Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 112-119). / Malaria accounts for over 500,000 deaths each year. While malaria is caused by multiple distinct parasites of the genus Plasmodium, P. falciparum is responsible for the majority of morbidity and mortality due to the disease. Despite this fact, molecular tools for genetic experimentation in the parasite remain underdeveloped. In particular, the ability to inducibly control gene expression and edit the genome in a site-specific manner present significant challenges. In addition, the building of genetic constructs poses challenges due to the required vector size and the high A+T richness of the P. falciparum genetic regulatory elements. This work begins by presenting the first vector family for use in the parasite made up of modular parts and encompassing all selectable markers and replication technologies in current use. It also discusses the development of a 2A like viral peptide tag for use in expression of multiple differentially localizing proteins from a single expression cassette. Based on this work, we were then able to construct vectors to reconstitute the T7 RNA polymerase expression system in P. falciparum, functionally creating the first system for directed expression of non-coding RNA in the parasite. We were then able to use this expression system to adapt a clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system in the parasite and use it to achieve genome editing at high efficiency at multiple loci. The data imply an adaptable system to readily edit the genome of the parasite and holds promise for the ability to create gene knockouts, perform allelic replacements, and add regulatory elements into the parasite significantly faster than has been previously demonstrated. This also represents the first illustration of the functionality of a CRISPR/Cas9 system in any non-bacterial pathogenic organism. In addition, we were able to introduce the lac repression system in order to regulate the T7 RNA polymerase dependent production of RNA and have created the first inducible expression system for RNA in any apicomplexan parasite. This work provides several new molecular tools and frameworks to aid in the study of, and fight against, malaria. / by Jeffrey C. Wagner. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 192-205). / Human obesity is a world-wide health crisis that promotes insulin resistance and type 2 diabetes. Obesity increases intracellular free fatty acid concentrations in peripheral tissues, particularly the liver, which disrupts molecular mechanisms that maintain normal glycemia in response to fasting and feeding. The progression towards outright pathology in response to obesity is a highly complex process that involves coordinated dysregulation of a variety of molecular processes across multiple regulatory levels. The goal of this thesis was to apply a quantitative, multi-omic systems biology approach to the study of obesity-induce hepatic insulin resistance. We fed male C57BL/6J mice high-fat diets (HFD) to induce obesity and insulin resistance. In the first presented study, our group collected datasets to profile the hepatic epigenomes, transcriptomes, proteomes, and metabolomes of chow diet (CD) control and HFD-fed mice. I extended and applied an established computational modeling algorithm, namely the prize-collecting Steiner forest (PCSF), to simultaneously integrate these molecular data with protein-protein and protein-metabolite interactions into a tractable network model of hepatic dysregulation. This model uncovered a variety of dysregulated pathways and processes, some of which are not well-established aspects of insulin resistance. We further tested and validated some of these model predictions, finding that HFD induces serious architectural defects in the liver and enhances hepatocyte apoptosis. In the next study, we focused more specifically on hepatic transcription. We fed mice short and long-term HFDs and treated them with the type 2 diabetes drug metformin. Compared to non-treated CD controls, diet exerted the strongest effect on transcription, progressively inducing changes as HFD duration increased. We additionally stimulated mice with insulin and collected temporal transcriptomic profiles. We found that long-term HFD almost completely blunted normal insulin-induced transcriptional changes, but also found a small set of genes that are specifically insulin-responsive in HFD livers. We further characterized one of these genes and provided evidence supporting the notion that aspects of hepatic insulin signaling are intact during insulin resistance. In another study, we collected transcriptomic and epigenomic data from mice fed a calorie-restricted (CR) diet. Interestingly, we found a small set of genes altered in the same direction by both CR and HFD. We then used chromatin accessibility experiments to infer regulators associated with these gene expression changes and found roles for PPAR[alpha] and RXR[alpha]. We performed ChIP-Seq experiments for these factors and treated mice and primary hepatocytes with a PPAR[alpha] activator, uncovering a role for PPARα in the regulation of anaerobic glycolysis. We also validated novel predicted target genes of PPAR[alpha] involved in glucose metabolism. Finally, we profiled hepatic miRNAs in CD and HFD livers, finding that HFD progressively alters their expression levels. We implemented an enrichment procedure and a network modeling approach to analyze these data. We integrated additional mRNA and epigenetic data to infer miRNAs that may play regulatory roles during insulin resistance. In total, this thesis presents a unique comprehensive approach to the study of diet-induced hepatic insulin resistance that revealed new insights into pathology. / by Anthony Robert Soltis. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / Page 193 blank. Cataloged from PDF version of thesis. / Includes bibliographical references (pages 185-192). / Rational drug design of small molecules has led to the development of robust therapeutics that are currently used in the clinic. However, key challenges remain in designing drugs against infectious disease targets that are susceptible to mutation. To achieve full clinical efficacy against rapidly-mutating targets, new methods must be developed for designing drugs. In this thesis, we utilize a three pronged approach for rational ligand design by developing methods, analyzing existing experimental data, and designing novel therapeutics. On-target mutations in infectious diseases often render inhibitors ineffective and are one of the key clinical failures of current therapies. We use HIV protease as a model system to understand mutation resistance. HIV protease substrates are unaffected or only moderately affected by resistance mutations that greatly decrease inhibitor binding. This idea has led to the design of broadly binding inhibitors using substrate mimicry. This is achieved by constraining inhibitors to bind within the consensus substrate volume, which we term the "substrate envelope". However, while the substrate envelope has been relatively successful, some inhibitors that are designed based on this model are sensitive to mutants. We performed a detailed biophysical binding energy decomposition of a flat and susceptible binder pair and found that the susceptible inhibitor forms stronger interactions with key residues. These residues are entirely characterized by examining known resistant mutants to approved HIV protease inhibitors. To generalize our findings, we cross-validate on a set of ten HIV protease inhibitors with previously measured sensitivity. We find that interaction energy successfully classifies susceptible and flat inhibitors. Based on these results, we extend the current design paradigm. We develop a methodology to minimize extraneous contacts with the active site and express it as an appropriate cost function, which is then minimized. We then implement this design scheme for HIV protease, yielding both flat and susceptible binders. Next, we apply rational drug design principles to other infectious disease targets. We first focus on the tuberculosis specific CIpP1P2 peptidase to optimize the antibiotic, acyl depsipeptides (ADEPs). We use component analysis to understand the biophysics of ADEP binding to the active site. We then design a series of analogs resulting in a two-fold affinity improvement along with enhanced peptidase activity. We also develop new methods to improve an anti-fungal for the treatment of Candida albicans. We use molecular docking to predict a binding mode for the lead compound and then account for receptor plasticity by performing molecular dynamics simulations. We use this improved receptor model to design novel analogs that are predicted to bind better than the parent compound. Lastly, we focus on disease diagnosis by developing a novel paradigm for MRI contrast agent design. We first integrate the governing thermodynamics and relevant parameters that influence imaging efficacy to develop an integrated workflow for contrast agent design. We then apply our methodology to the DOTA system and successfully explain differential activity of designed analogs. Put together, we demonstrate the power of rational design in various relevant biological contexts. Overall, this thesis presents new techniques, analysis, and applications of rational design to address unmet clinical problems. Work from this thesis accelerates the field of computational drug design, which has implications in many uncured diseases and diagnostics. / by Raja R. Srinivas. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Biotherapeutics have revolutionized medicine with their ability to achieve unprecedented molecular recognition and mediate complex biological responses. The intracellular delivery of biotherapeutics is an unmet scientific challenge and medical need. A wide variety of different treatment modalities depend on not only on the ability to achieve intracellular delivery, but to do so in a targeted manner. An independently-targeted, two-molecule system was developed to accomplish intracellular delivery in a uniquely specific manner. Immunotoxins were designed based on the plant toxin gelonin and targeted towards the canonical cancer-specific antigens: epidermal growth factor receptor and carcinoembryonic antigen. Using quantitative internalization flow cytometry matched with controlled exposure cytotoxicity, the number of internalized gelonin immunotoxins required to induce apoptosis in a single cell was found to be ~5x10⁶ molecules. This threshold to cytotoxicity was conserved across all gelonin constructs regardless of antigen target, binding scaffold, affinity, or cell line. Next, cholesterol-dependent cytolysins were targeted to the same antigens by genetic fusion to engineered fibronectin domains. When combined in vitro, targeted gelonin and cytolysin had synergistic cytotoxic effects and the presence of cytolysin reduced the intracellular barrier to cytotoxicity to < 10⁴ immunotoxin molecules. In vivo, these molecules induced nonspecific, dose-limiting toxicities at varying levels and were cleared from the plasma at rates consistent with their molecular weight. Dosed individually, neither compound was capable of controlling tumor xenografts, but when combined in a delayed dosing scheme they inhibited tumor growth and induced apoptosis throughout xenografts as confirmed by histology. Mathematical modeling was informed by in vivo experiments and provided insight in dosing and tumor exposure overlap. These results emphasize the necessity of a targeted intracellular delivery system and support the merit of the described approach. Additional research into the safety and efficacy of these molecules as well as the design of new constructs will certainly improve the clinical relevance of this technique. / by Christopher M. Pirie. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 99-107). / Microscopy has facilitated the discovery of many biological insights by optically magnifying small structures in cells and tissues. However, the resolution of optical microscopy is limited by the diffraction of light to ~200-300 nm, comparable or larger to the size of many subcellular structures. In this thesis, we describe a suite of tools based on a novel super-resolution microscopy approach called Expansion microscopy. Expansion microscopy (ExM) physically expands tissues so that the resolution of ordinary microscopes is increased -5 times by leveraging the swelling properties of polyelectrolyte hydrogels. Ordinary microscopes used with ExM are more accessible and faster than the specialized optical systems designed to image beyond the diffraction limit (e.g., STORM/PALM, STED, SIM), while yielding similar performance. Expanded tissues are also optically clear, allowing for unprecedented super-resolution imaging in thick tissues and facile reagent diffusion into the sample. We have since developed a variant of ExM, called protein retention ExM, in which proteins are directly anchored to the swellable gel using a commercially available cross-linking molecule. This strategy enables ExM of genetically encoded fluorescent proteins and commercial fluorescently labeled secondary antibodies. With these advancements, ExM can be carried out with purely commercial reagents and represents a simple extension of standard histological methods used to prepare samples for imaging. Furthermore, we have developed a variant of the ExM technology that enables RNA molecules to be directly linked to the ExM gel network via a small molecule linker and isotropic expansion. This technology, termed ExFISH, enables visualization of RNAs with nanoscale precision and single molecule resolution. We have demonstrated that the covalent anchoring of RNA also enables robust repeated washing and probe hybridization steps, opening the door to combinatorial multiplexing strategies. By leveraging these benefits, we have further developed in situ analysis tools which allow for highly multiplexed imaging of RNA identity and location with nanoscale precision in intact tissues. Taken together, these tools allow for spatially mapping molecular information onto cell types and tissue structures which could be invaluable for spatially complex biological processes such as brain function, cancer heterogeneity and organismal development. / by Fei Chen. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student submitted PDF version of thesis. / Includes bibliographical references (p. 119-124). / Cell size is often overlooked in the drive to define molecular mechanisms, but as a basic physical property it is an integrator of the cell's metabolic rate and indicator of cell fate. Development of the Suspended Microchannel Resonator (SMR), a microfluidic mass measurement system, enables femtogram cell mass resolution, and the resistive pulse (Coulter) technique provides high-speed electronic readout of cell volume. With these tools, we developed four methods to measure cell density, the ratio of mass to volume. We first measure the average density of cell populations using the SMR and a Coulter counter. We observe that cell density increases prior to bud formation at the G1/S transition of budding yeast, which is consistent with previous measurements using density gradient centrifugation. To investigate the origin of this density increase, we use the SMR to measure buoyant mass in high density media and monitor relative density changes of growing yeast cells. We find that the density increase requires energy, function of the protein synthesis regulator TOR, passage through START, and an intact actin cytoskeleton. These techniques are suitable for most non-adherent cells and subcellular particles to characterize cell growth in a variety of applications. We next develop two platforms to measure single-cell mass, volume, and density. These properties are calculated from two SMR buoyant mass measurements, each in different density fluids. These measurements are achieved by serially connecting two SMR structures through a microchannel with an intermediate T-junction, such that a cell is measured by each SMR in different density fluids. Similar measurements can also be made with one SMR by reversing the SMR fluid flow after a cell is measured-each cell re-enters the SMR in a higher density fluid for a second measurement. We find that the intrinsic cell-to-cell density variation is nearly 100-fold smaller than the mass or volume variation, and by simultaneously measuring density and mass, we identify distinct subpopulations of diseased and healthy cells that are indistinguishable by mass or volume alone. / by Andrea K. Bryan. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / In recent years, the field of systems biology rapidly expanded in both basic and translational science. This method of investigation revolves around an iterative cycle of observing a system, making predictions about its behavior using a model, and testing these hypotheses with further experiments. Though computational approaches have achieved astonishing sophistication, these models are fundamentally limited in their predictive power by the quality of data they are given. Thus, the lack of tools to capture information-rich data has become a bottleneck for our ability to predict and perturb biological systems. This thesis focuses on developing tools to collect data that captures the complexity of signaling networks to deepen our understanding of the mechanistic processes occurring inside the cell. In particular, we present a method capable of measuring phosphorylation changes in the cell with 10-second resolution. One of the best-characterized proteins in biology is the Epidermal Growth Factor Receptor (EGFR), which has long been associated with diseases including cancer. Despite development of several EGFR inhibitors, the clinical efficacy of targeting this receptor has been minimal. This shortcoming is attributable primarily to the incredible complexity of the EGFR signaling network, which includes hundreds of proteins throughout the cell. In this thesis, we use EGFR as a model to demonstrate the utility of measuring phosphorylation dynamics with high temporal resolution. We present an extensive characterization of EGFR signaling behavior across a range of growth factor concentrations, exposing distinct regimes of network activation. Bioinformatic analysis uncovers unexpected relationships within the data that uncover previously obscured biological distinctions within the system. This information is used to generate and test specific mechanistic hypotheses using broad and targeted perturbations. We explore the relationship between phosphorylation and complex formation of receptors and adaptors, finding evidence for distinct recruitment mechanisms for Shc and Gab1. Inhibition of phosphatase activity in the system shows unexpected behaviors in the form of specific phosphatase activity against sites on EGFR and Gab1 and ligand-independent activation of ERK. Examination of the data suggests a connection with Src family kinases as contributors to EGFR signaling. Further exploration with targeted inhibition of Src and P13K create a quantitative mechanistic explanation for EGFR signaling. Lastly, inhibition of the network with clinically relevant tyrosines kinase inhibitors reveals temporally distinct effects of inhibitors in early signaling. Combination of broad kinase and phosphatase inhibition produces unusual results that raise further questions of EGFR signaling. Together, the tools presented here for studying early signaling events at the systems level will contribute to our understanding of complex biological systems. / by Raven Jon Reddy. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Glioblastoma (GBM) is the most common malignant form of brain cancer. Even with treatment including surgery, radiation, and temozolomide chemotherapy, the 1 year survival rate is only 35%. To identify specific mediators of GBM progression in a genetically engineered murine model of proneural GBM, we quantified signaling networks using mass spectrometry. We identified oncogenic signaling associated with the GBM model, such as increased phosphorylation of ERK1/2, P13K, and PDGFRA, relative to murine brain. Phosphorylation of CDK₁ Y₁₅, which causes G₂ /M cell cycle arrest, was measured to be the most differentially phosphorylated site, with a 14-fold increase in the tumors. We used syngeneic cell lines to investigate this checkpoint further and treated these cells with MK-₁₇₇₅, an inhibitor of Wee₁, the kinase responsible for phosphorylation of CDK₁ Y₁₅. MK-₁₇₇₅ treatment resulted in mitotic catastrophe of these cells, as measured by increased DNA damage, abnormal percentages of cells in cell cycle phases, and death by apoptosis. This response was abrogated by inhibiting CDK₁ with roscovitine, a CDK inhibitor, demonstrating the necessity of active CDK₁ for MK-₁₇₇₅ induced mitotic catastrophe. To assess the extensibility of targeting Wee₁ and the G₂/M checkpoint in GBM, we treated patientderived xenograft (PDX) cell lines with MK-₁₇₇₅. The response was more heterogeneous, but we measured decreased CDK₁ phosphorylation, increased DNA damage, and death by apoptosis. These results were validated in a flank GBM PDX model where treatment with MK-₁₇₇₅ increased mouse survival by 1.74-fold. We also quantified the signaling differences in our murine GBM model after treatment with sunitinib, an inhibitor of its driver receptor tyrosine kinase, PDGFRA. Treatment increased survival but lead to a morphological change causing a more invasive phenotype. Pro-migratory signaling was characterized by mass spectrometry, such as increased phosphorylation of Eno₁, ELMO₂, and tubulins. Invasion was further characterized in a lung cancer model where we identified signaling specific to different ligands that result in similar levels of invasion. We have demonstrated that unbiased, quantitative phosphotyrosine proteomics has the ability to reveal therapeutic targets in tumor models and signaling differences between treatments. / by Rebecca S. Lescarbeau. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, February 2016. / Cataloged from PDF version of thesis. "September 2015." / Includes bibliographical references (pages 60-66). / The genome holds the blueprint of life and heredity. In the case of the mammalian genome it is comprised of billions of DNA bases grouped into elements that we are beginning to understand (ie genes) and others we know little about (ie noncoding DNA). Forward and reverse genetics in cells and animal models is key to discovering causal mechanisms relating molecular and genetic events to phenotypes. Therefore, the ability to sequence and edit DNA is fundamental to understanding of the role of genetic elements in normal biology and disease. Recently developed genome editing technologies are now making it possible to modify the genome in its endogenous context, opening up exciting possibilities for understanding its function. The RNA-guided endonuclease Cas9 from microbial type II CRISPR (clustered regularly interspaced short palindromic repeat) systems has been harnessed to facilitate facile genetic manipulations in a variety of cell types and organisms. Cas9 can be easily reprogrammed using RNA guides to generate targeted DNA double strand breaks, which can stimulate genome editing. A unique advantage of the Cas9 system is that Cas9 can be combined with multiple guide RNAs to achieve efficient multiplexed genome editing in mammalian cells, which opens up the possibility of interrogating multigenic biological processes. In this thesis, we utilize the Cas9 technology to facilitate genome editing experiments in vivo in mice. First, we create a Cas9 knockin mouse and demonstrate its utility for in vivo and ex vivo genome editing experiments. Then, we leverage the Cas9 knockin mouse and viral-mediated delivery of guide RNA to model lung adenocarcinoma to obtain pathology consistent with traditional transgenic mouse models and human patients. Finally, we utilize pronuclear injection of Cas9 mRNA and guide RNA to generate mice harboring a mutation in the autism-associated gene CHD8 and investigate the underlying behavioral and molecular phenotype. These applications broadly demonstrate the potential of Cas9 for interrogating genetic elements in vivo towards understand their role in normal biological processes and disease. / by Randall Jeffrey Platt. / Ph. D.

Thesis: M. Eng, Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 61-65). / Amitotic cells with large, hollow bell-shaped nuclei, or metakaryotic stem cells, are the post-embryonic stem cells of the fetal organs from about the fourth week post conception through physical maturity. These metakaryotic stem cells, after acquiring necessary genetic, and possibly other events, are also the stem cells of precancerous, cancerous and metastatic lesions of carcinogenesis. Furthermore, our lab has discovered that metakaryotic stem cells, both in fetal development and tumor growth, use a peculiar mode of DNA synthesis and segregation that involves inter alia expression of large amounts of RNA polymerase beta during DNA synthesis. It was hypothesized that an inhibitor of DNA polymerase beta would be toxic to metakaryotic stem cells at concentrations lower than necessary to kill eukaryotic non stem cells. The polymerase beta small-molecule inhibitor chosen for this study was pamoic acid, a napthoic acid derivative. With it we determined the relative sensitivity of metakaryotes and eukaryotic cells in the human colorectal cancer cell culture, HT- 29mes, that expresses characteristics expected of colorectal cancer metastases. We conclude that, at 300 [mu]M and above pamoic acid does not selectively kill metakaryotes in cell culture below that concentration which kills eukaryotes. Rather, pamoic acid acts in a similar fashion as X-rays: eukaryotic non-stem cells are killed at lower doses than those that kill metakaryotic stem cells. Treatment of pamoic acid with these concentrations causes concomitant declines in colony-formation potential for both metakaryotes and eukaryotes alike. At lower overall survival levels, surviving colonies appear to have arisen from metakaryotic cells, not eukaryotic cells as evidenced by the presence of visible metakaryotic cells in most colonies and the ability of such colonies to support continuous growth upon passaging. We conclude with the possibility that this specific polymerase beta inhibitor is not an effective metakaryocide in culture, insofar as they are not selectively toxic for these stem cells in the HT-29mes colorectal cancer cell line. / by Tushar Vinod Kamath. / M. Eng