We have identified nine oligopeptide transporter (OPT) orthologs (AtOPT1 to AtOPT9) in Arabidopsis. These proteins show significant sequence similarity to OPTs of Candida albicans (CaOpt1p),Schizosaccharomyces pombe (Isp4p), andSaccharomyces cerevisiae (Opt1p and Opt2p). Hydrophilicity plots of the OPTs suggest that they are integral membrane proteins with 12 to 14 transmembrane domains. Sequence comparisons showed that the AtOPTs form a distinct subfamily when compared with the fungal OPTs. Two highly conserved motifs (NPG and KIPPR) were found among all OPT members. The identification of multiple OPTs in Arabidopsis suggests that they may play different functional roles. This idea is supported by the fact that AtOPTs have a distinct, tissue-specific expression pattern. The cDNAs encoding seven of the AtOPTs were cloned into a yeast vector under the control of a constitutive promoter. AtOPT4 expressed in S. cerevisiae mediated the uptake of KLG-[3H]L. Similarly, expression of five of the seven AtOPT proteins expressed in yeast conferred the ability to uptake tetra- and pentapeptides as measured by growth. This study provides new evidence for multiple peptide transporter systems in Arabidopsis, suggesting an important physiological role for small peptides in plants.

Damage initiates a pleiotropic cellular response aimed at cellular survival when appropriate. To identify genes required for damage survival, we used a cell-based RNAi screen against the Drosophila genome and the alkylating agent methyl methanesulphonate (MMS). Similar studies performed in other model organisms report that damage response may involve pleiotropic cellular processes other than the central DNA repair components, yet an intuitive systems level view of the cellular components required for damage survival, their interrelationship, and contextual importance has been lacking. Further, by comparing data from different model organisms, identification of conserved and presumably core survival components should be forthcoming. We identified 307 genes, representing 13 signaling, metabolic, or enzymatic pathways, affecting cellular survival of MMS–induced damage. As expected, the majority of these pathways are involved in DNA repair; however, several pathways with more diverse biological functions were also identified, including the TOR pathway, transcription, translation, proteasome, glutathione synthesis, ATP synthesis, and Notch signaling, and these were equally important in damage survival. Comparison with genomic screen data from Saccharomyces cerevisiae revealed no overlap enrichment of individual genes between the species, but a conservation of the pathways. To demonstrate the functional conservation of pathways, five were tested in Drosophila and mouse cells, with each pathway responding to alkylation damage in both species. Using the protein interactome, a significant level of connectivity was observed between Drosophila MMS survival proteins, suggesting a higher order relationship. This connectivity was dramatically improved by incorporating the components of the 13 identified pathways within the network. Grouping proteins into “pathway nodes” qualitatively improved the interactome organization, revealing a highly organized “MMS survival network.” We conclude that identification of pathways can facilitate comparative biology analysis when direct gene/orthologue comparisons fail. A biologically intuitive, highly interconnected MMS survival network was revealed after we incorporated pathway data in our interactome analysis.

BackgroundA genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast) and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species.ResultsThe connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen) and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced.ConclusionsProtein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

Small peptides (2-5 amino acid residues) are transported into Saccharomyces cerevisiae via two transport systems: PTR (Peptide TRansport) for di-/tripeptides and OPT (OligoPeptide Transport) for oligopeptides of 4-5 amino acids in length. Although regulation of the PTR system has been studied in some detail, neither the regulation of the OPT family nor the environmental conditions under which family members are normally expressed have been well studied in S. cerevisiae. Using a lacZ reporter gene construct fused to 1 kb DNA from upstream of the genes OPT1 and OPT2, which encode the two S. cerevisiae oligopeptide transporters, the relative expression levels of these genes were measured in a variety of environmental conditions. Uptake assays were also conducted to measure functional protein levels at the plasma membrane. It was found that OPT1 was up-regulated in sulfur-free medium, and that Ptr3p and Ssy1p, proteins involved in regulating the di-/tripeptide transporter encoding gene PTR2 via amino acid sensing, were required for OPT1 expression in a sulfur-free environment. In contrast, as measured by response to toxic tetrapeptide and by real-time PCR, OPT1 was not regulated through Cup9p, which is a repressor for PTR2 expression, although Cup9p did repress OPT2 expression. In addition, all of the 20 naturally occurring amino acids, except the sulfur-containing amino acids methionine and cysteine, up-regulated OPT1, with the greatest change in expression observed when cells were grown in sulfur-free medium. These data demonstrate that regulation of the OPT system has both similarities and differences to regulation of the PTR system, allowing the yeast cell to adapt its utilization of small peptides to various environmental conditions.

Genome-wide RNA interference (RNAi) screening allows investigation of the role of individual genes in a process of choice. Most RNAi screens identify a large number of genes with a continuous gradient in the assessed phenotype. Screeners must decide whether to examine genes with the most robust phenotype or the full gradient of genes that cause an effect and how to identify candidate genes. The authors have used RNAi in Drosophila cells to examine viability in a 384-well plate format and compare 2 screens, untreated control and treatment. They compare multiple normalization methods, which take advantage of different features within the data, including quantile normalization, background subtraction, scaling, cellHTS2 (Boutros et al. 2006), and interquartile range measurement. Considering the false-positive potential that arises from RNAi technology, a robust validation method was designed for the purpose of gene selection for future investigations. In a retrospective analysis, the authors describe the use of validation data to evaluate each normalization method. Although no method worked ideally, a combination of 2 methods, background subtraction followed by quantile normalization and cellHTS2, at different thresholds, captures the most dependable and diverse candidate genes. Thresholds are suggested depending on whether a few candidate genes are desired or a more extensive systems-level analysis is sought. The normalization approaches and experimental design to perform validation experiments are likely to apply to those high-throughput screening systems attempting to identify genes for systems-level analysis. 1 Its compatibility with high-throughput technology 2 has revolutionized the quest for identification of novel genes in signal transduction pathways, human diseases, and drug targets. 1,3,4 Publications from analysis of these types of screens are constantly being added to the literature, with relatively few publications addressing experimental design and data analysis. Although publications have addressed general protocols and logical approaches for gene selection 5 or have introduced novel methods of data analysis and criteria for assessment of quality , 6 there is a lack of data in the literature to compare and contrast data analysis methods and a lack of design of rigorous validation methods. Because RNAi-based screening is a labor-intensive technology involving complex experimental setup, because there is a deficiency of appropriate standards and the current analytical tools are relatively limited, we address some of the deficiencies related to appropriate experimental design for Drosophila RNAi genomic screening, examine the available analytical methods, and develop a rigorous validation scheme. METHODS Tissue cultureKc 167 cells were grown in Schneider medium (Invitrogen, Carlsbad, CA) supplemented with 10% heat-inactivated fetal bovine serum (FBS; 65 °C, 10 min), 100 U/mL penicillin, and 100 μg/mL streptomycin, at 24 °C in a humidified chamber. One hour at 24 °C allowed phagocytic uptake of the dsR...