Mammalian Genetic Interaction Maps reverse genetic screens using combinations of perturbations

Cancer is a complex disease that requires the coordination of a number of processes to induce an oncogenic state. While many processes playing a role in oncogenesis have been identified, our understanding of the molecular events leading to and relationships between these various pathways is not yet completely adequate. Genetic interactions underly pathway form and function and occur when the biological activity of one gene is modified by another. In the context of cancer, we are mapping genetic interactions systematically in high-throughput using RNAi and small-molecule based screens. Our primary interest is uncovering genes and pathways which modify the transforming ability of the oncogene KRAS which is mutated in nearly 25% of all cancers. Since KRAS has been refractory to small molecule inhibition, defining pathways which underly its oncogeneic phenotype could lead to new druggable targets.

In previous work, we created large-scale maps of genetic interactions across species and across different conditions. Our findings indicated that the way in which genetic interactions maps were "different" from one another highlighted the key network modules which contributed to speciation and drug responses. In the case of the DNA damage response, differential networks were able to pinpoint key signaling molecules and events which were essential for the cellular response to DNA damage. As total gene deletion in mammalian cells is not as amenable as in lower eukaytoes, we are extending genetic interaction mapping approaches to mammalian cells in culture using siRNA, shRNA and small molecule screens.

Figure 1: Differential network maps highlight pathways active under DNA damage: (A) Combinations of mutations are analyzed under multiple conditions and phenotypes compared to determine network differences. (B) Differential networks highlight connections between pathways and complexes in a condition-specific manner. (C) Differential genetic relationships between proteins complexes.

Related Publications

  • Bandyopadhyay S, Mehta M, Kuo D, Sung M, Licon K, Chuang R, Jaehnig E, Bodenmiller B, Licon K, Copeland W, Shales M, Fiedler D, Dutkowski J, Guenole A, van Attikum H, Shokat K, Kolodner R, Huh W, Aebersold R, Keogh MC, Krogan NJ, Ideker T. Rewiring of Genetic Networks in Response to DNA Damage. Science. 330(6009):1385-89. 2010. [Science]
  • Wilmes G*, Bergkessel M*, Bandyopadhyay S, Chan A, Braberg H, Shales M, Collins SR, Whitworth BG, Kress TL, Weissman JS, Ideker T, Guthrie C, Krogan NJ. Cover Article: A Genetic Interaction Map of RNA Processing Factors Reveals Links Between Sem1/Dss1-Containing Complexes and mRNA Export and Splicing. Molecular Cell. 2008 Dec 5;32(5):735-46. Featured Article, [Cell] *Equal Contribution
  • Roguev A, Bandyopadhyay S, Zofall M, Zhang K, Fischer T, Collins SR, Qu H, Shales M, Park H, Hayles J, Hoe K, Kim D, Ideker T, Grewal SI, Weissman JS, Krogan NJ. Conservation and Rewiring of Functional Modules Revealed by an Epistasis Map in Fission Yeast. Science. 2008 Oct 17;322(5900):405-10. Epub 2008 Sep 25. [Science]
  • Bandyopadhyay S, Kelley RM, Krogan NJ, Ideker T. Functional maps of protein complexes from quantitative genetic interaction data. PLoS Computational Biology 2008 Apr 18;4(4):e1000065.[Plos] [supplement]
  • Beyer A, Bandyopadhyay S, Ideker T. Integrating physical and genetic maps: from genomes to interaction networks. Featured Review. Nature Reviews Genetics. 2007 Sep;8(9):699-710. [Nature]

Protein-Protein Interaction Maps High-throughput maps of pathway architecture

Pathway architecture is determined by physical binding between molecules. Our knowledge of pathways drive the discovery of new biological insights and interpretation of genomic-level data. As significant institutional investment was made to uncover the complement of genes in the genome in the human genome project, there is no similar effort to systematically map the complement of physical associations between proteins in the cell. This is largely due to the complexity of such an endeavor, as networks would be distinct for each cell type and cellular state. To establish the utility and feasability of such endeavors we are generating pathway-centric protein-protein interaction maps which we use as a scaffold for the discovery of novel insights which we test using more classical biochemical approaches.

As a proof of concept, we developed a pathway level map of human Mitogen Activated Protein Kinases (MAPK), which are aberrently active in most cancers and the central pathway controlling cellular proliferation. Using yeast-two hybrid (Y2H) methodology followed by bioinformatic filtering and network analysis we identified a number of proteins which bind a number of different kinases and serve as signaling scaffolds (Figure). As Y2H is an ex-vivo method and requires the expression of human proteins in yeast, we are now developing large scale protein-protein interaciton maps in vivo using Affinity Purification followed by Mass Spectrometry (AP-MS). These networks have the ability to be relevant in vivo and capture dynamic protein functions in responses to stimuli.

Figure 1: MAPK scaffolding molecules. Proteins which interact with multiple MAPKs using the Y2H system are shown.

Related Publications

  • Bandyopadhyay S, Chiang C, Srivastava J, Gersten M, White S, Bell R, Kurschner C, Martin CH, Smoot M, Sahasrabudhe S, Barber DL, Chanda SK, Ideker T. A Human MAP Kinase Interactome. Nature Methods. 7(10):801-5 2010. [Pubmed]
  • Fossum E, Friedel CC, Rajagopala SV, Titz B, Baiker A, Schmidt T, Kraus T, Stelberger T, Rutenberg C, Suthram S, Bandyopadhyay S, Rose D, Von Brunn A, Uhlmann M, Zeretzke C, Dong Y, Boulet H, Koegl M, Bailer SM, Koszinowski U, Ideker T, Uetz P, Zimmer R, Haas J. Evolutionarily conserved herpesviral protein interaction networks. PLoS Pathog. 2009 Sep;5(9):e1000570. Epub 2009 Sep 4. [Plos Pathogens]
  • Bandyopadhyay S, Kelley RM, Krogan NJ, Ideker T. Functional maps of protein complexes from quantitative genetic interaction data. PLoS Computational Biology 2008 Apr 18;4(4):e1000065.[Plos] [supplement]
  • Beyer A, Bandyopadhyay S, Ideker T. Integrating physical and genetic maps: from genomes to interaction networks. Featured Review. Nature Reviews Genetics. 2007 Sep;8(9):699-710. [Nature]

Bioinformatics for Systems Biology Network analysis for data integration

Systems biology is the study of biological systems through systematic perturbation, global read-out of the multifaceted response, and integration of these data to formulate models predictive of system structure and function. These integrative approaches are yielding network models that chart the key components and interactions of the system over scales ranging from single pathways to whole cells to entire populations of individuals. We are focused on application of network analysis to key problems in disease pathway modeling, personalized medicine and drug target identification.

We are actively involved in data integration efforts to interpret genomic screening data using a scaffold of protein complexes, pathways and protein-protein interactions. We have developed methods and algorithms to interpret genome-wide RNAi screens using protein complexes and are expanding these approaches to other heterogenous data sets.

Central to our brand of data integration is the reconciliation of genetic and physical interaction networks. Genetic interactions often do not simply overlap with physical interaction networks and often fall "between pathways" which have parallel or partially redundant functions (Figure 1). We have deveoped algorithms for the systematic interpretation of genetic interactions based on inference using physical interactions and applied this to the identification of protein complexes in yeast and the analysis of dynamic changes in pathway structure following DNA damage.

Figure 1:Integration of physical and genetic interactions. (A,B) Enrichment of genetic and physical interaction against a gold standard set of protein complexes. (C) Model as a basis for data integration using between pathway genetic interaction scores (b) and within module scores (m).

Related Publications

  • Bandyopadhyay S, Mehta M, Kuo D, Sung M, Licon K, Chuang R, Jaehnig E, Bodenmiller B, Licon K, Copeland W, Shales M, Fiedler D, Dutkowski J, Guenole A, van Attikum H, Shokat K, Kolodner R, Huh W, Aebersold R, Keogh MC, Krogan NJ, Ideker T. Rewiring of Genetic Networks in Response to DNA Damage. Science. 330(6009):1385-89. 2010. [Science]
  • Ideker T, Bandyopadhyay S. Integrative Systems Biology. Nature Genetics. 42(12). 2010. [Nature Genetics]
  • Konig R, Stertz S, Zhou Y, Inoue A, Hoffmann HH, Bhattacharyay S, Alamares J, Tscherne DM, Ortigoza MB, Liang Y, Gao Q, Andrews SE, Bandyopadhyay S, De Jesus P, Tu B, Pache L, Shih C, Orth A, Bonamy G, Miraglia L, Ideker T, Garcia-Sastre A, Young JAT, Palese P, Shaw ML, Chanda SK. Human Host Factors Required for Influenza Virus Replication. Nature. 2010 Feb 11;463(7282):813-7. [Nature]
  • Bushman FD, Malani N, Fernandes J, D'Orso I, Cagney G, Diamond TL, Zhou H, Hazuda DJ, Espeseth AS, Konig R, Bandyopadhyay S, Ideker T, Goff S, Krogan N, Frankel A, Young JAT, Chanda SK. Host cell factors in HIV replication: meta-analysis of genome-wide studies. PLoS Pathog. 2009 May;5(5):e1000437. Epub 2009 May 29. [Plos Pathogens]
  • Wilmes G*, Bergkessel M*, Bandyopadhyay S, Chan A, Braberg H, Shales M, Collins SR, Whitworth BG, Kress TL, Weissman JS, Ideker T, Guthrie C, Krogan NJ. Cover Article: A Genetic Interaction Map of RNA Processing Factors Reveals Links Between Sem1/Dss1-Containing Complexes and mRNA Export and Splicing. Molecular Cell. 2008 Dec 5;32(5):735-46. Featured Article, [Cell] *Equal Contribution
  • Roguev A, Bandyopadhyay S, Zofall M, Zhang K, Fischer T, Collins SR, Qu H, Shales M, Park H, Hayles J, Hoe K, Kim D, Ideker T, Grewal SI, Weissman JS, Krogan NJ. Conservation and Rewiring of Functional Modules Revealed by an Epistasis Map in Fission Yeast. Science. 2008 Oct 17;322(5900):405-10. Epub 2008 Sep 25. [Science]
  • Konig R, Zhou Y, Elleder D, Diamond TL, Bonamy GMC, Irelan JT, Chiang C, Tu BP, De Jesus PD, Lilley CE, Seidel S, Opaluch AM, Caldwell JS, Weitzman MD, Kuhen KL, Bandyopadhyay S, Ideker T, Orth AP, Miraglia LJ, Bushman FD, Young JA, Chanda SK. Global Analysis of Host-Pathogen Interactions that Regulate Early-Stage HIV-1 Replication. Cell. 2008 Oct 3;135(1):49-60.[Cell]
  • Bandyopadhyay S, Kelley RM, Krogan NJ, Ideker T. Functional maps of protein complexes from quantitative genetic interaction data. PLoS Computational Biology 2008 Apr 18;4(4):e1000065.[Plos] [supplement]
  • Beyer A, Bandyopadhyay S, Ideker T. Integrating physical and genetic maps: from genomes to interaction networks. Featured Review. Nature Reviews Genetics. 2007 Sep;8(9):699-710. [Nature]
  • Bandyopadhyay S, Sharan R, Ideker T. Cover Article: Systematic identification of functional orthologs by protein network comparison. Genome Research. 2006 Mar;16(3):428-35. [Genome Res] [supplement]
  • Bandyopadhyay S, Kelley RM, Ideker T. Discovering regulated networks during HIV-1 latency and reactivation. Pac Symp Biocomput. 2006:354-66.[PSB]