We present a method that uses fluorescent cellular barcodes to increase the number of unique samples that can be analyzed simultaneously by microengraving—a nanowell array-based technique for quantifying the secretory responses of thousands of single cells in parallel. By using n different fluorescent dyes to generate 2n unique cellular barcodes, we achieved a 2n-fold reduction in the number of arrays and quantity of reagents required per sample. The utility of this approach was demonstrated in three applications of interest in clinical and experimental immunology. Using barcoded human peripheral blood mononuclear cells and T cells, we constructed dose-response curves, profiled the secretory behavior of cells treated with mechanistically distinct stimuli, and tracked the secretory behaviors of different lineages of CD4+ T helper cells. In addition to increasing the number of samples analyzed by generating secretory profiles of single cells from multiple populations in a time- and reagent-efficient manner, we expect that cellular barcoding in combination with microengraving will facilitate unique experimental opportunities for quantitatively analyzing interactions among heterogeneous cells isolated in small groups (~2–5 cells).
This study illustrates that capillary network connectivity is altered by DM2 and this negatively impacts microvascular hemodynamics. This work can serve as a basis for a more quantitative approach to evaluating DM2 microvascular networks and their potential use as an early diagnostic aid and/or method for identifying therapeutic targets.
Over the past decade, studies applying data-driven modeling approaches have demonstrated significant contributions toward the integrative understanding of multivariate cell regulatory system operation. Here we review applications of several of these approaches, including principal component analysis, partial least squares regression, partial least squares discriminant analysis, decision trees, and Bayesian networks, and describe the advances they have offered in systems-level understanding of immune cell signaling and communication. We show how these approaches generate novel insights from high-throughput proteomic data, from classification to association to influence to mechanisms. Looking forward, new experimental technologies involving single-cell measurements of cytokine expression beckon extension of these modeling techniques to inference of immune cell-cell communication networks, with a goal of aiding development of improved vaccine therapeutics.
Using eight newly generated models relevant to addiction, Alzheimer’s disease, cancer, diabetes, HIV, heart disease, malaria, and tuberculosis, we show that systems analysis of small (4–25 species), bounded protein signaling modules rapidly generates new quantitative knowledge from published experimental research. For example, our models show that tumor sclerosis complex (TSC) inhibitors may be more effective than the rapamycin (mTOR) inhibitors currently used to treat cancer, that HIV infection could be more effectively blocked by increasing production of the human innate immune response protein APOBEC3G, rather than targeting HIV’s viral infectivity factor (Vif), and how peroxisome proliferator-activated receptor alpha (PPARα) agonists used to treat dyslipidemia would most effectively stimulate PPARα signaling if drug design were to increase agonist nucleoplasmic concentration, as opposed to increasing agonist binding affinity for PPARα. Comparative analysis of system-level properties for all eight modules showed that a significantly higher proportion of concentration parameters fall in the top 15th percentile sensitivity ranking than binding affinity parameters. In infectious disease modules, host networks were significantly more sensitive to virulence factor concentration parameters compared to all other concentration parameters. This work supports the future use of this approach for informing the next generation of experimental roadmaps for known diseases.Electronic supplementary materialThe online version of this article (doi:10.1007/s10439-010-0208-y) contains supplementary material, which is available to authorized users.
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