The complete automation of cell culture: improvements for high-throughput and high-content screening

Genomic approaches provide enormous amounts of raw data with regard to genetic variation, the diversity of RNA species, and protein complement. High-throughput (HT) and high-content (HC) cellular screens are ideally suited to contextualize the information gathered from other "omic" approaches into networks and can be used for the identification of therapeutic targets. Current methods used for HT-HC screens are laborious, time-consuming, and prone to human error. The authors thus developed an automated high-throughput system with an integrated fluorescent imager for HC screens called the AI.CELLHOST. The implementation of user-defined culturing and assay plate setup parameters allows parallel operation of multiple screens in diverse mammalian cell types. The authors demonstrate that such a system is able to successfully maintain different cell lines in culture for extended periods of time as well as significantly increasing throughput, accuracy, and reproducibility of HT and HC screens.     

Development of a high-content high-throughput screening assay for the discovery of ATM signaling inhibitors

The genome is constantly exposed to DNA damage agents, leading up to as many as 1 million individual lesions per cell per day. Cells have developed a variety of DNA damage repair (DDR) mechanisms to respond to harmful effects of DNA damage. Failure to repair the damaged DNA causes genomic instability and, as a result, leads to cellular transformation. Indeed, deficiencies of DDR frequently occur in human cancers, thus providing a great opportunity for cancer therapy by developing anticancer agents that work by synthetic lethality-based mechanisms or enhancing the clinical efficacy of radiotherapy and existing chemotherapies. Ataxia-telangiectasia mutated (ATM) plays a key role in regulating the cellular response to DNA double-strand breaks. Ionizing radiation causes double-strand breaks and induces rapid ATM autophosphorylation on serine 1981 that initiates ATM kinase activity. Activation of ATM results in phosphorylation of many downstream targets that modulate numerous damage-response pathways, most notably cell-cycle checkpoints. We describe here the development and validation of a high-throughput imaging assay measuring levels of phospho-ATM Ser1981 in HT29 cells after exposure to ionizing radiation. We also examined activation of downstream ATM effectors and checked specificity of the endpoint using known inhibitors of DNA repair pathways.     

Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis

We describe the application of a novel screening approach that combines automated yeast genetics, synthetic genetic array (SGA) analysis, and a high-content screening (HCS) system to examine mitotic spindle morphogenesis. We measured numerous spindle and cellular morphological parameters in thousands of single mutants and corresponding sensitized double mutants lacking genes known to be involved in spindle function. We focused on a subset of genes that appear to define a highly conserved mitotic spindle disassembly pathway, which is known to involve Ipl1p, the yeast aurora B kinase, as well as the cell cycle regulatory networks mitotic exit network (MEN) and fourteen early anaphase release (FEAR). We also dissected the function of the kinetochore protein Mcm21p, showing that sumoylation of Mcm21p regulates the enrichment of Ipl1p and other chromosomal passenger proteins to the spindle midzone to mediate spindle disassembly. Although we focused on spindle disassembly in a proof-of-principle study, our integrated HCS-SGA method can be applied to virtually any pathway, making it a powerful means for identifying specific cellular functions.     

A multi-parameter, high-content, high-throughput screening platform to identify natural compounds that modulate insulin and Pdx1 expression

Diabetes is a devastating disease that is ultimately caused by the malfunction or loss of insulin-producing pancreatic beta-cells. Drugs capable of inducing the development of new beta-cells or improving the function or survival of existing beta-cells could conceivably cure this disease. We report a novel high-throughput screening platform that exploits multi-parameter high-content analysis to determine the effect of compounds on beta-cell survival, as well as the promoter activity of two key beta-cell genes, insulin and pdx1. Dispersed human pancreatic islets and MIN6 beta-cells were infected with a dual reporter lentivirus containing both eGFP driven by the insulin promoter and mRFP driven by the pdx1 promoter. B-score statistical transformation was used to correct systemic row and column biases. Using this approach and 5 replicate screens, we identified 7 extracts that reproducibly changed insulin and/or pdx1 promoter activity from a library of 1319 marine invertebrate extracts. The ability of compounds purified from these extracts to significantly modulate insulin mRNA levels was confirmed with real-time PCR. Insulin secretion was analyzed by RIA. Follow-up studies focused on two lead compounds, one that stimulates insulin gene expression and one that inhibits insulin gene expression. Thus, we demonstrate that multi-parameter, high-content screening can identify novel regulators of beta-cell gene expression, such as bivittoside D. This work represents an important step towards the development of drugs to increase insulin expression in diabetes and during in vitro differentiation of beta-cell replacements.     

siRNA cell arrays for high-content screening microscopy

RNA interference (RNAi) is a recent advance that provides the possibility to reduce the expression of specific target genes in cultured mammalian cells with potential applications on a genome-wide scale. However, to achieve this, robust methodologies that allow automated and efficient delivery of small interfering RNAs (siRNAs) into living cultured cells and reliable quality control of siRNA function must be in place. Here we describe the production of cell arrays for reverse transfection of tissue culture cells with siRNA and plasmid DNA suitable for subsequent high-content screening microscopy applications. All the necessary transfection components are mixed prior to the robotic spotting on noncoated chambered coverglass tissue culture dishes, which are ideally suited for time-lapse microscopy applications in living cells. The addition of fibronectin to the spotting solution improves cell adherence. After cell seeding, no further cell culture manipulations, such as medium changes or the addition of 7 serum, are needed. Adaptation of the cell density improves autofocus performance for high-quality data acquisition and cell recognition. The co-transfection of a nonspecific fluorescently labeled DNA oligomer with the specific siRNA helps to mark each successfully transfected cell and cell cluster. We demonstrate such an siRNA cell array in a microscope-based functional assay in living cells to determine the effect of various siRNA oligonucleotides against endogenous targets on cellular secretion.     

Model-based extension of high-throughput to high-content data

Background  

High-quality quantitative data is a major limitation in systems biology. The experimental data used in systems biology can be assigned to one of the following categories: assays yielding average data of a cell population, high-content single cell measurements and high-throughput techniques generating single cell data for large cell populations. For modeling purposes, a combination of data from different categories is highly desirable in order to increase the number of observable species and processes and thereby maximize the identifiability of parameters.     

Biomolecular screening of formylpeptide receptor ligands with a sensitive, quantitative, high-throughput flow cytometry platform

The formylpeptide receptor (FPR) family of G protein-coupled receptors contributes to the localization and activation of tissue-damaging leukocytes at sites of chronic inflammation. Here we describe a high-throughput flow cytometry screening approach that has successfully identified multiple families of previously unknown FPR ligands. The assay detects active structures that block the binding of a fluorescent ligand to membrane FPR of intact cells, thus detecting both agonists and antagonists. It is homogeneous in that assay reagents are added in sequence and the wells are subsequently analyzed without intervening wash steps. Microplate wells are routinely processed at a rate of 40 wells per minute, requiring a volume of only 2 microl to be sampled from each. This screening approach has recently been extended to identify a high-affinity, selective agonist for the intracellular estrogen-binding G protein-coupled receptor GPR30. With the development of appropriate assay reagents, it may be generally adaptable to a wide range of receptors. The total time required for the assay ranges between 1.5 and 2.5 h. The time required for flow cytometry analysis of a 96-well plate at the end of the procedure is less than 2.5 min. By comparison, manual processing of 96 samples will typically require 40-50 min, and a fast commercial automated sampler processes 96-well plates in less than 15 min, requiring the aspiration of 22 microl per sample for an analysis volume of 2 microl.     

Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling

Flow cytometry allows high-content, multiparameter analysis of single cells, making it a promising tool for drug discovery and profiling of intracellular signaling. To add high-throughput capacity to flow cytometry, we developed a cell-based multiplexing technique called fluorescent cell barcoding (FCB). In FCB, each sample is labeled with a different signature, or barcode, of fluorescence intensity and emission wavelengths, and mixed with other samples before antibody staining and analysis by flow cytometry. Using three FCB fluorophores, we were able to barcode and combine entire 96-well plates, reducing antibody consumption 100-fold and acquisition time to 5-15 min per plate. Using FCB and phospho-specific flow cytometry, we screened a small-molecule library for inhibitors of T cell-receptor and cytokine signaling, simultaneously determining compound efficacy and selectivity. We also analyzed IFN-gamma signaling in multiple cell types from primary mouse splenocytes, revealing differences in sensitivity and kinetics between B cells, CD4+ and CD4- T cells and CD11b-hi cells.     

A parallel microfluidic flow cytometer for high-content screening

A parallel microfluidic cytometer (PMC) uses a high-speed scanning photomultiplier-based detector to combine low-pixel-count, one-dimensional imaging with flow cytometry. The 384 parallel flow channels of the PMC decouple count rate from signal-to-noise ratio. Using six-pixel one-dimensional images, we investigated protein localization in a yeast model for human protein misfolding diseases and demonstrated the feasibility of a nuclear-translocation assay in Chinese hamster ovary (CHO) cells expressing an NFκB-EGFP reporter.     

Cell-based high-content screening of small-molecule libraries

Advanced microscopy and the corresponding image analysis have been developed in recent years into a powerful tool for studying molecular and morphological events in cells and tissues. Cell-based high-content screening (HCS) is an upcoming methodology for the investigation of cellular processes and their alteration by multiple chemical or genetic perturbations. Multiparametric characterization of responses to such changes can be analyzed using intact live cells as reporter. These disturbances are screened for effects on a variety of molecular and cellular targets, including subcellular localization and redistribution of proteins. In contrast to biochemical screening, they detect the responses within the context of the intercellular structural and functional networks of normal and diseased cells, respectively. As cell-based HCS of small-molecule libraries is applied to identify and characterize new therapeutic lead compounds, large pharmaceutical companies are major drivers of the technology and have already shown image-based screens using more than 100,000 compounds.     

Phaedra, a protocol-driven system for analysis and validation of high-content imaging and flow cytometry

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community. After review of existing applications, we realized the possibility of adding innovative new analysis options. Phaedra was developed to support workflows for drug screening and target discovery, interact with several laboratory information management systems, and process data generated by a range of techniques including high-content imaging, multicolor flow cytometry, and traditional high-throughput screening assays. The application is modular and flexible, with an interface that can be tuned to specific user roles. It offers user-friendly data visualization and reduction tools for HCS but also integrates Matlab for custom image analysis and the Konstanz Information Miner (KNIME) framework for data mining. Phaedra features efficient JPEG2000 compression and full drill-down functionality from dose-response curves down to individual cells, with exclusion and annotation options, cell classification, statistical quality controls, and reporting.     

Hydrogel tissue construct-based high-content compound screening

Current pharmaceutical compound screening systems rely on cell-based assays to identify therapeutic candidates and potential toxicities. However, cells grown on 2D substrata or in suspension do not exhibit the mechanical or physiological properties of cells in vivo. To address this limitation, the authors developed an in vitro, high-throughput, 3D hydrogel tissue construct (HTC)-based assay system to quantify cell and tissue mechanical properties and multiple parameters of physiology. HTC mechanics was quantified using an automated device, and physiological status was assessed using spectroscopy-based indicators that were read on microplate readers. To demonstrate the application of this system, the authors screened 4 test compounds--rotenone (ROT), cytochalasin D (CD), 2,4-dinitrophenol (DNP), and Rho kinase inhibitor (H-1152)--for their ability to modulate HTC contractility without affecting actin integrity, mitochondrial membrane potential (MMP), or viability. All 4 compounds dose-dependently reduced HTC contractility. However, ROT was toxic, DNP dissipated MMP, and CD reduced both intracellular F-actin and viability. H-1152 was found to be the best candidate compound since it reduced HTC contractility with minimal side effects. The authors propose that their HTC-based assay system can be used to screen for compounds that modulate HTC contractility and assess the underlying physiological mechanism(s) of compound activity and toxicity.     

Comparison of multivariate data analysis strategies for high-content screening

High-content screening (HCS) is increasingly used in biomedical research generating multivariate, single-cell data sets. Before scoring a treatment, the complex data sets are processed (e.g., normalized, reduced to a lower dimensionality) to help extract valuable information. However, there has been no published comparison of the performance of these methods. This study comparatively evaluates unbiased approaches to reduce dimensionality as well as to summarize cell populations. To evaluate these different data-processing strategies, the prediction accuracies and the Z' factors of control compounds of a HCS cell cycle data set were monitored. As expected, dimension reduction led to a lower degree of discrimination between control samples. A high degree of classification accuracy was achieved when the cell population was summarized on well level using percentile values. As a conclusion, the generic data analysis pipeline described here enables a systematic review of alternative strategies to analyze multiparametric results from biological systems.     

Toward high-content/high-throughput imaging and analysis of embryonic morphogenesis

In vivo study of embryonic morphogenesis tremendously benefits from recent advances in live microscopy and computational analyses. Quantitative and automated investigation of morphogenetic processes opens the field to high-content and high-throughput strategies. Following experimental workflow currently developed in cell biology, we identify the key challenges for applying such strategies in developmental biology. We review the recent progress in embryo preparation and manipulation, live imaging, data registration, image segmentation, feature computation, and data mining dedicated to the study of embryonic morphogenesis. We discuss a selection of pioneering studies that tackled the current methodological bottlenecks and illustrated the investigation of morphogenetic processes in vivo using quantitative and automated imaging and analysis of hundreds or thousands of cells simultaneously, paving the way for high-content/high-throughput strategies and systems analysis of embryonic morphogenesis.     

Flow cytometry for immunology

Improvement in our knowledge in cellular biology is largely related to the use of new tools in quantitative cytology. Among them, flow cytometry was developed with numerous applications in the field of immunology including fundamental and applied research. Since its early beginning it has been associated with monoclonal antibodies to identify immuno-competent cells, to quantify changes in expression of surface determinants, to separate cells subsets prior to the test of their functional properties. Major advances gained using either single or dual-laser systems, multicolour fluorescence and computer facilities for multi-parametric analysis. Using this methodology it was possible to correlate analysis of cell cycle phases and membrane antigens expression. Applications have been developed for the analysis of new drugs in vitro, the evaluation of immunomodulating treatment and for clinical investigations.     

Enzyme assays for high-throughput screening

Assaying enzyme-catalyzed transformations in high-throughput is crucial to enzyme discovery, enzyme engineering and the drug discovery process. In enzyme assays, catalytic activity is detected using labelled substrates or indirect sensor systems that produce a detectable spectroscopic signal upon reaction. Recent advances in the development of high-throughput enzyme assays have identified new labels and chromophores to detect a wide range of enzymes activities. Enzyme activity profiling and fingerprinting have also been used as tools for identification and classification, while microarray formats have been devised to increase throughput.     

Cellular phenotype recognition for high-content RNA interference genome-wide screening

Genome-wide, cell-based screens using high-content screening (HCS) techniques and automated fluorescence microscopy generate thousands of high-content images that contain an enormous wealth of cell biological information. Such screens are key to the analysis of basic cell biological principles, such as control of cell cycle and cell morphology. However, these screens will ultimately only shed light on human disease mechanisms and potential cures if the analysis can keep up with the generation of data. A fundamental step toward automated analysis of high-content screening is to construct a robust platform for automatic cellular phenotype identification. The authors present a framework, consisting of microscopic image segmentation and analysis components, for automatic recognition of cellular phenotypes in the context of the Rho family of small GTPases. To implicate genes involved in Rac signaling, RNA interference (RNAi) was used to perturb gene functions, and the corresponding cellular phenotypes were analyzed for changes. The data used in the experiments are high-content, 3-channel, fluorescence microscopy images of Drosophila Kc167 cultured cells stained with markers that allow visualization of DNA, polymerized actin filaments, and the constitutively activated Rho protein Rac(V12). The performance of this approach was tested using a cellular database that contained more than 1000 samples of 3 predefined cellular phenotypes, and the generalization error was estimated using a cross-validation technique. Moreover, the authors applied this approach to analyze the whole high-content fluorescence images of Drosophila cells for further HCS-based gene function analysis.