Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, February 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Monoclonal antibodies have emerged as an important class of cancer therapeutics due to their ability to specifically bind tumor-expressed antigens. Unfortunately, attempts to treat solid tumors with these drugs are often limited by an inability of the antibodies to fully penetrate the tumor tissue, leaving large regions of untargeted and viable cells. The goal of this thesis is to understand the transport phenomena that contribute to poor antibody distribution in tumors, and engineer novel antibody variants with improved targeting properties. Previous studies identified a core set of parameters that impact tumor uptake including antibody size, binding affinity, plasma clearance rate, and cellular catabolism. Here we probe each of these parameters and its effect on tumor penetration using a combination of computational modeling and protein engineering. In the first part of this thesis, we characterize the cellular internalization kinetics of a series of anti-carcinoembryonic antigen (CEA) antibodies and antibody fragments. We demonstrate that internalization is independent of antibody affinity, stability, and valency, and that the measured rates can be used to mathematically predict antibody penetration distance in tumor spheroids. Next, we examine the effect of antibody size and affinity by developing a computational model of in vivo tumor targeting that incorporates size-dependent trends for capillary permeability, interstitial diffusion, available volume fraction, and plasma clearance. The model predicts that intermediate size antibody fragments (MW ~30 kDa) have the lowest tumor uptake with greater accumulation of small and large proteins. To probe size effects experimentally, we engineered a novel 79 kDa ds(Fv)-Fc antibody fragment that is approximately half the size of an IgG but retains its binding and Fc salvage activity. In mice, the ds(Fv)-Fc fragments are cleared from the plasma more rapidly than IgGs but have similar tumor uptake levels at 24 hours, likely due to higher capillary permeability. In the last section, we develop a series of matrix metalloproteinase (MMP) activatable antibody fragments that bind their target antigen up to 300 times faster following cleavage by the tumor expressed protease MMP-2. We believe that MMP dependent binding should prevent targeting of antigen depots in healthy tissues and further improve tumor specificity. / by Michael M. Schmidt. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 173-197). / Chemotherapy is widely used in the treatment of solid tumors, but its effects are often associated with cancer relapse, metastasis, and drug resistance. The biological mechanisms that drive the structural and functional changes in cancer cells associated with these features of disease progression remain poorly understood. Consequently, quantitative characterization of molecular signaling pathways and changes in cancer cell phenotypes induced by chemotherapy through the use of in vitro model systems would expand our understanding of drug mechanisms and provide for putative strategies to counteract drug-induced cancer progression. Toward this end, I develop bioimage informatics tools to characterize changes in signaling, structure, and function of cancer cells from fluorescence microscopy data. I first present a generally-applicable probabilistic time-series modeling framework to classify cell shape dynamics. Times-series models draw quantitative comparisons in cell shape dynamics that are used to distinguish and interpret cellular responses to diverse drug perturbations. Next, I investigate the effects of doxorubicin, a DNA-damaging chemotherapeutic drug, on breast cancer cell signaling and phenotype. Bioinformatics analyses of phosphoproteomics data are first used to infer biological processes downstream of DNA damage response signaling networks altered by doxorubicin treatment. These analyses reveal changes in phosphoproteins associated with the actomyosin cytoskeleton and focal adhesions. Live-cell imaging of cell morphology, motility, and apoptosis dynamics reveals a link between doxorubicin-induced cytoskeletal signaling and morphological elongation, directional migration, and enhanced chemo-tolerance. These findings imply that sub-maximal tumor killing can exacerbate disease progression through adaptive resistance to primary chemotherapy treatment through DNA damage response-regulated cytoskeletal signaling. Finally, I combine the results of the phosphoproteomic analysis with phenotypic profiling to characterize doxorubicin-induced changes in actomyosin signaling that affect cancer cell shape and survival. I additionally describe a generally-applicable multiplexed fluorescence imaging framework that uses diffusible nucleic acid probes to detect nearly a dozen subcellular protein targets within the same biological sample. Taken together, these methodologies reveal previously-unappreciated effects of chemotherapy on breast cancer signaling and phenotype, and demonstrate the value of combining bioinformatics analyses of -omics data with quantitative fluorescence microscopy as a general strategy in biological mechanism discovery. / by Simon Gordonov. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Fluorescence microscopy has proven to be immensely powerful for the study of biological systems at both the cellular and systems biological levels. The ability to specifically label a single molecular species fluorescently has enabled the study of complex cellular structures through the visualization of their constituent components both individually as well as in context of the overall structure. Since the advent of engineered fluorescent proteins (such as GFP) and other proteins capable of being genetically encoded as fusion constructs, the utility of fluorescence microscopy has increased exponentially in terms of the ability to efficiently, specifically label desired molecules while limiting perturbations to the biology under study. With this enhanced ability of visualization came a hand-in-hand evolution of computational techniques to extract quantitative information from microscopy images. In this thesis, I focus on the application of fluorescence imaging at the biophysical level in living cells: analyzing the motion/dynamics of single molecules and complexes, which are small relative to the structures of the cell, in order to elucidate their molecular function and mechanism. The motion of these "particles" within living cells is necessarily related to their functions as well as their interacting partners, which can vary dynamically during their lifetimes. Observation and analysis of this motion using a combination of fluorescence microscopy and robust quantitative analysis allows one to infer these characteristics. Here, I study three diverse biological systems in the context of live-cell fluorescence microscopy and biophysical analysis: 1) the transport of 0-actin mRNA particles in primary mouse neurons, 2) kinetochore motion during cell division, specifically focusing on anaphase dynamics, and 3) the motion of cell-growth-implicated membrane proteins in Bacillus subtilis. / Funded by the NSF Physics of Living Systems PHY 1305537. / by Zachary Thomas Barry. / Ph. D.

Thesis: S.M., Massachusetts Institute of Technology, Department of Biological Engineering, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 65-67). / Plasmodium falciparum is the deadliest malaria parasite. There is no approved vaccine to prevent this disease, and resistance to available antimalarial drugs is becoming widespread. Identification of parasite genes essential to survival and virulence could facilitate the development of novel therapeutics and vaccines. However, these efforts have been impeded by difficulties in manipulating the parasite's genome and functionally perturbing gene expression in a controlled way. Our lab has developed inducible systems to control P. falciparum gene expression, and has achieved successful editing of the P. falciparum genome using CRISPR/Cas9 technology. We have integrated these capabilities into a modular and scalable framework that can be used to efficiently edit, regulate and delete any target parasite gene after a single genome editing operation. This approach will accelerate studies of parasite gene function, and help prioritize potential drug and vaccine targets. A key requirement in this framework is the efficient assembly of donor vectors for modifying target loci and installing the necessary regulatory parts. This necessitates cloning several large, [A+T]-rich P.falciparum genomic regions that can be quite tedious and rate limiting. In this document, we show a new cloning strategy using linear vectors that facilitates rapid and accurate assembly of vectors capable of transforming P. falciparum. We present evidence of successful chromosomal modification of several genes via spontaneous single crossover, as well as zinc finger nuclease- and Cas9- mediated genome editing strategies using our assembled donor vectors. We also show that these modifications enable controllable expression of several previously uncharacterized genes to elicit phenotypes that we are investigating in further mechanistic detail. Importantly, these transgenic parasites can now be rapidly generated to allow identification of novel essential parasite genes in as little as a month. / by Armiyaw Sebastian Nasamu. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references. / There is an ever-growing demand for enantiopure chemical compounds, particularly new pharmaceuticals. Enzymes, as natural biocatalysts, possess many appealing properties as robust asymmetric catalysts for synthetic chemistry. However, their enantioselectivity toward most synthetically useful, non-natural substrates is typically low. Therefore, improving enzymatic enantioselectivity toward a given substrate is a practically important but arduous task. Here we report a highly efficient selection method for enhanced enzymatic enantioselectivity based on yeast surface display and fluorescenceactivated cell sorting (FACS). By exploiting the aforementioned method, in just three rounds of directed evolution we both greatly increased (up to 30-fold) and also reversed (up to 70-fold) the enantioselectivity of the commercially useful enzyme, horseradish peroxidase (HRP), toward a chiral phenol. In doing so, we discovered that mutations close to the active site not only preserve HRP catalytic activity but impact its enantioselectivity far greater than distal mutations. We thus examined how a single mutation near the active site (Argl78Glu) greatly enhances (by 25-fold) the enantioselectivity of yeast surface-bound HRP. Using kinetic analysis of enzymatic oxidation of various substrate analogs and molecular modeling of enzyme-substrate complexes, this enantioselectivity enhancement was attributed to changes in the transition state energy due to electrostatic repulsion between the carboxylates of the enzyme's Glu- 178 and the substrate's D enantiomer. In addition, the effect of yeast surface immobilization and influence of a fluorescent dye on controlling the enantioselectivity of the discovered HRP variants was investigated. Soluble variants were also shown to have marked improvements in enantioselectivity, which were rationalized by computational docking studies. / by Eugene Antipov. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011. / Each page number preceded by chapter or appendix number. Cataloged from PDF version of thesis. / Includes bibliographical references (p. F-150 - F-163). / The activation of inflammatory responses, while critical for host defense, contributes to hepatic injury in numerous acute and chronic liver disease states as well as drug-induced liver injury (DILI). The interactions that mediate susceptibility to liver injury and disease, however, are still poorly understood, underscored by the complexity of immune interactions and the diverse cellular composition and functions of the liver. Using Citrobacter rodentium, a well characterized rodent-specific enteric pathogen as a source of extrahepatic inflammatory stress; host liver responses, metabolic dysregulation, and susceptibility to injury in C57BL/6 mice were investigated. For the first time, we show altered liver pathology during the early course of C. rodentium infection, characterized by periportal necrosis indicative of thrombic ischemic injury, correlating with distinct circulating and tissue specific cytokine/chemokine profiles. Using Acetaminophen (APAP), a widely used analgesic and well-characterized hepatotoxin, we evaluated liver responses in isolation and in the context of host inflammation to gain insight into the role of live bacterial infection in altering liver metabolism and susceptibility to DILI. We combined systemic and tissue-specific cytokine/chemokine levels, clinical serum chemistries, and histopathological assessments of hepatic and enteric inflammation and necrosis to measure molecularlevel responses to treatment and their physiological effect. Using principal components analysis (PCA), clustering, partial least squares regression (PLSR), and a combination mutual-information-correlation network, enabled detection and visualization of both linear and nonlinear dependencies between molecules and physiological states across tissues and timepoints. C. rodentium-induced inflammatory stress was finally investigated for its potential in altering drug pharmacokinetics (PK) of substrates varying in their metabolic biotransformation and clearance mechanisms. Infection resulted in increased systemic oral exposure (AUC) of clinically relevant xenobiotics such as verapamil, propranolol, and digoxin. Functionally, these changes were not found dependent on CYP-mediated biotransformation of parent compounds; rather, they appear driven more by proposed gut barrier compromise. In conclusion, gastrointestinal infection with C. rodentium alters systemic and hepatocytes specific responses, not previously appreciated from this enteric pathogen, making it a useful model for studying host-pathogen interactions under acute hepatic inflammatory stress and injury. / by Arkadiusz R. Raczynski. / Ph.D.

Thesis: Sc. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 213-223). / Within synthetic biology, significant progress in creating networks using transcriptional and translational control has been made, but a network comprised solely of protein-protein interactions has not yet been built. To realize this goal, new design rules for assembling and connecting protein devices into circuits are required. In this thesis, a framework for rapid assembly and delivery of genetic networks in Saccharomyces cerevisiae is described. Utilizing this scheme, design principles of modular chimeric proteins, engineered pathway convergence, and phosphorylated activated localization are developed and subsequently applied to create phosphoin/phospho-out composable protein devices in yeast. The devices implement BUFFER, NOT and OR logical operations and collectively form a functionally complete set whereas multiple instances of the devices can be connected to implement any logical expression. Furthermore, bridge devices to interface small molecule sensors and transcriptional networks with protein devices are created. To illustrate composability, two systems are engineered in yeast, the first of which interfaces a phosphorylation load driver within flanking transcriptional regulatory modules to mitigate retroactivity, exemplifying time-scale separation as a means of realizing functional modularity in biological networks. The second system, a fast bistable toggle switch, is the first synthetic network based solely on protein interactions and can be interfaced endogenously to allow controllable abrogation of yeast budding. Work in this thesis provides a set of useful design principles for engineering protein networks in eukaryotes and may improve understanding of natural signaling motifs, allow modulation of existing networks, or foster new synthetic biology applications. / by Deepak Mishra. / Sc. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Integrins are a family of heterodimeric cell surface receptors that are functionally important for cell adhesion, migration and proliferation. Certain integrins, especially those that are known to recognize the arginine-glycine-aspartate (RGD) motif, are heavily overexpressed in many cancers relative to healthy tissue, making them attractive targets for therapeutic intervention. However, prior attempts to antagonize these integrins as a cancer therapy have all failed in the clinic. In this thesis, we instead exploit integrins as a target tumor antigen in the context of immunotherapy. The engineered cysteine knot peptide, 2.5F, is highly crossreactive and capable of recognizing multiple RGD-binding integrins. Our initial attempts to utilize this binder as a targeting moiety for delivering IL-2 as an immunocytokine failed. Mathematical modeling results indicated that immunocytokines, unless adhering to specific design criteria, are unlikely to benefit from targeting and may actually exhibit limited efficacy. Therefore, we "deconstructed" this immunocytokine into its functional parts: extended half-life IL-2 and 2.5F-Fc, the antibody-like construct directed against RGD-binding integrins. This combination immunotherapeutic approach was able to synergistically control tumor growth in three syngeneic murine models of cancer, including durable cures and development of immunological memory. Contrary to prior attempts at integrin-targeting, the mechanism of action was independent of functional integrin antagonism, including effects on angiogenesis and tumor proliferation. In fact, efficacy of this therapy depended solely upon the adaptive and innate arms of immunity, specifically CD8+ T cells, macrophages, and dendritic cells. Furthermore, checkpoint blockade, the gold standard for immunotherapy to date, can further enhance the efficacy of this therapeutic approach. This signifies that the combination of IL-2 and 2.5F-Fc exerts a distinct, yet complementary immune response that opens the door for clinical translation. / by Byron H. Kwan. / Ph. D.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references. / The validity and usefulness of clustering marine group II tetranucleotide signatures using emergent self-organizing maps was investigated. Fosmids from the HF200 library were chosen for sequencing based on end-sequence tetranucleotide clustering with group II seed sequences, as well as blastx homology. Fosmids were sequenced using a single 454- titanium sequencing run, and contigs subsequently assembled in silico. A total of 99 contigs over 20kb were retrieved, at least 72 of which belong to the marine group II archaea. The phylogenetic substructure of the marine group II archaeal clusters having more than a few representatives was investigated, by clustering tetranucleotide signatures of group II contigs over 20kb, also with an emergent self-organizing map. The distribution of these clusters in the Hawaii Ocean Time Series depth profile fosmid libraries in the DeLong lab were mapped onto depth profiles from three independent cruises. / by Rachel A. Hillmer. / S.M.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / The heterogeneity of individual cellular behavior in response to physical and chemical stimuli has raised increasing attention in many biological processes. There is great incentive in developing techniques for high throughput single-cell measurements and manipulations. Particularly, cell size has been recognized as an important parameter in single cell study and pericellular protease activity plays a key role in regulating the microenvironment of individual cells. Therefore, this thesis focuses on establishing new methods to address the issues of cell size and single cell protease measurement. We first develop a size-based cell separation technique using Dean-coupled inertial microfluidic sorter. Separation of cells by size before downstream assays might be beneficial in simplifying the system and facilitating the discovery of rare subpopulations through enrichment of cells with certain size range or cell cycle phase. By investigating the particle focusing and separation mechanisms in curved microfluidic channel, we develop a novel design of inertial microfluidic sorter with higher separation resolution and then demonstrate its capacity in leukocyte isolation from blood. This novel cell sorter would be a promising alternative to many other cell separation problems. We then establish a microfluidic platform for functional measurement of single cell pericellular proteases, including both those secreted and expressed on cell surface. We apply the platform to studying the PMA-mediated protease response of HepG2 cells at single-cell level and reveal the diversity in the dynamic patterns of single-cell protease activity profile upon drug stimulation. We also present the preliminary exploration of single-cell protease activity behavior in anticancer drug resistance development. Lastly, we explore the applicability of our platform for single-cell shedding measurement. Protease-mediated molecular shedding is one of the key mechanisms through which individual cells actively regulate their own microenvironment. However, the amount of molecules being shed for individual cells is extremely low, posing significant challenges in detecting shedding quantitatively. By means of analytical analysis and numerical simulations, we investigate the intrinsic noise of low-abundance molecule detection. Experimental characterizations have also been performed to evaluate the impact of practical factors on actual readout variation. / by Lidan Wu. / Ph. D.