Sebiha Cevik

Bio: Sebiha Cevik is an academic researcher from Abdullah Gül University. The author has contributed to research in topics: Cilium & Intraflagellar transport. The author has an hindex of 9, co-authored 15 publications receiving 4339 citations. Previous affiliations of Sebiha Cevik include University College Dublin & Harvard University.

Towards a proteome-scale map of the human protein–protein interaction network

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.

An empirical framework for binary interactome mapping

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.

Empirically-controlled mapping of the Caenorhabditis elegans protein-protein interactome network

Abstract: High-throughput yeast two-hybrid screening is used to generate the largest C. elegans interactome resource available thus far. Using an empirical quality control framework presented in Venkatesan et al., also online, the data set is evaluated for quality and is used to estimate the total size of the worm interactome. 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 ∼10,000 × ∼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 ∼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.

Joubert syndrome Arl13b functions at ciliary membranes and stabilizes protein transport in Caenorhabditis elegans

Abstract: The small ciliary G protein Arl13b is required for cilium biogenesis and sonic hedgehog signaling and is mutated in patients with Joubert syndrome (JS). In this study, using Caenorhabditis elegans and mammalian cell culture systems, we investigated the poorly understood ciliary and molecular basis of Arl13b function. First, we show that Arl13b/ARL-13 localization is frequently restricted to a proximal ciliary compartment, where it associates with ciliary membranes via palmitoylation modification motifs. Next, we find that loss-of-function C. elegans arl-13 mutants possess defects in cilium morphology and ultrastructure, as well as defects in ciliary protein localization and transport; ciliary transmembrane proteins abnormally accumulate, PKD-2 ciliary abundance is elevated, and anterograde intraflagellar transport (IFT) is destabilized. Finally, we show that arl-13 interacts genetically with other ciliogenic and ciliary transport–associated genes in maintaining cilium structure/morphology and anterograde IFT stability. Together, these data implicate a role for JS-associated Arl13b at ciliary membranes, where it regulates ciliary transmembrane protein localizations and anterograde IFT assembly stability.

Intraflagellar transport: from molecular characterisation to mechanism.

Abstract: Research from a wide range of model systems such as Chlamydomonas, C. elegans and mice have shown that intraflagellar transport (IFT) is a bidirectional motility of large protein complexes along cilia and flagella that is essential for building and maintaining these organelles. Since its discovery in 1993, much progress has been made in uncovering the molecular and functional basis of IFT. Presently, many components of the core IFT machinery are known, including the anterograde kinesin 2 motor(s), the IFT-dynein retrograde motor and the collection of at least 17 proteins that makes up the IFT particle. Most significantly, discoveries linking IFT to polycystic kidney disease and other developmental phenotypes have broadened the context of IFT research by demonstrating that primary cilia and IFT are required for processes such as kidney tubule and retinal tissue development, limb bud morphogenesis and organ patterning. Central to the functional basis of IFT is its ability to traffic various ciliary protein cargos, which include structural ciliary subunits, as well as non-structural proteins such as transmembrane channels/receptors and sensory signalling molecules. Indeed, exciting data over the past 3-4 years, linking IFT and primary cilia to developmental and growth factor signalling, as well as the cell cycle, indicates that the current repertoire of IFT cargos is likely to expand. Here we present a comprehensive review of IFT, with particular emphasis on its molecular composition and mechanism of action.

Tissue-based map of the human proteome

Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Network Medicine: A Network-Based Approach to Human Disease

Abstract: Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

p62/SQSTM1 Binds Directly to Atg8/LC3 to Facilitate Degradation of Ubiquitinated Protein Aggregates

Abstract: Protein degradation by basal constitutive autophagy is important to avoid accumulation of polyubiquitinated protein aggregates and development of neurodegenerative diseases. The polyubiquitin-binding protein p62/SQSTM1 is degraded by autophagy. It is found in cellular inclusion bodies together with polyubiquitinated proteins and in cytosolic protein aggregates that accumulate in various chronic, toxic, and degenerative diseases. Here we show for the first time a direct interaction between p62 and the autophagic effector proteins LC3A and -B and the related -aminobutyrate receptor-associated protein and-aminobutyrate receptor-associated-like proteins. The binding is mediated by a 22-residue sequence of p62 containing an evolutionarily conserved motif. To monitor the autophagic sequestration of p62- and LC3-positive bodies, we developed a novel pH-sensitive fluorescent tag consisting of a tandem fusion of the red, acid-insensitive mCherry and the acid-sensitive green fluorescent proteins. This approach revealed that p62- and LC3-positive bodies are degraded in autolysosomes. Strikingly, even rather large p62-positive inclusion bodies (2 m diameter) become degraded by autophagy. The specific interaction between p62 and LC3, requiring the motif we have mapped, is instrumental in mediating autophagic degradation of the p62-positive bodies. We also demonstrate that the previously reported aggresome-like induced structures containing ubiquitinated proteins in cytosolic bodies are dependent on p62 for their formation. In fact, p62 bodies and these structures are indistinguishable. Taken together, our results clearly suggest that p62 is required both for the formation and the degradation of polyubiquitin-containing bodies by autophagy.

The human disease network

Abstract: A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.