Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Investigating protein location and concentration is critical to understanding function. Reagentless biosensors, in which a reporting fluorophore is conjugated to a binding scaffold, can detect analytes of interest with high temporal and spatial resolution. However, because these biosensors require laborious empirical screening to develop, their adoption has been limited. Hence, we establish design principles that will facilitate development. In this thesis, we first develop a kinetic model for the dynamic performance of a reagentless biosensor. Using a sinusoidal signal for ligand concentration, our findings suggest that it is optimal to use a binding moiety whose equilibrium dissociation constant matches that of the average predicted input signal, while maximizing both the association rate constant and the dissociation rate constant at the necessary ratio to create the desired equilibrium constant. Although practical limitations constrain the attainment of these objectives, the derivation of these design principles provides guidance for improved reagentless biosensor performance and metrics for quality standards in the development of biosensors. Following these guidelines, we use the human tenth type III fibronectin domain to engineer new binders against several ligands of the EGFR receptor. Using these binders and others, we design and characterize biosensors based on various target analytes, scaffolds and fluorophores. We observe that analytes can harbor specific binding pockets for the fluorophore, which sharply increase the fluorescence produced upon binding. Furthermore, we demonstrate that a fluorophore conjugated to locally rigid surfaces possesses lower background fluorescence. Based on these newly identified properties, we design biosensors that produce a 100-fold increase in fluorescence upon binding to analyte, about a 10-fold improvement over the previous best biosensor. In order to improve the methodology of reagentless biosensor design, we establish a method for site-specific labeling of proteins displayed on the surface of yeasts. This procedure allows for the screening of libraries of sensors for binding and fluorescence enhancement simultaneously. Finally, we explore an alternative sensor design, based on competitive inhibition of fluorescence quenching. / by Seymour de Picciotto. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Non-small cell lung carcinoma (NSCLC) is the most common type of lung cancer and is the leading cause of cancer related mortality worldwide. The past decade has seen exciting advances in the development of targeted therapies for the treatment of NSCLC. However, the efficacy of such therapies in prolonging patient survival has been disappointing, and there remains an urgent need for a greater understanding of the molecular events involved in tumor progression and metastases. MET and members of the epidermal growth factor receptor (EGFR)- family are cell-surface receptor tyrosine kinases (RTK) commonly upregulated in NSCLC cells, and their signaling crosstalk can confer therapy resistance. The four EGFR-family members are similar in structure; each contains a ligand binding domain, a transmembrane region, and a phosphotyrosine cytosolic domain. Upon ligand binding, each of the family members dimerizes in a homo- or heterotypic manner to initiate signaling cascades that influence migration and proliferation outcomes. This thesis describes the use of engineered bivalent ligands to systematically manipulate receptor dimerization, perturb downstream signaling processes, and affect phenotypic outcomes. Results showed that biasing away from an EGFR-HER-2 with a bivalent ligand reduces cell motility significantly in a stem-cell model cell line, but does not inhibit cell proliferation or cell survival. Furthermore, reengineering ligands with varying intraligand distance showed that this inhibition of motility is distance-dependent. Lastly, a Neuregulin-Neuregulin (NN) ligand disrupts the crosstalk between MET and Her-3 receptor to reduce hepatocyte growth factor (HGF)-induced cell motility. Based on these results, a mass spectrometry (MS)-based phosphoproteomics approach to quantitatively map cellular signaling events mediated by Her-3 downstream of Met proceeded. The thesis concludes by quantitatively exploring the relationship between the measured signals of phosphorylated proteins and the cellular migration phenotypes, seeking novel potential therapeutic targets. Overall, this work illustrates the complexity of the EGFR signaling pathway and the need for new paradigms to target its signaling pathway to advance our knowledge in developing new therapeutic approaches. / by Edgar Ivan Sanchez Palacios. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 153-163). / Cells are constantly bombarded with stimuli that they must sense, process, and interpret to make decisions. This capability is provided by interconnected signaling pathways. Many of the components and interactions within pathways have been identified, and it is becoming clear that the precise dynamics they generate are necessary for proper system function. However, our understanding of how pathways are interconnected to drive decisions is limited. We must overcoming this limitation to develop interventions that can fine tune a cell decision by modulating specific features of its constituent pathway's dynamics. How can we quantatively map a whole cell decision process? Answering this question requires addressing challenges at three scales: the detailed biochemistry of protein-protein interactions, the complex, interlocked feedback loops of transcriptionally regulated signaling pathways, and the multiple mechanisms of connection that link distinct pathways together into a full cell decision process. In this thesis, we address challenges at each level. We develop new computational approaches for identifying the interactions driving dynamics in protein-protein networks. Applied to the cyanobacterial clock, these approaches identify two coupled motifs that together provide independent control over oscillation phase and period. Using the p53 pathway as a model transcriptional network, we experimentally isolate and characterize dynamics from a core feedback loop in individual cells. A quantitative model of this signaling network predicts and rationalizes the distinct effects on dynamics of additional feedback loops and small molecule inhibitors. Finally, we demonstrated the feasibility of combining individual pathway models to map a whole cell decision: cell cycle arrest elicited by the mammalian DNA damage response. By coupling modeling and experiments, we used this combined perspective to uncover some new biology. We found that multiple arrest mechanisms must work together in a proper cell cycle arrest, and identified a new role for p21 in preventing G2 arrest, paradoxically through its action on G1 cyclins. This thesis demonstrates that we can quantitatively map the logic of cellular decisions, affording new insight and revealing points of control. / by Jared E. Toettcher. / Ph.D.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 68-76). / The intestinal crypt is a highly dynamic system, as the entire epithelium is constantly turned over and renewed by the proliferative stem cells located at the bottom of the crypt. While this system is crucial for nutrient absorption, any derangements in the proliferative cells can quickly lead to cancer. In this thesis, we sought to better understand the behavioral and genetic characteristics of the different cell types along the intestinal crypt, in a mouse model. We first attempted to quantify the migration velocities and proliferative rates at a single-cell level using 5-ethynol-2'-deoxyuridine (EdU) pulse-chase labeling. While we observed marked differences in the proliferation rates between the absorptive and secretory lineages (the former is faster), our experimental setup was unable to resolve any possible differences in migratory behaviors. We then turned our attention to quantifying the spatial expression patterns of selected transcripts in the intestinal crypt, both in wildtype and in an inducible APC-loss cancer model. We were able to show that the transcript expression profiles of key differentiation and proliferation markers (Creb313, Gob5, Ki-67, cMyc), as well as the ephrin signaling (EphB2 and EphrinBl) were significantly altered in the early stages (7 days) of adenoma formation. A more detailed analysis also separated this derangement in terms of extrinsic factors (e.g. altered cell composition along the crypt) and intrinsic factors (e.g. inherent change of cellular expression profile after APC loss). What is particularly interesting is that even differentiated cells in adenomas can exhibit such derangements. Our hypothesis to explain this observation is that these differentiated cells actually come from transformed stem cells. To test this hypothesis, we needed to verify that these cells indeed have excision at the Apc locus. After several approaches involving both single-molecule fluorescent in situ hybridization and quantitative polymerase chain reaction (PCR), the results were ultimately inconclusive. However, we propose several additional approaches that this hypothesis can be verified, and if verified, some biologically significant questions that can be addressed regarding the early dynamics of stem cells in intestinal cancer development. / by Kevin Su Yau Kung. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 215-232). / Receptor tyrosine kinases (RTKs) are critical regulators of cellular homeostasis in multicellular organisms. They influence cell proliferation, migration, differentiation, and transcriptional activation, among other processes, and are therefore also relevant to cancer biology. Upon interaction with cognate ligand, RTKs initiate signaling cascades dependent in part on the phosphorylation of proteins. From a computational perspective, this thesis has studied methods for quantifying relationships between measured signals (using Bayesian network inference, correlation, and mutual information-based methods), and between signals and cellular phenotypes (using linear regression, partial least squares regression, and feature selection methods). From a biological perspective, this thesis has studied signaling between RTKs, signaling and cell migration downstream of RTKs in epithelial versus mesenchymal cell states, and comparative signaling across six RTKs. In the latter case, the results show that the six RTKs cluster into three classes based on their inferred signaling networks. Using publicly available transcriptional and pharmacological profiling data from hundreds of cancer cell lines, it was determined that expression of same-class RTK genes or their cognate ligands can correlate with insensitivity to drugs targeting other RTKs in that class. This suggests that resistance to RTK-targeted therapies in cancer may emerge in part because same-class RTKs can compensate for the reduced signaling of the inhibited receptor. The thesis concludes by quantitatively exploring the features of experimental data that improve model accuracy. / by Joel Patrick Wagner. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 129-141). / While technological advances have enabled measurements of thousands of molecules simultaneously, the data from each technology can only show a single-view of biological processes. Capturing a complete picture of these processes requires integrating data of different types, including clinical data, genomics, transcriptomics, proteomics and metabolomics. Here, we have demonstrated novel computational approaches for integrating a variety of biological data and used these methods to study Huntington's disease (HD). First, we established a computational approach for combining transcriptomics with qualitative, ordinal clinical information. Such data are available for a variety of diseases, but are rarely used in conjunction with molecular data. We adapted an ordinal regression model to analyze gene expression data from HD brains in conjunction with their grade of neuronal loss. This approach identified the SGPLl-encoded enzyme (SPL) as a potential therapeutic target for HD. Continuing our data-driven approach, we discovered the dysregulation of pathways associated with SPL and inferred molecular mechanisms by which SPL inhibition exerts protective effects. Then, we demonstrated a novel network-based, machine-learning algorithm for integrative analysis of untargeted metabolomic data. Metabolites are small molecules whose levels directly show cellular phenotypes. Despite their potential, the integrative analysis of metabolomic data has been limited because of challenges in metabolite identification. To address these challenges, we have developed a pioneering method for interpreting the large-scale metabolomic data in the context of other molecules such as proteins. We used our method to infer novel dysregulated pathways in a model of HD and experimentally verified our predictions. These two methods are extremely general and can be applied to a variety of diseases. As the costs of generating high-throughput data decrease, we anticipate that our approaches will have growing relevance to the discovery of therapeutic strategies for precision medicine. / by Leila Pirhaji. / Ph. D.

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.