The Role of Exopolyphosphatase in Neisseria meningitidis Infection

The development of vaccines against serogroup B Neisseria meningitidis to reduce the morbidity and mortality of meningococcal disease is a major public health priority. We developed a novel genetic screen for immunogens present on the bacterial surface using human immune sera with bactericidal activity. We found that two mutants lacking nmb1467 survived in high concentrations of sera from two patients, while the wild-type strain was killed. Biochemical assays using purified recombinant NMB1467 indicated that nmb1467 encodes an exopolyphosphatase (PPX) with the ability to hydrolyse inorganic polyphosphate (poly P). In addition, we demonstrated that the Δppx mutant has at least 2-fold more poly P than the wild-type strain. Therefore, we designated NMB1467 as PPX. We showed that N. meningitidis mutant lacking the ppx had an increased resistance against normal human complement system. Substitution of the glutamic acid at residue 147 of PPX with an alanine significantly reduced the enzymatic activity in vitro, and contributed to increased level of poly P in N. meningitidis and the resistance of bacteria against the complement-mediated killing. Levels of polysaccharide capsule and lipopolysaccharide (LPS) sialylation, two important virulence factors, were not affected by the loss of ppx in N. meningitidis. Using flow cytometry, we demonstrated that binding of factor H (fH), the negative regulator of the alternative pathway of complement activation, to the bacterial surface was increased in the strain lacking PPX. By Western blot analysis, we did not detect a significant change in the expression of the fH receptor, indicting another mechanism is involved in the fH binding to the bacterial surface and resistance of bacteria against complement-mediated killing

Optimization of Bioprocesses for multiple objectives

Ph.DDOCTOR OF PHILOSOPH

The elucidation of metabolic pathways and their improvements using stable optimization of large-scale kinetic models of cellular systems

Metabolic engineering of cellular systems to maximize reaction fluxes or metabolite concentrations still presents a significant challenge by encountering unpredictable instabilities that can be caused by simultaneous or consecutive enhancements of many reaction steps. It can therefore be important to select carefully small subsets of key enzymes for their subsequent stable modification compatible with cell physiology. To address this important problem, we introduce a general mixed integer non-linear problem (MINLP) formulation to compute automatically which enzyme levels should be modulated and which enzyme regulatory structures should be altered to achieve the given optimization goal using non-linear kinetic models of relevant cellular systems. The developed MINLP formulation directly employs a stability analysis constraint and also includes non-linear biophysical constraints to describe homeostasis conditions for metabolite concentrations and protein machinery without any preliminary model simplification (e.g. linlog kinetics approximation). The framework is demonstrated on a well-established large-scale kinetic model of the Escherichia coli central metabolism used for the optimization of the glucose uptake through the phosphotransferase transport system (PTS) and serine biosynthesis. Computational results show that substantial stable improvements can be predicted by manipulating only small subsets of enzyme levels and regulatory structures. This means that while more efforts can be required to elucidate larger stable optimal enzyme level/regulation choices, no further significant increase in the optimized fluxes can be obtained and, therefore, such choices may not be worth the effort due to the potential loss of stability properties. The source for instability through saddle-node and Hopf bifurcations is identified, and all results are contrasted with predictions from metabolic control analysis

Experiment design for systems biology

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 219-233).Mechanism-based chemical kinetic models are increasingly being used to describe biological signaling. Such models serve to encapsulate current understanding of pathways and to enable insight into complex biological processes. Despite the growing interest in these models, a number of challenges frustrate the construction of high-quality models. First, the chemical reactions that control biochemical processes are only partially known, and multiple, mechanistically distinct models often fit all of the available data and known chemistry. We address this by providing methods for designing dynamic stimuli that can distinguish among models with different reaction mechanisms in stimulus-response experiments. We evaluated our method on models of antibody-ligand binding, mitogen-activated protein kinase phosphorylation and de-phosphorylation, and larger models of the epidermal growth factor receptor (EGFR) pathway. Inspired by these computational results, we tested the idea that pulses of EGF could help elucidate the relative contribution of different feedback loops within the EGFR network. These experimental results suggest that models from the literature do not accurately represent the relative strength of the various feedback loops in this pathway. In particular, we observed that the endocytosis and feedback loop was less strong than predicted by models, and that other feedback mechanisms were likely necessary to deactivate ERK after EGF stimulation. Second, chemical kinetic models contain many unknown parameters, at least some of which must be estimated by fitting to time-course data. We examined this question in the context of a pathway model of EGF and neuronal growth factor (NGF) signaling. Computationally, we generated a palette of experimental perturbation data that included different doses of EGF and NGF as well as single and multiple gene knockdowns and overexpressions. While no single experiment could accurately estimate all of the parameters, we identified a set of five complementary experiments that could. These results suggest that there is reason to be optimistic about the prospects for parameter estimation in even large models. Third, there is no standard formulation for chemical kinetic models of biological signaling. We propose a general and concise formulation of mass action kinetics based on sparse matrices and Kronecker products. This formulation allows any mass action model and its partial derivatives to be represented by simple matrix equations, which enabled straightforward application of several numerical methods. We show that models that use other rate laws such as MichaelisMenten can be converted to our formulation. We demonstrate this by converting a model of Escherichia coli central carbon metabolism to use only mass action kinetics. The dynamics of the new model are similar to the original model. However, we argue that because our model is based on fewer approximations it has the potential to be more accurate over a wider range of conditions. Taken together, the work presented here demonstrates that experimental design methodology can be successfully used to improve the quality of mechanism-based chemical kinetic models.by Joshua Farley Apgar.Ph.D

Adaptive filtering applications to satellite navigation

PhDDifferential Global Navigation Satellite Systems employ the extended Kalman filter to estimate the reference position error. High accuracy integrated navigation systems have the ability to mix traditional inertial sensor outputs with navigation satellite based position information and can be used to develop high accuracy landing systems for aircraft. This thesis considers a host of estimation problems associated with aircraft navigation systems that currently rely on the extended Kalman filter and proposes to use a nonlinear estimation algorithm, the unscented Kalman filter (UKF) that does not rely on Jacobian linearisation. The objective is to develop high accuracy positioning algorithms to facilitate the use of GNSS or DGNSS for aircraft landing. Firstly, the position error in a typical satellite navigation problem depends on the accuracy of the orbital ephemeris. The thesis presents results for the prediction of the orbital ephemeris from a customised navigation satellite receiver's data message. The SDP4/SDP8 algorithms and suitable noise models are used to establish the measured data. Secondly, the differential station common mode position error not including the contribution due to errors in the ephemeris is usually estimated by employing an EKF. The thesis then considers the application of the UKF to the mixing problem, so as to facilitate the mixing of measurements made by either a GNSS or a DGNSS and a variety of low cost or high-precision INS sensors. Precise, adaptive UKFs and a suitable nonlinear propagation method are used to estimate the orbit ephemeris and the differential position and the navigation filter mixing errors. The results indicate the method is particularly suitable for estimating the orbit ephemeris of navigation satellites and the differential position and navigation filter mixing errors, thus facilitating interoperable DGNSS operation for aircraft landing

Proteome-Wide Analyis of Chaperonin-Dependent Protein Folding in Escherichia coli

In Escherichia coli, the cylindrical chaperonin GroEL and its cofactor GroES promote the folding of a fraction of newly synthesized polypeptide chains by acting as an Anfinsen cage. GroEL recognizes substrate proteins with its apical domains of the tetradecameric structure. Exposed hydrophobic side chains in non-native proteins interact with GroEL and bound substrates are subsequently encapsulated under the GroES lid, where they can fold in a protected environment. Despite the detailed knowledge about structural and mechanistic features of GroEL and GroES, little is known about its genuine in vivo substrate proteins. Here, the nearly complete set of GroEL interacting proteins in vivo was identified and quantified by an approach using affinity chromatography for the isolation of GroEL/GroES/substrate complexes and subsequent analysis by mass spectrometric methods. GroEL substrate proteins were analyzed with respect to their fold types and functional classes, revealing a preference for proteins which fold into the versatile TIM barrel fold to interact with GroEL. Further in vivo and in vitro experiments with individual proteins identified as GroEL substrates verified the data obtained by the proteomic approach and allowed conclusions on the usage of the other main chaperone system in E. coli: DnaK/DnaJ/GrpE. Taken together, the results culminated in the classification of GroEL interacting proteins according to their dependence on chaperones for folding. Class I proteins are largely independent of chaperones but their folding yield can be increased by chaperone interaction. Class II proteins do not refold efficiently in the absence of chaperones in vitro, but can utilize either the DnaK or the GroEL/GroES systems for folding. Class III substrates are fully dependent on GroEL. DnaK can bind class III proteins and thus prevent their aggregation, but folding is achieved only upon transfer to GroEL

Role of lysX gene from Mycobacterium avium hominissuis in metabolism and host-cell interaction

Non-tuberculous Mycobacteria (NTM) are an important but often overlooked group of pathogens, especially important in the immunocompromised and patients with pre-existing pulmonary disease. Their condition of environmental bacteria enables them to persist in a wide range of habitats. Although multiple virulence factors of M. avium have been proposed, the virulence strategies of M. avium are still not fully clear including the mechanisms allowing this environmental bacterium to cause chronic infections in humans. Lysyl-phosphatidylglycerol, a component of the mycobacterial membrane, contributes to the resistance towards cationic antimicrobial peptides. Its production is catalyzed by LysX, a bifunctional protein with lysyl transferase and lysyl transfer RNA synthetase activity. The main objective of the doctoral project was to characterize the role of the lysX gene for growth and host cell interaction of M. avium subsp. hominissuis (MAH). A considerable impact of the gene lysX on the different functional pathways of M. avium in particular the central carbon metabolism was demonstrated. Proteomics studies revealed that the lysX mutation led to a metabolic shift which enhanced the suitability of the bacteria to be adaptive towards the living conditions inside host cells. In addition, the mutation also caused an upregulation of lipid synthesis genes which resulted in an intracellular lipid accumulation. The measure of mycobacterial virulence has been stated to depend on the ability of the bacteria to invade, persist and replicate within the hostile macrophage environment. In accordance the lysX mutant already displayed a hypervirulent phenotype, exhibiting an excessive intracellular growth in in-vitro (human blood monocytes) and invivo (Galleria mellonella). Additionally, the lysX mutation also resulted in an hyperinflammatory behaviour (increased secretion of cytokines and increased MGC formation), which also indicates a novel functional role of lysX in regards to virulence in M. avium species. Interestingly, the results with respect to the host-pathogen interaction of an MAH with a deficient lysX gene obtained in this study contrasted with the results obtained by other authors with a lysX mutant from MTB. This makes it more interesting to further explore on the differential survival strategies of mycobacterial species. The lysX gene may also be instrumental in identifying factors involved in molecular pathogenesis of different mycobacterial diseases, thus benefitting the health systems for developing strategies to combat these hardy pathogens