A reference map of the human binary protein interactome.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes

Mapping and characterization of protein interactome networks

Numerous complex networks composed of diverse interactions, either physical interactions or functional associations, between macromolecules underlie most cellular functions. The sets of physical and functional associations are respectively defined as biophysical and genetic interactome networks. Mapping and characterizing biophysical and genetic interactome networks is necessary, albeit not sufficient, to understand complex genotype to phenotype relationships. However, as current individual interactome maps remain incomplete, their organization remains mysterious and the relationships between distinct maps are unclear. Moreover, understanding the nature of the interactions elucidated by each of these maps is essential to accurately interpret the functional relevance of their integration. Saccharomyces cerevisiae is one of the few organisms for which systematic genetic and biophysical maps have been generated at genome scale, making it possible to compare them. For my PhD thesis, my colleagues and I focused on protein interactome networks, and provided the first annotation of an expanded map of the yeast binary protein interactome. We first assessed the coverage of the yeast binary interactome network by generating an inventory of all protein-protein interactions reported in public repositories. Using comprehensive experimental validations, we identified and selected the datasets with a majority of binary direct interactions. Assembling a binary interactome network of only ~7,000 interactions from the literature highlighted the imperative need to systematically expand the coverage of the yeast binary interactome network. To that end, we expanded an available ORFeome collection, to assemble a nearly complete collection, and used it to systematically test all possible protein pairs to produce a new systematic binary map, YI-II. We revealed biological properties that govern the organization of the cellular interactome by integrating the expanded yeast binary interactome map with genetic network maps. Our results support recent observations, that the majority of interactions in the interactome are likely of a different nature, with most being more transient, potentially involved in context-specific regulatory processes. An understanding of the properties that govern integration of genetic and biophysical maps, as provided by this study, would be key to not only understand known genotype to phenotype relationships but identify novel ones

Towards a yeast reference interactome

Despite an increasing number of interactomic datasets already available for model organisms and humans, many aspects remain contradictory, debatable or unclear due to the lack of complete high-quality networks. It has, for instance, been proposed that macromolecule connectivity in interactome maps reflects functional importance, functional relatedness, pleiotropy, implication in diseases, and other important biological characteristics. The most notorious example of such relationships concerns so-called essential genes believed to correspond to highly connected hubs that are critical to network integrity. Such claims have led to debate in the literature because connectivity could also be explained by bias and uneven coverage of the interactome space. To provide fresh insight into these questions, we produced a new, systematic interactome map for S. cerevisiae, organism for which a plethora of systematic interactomic and functional data is available. This alternative view of the interactome network was generated by modifying our screening pipeline based on our empirically-controlled framework. Using a new high-quality ORFeome collection and a new assay version, we systematically performed three replicate yeast-two hybrid screens. This produced a map of 1,200 protein-protein interactions, which, while of similar size as previously published interactome maps, covers the entire proteome without bias. These interactions were subsequently successfully validated using an orthogonal protein complementation assay based on a split Gaussia princeps luciferase. The latest analyses of this new map and progress towards generating a first Yeast Reference Interactome map will be presented

Mapping, modeling, and characterization of protein–protein interactions on a proteomic scale

Proteins effect a number of biological functions, from cellular signaling, organization, mobility, and transport to catalyzing biochemical reactions and coordinating an immune response. These varied functions are often dependent upon macromolecular interactions, particularly with other proteins. Small-scale studies in the scientific literature report protein–protein interactions (PPIs), but slowly and with bias towards well-studied proteins. In an era where genomic sequence is readily available, deducing genotype–phenotype relationships requires an understanding of protein connectivity at proteome-scale. A proteome-scale map of the protein–protein interaction network provides a global view of cellular organization and function. Here, we discuss a summary of methods for building proteome-scale interactome maps and the current status and implications of mapping achievements. Not only do interactome maps serve as a reference, detailing global cellular function and organization patterns, but they can also reveal the mechanisms altered by disease alleles, highlight the patterns of interaction rewiring across evolution, and help pinpoint biologically and therapeutically relevant proteins. Despite the considerable strides made in proteome-wide mapping, several technical challenges persist. Therefore, future considerations that impact current mapping efforts are also discussed.Mapping, modeling, and characterization of protein–protein interactions on a proteomic scal

microRNA expression in autonomous thyroid adenomas: Correlation with mRNA regulation.

The objective of the study was to identify the deregulated miRNA in autonomous adenoma and to correlate the data with mRNA regulation. Seven autonomous adenoma with adjacent healthy thyroid tissues were investigated. Twelve miRNAs were downregulated and one was upregulated in the tumors. Combining bioinformatic mRNA target prediction and microarray data on mRNA regulations allowed to identify mRNA targets of our deregulated miRNAs. A large enrichment in mRNA encoding proteins involved in extracellular matrix organization and different phosphodiesterases were identified among these putative targets. The direct interaction between miR-101-3p and miR-144-3p and PDE4D mRNA was experimentally validated. The global miRNA profiles were not greatly modified, confirming the definition of these tumors as minimal deviation tumors. These results support a role for miRNA in the regulation of extracellular matrix proteins and tissue remodeling occurring during tumor development, and in the important negative feedback of the cAMP pathway, which limits the consequences of its constitutive activation in these tumors.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

miRNA expression in anaplastic thyroid carcinomas.

Anaplastic thyroid carcinoma (ATC) is the most lethal form of thyroid neoplasia and represents an end stage of thyroid tumor progression. No effective treatment exists so far. In this study, we analyzed the miRNA expression profiles of 11 ATC by microarrays and their relationship with the mRNA expression profiles of the same 11 ATC samples. ATC show distinct miRNA expression profiles compared to other less aggressive thyroid tumor types. ATC show 18 commonly deregulated miRNA compared to normal thyroid tissue (17 downregulated and 1 upregulated miRNA). First, the analysis of a combined approach of the mRNA gene expression and of the bioinformatically predicted mRNA targets of the deregulated miRNA suggested a role for these regulations in the epithelial to mesenchymal transition (EMT) process in ATC. Second, the direct interaction between one of the upregulated mRNA target, the LOX gene which is an EMT key player, and a downregulated miRNA, the miR-29a, was experimentally validated by a luciferase assay in HEK cell. Third, we confirmed that the ATC tissue is composed of about 50% of tumor associated macrophages (TAM) and suggested, by taking into account our data and published data, their most likely direct or paracrine intercommunication between them and the thyroid tumor cells, amplifying the tumor aggressiveness. Finally, we demonstrated by in situ hybridization a specific thyrocyte localization of 3 of the deregulated miRNA: let-7g, miR-29a and miR-30e and we pointed out the importance of identifying the cell type localization before drawing any conclusion on the physiopathological role of a given gene.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Immunohistochemistry with the CD163 antibody on 3 different ATC and on normal thyroid tissue.

<p>a, b, c: 20× magnification showing that about 50% of the nucleated cells are TAM, d: 40× magnification showing elongated cytoplasmic extensions in TAM as illustrated by the red arrows; e: 20× magnification illustrating the almost absence of TAM in normal thyroid tissue.</p

Normalized luciferase activity in HEK293 cells cotransfected during 24 h or 48 h with the 3′UTR-LOX construction or with the mutated construction (3′UTR-LOX mutated: partial deletion of the seed sequence) and with miR-29a or with the scramble.

<p>The seed sequence is represented in blue and the * indicates a p-value<5%.</p

Proposed scheme synthetizing the miRNA and mRNA expression analyses of the same 11 ATC and highlighting the EMT feature of this tumor.

<p>Only direct binding of miRNA on mRNA are represented (green: downregulated m(i)RNA; red: upregulated m(i)RNA.</p