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Jan 1, 2012 (Vol. 32, No. 1)

High-Content Analysis: One Cell at a Time

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    hESCs, line H7, were differentiated to placental stem cells (trophectoderm) by treatment with bone morphogenic protein 4 (BMP4) in a custom basal media containing only the growth factor insulin, by researchers at the University of Pittsburgh. Time-lapse images of one colony in panel A show the change in colony morphology as cells enlarge and spread into a flattened epithelium. A phenotypic assay of the live-cell images measures changes in colony texture, cell shape, and granularity during differentiation without interfering with the cultures. Quantitative texture analysis in panel B provides statistical estimates of colony dissimilarity between the population of colonies. The chart shows the dissimilarity (red) between all images for 3 colonies on days 1, 2, 4, and 10. The 3 colonies on days 2 and 4 were dissimilar with a 0.98 confidence level. Noninvasive texture analysis can also be used to measure the kinetic effects of the drug trichostatin A (2 µM for 2 days) on the rate of differentiation in panel C. The validity of the phenotypic assay was confirmed by a panel of transcription factors using single-cell immunofluorescence and standard HCA.[Erb et al., Stem Cells and Development, September 2011]

    High-content analysis (HCA) sits at the intersection of modern cell biology, high-resolution microscopy, advanced image processing, and analysis software. Constantly evolving cellular-imaging techniques and the ability to interrogate single cells can produce a wealth of information. Questions that could not be asked can now be answered.

    Pharmaceutical and biotech industries have adopted HCA for target identification and validation, drug characterization, and predictive toxicity. HCA has surpassed high-throughput screening in measuring multiple biological pathways simultaneously or revealing off-target drug effects.

    CHI’s upcoming “High Content Analysis” conference will cover the entire HCA gamut, from toxicity assessment and drug screening, to image analysis and data management, to pathway analysis and RNAi.

    Stem cells hold great potential for regenerative medicine because of their ability to differentiate into all the cells of the body. However, the degree of pluripotency can vary and “a stem cell is not a stem cell is not a stem cell” says Paul Sammak, Ph.D., member of the McGowan Institute for Regenerative Medicine, The University of Pittsburgh. Dr. Sammak studies the paracrine and epigenetic control of trophectoderm differentiation in the early stages of embryonic development.

    “By measuring lineage-specific transcription factor expression levels in single cells we identified culture conditions for the quantitative conversion from pluripotent to trophectoderm committed cells,” explains Dr. Sammak. “Treatment of the cells with a histone deacetylase inhibitor slowed differentiation in a dose-dependent manner. We believe that epigenetic regulators play a role in early blastocyst viability.

    “A rapid, selective protocol for trophectoderm induction will allow us to perform further mechanistic studies on the role of environmental factors on human trophectoderm and blastocyst development,” he adds.

    Dr. Sammak will present the results of a collaboration with Rami Mangoubi at the C. S. Draper Laboratories, which will demonstrate a live-cell quantitative method for following differentiation and changes in colony morphology using texture analysis.

    “The combination of phenotypic measurements and HCA screening will allow us to better characterize stem cells for drug discovery or cell therapy.

    “A major bottleneck in the clinical use of stem cells for regenerative medicine is an understanding of the precise differentiation conditions required for individual lines to make early cell-fate decisions,” notes Emanuel Nazareth, graduate student in the laboratory of Peter Zandstra, Institute of Biomaterials and Biomedical Engineering at the University of Toronto.

    Cell distribution plays a major role in determining stem-cell fate, however, this distribution is difficult to measure or control. To address this, the group has developed a bioengineered cell-culture system that allows the control of colony size, spacing, and cell density.

    Using high-content analysis they compared the response of four different stem-cell lines to six different growth factor cocktails chosen to induce rapid differentiation into either neurectoderm, primitive streak/mesendoderm, or extraembryonic lineages on two different substrates.

    “By monitoring the single-cell protein expression of Oct4 and Sox2 we were able to discover and optimize conditions that resulted in the rapid induction of these cell fates,” explains Nazareth. Future work will not only refine the characterization of the effect of these ligands on cell-fate decisions in step-wise differentiation protocols but will also study the effects of various agonists and antagonists on these pathways.

  • Miniaturization Arrays

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    Researchers at MIT have developed a microfabricated array of up to 100,000 subnanoliter wells suitable for dynamic single-cell analysis using automated microscopy. Immune cells are shown labeled with different fluorescent dyes to identify unique subsets of cells. The array is loaded to allow a range of well occupancies.

    Anthony Davies, head, Irish National Centre for High Content Analysis and Screening, will talk about the Trinity Nano Plate Bioreactor, a new microplate system fabricated by Biocroi that utilizes nanoliter volumes and, correspondingly, small numbers of cells. The resulting cell densities are similar to those found in normal microplate experiments with equivalent cell viabilities.

    “The system allows us to miniaturize the most expensive part of the experiments such as lipid-based transfections of siRNAs.”

    Davies will also discuss a 3-D culture system that is particularly well suited to HCA. “The system does not require solid matricies but relies on a liquid that suspends the cells and allows cells to form 3-D structures such as spheroids. Cancer-cell lines form tumor-like structures that release increased amounts of relevant biomarkers when compared to traditional 2-D culture conditions. The system is completely scalable, works with adherent and suspension cells, and is very user friendly for liquid handling and HCA imaging applications.”

    “In the future, HCA has the opportunity to incorporate a broader range of data than presently available. We are beginning to rethink the tools we have now, exploring the boundaries of the current technologies in an attempt to increase the amount of information that can be extracted from biological systems,” J. Christopher Love, associate professor, chemical engineering at MIT, says.

    “Bioanalytics, typically, has a single question in mind. The real renaissance over the last few years is that you can ask multiple questions from a given image. We are trying to push those limits further to include other types of information such as secreted proteins and the genetic composition of single cells.”

    Love’s laboratory has developed a micro-fabricated array of up to 100,000 subnanoliter wells suitable for dynamic single-cell analysis using automated microscopy. Factors secreted by the cells can be “printed” onto a second glass slide in a nondestructive process known as microengraving that allows the cells’ secretions to be re-sampled multiple times and the results related back to the original cells.

    “We have used our system to evaluate the ability of thousands of individual CD8+ T cells from HIV-infected patients to mediate lysis and to produce cytokines. We believe that it is the first in vitro demonstration of a single cells ability to lyse a target cell combined with its secretory profile.”

    Love’s laboratory is also exploring the heterogeneity in recombinant protein secretion by the yeast Pichia pastoris. “By monitoring the secretion from single cells (and their progeny) over time, we can observe fluctuations. Understanding the mechanisms behind these variations will be important to maximize the yield in bioprocesses.”

  • Technology Showcase

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    Genedata Screener reportedly provides instant access to high-content screening images for scientists working with assay data.

    “Managing images and multiparametric datasets can be overwhelming. This is particularly the case when drilling down to cell-level data and reviewing information for single cells,” explained David Novo, Ph.D., and CEO of De Novo Software. “We offer a dedicated analysis and reporting package for image cytometry to improve workflows and results while giving users access to single-cell results even with high-content screening data.

    At the meeting, Dr. Novo will discuss his company’s collaborations with Molecular Devices and Thermo Scientific Cellomics. “These collaborations are essential because the acquisition and segmentation of the data is done by platform-specific algorithms. FCS Express Image Cytometry is a user-friendly tool to mine these rich datasets in real time. The lack of these tools has held back the high content field as a whole.

    “High-content screens produce data at a high level of complexity and volume, challenge image management, and require more sophisticated analysis workflows. None of these aspects were envisioned at the time many screening informatics systems were developed.”

    Genedata developed the Genedata Screener to address these issues. A mature and proven solution with a 10-year track record of success, Genedata Screener provides specialized analytics, viewers, and workflows for high-content screening, as well as instant access to the original images for unrivaled data analysis, according to Jon Tupy, head of professional services.

    “More types of analysis and more kinds of assay data are supported than ever before,” adds Tupy. “New capabilities added to the platform will provide unprecedented access and flexibility when performing QC on cell populations. In addition, it enhances support for the latest, most complex analyses allowing for new levels of efficiency in routine applications.”

    For example, instead of taking 30 minutes per plate to change analysis parameters, the new plate normalization results can be re-calculated in seconds per plate, resulting in a thousand-fold savings in time, Tupy says. “The goal of the entire Screener organization is to provide scientists with exceptional software that addresses the toughest problems they face in analyzing their data regardless of their data-acquisition platform.”


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