http://hdl.handle.net/1721.1/7622 Sun, 09 Jul 2017 21:33:57 GMT 2017-07-09T21:33:57Z http://hdl.handle.net/1721.1/109668 Molecular pathway analysis and therapeutics development in post-traumatic osteoarthritis Wang, Yang, Ph. D. Massachusetts Institute of Technology Post traumatic osteoarthritis (PTOA) refers to the progressive degradation of cartilage often triggered by a traumatic joint injury, such as a tear of the meniscus or anterior cruciate ligament (ACL). Such impact injuries lead to elevated levels of inflammatory cytokines in the synovial fluid of the joint, including IL-1, IL-6, and TNFa. In turn, these cytokines cause decreased matrix synthesis by chondrocytes and contribute to reprogramming of chondrocytes and synovial cells to increase release of matrix proteases. PTOA accounts for 12% of the OA population and typically affects younger individuals. The first part of this thesis focuses on developing a combination therapeutic which can address multiple aspects of cartilage degradation associated with the pathogenic responses to joint injury. We studied the combined use of insulin-like growth factor 1 (IGF-1) and dexamethasone (Dex) to block multiple degradative effects of cytokine challenge to articular cartilage. We found that in young bovine cartilage, the combination of IGF- 1 and Dex significantly inhibited the loss of sulfated glycosaminoglycans (sGAG) and collagen induced by IL-I. rescued the suppressed matrix biosynthesis, and inhibited the loss of chondrocyte viability caused by iL- 1 treatment. In adult human cartilage, only IGF- 1 rescued matrix biosynthesis and only Dex inhibited sGAG loss and improved cell viability. Thus, the combination of IGF-1+Dex together showed combined beneficial effects in human cartilage. Our findings suggest that the combination of IGF-I and Dex has greater beneficial effects than either molecule alone in preventing cytokine-mediated cartilage degradation in adult human and young bovine cartilage. In the second part of this thesis, a global phosphoproteomics approach was employed to determine the pathways that are activated upon cytokine challenge of adult human chondrocytes. We identified key regulatory kinases, p38, JNKI/2, ERKI/2, ERK5, JAK2, and STAT3 that were upregulated in phosphorylation as a result of inflammatory cytokine treatment. In addition, we identified 417 phosphopeptides with MAPK substrate motif that were more than 4 times upregulated in response to cytokine treatment. Using inhibitors against the key kinases, it was shown that P38, JNK1/2, ERK5 played important roles in cytokine induced cell death in bovine and human cartilage, while inhibition of JNK1/2 and ERK5 had the anti-catabolic effect of reducing GAG loss from cartilage matrix. In addition, JNK inhibition sensitized chondrocytes to IGF-1 stimulation in young bovine cartilage. These result indicate that kinase activity plays an essential role in cytokine induced cartilage catabolism and that kinase inhibitors have therapeutic potential in preventing cartilage degeneration. The third and final part of this work examined the release of matrix molecules upon mechanical injurious compression and/or cytokine treatment in long term culture to identify potential biomarkers of cartilage degeneration. A quantitative mass spectrometry approach was used to characterize the kinetics of aggrecan and collagen degradation. Although mechanical injury alone does not lead to a substantial increase in matrix degradation, mechanical injury can accelerate cytokine-induced matrix degradation and release. Additionally, we found that a collagen type III neo-epitope could be a potential biomarker for cartilage degradation. A neoepitope of cartilage oligomeric matrix protein (COMP), which was identified in the synovial fluid of acute injury patients, was also found in our ex vivo explant injury model. This makes our model physiologically relevant and it can be a valuable system for determining the effects of potential drug treatment on matrix degradation. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, February 2017.; Cataloged from PDF version of thesis.; Includes bibliographical references. Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/1721.1/109668 2017-01-01T00:00:00Z http://hdl.handle.net/1721.1/109667 Computational engineering of small molecules to treat infectious diseases Srinivas, Raja R Rational drug design of small molecules has led to the development of robust therapeutics that are currently used in the clinic. However, key challenges remain in designing drugs against infectious disease targets that are susceptible to mutation. To achieve full clinical efficacy against rapidly-mutating targets, new methods must be developed for designing drugs. In this thesis, we utilize a three pronged approach for rational ligand design by developing methods, analyzing existing experimental data, and designing novel therapeutics. On-target mutations in infectious diseases often render inhibitors ineffective and are one of the key clinical failures of current therapies. We use HIV protease as a model system to understand mutation resistance. HIV protease substrates are unaffected or only moderately affected by resistance mutations that greatly decrease inhibitor binding. This idea has led to the design of broadly binding inhibitors using substrate mimicry. This is achieved by constraining inhibitors to bind within the consensus substrate volume, which we term the "substrate envelope". However, while the substrate envelope has been relatively successful, some inhibitors that are designed based on this model are sensitive to mutants. We performed a detailed biophysical binding energy decomposition of a flat and susceptible binder pair and found that the susceptible inhibitor forms stronger interactions with key residues. These residues are entirely characterized by examining known resistant mutants to approved HIV protease inhibitors. To generalize our findings, we cross-validate on a set of ten HIV protease inhibitors with previously measured sensitivity. We find that interaction energy successfully classifies susceptible and flat inhibitors. Based on these results, we extend the current design paradigm. We develop a methodology to minimize extraneous contacts with the active site and express it as an appropriate cost function, which is then minimized. We then implement this design scheme for HIV protease, yielding both flat and susceptible binders. Next, we apply rational drug design principles to other infectious disease targets. We first focus on the tuberculosis specific CIpP1P2 peptidase to optimize the antibiotic, acyl depsipeptides (ADEPs). We use component analysis to understand the biophysics of ADEP binding to the active site. We then design a series of analogs resulting in a two-fold affinity improvement along with enhanced peptidase activity. We also develop new methods to improve an anti-fungal for the treatment of Candida albicans. We use molecular docking to predict a binding mode for the lead compound and then account for receptor plasticity by performing molecular dynamics simulations. We use this improved receptor model to design novel analogs that are predicted to bind better than the parent compound. Lastly, we focus on disease diagnosis by developing a novel paradigm for MRI contrast agent design. We first integrate the governing thermodynamics and relevant parameters that influence imaging efficacy to develop an integrated workflow for contrast agent design. We then apply our methodology to the DOTA system and successfully explain differential activity of designed analogs. Put together, we demonstrate the power of rational design in various relevant biological contexts. Overall, this thesis presents new techniques, analysis, and applications of rational design to address unmet clinical problems. Work from this thesis accelerates the field of computational drug design, which has implications in many uncured diseases and diagnostics. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017.; Page 193 blank. Cataloged from PDF version of thesis.; Includes bibliographical references (pages 185-192). Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/1721.1/109667 2017-01-01T00:00:00Z http://hdl.handle.net/1721.1/109666 Investigation into the role of DNA damage and repair during influenza infection and inflammation Parrish, Marcus Curtis The DNA in every cell accrues nearly 100,000 lesions daily from both endogenous and exogenous sources. The accumulated damage, e.g. strand breaks and base lesions, can lead to mutations, cell death, and cancer if not repaired efficiently. To protect genome integrity, organisms have evolved multiple DNA repair processes. A deeper comprehension of DNA damage and repair during disease pathogenesis can aid the development of novel therapeutics to reduce the damage and ameliorate the disease. Here, we studied DNA damage and repair in two inflammatory contexts. First, we investigated the role of DNA damage and repair during influenza infection, a common viral respiratory disease with an active inflammatory response. Second, we examined the effects of S-nitrosation, a post-translational modification that is common in inflammatory regions, on repair of alkylation damage. Influenza induces an excessive inflammatory response in the host and a reduction in inflammation reduces morbidity. While inflammation can cause DNA damage and induce DNA repair in other inflammatory contexts, there has been minimal analysis on the existence and function of DNA damage and repair during influenza infection. Utilizing immuno-fluorescent analysis of double strand break markers, we observed an increase in strand breaks both in vitro and in vivo. Influenza infected mice also displayed a significant increase in homologous recombination (HR) gene and protein expression during the recovery phase of infection in multiple virus and mouse backgrounds. Moreover, influenza infected mice deficient in DNA repair proteins AAG, ALKBH2, and ALKBH3, displayed increased morbidity and HR protein expression when compared to wild type. Together, these results raise the possibility of a role for DNA repair and more specifically HR during influenza infection. To study the effects of inflammation on DNA repair protein function, we analyzed the capacity of cells treated with S-nitrosoglutathione (GSNO), a nitrosating agent, to repair alkylation damage. GSNO-exposed cells displayed dysregulation in the activities base excision repair (BER) proteins. Following challenge with an alkylating agent, GSNO-exposed cells had an increase in repair intermediates and reduced viability, suggesting that GSNO exposure inhibits BER completion. The knowledge gained from these studies lays the groundwork for new prevention strategies and novel therapeutics. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017.; Cataloged from PDF version of thesis.; Includes bibliographical references. Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/1721.1/109666 2017-01-01T00:00:00Z http://hdl.handle.net/1721.1/109665 Biomolecular and computational frameworks for genetic circuit design Nielsen, Alec A. K Living cells naturally use gene regulatory networks termed "genetic circuits" to exhibit complex behaviors such as signal processing, decision-making, and spatial organization. The ability to rationally engineer genetic circuits has applications in several biotechnology areas including therapeutics, agriculture, and materials. However, genetic circuit construction has traditionally been time- and labor-intensive; tuning regulator expression often requires manual trial-and-error, and the results frequently function incorrectly. To improve the reliability and pace of genetic circuit engineering, we have developed biomolecular and computational frameworks for designing genetic circuits. A scalable biomolecular platform is a prerequisite for genetic circuits design. In this thesis, we explore TetR-family repressors and the CRISPRi system as candidates. First, we applied 'part mining' to build a library of TetR-family repressors gleaned from prokaryotic genomes. A subset were used to build synthetic 'NOT gates' for use in genetic circuits. Second, we tested catalytically-inactive dCas9, which employs small guide RNAs (sgRNAs) to repress genetic loci via the programmability of RNA:DNA base pairing. To this end, we use dCas9 and synthetic sgRNAs to build transcriptional logic gates with high on-target repression and negligible cross-talk, and connected them to perform computation in living cells. We further demonstrate that a synthetic circuit can directly interface a native E. coli regulatory network. To accelerate the design of circuits that employ these biomolecular platforms, we created a software design tool called Cello, in which a user writes a high-level functional specification that is automatically compiled to a DNA sequence. Algorithms first construct a circuit diagram, then assign and connect genetic "gates", and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design the largest library of genetic circuits to date, where each DNA sequence was built as predicted by the software with no additional tuning. Across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decisionmaking, control, sensing, or spatial organization. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017.; Page 322 blank. Cataloged from PDF version of thesis.; Includes bibliographical references (pages 295-321). Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/1721.1/109665 2017-01-01T00:00:00Z