Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.

No description available.

Legionella spp. can cause a life threatening form of pneumonia, which is observed world-wide. Outbreaks of the disease are, unfortunately, not a rare event, despite the introduction of government regulations which enforce the mandatory testing of cooling towers to ensure that they contain levels of the organism which are regarded as being within safe limits. Therefore, cooling towers should be monitored for Legionella spp. by using a biosensor. These could potentially save the community from a great deal of morbidity and mortality due to legionellosis. This study identified and investigated novel outer membrane proteins in L. pneumophila, and analysed their potential for use in a Legionella biosensor. A combination of bioinformatics and laboratory investigations was used to identify the Omp87, an outer membrane protein of L. pneumophila which had not been previously described in this organism. Sequence analysis of the protein showed that it shares similarity with various other members of the Omp85 protein family, including the D15 antigen of Haemophilus influenzae and the Oma87 of Pseudomonas aeruginosa. The omp87 gene of L. pneumophila was amplified and cloned, and was found to encode a protein of 786 amino acids, with a molecular weight of 87 kDa. Distribution studies revealed that the gene is present in most, but not all species and serogroups of Legionella. To investigate the function of the Omp87 protein in L. pneumophila, the omp87 gene was insertionally inactivated with the use of a kanamycin resistance gene. Amplicons of this disrupted gene were then introduced into L. pneumophila, and a double-cross over event occurred, integrating the inactivated gene into the genome of the organism. This resulted in non-viable cells, indicating that the gene is essential in L. pneumophila. The expression vector pRSETA was used to express the Omp87 protein in E. coli, and four truncates of varying sizes were designed, through the use of different PCR primers. Two of the protein truncates were then expressed and purified by gravity flow chromatography using columns packed with Ni-NTA sepharose resin. Following analysis of the proteins by SDS-PAGE and Western blotting, polyclonal antibodies were raised against the truncates. Distribution studies were then performed using the antiserum with different strains and species of Legionella. This study demonstrated that most serogroups of L. pneumophila, and most other Legionella species reacted with the polyclonal anti-Omp87 L. pneumophila antisera. Cross-reactivity was also observed with most other Legionella related organisms tested. The results presented in this thesis demonstrated that the Omp87 protein or the omp87 gene can be used to construct a biosensor. In addition other novel outer membrane proteins were identified which could also serve as potential targets for a biosensor. These biosensors will be able to identify Legionella spp. in water reservoirs and in clinical samples and hopefully reduce the number of infections and deaths caused by this organism.

In this study, Smiles?? sorptivity-diffusivity numerical analysis is demonstrated to offer a comprehensive description of dead-end constant-pressure compressible cake filtration for water treatment. In addition to providing an insight on filtration performance and cake behaviour in terms of cake hydraulic permeability and compressibility in good agreement with the results derived using Ruth??s conventional cake filtration theory, the sorptivity-diffusivity model can be used to gain further information on depth-dependent local cake properties and extend our knowledge on the effect of feed suspension conditions (including solution composition, coagulant dosage and mixing) on the characteristics of the particulate assemblages (including size, structure and strength). Feed suspension conditions and primary particle properties exert significant effect on the characteristics of particles in suspensions and the resultant particulate assemblages. In the non-coagulated latex systems, an increase in ionic strength resulted in a suppression of the electric double layer of latex particles as indicated by a significant drop in the zeta potential of the feed suspension which lead to a dramatic reduction in cake hydraulic permeability. In the non-coagulated montmorillonite systems, feed suspensions with high ionic strength (1 M Na+, 50 mM Ca2+ and 50 mM Fe2+) were associated with larger suspended solids which appeared to form assemblages with nematic structures that are denser yet more permeable when compared to those with low ionic strength (0.1 M Na+, 1 mM Ca2+ and 2 mM Fe2+) which appeared to form highly ??cross-linked?? voluminous honeycomb type gel of very low permeability. Pre-coagulation of latex and montmorillonite suspensions with Al-based coagulants (alum and ACH) both resulted in formation of very large flocs which subsequently formed highly permeable solid assemblages. In the latex systems, the ratio of optimal alum to ACH dose was approximately 5:1 on a total coagulant mass basis and 1.3:1 as Al while the ratio of optimal alum to ACH dose was as high as 22:1 on a total coagulant mass basis and 6:1 as Al in the montmorillonite systems. Although both alum and ACH resulted in comparable filtration performances, the distinction in Al concentration and results of local cake properties analysis indicated the presence of different cake structures presumably due to the formation of different Al species.

Enclosed reprint of author's article: `Outer membrane of Eschericherichia coli k-12`, published in J. of Bacteriology, 1976, v. 127, no. 3 / Bibliography: leaves 105-120 / 120 leaves, 3 leaves of plates : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, 1984

Typescript (photocopy) / 146 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.) Dept. of Microbiology, University of Adelaide, 1982

Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.

Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.

No description available.

Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.