Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 119-128). / The physical properties of a cell are manifestations of its most basic molecular and metabolic processes. In particular, size has been a sought metric, which can be difficult to ascertain with great resolution or for smaller organisms. The advancement of single-cell measurement techniques and the understanding of cell-to-cell variability have renewed the interest in size characterization. In addition, knowledge of how individual cells grow and coordinate their growth with the cell cycle is of fundamental interest to understanding cell development, but various approaches for describing cellular growth patterns have often reached irreconcilable conclusions. In this thesis, a highly sensitive microfabricated single-cell mass sensor - the suspended microchannel resonator - is used to demonstrate cellular growth measurements by mass accumulation for several microorganism, ranging from bacterial cells to eukaryotes and mammalian cells. From those measurements insights about cellular growth are derived, demonstrating that larger cells grow faster than smaller ones, consistent with exponential-like growth patterns and incompatible with linear growth models. Subsequently, the implementation of mechanical traps as means to optimize existing sensors is presented and the techniques are applied to the measurement of total mass, density and volume at the single-cell level. Finally, a method is introduced to quantify cellular dry mass, dry density and water content. It is based on weighing the same cell first in a water-based fluid and subsequently in a deuterium oxide-based fluid, which rapidly exchanges the intracellular water content. Correlations between dry density and cellular proliferation and composition are described. Dry density is described as a quantitative index that correlates with proliferation and cellular chemical composition. / by Francisco Feijó Delgado. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 149-156). / Targeted cancer therapeutics have seen constraint in clinical efficacy due to resistance. Indicators for resistance may include genetic mutations or protein-level overexpression of targeted or bypass receptor tyrosine kinases (RTKs). While the latter is often attributed to gene amplification, genetic characterization of tumor biopsies has failed to explain substantial proportions of resistance. We hypothesize that post-synthesis mechanisms governing RTK levels may represent underappreciated contributors to drug resistance. We have developed an experimental and computational model for the simultaneous analysis of synthesis and post-synthesis mechanisms contributing to protein level changes. The experimental component quantitatively measures processes operating on multiple time scales in a multi-plexed fashion, with methods generalizable to any membrane bound protein. Parameter distribution estimation by fitting data to an integrative cellular model quantifies native RTK processes and enables the study of treatment induced mechanistic changes. It has been reported that triple negative breast cancer cell lines up-regulate many RTKs in response to Mek inhibition, although reported with conflicting mechanisms. Upon integrated analysis, we find both Axl and Her2 have increased lysate levels after Mek inhibition with 3 Mek inhibitors, Selumetinib, Binimetinib, and PD0325901. Axl changes are attributed to a decrease in proteolytic shedding and protein degradation, and Her2 changes are attributed to decreased synthesis. Met shows a decrease in proteolytic shedding similar to Axl, but compensating synthesis and degradation mechanisms counteract the effect. Contrastingly, Erk inhibition shows minor effects on RTK reprogramming, with Erk dimer inhibitor DEL-22379 exhibiting RTK specific protease effects and highlighting RTK specific outcomes of decreased endocytosis. This quantitative model enables prediction of combination therapies with mechanistic process inhibitors. Our predictions match experimental observations that Axl lysate level increases with Mek inhibition remains unchanged in the presence of transcriptional inhibition, supporting a role for post-synthesis mechanisms. Through additional combination with an Axl inhibitor, we are able to further the anti-proliferative and anti-migratory effect of Mek and transcriptional inhibition in TNBC. This study not only provides a novel and broadly applicable quantitative framework for characterizing RTK level changes, but also emphasizes the RTK, pathway target, and inhibitor variation of RTK reprogramming in drug resistance. / by Allison Claas. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Methylating agents are ubiquitous in our internal and external environments and can cause damage to all cellular components, including our DNA. If left unrepaired, methylated DNA can cause mutations, cell death, and disease, such as cancer and neurodegeneration. The majority of DNA lesions caused by methylating agents are repaired by the base excision repair (BER) pathway, which is initiated by the lesion-specific alkyladenine glycosylase (Aag). Loss of Aag in embryonic stem (ES) cells renders them sensitive to the methylating agent MMS (methyl methanesulfonate) compared to wild-type (WT). Surprisingly, this phenotype is reversed in hematopoietic myeloid progenitors and cerebellar granule neurons (CGNs) where Aag' cells are resistant to MMS induced killing compared to WT. In this study, we investigated how Aag can cause cell-specific responses to alkylating agents. We generated new WT, Aag-/-, and Aag overexpressing (mAagTg) 129 and C57B1/6 ES cells and showed that inbred genetic background did not affect sensitivity to MMS, indicating this to be a cell-intrinsic response. Moreover, we found that cells overexpressing Aag were even more sensitive to MMS than Aag-/- cells, suggesting that ES cells endure methylation treatment best when they express Aag within an optimal range. To study Aag-dependent neural sensitivity to methylating agents, we optimized protocols for the isolation and culture of primary cerebellar granule neurons and determination of cell death after drug treatment by high-throughput imaging. CGNs isolated from WT, Aag-/-, and mAagTg mice exhibited cell sensitivity to MMS treatment that was dependent on Aag and Parp activity, thus recapitulating in vivo results and proving that CGN death is cell-intrinsic. Cell death was independent of caspases, mitochondrial depolarization, and AIF translocation. We did observe the formation of enlarged mitochondria and are investigating whether mitochondrial dynamics are causative of cell death in an Aag-dependent manner. Finally, we used in vitro hematopoietic and neuronal differentiation to monitor cell responses to MMS as a function of cellular development. Three different methods all successfully generated mature neurons based on morphology, immunochemical staining, and Aag expression. Though we successfully differentiated ES cells into cell types of interest, we are continuing to optimize methods for the assessment of alkylation sensitivity in the resulting heterogeneous populations. / by Carrie Marie Margulies. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / 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 161-180). / The field of DNA nanotechnology has rapidly evolved over the past three decades, reaching a point where researchers can conceive of and implement both bioinspired and biomimetic devices using the programmed self-assembly of DNA molecules. The sophisticated natural systems that these devices seek to interrogate and to imitate have Angstrom-level organizational precision, however, and the nanotechnology community faces the challenge of fine-tuning their design principles to match. A necessity for achieving this level of spatial control is an understanding of the atomic-level physico-chemical interactions and temporal dynamics inherent to fundamental structural motifs used for nanodevice design. The stacked configurational isomers of four-way junctions, the motif on which DNA nanotechnology was founded, are the focus of this work; initially in isolation and then as part of larger DNA nano-assemblies. The first study presented here investigates the impact of sequence on the structure, stability, and flexibility of these junction isomers, along with their canonical B-form duplex, nicked-duplex and single cross-over topological variants. Using explicit solvent and counterion molecular dynamics simulations, the base-pair level interactions that influence experimentally-observed conformational state preferences are interrogated and free-energy calculations provide a detailed theoretical picture of isomerization thermodynamics. Next, the synergy of single molecule imaging, computational modelling, and a novel enzymatic assay is exploited to characterize the three-dimensional structure and catalytic function of a DNA tweezer-actuated nanoreactor. The analyses presented here show that rational redesign of the four-way junctions in the device enables the tweezers to be more completely and uniformly closed, while the sequence-level design strategies explored in this study provide guidelines for improving the performance of DNA-based structures. Finally, MD simulations are used to inform finite-element method coarse-grained models for the ground-state structure determination and equilibrium Brownian Dynamics of large-scale DNA origamis. Together, this thesis presents a set of guidelines for the rational design of nanodevices comprising arrays of constrained four-way junctions. / by Matthew R. Adendorff. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Cytokine therapy can activate potent antitumor responses, yet collateral toxicity often limits dosages. Although immunocytokines have been designed with the intent to localize cytokine activity, systemic dose-limiting side effects are not fully ameliorated by attempted tumor targeting. In the first part of this work, we used the B 1 6F 10 melanoma model to demonstrate that a nontoxic dose of IL-2 immunocytokine synergized with tumor-specific antibody to significantly enhance therapeutic outcomes compared to monotherapy with immunocytokine, concomitant with increased tumor saturation and intratumoral cytokine responses. Examination of cell subset biodistribution showed that the immunocytokine associated mainly with IL-2R-expressing innate immune cells, with more bound immunocytokine present in systemic organs than in the tumor microenvironment. More surprisingly, immunocytokine antigen specificity and Fc[gamma]R interactions did not appear necessary for therapeutic efficacy or biodistribution patterns, as immunocytokines with irrelevant specificity and/or inactive mutant Fc domains behaved similarly to tumor-specific immunocytokine. IL-2-IL-2R interactions, rather than antibody-antigen targeting, dictated immunocytokine localization; however, the lack of tumor targeting did not preclude successful antibody combination therapy. This study presents a safe, straightforward strategy for augmenting immunocytokine efficacy via supplementary antibody dosing and explores underappreciated factors that can subvert efforts to purposefully alter cytokine biodistribution. Numerous studies have identified cancer immunotherapy combinations that exhibit synergistic antitumor activity, but surprisingly, these studies rarely consider the effects of relative dose timing. In the second part of this work, using established syngeneic tumor models, we found that staggering IFN[alpha] administration after, rather than simultaneously with, serum-persistent IL-2 and tumor-specific antibody significantly increased long-term survival and generated immunological memory. Successful combination therapy required IFNa-induced activation of cross-presenting CD8[alpha]+ DCs following release of antigenic tumor debris by the IL-2-and-antibody-mediated immune response. Due to decreased phagocytic ability post-maturation, DCs activated too early captured much less antigen and could not effectively prime CD8+ T cells. Temporally programming DC activation to occur after tumoricidal activity enhanced tumor control by multiple combination immunotherapies that act through distinct mechanistic pathways, presenting a facile strategy for augmenting efficacy in the combinatorial treatment setting and highlighting dose schedule as an overlooked factor that can profoundly affect the success of multi-component immunotherapies. / by Alice Tzeng. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Genomes experience an often hostile environment that creates a vast array of damages that can give rise to myriad biological outcomes. Fortunately, cells are equipped with networks such as direct reversal, base excision repair, nucleotide excision repair, homologous recombination, and translesion synthesis that help preserve informational integrity. The first part of this dissertation focuses on whether or not bulky alkyl lesions at the N2 atom of guanine are addressed in vivo by the DinB bypass polymerase. In the work described herein, a collection of N2-guanine lesions was inserted in single-stranded M13 genomes and evaluated in strains possessing or lacking DinB via the competitive replication and adduct bypass (CRAB) and restriction endonuclease and postlabeling (REAP) assays. It was found that DinB could in fact bypass the N2-furfuryl-guanine lesion and its saturated homolog in vivo. The second part of this work describes how we systematically investigated the role that the distance from an origin of replication may have in the mutagenesis of an adduct. Our hypothesis was that a lesion farther from the origin of replication would be less mutagenic since it would be afforded more time for detection and removal before the replicative polymerase traversed it, fixing the mutation. We inserted 0-methylguanine in single-stranded M13 genomes at different distances from the origin of replication and analyzed progeny phage by the REAP assay. Our findings were in contrast with the hypothesis; a higher mutation frequency was obtained at the site distal from the origin of replication. Alternative hypotheses and future experiments are discussed as part of this work. The third part of this dissertation seeks to expand the spectrum of known substrates for the enzyme AIkB, which mediates direct reversal of DNA damage. AlkB is an iron- and CCketoglutarate- dependent dioxygenase that is part of the adaptive response in E. coli, and has homologs in many species. On basis of in vitro data we created the hypothesis that the N 2 guanine lesions as well as 6-methyladenine would be substrates for the enzyme AlkB in vivo. We found, however, in this case the in vitro results did not predict the biology observed in cells. / by Nidhi Shrivastav. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 161-171). / Normalizing angiogenesis is a promising strategy for treatments of cancer and several disorders plagued by misregulated blood supplies. To address the daunting complexity of angiogenesis arising from multiple phenotypic behaviors governed by multiple stimuli, computational approaches have been developed to predict sprouting angiogenic outcomes. In recent years, the agent based model, in which individual cells are modeled as autonomous decision making entities, has become an important tool for simulating complex phenomena including angiogenesis. The reliability of these models depends on model validation by quantitative experimental characterization of the cellular (agent) behaviors which so far has been lacking. To this end, I develop an experimental and computational method to semi-automatically estimate parameters describing the single-cell decision in the agent based model based on flow cytometry aggregate headcount data and single cell microscopy which yields full panel single cell trajectories of individual endothelial cells. Applying thees method to the single cell decision data, I propose two conceptual models to account for the different state transition patterns and how they are modulated in the presence of opposing inflammatory cytokines. The observed unique state transition patterns in the angiogenic endothelial cell population are consistent with one of these descriptions, the diverse population model (DPM). The DPM interpretation offers an alternative view from the traditional paradigm of cell population heterogeneity. This understanding is important in designing appropriate therapeutic agents that take effect at the cellular level to meet a tissue level therapeutic goal. / by Tharathorn Rimchala. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009. / Vita. Cataloged from PDF version of thesis. / Includes bibliographical references. / Major therapeutic efforts have been devoted to targeting the epidermal growth factor receptor (EGFR), which is aberrantly expressed in many cancers and is correlated with tumor progression and invasiveness. In the current tumor progression paradigm, individual invasive carcinomas arise upon epithelial-mesenchymal transition (EMT) and migrate through a complex tumor microenvironment to successfully metastasize. While the activation of EGFR enhances invasiveness in vivo, it is still unclear which downstream molecular changes caused by EMT contribute to the invasive phenotype and subsequently, how the invasive cell integrates downstream biophysical processes to invade through a three-dimensional (3D) extracellular matrix (ECM). This thesis addresses these questions from a quantitative, engineering perspective, that cell migration in the context of the invasion microenvironment is an inherently multivariate biochemical and biophysical problem. As such, we developed various carefully controlled, but biologically relevant, in vitro experimental systems with an emphasis on the extracellular microenvironment. These systems were combined with quantitative data-driven parameterization of signaling components and subsequent modeling of migration phenotypes via various 2D and 3D single cell tracking assays. By measuring 2D cell migration of immortalized human mammary epithelial cells conferring pre- or post-EMT states, we respectively identified physiologically relevant, EMT-dependent collective and individual migration modes. A comprehensive systems modeling approach identified the novel activation of a downstream kinase, which acts in a switch-like manner to differentially regulate epithelial, EGFR-dependent migration versus mesenchymal migration. Next, the subsequent mesenchymal migration in 3D, as modeled by a human glioblastoma cell line, was assessed via a quantitative biophysical analysis. EGF-enhanced 3D migration arose from a balance between a cell-intrinsic regulation of cell speed and a matrix- and proteolysis-dependent, extrinsic regulation of directional persistence. Lastly, we quantified fibroblast migration in a porous scaffold of varying pore sizes and stiffness to model contact-guided quasi-3D migration. We surprisingly found that the micro-architecture of guidance structures alone influenced cell speed. Therefore, the combination of biologically relevant experimental systems and quantitative models provided novel mechanistic insights pertinent to early stages of tumor metastasis. The experimental approaches and biological mechanisms in this thesis hold potential in guiding therapeutic targeting of the biophysical responses prompted by the extracellular microenvironment. / by Hyung-Do Kim. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 72-76). / In systems biology, ordinary differential equation models are used frequently to model the dynamics of molecular and cellular systems. These models are parameterized with rate constants and other quantities that are often estimated from empirical data. When the data are insufficient to fully determine the model parameters, the parameter values are unidentifiable, and many parameter sets are consistent with the data. To cope, many studies sample a collection of parameters to represent the uncertainty or simplify the model to remove parameters. Studies rarely verify that their sampling is sufficient or test alternative model simplifications. There is a need for better practices for uncertainty quantification. In this work, I present two case studies demonstrating the use of biochemical models with unidentifiable parameters to make useful predictions. The first study investigates a model of the complement system, a system of circulating proteins involved in immune response, to find promising drug targets for treatment of sepsis. I compared a sampling method to a worst-case search method for quantifying the uncertainty in responses to hypothetical inhibitors and found that the choice of method significantly impacts the results. I identified mechanistic explanations for the observed inhibitor responses that demonstrate limitations of intuition and suggest strategies for further studies. The second study uses a kinetic model of the thiolase and reductase enzymes of the 3-hydroxyacid metabolic pathway to interpret available in vitro data to determine the kinetic changes induced by a mutation in the thiolase. Sampling approaches cannot identify all combinations of rate constants that could have changed according to the data, so I perform a selective enumeration strategy that identifies all feasible combinations by testing only a limited number. The simplest feasible combinations identify three classes of rate constant changes induced by the mutation. I also use a global sensitivity analysis approach to predict which reaction steps are most likely to positively affect the product selectivity ratio of the system. Together, these studies demonstrate that unidentifiable models can be useful if the correct methods are chosen to quantify their uncertainty and serve as examples of how to choose or design these methods. / by David C. Flowers. / Ph. D.

Thesis (M. Eng.)--Massachusetts Institute of Technology, Biological Engineering Division, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 58-63). / Metastasis is a multistep process during which tumor cells separate from a primary tumor, penetrate the bloodstream, evade host defenses, and colonize distant organs. This final and fatal step in tumor development is the cause of more than 90% of cancer related deaths. Therapies and diagnostics can be targeted to metastasis at three points in its progression: the primary tumor, the secondary tumor, and circulating tumor cells (CTCs). While much work has focused on primary tumors, less effort has concentrated on targeted isolation, detection and therapy of deeply penetrated metastases and CTCs. Here, I discuss cell and nanomaterial-based approaches for detecting and ablating these malignant populations. The number of CTCs in the blood directly correlates with disease progression; however, the lack of definitive markers has limited their isolation and characterization. I have demonstrated the potential use of platelets as a cell-based marker for isolation and detection of CTCs. Using phage display technology, it was possible to identify candidate peptides specific to mesenchymal-like tumor cells that may mimic the motile and aggressive CTC population. In order to detect and ablate metastases and CTCs, M13 bacteriophage was engineered into a platform for simultaneous tumor targeting, imaging, and therapy. Single-walled carbon nanotubes (SWNTs) and doxorubicin, a chemotherapeutic agent, were loaded on phage for fluorescent near-infrared imaging and cytotoxicity of metastatic lesions, respectively. The near-infrared optical properties of SWNTs in the "second window" make them promising candidates for imaging nascent and deeply seeded tumors. This approach provides an 'all-in-one' platform for targeted fluorescence imaging and efficient drug delivery and may allow for real-time monitoring of tumor response to drug regimens. / by Aditya Kohli. / M.Eng.