Lysate Microarrays Enable High-throughput, Quantitative Investigations of Cellular Signaling

Abstract

Lysate microarrays (reverse-phase protein arrays) hold great promise as a tool for systems-level investigations of signaling and multiplexed analyses of disease biomarkers. To date, however, widespread use of this technology has been limited by questions concerning data quality and the specificity of detection reagents. To address these concerns, we developed a strategy to identify high-quality reagents for use with lysate microarrays. In total, we tested 383 antibodies for their ability to quantify changes in protein abundance or modification in 20 biological contexts across 17 cell lines. Antibodies yielding significant differences in signal were further evaluated by immunoblotting and 82 passed our rigorous criteria. The largescale data set from our screen revealed that cell fate decisions are encoded not just by the identities of proteins that are activated, but by differences in their signaling dynamics as well. Overall, our list of validated antibodies and associated protocols establish lysate microarrays as a robust tool for systems biology. One of the primary goals of systems biology is to uncover and model the complex relationships between proteins in living cells and organisms. Data-driven approaches to addressing this problem require ways to obtain quantitative information on protein abundance and post-translational modifications (PTMs) 1 in a systematic and high-throughput fashion. Several different immunoaffinity-based methods have been used in systems-level studies to determine the amounts, subcellular locations, and PTM levels of proteins in complex biological samples. Antibody-based technologies that are compatible with multiplexing include flow cytometry (1), microsphere-based assays (2, 3), immunocytochemistry coupled with automated microscopy (4), miniaturized Western blotting (5), and antibody microarray-based methods such as direct-detection microarrays (6, 7), sandwich-style microarrays (8 -11), and "reverse-phase" or lysate microarrays (12, 13). Compared with their low-throughput counterparts, highthroughput technologies are often constrained by smaller sample sizes, lack of separation steps, and an inability to tailor the assay to each antibody. To ensure uniformly high data quality across a large number of analytes and biological samples, careful characterization of each antibody is critical. Studies in which the quantitative data are used to train computational models impose an even higher standard.Among high-throughput approaches, lysate microarray technology is particularly well suited for systems-level investigations. Thousands of biological specimens can be arrayed onto hundreds of membrane-coated slides, each of which can be queried with a different detection antibody. This format allows dense sampling of information at a protein level and in a high-throughput fashion. Although several groups have used this technology to study biological systems (12, 14) and although standardized protocols have been published (15), lysate microarrays have not yet gained wide-spread adoption, largel...

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“…Beyond the RPPA community, these data are of interest for many laboratories and many applications. Although validated antibodies can only be considered as such in the samples (and under the conditions) that they have been tested in, an antibody that performs well in a particular context is more likely to give satisfactory results in other assays (59). It is also likely that the RPPA format and experimental conditions utilized could alter the validity of particular antibody reagents.…”

“…Such datasets are ideally suited to building more accurate mathematical models that can be used to predict how dynamic remodeling of pathway networks can modify cell function (74). However, the number of samples easily exceeds 1000 in these types of analyses (59,75). RPPA is currently the only technology capable of analyzing protein pathways in such large series of samples simultaneously, and the RPPA technology provides a tremendous contribution to our systems biology modeling of cancer based on network models (76 -80) and can serve to validate the integrity of established mathematical models (81).…”

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“…This omission reduces assay time but also can increase non-specific antibody binding, which limits dynamic range and assay sensitivity. Thus, antibodies used in RPPA need to be carefully validated [19,20]. A modification to the RPPA method that may improve sensitivity is the micro-western array [21].…”

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“…There is great potential in the application of 'reverse-phase' protein microarray (RPPA) technology for multiplexed analysis of signalling pathways and their chemical modulation [1,2].…”