In Depth Exploration of the Alternative Proteome of Drosophila melanogaster.

Recent studies have shown that hundreds of small proteins were occulted when protein-coding genes were annotated. These proteins, called alternative proteins, have failed to be annotated notably due to the short length of their open reading frame (less than 100 codons) or the enforced rule establishing that messenger RNAs (mRNAs) are monocistronic. Several alternative proteins were shown to be biologically active molecules and seem to be involved in a wide range of biological functions. However, genome-wide exploration of the alternative proteome is still limited to a few species. In the present article, we describe a deep peptidomics workflow which enabled the identification of 401 alternative proteins in Drosophila melanogaster. Subcellular localization, protein domains, and short linear motifs were predicted for 235 of the alternative proteins identified and point toward specific functions of these small proteins. Several alternative proteins had approximated abundances higher than their canonical counterparts, suggesting that these alternative proteins are actually the main products of their corresponding genes. Finally, we observed 14 alternative proteins with developmentally regulated expression patterns and 10 induced upon the heat-shock treatment of embryos, demonstrating stage or stress-specific production of alternative proteins.

Genetic Predisposition to the Mortality in Septic Shock Patients: From GWAS to the Identification of a Regulatory Variant Modulating the Activity of a CISH Enhancer.

The high mortality rate in septic shock patients is likely due to environmental and genetic factors, which influence the host response to infection. Two genome-wide association studies (GWAS) on 832 septic shock patients were performed. We used integrative bioinformatic approaches to annotate and prioritize the sepsis-associated single nucleotide polymorphisms (SNPs). An association of 139 SNPs with death based on a false discovery rate of 5% was detected. The most significant SNPs were within the CISH gene involved in cytokine regulation. Among the 139 SNPs associated with death and the 1311 SNPs in strong linkage disequilibrium with them, we investigated 1439 SNPs within non-coding regions to identify regulatory variants. The highest integrative weighted score (IW-score) was obtained for rs143356980, indicating that this SNP is a robust regulatory candidate. The rs143356980 region is located in a non-coding region close to the CISH gene. A CRISPR-Cas9-mediated deletion of this region and specific luciferase assays in K562 cells showed that rs143356980 modulates the enhancer activity in K562 cells. These analyses allowed us to identify several genes associated with death in patients with septic shock. They suggest that genetic variations in key genes, such as CISH, perturb relevant pathways, increasing the risk of death in sepsis patients.

In utero exposure to acetaminophen and ibuprofen leads to intergenerational accelerated reproductive aging in female mice.

Nonsteroidal anti-inflammatory drugs (NSAIDs) and analgesic drugs, such as acetaminophen (APAP), are frequently taken during pregnancy, even in combination. However, they can favour genital malformations in newborn boys and reproductive disorders in adults. Conversely, the consequences on postnatal ovarian development and female reproductive health after in utero exposure are unknown. Here, we found that in mice, in utero exposure to therapeutic doses of the APAP-ibuprofen combination during sex determination led to delayed meiosis entry and progression in female F1 embryonic germ cells. Consequently, follicular activation was reduced in postnatal ovaries through the AKT/FOXO3 pathway, leading in F2 animals to subfertility, accelerated ovarian aging with abnormal corpus luteum persistence, due to decreased apoptosis and increased AKT-mediated luteal cell survival. Our study suggests that administration of these drugs during the critical period of sex determination could lead in humans to adverse effects that might be passed to the offspring.

Understanding protein multifunctionality: from short linear motifs to cellular functions.

Moonlighting proteins perform multiple unrelated functions without any change in polypeptide sequence. They can coordinate cellular activities, serving as switches between pathways and helping to respond to changes in the cellular environment. Therefore, regulation of the multiple protein activities, in space and time, is likely to be important for the homeostasis of biological systems. Some moonlighting proteins may perform their multiple functions simultaneously while others alternate between functions due to certain triggers. The switch of the moonlighting protein's functions can be regulated by several distinct factors, including the binding of other molecules such as proteins. We here review the approaches used to identify moonlighting proteins and existing repositories. We particularly emphasise the role played by short linear motifs and PTMs as regulatory switches of moonlighting functions.

Perturbed human sub-networks by Fusobacterium nucleatum candidate virulence proteins.

BACKGROUND: Fusobacterium nucleatum is a gram-negative anaerobic species residing in the oral cavity and implicated in several inflammatory processes in the human body. Although F. nucleatum abundance is increased in inflammatory bowel disease subjects and is prevalent in colorectal cancer patients, the causal role of the bacterium in gastrointestinal disorders and the mechanistic details of host cell functions subversion are not fully understood. RESULTS: We devised a computational strategy to identify putative secreted F. nucleatum proteins (FusoSecretome) and to infer their interactions with human proteins based on the presence of host molecular mimicry elements. FusoSecretome proteins share similar features with known bacterial virulence factors thereby highlighting their pathogenic potential. We show that they interact with human proteins that participate in infection-related cellular processes and localize in established cellular districts of the host-pathogen interface. Our network-based analysis identified 31 functional modules in the human interactome preferentially targeted by 138 FusoSecretome proteins, among which we selected 26 as main candidate virulence proteins, representing both putative and known virulence proteins. Finally, six of the preferentially targeted functional modules are implicated in the onset and progression of inflammatory bowel diseases and colorectal cancer. CONCLUSIONS: Overall, our computational analysis identified candidate virulence proteins potentially involved in the F. nucleatum-human cross-talk in the context of gastrointestinal diseases.

Cancer-associated fibroblast-derived annexin A6+ extracellular vesicles support pancreatic cancer aggressiveness.

The intratumoral microenvironment, or stroma, is of major importance in the pathobiology of pancreatic ductal adenocarcinoma (PDA), and specific conditions in the stroma may promote increased cancer aggressiveness. We hypothesized that this heterogeneous and evolving compartment drastically influences tumor cell abilities, which in turn influences PDA aggressiveness through crosstalk that is mediated by extracellular vesicles (EVs). Here, we have analyzed the PDA proteomic stromal signature and identified a contribution of the annexin A6/LDL receptor-related protein 1/thrombospondin 1 (ANXA6/LRP1/TSP1) complex in tumor cell crosstalk. Formation of the ANXA6/LRP1/TSP1 complex was restricted to cancer-associated fibroblasts (CAFs) and required physiopathologic culture conditions that improved tumor cell survival and migration. Increased PDA aggressiveness was dependent on tumor cell-mediated uptake of CAF-derived ANXA6+ EVs carrying the ANXA6/LRP1/TSP1 complex. Depletion of ANXA6 in CAFs impaired complex formation and subsequently impaired PDA and metastasis occurrence, while injection of CAF-derived ANXA6+ EVs enhanced tumorigenesis. We found that the presence of ANXA6+ EVs in serum was restricted to PDA patients and represents a potential biomarker for PDA grade. These findings suggest that CAF-tumor cell crosstalk supported by ANXA6+ EVs is predictive of PDA aggressiveness, highlighting a therapeutic target and potential biomarker for PDA.

Integration of quantitative proteomics data and interaction networks: Identification of dysregulated cellular functions during cancer progression.

Quantitative proteomics allows the characterization of molecular changes between healthy and disease states. To interpret such datasets, their integration to the protein-protein interaction network provides a more comprehensive understanding of cellular function dysregulation in diseases than just considering lists of dysregulated proteins. Here, we propose a novel computational method, which combines protein interaction network and statistical analyses to establish expression profiles at the network module level rather than at the individual protein level, and to detect and characterize dysregulated network modules through different stages of cancer progression. We applied our approach to two publicly available datasets as case studies.

The functional landscape of Hsp27 reveals new cellular processes such as DNA repair and alternative splicing and proposes novel anticancer targets.

Previously, we identified the stress-induced chaperone, Hsp27, as highly overexpressed in castration-resistant prostate cancer and developed an Hsp27 inhibitor (OGX-427) currently tested in phase I/II clinical trials as a chemosensitizing agent in different cancers. To better understand the Hsp27 poorly-defined cytoprotective functions in cancers and increase the OGX-427 pharmacological safety, we established the Hsp27-protein interaction network using a yeast two-hybrid approach and identified 226 interaction partners. As an example, we showed that targeting Hsp27 interaction with TCTP, a partner protein identified in our screen increases therapy sensitivity, opening a new promising field of research for therapeutic approaches that could decrease or abolish toxicity for normal cells. Results of an in-depth bioinformatics network analysis allying the Hsp27 interaction map into the human interactome underlined the multifunctional character of this protein. We identified interactions of Hsp27 with proteins involved in eight well known functions previously related to Hsp27 and uncovered 17 potential new ones, such as DNA repair and RNA splicing. Validation of Hsp27 involvement in both processes in human prostate cancer cells supports our system biology-predicted functions and provides new insights into Hsp27 roles in cancer cells.

In silico prediction of protein-protein interactions in human macrophages.

BACKGROUND: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. RESULTS: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. CONCLUSION: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.

Met acts through Abl to regulate p53 transcriptional outcomes and cell survival in the developing liver.

BACKGROUND & AIMS: Genetic studies indicate that distinct signaling modulators are each necessary but not individually sufficient for embryonic hepatocyte survival in vivo. Nevertheless, how signaling players are interconnected into functional circuits and how they coordinate the balance of cell survival and death in developing livers are still major unresolved issues. In the present study, we examined the modulation of the p53 pathway by HGF/Met in embryonic livers. METHODS: We combined pharmacological and genetic approaches to biochemically and functionally evaluate p53 pathway modulation in primary embryonic hepatocytes and in developing livers. RT-PCR arrays were applied to investigate the selectivity of p53 transcriptional response triggered by Met. RESULTS: Met recruits p53 to regulate the liver developmental program, by qualitatively modulating its transcriptional properties: turning on the Mdm2 survival gene, while keeping death and cell-cycle arrest genes Pmaip1 and p21 silent. We investigated the mechanism leading to p53 regulation by Met and found that Abl and p38MAPK are required for p53 phosphorylation on S(389), Mdm2 upregulation, and hepatocyte survival. Alteration of this signaling mechanism switches p53 properties, leading to p53-dependent cell death in embryonic livers. RT-PCR array studies affirmed the ability of the Met-Abl-p53 axis to modulate the expression of distinct genes that can be regulated by p53. CONCLUSIONS: A signaling circuit involving Abl and p38MAPK is required downstream of Met for the survival of embryonic hepatocytes, via qualitative regulation of the p53 transcriptional response, by switching its proapoptotic into survival properties.

Insights into Hox protein function from a large scale combinatorial analysis of protein domains.

Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA), we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences.

Interactome mapping of the phosphatidylinositol 3-kinase-mammalian target of rapamycin pathway identifies deformed epidermal autoregulatory factor-1 as a new glycogen synthase kinase-3 interactor.

The phosphatidylinositol 3-kinase-mammalian target of rapamycin (PI3K-mTOR) pathway plays pivotal roles in cell survival, growth, and proliferation downstream of growth factors. Its perturbations are associated with cancer progression, type 2 diabetes, and neurological disorders. To better understand the mechanisms of action and regulation of this pathway, we initiated a large scale yeast two-hybrid screen for 33 components of the PI3K-mTOR pathway. Identification of 67 new interactions was followed by validation by co-affinity purification and exhaustive literature curation of existing information. We provide a nearly complete, functionally annotated interactome of 802 interactions for the PI3K-mTOR pathway. Our screen revealed a predominant place for glycogen synthase kinase-3 (GSK3) A and B and the AMP-activated protein kinase. In particular, we identified the deformed epidermal autoregulatory factor-1 (DEAF1) transcription factor as an interactor and in vitro substrate of GSK3A and GSK3B. Moreover, GSK3 inhibitors increased DEAF1 transcriptional activity on the 5-HT1A serotonin receptor promoter. We propose that DEAF1 may represent a therapeutic target of lithium and other GSK3 inhibitors used in bipolar disease and depression.

The pitfalls of proteomics experiments without the correct use of bioinformatics tools.

The elucidation of the entire genomic sequence of various organisms, from viruses to complex metazoans, most recently man, is undoubtedly the greatest triumph of molecular biology since the discovery of the DNA double helix. Over the past two decades, the focus of molecular biology has gradually moved from genomes to proteomes, the intention being to discover the functions of the genes themselves. The postgenomic era stimulated the development of new techniques (e.g. 2-DE and MS) and bioinformatics tools to identify the functions, reactions, interactions and location of the gene products in tissues and/or cells of living organisms. Both 2-DE and MS have been very successfully employed to identify proteins involved in biological phenomena (e.g. immunity, cancer, host-parasite interactions, etc.), although recently, several papers have emphasised the pitfalls of 2-DE experiments, especially in relation to experimental design, poor statistical treatment and the high rate of 'false positive' results with regard to protein identification. In the light of these perceived problems, we review the advantages and misuses of bioinformatics tools - from realisation of 2-DE gels to the identification of candidate protein spots - and suggest some useful avenues to improve the quality of 2-DE experiments. In addition, we present key steps which, in our view, need to be to taken into consideration during such analyses. Lastly, we present novel biological entities named 'interactomes', and the bioinformatics tools developed to analyse the large protein-protein interaction networks they form, along with several new perspectives of the field.

Protein interaction mapping: a Drosophila case study.

The Drosophila (fruit fly) model system has been instrumental in our current understanding of human biology, development, and diseases. Here, we used a high-throughput yeast two-hybrid (Y2H)-based technology to screen 102 bait proteins from Drosophila melanogaster, most of them orthologous to human cancer-related and/or signaling proteins, against high-complexity fly cDNA libraries. More than 2300 protein-protein interactions (PPI) were identified, of which 710 are of high confidence. The computation of a reliability score for each protein-protein interaction and the systematic identification of the interacting domain combined with a prediction of structural/functional motifs allow the elaboration of known complexes and the identification of new ones. The full data set can be visualized using a graphical Web interface, the PIMRider (http://pim.hybrigenics.com), and is also accessible in the PSI standard Molecular Interaction data format. Our fly Protein Interaction Map (PIM) is surprisingly different from the one recently proposed by Giot et al. with little overlap between the two data sets. Analysis of the differences in data sets and methods suggests alternative strategies to enhance the accuracy and comprehensiveness of the post-genomic generation of broad-scale protein interaction maps.

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Human telomeric position effect is determined by chromosomal context and telomeric chromatin integrity.

We investigated the influence of telomere proximity and composition on the expression of an EGFP reporter gene in human cells. In transient transfection assays, telomeric DNA does not repress EGFP but rather slightly increases its expression. In contrast, in stable cell lines, the same reporter construct is repressed when inserted at a subtelomeric location. The telomeric repression is transiently alleviated by increasing the dosage of the TTAGGG repeat factor 1 (TRF1). Upon a prolongated treatment with trichostatin A, the derepression of the subtelomeric reporter gene correlates with the delocalization of HP1alpha and HP1beta. In contrast, treating the cells with 5 azacytidin, a demethylating agent, or with sirtinol, an inhibitor of the Sir2 family of deacetylase, has no apparent effect on telomeric repression. Overall, position effects at human chromosome ends are dependent on a specific higher-order organization of the telomeric chromatin. The possible involvement of HP1 isoforms is discussed.