[show abstract][hide abstract] ABSTRACT: Human T-cell leukemia virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar to HTLV-1, causes no known overt disease. HTLV gene products are engaged in a dynamic struggle of activating and antagonistic interactions with host cells. Investigations focused on one or a few genes have identified several human factors interacting with HTLV viral proteins. Most of the available interaction data concern the highly investigated HTLV-1 Tax protein. Identifying shared and distinct host-pathogen protein interaction profiles for these two viruses would enlighten how they exploit distinctive or common strategies to subvert cellular pathways toward disease progression.
We employ a scalable methodology for the systematic mapping and comparison of pathogen-host protein interactions that includes stringent yeast two-hybrid screening and systematic retest, as well as two independent validations through an additional protein interaction detection method and a functional transactivation assay. The final data set contained 166 interactions between 10 viral proteins and 122 human proteins. Among the 166 interactions identified, 87 and 79 involved HTLV-1 and HTLV-2 -encoded proteins, respectively. Targets for HTLV-1 and HTLV-2 proteins implicate a diverse set of cellular processes including the ubiquitin-proteasome system, the apoptosis, different cancer pathways and the Notch signaling pathway.
This study constitutes a first pass, with homogeneous data, at comparative analysis of host targets for HTLV-1 and -2 retroviruses, complements currently existing data for formulation of systems biology models of retroviral induced diseases and presents new insights on biological pathways involved in retroviral infection.
[show abstract][hide abstract] ABSTRACT: Next-generation sequencing has not been applied to protein-protein interactome network mapping so far because the association between the members of each interacting pair would not be maintained in en masse sequencing. We describe a massively parallel interactome-mapping pipeline, Stitch-seq, that combines PCR stitching with next-generation sequencing and used it to generate a new human interactome dataset. Stitch-seq is applicable to various interaction assays and should help expand interactome network mapping.
[show abstract][hide abstract] ABSTRACT: "Smart-pooling," in which test reagents are multiplexed in a highly redundant manner, is a promising strategy for achieving high efficiency, sensitivity, and specificity in systems-level projects. However, previous applications relied on low redundancy designs that do not leverage the full potential of smart-pooling, and more powerful theoretical constructions, such as the Shifted Transversal Design (STD), lack experimental validation. Here we evaluate STD smart-pooling in yeast two-hybrid (Y2H) interactome mapping. We employed two STD designs and two established methods to perform ORFeome-wide Y2H screens with 12 baits. We found that STD pooling achieves similar levels of sensitivity and specificity as one-on-one array-based Y2H, while the costs and workloads are divided by three. The screening-sequencing approach is the most cost- and labor-efficient, yet STD identifies about twofold more interactions. Screening-sequencing remains an appropriate method for quickly producing low-coverage interactomes, while STD pooling appears as the method of choice for obtaining maps with higher coverage.
Genome Research 06/2009; 19(7):1262-9. · 14.40 Impact Factor
[show abstract][hide abstract] ABSTRACT: To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins
[show abstract][hide abstract] ABSTRACT: Several attempts have been made to systematically map protein-protein interaction, or 'interactome', networks. However, it remains difficult to assess the quality and coverage of existing data sets. Here we describe a framework that uses an empirically-based approach to rigorously dissect quality parameters of currently available human interactome maps. Our results indicate that high-throughput yeast two-hybrid (HT-Y2H) interactions for human proteins are more precise than literature-curated interactions supported by a single publication, suggesting that HT-Y2H is suitable to map a significant portion of the human interactome. We estimate that the human interactome contains approximately 130,000 binary interactions, most of which remain to be mapped. Similar to estimates of DNA sequence data quality and genome size early in the Human Genome Project, estimates of protein interaction data quality and interactome size are crucial to establish the magnitude of the task of comprehensive human interactome mapping and to elucidate a path toward this goal.
[show abstract][hide abstract] ABSTRACT: Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering approximately 20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.
[show abstract][hide abstract] ABSTRACT: The karyotypic chaos exhibited by human epithelial cancers complicates efforts to identify mutations critical for malignant transformation. Here we integrate complementary genomic approaches to identify human oncogenes. We show that activation of the ERK and phosphatidylinositol 3-kinase (PI3K) signaling pathways cooperate to transform human cells. Using a library of activated kinases, we identify several kinases that replace PI3K signaling and render cells tumorigenic. Whole genome structural analyses reveal that one of these kinases, IKBKE (IKKepsilon), is amplified and overexpressed in breast cancer cell lines and patient-derived tumors. Suppression of IKKepsilon expression in breast cancer cell lines that harbor IKBKE amplifications induces cell death. IKKepsilon activates the nuclear factor-kappaB (NF-kappaB) pathway in both cell lines and breast cancers. These observations suggest a mechanism for NF-kappaB activation in breast cancer, implicate the NF-kappaB pathway as a downstream mediator of PI3K, and provide a framework for integrated genomic approaches in oncogene discovery.
[show abstract][hide abstract] ABSTRACT: A comprehensive mapping of interactions among Epstein-Barr virus (EBV) proteins and interactions of EBV proteins with human proteins should provide specific hypotheses and a broad perspective on EBV strategies for replication and persistence. Interactions of EBV proteins with each other and with human proteins were assessed by using a stringent high-throughput yeast two-hybrid system. Overall, 43 interactions between EBV proteins and 173 interactions between EBV and human proteins were identified. EBV-EBV and EBV-human protein interaction, or "interactome" maps provided a framework for hypotheses of protein function. For example, LF2, an EBV protein of unknown function interacted with the EBV immediate early R transactivator (Rta) and was found to inhibit Rta transactivation. From a broader perspective, EBV genes can be divided into two evolutionary classes, "core" genes, which are conserved across all herpesviruses and subfamily specific, or "noncore" genes. Our EBV-EBV interactome map is enriched for interactions among proteins in the same evolutionary class. Furthermore, human proteins targeted by EBV proteins were enriched for highly connected or "hub" proteins and for proteins with relatively short paths to all other proteins in the human interactome network. Targeting of hubs might be an efficient mechanism for EBV reorganization of cellular processes.
Proceedings of the National Academy of Sciences 06/2007; 104(18):7606-11. · 9.74 Impact Factor
[show abstract][hide abstract] ABSTRACT: Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.
[show abstract][hide abstract] ABSTRACT: The recently completed Caenorhabditis elegans genome sequence allows application of high-throughput (HT) approaches for phenotypic analyses using RNA interference (RNAi). As large phenotypic data sets become available, "phenoclustering" strategies can be used to begin understanding the complex molecular networks involved in development and other biological processes. The current HT-RNAi resources represent a great asset for phenotypic profiling but are limited by lack of flexibility. For instance, existing resources do not take advantage of the latest improvements in RNAi technology, such as inducible hairpin RNAi. Here we show that a C. elegans ORFeome resource, generated with the Gateway cloning system, can be used as a starting point to generate alternative HT-RNAi resources with enhanced flexibility. The versatility inherent to the Gateway system suggests that additional HT-RNAi libraries can now be readily generated to perform gene knockdowns under various conditions, increasing the possibilities for phenome mapping in C. elegans.
Genome Research 11/2004; 14(10B):2162-8. · 14.40 Impact Factor
[show abstract][hide abstract] ABSTRACT: The advent of systems biology necessitates the cloning of nearly entire sets of protein-encoding open reading frames (ORFs), or ORFeomes, to allow functional studies of the corresponding proteomes. Here, we describe the generation of a first version of the human ORFeome using a newly improved Gateway recombinational cloning approach. Using the Mammalian Gene Collection (MGC) resource as a starting point, we report the successful cloning of 8076 human ORFs, representing at least 7263 human genes, as mini-pools of PCR-amplified products. These were assembled into the human ORFeome version 1.1 (hORFeome v1.1) collection. After assessing the overall quality of this version, we describe the use of hORFeome v1.1 for heterologous protein expression in two different expression systems at proteome scale. The hORFeome v1.1 represents a central resource for the cloning of large sets of human ORFs in various settings for functional proteomics of many types, and will serve as the foundation for subsequent improved versions of the human ORFeome.
Genome Research 11/2004; 14(10B):2128-35. · 14.40 Impact Factor
[show abstract][hide abstract] ABSTRACT: To initiate studies on how protein-protein interaction (or "interactome") networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together with already described Y2H interactions and interologs predicted in silico, the current version of the Worm Interactome (WI5) map contains approximately 5500 interactions. Topological and biological features of this interactome network, as well as its integration with phenome and transcriptome data sets, lead to numerous biological hypotheses.