Characterization of a more clinically relevant human leukemia xenograft model to examine perturbation of MET/SAM metabolism as a novel therapeutic paradigm for MLL-R leukemia in vivo.

Acute myeloid leukemia (AML), is a heterogeneous clonal disorder characterized by an accumulation of malignant myeloid progenitors in the bone marrow (BM), hindering normal hematopoiesis. AML exhibits dramatic heterogeneity in terms of cytogenetics, morphology, and chemotherapeutic sensitivity. Therefore, the investigation of novel, efficacious AML therapeutics will require advanced preclinical in vivo model systems, capable of recapitulating patient specific disease heterogeneity, and induction chemotherapy outcomes. A major focus and eventual outcome of this work was the establishment and development of a more clinically relevant mouse xenograft model of patient AML, that efficiently harbors patient derived xenografts (PDXs), and unlike more prevalent SCID models can tolerate more clinically relevant doses of DNA damaging induction chemotherapy. We examined the functional utility of our newly established, advanced AML PDX model to confirm our in vitro findings that perturbation of methionine (Met) / S-adenosylmethionine (SAM) metabolism is uniquely cytotoxic to MLL-rearranged (MLL-R) leukemic cells, in vivo. We demonstrate here that perturbation of Met/SAM metabolism decreases intracellular methylation potential, alters global histone methylation dynamics, impairs the expression and function of the H3K79 methyltransferase DOT1L, and induces apoptosis in MLL-R leukemic cells. We show a significant extension in the survival of mice harboring aggressive patient MLL-R leukemias, when treated with a pharmacologic inhibitor of Met/SAM metabolism and induction therapy, as compared to induction alone. The work featured in this dissertation establishes a novel chemotherapy tolerant AML xenograft model, demonstrates its translational utility, and supports the continued investigation of targeted inhibition of Met/SAM metabolism against MLL-R leukemia

Establishing a clinically relevant mouse model of human AML to test novel transmethylation inhibitors.

Acute myeloid leukemia (AML) is a highly heterogeneous clonal disorder characterized by an accumulation of malignant immature myeloid progenitors in the bone marrow (BM) that hinder normal hematopoiesis. Patient AML exhibits a dramatic heterogeneity in terms of cytogenetics, disease morphology, and associated prognoses and/or chemotherapeutic sensitivity. Thus it becomes clearly evident that the investigation of novel therapeutics for AML will require model systems that are capable of recapitulating this stark heterogeneity in a patient specific manner. Furthermore, it is now understood that the surrounding bone marrow (BM) microenvironment and supporting cells play a critical role in leukemic progression as well as providing a chemotherapy protected sanctuary for residual disease. Therefore, the focus of this study was the establishment and development of a more clinically relevant mouse xenograft model of patient derived AML that not only recapitulates patient disease but also simulates the clinical standard of care induction therapy. The crux of our model system was the NRGS mouse, which were not only capable of reliable high rates of engraftment of established cell lines and patient derived AML cells, but also expresses three human myeloid cytokines (IL-3, GM-CSF, SF). Additionally these mice were able to tolerate aggressive induction therapy at doses similar to those administered to patients, and therapy was efficacious in prolonging the survival of mice engrafted with patient AML. Such model systems that can simulate patient specific AML along with the standard of care therapy, will be essential for the successful investigation of novel, translational therapeutics

The organization of metabolic genotype space facilitates adaptive evolution in nitrogen metabolism

A metabolism is a complex chemical reaction system, whose metabolic genotype – the DNA encoding the enzymes catalyzing these reactions – can be compactly represented by its complement of metabolic reactions. Here, we analyze a space of such metabolic genotypes. Specifically, we study nitrogen metabolism and focus on nitrogen utilization phenotypes that are defined through the viability of a metabolism – its ability to synthesize all essential small biomass precursors – on a given combination of sole nitrogen sources. We randomly sample metabolisms with known phenotypes from metabolic genotype space with the aid of a method based on Markov Chain Monte Carlo sampling. We find that metabolisms viable on a given nitrogen source or a combination of nitrogen sources can differ in as much as 80 percent of their reactions, but can form networks of genotypes that are connected to one another through sequences of single reaction changes. The reactions that cannot vary in any one metabolism differ among metabolisms, and include a small core of “absolutely superessential” reactions that are required in all metabolisms we study. Only a small number of reaction changes are needed to reach the genotype network of one metabolic phenotype from the genotype network of another metabolic phenotype. Our observations indicate deep similarities between the genotype spaces of macromolecules, regulatory circuits, and metabolism that can facilitate the origin of novel phenotypes in evolution.  

Strategies for Alang's shipbreaking industry

Thesis (S.M. in Architecture Studies)--Massachusetts Institute of Technology, Dept. of Architecture, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 137-143).Waste is an integral part of our contemporary civilization based on consumption and material culture. From an empty soda can to the spent nuclear fuel rod, we define waste as the matter without immediate use: rotten, broken, unwanted. The notion of waste is also spatial-waste is simply matter in the wrong place and consequently of no value. One defining feature of globalization is the flow of waste to the places that extract value out of this otherwise worthless matter. Situated on the western shore of the Gulf of Cambay in India, Alang is one such place. Alang owes its existence to the rise of modern maritime industry. Here obsolete end of life ships are broken, by manual labor, to transform them into a reusable commodity- steel. With an average lifespan of 25 to 30 years, most of these ships, often full of hazardous waste at the end of their working life, end up on the beach of Alang to be dismantled for their steel. Taking advantage of its unique geographical conditions, cheap migrant labor, and lax environmental regulations, Alang recycles half of the world's scrapped ships. It is the epicenter of a scavenger economy that turns obsolete vessels into reusable commodities for a rapidly developing economy. With the example of Alang, this thesis asserts that, due to their intricate connectivity to the global networks, places of resource extraction acquire an extra-territorial urban character. Only by acknowledging the urban nature of such places, can we start to design for these flows of waste, migration and resources. This thesis aims to explore the potential for urbanism to intervene into an industry like Alang to develop a regional strategy of urban metamorphosis.by Aditya S. Barve.S.M.in Architecture Studie

Historical contingency and the gradual evolution of metabolic properties in central carbon and genome-scale metabolisms

BACKGROUND A metabolism can evolve through changes in its biochemical reactions that are caused by processes such as horizontal gene transfer and gene deletion. While such changes need to preserve an organism's viability in its environment, they can modify other important properties, such as a metabolism's maximal biomass synthesis rate and its robustness to genetic and environmental change. Whether such properties can be modulated in evolution depends on whether all or most viable metabolisms - those that can synthesize all essential biomass precursors - are connected in a space of all possible metabolisms. Connectedness means that any two viable metabolisms can be converted into one another through a sequence of single reaction changes that leave viability intact. If the set of viable metabolisms is disconnected and highly fragmented, then historical contingency becomes important and restricts the alteration of metabolic properties, as well as the number of novel metabolic phenotypes accessible in evolution. RESULTS We here computationally explore two vast spaces of possible metabolisms to ask whether viable metabolisms are connected. We find that for all but the simplest metabolisms, most viable metabolisms can be transformed into one another by single viability-preserving reaction changes. Where this is not the case, alternative essential metabolic pathways consisting of multiple reactions are responsible, but such pathways are not common. CONCLUSIONS Metabolism is thus highly evolvable, in the sense that its properties could be fine-tuned by successively altering individual reactions. Historical contingency does not strongly restrict the origin of novel metabolic phenotypes

The organization of metabolic genotype space facilitates adaptive evolution in nitrogen metabolism

A metabolism is a complex chemical reaction system, whose metabolic genotype – the DNA encoding the enzymes catalyzing these reactions – can be compactly represented by its complement of metabolic reactions. Here, we analyze a space of such metabolic genotypes. Specifically, we study nitrogen metabolism and focus on nitrogen utilization phenotypes that are defined through the viability of a metabolism – its ability to synthesize all essential small biomass precursors – on a given combination of sole nitrogen sources. We randomly sample metabolisms with known phenotypes from metabolic genotype space with the aid of a method based on Markov Chain Monte Carlo sampling. We find that metabolisms viable on a given nitrogen source or a combination of nitrogen sources can differ in as much as 80 percent of their reactions, but can form networks of genotypes that are connected to one another through sequences of single reaction changes. The reactions that cannot vary in any one metabolism differ among metabolisms, and include a small core of “absolutely superessential” reactions that are required in all metabolisms we study. Only a small number of reaction changes are needed to reach the genotype network of one metabolic phenotype from the genotype network of another metabolic phenotype. Our observations indicate deep similarities between the genotype spaces of macromolecules, regulatory circuits, and metabolism that can facilitate the origin of novel phenotypes in evolution

Exhaustive analysis of a genotype space comprising 1015 central carbon metabolisms reveals an organization conducive to metabolic innovation

All biological evolution takes place in a space of possible genotypes and their phenotypes. The structure of this space defines the evolutionary potential and limitations of an evolving system. Metabolism is one of the most ancient and fundamental evolving systems, sustaining life by extracting energy from extracellular nutrients. Here we study metabolism's potential for innovation by analyzing an exhaustive genotype-phenotype map for a space of 10(15) metabolisms that encodes all possible subsets of 51 reactions in central carbon metabolism. Using flux balance analysis, we predict the viability of these metabolisms on 10 different carbon sources which give rise to 1024 potential metabolic phenotypes. Although viable metabolisms with any one phenotype comprise a tiny fraction of genotype space, their absolute numbers exceed 10(9) for some phenotypes. Metabolisms with any one phenotype typically form a single network of genotypes that extends far or all the way through metabolic genotype space, where any two genotypes can be reached from each other through a series of single reaction changes. The minimal distance of genotype networks associated with different phenotypes is small, such that one can reach metabolisms with novel phenotypes--viable on new carbon sources--through one or few genotypic changes. Exceptions to these principles exist for those metabolisms whose complexity (number of reactions) is close to the minimum needed for viability. Increasing metabolic complexity enhances the potential for both evolutionary conservation and evolutionary innovation