Profiling Cellular Protein Complexes by Proximity Ligation with Dual Tag Microarray Readout Maria Hammond . , Rachel Yuan Nong . , Olle Ericsson¤a, Katerina Pardali¤b, Ulf Landegren* Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden Abstract Patterns of protein interactions provide important insights in basic biology, and their analysis plays an increasing role in drug development and diagnostics of disease. We have established a scalable technique to compare two biological samples for the levels of all pairwise interactions among a set of targeted protein molecules. The technique is a combination of the proximity ligation assay with readout via dual tag microarrays. In the proximity ligation assay protein identities are encoded as DNA sequences by attaching DNA oligonucleotides to antibodies directed against the proteins of interest. Upon binding by pairs of antibodies to proteins present in the same molecular complexes, ligation reactions give rise to reporter DNA molecules that contain the combined sequence information from the two DNA strands. The ligation reactions also serve to incorporate a sample barcode in the reporter molecules to allow for direct comparison between pairs of samples. The samples are evaluated using a dual tag microarray where information is decoded, revealing which pairs of tags that have become joined. As a proof-of-concept we demonstrate that this approach can be used to detect a set of five proteins and their pairwise interactions both in cellular lysates and in fixed tissue culture cells. This paper provides a general strategy to analyze the extent of any pairwise interactions in large sets of molecules by decoding reporter DNA strands that identify the interacting molecules. Citation: Hammond M, Nong RY, Ericsson O, Pardali K, Landegren U (2012) Profiling Cellular Protein Complexes by Proximity Ligation with Dual Tag Microarray Readout. PLoS ONE 7(7): e40405. doi:10.1371/journal.pone.0040405 Editor: Pierre-Antoine Defossez, Universite´ Paris-Diderot, France Received February 27, 2012; Accepted June 6, 2012; Published July 10, 2012 Copyright: 2012 Hammond et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the National Institutes of Health/National Cancer Institute grant 1R21CA126727-01A1 and by funding from the Knut and Alice Wallenberg Foundation, as well as by the Swedish Research Council, Uppsala Berzelii Technology Centre for Neurodiagnostics, and the European Community’s Sixth and Seventh Framework Programs. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: UL holds stock in Olink Bioscience, having rights to the proximity ligation technique. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials. * E-mail: Ulf.Landegren@igp.uu.se . These authors contributed equally to this work. ¤a Current address: Agilent Technologies, Santa Clara, California, United States of America ¤b Current address: Respiratory and Inflammation iMed, AstraZeneca, Mo¨ lndal, Sweden Introduction It is likely that future protein biomarkers will be selected from a far wider repertoire of molecular entities than those currently in focus. For example, it is of growing interest to distinguish protein isoforms that arise due to splicing, processing, or posttranslational modifications and that may have drastically different functions. Another emerging class of targets for protein analysis in basic research and to diagnose disease states and responses to therapy, are sets of interacting proteins, jointly executing various cellular functions [1]. Improved methods are therefore needed to search for proteins as well as their modifications and interactions, in order to investigate the predictive and diagnostic value of these molecular features in patient samples. Most methods developed to study protein-protein interactions require genetic modification of proteins of interest to generate a detectable signal. The methods are therefore limited to research applications and cannot be applied for clinical samples. Immuno- fluorescence with two dye-labeled antibodies co-localizing as revealed via Fo¨rster resonance energy transfer (FRET) between the dyes can be used to analyze native proteins, however the method has a low signal to noise ratio, complicating analyses of patient samples. Moreover, with FRET only single interactions can be targeted in each analysis [2–4]. The VeraTag test is in use to investigate interactions among Her2 protein molecules in e.g. breast tumors, and it involves a pair of antibodies each linked to a fluorescent reporter and a photosensitizer molecule, respectively [5]. Upon photoactivation, the photosensitizer molecules cleave reporters in close proximity via the generated free radical oxygen. The liberated reporters are then recorded and used to quantify an average concentration of interacting target molecules in the sample. For multiplex studies of interactions among endogenous proteins the gold standard method has so far involved a combination of co-immunoprecipitation (Co-IP) followed by western blot or mass spectrometry, to look for interaction partners of a targeted protein. In order to carry out such experiments relatively large amounts of cells or tissues have to be lysed, disrupting cellular structures and local protein compartmentaliza- tion, potentially causing weakly interacting proteins to fall apart. A method called interaction-dependent PCR (IDPCR) was recently developed by McGregor et al. [6] to detect interactions between ligands and targets in libraries of small molecules. The use of DNA barcodes overcame limitations in multiplexing for both bait and prey libraries and thus binary interactions between any PLoS ONE | www.plosone.org 1 July 2012 | Volume 7 | Issue 7 | e40405