factors in a binary fashion. Chinenov and Kerppola comprehen- sively collected reported Jun-interactors in their review, and the number of mammalian Jun-interactors was 51 at that time [27]. Of the 51 interactors, some lack the potential to bind with the bait Jun protein in our experiment for various reasons. For example, the SMAD interacting region of Jun [28] was deleted from our bait protein construct, and NFAT family proteins require a DNA fragment including the AP-1 sequence [TGA(C/G)TCA] and NFAT recognition element (GGAAAA) for stable interaction with Jun [29]. Also, the expression of some of the interactors, e.g., JunD, Fra1, Batf, MafA, Nrl and NF-IL16, was not confirmed in the cDNA library used in this study (data not shown). In all, 29 Jun- interactors were expressed in the cDNA library and were expected to bind with the bait Jun protein used here. Of these 29 proteins, four (14%) and eight (28%) were detected by the conventional sequencing and by the newly introduced TFT array method, respectively. This is a remarkable increase and confirms the value of our new methodology as a screening tool for protein interactions. While the coverage was increased considerably, the accuracy did not decrease. Specifically, the number of false positives did not increase: the rates of confirmation of proteins by in vitro pull-down assays in the previous and present studies were 75% and 74%, respectively. Further, we confirmed by SPR that most of the unbound candidates in the pull-down assay actually interacted with Jun. These results indicate that generation of false positives in this novel method is low, and that the method is practical. Undetected remaining interactors were considered to be false negatives. Mismatching of the selection conditions, e.g., salts, detergents, and pH, or the bait construct, e.g., length, region, and tags, might inhibit these interactions. For quantitative analysis, the abundance ratios of 35 specifically selected candidates in the initial and screened cDNA libraries were determined by real-time PCR, and the enrichment rates (abundance ratio in the 5th round library per that in the initial library) were also calculated (Table 1). The abundance of the 15 newly found candidates (excluding c-Maf, Cutl1 and Ofd1) was less than the theoretical threshold determined from the results of our previous study (an analysis of 451 clones) [21,22]. In order to detect the least abundant candidate (Myt1; 1.361024% of the screened cDNA library) by cloning and sequencing, it would have been necessary to analyze at least 1.06106 clones. These results indicate that our new method is more sensitive, higher-throughput and more cost-effective than the previous method. From the standpoint of the detection sensitivity, the combinatorial use of the IVV method with TFT arrays provides an extremely sensitive method for protein-interaction analysis, because even a very weakly expressed target, Atf3, could be detected in this study. In the cDNA library before IVV screening, the content of fragments of the selected region of Atf3 was 1.261027%. If one mRNA molecule existed per cell, the content of a fragment of the gene would be about 1.261025 to 5.961025% (we employed the parameters from a reference for this calculation [30], and the details are given in Methods S1 online). Thus, the content of Atf3 mRNA in the initial library corresponds to about one molecule per 20 to 100 cells. This suggests that Atf3 is expressed at a very low level in a cell type that is a minor component of whole mouse brain tissue. It is noteworthy that targets expressed at such low levels can be detected without the need for a cell purification procedure, e.g., collection of somatic stem cells by flow cytometry. The high sensitivity of our method may allow access to targets which would be hard to analyze with other existing tools, e.g., the TAP method [18]. Among the newly detected Jun-associated protein candidates, Cebpg, Creb3, and Tef are intriguing proteins as Jun-associated transcriptional regulators, because they contain basic regions near Tiling Arrays for mRNA Display the leucine heptad motifs, which are necessary for binding with regulatory sequences on the genomic DNA; many known Jun- associated proteins contain such structures. Cebeg is a member of the CAAT/enhancer-binding protein (C/EBP) family, which is one of the largest and most highly conserved groups of eukaryotic transcription factors. Cebpg is known to interact with Cebpb, a member of the C/EBP family, but the function of the protein is not well understood [31]. Davydov et al. indicated that Cebpg binds to the positive regulatory element-I (PRE-I) of the human interleukin-4 gene by forming a heterodimer with Fos protein. However, the interaction between Cebpg and Jun was not clearly delineated [32]. Creb3 is also a transcriptional regulator belonging to the cyclic AMP response element-binding (CREB)/activating transcription factor (ATF) protein family. The bZIP region of Creb3 is strikingly similar to that of ATFa, a known partner of Jun [33]. Tef is a member of the proline and acidic amino acid-rich basic leucine zipper (PAR bZIP) transcription factor family. The PAR bZIP proteins control circadian rhythms in tissues such as the suprachi- asmatic nucleus and the liver. Mice deficient in all three PAR bZIP proteins are highly susceptible to generalized spontaneous and audiogenic epilepsies that are frequently lethal [34]. No information is available about the functional relationship between Tef and Jun. More detailed studies in vivo may reveal novel and unexpected functions of Jun in combination with these proteins. In summary, we have applied tiling array technology, which has previously been used for ChIP-chip assays [26] and transcriptome analyses [20], to protein-interaction analysis with an in vitro display technique for the first time. Compared with previous results obtained with cloning and sequencing [21,22], use of the tiling array greatly increased the coverage of known Jun-interactors from 14% to 28% without any decrease of accuracy (,75%). The new method can also detect targets expressed at extremely low levels. We believe that this highly sensitive and reliable method has the potential to be used widely, because the tiling array method can easily be extended to genome-wide scale, even though the search space is limited in tiled sequences, and the method can also be used in combination with other display technologies, such as phage display and ribosome display. Supporting Information Data S1 All ratio data from the tiling arrays Found at: doi:10.1371/journal.pone.0001646.s001 (2.36 MB ZIP) Figure S1 Signal ratio and peak data of selected candidates Found at: doi:10.1371/journal.pone.0001646.s002 (2.14 MB PDF) Figure S2 In vitro pull-down assay Found at: doi:10.1371/journal.pone.0001646.s003 (1.80 PDF) Figure S3 SPR analysis Found at: doi:10.1371/journal.pone.0001646.s004 (0.46 PDF) Table S1 All detected reproducible signal peaks Found at: doi:10.1371/journal.pone.0001646.s005 (0.09 XLS) Table S2 Oligonucleotides for PCR Found at: doi:10.1371/journal.pone.0001646.s006 (0.16 DOC) Methods S1 Found at: doi:10.1371/journal.pone.0001646.s007 (0.05 DOC) MB MB MB MB MB PLoS ONE | www.plosone.org 5 February 2008 | Volume 3 | Issue 2 | e1646