A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies.

Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms.

Chemical combination effects predict connectivity in biological systems.

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured.

Synergistic drug combinations tend to improve therapeutically relevant selectivity.

Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.

ATP-binding cassette transporter A1 contains a novel C-terminal VFVNFA motif that is required for its cholesterol efflux and ApoA-I binding activities.

The stimulation of cellular cholesterol and phospholipid efflux by apolipoprotein A-I is mediated by the activity of the ATP-binding cassette transporter A1 (ABCA1). Individuals with Tangier disease harbor loss-of-function mutations in this transporter that have proven useful in illuminating its activity. Here, we analyze a mutation that deletes the last 46 residues of the 2261 amino acid transporter (Delta46) and eliminates its lipid efflux. As the final four amino acids of the C terminus represent a putative PDZ-binding motif, we initially characterized deletion mutants lacking only these residues. Although a moderate decline in lipid efflux was detected, this decline was not as profound as that seen in the Delta46 mutant. Subsequent systematic analysis of the ABCA1 C terminus revealed a novel, highly conserved motif (VFVNFA) that was required for lipid efflux. Alteration of this motif, which is present in some but not all members of the ABCA family, did not prevent trafficking of the transporter to the plasma membrane but did eliminate its binding of apoA-I. Chimeric transporters, generated by substituting the C termini of either ABCA4 or ABCA7 for the endogenous terminus, demonstrated that ABCA1 could stimulate cholesterol efflux without its PDZ-binding motif but not without the VFVNFA motif. When a peptide containing the VFVNFA sequence was introduced into ABCA1-expressing cells, ABCA1-mediated lipid efflux was also markedly inhibited. These results indicate that the C-terminal VFVNFA motif of ABCA1 is essential for its lipid efflux activity. The data also suggest that this motif participates in novel protein-protein interactions that may be shared among members of the ABCA family.