Attenuated IL-2 muteins leverage the TCR signal to enhance regulatory T cell homeostasis and response in vivo

Interleukin-2 (IL-2), along with T-cell receptor (TCR) signaling, are required to control regulatory T cell (Treg) homeostasis and function in vivo. Due to the heightened sensitivity to IL-2, Tregs retain the ability to respond to low-dose or attenuated forms of IL-2, as currently being developed for clinical use to treat inflammatory diseases. While attenuated IL-2 increases Treg selectivity, the question remains as to whether a weakened IL-2 signal sufficiently enhances Treg suppressive function(s) toward disease modification. To understand this question, we characterized the in vivo activity and transcriptomic profiles of two different attenuated IL-2 muteins in comparison with wildtype (WT) IL-2. Our study showed that, in addition to favoring Tregs, the attenuated muteins induced disproportionately robust effects on Treg activation and conversion to effector Treg (eTreg) phenotype. Our data furthermore suggested that Tregs activated by attenuated IL-2 muteins showed reduced dependence on TCR signal, at least in part due to the enhanced ability of IL-2 muteins to amplify the TCR signal in vivo. These results point to a new paradigm wherein IL-2 influences Tregs’ sensitivity to antigenic signal, and that the combination effect may be leveraged for therapeutic use of attenuated IL-2 muteins

Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex

Dissecting genotype-phenotype relationships through integration and analysis of differential genetic interaction maps

Epistasis, refers to the phenomenon, in which the phenotypic effect of one gene depends on or is modified by a secondary gene. High-throughput screening of genetic interactions has been made possible through a variety of methods such as Synthetic Genetic Array, combinatorial RNAi and genome-wide association studies. However, thus far the majority of data has been generated in standard laboratory conditions. Yet in the course of their lives, cells are exposed to a wide-array of environmental stresses. How genetic interaction networks are re-wired in response to such stimuli remains an open question. In this thesis, I describe the generation and analysis of differential genetic interaction data, in response to numerous genotoxic stresses and demonstrate how this data can be used to elucidate cellular pathways required for the response to these stresses. In Chapter 2, I describe the development of computational and visualization algorithms designed to integrate physical and differential genetic interaction data. This integrative approach enables the automatic assembly of raw interactions into pathway models and maps the higher-order functional relationships between such pathways. In Chapter 3, I map changes in the cell's genetic network across a panel of mechanistically distinct DNA-damaging agents. This multi- conditional genetic interaction map identifies both agent- specific and general DNA damage response pathways. More over, we anticipate that this data will be an important resource for the study of the DDR and its associated diseases. In Chapters 4 and 5, I describe our efforts to analyze genetic interactions derived from forward genetic screening approaches, such as genome-wide association studies (GWAS). We develop a novel computational algorithm, which greatly increases our power to detect such interactions and furthermore, through projection of these genetic interactions within and across protein complexes, demonstrate that such pathway-based interpretations of GWAS data provide novel hypothesis regarding the mechanism through which combinations of polymorphisms may affect a phenotyp

Global reconstruction of the human metabolic network based on genomic and bibliomic data.

Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology

A UV-Induced Genetic Network Links the RSC Complex to Nucleotide Excision Repair and Shows Dose-Dependent Rewiring

Efficient repair of UV-induced DNA damage requires the precise coordination of nucleotide excision repair (NER) with numerous other biological processes. To map this crosstalk, we generated a differential genetic interaction map centered on quantitative growth measurements of >45,000 double mutants before and after different doses of UV radiation. Integration of genetic data with physical interaction networks identified a global map of 89 UV-induced functional interactions among 62 protein complexes, including a number of links between the RSC complex and several NER factors. We show that RSC is recruited to both silenced and transcribed loci following UV damage where it facilitates efficient repair by promoting nucleosome remodeling. Finally, a comparison of the response to high versus low levels of UV shows that the degree of genetic rewiring correlates with dose of UV and reveals a network of dose-specific interactions. This study makes available a large resource of UV-induced interactions, and it illustrates a methodology for identifying dose-dependent interactions based on quantitative shifts in genetic networks

Early Assessment of Molecular Progression and Response by Whole-genome Circulating Tumor DNA in Advanced Solid Tumors.

Treatment response assessment for patients with advanced solid tumors is complex and existing methods require greater precision. Current guidelines rely on imaging, which has known limitations, including the time required to show a deterministic change in target lesions. Serial changes in whole-genome (WG) circulating tumor DNA (ctDNA) were used to assess response or resistance to treatment early in the treatment course. Ninety-six patients with advanced cancer were prospectively enrolled (91 analyzed and 5 excluded), and blood was collected before and after initiation of a new, systemic treatment. Plasma cell-free DNA libraries were prepared for either WG or WG bisulfite sequencing. Longitudinal changes in the fraction of ctDNA were quantified to retrospectively identify molecular progression (MP) or major molecular response (MMR). Study endpoints were concordance with first follow-up imaging (FFUI) and stratification of progression-free survival (PFS) and overall survival (OS). Patients with MP (n = 13) had significantly shorter PFS (median 62 days vs. 310 days) and OS (255 days vs. not reached). Sensitivity for MP to identify clinical progression was 54% and specificity was 100%. MP calls were from samples taken a median of 28 days into treatment and 39 days before FFUI. Patients with MMR (n = 27) had significantly longer PFS and OS compared with those with neither call (n = 51). These results demonstrated that ctDNA changes early after treatment initiation inform response to treatment and correlate with long-term clinical outcomes. Once validated, molecular response assessment can enable early treatment change minimizing side effects and costs associated with additional cycles of ineffective treatment

Dissection of DNA Damage Responses Using Multiconditional Genetic Interaction Maps

To protect the genome, cells have evolved a diverse set of pathways designed to sense, signal, and repair multiple types of DNA damage. To assess the degree of coordination and crosstalk among these pathways, we systematically mapped changes in the cell's genetic network across a panel of different DNA-damaging agents, resulting in ~1,800,000 differential measurements. Each agent was associated with a distinct interaction pattern, which, unlike single-mutant phenotypes or gene expression data, has high statistical power to pinpoint the specific repair mechanisms at work. The agent-specific networks revealed roles for the histone acetyltranferase Rtt109 in the mutagenic bypass of DNA lesions and the neddylation machinery in cell-cycle regulation and genome stability, while the network induced by multiple agents implicates Irc21, an uncharacterized protein, in checkpoint control and DNA repair. Our multiconditional genetic interaction map provides a unique resource that identifies agent-specific and general DNA damage response pathways

Quantitative Proteomics Reveal ATM Kinase-dependent Exchange in DNA Damage Response Complexes

ATM is a protein kinase that initiates a well-characterized signaling cascade in cells exposed to ionizing radiation (IR). However, the role for ATM in coordinating critical protein interactions and subsequent exchanges within DNA damage response (DDR) complexes is unknown. We combined SILAC-based tandem mass spectrometry and a subcellular fractionation protocol to interrogate the proteome of irradiated cells treated with or without the ATM kinase inhibitor KU55933. We developed an integrative network analysis to identify and prioritize proteins that were responsive to KU55933, specifically in chromatin, and that were also enriched for physical interactions with known DNA repair proteins. This analysis identified 53BP1 and annexin A1 (ANXA1) as strong candidates. Using fluorescence recovery after photobleaching, we found that the exchange of GFP-53BP1 in DDR complexes decreased with KU55933. Further, we found that ANXA1 knockdown sensitized cells to IR via a mechanism that was not potentiated by KU55933. Our study reveals a role for ATM kinase activity in the dynamic exchange of proteins in DDR complexes and identifies a role for ANXA1 in cellular radioprotection

Quantitative Proteomics Reveal ATM Kinase-dependent Exchange in DNA Damage Response Complexes

ATM is a protein kinase that initiates a well-characterized signaling cascade in cells exposed to ionizing radiation (IR). However, the role for ATM in coordinating critical protein interactions and subsequent exchanges within DNA damage response (DDR) complexes is unknown. We combined SILAC-based tandem mass spectrometry and a subcellular fractionation protocol to interrogate the proteome of irradiated cells treated with or without the ATM kinase inhibitor KU55933. We developed an integrative network analysis to identify and prioritize proteins that were responsive to KU55933, specifically in chromatin, and that were also enriched for physical interactions with known DNA repair proteins. This analysis identified 53BP1 and annexin A1 (ANXA1) as strong candidates. Using fluorescence recovery after photobleaching, we found that the exchange of GFP-53BP1 in DDR complexes decreased with KU55933. Further, we found that ANXA1 knockdown sensitized cells to IR via a mechanism that was not potentiated by KU55933. Our study reveals a role for ATM kinase activity in the dynamic exchange of proteins in DDR complexes and identifies a role for ANXA1 in cellular radioprotection