Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Cells are constantly faced with the challenge of functioning reliably while being subject to unpredictable changes from within and outside. Here, I present two studies in which I analyze how biochemical circuits that regulate signaling and gene expression can generate robustness or phenotypic variability between otherwise identical yeast cells. Using the osmosensing signaling pathway which consists of a phosphorelay connected to a MAPK cascade, we predict signaling robustness to changes in kinetic rate constants by employing a computational sensitivity analysis. Consistent with the model predictions, we find that the input-output relation of signaling activation is severely impacted by protein coding sequence changes in the MAPK cascade genes, but not the phosphorelay genes. By decoupling the network into two separate modules, we show that an input-output analysis of each of the modules can generate the observed disparity in their tolerance to kinetic parameter variations. Our analysis suggests that the input-output relation of catalytic signaling pathways i.e. MAPK cascade are intrinsically sensitive to kinetic rate perturbations. By contrast, signaling governed by stoichiometric biochemical reactions i.e. phosphorelay exhibit robust input-output functions. We further find that cells challenged to alter their input-output function mostly recovered by gaining mutations in the MAPK cascade genes, which further supports our model. We next explore how HAC1 RNA splicing contributes to heterogeneity in the unfolded protein response (UPR). We adapt the single molecule FISH (sm-FISH) method to count endogenous spliced and unspliced HAC1 transcripts in single cells. We use a stochastic bursting-transcription-and-splicing model to determine the kinetic rates from the single cell measurements. We find that the cell-to-cell variability in the degree of splicing is tightly regulated in the presence of a UPR-inducing chemical agent, but is compromised under heat stress. By considering models including extrinsic noise at the splicing or transcriptional level, we show that the increased variability in the degree of splicing under heat stress can be generated by increased fluctuations in the splicing rate. Lastly, we present an approach using sm-FISH and protein synthesis inhibitors to measure translation and we show preliminary results suggesting its feasibility. / by Mei-Lyn Ong. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Many organisms have evolved DNA damage response mechanisms to deal with the constant damage to DNA caused by endogenous and exogenous agents. These mechanisms activate cell cycle checkpoints to allow time for DNA repair or, in the case of severely damaged DNA, initiate cell death mechanisms to maintain genomic integrity. The cell's response to DNA damaging agents includes wide spread changes in the transcriptional state of the cell that have been implicated in cell death or survival decisions. However, we do not fully understand how the multiple and sometimes opposing transcriptional signals are interpreted to make these critical decisions. A computational and systems biology approach was taken to study the wide-spread transcriptional changes induced in human cell lines after exposure to a DNA damaging and chemotherapeutic agent, 1,3-bis-(2-chloroethyl)- 1 -nitrosourea (BCNU or carmustine). Cell lines with extreme sensitivity or resistance to BCNU were identified from a set of twenty four genetically diverse human lymphoblastoid cell lines using a high-throughput method that was developed as part of this thesis. This assay has broad applications and can be used to simultaneously screen multiple cell lines and drugs for accurate measurements of cell proliferation and survival after drug treatment. The assay has the advantage of having a large dynamic range that allows sensitivity measurements on a multi-log scale allowing better resolution of comparative sensitivities. Temporal transcription profiles were measured in cell lines with extreme BCNU sensitivity or resistance to generate a large transcription data set amenable to bioinformatics analysis. A transcriptional signature of 706 genes, differentially expressed between BCNU sensitive and resistant cell lines, was identified. Network and gene ontology enrichment identified these differentially expressed genes as being involved in key DNA damage response processes like apoptosis and mitosis. Experimental evidence showed that the transcription signature correlated with observed cellular phenotypes. Furthermore, the NF-Y transcription factor binding motif was enriched in the promoter region of 62 mitosis-related genes downregulated in BCNU sensitive but not resistant cell lines. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) confirmed NF-Y occupancy in 54 of the 62 genes, thus implicating NF-Y as a possible regulator of the observed stalling of entry into mitosis. Using experimental and computational techniques we deciphered the functional importance of differential transcription between BCNU sensitive and resistant cell lines and identified NF-Y as an important factor in the transcriptional and phenotypic cell response to BCNU such as the control of entry into mitosis. / by Chandni Rajan Valiathan. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 141-149). / The reconstruction of regulatory networks is one of the most challenging tasks in systems biology. Although some models for inferring regulatory networks can make useful predictions about the wiring and mechanisms of molecular interactions, these approaches are still limited and there is a strong need to develop increasingly universal and accurate approaches for network reconstruction. This problem is particularly challenging in mammals, due to the higher complexity of mammalian regulatory networks and limitations in experimental manipulation. In this thesis, I present three systematic approachs to reconstruct, analyse and refine models of gene regulation. In Chapter 1, I devise a method for deriving an observational model from temporal genomic profiles. I use it to choose targets for perturbation experiments in order to determine a network controlling the responses of mouse primary dendritic cells to stimulation with pathogen components. In Chapter 2, I introduce the algorithm Exigo, for identifying essential interactions in regulatory networks reconstructed from experimental data where regulators have been silenced, using a network reduction strategy. Exigo outperforms previous approaches on simulated data, uncovers the core network structure when applied to real networks derived from perturbation studies in mammals, and improves the performance of network inference methods. Lastly, I introduce in Chapter 3 an approach to learn a module network from multiple highthroughput assays. Analysis of a diffuse large B-cell lymphoma dataset identifies candidate regulator genes, microRNAs and copy number aberrations with biological, and possibly therapeutic, importance. / by Ana Paula Santos Botelho Oliveira Leite. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 119-121). / Cancer is a clonal evolutionary process. This results in complex clonal architecture and intratumoral heterogeneity in each patient. This also presents challenges for effective therapeutic intervention - with constant selective pressure to induce or select pre-existing resistant subclones toward drug resistance. Mathematical/computational modeling from population genetics, evolutionary dynamics, and engineering are being utilized to a greater extent in recent times to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling/combinations design. In this thesis we present several joint quantitative and experimental approaches for the rational design of drug combinations to tackle the issue of intratumoral heterogeneity and clonal evolution. Using a tractable experimental system with pre-defined tumor compositions, we derived computational approaches to rationally design drug combinations with the goal of minimizing a given heterogeneous tumor. We found that the best drug combinations can oftentimes be non-intuitive as they do not contain component drugs most effective for the individual subpopulations. This was the result of a need for combinatorial considerations on the effects of each drug on all subpopulations, hence at times leading to non-intuitive drug regimens. We validated our computational model predictions in vitro and in vivo in a preclinical model of Burkitt's lymphoma, with predictable evolutionary trajectories upon treatment. Next, we extended this methodology to study the effects of more complex tumor heterogeneity on combinatorial drug design, with similar conclusions. Sampling and statistical analyses over a range of tumor compositions can further inform effective drug combinations under some uncertainty in initial tumor heterogeneity. Moving beyond a model where we have control of initial tumor composition, we sought to examine collateral resistance and sensitivity during clonal evolution. Using a murine model of Ph+ acute lymphoblastic leukemia, we performed drug selection and pharmacological screen experiments. We observed important evolutionary processes of selection and drift in giving rise to resistance to clinically used BCR-ABL1 inhibitors. Remarkably, the resistant population also became hyper-sensitized to nonclassical BCR-ABL1 inhibitors at intermediate stages of the clonal evolution, in this so-called 'temporally collateral sensitivity'. Mathematical modeling and experimentation brought additional insight into the evolutionary dynamics and mechanism of action, with demonstrated in vivo efficacy. / by Boyang Zhao. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 114-124). / Protein aggregation underlies a number of human diseases. Most notably, it occurs widely in neurodegenerative diseases, including Alzheimer's and Parkinson's. At the molecular level, neurotoxicity is thought to originate from toxic gains of function in multimeric aggregates of proteins that are otherwise predominantly monomeric and disordered, fluctuating between a very large number of structurally dissimilar states on nano- and microsecond timescales. These proteins, termed Intrinsically Disordered Proteins (IDPs), are notoriously difficult to probe using traditional biophysical techniques. In order to obtain structural information pertaining to the aggregation of IDPs, it is often necessary to develop computational and modeling tools, both to leverage the full extent of the experimental data, and to generate testable predictions for future experiments. In this thesis, I present three separate computational studies studying the formation of multimeric aggregates in IDPs, spanning different aspects of the aggregation process, from early nucleation events to fibril elongation. In the first study, I present a conformational ensemble of a-synuclein, the culprit protein of Parkinson's disease, constructed using a Variational Bayesian Weighting algorithm in combination with NMR data collected by our collaborators. We find that the data fit a description in which the protein predominantly exists as a disordered monomer but contains small quantities of multimeric states containing both helical and strand-rich conformations. In the second study, I focus on the process of amyloid fibril elongation in the Amyloid-[beta] (A[beta]) peptide of Alzheimer's disease. I compute the free energy surface associated with the fibril elongation reaction, and find that elongation of both A[beta]40 and A[beta]42 experimental fibril structures occurs on a downhill free energy pathway, proceeding via an obligate, fibril-associated hairpin intermediate. The fibril-associated hairpin is significantly more stable (relative to the fibrillar, elongated state) in A[beta]42 compared with A[beta]40, suggesting a potential clinical target of interest. Finally, I present lengthy, all-atom molecular simulations that suggest that nucleation of the minimum aggregating fragment of c-synuclein proceeds via a helical intermediate, requiring a structural conversion into a strand-rich nucleating species via a stochastic process of individual helices unfolding and self-associating via backbone hydrogen bonds. / by Thomas Gurry. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2018. / 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. / High-throughput "omics" data are becoming commonplace in biological research and can provide important translational insights, but there is a need for well-crafted user-friendly tools for integrating and analyzing these data. In this thesis, I present versions 1 and 2 of Omics Integrator, a software tool designed to take advantage of the Prize-Collecting Steiner Forest algorithm from graph theory to provide users with high-confidence biological networks informed by their omics results. I show the results of using this flexible tool in several studies of Huntington's disease (HD), a fatal neurodegenerative disorder with no cure. By leveraging Omics Integrator on omics datasets from induced pluripotent stem cell (iPSC) derived models of HD, I discovered and highlighted several pathways that are altered in these cell line models, including neurodevelopment and glycolytic metabolism, which may lead to important therapeutic targets in the disease. Finally, I compare omics data derived from three iPSC-derived models differentiated towards a striatal neuron cell type using different protocols, and show that by performing this large comparative analysis I can implicate functions and pathways common to several models of HD. Future integrative and comparative studies like these will be made easier by the Omics Integrator tool. / by Amanda Joy Kedaigle. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2013. / Cataloged from PDF version of thesis. "September 2013." / Includes bibliographical references (pages 54-60). / DnaA is the bacterial replication initiator, which also functions as a transcription factor to regulate gene expression. In B. subtilis, DnaA has previously been shown to repress its own transcription and has also been implicated in directing part of the transcriptional response to replication stress. Because dnaA is essential, most of DnaA's potential effects on gene expression have been determined through indirect methods, which have implemented perturbations in replication and sequence analyses to predict direct effects of DnaA transcriptional regulation. Below, I take a more direct approach to assay DnaA's effect on gene expression and specific transcriptional regulatory networks by deleting dnaA in an oriN+ [delta]oriC strain background, which renders dnaA non-essential. Isogenic dnaA+ cells were constructed similarly and have dnaA constitutively expressed from an ectopic locus. In this background, DNA replication no longer depends on dnaA and is initiated instead by a plasmid replicon, oriN. The native origin of replication, oriC, is also deleted to eliminate differences in replication between [delta]dnaA and dnaA+ cells. Consequently, I can directly compare differences in gene expression due to the presence versus absence of dnaA. Deletion of dnaA results in approximately 463 significant differences in gene expression, most of which I show are due to DnaA direct activation of the gene sda. Many of these genes lie downstream of Sda activity and comprise several regulons, such as the Spo0A, AbrB, and SinR regulons. These regulons are known to become active during the transition from exponential growth to stationary phase. In addition to the many effects on gene expression, I show that deletion of dnaA results in lowered competence development. I also revisit the transcriptional response to replication stress and show that some of the previously predicted targets of DnaA respond to replication stress in a DnaA-dependent manner. Lastly, in collaboration with others, I have studied the relationship between a DnaA regulator, YabA and a nucleoid binding protein Rok. YabA and Rok associate at some of the same chromosomal regions, and at these regions YabA absolutely depends on Rok for its association. We are currently trying to understand the functional relationship between YabA, Rok, and DnaA. / by Tracy Washington. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Metabolic syndrome describes a complex set of obesity-related disorders that enhance diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase lb (PTPlb) deletion mice (L-PTPlb-/-) suggests that hepatic PTPlb inhibition would mitigate metabolic syndrome progression through amelioration of hepatic insulin resistance, endoplasmic reticulum stress, and whole-body lipid metabolism. However, the network alterations underlying these phenotypes are poorly understood. Mass spectrometry was used to quantitatively discover protein phosphotyrosine network changes in L-PTP lb-/- mice relative to control mice under both normal and high-fat diet conditions. A phosphosite set enrichment analysis was developed to identify numerous pathways exhibiting PTPlb- and diet-dependent phosphotyrosine regulation. Detection of PTP lb-dependent phosphotyrosine sites on lipid metabolic proteins initiated global lipidomics characterization of corresponding liver samples and revealed altered fatty acid and triglyceride metabolism in L-PTPlb-/- mice. Multivariate modeling techniques were developed to infer molecular dependencies between phosphosites and lipid metabolic changes, resulting in quantitatively predictive phenotypic models. / by Emily R. Miraldi. / Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references. / To better understand the tissue-specific regulation of chromatin state in cell-fate determination and development, we defined the tissue-specific expression of all 36 lysine methyltransferase (KMT) genes by endogenous mRNA detection in C. elegans. We found that most KMTs are expressed in only one or two tissues and that the germline is the tissue with the most general KMT expression. We discovered that the germline-expressed C. elegans ortholog of mammalian PRDM9, SET-1 7, promotes fertility through gene regulation in primary spermatocytes. SET-17 drives transcription of spermatocyte-specific genes from four genomic clusters to promote spermatid production. SET-1 7 is concentrated in stable, chromatin-associated nuclear foci at actively transcribed gene clusters, which we term spermatocyte transcription bodies. Our results identify the spatially restricted function of a PRDM9 ortholog in spermatocyte transcription and we propose that the spatial organization of chromatin factors might be a conserved mechanism in tissue-specific control of transcription. / by Christoph G. Engert. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 203-226). / Elevated expression of the c-Myc transcription factor occurs frequently in human cancers and is associated with tumor aggression and poor clinical outcome. However, the predominant mechanism by which c-Myc regulates global transcription in both healthy and tumor cells is poorly understood. In this thesis, I present evidence that c-Myc is a global regulator of RNA Polymerase II (RNA Pol II) transcriptional pause release. Transcriptional pausing occurs when additional regulatory steps are required to promote elongation of genes after transcription has initiated. Chapter 2 identifies transcriptional pausing as a general feature of transcription by RNA Pol II in mammalian cells. c-Myc is identified as having a major role in promoting release from pause at its target genes. Chapter 3 finds in tumor cells with elevated c-Myc, the transcription factor binds to promoters and enhancers of most actively transcribed genes. The predominant effect of c-Myc binding is to produce higher levels of transcription by promoting RNA Pol II transcriptional pause release. Thus, c-Myc accumulates in the promoter regions of active genes across the cancer cell genome and causes transcriptional amplification, producing increased levels of transcripts within the cells gene expression program. These results imply that transcriptional amplification can reduce rate-limiting constraints for tumor cell growth and proliferation. / by Charles Yang Lin. / Ph.D.