (reporters) are optionally added before the plate (or other substrate) is scanned or read. Fixation and labeling (or staining) with reporters such as antibodies, dyes, etc. is routine and can be automated, allowing efficient processing of assays. For fixed cell assays, spatial information is acquired, but only at one time point. However, where iterative assays are conducted in parallel, it is possible to fix hepatocytes in separate wells at desired time intervals (e.g., every second, every minute, etc.) to facilitate analysis of like populations of hepatocytes over time. By contrast, live cell assays permit an array of living hepatocytes containing the desired to be imaged over time, as well as space. However, environmental control of the hepatocytes (e.g., temperature, humidity, and carbon dioxide) is required during measurement, since the physiological health of the hepatocytes should be maintained for multiple luminescence or fluorescence measurements over time. For either live or fixed hepatocyte assays, scanning of the hepatocytes (or of separate subpopulations of the hepatocytes) can be repeated multiple times to facilitate analysis at each time point to capture a kinetic response to the test or reference substance.

Acquiring images of the hepatocytes and analysis can be accomplished by standard methods and equipment (e.g., Schroeder et al., J. Biomol. Screen, 1(2), 75- 80 (1996); Taylor et al., Toxicol. Pathol, 22(2), 145-59 (1994)), such as High Content Screening (HCS) (e.g., Giuliano et al., J Biomol Screen, 1997. 2(4): p. 249- 259) and high throughput cell analysis, automated microscope, or other detector. For example, an instrument is used to scan one or more optical fields in each sample or microplate well, thereby collecting one or more channels of fluorescence for each optical field. The multiwavelength images allow a panel of assays to be multiplexed in a single preparation, but assays can also be run across multiple preparations, and the feature measurements combined into a single activity profile. The extraction of biomarkers can be accomplished during image acquisition, or the images can be acquired and processed later. Suitable instruments include those for analysis of cell population responses on a whole plate at once, such as the FLIPR (Molecular Devices, Sunnyvale, CA) or FDSS 6000 (Hamamatsu City, Japan), as well as instrumentation for well-by-well and cell-by-cell analysis, such as the ArrayScan® HCS reader (Cellomics, Pittsburgh, PA); fixed endpoint and kinetic cell-based assays; image analysis algorithms that generate the primary hepatocyte response data; and data analysis tools for extracting derived features such as kinetic parameters, EC50, IC50, and population response distributions from the measurements. The assays can include combinations of HCS assays where individual hepatocytes are measured, along with higher throughput assays where the population of hepatocytes in a well is analyzed as a whole, either at a single time point, or at multiple time points to measure a kinetic response. For kinetic assays, multiple features can be extracted from the kinetic curve to create additional derived features. For example, features such as delay to peak, peak intensity, half time of decay, slope, and others can be derived from kinetic curves. An algorithm can be used to extract information from the images to produce outputs of different hepatocellular biomarkers. Typically, such algorithms convert raw image data to assay data points. Those skilled in the art of imaging and cell analysis will recognize that many such algorithms are readily available, and that there are many such hepatocellular processes that are amenable to image-based analysis of hepatocytes to measure hepatocellular functions. The algorithms, custom designed or encapsulated in the BioApplication software provided by the HCS vendors, produce multiple numerical feature values such as subcellular object intensities, shapes, and location for each cell within an optical field. For example, the vHCS™ Discovery Toolbox (Cellomics, Inc), Metamorph™ (Molecular Devices), software from GE Healthcare and other HCS and image analysis packages can be used to batch analyze images following acquisition. In such systems, the total number of hepatocytes measured per well is typically in the range of 100-1500, depending on the heterogeneity of the hepatocellular response and the sensitivity of the assay. Whole plate readers are typically supplied with software to identify well areas in the image and measure the total fluorescence in those areas for one or more time points.

Desirably, an algorithm is used to combine outputs of different biomarkers and assays from one or more or more assay plates or wells to produce a compound cellular systems biology response profile suitable for predicting higher level integrated functions. Features can be combined for cells or plates at different time points (e.g., where a physiological response occurs over a period of time). Alternatively, iterative experiments using different cell types in different wells or plates can be similarly combined. Preferably, the cellular systems biology response profile represents at least about 5 or more, at least about 6 or more, at least 7 or more, at least about 8 or more, or at least about 9 or more, at least about 10 or more, at least about 1 1 or more, at least about 12 or more, at least about 13 or more, at least about 14 or more, or at least about 15 or more features or functional classes. Each plate in the plate set can produce an image set consisting of images from one or more fields in each well, at each of the wavelengths and time points to be analyzed. Analysis of the image set produces a hepatocyte data set for each plate representing feature values over time and over concentration series for each field imaged on the plate. Finally, the hepatocyte data sets are processed and clustered to produce a set of cellular systems biology response profiles to be added to the database or knowledgebase, or to be used to search the database or knowledgebase to identify probable modes of physiological response. Figure 3 illustrates the overall sample flow while processing plates to produce profiles. Several methods can be used to generate the profiles from the feature measurements. For example, a parameter such as Kolmogorov-Smirnov (KS) values or average values as a measure of cell population shifts can be calculated for each feature measurement at each compound concentration for each compound, for single hepatocyte or a hepatocyte population which results in the generation of parameters dilution series. Such dilution series parameters then can be fitted, using a 4- parameter logistic fit and the resulting fitted data analyzed to calculate the AC50 (the concentration that leads to 50% maximal activity) of the response. The calculated AC50 values can, in turn, be converted to a log scale as a measure of test substance or reference substance activity. Cluster analysis then can be used to identify similarities in profiles as well as correlations between cellular systems responses.

Figure 2 illustrates one embodiment for producing the reference response curves to construct the database or knowledgebase. In accordance with this method, some assay data points generated by the algorithm can be analyzed to identify 2 or more subpopulation of cells. For example, the intensity of nuclear labeling is related to the amount of DNA in the nucleus. The nuclear intensity data from a population of cells in a well can be analyzed to identify cells with 2N, 4N and sub 2N amounts of DNA, the latter being an indication of DNA breakdown. The population of cells can thus be clustered into subpopulations based on 1 or more assay values, each subpopulation having a characteristic profile of those assay values, and therefore representing a class of hepatocellular response. In this simple case there are three subpopulations and therefore three features consisting of the percent of cells with 2N DNA, percent of cells with 4N DNA, and the percent of cells with sub2N DNA. Each of these features can be usefully included as a component of the compound profile. Combinations of any number of other assay features can also be used to classify hepatocytes into subpopulations. Some assay features, such as fraction cell loss, are characteristics of the whole population and therefore are used directly as a component in the compound profile. In all cases assay values for treated hepatocytes are compared with hepatocytes treated with vehicle (e.g. 0.4% DMSO) alone.

Compound profiles can be subjected to cluster analysis, principle component analysis and other pattern analysis methods to identify common cellular systems biology response profiles among a collection of compounds. These clusters of compounds represent a common class of response, and the profile of that response can be used to construct a classifier. The profiles of all the reference compounds along with the profiles of compound classes are stored in a Profile Database for additional pattern analysis. By way of example, Figure 3 illustrates one embodiment for producing the cellular systems biology response profiles involving evaluating a test compound in HeIa and A549 cells, and classification of the compound response. Similar cellular systems biology response profiles can be applied to hepatocytes. As with the analysis of the reference compounds, the assay features are further analyzed to identify cell subpopulation profiles which along with the direct assay features form the compound profiles which are stored in the database. The comparison of cellular systems biology profiles permits the identification of similarities, differences, or a combination thereof, between the cellular systems biology profiles being compared. Various methods can be used to compare two or more cellular systems biology profiles, such as by graphical display, cluster analysis, or statistical measure of correlation and combinations thereof. Thus, a measure of the similarity between the cellular systems biology response profile of a test compound and the cellular systems biology response profile in the database or knowledgebase can be used to calculate a probability that a test compound would produce the associated profile in vitro or in vivo. The metric used to compare compound profiles can be any of a number of standard metrics such as Euclidean distance, Pearson's correlation coefficient, Manhatten distance, or any other metric for comparing multiparameter profiles. Test compounds profiles are analyzed with reference compounds to identify linkage of the test compound with a particular cluster. There are a variety of linkage models as well as other classification approaches that can be used to classify test compounds relative to reference compound profiles in the database. As noted before, in one embodiment, the hepatocytes are metabolically active for cytochrome P450 (also referred to herein as "competent hepatocytes" or "metabolically competent hepatocytes"). Currently, about fifty-five human isoforms of cytochrome P450 have been discovered. However, nearly all of these isoforms are involved in endogenous substrate metabolism. Only about 5-9 of the cytochrome P450 isoforms have been shown to metabolize drugs. The known clinically relevant cytochromes which are involved in toxicity are CYP3A4, CYP2D6, CYP 1A2, CYP2C9, CYP2C19 and CYP2E1. With the exception of CYPl A2, which induces to higher levels in vitro as compared to in vivo, all others are down regulated in primary hepatocytes over time. As will be appreciated by the skilled artisan, primary hepatocytes can lose cytochrome P450 metabolic activity over time and/or depending on cell culture conditions in vitro. For example, as illustrated in Figure 1 IA, primary hepatocytes exhibit a time-dependent decrease in metabolic capacity. Three hours after plating hepatocytes cytochrome P450 metabolism is approximately 70% the level of freshly isolated cells, and falls to 30% and 20% after 16 and 24 hr, respectively. Furthermore, the hepatotoxic effects of some substances can be attributed to their metabolized form(s). For example, as illustrated in Figures 1 IB-C, the compound diclofenac is toxic only when hepatocytes bioactivate (e.g., metabolize) the parent compound to a 4'-OH- and 5- OH diclofenac derivative. Thus, for some applications, the hepatocyte feature values from each hepatocyte are dependent on the hepatocyte's manipulation (e.g., metabolism) of the test substance or compound. Thus, in one embodiment of the invention, when assaying test or reference substances for their toxic effects on cellular systems biology, it is useful to use competent hepatocytes that have the necessary cellular machinery intact (e.g., hepatocytes that have cytochrome P450 metabolic activity, e.g., at least one or more active P450 cytochromes selected from the group consisting of CYP3A4, CYP2D6, CYP 1A2, CYP2C9, CYP2C19 and CYP2E1), as opposed to cells which lack or have limited cytochrome P450 metabolic activity (e.g., HepG2 cells). In a preferred embodiment, a test substance is contacted with one or more hepatocytes having at least about 90%- 100% cytochrome P450 metabolic activity as compared to freshly isolated hepatocytes. In another embodiment, the hepatocytes have at least about 80-100%, at least about 70- 100%, at least about 60- 100%, at least about 50- 100%, at least about 40- 100%, at least about 30-100%, at least about 20-100%, at least about 10-100%, or ranges therein, cytochrome P450 metabolic activity as compared to freshly isolated hepatocytes. In one embodiment, a test substance is contacted with a primary hepatocyte within about 1 minute to about 1 hour, about 1-12 hours, about 1-10 hours, or about 3, 4, 5, 6, 7, 8, 9, 10, 1 1 or 12 hours after plating the hepatocytes in 2-D in vitro. In another embodiment, a test substance is contacted with a primary hepatocyte within about 0-120 hours, about 5 minutes to about 1 hour, about 1, 2, 3, 4, 5, 6, 9, 12, 15, 18, 21, 24, 30, 36, 48, 60, 72, 84, 96, 108, 120 hours after plating (e.g., using collagen gel overlay techniques) the hepatocytes in 3-D in vitro. In another embodiment of the invention, all the hepatocyte feature values from each hepatocyte can be combined to create a hepatocyte profile. Figure 4 illustrates some graphical display methods to display cellular responses that contribute to creating a cellular systems biology response profile. These graphical displays are also use to review multidimensional cellular responses. Cell feature maps, illustrated for HeLa and A549 cells (4A) are used to identify cellular functions that are associated with specific cellular systems biology response profiles. Knowledge of the cell physiology events that lead to apoptosis, as depicted here, can enhance the information in the output of a classifier, but is not necessarily required for the application of the method of this invention. Cell distribution maps (4B) depict the changes in the cellular response distributions, as the substance concentration is varied. These plots illustrate how the cells in a population can occupy discrete response classes, and move from class to class as substance concentration is varied. Cellular systems biology response profiles (4C) are used to quantify the variation in population response distributions through the application of the KS analysis. The percent occupation of each of these classes then becomes a population cellular systems biology response profile for that well. The population profiles from the reference compounds are linked to the profiles from the reference compounds and stored in the database or knowledgebase. The population profiles from the test compounds are compared with the population profiles of the reference compounds in the database and the probability of a match is calculated.

To quantify changes in the hepatocellular responses induced in a population of hepatocytes by treatment with reference or test substances, several different methods can be effectively used. Within a population of hepatocytes, many different individual cellular systems biology response profiles are possible, due to the heterogeneity in cellular responses (Elsasser, Proc Natl Acad Sci USA 1984; 81 (16):5126-9; Rubin H, Proc Natl Acad Sci USA 1984; 81 (16):5121-5). In one embodiment, the hepatocellular response distribution for each hepatocyte parameter in a well or on a slide can be compared with that of a control substance using a Kolmogorov-Smirnov (KS) goodness of fit analysis (KS value) (Giuliano et al., Assay Drug Dev Technol 2005; 3 (5):501-14). For example, to perform significance testing of substance dependent changes in multiplexed HCS-derived cell population distribution data, the one-dimensional KS test can be adapted to two dimensions as described by Peacock (Peacock, Monthly Notices of the Royal Astronomical Society 1983; 202:615-27) and further refined by Fasano and Franceschini (Fasano et al., Monthly Notices of the Royal Astronomical Society 1987; 225: 155-70.). The two dimensional cell population data distributions representing two physiological parameters from a multiplexed HCS assay obtained after treatment with a substance can be compared to the two dimensional cell population data distributions obtained from multiple wells of untreated hepatocytes. First, each distribution can be divided into quadrants defined by the median x and y axis values calculated from the untreated cell data distributions. The two dimensional KS value can then be found by ranging through all four quadrants to find the maximal difference between the fraction of hepatocytes in each treated quadrant and the fraction of hepatocytes in each corresponding untreated quadrant. The heterogeneity of cell population responses can also be analyzed with other statistical methods. Several other possible analysis algorithms or methods can be used to classify cellular systems biology response profiles based on the known properties of a training set of reference substances, including methods such as neural nets. KS cellular systems biology response profiles can be clustered by agglomerative clustering, to identify compounds with similar activities. Other methods in addition to KS analysis can be used to process data prior to clustering, and a variety of clustering algorithms can be usefully applied.

The practice of the inventive method also is aided through graphical analysis of cellular responses that contribute to a cellular systems biology response profile. Figures 4A-4C, additionally, illustrates some graphical display methods to display cellular responses that contribute to creating a cellular systems biology response profile. These graphical displays are also use to review multidimensional cellular responses. Cell feature maps are used to identify cellular functions that are associated with specific cellular systems biology response profiles. Knowledge of the cell physiology events that lead to apoptosis, as depicted here using various cell types, can enhance the information in the output of a classifier, but is not necessarily required for the application of the method of this invention. Cell distribution maps depict the changes in the cellular response distributions, as the substance concentration is varied. These plots illustrate how the cells in a population can occupy discrete response classes, and move from class to class as substance concentration is varied. Cellular systems biology response profiles are used to quantify the variation in population response distributions through the application of the KS analysis. Figures 5A-5C depict additional visualization tools used for cellular systems biology response profiles obtained from HCS analyses. For example, a data set showing the effect of 1 1 concentrations of laulimalide (LML) on the DNA content of MDA-MB-231 breast cells is presented using three visualization tools. Figure 5 A shows an array of cellular response data plots. Each plot shows the population distribution of cellular DNA content at every concentration (nM) of LML. Subtle changes in the shapes of the population distributions were easily seen with this approach, but trends across the entire range of concentrations were difficult to discern except by KS analysis that proved to be a more sensitive measure of the shift in an overall population response. A three-dimensional surface plot is depicted in Figure 5B. When viewed at the optimal angle with the appropriate color encoding, a stacked series of cell population distribution curves provided an ideal context in which a series of complex curves could be simultaneously viewed and analyzed. However, comparisons between multiple three-dimensional surface plots on two- dimensional palettes such as computer screens or paper were problematic due to the awkward shape of the plots and lack of visual alignment cues. Finally, Figure 5C presents a two dimensional contour plot or "Distribution Map" of the data. Color encoding of data point densities in Distribution Map can produce a unique approach for essentially projecting a three- dimensional surface plot onto a two-dimensional plane. For example, blue shades can encode the lowest population densities while shades of black and yellow can encode the highest population densities. Much of the detail provided by the three-dimensional surface plot was reproduced when the DNA content data were plotted as a Distribution Map. Furthermore, multiple Distribution Maps were easily arrayed for the simultaneous visualization of multiplexed HCS data sets. These and other visualization tools can readily be applied to hepatocyte profiling.

In another embodiment, the invention provides a set of protocols and software tools used to carry out the profiling. Another embodiment of the invention is a panel of reagents and protocols for generating cellular systems biology response profiles, either to create a knowledgebase, or to use with an existing knowledgebase and informatics software to profile substance physiological effects. Another embodiment of the invention is a database of physiological profiles. These could be provided as a product (i.e., a kit) to end users or used to perform profiling services for customers either with the inventive reagent panels and software or with the customer's own assays. Accordingly, the invention provides a kit comprising reagents and instructions for using the reagents in accordance with the inventive method. In one embodiment, the kit comprises one or more reagents and instructions for employing the reagents to assay a battery of hepatocytes in accordance with a protocol involving incubating a battery of hepatocytes with a test or reference substance; acquiring images of hepatocytes within the battery; analyzing the images to measure or detect biomarkers indicative of cellular functional classes; and creating a cellular systems biology response profile comprising at least 5, 6, 7, 8, 9, 10 or more of the biomarkers. The kit can further include instructions for comparing the cellular systems biology response profile of a test substance to a database of cellular systems biology response profiles for substances with known biological systems effects. The reagents can include hepatocytes or cells manipulated to function as hepatocytes (preserved in liquid nitrogen), one or more fluorescent or luminescent labels, labware such as multiwell plates, culture medium, and the like. Furthermore, the kit can include a database of cellular systems biology response profiles for substances with known biological systems effects (e.g., on electronic storage media). As an example of a kit, all the reagents specified in Table 5, 6 and 7 could be packaged in the appropriate amounts for the preparation of a standard number of assay plates, such as the 6 plates required to process 16 compounds as described in Example 1. The kit would normally include a protocol for sample preparation, as described in Example 1 , and optionally reference data values for compounds with known cellular systems biology response profiles. This data could be provided in electronic format on an included CD or DVD disk or other data storage medium, as well as via network access to a centralized database of compound profiles. The selection, testing and validation of such reagent combinations and protocols requires significant effort to avoid interferences and ensure reliable performance, and therefore results in unique combinations of reagents and methods that are difficult to reengineer, and enable multiplexed data acquisition used in profiling cellular activities. EXAMPLE 1 This example demonstrates an embodiment of the invention in which a panel of assay function classes is used to profile substance-produced hepatotoxicity. The function classes to be assayed for toxicity include stress pathways, mitochondrial function, cell cycle stage, morphology changes, apoptosis, nuclear alterations, phospholipidosis and peroxisomal proliferation. In one embodiment, the function classes to be assayed for toxicity are selected from the group consisting of mitochondrial function, apoptosis, nuclear alterations, phospholipidosis, steatosis and DNA damage. In a preferred embodiment, at least one function class assayed for toxicity is phospholipidosis or steatosis. In another preferred embodiment, at least two function classes are assayed for toxicity, wherein in at least one function class is phospholipidosis or steatosis. In another preferred embodiment, at least three function classes are assayed for toxicity, wherein in at least one function class is phospholipidosis or steatosis. In another preferred embodiment, at least four, five, six, or more function classes are assayed for toxicity, wherein in at least one function class is phospholipidosis or steatosis.

Some features that can be assayed in accordance with the inventive method to produce a knowledgebase or to assay a test compound are presented in the following

Table 1 and also in Figure 6.

Table 1

Within each of these assay function classes, one or more assays are selected to be used to measure one or more biomarkers as an indication of a response in that assay function class. The methods of this invention can be used to validate additional assays and functional classes which can be added to a profile to improve the sensitivity, specificity or range of applicability of a specific embodiment of this invention.

One embodiment employs a panel of assays with one from each of these functional classes. These assays are used first to build a predictive toxicology knowledgebase, and then to generate profiles of test compounds, to compare with the classes in the knowledgebase, and thereby to predict toxic affects of the test substances. Another embodiment of the invention uses all the assays listed in Figure 6 to produce a more extensive profile, and then uses a statistical method such as principle components analysis to identify the features with the highest predictive power for a selected profile of toxicology parameters.

Reagents for assaying these cellular function classes and features are known to those of skill in the art and commercially available. Examples are presented in table 2: Table 2

This example pertains to a multiplexed cell systems biology toxicity HCS profiling panel. It describes the performance of the hepatotoxicity profile which is designed to measure 8 cellular functions as cytotoxicity parameters using a two plate assay as shown in Table 3 and 4A. Additional hepatocyte features for new panels are shown in Table 4B. The example also demonstrates how the resulting response data can be analyzed and interpreted.

Assay and Reagent Specifications. The Hepatotoxicity Profile Plate 1 contains the labels and features as indicated in Table 5, and the Hepatotoxicity Profile Plate 2 contains the labels and features as indicated in Table 6. The antibody and fluorescent indicators of cell physiology reagent specifications for Cytotox Profile Plate 1 are contained in Table 5 whereas the antibody and fluorescent indicators of cell physiology reagent specifications for Cytotox Profile Plate 2 are contained in Table 6. Finally, the assay buffer specifications for both Cytotox Profile Plates 1 and 2 are contained in Table 7. Table 3 - CellCipher™ Hepatotoxicity Profile: Multiplex Plate 1

Table 4A - CellCipher™ Hepatotoxicity Profile: Multiplex Plate 2

Table 4B Potential Multiplex Cell Features

Table 5 - Reagent Requirements for Multiplex Plate 1. Table 6 - Reagent Requirements for Multiplex Plate 2.

Table 7 - Assay Buffer Requirements for Multiplex Plates 1 and 2. Second wash after Hanks Balanced Hyclone 38.4 ml secondary antibody Salt Solution with SH30030.03 labeling Phenol Red - Ix (AQL25083)

Hepatocyte cell handling and plating procedure. For the hepatotoxicity profile, thin bottom 384-well microtiter plates were used that are compatible with the high numerical aperture optics available on most HCS readers. Falcon #3962 plates or Greiner #781091 have the largest surface area and are suitable for HCS. These microtiter plates were coated with collagen I coating, by rinsing the microtiter plates with collagen I (Sigma C9791) solubilized in 1 : 1000 glacial acetic acid (Sigma A6283) at a concentration of 0.25 mg/ml and letting them air dry in a sterile hood produces a substrate for optimal attachment and spreading of HepG2 35 hepatocytes. The solubilized collagen I was added to dry 384-well microtiter plates (16 μl/well), the plates were incubated at room temperature for 5 min, the solution was then shaken out of the wells, and the microtiter plate left to air dry in a sterile hood.

Hepatocytes are isolated from an appropriate sized male rat into plating media according to standard isolation methods. Hepatocytes were plated at a density of 10,000 hepatocytes/well into 384 well microtiter plates. After each microtiter plate was filled, it was placed onto a stable bench top to settle for 30 min. After 30 min settling at room temperature the microtiter plates were placed into the 37 C 5% CO2 incubator. After 3 - 4 hr of additional attachment, the plating media was decanted and replaced with serum-free culture media.

Compound preparation and treatment of hepatocytes. Standard compounds were prepared in DMSO (Sigma D8418) at the following concentrations: CCCP - Sigma C2759 20 mM; Tunicaymcin - Sigma T789, 1OmM; Chloroquine - Sigma C6626 33.3 mM; and bupivacaine - Sigma B5274, 16 mM. The test compounds were prepared in DMSO at concentrations up to 50 mM and stored at -20 C. All compound dilutions were performed in DMSO prior to further dilution in HBSS with phenol red. The maximal final concentrations of the standard compounds are as follows: Bupivicaine - 160 μM (200 μl of a 5x solution [50 μM] for each 3 plate set); Chloroquine - 333 μM (200 μl of a 5x solution [50 μM] for each 3 plate set); CCCP - 200 μM (200 μl of a 5x solution [500 μM] for each 3 plate set); and tunicamycin - 150 μM (200 μl of a 5x solution [5 μM] for each 3 plate set).

A 10-point dilution set was made for each compound by diluting slightly more than

3- fold (square root of 10) on each step. Compound additions were made by transferring 10 μl of 5x compound stocks. For all conditions, DMSO was used at a final concentration of 1 % in each well after compound addition (50 μl total volume).

Labeling of Hepatotoxicity Profiling Multiplex Plate 2 with M itoTracker

Red before fixation. First, a 400 nM MitoTracker Red stock solution was prepared in warmed medium. To each well of the microplate, 50 μl of 2x Mitotracker Red solution was added to each well for a final concentration of 200 nM. The microplate was incubated for 45 min at 37 C in CO2 incubator before proceeding to the cell fixation protocol.

Labeling of Hepatotoxicity Profiling Multiplex Plate 3 with Red before fixation. A 42 uM Lysotracker. Red stock solution was prepared in warmed medium. To each well of the microplate, 50 μl of 2x Lysotracker Red solution was added to each well for a final concentration of 1 uM. The microplate was incubated for 45 min at 37 C in CO2 incubator before proceeding with the cell fixation protocol.

Mitotracker Red Plate Cell fixation protocol. A 2x fixative was prepared containing formaldehyde (Sigma, 252549, 36% stock) at a concentration of 7.2% in

HBSS with phenol red. To each well in the microplate, 50 μl fixative was added.

The microplates were incubated for 30 min at room temp before being washed with

HBSS (100 μl/well) which was immediately removed.

Lysotracker Red Plate Cell fixation protocol. A 1 x fixative was prepared containing formaldehyde (Sigma, 252549, 36% stock) at a concentration of 3.6% in

HBSS with phenol red. The Lysotracker Red plate was removed from the incubator and decanted. To each well in the microplate, 50 μl fixative was added. The microplates were incubated for 30 min at room temp before being washed with

HBSS (100 μl/well) which was immediately removed. Cell permeabilization and labeling protocol. Hepatocytes were permeabilized by incubating with 0.5% (v/v) Triton X-100 (Sigma T9284) for 5 min at room temperature (16 μl/well). The microplates were washed with HBSS (100 μl/well) which was immediately removed. Hepatocytes in Multiplex Plate 1 were incubated with the primary antibody reagents as listed in Table 3 for 1 h at room temperature (20 μl/well). Hepatocytes in Multiplex Plate 2 were incubated with lipidtox deep red reagent as listed in Table 4 for 1 hr at room temperature (30 μl/well). The microplates were washed with HBSS (100 μl/well) which was immediately removed. Hepatocytes in Multiplex Plate 1 were incubated with the secondary antibody reagents and Hoechst 33342 as listed in Table 3 for 1 h at room temperature (10 μl/well). Hepatocytes in Multiplex Plate 2 were washed once with HBSS (50 μl/well) leaving the wash in the wells. The plates were then sealed for HCS analysis.

Exemplary Standard plate layouts for CellCipher Hepatotoxicity Profiling Multiplex Plates. Exemplary standard plate layouts for Multiplex Plates 1 and 2 are depicted in Figure 7. Each microplate contained 24 DMSO control wells distributed in the corners. Each microplate contained 2 duplicate controls in 10- point concentration series. Each microplate also contained 16 duplicate test articles in 10-point concentration series.

Reading plates. Cell imaging of prepared microplates or slides was performed with an ArrayScan® HCS Reader using the Cellomics® BioApplication Software coupled to a Cellomics® Store database. Other HCS readers and applications, as well as other microscope imaging systems, coupled with the same or alternative image analysis packages, can be used to perform data acquisition and feature extraction. Briefly, the instrument was used to scan one or more optical fields in each sample or microplate well, collecting four channels of fluorescence for each optical field on each plate. Algorithms. The algorithms, encapsulated in the Cellomics BioApplication software produced multiple numerical feature values for each cell and for each well on each plate. Examples of biomarkers include subcellular object total and mean intensities, shape features such as perimeter to area and length width ratio, and location for each cell within an optical field. Well features are averaged or accumulated over the whole population of hepatocytes measured in the well and include cell count, mean nuclear size, mean nuclear intensity, total nuclear intensity, mean cytoplasmic/nuclear ratio and along with the standard deviation of each of these mean values. Contingent on the effect that the added chemical compounds had on the attachment of hepatocytes to the substrate, the total number of hepatocytes measured per well was typically in the range of 100-1500, depending on the heterogeneity of the cellular response and the sensitivity of the assay. The assay output parameters were used to measure the heptotoxicity parameters shown in Tables 1 and 2 at 2 time points, acute (30 min) and early (24 hour). For example, to calculate changes in nuclear morphology, the average nuclear intensity value for each cell was used. The measurement of c-jun phosphorylation was obtained using the average nuclear intensity of hepatocytes labeled with antibodies specific for cjun. The image features used to extract information on the biological functions are listed in Tables 3, 4A and 4B. Those skilled in the art of imaging and cell analysis will recognize that there are many such algorithms readily available, and that there are many such cellular processes that are amenable to image-based analysis of hepatocytes to measure cellular functions. Quantifying the Response values. To quantify overall changes in the cellular responses induced in a population of hepatocytes by treatment with reference or test molecules, the cellular response distribution for each cell parameter in a well was compared with that of control wells containing only DMSO using a non-parametric Kolmogorov-Smirnov (KS) goodness of fit analysis (KS value) (Giuliano et al., Assay Drug Dev Technol 2005; 3 (5):501-14).The KS analysis produced a single value for each well, and therefore, for each concentration. The doseresponse data were fit to a 4 parameter logistics model using XLfit (IDBS, Guildford, UK). The AC50 values from the fits to the entire concentration series' were converted to a log scale (log[IC50]). Examples of dose-response curve fits are illustrated for CCCP and paclitaxel in Figures 8A and 8B.

Clustering and Classification of Compound Responses. Figure 9 is a heat map of the response values for test compounds in HepG2 cells although the clustering and classification of compound responses can be applied to hepatocytes. The compound names are along the horizontal axis and the measured features are plotted on the vertical axis. The measured features are in 2 groups. Early toxicity assessment is made at 24 hours and Chronic at 48 hours of exposure. The gray level indicates the AC50 concentration, where white is mM and above, neutral gray is μM and black is nM and below. The compounds were clustered using a standard Euclidean distance metric. Those skilled in the art will recognize that many other metrics could also be used. The height of the dendrogram at the top indicates the degree of similarity between profiles, where shorter branches indicate that profiles are more similar. Three clusters of compounds are indicated by rectangles A-C. The 3 compounds in rectangle A have no activity in any of the assays, and thereby have a very high degree of similarity. The 2 compounds in cluster B, mevastatin and lovastatin have a moderate degree of activity (in the μM range) in many assays, have a very similar profile of activity across the assays, and in fact have very similar chemical structures. The 5 compounds in cluster C have a very high degree of activity (in the nM range) in many assays, and a varying degrees of similarity in their profiles. Even within this small data set, clustering on compound cellular systems biology response profiles can be used to identify compounds that are chemically similar, as well as biologically similar. In addition to the many methods of cluster analysis, those skilled in the art of data-mining will recognize that other statistical methods can be usefully applied to discover relationships in multidimensional data sets such as this. Figure 10 illustrates a Principle Components (PC) plot of this same data set. Principle components analysis (PCA) is well known in the art and results in a linear mapping of the data into a set of orthogonal components that maximize the variance. The large cluster near the middle of the plot are compounds for which there is little or no discrimination. However there are 2 significant clusters (A and B in Figure 10) of compounds that are clearly discriminated from the rest, but similar to each other with respect to the first 2 PCs. There are also 2 compounds (C and D in Figure 10), which are unique in this set with respect to the first 2 PCs. Several other compounds were also clearly discriminated in this plot. Analysis of the loadings of the first PC indicated that there was nearly equal contribution of many different assay features to the variance in the PC. The 10 most significant assays were: chronic oxidative stress, chromatin condensation, stress kinase activation, cell loss, DNA repair activity, nuclear size, and early stress kinase activation, oxidative stress, nuclear size, and cell loss. The PC loadings for these features ranged from 0.22-0.3 indicating that all contributed significantly to the discrimination of compounds by this profile. Analysis of loadings for other PCs indicates that even with this small library most of the assay features contributed significantly to discriminating the cellular modes of action for these compounds. The conclusion is that the breadth of assays in this profile provides an important tool for comparing compound activities and identifying common modes of action. These critical analyses can also to be applied to hepatocytes screens.

Materials and Methods for Overlay Cultures. Hepatocyte Overlay 3D Cell Cultures are known in the art (see, e.g., Ng et al., "Improved Hepatocyte Excretory Function by Immediate Presentation of Polarity Cues" Tissue Engineering, 2006, 12(8): 2181-2191, and Richert et al., "Evaluation of the effect of culture configuration on morphology, survival time, antioxidant status and metabolic capacities of cultured rat hepatocytes" Toxicol In Vitro, 2002; 16(1): 89-99). Briefly, hepatocytes are isolated from an appropriate sized male rat into plating media according to standard isolation methods. Hepatocytes were plated at a density of 16,000 - 18,000 hepatocytes/well into 384 well microtiter plates. After each microtiter plate was filled, it was placed onto a stable bench top to settle for 30 min. After 30 min settling at room temperature the microtiter plates were placed into the 37 C 5% CO2 incubator. After 3 - 8 hr of additional attachment, the plates are briefly cooled to 10 - 15 degrees by placing them on ice for 10 minutes. The plating media was decanted and replaced with 10 ul of 50% matrigel media cooled to 4 degrees. The plates are put on ice for an additional 5 minutes before the plates are centrifuged for 1 minute at 50 g in a centrifuge cooled to 10 degrees C. Following centrifugation the plates are placed in a 37 C 5% CO2 incubator for one hour to allow the overlay to gel (solidify). After gelling, 40 ul of hepatocyte cell culture media is added. The plates are incubated for 48 hr and then an additional 40 ul of hepatocyte culture media is added on top of the existing media. The plates are incubated for another 48 - 72 hr of culturing.

Compound preparation and treatment of hepatocytes. Troglitazone, chlorpromazine controls were prepared in DMSO (Sigma D8418) at the following concentrations: troglitazone 10 mM and chlorpromazine at 10 mM. All compound dilutions were performed in DMSO prior to further dilution in HBSS with phenol red. The maximal final concentrations of the standard compounds are as follows: troglitazone - 100 μM and chlorpromazine - 100 uM. A 10-point dilution set was made for each compound by diluting slightly more than 3-fold (square root of 10) on each step. Compound additions were made by transferring 10 μl of 5x compound stocks. For all conditions, DMSO was used at a final concentration of 1% in each well after compound addition (50 μl total volume).

Materials and Methods for Figures 1 IA-11C. Cytochrome P450 3A4 activity levels can be determined through various published and standard methods. See e.g., Promega P450-Glo 3A4 luminescent whole cell assay kit. Briefly, hepatocytes were plated down in 24 well collagen 1 coated plates at a density of 100,000 cells per 250 ul media. The luciferin-linked Cyp P450 3 A substrate reagent is added selected wells and allowed to incubate for 3 hrs. An aliquot of the media was withdrawn after three hrs and assayed by luminescence for luciferin released into the media. Additional wells of hepatocytes are assayed in the same manner but following a 3, 16 24 or 48 hr attachment and incubation period. In one experiment, Diclofenac is added to the hepatocytes after 3 hr attachment or 16 hr attachment and allowed to remain in solution with hepatocytes for 24 hr. After the drug exposure period the hepatocytes are fixed and processed for nuclear staining and VTI image data collection as seen in Figures 1 IA-11C. Metabolism dependent toxicity in isolated rat hepatocytes is demonstrated in Figures 1 IA-11C. Figure 1 IA is a graph showing time dependent decrease in metabolic capacity in hepatocytes. Three hours after plating Cytochrome P450 metabolism is approximately 70% the level of freshly isolated cells but falls to 30% and 20% after 16 or 24 hr, respectively. Figure 1 I B is a graph illustrating that the toxic product from diclofenac metabolism is required to produce overt cytotoxicity and is demonstrated as dose and time-dependent cell loss at 24 and 48 hr. However, no toxicity is evident after 72 hr exposure to a cell line that lacks metabolic capacity (HepG2 cells). Figure 1 1C is a graph illustrating the importance of timing compound exposure to metabolic activity is demonstrated in hepatocytes. When diclofenac is treated in hepatocytes 16 hr after plating, the toxicity is reduced as compared to those treated at 3 hr.

Labeling of Overlay Cultures Hepatotoxicity Profiling Multiplexed Plate 3. The overlay cultures are incubated with Hoechst for 1.5 hr prior to adding vehicle or compound for 30 minutes drug treatment. CMFDA is prepared as a 1OX concentrate (40 uM in HBSS) and added to achieve a final concentration of 4 uM. The overlays are incubated an additional 20 - 30 minutes and then imaged without fixation. Figures 12A-12C illustrate hepatocytes regaining polarized bile canalicular transport functions after 4 days in overlay cultures. Figure 12A is an image demonstrating normal transport in control cells and showing increased fluorescence in bile canalicular spaces formed between adjacent hepatocytes. Figure 12B is an image showing that normal transport function can be inhibited by compounds such as troglitazone as shown by decreased fluorescence into bile canalicular spaces.

Figure 12C is a graph of image analysis processing that can be used to quantify the transport of fluorescent dye by normalizing the either the intensity or the area of fluorescence in-between adjacent hepatocytes to the total hepatocyte intensity or area, respectively. The use of the terms "a" and "an" and "the" and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The terms "comprising," "having," "including," and "containing" are to be construed as open- ended terms (i.e., meaning "including, but not limited to,") unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., "such as") provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

Preferred embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Variations of those preferred embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than as specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context. This application incorporates by reference International applications

PCT/US2007/01 1865, published as WO2007/136724; PCT/US2007/012406, published as WO2007/139895; PCT/US2007/023678, published as WO2008/060483; PCT/US2007/01217, published as WO2008/018905; PCT/US2005/027919, published as WO2006/017751 ; PCT/US2008/003401;and U.S. Provisional Patent Application No. 60/759,476, filed January 17, 2006, and U.S. Provisional Patent Application No. 60/846,006, filed September 20, 2006.

All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

While this invention has been particularly shown and described with references to example embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.

Claims

CLAIMSWhat is claimed is:

1. A method for predicting the biological systems effect of a test substance on hepatocytes comprising: a) contacting hepatocytes having metabolically active cytochrome P450 with the test substance; b) measuring six or more cellular features in at least two cellular functional classes, wherein at least one cellular functional class is phospholipidosis or steatosis, thereby producing a response profile of the hepatocytes contacted with the test substance; and c) comparing the response profile of the hepatocytes contacted with the test substance to a database comprising response profiles of known biological systems effects of one or more substances on hepatocytes, wherein if the response profile of the hepatocytes contacted with the test substance is the same as, or is similar to, a response profile in the database, then the test substance is predicted to have the same or similar biological systems effect as the substance that produced the known biological systems effect on hepatocytes in the database.,

2. The method of Claim 1 , wherein the known biological systems effect is a toxic biological systems effect.

3. The method of Claim 1, wherein the hepatocytes are primary hepatocytes, stem cell-derived hepatocytes, hepatocytes within a liver section, hepatocyte explant culture, or a hepatocyte-derived cell line.

4. The method of Claim 1 , wherein the hepatocytes are labeled with a panel of fluorescently labeled reagents, wherein each fluorescently labeled reagent is specific for a biomarker, the panel of fluorescently labeled reagents detects at least five different biomarkers, and the detection of a biomarker is a read-out of one or more features.

5. The method of Claim 1 , wherein the hepatocytes express one or more fluorescent or luminescent reporters.

6. The method of Claim 1, wherein one or more fluorescent or luminescent reporters is introduced into the hepatocytes.

7. The method of Claim 1, wherein the hepatocytes are in a mixed population of cell types.

8. The method of Claim 1, wherein at least one cellular feature indicates at least one cellular functional class selected from the group consisting of cell proliferation, stress pathways, oxidative stress, stress kinase activation, DNA damage, lipid metabolism, carbohydrate regulation, metabolic activation including Phase I and Phase II reactions, Cytochrome P-450 induction or inhibition, ammonia detoxification, mitochondrial function, peroxisome proliferation, organelle function, cell cycle state, morphology, apoptosis, DNA damage, metabolism, signal transduction, cell differentiation, cell-cell interaction and cell to non-cellular compartment.

9. The method of Claim 8, wherein the at least one cellular feature indicating cell proliferation is selected from the group consisting of nuclear count, cell count, total cell mass, total DNA, the phosphorylation state of cell cycle regulatory proteins, and post- translational modification state of any protein involved in cell growth or division.

10. The method of Claim 8, wherein the at least one cellular feature indicating stress pathway activation is transcription factor activation of a transcription factor selected from NRF2, NF-κB, Pl, ATF2, MSKl , CREB, and NFAT, or kinase activation of p38, JNK, ERK, RSK90 and MEK, or a combination thereof.

1 1. The method of Claim 8, wherein at least one cellular feature indicating organelle function is selected from the group consisting of cytoskeletal organization, mitochondrial mass, mitochondial membrane potential, peroxisome mass, uptake of fluorescent peroxisomal specific substrate, increase in peroxisomal protein PMP70, increase in ALD, lysosomal mass, uptake of a fluorescent lysosomal specific substrate, increase in lysosomal protein LAMPl staining, golgi organization, and plasma membrane permeability.

12. The method of Claim 8, wherein at least one cellular feature indicating cell cycle state is selected from the group consisting of DNA content, Histone H3 phosphorylation state, Rb phosporylation state, cyclin Bl (CDKl) biosynthesis, cyclin Dl (CDK4, 6) biosynthesis, and cyclin E (CDK2) biosysnthesis.

13. The method of Claim 8, wherein at least one cellular feature indicating morphology is selected from the group consisting of motility, cell spreading, adhesion, blebbing, vacuolization, ruffling, and colony formation.

14. The method of Claim 8, wherein at least one cellular feature indicating apoptosis is selected from the group consisting of nuclear size and shape, DNA content and degradation, gluthatione content, measure of reactive oxygen species, cytochrome C release, caspase activation, phosphatidyl- expression, and Bax translocation.

15. The method of Claim 8, wherein at least one cellular feature indicating metabolism is selected from the group consisting of cAMP concentration, P- glycoprotein, transport pump activity, and CYP450 induction/inhibition.

16. The method of Claim 8, wherein at least one cellular feature indicating signal transduction is selected from the group consisting of Ca++ ion concentration and pH.

17. The method of Claim 8, wherein at least one cellular feature indicating cell differentiation is selected from the group consisting of expression of a tissue- specific differentiation marker and tissue-specific differentiation morphology.

18. The method of Claim 8, wherein at least one cellular feature indicating cell- cell interactions or cell to non-cell interactions are selected from the group consisting of concentration of tight junction proteins at a cell-cell interface, cell-cell communication, cell-non cell communication, and material transfer from cell to canalicular intracellular spaces.

19. The method of Claim 1 , wherein at least one cellular feature is cell loss, DNA degradation, cell cycle arrest, nuclear size, histone H2A.X phosphorylation level, c-jun phosphorylation level, p53 activation, GADDl 53 induction, increase or decrease in triglyceride accumulation, Phase I metabolism, Phase II metabolism, cytochrome P-450 enzyme activity, albumin synthesis or albumin release.

20. The method of Claim 1 , wherein at least one of the six or more cellular features are measured by imaging.

21. A method for constructing a database of cellular systems biology response profiles for hepatocytes contacted with one or more reference substances comprising: a) contacting hepatocytes having metabolically active cytochrome P450 with a first reference substance; b) labeling the hepatocytes with a panel of fluorescently labeled reagents, thereby producing one or more fluorescently labeled hepatocytes, wherein each fluorescently labeled reagent is specific for a biomarker, the panel of fluorescently labeled reagents detects at least five different biomarkers, the detection of a biomarker provides a read-out of one or more features, and wherein at least one feature is related to at least one cellular functional class selected from the group consisting of phospholipidosis and steatosis; c) imaging the one or more fluorescently labeled hepatocytes with at least one optical mode, wherein the imaging produces a set of data; d) analyzing the set of data for one or more features of each of the five or more biomarkers, wherein the combination of the features of the five or more biomarkers generates a cellular systems biology profile of the hepatocytes for the first reference substance; and e) optionally repeating steps a-f substituting a second or further reference substances for the first reference substance, thereby constructing a database of cellular systems biology response profiles for hepatocytes contacted with one or more reference substances.

22. The method of Claim 21 , further comprising comparing the cellular systems biology profile of the first, second and/or further reference substance to cellular systems biology profiles of substances with known biological systems effects on hepatocytes in the database, wherein if the response profile of the hepatocytes contacted of the first, second or further reference substance is the same as, or is similar to, a response profile in the database, then the first, second or further reference substance is predicted to have the same or similar biological systems effect as the substance that produced the known biological systems effect on hepatocytes in the database.

23. The method of Claim 21, wherein analyzing the set of data comprises cluster analysis.

24. The method of Claim 21, wherein the hepatocytes are contacted with a range of reference substance concentrations and a cellular systems biology response profile is constructed for each reference substance concentration.

25. The method of Claim 21 , wherein imaging the one or more fluorescently labeled hepatocytes is performed at more than one time point, wherein the imaging produces a set of data for each time point.

26. The method of Claim 22, wherein a profile is built from the feature measurements at each substance concentration comprising: a) calculating a parameter using Kolmogorov-Smirnov values or average values as a measure of cell population shifts for each feature measurement at each substance concentration to generate parameters for a concentration series; b) fitting the parameters for the concentration series using a 4-parameter logistic fit, thereby producing fitted data; c) analyzing the fitted data to calculate EC50 values; d) converting the EC50 values to log scale as a measure of compound activity; and e) using cluster analysis to identify similarities in profiles as well as correlations between cellular systems responses.

27. A kit comprising one or more reagents for measuring six or more cellular features in at least two cellular functional classes, wherein at least one cellular functional class is phospholipidosis or steatosis and instructions for employing the reagents for predicting the biological systems effect of a test substance on hepatocytes.

28. The kit of Claim 27, further comprising a panel of fiuorescently labeled reagents, wherein each fiuorescently labeled reagent is specific for a biomarker, the panel of fiuorescently labeled reagents detects at least five different biomarkers, and the detection of a biomarker is a read-out of one or more features.

29. The kit of Claim 27, further comprising a database of hepatocyte response profiles.

30. The kit of Claim 27, wherein at least one cellular feature indicates at least one cellular functional class selected from the group consisting of cell proliferation, stress pathways, oxidative stress, stress kinase activation, DNA damage, lipid metabolism, carbohydrate regulation, metabolic activation including Phase I and Phase II reactions, Cytochrome P-450 induction or inhibition, ammonia detoxification, mitochondrial function, peroxisome proliferation, organelle function, cell cycle state, morphology, apoptosis, DNA damage, metabolism, signal transduction, cell differentiation, cell-cell interaction and cell to non-cellular compartment.

31. The kit of Claim 30, wherein the at least one cellular feature indicating cell proliferation is selected from the group consisting of nuclear count, cell count, total cell mass, total DNA, the phosphorylation state of cell cycle regulatory proteins, and post- translational modification state of any protein involved in cell growth or division.

32. The kit of Claim 30, wherein the at least one cellular feature indicating stress pathway activation is transcription factor activation of a transcription factor selected from NRF2, NF-κB, Pl, ATF2, MSKl, CREB, and NFAT, or kinase activation of p38, JNK, ERK, RSK90 and MEK, or a combination thereof.

33. The kit of Claim 30, wherein at least one cellular feature indicating organelle function is selected from the group consisting of cytoskeletal organization, mitochondrial mass, mitochondial membrane potential, peroxisome mass, uptake of fluorescent peroxisomal specific substrate, increase in peroxisomal protein PMP70, increase in ALD, lysosomal mass, uptake of a fluorescent lysosomal specific substrate, increase in lysosomal protein LAMP 1 staining, golgi organization, and plasma membrane permeability.

34. The kit of Claim 30, wherein at least one cellular feature indicating cell cycle state is selected from the group consisting of DNA content, Histone H3 phosphorylation state, Rb phosporylation state, cyclin Bl (CDKl) biosynthesis, cyclin Dl (CDK4, 6) biosynthesis, and cyclin E (CDK2) biosysnthesis.

35. The kit of Claim 30, wherein at least one cellular feature indicating morphology is selected from the group consisting of motility, cell spreading, adhesion, blebbing, vacuolization, ruffling, and colony formation.

36. The kit of Claim 30, wherein at least one cellular feature indicating apoptosis is selected from the group consisting of nuclear size and shape, DNA content and degradation, gluthatione content, measure of reactive oxygen species, cytochrome C release, caspase activation, phosphatidyl-expression, and Bax translocation.

37. The kit of Claim 30, wherein at least one cellular feature indicating metabolism is selected from the group consisting of cAMP concentration, P- glycoprotein, transport pump activity, and CYP450 induction/inhibition.

38. The kit of Claim 30, wherein at least one cellular feature indicating signal transduction is selected from the group consisting of Ca++ ion concentration and pH.

39. The kit of Claim 30, wherein at least one cellular feature indicating cell differentiation is selected from the group consisting of expression of a tissue- specific differentiation marker and tissue-specific differentiation morphology.

40. The kit of Claim 30, wherein at least one cellular feature indicating cell-cell interactions or cell to non-cell interactions are selected from the group consisting of concentration of tight junction proteins at a cell-cell interface, cell-cell communication, cell-non cell communication, and material transfer from cell to canalicular intracellular spaces.

41. The kit of Claim 30, wherein at least one cellular feature is cell loss, DNA degradation, cell cycle arrest, nuclear size, histone H2A.X phosphorylation level, c-jun phosphorylation level, p53 activation, GADDl 53 induction, increase or decrease in triglyceride accumulation, Phase I metabolism, Phase II metabolism, cytochrome P-450 enzyme activity, albumin synthesis or albumin release.

42. A kit comprising a panel of fluorescently labeled reagents, wherein each fluorescently labeled reagent is specific for a biomarker, wherein the panel of fluorescently labeled reagents detects at least five different biomarkers, and the detection of a biomarker provides a read-out of one or more features, wherein at least one feature indicates at least one cellular functional class selected from the group consisting of phospholipidosis and steatosis, and instructions for use.