Selected species in nature are able to tolerate prolonged periods of severe water stress. Survival of cellular desiccation in these anhydrobiotic organisms is conferred by a number of mechanisms including accumulation of stabilizing solutes, such as trehalose, and expression of Late Embryogenesis Abundant (LEA) proteins. An additional feature shared by some anhydrobiotic animals is the capacity to suppress mitochondrial oxidative phosphorylation in preparation for desiccation. These mechanisms improve the physiological robustness of cells to stress. The primary aim of this dissertation is to evaluate forms of metabolic preconditioning and to test the most propitious as a means to improve desiccation tolerance of mammalian cells. Several chemical agents, termed hypoxia mimetics, were evaluated in this study for utility in metabolic preconditioning. My results demonstrate that although each treatment increased Hypoxia Inducible Factor-1α (HIF-α) to varying degrees, none of them emulated every aspect of the hypoxia response in mammalian cells. A key aspect of the cellular hypoxia response is the phosphorylation and inhibition of pyruvate dehydrogenase (PDH). CoCl2 unexpectedly and strikingly decreased the phosphorylation of PDH. Neither desferrioxamine nor the prolyl-hydroxylase inhibitor FG-4592 caused an increase in PDH phosphorylation. Although dimethyloxalolglycine (DMOG) increased PDH phosphorylation, further examination of mitochondrial respiration showed that routine respiration was not reestablished 24 h after the treatment was removed. Based on these results hypoxia preconditioning was determined to be the most promising avenue for metabolic preconditioning. The effects of hypoxia preconditioning on desiccation tolerance were investigated with HepG2 cells that had been modified to accumulate trehalose and express AfrLEA2 from the brine shrimp Artemia franciscana. Spin-drying was used to quickly dehydrate the cells to a residual water content of 0.225 g H2O/g dry mass. Cells were then immediately rehydrated. The growth profiles of cells that received hypoxic preconditioning, with and without the nitric oxide donor MitoSNO, were compared to the growth of control cells without preconditioning. Results indicated that hypoxia preconditioning significantly increased cell proliferation compared to controls, and proliferation was further bolstered by the addition of MitoSNO. These findings support the concept that metabolic preconditioning can improve the biostability of mammalian cells after desiccation.

There is growing evidence for the regulatory roles of extracellular RNAs (exRNAs) in mediating cell-to-cell communication. To test whether exosomal RNA might also contribute to changes in gene expression in recipient cells, and to test whether mutant KRAS might regulate the composition of secreted RNAs, we comprehensively profiled small and long RNAs of cells and matched exosomes from isogenic colorectal cancer (CRC) cell lines differing only in KRAS status by RNA sequencing. We found that exosomal profiles are distinct from cellular profiles, and differentially enriched for specific small RNA, circular RNA (circRNA) and long RNA transcripts in exosomes dependent on KRAS status. Our small RNA analysis found that miR-10b was selectively increased in wild type KRAS exosomes while miR-100 was increased in mutant KRAS exosomes. In Transwell co-culture experiments, mutant KRAS donor cells conferred miRNA-mediated target repression in wild type KRAS recipient cells. In addition, we developed a bioinformatics pipeline to identify and evaluate circRNA candidates from RNA-Seq data. We found a significant down-regulation of circRNAs at a global level in mutant KRAS cells compared to wild type KRAS cells, indicating a widespread effect of mutant KRAS on circRNA abundance. Interestingly, circRNAs were more abundant in exosomes than cells, independent of KRAS status. Our long RNA analysis revealed that distinct RNAs species, such as pseudogene and antisense transcripts, are enriched in exosomes compared to cellular profiles. Additionally, specific mRNAs, such as Rab13, are upregulated in mutant KRAS exosomes. Here, we present comprehensive data to identify the broad and diverse classes of extracellular RNAs secreted in exosomes and we demonstrate that export of specific RNA can be altered by oncogenic KRAS signaling to potentially function beyond the cell of origin. Collectively, this will advance our understanding of exRNA biology in CRC and facilitate the development of potential exRNA biomarkers.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2019 / "DOCTOR OF PHILOSOPHY IN BIOLOGICAL ENGINEERING With a focus in Polymers and Soft Matter (PPSM)." Cataloged from PDF version of thesis. / Includes bibliographical references (pages 106-112). / Osteoarthritis is a debilitating joint disease that affects over 30 million people and has no disease-modifying therapies. The current standard of care for the disease is merely palliative until joint replacement is necessary. Disease-modifying osteoarthritis drugs have been tested in the clinic, but all have been unsuccessful in clinical trials. A key point of failure for several of these drugs has been inefficient and inadequate delivery to target cartilage cells. Cartilage is avascular and thus cannot be targeted efficiently through the systemic circulation. Due to the localized nature of osteoarthritis, direct injection of therapeutics into affected joints is an attractive solution to this problem. However, delivery via this approach remains impeded by rapid turnover of the synovial fluid within joints and the dense, highly charged nature of cartilage tissue. / To overcome this biological barrier, we took advantage of a recently demonstrated phenomenon in which positively charged nanomaterials electrostatically interact with anionic cartilage, both avoiding joint clearance and facilitating diffusion through the tissue in the process. This work describes two strategies using such polycationic materials to deliver insulin-like growth factor 1 (IGF-1), a promising anabolic growth factor for osteoarthritis that has known delivery challenges. The first approach used an electrostatic assembly of IGF-1, poly(L-glutamic acid), and poly(L-arginine) into a nanoscale complex coacervate, or nanoplex, for delivery of unmodified, bioactive IGF-1. The second approach involved a densely charged polyamidoamine (PAMAM) dendrimer, end-grafted with poly(ethylene glycol) (PEG) of various molecular weights at various % end group functionalization. / From this panel of nearly 50 PEGylated dendrimers, an optimally charged dendrimer was selected based on criteria of cartilage uptake and nontoxicity. The selected dendrimer was covalently modified with IGF-1. Both systems were tested to ensure that they could deliver bioactive IGF-1, penetrate human thickness cartilage tissue, extend joint residence time in vivo, and mitigate the progression of early traumatic osteoarthritis in rats. Both the nanoplex and optimally PEGylated dendrimer-IGF-1 achieved these goals, suggesting that polycationic nanocarriers could potentially improve pharmacokinetics and efficacy of disease-modifying osteoarthritis drugs in the clinic. / by Brett Charles Geiger. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2019 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 153-172). / Mathematical modeling is essential to the understanding and design of biological systems. Modeling uncertainty, which variously represents lack of data, variability between individuals and between different measurements of a single individual, ambiguity in the proper model form, and others, is essential to explaining the limitations of our understanding and constraining the confidence of our predictions. Current methods for modeling uncertainty provide a rich mathematical means of analyzing simple forms of uncertainty in self-contained models. However, real biological systems of interest exhibit many forms of uncertainty simultaneously and may require the composition of multiple levels of models to create useful predictions. I develop and test new methods for characterizing and propagating uncertainty through multi-level models in order to better make clinically relevant predictions. These methods are applied to three systems. / First, a selenium chemoprevention clinical trial's patients were modeled at the cellular metabolic, mutation accumulation, and cancer detection levels. Metabolite, demographic, and epidemiological data were integrated to produce predictions of prostate cancer risk and putative trial outcomes. The value of information - from doing experiments to reduce uncertainty in a targeted manner - was evaluated on trial design. Second, a population pharmacokinetics/ pharmacodynamics model was created to guide preclinical studies of antibody-drug conjugates targeting breast cancer. An optimal experimental design method was created to efficiently reduce uncertainty in estimates of drug-related parameters of interest. The contributions of inter-individual variability and parameter uncertainty are specially handled by sampling and propagating ensembles of models. / Third, a two-level drug efficacy and cellular dynamics model was created to analyze the efficacy of targeted liposomal-doxorubicin in multiple nucleolin-overexpressing cell lines. A single model topology (but with selected species- and cell line-independent parameters) adequately described the measured behavior in all cell lines. These were then used predict drug uptake and cell killing as a function of surface receptor density. In each system, a modeling framework that integrates data from multiple sources and different forms of uncertainty is applied to make predictions, quantify gaps in knowledge (and help fill them), and guide decision making in controlling clinically important outcomes. / by Kevin Shi. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering

In recent years, there has been a rise in antimicrobial-resistant bacteria caused by overdependence on, and misuse of, antibiotics. This has led to an increase in research for identifying alternatives to combat pathogens. One promising means of combating pathogenic bacteria, particularly for those residing in the gastrointestinal tract (GIT), is the use of probiotics. This thesis focuses on a potential probiotic strain Lactobacillus fermentum 3872, the genome sequence of which was circularised during the study, identifying genes that may contribute to probiotic activity. Several genes involved in GIT survival, such as acid symporters were discovered, along with genes that encode adhesion proteins such as those involved in mucus, fibronectin and collagen binding. The genes mentioned above may contribute to L. fermentum 3872 survivability within the GIT and have an antagonistic effect on enteric pathogens via competitive exclusion. Other interesting genes identified in L. fermentum 3872 were potentially involved in bacterial aggregation, exopolysaccharide and vitamin synthesis, along with four prophage encoding regions. Genes that encode a class III bacteriocin was also identified. An additional gene encoding a collagen binding protein (CBP) of a newly discovered plasmid pLF3872, was recognised. The chromosomal sequence also had a partial CBP encoding gene. pLF3872 has a toxin-antitoxin gene pair that ensures stable maintenance of the plasmid, along with conjugation-related genes. Functional analysis of the recombinant CBP via ELISA experiments found that the protein had the ability to bind to collagen I, a protein present on the epithelial lining of cells of the GIT. ELISA experiments also demonstrated that a common gastrointestinal pathogen, Campylobacter jejuni, can bind to collagen I in a concentration-dependent manner. In addition, mass spectrometry analysis identified that C. jejuni strains 11168H and 81-176 may utilise flagellar components (FlaA and FlaB) for adhesion. Furthermore, C. jejuni 11168H and 81-176 binding to collagen I was inhibited in the presence of either L. fermentum 3872 or CBP, thus reducing C. jejuni adherence via competitive exclusion. Using an in vitro assay, it was also demonstrated that L. fermentum 3872 cell-free supernatant could inhibit the growth of C. jejuni, due to the acidic environment brought about by L. fermentum 3872. During the completion of the genome sequence of L. fermentum 3872, comparison of various sequence assembly techniques which focused on the quality of the genome assembly was conducted. The results showed that further extension of the genome sequence during sequence assembly may lead to assembly errors when over-relying on a commonly-used sequence quality indicator, referred to as read mapping. It is suggested that care must also be taken when using long read technology to complete the genome sequence of a bacteria, as this may result in nucleotide sequence redundancies.

Colorectal cancer (CRC) is one of the most commonly diagnosed types of cancer in the developed countries and the incidence is rising in the developing regions. Chronic inflammation, which is propagated by overexpression of cyclooxygenase-2 (COX-2) and its major product prostaglandin E2 (PGE2), plays a key role in the development of CRC. Culinary herbs and spices (CHS) are rich in polyphenols, have a high anti-oxidant capacity and possess anti-inflammatory activity. It has been shown that CHS inhibit the growth of CRC cells, however, their anti-carcinogenic mechanisms are mainly unknown. Hence, the aim of this study was to identify the CHS that were most potent inhibiting the growth of CRC cells, and subsequently to elucidate their anti-carcinogenic mechanisms, in particular, focusing on COX-2, the Wnt/β-catenin signalling pathway, and proteins involved in apoptosis. Another goal was to investigate whether combining the CHS would result in synergistic effects on the above. This study demonstrated that CHS extracted in water/or ethanol and their combinations inhibited CRC cell growth. This study also revealed that the most potent CHS extracted in ethanol (turmeric (TE), bay leaf (BLE) and ginger (GE)) and combinations downregulated the expression of COX-2 and suppressed COX-2 activity by reducing PGE2 release; their effect was comparable to that of the selective COX-2 inhibitor Celecoxib (50 μM). These CHS also induced apoptosis in CRC cells by targeting several key proteins: p53, caspase-3, and PAPR. However, the CHS did not have an effect on Wnt signalling pathway, which partially could be due to insufficient treatment time. In conclusion, this study demonstrated that CHS and their combinations inhibited CRC cell growth, inhibited COX-2 expression and activity, and modulated several key molecules involved in the development of CRC. Based on these findings, CHS have the potential to be utilized for CRC chemoprevention and possibly be used as a complimentary treatment. However, in vivo studies are needed to establish the true potential of these foods.

'Psedomonas aeruginosa' is a prevalent nosocmial pathogen predominantly associated with infections in immune compromised individuals and long term colonisation and pathogenesis in the lungs of Cystic Fibrosis patients. With multi-drug resistant strains increasingly common, the discovery of novel targets for antimicrobial chemotherapy is of utmost importance and expansion of data on 'P. aeruginosa's' complex genome could facilitate this. Azoreductases are a group of enzymes mainly noted for their reductive capacity against azo and quinone compounds. Ubiquitous amongst many classes of organism including prokaryotes and eukaryotes, the primary physiological role of azoreductases remians unclear. This study characterises azoreductase-like enzymes from 'P. aeruginosa' in terms of biochemical properties, substrate specificity and structural analysis. The effect of these enzymes on bacterial physiology in 'P. aeruginosa' is also explored in relation to antibiotic susceptibility. Three azoreductase-like genes from 'P. aeruginosa' (pa1224, pa1225 and pa4975) were overexpressed in 'E. coli' strains following molecular cloning. Recombinant proteins were biochemically characterised by means of Thin Layer Chromatography, Differential Scanning Fluorimetry and ezymatic assays. All enzymes were noted to be selective for FAD as the flavin cofactor and NADPH as the preferred reductant. All three enzymes were confirmed as NAD(P)H dependent quinone oxidoreductases (NQOs) with PA1224 also catalysing reduction of the azo substrate methyl red, albeit at a rate an order of magnitude lower than that observed for the quinone compounds. The preferred flavin cofactor for four previously characterised azoreductase and NQO enzymes (PA2280, PA2580, PA1204 and PA0949) was also explored and PA2280 and PA0949 were observed to select for FMN while PA2580 and PA1204 were selective for FAD. The crystal structure of PA2580 was solved with the nicotinamide group of NADPH bound and was noted to form a homodimer with the same short flavodoxin-like fold as previously described for other members of this enzyme family. Complemented strains of azoreductase-like gene deletion mutants of 'P. aeruginosa' PAO1 were generated via molecular cloning and used to monitor the effects of these enzymes on antibiotic susceptibility. Antimicrobial sensitivity assays were carried out and although the knockout strains displayed increased sensitivity to fluroquinolones, they did not revert to the wild type phenotype upon reinsertion of the genes of interest. This study has for the first time characterised three new NQO's from 'P. aeruginosa' PAO1 and solved the crystal structure of an azoreductase/NQO with nicotinamide bound. With these findings and a library of complemented strains generated, this original study offers a platform for the continued research into the physiological role of these enzymes.

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. / Microbial ecology has benefited from the decreased cost and increased quality of next-generation DNA sequencing. In general, studies that use DNA sequencing are no longer limited by the sequencing itself but instead by the acquisition of the samples and by methods for analyzing and interpreting the resulting sequence data. In this thesis, I describe the results of three projects that address challenges to interpreting or acquiring sequence data. In the first project, I developed a method for analyzing the dynamics of the relative abundance of operational taxonomic units measured by next-generation amplicon sequencing in microbial ecology experiments without replication. In the second project, I and my co-author combined a taxonomic survey of a dimictic lake, an ecosystem-level biogeochemical model of microbial metabolisms in the lake, and the results of a single-cell genetic assay to infer the identity of taxonomically-diverse, putatively-syntrophic microbial consortia. In the third project, I and my co-author developed a model of differences in the efficacy that stool from different donors has when treating patients via fecal microbiota transplant. We use that model to compute statistical powers and to optimize clinical trial designs. Aside from contributing scientific conclusions about each system, these methods will also serve as a conceptual framework for future efforts to address challenges to the interpretation or acquisition of microbial ecology data. / by Scott Wilder Olesen. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 133-153). / Traumatic brain injury (TBI) is a significant cause of death and morbidity in both the civilian and military populations. The major causes of TBI, such as motor vehicle accidents, falls, sports concussions, and ballistic and explosive blast threats for military personnel, are well established and extensively characterized; however, there remains much to be learned about the specific mechanisms of damage leading to brain injury, especially at the cellular level. In order to understand how cells of the central nervous system (CNS) respond to mechanical insults and stimuli, a combined modeling/experimental approach was adopted. A computational framework was developed to accurately model how cells deform under various macroscopically imposed loading conditions. In addition, in vitro (cell culture) models were established to investigate damage responses to biologically relevant mechanical insults. In order to develop computational models of cell response to mechanical loading, it is essential to have accurate material properties for all cells of interest. In this work, the mechanical responses of neurons and astrocytes were quantified using atomic force microscopy (AFM) at three different loading rates and under relaxation to enable characterization of both the elastic and viscous components of the cell response. AFM data were used to calibrate an eight-parameter rheological model implemented in the framework of a commercial finite element package (Abaqus). Model parameters fit to the measured responses of neurons and astrocytes provide a quantitative measure of homogenized nonlinear viscoelastic properties for each cell type. In order to ensure that the measured responses could be considered representative of cell populations in their physiological environment, cells were also grown and tested on substrates of various stiffness, with the softest substrate mimicking the stiffness of brain tissue. Results of this study showed both the morphology and measured force response of astrocytes to be significantly affected by the stiffness of their substrate, with cells becoming increasingly rounded on soft substrates. Results of simulations suggested that changes in cell morphology were able to account for the observed changes in AFM force response, without significant changes to the cell material properties. In contrast, no significant changes in cell morphology were observed for neurons. These results highlight the importance of growing cells in a biologically relevant environment when studying mechanically mediated responses, such as TBI. To address this requirement, we developed two model systems with CNS cells grown in soft, 3D gels to investigate damage arising from dynamic compressive loading and from a shock pressure wave. These damage protocols, coupled with the single cell computational models, provide a new tool set for characterizing damage mechanisms in CNS cells and for studying TBI in highly controllable in vitro conditions. / by Kristin Briana Bernick. / Ph.D.

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). / 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. / by Alec A.K. Nielsen. / Ph. D.