Genetic Engineering & Biotechnology News

AUG 2017

Genetic Engineering & Biotechnology News (GEN) is the world's most widely read biotech publication. It provides the R&D community with critical information on the tools, technologies, and trends that drive the biotech industry.

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12 | AUGUST 2017 | | Genetic Engineering & Biotechnology News Joe Clayton, Ph.D. Proliferation assays provide quantitative evaluation of a cell population's viability and growth, and are a crucial aspect of cancer biology research. There are various types of proliferation assays, the principal differences being what is actually measured and whether it is an endpoint or kinetic assay. Challenges of Conventional Proliferation Assays Endpoint assays for measuring prolifera- tion, including those based on cellular me- tabolism and DNA synthesis, require sepa- rate experiments for each time point and are difficult to normalize across conditions. Ad- ditionally, these indirect metrics necessitate the collection and processing of cells with potentially expensive reagents and compli- cated protocols that can lead to artifacts and misleading results. Kinetic proliferation assays deliver a more accurate and complete profile of prolifera- tion rates over time, providing an attractive alternative to endpoint assays. Recent ad- vances in automated microscopy and image- analysis tools have enabled researchers to conduct imaging-based kinetic proliferation assays for detailed characterization of cell culture viability and growth over time peri- ods spanning days to weeks. With this ap- proach, quantification of cell-population size is generally determined using either percent- confluence measurements or cell counts. Although percent confluence provides some insight into the relative size of a popula- tion, the relationship between cell confluence and number of cells present is not linear at many culture densities. Therefore, a kinetic proliferation assay that directly determines cell count is preferable to confluence mea- surements for many applications. However, conventional methods for counting cells rely on nuclear labels that come with considerable limitations. Intercalating dyes, such as DAPI and Hoechst, are not suit- able for conducting kinetic live-cell assays because of induced toxicity. Expressed fluo- rescent nuclear labels, such as H2B–GFP, are also potentially disruptive to cells and require considerable time and expense to establish and maintain stable cell lines. A Label-Free Cell-Counting Solution The Lionheart FX Automated Microscope and Cytation Cell Imaging Readers from BioTek Instruments are fully automated im- aging systems optimized to perform a broad range of live-cell applications. Both instru- ments are available with high-contrast bright- field—an imaging technique that generates enhanced image quality and contrast over conventional brightfield for improved quan- titative analysis. High Contrast (HC) Cell Counting uses a modified form of high-con- trast brightfield to determine accurate label- free cell counts for normalization of experi- mental data and kinetic proliferation assays. In HC Cell Counting mode, refraction of white light by each cell produces a distinct bright spot against a dark background. Gen5 Monitoring the Proliferation of Cells Is Useful to Evaluate Drug-Dose Response Automated Label-Free Cell Counting Drug Discovery Tutorial Insights Discovery & Development Mass spectrometry, a mainstay of drug development, is broadening its purview. Besides confirming drug structures, identifying ancillary or extraneous molecules in formula- tions, and gathering pharmacokinetic information, mass spectrometry is venturing into metabolomics. Mass spec, with its unique detection capabilities, can identify and quantify all the metabolites in a biological system. Mass spec is especially useful in metabolomically inspired small-molecule analysis when it characterizes shifts between experimental and control groups. The problem, however, is that processing all the data that are involved is generally beyond human ken, to say nothing of the interpretive challenges. Consequently, mass spec instrumentation providers are improving their discovery software. For example, they are incorporating sophisticated informatics, through partnerships and acquisitions. Thermo Fisher Scientific, notable for its mass-spec devel- opment, is teaming with SRI International. The companies have announced that they are working together to enable quick and effective mass spec-based small-molecule research and analysis. As a result of this collaboration, results obtained via Thermo Fisher Scientific's high-resolution Orbitrap LC/ MS experiments may be combined with highly curated and organism-specific metabolic pathway and genome data. According to the companies, researchers may now benefit from a direct link between the Thermo Scientific Compound Discoverer 2.1 software platform for small-molecule research and SRI International's BioCyc, a collection of 9,300 databases that provide electronic reference sources on the metabolic pathways and genomes of many organisms. The ability to automatically and interactively overlay statistical data onto these pathways can facilitate the biological interpretation of results obtained from a metabolomics experiment. Ultimately, this new link is ex- pected to speed data analysis for Compound Discoverer users and enable them to visualize many individual compound measurements to gain a comprehensive under- standing of biological processes in an experiment. Such capabilities may contribute to growth in the metabo- lomics segment. According to Markets and Markets, the global metabolomics market is estimated to grow at a CAGR of 14.6% from 2016 to 2021 to reach $2.39 billion by 2021. Mar- kets and Markets cites favorable factors such as the increasing need for accurate diagnosis of diseases, rising demand for personalized medicine, emergence of advanced technologies, increasing pharmaceutical and biotech R&D expenditure, and the availability of government and private funding. n No Small Thing: The Combination of Mass Spec and Informatics Figure 1. HC Cell Counting produces accurate cell counts without the use of fluorescent labels. (A) High-contrast brightfield image of NIH3T3 cells. (B) HC Cell Counting mode generates images in which each cell produces a distinct bright spot against a dark background. (C) Gen5 image analysis software identifies each bright spot to generate HC cell counts. (D) HC cell counts are comparable to those achieved using fluorescently labeled nuclei across a range of cell densities. Figure 3. Unique quantitative and qualitative analysis of drug-treatment response using kinetic proliferation data. (A) Area under the curve (AUC) of cell count per mm 2 were used to calculate IC 50 values for NIH 3T3, HeLa, and HCT116. (B) Qualitative analysis of kinetic cell proliferation provides valuable insight into phenotypic response to drug treatment. NIH 3T3 proliferation images 36 hours after treatment with indicated concentration of doxorubicin. With 10 nM doxorubicin, cell division is inhibited without causing overt cytotoxicity; while at 100 nM and higher concentrations, signs of cytotoxicity are clearly evident. Figure 2. NIH 3T3, HeLa, and HCT116 kinetic cell proliferation profiles generated from HC cell counts enable quantitative analysis of doubling times and response to drug treatment. Cell counts per mm 2 were determined every two hours over a five-day period or until cells reached full confluence. Profiles from five concentrations of doxorubicin and cercosporamide demonstrate a cell-type- dependent differential- dose response.

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