Investigation of polyhydroxyalkanoate production by an activated sludge microbial consortium treating artificial dairy wastewater

Petrochemical plastics/polymers are a common feature of day to day living as they occur in packaging, furniture, mobile phones, computers, construction equipment etc. However, these materials are produced from non-renewable materials and are resistant to microbial degradation in the environment. Considerable research has therefore been carried out into the production of sustainable, biodegradable polymers, amenable to microbial catabolism to CO2 and H2O. A key group of microbial polyesters, widely considered as optimal replacement polymers, are the Polyhydroxyalkaonates (PHAs). Primary research in this area has focused on using recombinant pure cultures to optimise PHA yields, however, despite considerable success, the high costs of pure culture fermentation have thus far hindered the commercial viability of PHAs thus produced. In more recent years work has begun to focus on mixed cultures for the optimisation of PHA production, with waste incorporations offering optimal production cost reductions. The scale of dairy processing in Ireland, and the high organic load wastewaters generated, represent an excellent potential substrate for bioconversion to PHAs in a mixed culture system. The current study sought to investigate the potential for such bioconversion in a laboratory scale biological system and to establish key operational and microbial characteristics of same. Two sequencing batch reactors were set up and operated along the lines of an enhanced biological phosphate removal (EBPR) system, which has PHA accumulation as a key step within repeated rounds of anaerobic/aerobic cycling. Influents to the reactors varied only in the carbon sources provided. Reactor 1 received artificial wastewater with acetate alone, which is known to be readily converted to PHA in the anaerobic step of EBPR. Reactor 2 wastewater influent contained acetate and skim milk to imitate a dairy processing effluent. Chemical monitoring of nutrient remediation within the reactors as continuously applied and EBPR consistent performances observed. Qualitative analysis of the sludge was carried out using fluorescence microscopy with Nile Blue A lipophillic stain and PHA production was confirmed in both reactors. Quantitative analysis via HPLC detection of crotonic acid derivatives revealed the fluorescence to be short chain length Polyhydroxybutyrate, with biomass dry weight accumulations of 11% and 13% being observed in reactors 1 and 2, respectively. Gas Chromatography-Mass Spectrometry for medium chain length methyl ester derivatives revealed the presence of hydroxyoctanoic, -decanoic and -dodecanoic acids in reactor 1. Similar analyses in reactor 2 revealed monomers of 3-hydroxydodecenoic and 3-hydroxytetradecanoic acids. Investigation of the microbial ecology of both reactors as conducted in an attempt to identify key species potentially contributing to reactor performance. Culture dependent investigations indicated that quite different communities were present in both reactors. Reactor 1 isolates demonstrated the following species distributions Pseudomonas (82%), Delftia acidovorans (3%), Acinetobacter sp. (5%) Aminobacter sp., (3%) Bacillus sp. (3%), Thauera sp., (3%) and Cytophaga sp. (3%). Relative species distributions among reactor 2 profiled isolates were more evenly distributed between Pseudoxanthomonas (32%), Thauera sp (24%), Acinetobacter (24%), Citrobacter sp (8%), Lactococcus lactis (5%), Lysinibacillus (5%) and Elizabethkingia (2%). In both reactors Gammaproteobacteria dominated the cultured isolates. Culture independent 16S rRNA gene analyses revealed differing profiles for both reactors. Reactor 1 clone distribution was as follows; Zooglea resiniphila (83%), Zooglea oryzae (2%), Pedobacter composti (5%), Neissericeae sp. (2%) Rhodobacter sp. (2%), Runella defluvii (3%) and Streptococcus sp. (3%). RFLP based species distribution among the reactor 2 clones was as follows; Runella defluvii (50%), Zoogloea oryzae (20%), Flavobacterium sp. (9%), Simplicispira sp. (6%), Uncultured Sphingobacteria sp. (6%), Arcicella (6%) and Leadbetterella bysophila (3%). Betaproteobacteria dominated the 16S rRNA gene clones identified in both reactors. FISH analysis with Nile Blue dual staining resolved these divergent findings, identifying the Betaproteobacteria as dominant PHA accumulators within the reactor sludges, although species/strain specific allocations could not be made. GC analysis of the sludge had indicated the presence of both medium chain length as well short chain length PHAs accumulating in both reactors. In addition the cultured isolates from the reactors had been identified previously as mcl and scl PHA producers, respectively. Characterisations of the PHA monomer profiles of the individual isolates were therefore performed to screen for potential novel scl-mcl PHAs. Nitrogen limitation driven PHA accumulation in E2 minimal media revealed a greater propensity among isoates for mcl-pHA production. HPLC analysis indicated that PHB production was not a major feature of the reactor isolates and this was supported by the low presence of scl phaC1 genes among PCR screened isolates. A high percentage distribution of phaC2 mcl-PHA synthase genes was recorded, with the majority sharing high percentage homology with class II synthases from Pseudomonas sp. The common presence of a phaC2 homologue was not reflected in the production of a common polymer. Considerable variation was noted in both the monomer composition and ratios following GC analysis. While co-polymer production could not be demonstrated, potentially novel synthase substrate specificities were noted which could be exploited further in the future.

Application of mesoporous silica for the oral delivery of poorly water-soluble drugs

The objective of this thesis was to improve the dissolution rate of the poorly waters-soluble drug, fenofibrate by processing it with a high surface area carrier, mesoporous silica. The subsequent properties of the drug – silica composite were studied in terms of drug distribution within the silica matrix, solid state and release properties. Prior to commencing any experimental work, the properties of unprocessed mesoporous silica and fenofibrate were characterised (chapter 3), this allowed for comparison with the processed samples studied in later chapters. Fenofibrate was a highly stable, crystalline drug that did not adsorb moisture, even under long term accelerated storage conditions. It maintained its crystallinity even after SC-CO2 processing. Its dissolution rate was limited and dependent on the characteristics of the particular in vitro media studied. Mesoporous silica had a large surface area and mesopore volume and readily picked up moisture when stored under long term accelerated storage conditions (75% RH, 40 oC). It maintained its mesopore character after SC-CO2 processing. A variety of methods were employed to process fenofibrate with mesoporous silica including physical mixing, melt method, solvent impregnation and novel methods such as liquid and supercritical carbon dioxide (SC-CO2) (chapter 4). It was found that it was important to break down the fenofibrate particulate structure to a molecular state to enable drug molecules enter into the silica mesopores. While all processing methods led to some increase in fenofibrate release properties; the impregnation, liquid and SC-CO2 methods produced the most rapid release rates. SC-CO2 processing was further studied with a view to optimising the processing parameters to achieve the highest drug-loading efficiency possible (chapter 5). In this thesis, it was that SC-CO2 processing pressure had a bearing on drug-loading efficiency. Neither pressure, duration or depressurisation rate affected drug solid state or release properties. The amount of drug that could be loaded onto to the mesoporous silica successfully was also investigated at different ratios of drug mass to silica surface area under constant SC-CO2 conditions; as the drug – silica ratio increased, the drug-loading efficiency decreased, while there was no effect on drug solid state or release properties. The influence of the number of drug-loading steps was investigated (chapter 6) with a view to increasing the drug-loading efficiency. This multiple step approach did not yield an increase in drug-loading efficiency compared to the single step approach. It was also an objective in this chapter to understand how much drug could be loaded into silica mesopores; a method based on the known volume of the mesopores and true density of drug was investigated. However, this approach led to serious repercussions in terms of the subsequent solid state nature of the drug and its release performance; there was significant drug crystallinity and reduced release extent. The impact of in vitro release media on fenofibrate release was also studied (chapter 6). Here it was seen that media containing HCl led to reduced drug release over time compared to equivalent media not containing HCl. The key findings of this thesis are discussed in chapter 7 and included: 1. Drug – silica processing method strongly influenced drug distribution within the silica matrix, drug solid state and release. 2. The silica surface area and mesopore volume also influenced how much drug could be loaded. It was shown that SC-CO2 processing variables such as processing pressure (13.79 – 41.37 MPa), duration time (4 – 24 h) and depressurisation rate (rapid or controlled) did not influence the drug distribution within the SBA- 15 matrix, drug solid state form or release. Possible avenues of research to be considered going forward include the development and application of high resolution imaging techniques to visualise drug molecules within the silica mesopores. Also, the issues surrounding SBA-15 usage in a pharmaceutical manufacturing environment should be addressed.

Reasoning with sorted-pareto dominance and other qualitative and partially ordered preferences in soft constraints

In decision making problems where we need to choose a particular decision or alternative from a set of possible choices, we often have some preferences which determine if we prefer one decision over another. When these preferences give us an ordering on the decisions that is complete, then it is easy to choose the best or one of the best decisions. However it often occurs that the preferences relation is partially ordered, and we have no best decision. In this thesis, we look at what happens when we have such a partial order over a set of decisions, in particular when we have multiple orderings on a set of decisions, and we present a framework for qualitative decision making. We look at the different natural notions of optimal decision that occur in this framework, which gives us different optimality classes, and we examine the relationships between these classes. We then look in particular at a qualitative preference relation called Sorted-Pareto Dominance, which is an extension of Pareto Dominance, and we give a semantics for this relation as one that is compatible with any order-preserving mapping of an ordinal preference scale to a numerical one. We apply Sorted-Pareto dominance to a Soft Constraints setting, where we solve problems in which the soft constraints associate qualitative preferences to decisions in a decision problem. We also examine the Sorted-Pareto dominance relation in the context of our qualitative decision making framework, looking at the relevant optimality classes for the Sorted-Pareto case, which gives us classes of decisions that are necessarily optimal, and optimal for some choice of mapping of an ordinal scale to a quantitative one. We provide some empirical analysis of Sorted-Pareto constraints problems and examine the optimality classes that result.