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Adaptive informatics for multifactorial and high-content biological data.

Millard BL, Niepel M, Menden MP, Muhlich JL, Sorger PK - Nat. Methods (2011)

Bottom Line: Here we describe an adaptive approach to managing experimental data based on semantically typed data hypercubes (SDCubes) that combine hierarchical data format 5 (HDF5) and extensible markup language (XML) file types.We demonstrate the application of SDCube-based storage using ImageRail, a software package for high-throughput microscopy.Experimental design and its day-to-day evolution, not rigid standards, determine how ImageRail data are organized in SDCubes.

View Article: PubMed Central - PubMed

Affiliation: Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

ABSTRACT
Whereas genomic data are universally machine-readable, data from imaging, multiplex biochemistry, flow cytometry and other cell- and tissue-based assays usually reside in loosely organized files of poorly documented provenance. This arises because the relational databases used in genomic research are difficult to adapt to rapidly evolving experimental designs, data formats and analytic algorithms. Here we describe an adaptive approach to managing experimental data based on semantically typed data hypercubes (SDCubes) that combine hierarchical data format 5 (HDF5) and extensible markup language (XML) file types. We demonstrate the application of SDCube-based storage using ImageRail, a software package for high-throughput microscopy. Experimental design and its day-to-day evolution, not rigid standards, determine how ImageRail data are organized in SDCubes. We applied ImageRail to collect and analyze drug dose-response landscapes in human cell lines at single-cell resolution.

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Single-cell analysis of drug-ligand dose responses uncovers cell-to-cell heterogeneity. (a) ppERK was measured at 10 min and 20 hr in SKBR3 cells treated with a combination of EGF and gefitinib at the indicated doses. Shown are heat maps of the mean values (red) and coefficients of variation (blue) of the underlying cell population histograms overlaid on representation of a standard 96-well microtiter plate. (b) Selected immunofluorescence images of ppERK (red) and Hoechst (blue) staining of cells 20 hr after exposure first to 10 µM gefitinib and then to 100 ng/mL EGF. Scale bar = 100µm. (c) EGF-induced ppERK dose-response curves in SKBR3 cells pretreated with sub-saturating doses of gefitinib or the MEK inhibitor PD0325901 (MEKi). Error bars represent the standard error of the mean of biological triplicates. (d) Corresponding single-cell distributions for the population mean data shown in c.
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Figure 5: Single-cell analysis of drug-ligand dose responses uncovers cell-to-cell heterogeneity. (a) ppERK was measured at 10 min and 20 hr in SKBR3 cells treated with a combination of EGF and gefitinib at the indicated doses. Shown are heat maps of the mean values (red) and coefficients of variation (blue) of the underlying cell population histograms overlaid on representation of a standard 96-well microtiter plate. (b) Selected immunofluorescence images of ppERK (red) and Hoechst (blue) staining of cells 20 hr after exposure first to 10 µM gefitinib and then to 100 ng/mL EGF. Scale bar = 100µm. (c) EGF-induced ppERK dose-response curves in SKBR3 cells pretreated with sub-saturating doses of gefitinib or the MEK inhibitor PD0325901 (MEKi). Error bars represent the standard error of the mean of biological triplicates. (d) Corresponding single-cell distributions for the population mean data shown in c.

Mentions: On comparing mean ppERK levels with cell-to-cell variance using plate maps (Fig. 5a), we observed maximum variability at physiologically relevant doses of drug and ligand (estimated to be 0.1–1.5 ng/mL for EGF and 0.4–50 µM for gefitinib21,22). Mean value and variance in response changed over time, such that 20 hours post-EGF/gefitinib treatment, IC50 was less dependent on [EGF] but the variance increased. By linking back to the underlying images, we observed that even in cells exposed to saturating doses of gefitinib (10 µM) for 20 hr, a subpopulation of cells (~1%) exhibited elevated ppERK levels. This implies not only that these cells were drug-resistant but also that ERK signaling could be sustained in the absence of exogenous ligand (a behavior different from that of cells that are simply gefitinib-insensitive; Fig. 5a and Fig. 5b). Thus, single-cell data revealed three interesting features of cellular responses to gefitinib and EGF. First, IC50 varied with the concentration of extracellular ligand, particularly at early time points. Second, the extent of cell-to-cell variability was maximal near intermediate, physiologically-relevant concentrations; conversely, it was masked when drug or ligand were added at high levels. Third, cell-to-cell heterogeneity changed over time, being dominated initially by broad distributions and subsequently by rare cells with sustained signaling. Whether the differences we observe are genetic23, epigenetic24 or stochastic25 in origin is not yet clear, but reversibility implies that some are indeed stochastic, as we have previously demonstrated for TNF-responsive apoptosis-inducing ligand (TRAIL)25.


Adaptive informatics for multifactorial and high-content biological data.

Millard BL, Niepel M, Menden MP, Muhlich JL, Sorger PK - Nat. Methods (2011)

Single-cell analysis of drug-ligand dose responses uncovers cell-to-cell heterogeneity. (a) ppERK was measured at 10 min and 20 hr in SKBR3 cells treated with a combination of EGF and gefitinib at the indicated doses. Shown are heat maps of the mean values (red) and coefficients of variation (blue) of the underlying cell population histograms overlaid on representation of a standard 96-well microtiter plate. (b) Selected immunofluorescence images of ppERK (red) and Hoechst (blue) staining of cells 20 hr after exposure first to 10 µM gefitinib and then to 100 ng/mL EGF. Scale bar = 100µm. (c) EGF-induced ppERK dose-response curves in SKBR3 cells pretreated with sub-saturating doses of gefitinib or the MEK inhibitor PD0325901 (MEKi). Error bars represent the standard error of the mean of biological triplicates. (d) Corresponding single-cell distributions for the population mean data shown in c.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3105758&req=5

Figure 5: Single-cell analysis of drug-ligand dose responses uncovers cell-to-cell heterogeneity. (a) ppERK was measured at 10 min and 20 hr in SKBR3 cells treated with a combination of EGF and gefitinib at the indicated doses. Shown are heat maps of the mean values (red) and coefficients of variation (blue) of the underlying cell population histograms overlaid on representation of a standard 96-well microtiter plate. (b) Selected immunofluorescence images of ppERK (red) and Hoechst (blue) staining of cells 20 hr after exposure first to 10 µM gefitinib and then to 100 ng/mL EGF. Scale bar = 100µm. (c) EGF-induced ppERK dose-response curves in SKBR3 cells pretreated with sub-saturating doses of gefitinib or the MEK inhibitor PD0325901 (MEKi). Error bars represent the standard error of the mean of biological triplicates. (d) Corresponding single-cell distributions for the population mean data shown in c.
Mentions: On comparing mean ppERK levels with cell-to-cell variance using plate maps (Fig. 5a), we observed maximum variability at physiologically relevant doses of drug and ligand (estimated to be 0.1–1.5 ng/mL for EGF and 0.4–50 µM for gefitinib21,22). Mean value and variance in response changed over time, such that 20 hours post-EGF/gefitinib treatment, IC50 was less dependent on [EGF] but the variance increased. By linking back to the underlying images, we observed that even in cells exposed to saturating doses of gefitinib (10 µM) for 20 hr, a subpopulation of cells (~1%) exhibited elevated ppERK levels. This implies not only that these cells were drug-resistant but also that ERK signaling could be sustained in the absence of exogenous ligand (a behavior different from that of cells that are simply gefitinib-insensitive; Fig. 5a and Fig. 5b). Thus, single-cell data revealed three interesting features of cellular responses to gefitinib and EGF. First, IC50 varied with the concentration of extracellular ligand, particularly at early time points. Second, the extent of cell-to-cell variability was maximal near intermediate, physiologically-relevant concentrations; conversely, it was masked when drug or ligand were added at high levels. Third, cell-to-cell heterogeneity changed over time, being dominated initially by broad distributions and subsequently by rare cells with sustained signaling. Whether the differences we observe are genetic23, epigenetic24 or stochastic25 in origin is not yet clear, but reversibility implies that some are indeed stochastic, as we have previously demonstrated for TNF-responsive apoptosis-inducing ligand (TRAIL)25.

Bottom Line: Here we describe an adaptive approach to managing experimental data based on semantically typed data hypercubes (SDCubes) that combine hierarchical data format 5 (HDF5) and extensible markup language (XML) file types.We demonstrate the application of SDCube-based storage using ImageRail, a software package for high-throughput microscopy.Experimental design and its day-to-day evolution, not rigid standards, determine how ImageRail data are organized in SDCubes.

View Article: PubMed Central - PubMed

Affiliation: Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

ABSTRACT
Whereas genomic data are universally machine-readable, data from imaging, multiplex biochemistry, flow cytometry and other cell- and tissue-based assays usually reside in loosely organized files of poorly documented provenance. This arises because the relational databases used in genomic research are difficult to adapt to rapidly evolving experimental designs, data formats and analytic algorithms. Here we describe an adaptive approach to managing experimental data based on semantically typed data hypercubes (SDCubes) that combine hierarchical data format 5 (HDF5) and extensible markup language (XML) file types. We demonstrate the application of SDCube-based storage using ImageRail, a software package for high-throughput microscopy. Experimental design and its day-to-day evolution, not rigid standards, determine how ImageRail data are organized in SDCubes. We applied ImageRail to collect and analyze drug dose-response landscapes in human cell lines at single-cell resolution.

Show MeSH
Related in: MedlinePlus