Cellular barcodes for efficiently profiling single-cell secretory responses by microengraving.

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. Using n different fluorescent dyes to generate 2(n) unique cellular barcodes, we achieved a 2(n)-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.

Insights into proteomic immune cell signaling and communication via data-driven modeling.

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.

Hemodynamic systems analysis of capillary network remodeling during the progression of type 2 diabetes.

Objective: Early alterations in the skeletal muscle microvasculature may contribute to the onset and progression of type 2 diabetes (DM2) by limiting insulin and glucose availability to skeletal muscle. Microvascular alterations reported with DM2 are numerous and include impaired endothelium-mediated vasodilation, increased arteriole wall stiffness, and decreased capillary density. Most previous analyses of skeletal muscle microvascular architecture have been limited to skeletal muscle cross sections and thus have not presented an integrated, quantitative analysis of the relative significance of observed alterations to elevated microvascular network resistance and decreased blood flow.

Systems analysis of small signaling modules relevant to eight human diseases.

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.