Biology subjects

Gumus, Z. H.

Publications and source records attributed to Gumus, Z. H..

6 recordsLinked to original sources

bioRxiv2022

Brain aging is faithfully modelled in organotypic brain slices and accelerated by prions

Mammalian models are essential for brain aging research. However, the long lifespan and limited amenability to genetic and pharmacological perturbations have hindered the use of mammals for dissecting aging-regulatory molecular networks and discovering new anti-aging interventions. To circumvent these limitations, we developed an ex vivo model system that faithfully mimics the aging process of the mammalian brain using cultured mouse brain slices. Genome-wide gene expression analyses showed that brain slices spontaneously upregulated senescence-associated genes over time and reproduced many of the transcriptional characteristics of aged brains. Treatment with rapamycin, a classical anti-aging compound, largely abolished the time-dependent transcriptional changes in brain slices. Using this model system, we discovered that prions drastically accelerated the development of age-related molecular signatures and the pace of brain aging. We confirmed this finding in mouse models and human victims of Creutzfeldt-Jakob disease. These data establish a novel, eminently tractable mammalian model of brain aging, and uncover a surprising acceleration of brain aging in prion diseases.

neuroscience↗

bioRxiv2020

Comparative effects of oncogenic mutations G12C, G12V, G13D, and Q61H on local conformations and dynamics of K-Ras

K-Ras is the most frequently mutated protein in human cancers. However, until very recently, its oncogenic mutants were viewed as undruggable. To develop inhibitors that directly target oncogenic K-Ras mutants, we need to understand both their mutant-specific and pan-mutant dynamics and conformations. Recently, we have investigated how the most frequently observed K-Ras mutation in cancer patients, G12D, changes its local dynamics and conformations1. Here, we extend our analysis to study and compare the local effects of other frequently observed oncogenic mutations, G12C, G12V, G13D and Q61H. For this purpose, we have performed Molecular Dynamics (MD) simulations of each mutant when active (GTP-bound) and inactive (GDP-bound), analyzed their trajectories, and compared how each mutant changes local residue conformations, inter-protein distance distributions, local flexibility and residue pair correlated motions. Our results reveal that in the four active oncogenic mutants we have studied, the 2 helix moves closer to the C-terminal of the 3 helix. However, P-loop mutations cause 3 helix to move away from Loop7, and only G12 mutations change the local conformational state populations of the protein. Furthermore, the motions of coupled residues are mutant-specific: G12 mutations lead to new negative correlations between residue motions, while Q61H destroys them. Overall, our findings on the local conformational states and protein dynamics of oncogenic K-Ras mutants can provide insights for both mutant-selective and pan-mutant targeted inhibition efforts.

biophysics↗

bioRxiv2020

ProNetView-ccRCC: A web-based portal to interactively explore clear cell renal cell carcinoma proteogenomics networks

To better understand the molecular basis of cancer, the NCIs Clinical Proteomics Tumor Analysis Consortium (CPTAC) has been performing comprehensive large-scale proteogenomic characterizations of multiple cancer types. Gene/protein regulatory networks has subsequently been derived based on these proteogenomic profiles, which serve as useful tools to gain system-level understanding of the molecular regulatory factories underlying the diseases. On the other hand, it remains a challenge to effectively visualize and navigate the resulting network models, which capture higher order structures in the proteogenomic profiles. There is a pressing need to have a new open community resource tool for intuitive visual exploration, interpretation and communication of these gene/protein regulatory networks by the cancer research community. In this work, we introduce ProNetView-ccRCC (http://ccrcc.cptac-network-view.org/), an interactive web-based network exploration portal for investigating phosphopeptide co-expression network inferred based on the CPTAC clear cell renal cell carcinoma (ccRCC) phosphoproteomics data. ProNetView-ccRCC enables quick, user-intuitive visual interactions with the ccRCC tumor phosphoprotein co-expression network comprised of 3,614 genes, as well as 30 functional pathway-enriched network modules. Users can interact with the network portal and can conveniently query for association between abundance of each phosphopeptide in the network and clinical variables such as tumor grade.

bioinformatics↗

bioRxiv2018

ImmuneRegulation: A web-based tool for identifying human immune regulatory elements

Humans can vary considerably in their healthy immune phenotypes and in their immune responses to various stimuli. We have developed an interactive web-based tool, ImmuneRegulation, to enable discovery of human regulatory elements that drive some of the phenotypic differences observed in gene expression profiles. ImmuneRegulation currently provides the largest centrally integrated resource available in the literature on transcriptome regulation in whole blood and blood cell types, including genotype data from 23,040 individuals, with associated gene expression data from 30,562 experiments, that provide genetic variant-gene expression associations on [~]200 million eQTLs. In addition, it includes 14 million transcription factor (TF) binding region hits extracted from 1945 TF ChIP-seq peaks and the latest GWAS catalog of 67,230 published SNP-trait associations. Users can interactively explore ImmuneRegulation to visualize and discover associations between their gene(s) of interest and their regulators (genetic variants or transcription factors) across multiple cohorts and studies. These regulators can explain cohort or cell type dependent gene expression variations and may be critical in selecting the ideal cohorts or cell types for follow-up studies. Overall, ImmuneRegulation aims to contribute to our understanding of the effects of eQTLs and TFs on heterogeneous transcriptional responses reported in studies on the blood; in the development of molecular signatures of immune response; and facilitate their future application in patient management. ImmuneRegulation is freely available at http://icahn.mssm.edu/immuneregulation.

immunology↗

bioRxiv2018

Ancestral resurrection reveals mechanisms of kinase regulatory evolution

Protein kinases are crucial to coordinate cellular decisions and therefore their activities are strictly regulated. We used ancestral resurrection to uncover a mechanism underlying the evolution of kinase control within the ERK family of Mitogen Activated Protein Kinases (MAPKs). Kinase activities switched from high to low intrinsic autophosphorylation at the transition from the ancestors of ERKs1-5 and ERKs1-2. A shortening of the loop between {beta}3-C and a mutation in the gatekeeper residue drove this transition. Molecular dynamics simulations suggested that the change in the {beta}3-C loop length affected kinase cis-autophosphorylation by altering the positioning of catalytic residues and by allowing greater flexibility in the L16 kinase loop. This latter effect likely synergizes with the known role of gatekeeper mutations in facilitating domain closure and thus kinase activation, providing a rationale for the synergy between the two evolutionary mutations. Our results shed light on the evolutionary mechanisms that led to tight regulation of a central kinase in development and disease.

evolutionary biology↗

bioRxiv2017

Exploring biological networks in 3D, stereoscopic 3D and immersive 3D with iCAVE

Biological networks are becoming increasingly large and complex, pushing the limits of existing 2D tools. iCAVE is an open source software tool for interactive visual explorations of large and complex networks in 3D, stereoscopic 3D or immersive 3D. It introduces new 3D network layout algorithms and 3D-extensions of popular 2D network layout, clustering and edge bundling algorithms to assists researchers in understanding the underlying patterns in large, multi-layered, clustered or complex networks. This protocol aims to guide new users on the basic functions of iCAVE for loading data, laying out networks (single or multi-layered), bundling edges, clustering networks, visualizing clusters, visualizing data attributes and saving output images or videos. It also provides examples on visualizing networks constrained in physical 3D space (e.g. proteins; neurons; brain). It is accompanied with a new version of iCAVE with an enhanced user interface and highlights new features useful for existing users.\n\nSignificance StatementNetwork representations assist in systems-level data exploration in many research fields, providing valuable insights. However, with the recent advances in experimental technologies, biological networks are becoming increasingly large and complex, necessitating new data visualization solutions. We have recently developed iCAVE (Liluashvili et al., 2017), an open?source software platform that enables 3D (optionally stereoscopic and or immersive) visualizations of complex, dense or multi?layered biological networks. Users can select from several new 3D network layout and clustering algorithms, bundle network edges and customize network attributes to reveal hidden structures within them. This protocol guides new users on loading, navigating, customizing and saving networks in iCAVE and is accompanied by an updated version of the software.

bioinformatics↗