Nevan J. Krogan - US grants

The viral infectivity factor Vif is an essential accessory protein of primate lentiviruses, HIV-1, HIV-2, and SIV. Without Vif, these viruses do not replicate in non-permissive cells or in the host. Vif inactivates the cellular cytidine deaminases ASF and A3G, which are members of the APOBEC3 (apolipoprotein BmRNA-editing enzyme catalytic-polypeptides 3) family. In the absence of Vif, these APOBEC3 proteinsare incorporated into new viral particles where they deaminate [unreadable]cytidines in the minus-strand cDNA during reverse transcription. These DNA lesions result in viral DNA degradation or introduction of deleterious mutations. In addition, the APOBEC3 proteins can inhibit viral replication in the absence of their enzymatic activity, possibly by altering the reverse transcription process itself. Thus, APOBEC proteins protect cells against HIV, and Vif has evolved to provide an essential viral counter defense. A key role for Vif is to promote ubiquitination and subsequent destruction of A3G and ASF by the proteosome. Vif recruits A3G and ASF to a cellular ubiquitin protein ligase that includes Cullin-5, Ring-box2, and Elongins B and C (EloBC). Even modest inhibition of Vif function, either by interfering with binding to A3G and/or ASF or by blocking recruitment of the EloBC/Cul5/Rbx2 E3 ligase, might significantly reduceHIV-1 loads in vivo. Therefore, a major objective of this project is to determine the architecture of theVif/EloBC/Cul5/Rbx2 complex and subcomplexes with A3G

DESCRIPTION (provided by applicant): Comparative interaction mapping resolves protein complexes and signaling pathways on the basis of their conservation across different species or types of interaction network. It is an emerging methodology which, like comparative genomics, provides a powerful tool for understanding cellular function. Network comparison has been used to identify the functional roles of many proteins, and it offers insight into how mutations in the genome contribute to the evolution of new functions and phenotypes. A current hurdle towards these goals is the lack of high-coverage interaction maps at the appropriate evolutionary distances to enable network comparison. To address this shortcoming, the major goal of this project is to obtain matching sets of highdensity physical and genetic interaction maps across the model organisms Schizosaccharomyces pombe and Saccharomyces cerevisiae. Use of these data will ultimately help resolve the following questions: How closely do the architectures of the physical, genetic, and transcriptional interaction networks reflect variation in the underlying genomic sequence?;What relative contributions do changes in the physical interactome, genetic pathways, transcriptional networks, and mutations at the protein sequence level make to the evolution of new cellular functions? Specific hypotheses directly related to the physiologies of S. pombe and S. cerevisiae can also be addressed. Many aspects of S. pombe physiology bear more in common with mammals than does S. cerevisiae, including intron/exon splicing, chromosomal architecture, and RNA interference machinery. In fact, the last common ancestor of S. pombe and S. cerevisiae is quite ancient (420 mya), making the conserved interaction map generalizable to large parts of the eukaryotic lineage. To focus our initial interaction mapping efforts on the regulatory machinery most likely to form the basis for the similarities and differences between S. pombe and S. cerevisiae physiology, we will screen interactions among a targeted set of ~400 kinases and transcriptional regulators. This set will limit our scope sufficiently such that high coverage maps can be obtained at reasonable funding levels within a five-year time frame. Pair-wise genetic interactions will be measured using epistatic phenotyping, protein-protein interactions using affinity purification followed by tandem mass spectrometry, and transcription factor / promoter binding interactions using genome-wide chromatin immunoprecipitation assays. In parallel, we will develop a companion suite of bioinformatic methods to perform integrative and comparative analysis of the yeast interaction networks. Bioinformatic research will address: [1] Models of interplay between quantitative genetic and physical interactions;[2] Alignment of the integrated networks across species;and [3] Prediction and transfer of interactions within and across species, at varying degrees of data integration. Assembling the network of transcriptional regulators and kinases will serve as a pilot for establishing basic principles of network integration and comparison prior to embarking on larger-scale efforts to comprehensively map fission yeast as well as higher eukaryotes. It will involve close coordination among the two principal investigators Krogan and Ideker. It will join two University of California campuses as well as two California institutes, Cal-IT2 and QB3, which are committing space to house the proposed project in the San Diego and San Francisco areas.

DESCRIPTION (provided by applicant): Functional genomics builds naturally on recent successes in comparative prokaryotic genomics. The power of these methods for interrogation of the pathways regulating growth has recently been demonstrated for yeast, but the field is less developed for bacteria, partly due to a lack of experimental tools. We propose to develop and exploit quantitative genetic approaches for prokaroytic organisms, opening up the power of these approaches initially to two organisms, E. coli, a gram negative model organism and S. pneumoniae, a gram positive pathogen. We will build the methodology we developed in E. coli to systematically introduce gene disruptions two at a time. We will carry out the procedure en masse, initially focusing on genes involved in cell envelope function and DNA metabolism, so that the effect on bacterial growth of thousands of combinations of pair-wise disruptions can be analyzed and compared. We will apply the analytical tools that had led to important insights into yeast cell biology to our data set and refine them for bacteria. These approaches have proven powerful for discovering the function of uncharacterized genes and the nature of protein pathways and networks within the cell. We will complement quantitative genetic interaction studies with chemical genetic initiatives, thus experimentally linking pharmacological targets to the genes involved in their biology. In this way, a more complete picture of how bacterial proteins function, and how different areas of bacterial cell biology are interconnected, will be assembled. Moreover, this work in E. coli and S. pneumoniae will confer more power on existing comparative genomic data for hundreds of bacteria. Great emphasis will be placed on dissemination of the results (which will be of wide interest) via searchable database that will link to other relevant websites (e.g. EcoliHub) so that diverse datasets can be integrated, as well as providing the community with the experimental tools (strains, plasmids, libraries, computer programs etc.) needed to extend this approach to other organisms. Bacteria are among the simplest organisms in nature. By removing genes two at a time and observing the effect, we will build the first comprehensive picture of how the E.coli bacterium's 4000 genes relate to each other. This type of work can help us understand how a bacterial cell works, and the information can be used to design useful organisms for industry, to identify drug targets, and improve therapy for bacterial disease.

DESCRIPTION (provided by applicant): We have recently developed a genetic screening approach, termed E-MAP (Epistatic MiniArray Technology Profiling), that can quantify the strength of systematically generated pair-wise genetic interactions. The method identifies negative double mutant interactions, where combination of mutations causes defects leads to enhancement of growth defects or lethality. Such interactions often specify membership of parallel biochemical pathways. Additionally, E-MAP also identifies positive interactions, where combination of mutants show mutual suppression or lack any additive defects, which are enriched among physically interacting gene products. Using gene deletions of non-essential genes and hypomorphic alleles of essential genes, we have recently generated E-MAPs in S. cerevisiae that have focused on 1) the early secretory pathway and 2) chromosome biology, which includes transcriptional regulation, chromatin remodeling and DNA repair. We now propose the second generation of E-MAP analysis, allowing us to address the next level of complexity, via examination of point mutants of multifunctional and essential genes. Specifically, we will genetically dissect two essential, multisubunit, multifunctional complexes at the heart of gene expression and chromatin structure: RNA polymerase II (RNAPII) and the nucleosome. This approach will allow us to A) map the structural features of these complexes onto their functional roles, and B) characterize the functional relationships between RNAPII and the nucleosome and the wider gene expression apparatus. In Aim #1, we will use the chromosome biology E-MAP to genetically examine a set of approximately 450 histone H3 and H4 mutants including A) complete alanine (or serine)-scans, B) comprehensive substitution of modifiable residues, and C) semisystematic deletions of the N-terminal tails. The work, which is being done collaboratively with NIH Roadmap TCNP (Technology Center for Networks and Pathways) of Lysine Modification (PI Jef Boeke), will help reveal how histone-histone and histone-DNA contacts and histone modifications influence the steps of transcription and chromatin regulation. In Aim #2, we will screen approximately 100 distinct and diverse point mutants of several essential RNAPII subunits isolated in collaboration with Craig Kaplan and Roger Kornberg. In Aim #3, we will subject these data to hierarchical clustering and our recently developed metrics (S- and COP-scoring systems) to help identify functional relationships using the E-MAP data. We will also employ newly developed algorithms that identify functionally related sets of genes (or modules) from large-scale interaction datasets and allows for multi-functional genes to be members of more than one module. We anticipate that a systematic genetic approach described here will provide a more holistic view of chromatin function and transcriptional regulation in eukaryotic cells.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The aim is to generate a protein interaction map for M.tuberculosis in the persistent state. There is great potential that this information will accelerate the identification and prioritization of drug targets for antibiotics that kill persistent M.tuberculosis. Proteins will be tagged in M.tuberculosis strains grown in the lab of Prof. Jeffrey Cox, purified using affinity chromatography, and identified by MALDI-TOF and LC/MS/MS mass spectrometry. Initially, approximately 20 proteins will be purified from log phase cultures, and ultimately the project aims to purify approximately 200 proteins from persistent M.tuberculosis cultures, with mass spectrometry analysis carried out on the successful purifications, to generate a physical interaction map for the persistence regulon.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The HARC (HIV Accessory and Regulatory Complexes Center) at UCSF is directed by Prof Al Frankel and aims to develop new tools and methods to create a complete picture of HIV-host cell interactions occurring during the early phases of the virus's life cycle. The aim of the project with the UCSF Mass Spectrometry Facility is to build HIV-host protein interaction maps of HIV complexes in uninfected and infected states. Affinity tagged proteins from uninfected and HIV-infected Jurkat cells will be isolated and the associated proteins will be identified by MALDI-TOF and LC/MS/MS mass spectrometry. Approximately 15 HIV-encoded proteins will be expressed, with some mutant variants. Additionally, affinity-tagged versions of selected host proteins found to interact with the HIV proteome will be generated and complexes will be purified from infected cells to confirm that the interactions and physiologically relevant. The wider aim of the work is the generation of well-characterized complexes for structural studies.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We previously completed a large-scale analysis of physical protein interactions in yeast resulting in the identification of over 500 protein complexes (Nature 440, 637). More recently, we completed a screen for epistatically interacting genes in collaboration with Prof. Kevan Shokat, and have found that pairs of genes interacting positively correlate strongly with physical interactions, in particular between pairs of kinases/phosphatases and their substrate proteins. In this project, affinity tagged potential substrate proteins will be purified from yeast, digested into peptides, and enriched for phosphopeptides using the method of Beltrao et al., (PLoS Biol. 7(6):e1000134). Enriched fractions will be analyzed by LCMS.

Adaptive Behaviors; Autoimmunity; Behavior; Bioinformatics; biological adaptation to stress; Comparative Study; Defect; deletion library; design; Diabetes Mellitus; Disease; Elements; Fission Yeast; Genetic; Heat-Shock Response; insight; Leg; Malignant Neoplasms; Mammalian Cell; Maps; Methods; Nature; Osmolar Concentration; Pathway interactions; Phosphorylation; Property; Proteins; Resolution; response; Screening procedure; Signal Transduction; Solutions; Stimulus; synthetic biology; Testing; Yeasts

PROJECT SUMMARY (See instructions): In this study, we aim to functionally Interrogate host-pathogen relationships using three different enteroviruses (poliovirus, EV71 and coxsackievirus). To this end, we will use a variety of methods to systematically generate viral-host protein-protein and genetic interaction maps. The data generated using these initial, unbiased approaches will fuel more targeted, hypothesis-driven research in the subsequent projects. Although we intend to follow up on the most Interesting, unanticipated connections we uncover, we will be closely monitoring for links to host factors involved in quality control processes, including chaperone function, protein ubiquitination and protein degradation, which will link this work to the work described in Projects 2 and 3. In collaboration with Sumit Chanda (Burnham Institute) and John Young (Salk Institute), we will utilize RNAI methodology to globally assess the genetic dependencies, both positive and negative, of host factors to the pathogenesis of the three enteroviruses (Aim 1). Next, to characterize the enterovlrus-human protein-protein interactions, we intend to collaborate with Al Burlingame (UCSF) to employ a systematic affinity tag/purlflcation-mass spectrometry approach to Identify the viral-host protein complexes (Aim 2). We also Intend to globally ascertain the effects of protein post-translational modifications upon infection using mass spectrometry (Aim 3). Finally, In Aim 4, we will utilize a suite of bioinformatic and visualization tools to integrate the data sets in a meaningful fashion so that specific hypotheses regarding quality control processes can be generated and tested in collaboration with Judith Frydman (Project 2) and Raul Andino (Project 3). This integrated approach will leverage the expertise from multiple groups, including Pis of the Technology Core (Andrej Sali and Joe Derisi), so that novel host pathways that are hijacked during Infection can be Identified and characterized. This information will hopefully lead to breakthroughs with anti-viral drugs and vaccines.

DESCRIPTION (provided by applicant): Large-scale biological datasets (e.g. genetic and protein-protein interactions) are becoming easier to systematically produce in a variety of organisms, but it can be difficult to extract testable hypotheses on how individual proteins function. The overall objective of this research is to develop an experimental and computational platform that helps to address this gap between high-throughput information at the genomic scale and detailed mechanistic analysis of biological processes at the protein, protein domain and amino acid residue scale. To achieve this, the proposal integrates the complementary expertise of two investigators at the University of California-San Francisco in structural biophysics and computational protein modeling and design (Tanja Kortemme) and in large-scale, quantitative genetic and protein-protein interaction mapping strategies (Nevan Krogan). This work will specifically focus on specificity and promiscuity of protein recognition domains that mediate a considerable fraction of interactions in all biological processes. The central hypothesis this project will test is that there exist biologically important differences between the functional and biochemical overlap of members of a domain family. To test for such differences, we will simultaneously characterize the functional processes all members of a major domain family are involved in, and how these functions relate to the intrinsic protein recognition preferences of the family members. As a proof of principle, we aim to interrogate the family of 23 SH3 domain containing proteins in the model organism S. cerevisiae. SH3 domains have considerable biological importance: they are involved in a several critical processes in signal transduction, reorganization of the actin cytoskeleton, stress response and endocytosis. More practically, SH3 domains were selected as a manageable model system due to the amount of structural and biochemical data accumulated for this domain family. Aim 1 uses an unbiased large-scale genetic interaction mapping strategy to genetically interrogate SH3 domain deletions in all SH3-containing proteins in budding yeast so that their in vivo relevance can be studied. Aim 2 proposes to use this information, along with previously published physical interaction data, to aid in structure-based predictions of the recognition specificity of individual SH3 domains. Computational strategies using RosettaDesign will be used to reengineer domains to tune interaction specificity and promiscuity. These predictions will be tested in Aim 3 using biochemical, functional and genetic approaches and the resulting data will be used to refine the models generated in Aim 2. In the future, we intend to extend our findings and the experimental platform this project seeks to establish into other species, initially into fission yeast, but ultimately to higher organisms. We expect our developed framework to be broadly informative for applications in molecular reengineering as well as for development of therapeutics acting on interconnected protein networks.

One of the bottlenecks in structural studies of HIV-host complexes has been an incomplete picture of the repertoire of interactions. Without appropriate host partners, many of the HIV proteins do not adopt folded structures or exist in alternative conformations, particularly in cases where the viral protein interacts with more than one host complex. To address this problem, the HARC Center performed a comprehensive analysis of HIV-human protein-protein interactions (PPIs) using affinity-tagged HIV proteins expressed in both HEK293 and Jurkat T cell lines. By combining affinity purification/mass spectrometry (AP-MS) with a novel scoring algorithm, termed MiST, 497 high confidence HIV-human PPIs involving 435 human factors were identified. Among the PPIs'' found, we recapitulated many known HIV-human physical interactions, but the vast majority has not been previously described. Many of these are presently being followed up in the context of the HARC Center as well as collaboratively with outside groups with expertise in particular systems. For example, a collaboration between Krogan, Gross, and Reuben Harris (U. Minn.) identified CBF|3 as a new component of the Vif ubiquitin ligase complex that is essential for Vif function in the virus and stabilizes the complex in vitro, thereby allowing structural investigations of Vif to proceed (see Vif project). A collaboration between Krogan and Craik demonstrated that PR interacts with and cleaves the elF3d subunit of the elF3 translational initiation complex, a protein that inhibits HIV replication (see PR project). An exciting cross-Center collaboration between Krogan and Wes Sundquist (CHEETAH) has found that several Gag interactors play significant and unexpected roles in HIV infection and already has led to the crystal structure of one new factor.

In the Advanced Proteomics Core, we will apply unbiased proteomics approaches to characterize protein- protein interactions (PPIs) and post-translational modifications (PTMs) for transcription factor complexes that play important roles in early heart development. These studies will describe the interconnected networks of transcription factors, chromatin remodeling complexes, and as-yet-undefined cellular factors that function to regulate gene expression during cardiac development. The Proteomics Core will enable research projects to analyze biochemical complexes that underlie cardiac development. Through tagging of these factors, cellular expression, and affinity purification, these complexes will be elucidated by mass spectrometry (AP-MS), and data will be analyzed using newly developed algorithms to determine high confidence protein interactions. Using specific enrichment and mass spectrometry-based approaches, the Proteomics Core will identify post- translational modifications of purified complex components. Chemical enrichment strategies to purify phosphorylated species and antibody-based strategies to purify acetylated or ubiquitylated species will collectively identify modification events that may affect the formation or function of protein complexes underlying cardiac gene expression.

PROJECT SUMMARY (See instructions): In this study, we aim to functionally interrogate host-pathogen relationships in human influenza viruses. The Proteomics Core will employ a systematic affinity tag/purification-mass spectrometry approach to identify the viral-host protein complexes. The data generated using these initial, unbiased approaches will fuel more targeted, hypothesis-driven research in the subsequent projects. In tandem with this work and with more targeted downstream work, we will be closely monitoring for links to host factors involved in quality control processes, including chaperone function, protein ubiquitination, and protein degradation, which will link this work to the collaborations with Adolfa Garcia-Sastre, Sumit Chanda, and John Young.

Summary: Genetic interaction mapping is an emerging methodology that provides a powerful tool for understanding cellular function. However, despite all of the exciting prior work in this field, several points stand out as remarkable: First, almost all networks to date have been examined under a single static (usually standard laboratory) condition. Biological networks, however, are highly dynamic entities that continuously respond to a host of environmental and genetic changes or are altered more slowly over an evolutionary period. Second, such network changes occur across a wide range of scales, some impacting individual gene interactions, others affecting protein complexes, still others best summarized at the level of broad cell processes. This project addresses these two core issues (network dynamics and scales) by studying how a genetic network is reconfigured under complex species and stresses and by performing these comparisons using tools that capture a network's multi-scale, modular architecture. In the previous funding period, we successfully focused attention on generating genetic interaction maps across two yeasts, S. cerevisiae and S. pombe. We now pursue this analysis in mammals by furthering methodology to generate quantitative genetic networks using combinatorial RNAi in mouse fibroblast cells. Also, in the previous period we developed an approach termed dE-MAP (differential E-MAP), which allowed for the comparative analysis of yeast genetic interaction maps generated across different exogenous stresses. We now propose to leverage this analysis to create the first dE-MAPs in mammals, allowing us to study the evolution of stress response networks across the eukaryotic lineage. Finally, we will further develop a novel systems biology framework to use genetic interaction maps to drive the creation of a data-driven Gene Ontology (GO), which ultimately feeds back to design of subsequent E-MAPs and iterative refinement of GO. This work will be carried out over three Specific Aims: (1) Improvement and scale-up of a platform for high- density quantitative genetic interaction mapping in mammals; (2) Generation of differential genetic networks in response to stress in mammals and yeasts; and (3) Development of a computational methodology called network-extracted ontologies to enable multi-scale modeling and comparison of genetic networks. Successful completion of these aims will generate important community resources, including a large database of genetic interactions and modules in three different eukaryotic species and further development of network-based ontologies as a new multi-scale approach for network analysis. Because this project will involve close coordination between the Krogan and Ideker laboratories, this grant invokes the co-Principal Investigator mechanism. It joins two University of California campuses as well as two California Institutes for Science and Innovation, QB3 and Calit2, which support the PIs in the San Francisco and San Diego areas, respectively.

DESCRIPTION (provided by applicant): Signaling by tyrosine kinases play a major role in mammalian signal transduction and is a major component of nearly every major disease type. However, a systematic understanding of signaling pathways has remained elusive. While a number of techniques have been developed to map signaling pathways, used alone they only provide insight into one facet of signaling. We will use an integrative approach to chart the networks which control tyrosine kinase signaling at multiple levels through the use of complementary physical and genetic interaction mapping approaches. These maps will lead to network models which reflect proteins that can functionally modulate signaling and are physically associated with kinases including substrates, adaptors and regulatory subunits. To achieve this, the proposal integrates the complementary expertise of investigators at the University of California-San Francisco in high-throughput physical and genetic interaction mapping (Krogan), chemical-genetic approaches for tracing signaling pathways (Shokat) and network analysis and data integration (Bandyopadhyay). We aim to identify proteins that associate with tyrosine kinases through affinity purification-mass spectrometry (AP-MS) and kinase substrates through covalent capture-and-release in Aim 1. These data will be further characterized using a newly developed platform for quantitative genetic interaction mapping in mammalian cells, which will establish the functional relevance of these interactions by systematically identifying epistatic genetic relationships between kinases and associated proteins in Aim 2. Lastly, in Aim 3, we will unify data collected in the first two aims using network modeling to uncover detailed, mechanistic biological insights relating to mammalian tyrosine kinases. All data (raw, processed and integrated) will be made immediately available in an interactive and searchable fashion so that others can exploit the information we have collected on the tyrosine kinome.

? DESCRIPTION (provided by applicant): Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis, remains a major cause of human morbidity and mortality, particularly in the developing world. Chronic M. tuberculosis infection requires long- term interactions between the bacterium and host immune system, and tissue macrophages play key roles in the outcome of infection. Although technologies to monitor global changes in host gene expression have catalyzed our understanding of the important roles for TLR activation and interferon during TB infection, modulation of transcription represents only one of many cellular responses to bacterial infection. Post- translational modification of proteins, such as ubiquitylation, phosphorylation, and acetylation play a role in regulating virtually every cellular process. How these signaling events lead to observed changes in metabolic pathways, autophagy, and vesicular trafficking during bacterial infection remain unknown. Furthermore, how these processes may be manipulated by pathogens is crucial for understanding the pathogenic strategies of microorganisms. This proposal seeks to use powerful new proteomic technologies to globally quantify changes in ubiquitylation in order to identify novel functional macrophage responses to M. tuberculosis infection. Our preliminary experiments utilizing this approach have uncovered profound changes in host protein ubiquitylation in response to intracellular pathogens. These studies have provided the first glimpse into a vast unknown of post-translational modifications during innate immune responses. Our hypothesis is that these changes play fundamental roles in shaping the subsequent innate responses to infection by controlling autophagy, metabolism, protein degradation, and signaling, and may be manipulated by pathogens for their own benefit. Our preliminary genetic work indicates that novel pathways are controlled by ubiquitylation during infection and are capable of restricting M. tuberculosis growth in macrophages, further validating the power of this approach to uncover new biology. Ultimately, our long-term goal is to harness these powerful immune mechanisms for therapeutic purposes.

SUMMARY In the Proteomics Core (Core C), part of the Dengue Human Immunology Project Consortium, we will apply mass spectrometry-based proteomics approaches to quantitatively measure responses to viral infection and vaccination in clinical cohorts. We will first measure global changes in a number of protein readouts including phosphorylation, ubiquitination, and protein abundance, in ex vivo primary cells infected with Dengue virus to identify proteins of interest worth pursuing in more targeted proteomics studies in clinical samples. Data from Core C will be integrated with data from Cores B (Genomics Core) and D (Immune Monitoring Core) by Core E (Data Analysis and Modeling Core) to select approximately 200 proteins for which to develop sensitive assays for detection and quantification from very limited sample amounts. Finally, we will apply the developed assays to quantify protein responses in patient-derived samples from clinical cohorts in natural populations to compare clinical outcomes of viral infection and vaccination. These targeted proteomics approach will also be used to conduct ex vivo validation studies after perturbing predicted host driver genes.

? DESCRIPTION (provided by applicant): Chlamydia species are important causes of human disease for which no vaccine exists. An important gap in our knowledge is how this obligate intracellular parasite establishes a privileged niche--a membrane bound compartment termed the inclusion--in order to survive and replicate in the hostile intracellular environment. Chlamydiae encode a distinctive family of secreted effectors, the Incs (Inclusion membrane proteins) that are translocated from the bacteria and inserted into the inclusion membrane. We hypothesize that these effectors are ideally positioned at the host-pathogen interface to mediate interactions between the inclusion and the host and contribute to successful intracellular survival. This grant builds on our extensive preliminary studies in which we used large-scale affinity purification/mass spectrometry (AP-MS) to comprehensively identify protein- protein interactions (PPIs) between all C. trachomatis Incs and the human proteome. From amongst 404 interactions for 38/62 Incs, we identified a plethora of new potential interactions. We propose to use biochemical, cell biological, and newly developed Chlamydial genetic strategies to validate our highest priority Inc-host PPIs and explore their role in C. trachomatis infections. In Aim 1, we follow-up at the detailed molecular level our novel observation that IncE subverts retromer components and possibly a subset of syntaxins to modulate host cell vesicular trafficking. In aim 2, we will investigate the mechanism and functional significance of the interaction of the Inc CT192 with the dynactin complex. We propose that either CT192 sequesters dynactin to interfere with dynein-dependent transport or that it allows the inclusion to hitch a ride onto dynein-dependent microbule transport. The proposed approaches are applicable to other high confidence PPIs that we have identified and determined to be high priority. In aim 3, we team up with our Co-investigator, Dr. Nevan Krogan, to apply powerful new proteomic technologies to globally profile changes in the host ubiquitome in response to pathogens. Our finding that up to 12 Incs appear to interact with various components of the host cell ubiquitin machinery suggests that Chlamydia reprograms the host ubiquitin program to facilitate infection. We prioritized study of Inc CT383, as it is expressed early, predicted to interact with 3 different Ub ligases, and has the potential to substantially remodel the host ubiquitinome. Together, these aims build upon our extensive preliminary data and allow us to comprehensively understand how Chlamydia employs Incs to create a unique intracellular niche and reprogram the host.

PROJECT SUMMARY/ABSTRACT ? MASS SPECTROMETRY CORE The Mass Spectrometry Core will support research into the causes of tau toxicity in the context of Frontotemporal Dementia (FTD). The core will apply quantitative proteomics approaches to characterize post- translational modifications (PTMs) and protein-protein interactions (PPIs) of wildtype and FTD-mutants of tau. Although tau mutations and dysregulations are prominent in FTD, little is known about tau function in this disease, which is a common cause of young-onset dementia. A thorough description and exploration of tau- mediated FTD will provide a significant and essential resource for the neurological disorder community. We will comprehensively characterize tau PTMs in different cellular compartments and tissues using a novel platform we have developed that allows for the selective enrichment of tau from human brain tissues and cells. Combined with quantitative mass spectrometry (MS) approaches, we will comprehensively monitor acetylation, phosphorylation, ubiquitylation and methylation sites and determine their regulation in the context of FTD mutations. We will validate FTD mutant regulated PTM sites using a targeted approach called selected reaction monitoring (SRM). In contrast to systematic PTM site mapping which is used for hypothesis generation, SRM allows hypothesis testing by quantifying an a priori selected set of PTM sites in a highly accurate, sensitive, and reproducible fashion across many conditions and larger sample sets. Additionally, we will generate PPI maps for tau in the context of mutations, perturbations, and different cellular localizations. We will use classical affinity purification followed by MS (AP-MS) and novel APEX-based proximity biotinylation to identify tau-interacting proteins mediating aberrant activity and homeostasis in FTD neurons. We will study the interactome associated with both normal and FTD-mutants of tau in autophagosomes, autolysosomes and endosomes, and characterize the mechanisms of how tau is released in an activity-dependent manner as well as study the cellular machinery involved in normal or mutant tau uptake. The Core will interact with the CRISPR Core to functionally validate proteomics data and with the Data Core to integrate datasets and share results with the scientific community.

Project Summary/Abstract (Core C, Krogan) Core C of this renewal of NIH 5P01AI063302-12 will apply innovative proteomics approaches to study the early immune response to bacterial infection. Using mass spectrometry-based approaches, we will analyze macrophages infected with three different bacteria (L. monocytogenes, L. pneumophila, and M. tuberculosis) to identify the host and bacterial proteins that are ubiquitylated or phosphorylated during infection. This work will provide a comprehensive, global view of the posttranslational landscape during early infection, how these events influence host and pathogen defenses, and how these events vary across bacterial species. These global studies will dovetail with other, more targeted studies that employ host and bacterial mutants to perturb specific pathways and proteins. We will employ innovative and powerful modeling approaches to map and integrate this data to uncover the complex functions and pathways that are a part of the immune system's ability to detect and thwart bacterial pathogenesis, and the specific ways in which the pathogens are able to disrupt these mechanisms. The core's analysis and modeling work will serve three experimental Projects and will integrate the effort of each, providing a unified vision of the Program's results.

? DESCRIPTION (provided by applicant): The long-term goal of our research is to elucidate the mechanism of action of key fungal molecules that mediate pathogenesis. In recent years, proteomics technologies and analyses have advanced to the point where comprehensive, genome-wide studies of host-pathogen interactions can be performed. We propose to apply these technologies to identify mammalian host proteins that interact with secreted fungal proteins from the intracellular fungal pathogen Histoplasma capsulatum. This work is a collaboration between a fungal biologist experienced in Histoplasma molecular biology and genetics (Anita Sil, UCSF) and a premiere expert in using proteomics to identify host-pathogen interactions (Nevan Krogan, UCSF). After inhalation into mammalian hosts, Histoplasma senses the temperature of the host and undergoes a morphologic transition to yield yeast-form cells. Yeast cells colonize macrophages and must evade anti-microbial defenses to replicate to high levels within these immune cells. Based on precedent from viral and bacterial pathogens, we hypothesize that secreted factors from Histoplasma yeast cells are likely to interact with intracellular host proteins to manipulate the outcome of infection. We have used experimental data and bioinformatics analyses to identify secreted fungal proteins with preferential expression in the yeast form of Histoplasma. We will use a robust proteomics pipeline developed by the Krogan laboratory to define the network of host proteins that interact with these putative fungal virulence factors. We will then exploit host and pathogen genetics to define the role of these host-pathogen protein-protein interactions during infection. Analysis of the resultant dataset will generate specific hypotheses about mechanisms of pathogenesis that will fuel current and future advances in our understanding of how fungi manipulate host cells. Ultimately, these studies will lead to the development of anti-fungal therapeutics that will target key molecules in ubiquitous fungal pathogen.

ADMINISTRATIVE CORE SUMMARY The mission of the ?Administrative Core is to support and promote the scientific and outreach goals of the Host Pathogen Map Initiative (HPMI). Amongst its responsibilities, the Core will perform the following: provide leadership that ensures strong oversight and representation of all stakeholders in decisions; facilitate integration of research projects; and connect the HPMI to the broader community interested in infectious disease. Day-to-day activities will be coordinated by a cross-campus team consisting of the HPMI Leaders (Dr. Nevan Krogan, the contact PI, and Dr. Jeff Cox) and the Grant Administrators (Donna Even-Kesef and Anny Lin). The entire leadership team, equally split between UCSF and UCB, has extensive experience leading and managing large research grants. We will also form a Steering Committee consisting of the Co-Investigators, which will evaluate the progress and needs of each component, review and possibly modify priorities, and identify areas deserving extra focus. An External Advisory Committee (EAC) will be formed to review the Center?s progress and future plans. To facilitate communication amongst Center members and with the other members of the community, the ?Administrative Core ?will organize and manage a number of regularly scheduled meetings, some specifically for members of the Steering Committee and others for the entire HPMI. These various meetings will provide ample opportunities to discuss overall research directions and specific experimental concerns. The Core will plan a workshop for early spring of 2018, which will feature talks by all 12 HPMI faculty members along with talks from other members of the infectious disease community. The Administrative Core ?will lead the maintenance of the HPMI ?website (http://www.hpmi.ucsf.edu) and shared file servers. To provide formal site review and involvement with NIH, the Core will organize an annual EAC Meeting, in which the PIs and key personnel will meet with the EAC and NIH program staff to review the Center?s activities. The EAC Meeting will be held in conjunction with an annual Infectious Disease Quantitative Biology Symposium, an event that will be organized by the ?Administrative Core.? ?Overall, the ?Administrative Core will ensure that projects are productive, synergistic and have sufficient support; that resource-sharing obligations are met; and that outreach activities are of maximum impact.

CORE 1: FUNCTIONAL GENOMICS  SUMMARY   The objective of the Functional Genomics Core (FGC) is to provide cutting­edge and innovative technologies  for  the  functional  characterization  of  the  genome  in  a  reliable,  reproducible  and  cost­efficient  manner.  It  will  support ?Project 1 ?and Project 2 by facilitating proteomics experiments, including mapping of physical protein  interactions, and CRISPR experiments, including mapping of genetic interactions. In particular, the FGC will  perform  mass  spectrometry  characterization,  CRISPR  gene  editing,  CRISPRi  and  CRISPRa  screening,  and  provide expertise in data processing for these experimental platforms. This core will be comprised of three well  established facilities: the Thermo Fisher Scientific Proteomics Facility for Disease Target Discovery located at  the J. David Gladstone Institutes, the UCSD Institute for Genomic Medicine (IGM) Genomics Center and the  UCSD Center for Computational Biology & Bioinformatics (CCBB). Additionally, we propose to create a new  CRISPR screening core that leverages the Mali lab?s ?foundational expertise in genome engineering.  The FGC core will be led by two pioneers in the fields of functional genomics, Drs. Krogan and Mali, who will  employ  state­of­the­art  techniques,  many  of  which  were  developed  or  optimized  in  their  respective  labs.  Co­Investigator Alan Ashworth, an internationally recognized expert in breast cancer genomics and one of the  first  to  demonstrate  the  therapeutic  promise  targeting  synthetic  lethal  interactions  in  cancer,  will  contribute  expertise in target selection. Dr. Ashworth?s input will ensure that considerations of translational impact will be  incorporated  at  all  stages  of  experimentation.  FGC  technologies  will  be  used  extensively  by  ?Project  1  ?and  Project 2?. The FGC will not only enable Center investigators to accomplish the individual aims of this proposal,  it will also serve as a resource to the wider scientific community by disseminating new assays and protocols.       

  PROJECT 1: SYSTEMATIC IDENTIFICATION OF DRIVER NETWORKS IN CANCER   SUMMARY  A vast number of mutations contribute to cancer, but the observed non­random combinations of those leading  to  transformation  highlight  the  importance  of  hallmark  pathways  and  networks  in  cancer  progression.  While  many pathways have been implicated in cancer, attributes such as tumor heterogeneity, tissue of origin, and  degree of progression lead to each case exhibiting a unique subset of altered pathways. Taken together, this  diversity  among  cancer  types  and  their  origins  has  complicated  the  development  of  targeted  cancer  treatments. We propose here to systematically identify the protein networks that drive cancer, across a range  of  tumor  types  starting  with  head  and  neck  squamous  cell  carcinoma  (HNSCC)  and  breast  cancer  (BC).  Coupled  with  functional  validation  and  high­resolution  structural  analysis  of  the  key  protein  interactions  and  complexes, we anticipate major insights into the underlying tumor biology as well as the potential to unravel  genetic vulnerabilities of therapeutic relevance.   In ?Project 1?, CCMI investigators will build a physical interaction mapping pipeline focused on understanding  the  underlying  network  biology  behind  cancer.  To  this  end,  we  are  targeting  80  genes  genetically  linked  to  either HNSCC or BC and subjecting the wild­type proteins and numerous mutant forms to affinity purification  mass spectrometry (AP­MS) in a panel of relevant cancer subtype cell lines (?Aim 1?). To complement these  data we will perform functional kinome screens using the high throughput kinase­activity mapping (HT­KAM)  platform, which will quantify how kinase signaling networks are rewired by different protein mutations, and in  different cellular backgrounds. Next, we will use the computational technique of network propagation to define  the major mutated driver pathways underlying each disease subtype, in which physical protein interactions are  integrated  with  somatic  and  germline  mutations  identified  in  tumor  genomes.  The  results  of  this  network  characterization (?Aim 1?) and integrative analysis (?Aim 2?) will identify network components that could serve as  targets for therapeutic intervention? in ?Aim 3 we will perform cellular assays to validate these network targets.  Lastly,  in  ?Aim  4  ?we  will  use  cryogenic  electron  microscopy  (cryo­EM)  to  structurally  characterize  therapeutically actionable protein complexes and develop technology to enable the screening of many more.  Successful completion of this work will yield a network mapping pipeline that can be extended to many cancer  types and will aid in the rational selection of therapeutic targets with greater precision and speed.          

THE CANCER CELL MAP INITIATIVE:  A NATIONAL RESEARCH CENTER FOR CANCER SYSTEMS BIOLOGY  OVERALL SUMMARY  The Cancer Genome Atlas and sister projects have now completed analysis of over 10,000 tumor genomes,  providing  a  catalog  of  the  gene  mutations,  copy  number  variants  and  other  genetic  alterations  that  cause  cancer. In many cases it remains unclear, however, which are the key driver mutations or dependencies in a  given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types  and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that  these  mutations  recurrently  hijack  the  same  hallmark  molecular  pathways  and  networks.  For  this  reason,  cancer  research  and  treatment  is  increasingly  dependent  on  knowledge  of  biological  networks  of  multiple  types,  including  physical  interactions  among  proteins  and  synthetic­lethal  and  epistatic  interactions  among  genes.  Here  we  seek  support  for  a  new  effort,  The  Cancer  Cell  Map  Initiative  (CCMI),  aimed  at  comprehensively detailing these complex interactions among cancer genes and proteins and how they differ  between  diseased  and  healthy  states.  The  CCMI  is  a  multi­campus  initiative  of  the  University  of  California,  centered at UC San Francisco and UC San Diego, which leverages advanced network mapping, computational  analysis and cancer research platforms developed by multiple CCMI investigators over the past decade. Thus  primed, these platforms will be turned to efficiently generate, assemble and analyze cancer molecular networks  with a view towards pathway and network­based personalized therapy. Specifically, over the next five years  the CCMI will seek to catalyze major phase transitions in cancer research and therapy by (1) Comprehensively  mapping  the  networks  of  physical  interactions  among  cancer  proteins,  revealing  the  protein  complexes  and  higher­order  molecular  units  under  selection  in  cancer?  (2)  Mapping  the  parallel  networks  of  synthetic­lethal  and epistatic interactions among cancer genes, revealing the functional logic of cancer? (3) Establishing the  robust  computational  methodology,  end­user  software,  and  databases  for  assembly  and  use  of  cancer  cell  network maps in both basic and clinical modalities? (4) Building a critical mass of leading cancer investigators  worldwide  to  expand  CCMI  into  a  global  coordinated  partnership?  and  (5)  Training  the  current  and  next­generation of scientists in Network Biology and its applications to cancer research.      

The goal of Core 1 is to provide mass spectrometry-based proteomic platforms for global and targeted characterization of HIV and host proteins in support of the aims and efforts for Projects 1-7 of the HARC Center. We are continuously developing new innovative strategies and improvements for more sensitive and quantitative analysis of protein abundance and posttranslational modifications, as well as for protein-protein interactions (PPIs) and protein structure determination. Our affinity-purification mass spectrometry (AP-MS) capabilities, along with newly developed proximity-based biotinylation (APEX-MS) and cross-linking mass spectrometry (XL-MS) platforms, will aid research in Projects 1-6 through interaction network mapping for Vif, Vpu, Nef, Tat, and Rev proteins in the context of HIV infection, as well as new factors identified through our unique evolutionary analysis in Project 7. Also, our new global PTM analyses pipeline will provide direct support for researchers in Projects 2, 3 and 5, focused on Vif, Vpu and Tat, respectively. Core 1 will work closely with Core 5, which will focus on computationally analyzing all the proteomic data generated. In addition, our XL-MS capabilities will also collaborate with Core 5 for structural determination and protein-interface mapping analysis for Projects 1, 3, 4 and 5. The expertise, highly sensitive MS-analysis, and ongoing innovations provided by Core 1 will continue to serve and adapt to the needs of Projects and Cores of the HARC Center.

The overall goal ofthe Modeling Core is to drive the integration of global -OMICS data to identify virus-host networks that control the innate immune response and influence pathogenicity. This will be accomplished through two main objectives a) to design and provide tools to analyze -OMICS data and b) to serve as an engine for integrating -OMICS data into network models of pathogenicity that are subject to further refinement in an iterative fashion. This Core will employ existing bioinformatics and systems biology approaches as well as develop novel approaches to identify cellular proteins and networks which influence influenza virus replication and contribute to virulence in vivo. The modeling core will be the engine for translating -OMICS data into biological insight and has a central role in the successful completion of this program. Co-directors Bandyopadhyay and Krogan have a strong history of innovation and collaboration with each other and others on this proposal and are well suited to direct the modeling efforts. Predictions that are based upon our models will be tested in primary cell culture and in animal model systems by employing targeted -OMICS technologies as well as in vivo experimentation and analysis of clinical phenotypes.

PROJECT 1: SYSTEMATIC IDENTIFICATION OF HOST NETWORKS IN INFECTIOUS DISEASE PATHOGENESIS SUMMARY The Centers for Disease Control and Prevention (CDC) estimates that more than 2 million people acquire a serious drug-resistant bacterial infections each year, with at least 23,000 deaths resulting. These numbers will increase dramatically as the frequency of multidrug resistant bacteria rise and infections spread worldwide. Unfortunately, the production of novel classes of antibiotics has stagnated since the 1960s, thus underscoring a critical need for the development of alternate approaches that can be used to treat infection. There has been a new push for the development of host-directed therapies for treatment of infectious diseases as they are expected to be less susceptible to drug-resistance. In addition, recent work has revealed that while similar proteins may not be targeted by different pathogens, the same functional pathways are often hijacked and re-wired during the course of infection. Thus, drugs that target host pathways, rather than individual pathogen factors, may represent improved targets for treatment. For these reasons, the study of infectious disease is becoming increasingly dependent on knowledge of host biological networks of multiple types, including physical interactions among proteins, which allow for deconstruction of functional pathways. Here we propose to systematically identify the protein networks that drive pathogenesis in clinically relevant model systems. Coupled with functional validation and high-resolution structural analysis of key pathogen-host interactions and complexes, we anticipate major insights into the underlying biology of pathogenesis, as well as the potential to unravel novel vulnerabilities of therapeutic relevance. To this end, we are targeting hundreds of pathogen encoded genes from ?Mycobacte? rium tuberculosis, Staph? ylococcus aureus, and ?Chla? mydia trachomatis, and subjecting them to affinity purification mass spectrometry (AP-MS) in a panel of clinically relevant immune cell lines (?Aim 1?). To complement these data we will perform proteome wide quantitative profiling of phosphorylation, ubiquitylation and protein abundance levels over a time course of pathogen infection (?Aim 2?). In ?Aim 3, ?we will use a suite of structural characterization methods, including X-ray crystallography, cryogenic electron microscopy (cryo-EM) and cross-linking mass spectrometry (XL-MS) to structurally characterize therapeutically actionable protein complexes and signaling nodes. These aims will inform the selection of host target proteins for ?in vivo validation in ?Aim 4?, in which we will generate knockout mice and subject them to infection to test for increased resistance to bacterial pathogens. Successful completion of this this work will not only significantly enrich our limited understanding of host-pathogen networks interactions, but it will also identify novel therapeutic opportunities for these three pathogens. Additionally, the development of this platform will yield an integrated systems-to-structure pipeline that can be extended to many pathogen types, and will aid in the rational selection of therapeutic targets with greater precision and speed. 1

SUMMARY The global burden of mental illness, including autism spectrum disorders (ASD), intellectual disability, epilepsy, Tourette disorder, schizophrenia and bipolar disorder, is enormous, whether measured in health care expenditures, lost productivity, or personal suffering. Unfortunately, there is a striking lack of insight into the underlying molecular biology of these syndromes. However, recent advances in gene discovery are setting the stage for a transformation in the understanding of these psychiatric disorders. Understanding pathobiology and developing novel treatments is becoming increasingly dependent on knowledge of biological networks of multiple types, including physical interactions among proteins and synthetic­lethal and epistatic interactions among genes. Here we seek support for a new effort, the Psychiatric Cell Map Initiative (PCMI, www.pcmi.ucsf.edu), aimed at comprehensively understanding these complex interactions in psychiatric disorders and how they differ between diseased and healthy states. While we will focus on ASD in this proposal, this work will establish a paradigm to investigate other psychiatric disorders in future work. The PCMI is a multi­campus initiative of the University of California, involving UC San Francisco, UC San Diego and UC Berkeley, which leverages genomics, proteomics, high­throughput sequencing, advanced network mapping, computational analysis, and research platforms developed by multiple PCMI investigators over the past decade. Thus primed, these platforms will be tuned to efficiently generate, assemble, and analyze molecular networks linked to ASD, in relevant cell types, with a view towards pathway and network­based personalized therapy. Specifically, over the next five years the PCMI will seek to catalyze major phase transitions in ASD research and therapy by (1) Comprehensively mapping the networks of physical interactions among proteins linked to ASD, revealing the protein complexes and higher­order molecular units underlying ASD in multiple cell types of the human brain? (2) Mapping the parallel networks of synthetic­lethal and epistatic interactions among ASD genes using CRISPR­based approaches? (3) Establishing the robust computational methodology, end­user software, and databases for assembly and use of ASD cell network maps in both basic and clinical modalities? (4) Translating molecular insights into an understanding of higher order phenotypes? (5) Building a critical mass of leading investigators focused on psychiatric disorders worldwide to expand PCMI into a global coordinated partnership? and (6) Training the current and next­generation of scientists in Network Biology and its applications to research focused on psychiatric disorders.

THE HOST PATHOGEN MAP INITIATIVE: A NATIONAL RESEARCH CENTER FOR SYSTEMS BIOLOGY OF INFECTIOUS DISEASE OVERALL SUMMARY Antibiotic-resistant pathogens are no longer an ?emerging? threat as we face the reality of a return to the pre-antibiotic age where treatments for the simplest microbial infections are ineffective. The Centers for Disease Control and Prevention (CDC) estimates that more than 2 million people acquire a serious resistant bacterial infection each year, and at least 23,000 deaths result. These numbers will increase dramatically as our ability to fight these infections diminishes. Unfortunately, there have been no novel classes of antibiotics discovered since the 1960s, underscoring the fact that novel approaches are required to develop novel therapies to treat infection. As a result of these facts, it is now being realized that efforts to develop host-directed therapies to treat infectious diseases may have unique advantages. Also, recent work has revealed that although similar proteins may not be targeted by different pathogens, the same functional pathways are often hijacked and re-wired during the course of infection. For these reasons, the study of infectious disease is becoming increasingly dependent on knowledge of biological networks of multiple types, including physical interactions among proteins and synthetic-lethal and epistatic interactions among genes, which allow for deconstruction of functional pathways. Here we seek support for a new effort, termed The Host Pathogen Map Initiative (HPMI) (http://www.hpmi.ucsf.edu), aimed at comprehensively detailing the complex interactions among pathogenic genes and proteins with the host factors they hijack and rewire during the course of infection. The HPMI is a multi-campus initiative of the University of California, centered at UC San Francisco and UC-Berkeley, which leverages advanced network mapping, computational analysis and infectious disease research platforms developed by multiple HPMI investigators over the past decade. Thus primed, these platforms will be turned to efficiently generate, assemble, and analyze host-pathogen molecular networks with a view towards using this information in a clinical setting. Over the next five years, the HPMI will seek to catalyze major phase transitions in pathogenesis research by (1) Comprehensively mapping the networks of physical interactions using sets of secreted proteins from three bacteria; ?Mycobacterium tuberculosis (Mtb), ?Staphylococcus aureus (SA) and ?Chlamydia trachomatis (CT) with their host, revealing the protein complexes and higher-order molecular units targeted by these pathogens; (2) Mapping the parallel networks of synthetic-lethal and epistatic interactions among the genes being targeted by the bacteria, revealing the functional logic of pathogenesis; (3) Establishing the robust computational methodology, end-user software, and databases for assembly and use of host-pathogen network maps in both basic and clinical modalities; (4) Building a critical mass of leading infectious disease investigators worldwide to expand HPMI into a global coordinated partnership; and (5) Training the current and next-generation of scientists in Network Biology and its applications to infectious disease research.

Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer?s disease (AD). In fact, more than 70 million Americans are at higher risk for AD because of their apoE4 carrier status. Two-thirds of AD patients are apoE4 carriers, with apoE4 increasing the risk and decreasing the age of onset of this devastating disease. Understanding how apoE4 causes neuropathology is critically important because it will guide the development of therapies to retard, or possibly prevent, apoE4-associated neuropathology. This proposal builds on our hypothesis that apoE4-associated neuropathology is related to the susceptibility of apoE4 to neuron-specific proteolysis. Neurotoxic fragments resulting from the proteolysis escape the secretory pathway and enter the cytosol where they alter several cellular and metabolic processes (e.g., mitochondrial dysfunction and cytoskeletal alterations). Human apoE4 carriers, even 20?30-year-old cognitively normal subjects, display brain glucose hypometabolism and impaired mitochondrial enzyme activity. In mouse neurons expressing human apoE4, several abnormalities arise. For example, apoE4 is associated with impaired mitochondrial respiration, neurite outgrowth and neurotoxicity, and these can be reversed by apoE4 structure correctors that convert apoE4 to an apoE3-like conformation, thus preventing neurotoxic fragment generation and neurodegeneration. Despite our advances in understanding the genesis and ultimate consequences of apoE4 proteolysis in neurons, many of the defining intermediate steps remain unclear. Indeed, our preliminary results indicate potentially broad detrimental downstream effects of apoE4 expression in neural cells. The goal of this project is to exploit the combined expertise of the Mahley and Krogan laboratories and advanced proteomic and genetic analyses of our models of apoE4-mediated neurotoxicity to establish how apoE4 alters neuronal processes/metabolism. We will combine label-free quantitative mass spectrometry?based protein-protein interaction pathway analysis with profiling of the total and post-translational modification proteomes, and validate targets using transcriptomic profiling and the latest CRISPRi/a gene regulation technologies. Comparing changes in neuronal protein networks associated with the expression of apoE3, apoE4, and the predominant apoE4(1?272) fragment in cultured neurons will elucidate the critical mediators of apoE4 neurotoxicity. Treatment of the apoE4 neurons with an apoE4 structure corrector will establish the importance of apoE4 structure to alterations in the neuronal proteome. Our joint expertise positions us well to address these longstanding questions about apoE4 function in the nervous system, and our preliminary data demonstrate the validity of our methods to identify new targets. Our multi-omic approach will yield mechanistic insights into apoE4-driven neuropathology and fill critical gaps in our understanding of AD pathogenesis.

PROJECT SUMMARY/ABSTRACT CORE A ? ADVANCED PROTEOMICS CORE The goal of Core A is to provide mass spectrometry?based proteomic platforms for global and targeted characterization of transcriptional regulators that play a central role in cardiac development and congenital heart defects in support of the aims and efforts for Projects 1?3 of the proposed PPG Project. We are continuously developing new and innovative strategies for more sensitive and quantitative analysis of protein- protein interactions (PPIs) and post-translational modifications (PTMs). These efforts now allow us to look beyond static PPIs or PTMs and towards more dynamic characterization in the context of different developmental stages, gene knockouts or gene mutations. Our affinity-purification mass spectrometry (AP-MS) capabilities along with newly developed proximity-based biotinylation (APEX-MS), will aid research in Projects 1?3 through dynamic interaction network mapping for transcriptional regulators, such as GATA4, TBX5, MEF2C, Myocardin and BAF complex members. Also, our quantitative analyses pipeline to determine PTMs on specific proteins will provide direct support for researchers in Project 3, focused on MEF2C and Myocardin, two signal responsive factors. All of these experiments will be performed in relevant systems for cardiac development, either induced pluripotent stem cell (iPSC)- or embryonic stem cell (ESC)-derived cardiac precursors (CPs), as well as cardiomyocytes (CMs) or cardiac tissue derived from neonatal mice. Beyond support of the projects, Core A will work closely with Core B to develop analysis strategies for APEX-MS data. The expertise, the highly sensitive and quantitative MS analysis, as well as ongoing innovations provided by Core A will serve and adapt to the needs of Projects and Cores of the PPG project.

ABSTRACT The filoviruses, Ebola and Marburg viruses (EBOV and MARV), are emerging, negative-strand RNA viruses associated with outbreaks of severe viral hemorrhagic fever. The virulence and emerging nature of these zoonotic pathogens makes them a significant threat to human health, potential agents of bioterrorism, and NIAID category A priority pathogens. Currently, no approved anti-filovirus therapeutics are available. Importantly, there is a major gap in our understanding with regard to the role of host factors at critical stages in the viral replication cycle. The overall goal of this revised R01 application is to characterize EBOV VP30 (eVP30), a key viral protein that facilitates viral transcription, and its interactions with host factors. Our plan builds on recent successes in structurally and functionally characterizing how eVP30 interacts with the viral nucleoprotein (NP) to modulate EBOV RNA synthesis and on a joint (Amarasinghe, Basler, and Krogan groups) unbiased proteomics screen using EBOV proteins as bait that uncovered 193 high-confidence EBOV- human protein-protein interactions (PPIs), including one between eVP30 and the host ubiquitin ligase RBBP6. A crystal structure of this complex revealed that RBBP6 and the viral NP compete for the same VP30 binding surface. Comparison of NP and RBBP6 peptides that bind eVP30 revealed a common PPxPxY motif that is necessary for the interaction. Whereas knockdown of endogenous RBBP6 stimulated viral transcription and increased EBOV infectivity, overexpression of RBBP6 or its peptide severely inhibited EBOV transcription and infection. Interestingly, at least two additional eVP30 interactors from our dataset (hnRNP L and hnRNP UL1) also possess PPxPxY motifs. Based on these findings, we propose a multidisciplinary approach to (1) Determine the structure of eVP30 N-terminus and define its association with RNA and protein ligands in the absence and presence of NP; (2) Determine the mechanisms by which eVP30-interacting proteins RBBP6, hnRNP L, and hnRNP UL1 modulate eVP30 function and RNA synthesis; and (3) Test the hypothesis that eVP30 modulates the function of host factors RBBP6, hnRNP L, and hnRNP UL1. These studies will characterize unique host interactions that negatively regulate EBOV replication with the goals of defining how EBOV manipulates host pathways and identifying novel therapeutic targets.

TITLE CasCUT&RUN: An in vivo method to analyze locus-specific protein complexes driving transcription of target genes in cancer Project Summary/Abstract Aberrant regulation of gene transcription commonly causes disease, including cancer. Transcriptional regulatory factors (TFs) are central players, binding to specific genomic response elements and nucleating assembly of multiprotein transcriptional regulatory complexes (TRCs) whose compositions and conformations are sensitive to gene, cell, and physiological context. For the many cancers in which a causative gene displays altered transcription, detailed analysis of causative TRCs would open direct routes to mechanisms (even if the driver is upstream, e.g., in a signaling pathway), and to potential treatments. However, no existing method can identify the unique combination of TFs and coregulator factors that occupy a single-locus mammalian response element in vivo. Described here are the development and validation of a new technology, CasCUT&RUN, which exploits at two steps the precision of Cas9 RNP genomic locus specificity to enable for the first time the isolation, purification and compositional identification of in vivo assembled, response element-specific TRCs from single loci in the human genome. The method will be unbiased, enabling identification of unique combinations of ~102 polypeptides that comprise individual TRCs, and amenable to future structural analysis by cryo-EM to detect conformational changes associated with altered regulation. Finally, CasCUT&RUN will be seamlessly adaptable to primary normal and tumor patient samples. Three specific aims are envisioned: 1. Develop and optimize: accuracy and sensitivity of isolation of promoter-bound RNA polymerase II transcription initiation complexes. Develop CasCUT&RUN using a collection of cell lines containing 1-200 copies of a single RNA polymerase II promoter, focused initially on recovering the many well-established promoter-bound proteins, and later on optimization to single copy sensitivity. 2. Isolate single locus TRCs and identify bound proteins in established cell lines. Use the same cell line collection to purify TRCs by CasCUT&RUN, focusing on the 1-200 copies of a glucocorticoid response element that confers hormone-inducible transcription on each of the linked promoters. When single copy sensitivity is achieved, isolate and analyze an endogenous single copy TRC in a second cell culture line. 3. Isolate single locus TRCs and identify bound proteins in primary cancer patient samples. Further develop CasCUT&RUN techniques for use in primary patient leukemia cells and formalin-fixed paraffin embedded solid tumor biopsies, and validate single copy TRC examined in Aim 2. These experiments will provide proof-of-principle for a new technology that can be applied to the wide range of cancers that display dysregulation of transcription of causative genes. CasCUT&RUN will also correlate structure, mechanism and pathophysiology in ways that could yield deep insight into combinatorial transcriptional regulation and its linkage to signaling networks, as well as pathways that produce or enhance cancer, or that cause resistance to therapies.

SUMMARY The global burden of mental illness, including autism spectrum disorders (ASD), intellectual disability, epilepsy, Tourette disorder, schizophrenia and bipolar disorder, is enormous, whether measured in health care expenditures, lost productivity, or personal suffering. Unfortunately, there is a striking lack of insight into the underlying molecular biology of these syndromes. However, recent advances in gene discovery are setting the stage for a transformation in the understanding of these psychiatric disorders. Understanding pathobiology and developing novel treatments is becoming increasingly dependent on knowledge of biological networks of multiple types, including physical interactions among proteins and synthetic­lethal and epistatic interactions among genes. Here we seek support for a new effort, the Psychiatric Cell Map Initiative (PCMI, www.pcmi.ucsf.edu), aimed at comprehensively understanding these complex interactions in psychiatric disorders and how they differ between diseased and healthy states. While we will focus on ASD in this proposal, this work will establish a paradigm to investigate other psychiatric disorders in future work. The PCMI is a multi­campus initiative of the University of California, involving UC San Francisco, UC San Diego and UC Berkeley, which leverages genomics, proteomics, high­throughput sequencing, advanced network mapping, computational analysis, and research platforms developed by multiple PCMI investigators over the past decade. Thus primed, these platforms will be tuned to efficiently generate, assemble, and analyze molecular networks linked to ASD, in relevant cell types, with a view towards pathway and network­based personalized therapy. Specifically, over the next five years the PCMI will seek to catalyze major phase transitions in ASD research and therapy by (1) Comprehensively mapping the networks of physical interactions among proteins linked to ASD, revealing the protein complexes and higher­order molecular units underlying ASD in multiple cell types of the human brain? (2) Mapping the parallel networks of synthetic­lethal and epistatic interactions among ASD genes using CRISPR­based approaches? (3) Establishing the robust computational methodology, end­user software, and databases for assembly and use of ASD cell network maps in both basic and clinical modalities? (4) Translating molecular insights into an understanding of higher order phenotypes? (5) Building a critical mass of leading investigators focused on psychiatric disorders worldwide to expand PCMI into a global coordinated partnership? and (6) Training the current and next­generation of scientists in Network Biology and its applications to research focused on psychiatric disorders.