Bridging the gap between protein-tyrosine phosphorylation networks, metabolism and physiology in liver-specific PTP1b deletion mice

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012.Cataloged from PDF version of thesis.Includes bibliographical references.Metabolic syndrome describes a complex set of obesity-related disorders that enhance diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase lb (PTPlb) deletion mice (L-PTPlb-/-) suggests that hepatic PTPlb inhibition would mitigate metabolic syndrome progression through amelioration of hepatic insulin resistance, endoplasmic reticulum stress, and whole-body lipid metabolism. However, the network alterations underlying these phenotypes are poorly understood. Mass spectrometry was used to quantitatively discover protein phosphotyrosine network changes in L-PTP lb-/- mice relative to control mice under both normal and high-fat diet conditions. A phosphosite set enrichment analysis was developed to identify numerous pathways exhibiting PTPlb- and diet-dependent phosphotyrosine regulation. Detection of PTP lb-dependent phosphotyrosine sites on lipid metabolic proteins initiated global lipidomics characterization of corresponding liver samples and revealed altered fatty acid and triglyceride metabolism in L-PTPlb-/- mice. Multivariate modeling techniques were developed to infer molecular dependencies between phosphosites and lipid metabolic changes, resulting in quantitatively predictive phenotypic models.by Emily R. Miraldi.Ph.D

Molecular network analysis of phosphotyrosine and lipid metabolism in hepatic PTP1b deletion mice

Metabolic syndrome describes a set of obesity-related disorders that increase diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase 1b (PTP1b) deletion mice (L-PTP1b[superscript −/−]) suggest that hepatic PTP1b inhibition would mitigate metabolic-syndrome through amelioration of hepatic insulin resistance, endoplasmic-reticulum stress, and whole-body lipid metabolism. However, the altered molecular-network states underlying these phenotypes are poorly understood. We used mass spectrometry to quantify protein-phosphotyrosine network changes in L-PTP1b[superscript −/−] mouse livers relative to control mice on normal and high-fat diets. We applied a phosphosite-set-enrichment analysis to identify known and novel pathways exhibiting PTP1b- and diet-dependent phosphotyrosine regulation. Detection of a PTP1b-dependent, but functionally uncharacterized, set of phosphosites on lipid-metabolic proteins motivated global lipidomic analyses that revealed altered polyunsaturated-fatty-acid (PUFA) and triglyceride metabolism in L-PTP1b[superscript −/−] mice. To connect phosphosites and lipid measurements in a unified model, we developed a multivariate-regression framework, which accounts for measurement noise and systematically missing proteomics data. This analysis resulted in quantitative models that predict roles for phosphoproteins involved in oxidation–reduction in altered PUFA and triglyceride metabolism.Pfizer Inc. (grant)National Institutes of Health (U.S.) (grant 5R24DK090963)National Institutes of Health (U.S.) (grant U54-CA112967)National Institutes of Health (U.S.) (grant CA49152 R37)National Institutes of Health (U.S.) (grant R01-DK080756)National Mouse Metabolic Phenotyping Center at UMASS (Grant (U24-DK093000))National Science Foundation (U.S.) (Graduate Research Fellowship

Phosphotyrosine signaling analysis of site-specific mutations on EGFRvIII identifies determinants governing glioblastoma cell growth

available in PMC 2012 March 1.To evaluate the role of individual EGFR phosphorylation sites in activating components of the cellular signaling network we have performed a mass spectrometry-based analysis of the phosphotyrosine network downstream of site-specific EGFRvIII mutants, enabling quantification of network-level effects of site-specific point mutations. Mutation at Y845, Y1068 or Y1148 resulted in diminished receptor phosphorylation, while mutation at Y1173 led to increased phosphorylation on multiple EGFRvIII residues. Altered phosphorylation at the receptor was recapitulated in downstream signaling network activation levels, with Y1173F mutation leading to increased phosphorylation throughout the network. Computational modeling of GBM cell growth as a function of network phosphorylation levels highlights the Erk pathway as crucial for regulating EGFRvIII-driven U87MG GBM cell behavior, with the unexpected finding that Erk1/2 is negatively correlated to GBM cell growth. Genetic manipulation of this pathway supports the model, demonstrating that EGFRvIII-expressing U87MG GBM cells are sensitive to Erk activation levels. Additionally, we developed a model describing glioblastoma cell growth based on a reduced set of phosphoproteins, which represent potential candidates for future development as therapeutic targets for EGFRvIII-positive glioblastoma patients.National Institutes of Health (U.S.) (Grant P01-CA95616)National Cancer Institute (U.S.) (Grant U54-CA112967)National Cancer Institute (U.S.) (grant R01-CA118705)National Cancer Institute (U.S.) (Grant R01-CA096504)National Foundation for Cancer Research (Fellowship)National Science Foundation (U.S.) (Graduate Research Fellowship)Goldhirsh Foundation (Award)National Cancer Institute (U.S.) (NCI Integrative Cancer Biology Program Graduate Fellowship