Absolute configuration and biosynthesis of pahayokolide A from Lyngbya sp. Strain 15-2 of the Florida Everglades

Pahayokolides A-D are cytotoxic cyclic polypeptides produced by the freshwater cyanobacterium Lyngbya sp. strain 15-2 that possess an unusual β-amino acid, 3-amino-2,5,7,8-tetrahydroxy-10-methylundecanoic acid (Athmu). The absolute configuration of pahayokolides A-D was determined using advanced Marfey’s method. It was also confirmed that a pendant N-acetyl- N-methyl leucine moiety in pahayokolide A was absent in pahayokolides B and pahayokolides C-D were conformers of pahayokolide A. Feeding experiments indicated that the biosynthesis of the Athmu sidechain arises from leucine or α-ketoisovalerate, however could not be further extended by three rounds of condensation with malonate units. Putative four peptide and one unique polyketide synthetases in Lyngbya sp. strain 15-2 were identified by using a PCR method and degenerate primers derived from conserved core sequences of known NRPSs and PKSs. Identification of one unique KS domain conflicted with the logic rule that the long side chain of Athmu was assembled by three rounds of ketide extensions if PKSs were involved. A gene cluster (pah) encoding a peptide synthetase putatively producing pahayokolide was cloned, partially sequenced and characterized. Seven modules of the non-ribosomal peptide synthetase (NRPS) were identified. Ten additional opening reading frames (ORFs) were found, responsible for peptide resistance, transport and degradation. Although the predicted substrate specificities of NRPS agreed with the structure of pahayokolide A partially, the disagreement could be explained. However, no PKS gene was found in the pah gene cluster.

Absolute Configuration and Biosynthesis of Pahayokolide A from Lyngbya sp. Strain 15-2 of the Florida Everglades

Pahayokolides A-D are cytotoxic cyclic polypeptides produced by the freshwater cyanobacterium Lyngbya sp. strain 15-2 that possess an unusual β-amino acid, 3-amino-2,5,7,8-tetrahydroxy-10-methylundecanoic acid (Athmu). The absolute configuration of pahayokolides A-D was determined using advanced Marfey’s method. It was also confirmed that a pendant N-acetyl-N-methyl leucine moiety in pahayokolide A was absent in pahayokolides B and pahayokolides C-D were conformers of pahayokolide A. Feeding experiments indicated that the biosynthesis of the Athmu sidechain arises from leucine or α-ketoisovalerate, however could not be further extended by three rounds of condensation with malonate units. Putative four peptide and one unique polyketide synthetases in Lyngbya sp. strain 15-2 were identified by using a PCR method and degenerate primers derived from conserved core sequences of known NRPSs and PKSs. Identification of one unique KS domain conflicted with the logic rule that the long side chain of Athmu was assembled by three rounds of ketide extensions if PKSs were involved. A gene cluster (pah) encoding a peptide synthetase putatively producing pahayokolide was cloned, partially sequenced and characterized. Seven modules of the non-ribosomal peptide synthetase (NRPS) were identified. Ten additional opening reading frames (ORFs) were found, responsible for peptide resistance, transport and degradation. Although the predicted substrate specificities of NRPS agreed with the structure of pahayokolide A partially, the disagreement could be explained. However, no PKS gene was found in the pah gene cluster.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

Integrated Bayesian network frameworks for modelling complex ecological issues

Ecological problems are typically multi faceted and need to be addressed from a scientific and a management perspective. There is a wealth of modelling and simulation software available, each designed to address a particular aspect of the issue of concern. Choosing the appropriate tool, making sense of the disparate outputs, and taking decisions when little or no empirical data is available, are everyday challenges facing the ecologist and environmental manager. Bayesian Networks provide a statistical modelling framework that enables analysis and integration of information in its own right as well as integration of a variety of models addressing different aspects of a common overall problem. There has been increased interest in the use of BNs to model environmental systems and issues of concern. However, the development of more sophisticated BNs, utilising dynamic and object oriented (OO) features, is still at the frontier of ecological research. Such features are particularly appealing in an ecological context, since the underlying facts are often spatial and temporal in nature. This thesis focuses on an integrated BN approach which facilitates OO modelling. Our research devises a new heuristic method, the Iterative Bayesian Network Development Cycle (IBNDC), for the development of BN models within a multi-field and multi-expert context. Expert elicitation is a popular method used to quantify BNs when data is sparse, but expert knowledge is abundant. The resulting BNs need to be substantiated and validated taking this uncertainty into account. Our research demonstrates the application of the IBNDC approach to support these aspects of BN modelling. The complex nature of environmental issues makes them ideal case studies for the proposed integrated approach to modelling. Moreover, they lend themselves to a series of integrated sub-networks describing different scientific components, combining scientific and management perspectives, or pooling similar contributions developed in different locations by different research groups. In southern Africa the two largest free-ranging cheetah (Acinonyx jubatus) populations are in Namibia and Botswana, where the majority of cheetahs are located outside protected areas. Consequently, cheetah conservation in these two countries is focussed primarily on the free-ranging populations as well as the mitigation of conflict between humans and cheetahs. In contrast, in neighbouring South Africa, the majority of cheetahs are found in fenced reserves. Nonetheless, conflict between humans and cheetahs remains an issue here. Conservation effort in South Africa is also focussed on managing the geographically isolated cheetah populations as one large meta-population. Relocation is one option among a suite of tools used to resolve human-cheetah conflict in southern Africa. Successfully relocating captured problem cheetahs, and maintaining a viable free-ranging cheetah population, are two environmental issues in cheetah conservation forming the first case study in this thesis. The second case study involves the initiation of blooms of Lyngbya majuscula, a blue-green algae, in Deception Bay, Australia. L. majuscula is a toxic algal bloom which has severe health, ecological and economic impacts on the community located in the vicinity of this algal bloom. Deception Bay is an important tourist destination with its proximity to Brisbane, Australia’s third largest city. Lyngbya is one of several algae considered to be a Harmful Algal Bloom (HAB). This group of algae includes other widespread blooms such as red tides. The occurrence of Lyngbya blooms is not a local phenomenon, but blooms of this toxic weed occur in coastal waters worldwide. With the increase in frequency and extent of these HAB blooms, it is important to gain a better understanding of the underlying factors contributing to the initiation and sustenance of these blooms. This knowledge will contribute to better management practices and the identification of those management actions which could prevent or diminish the severity of these blooms.

Mapping of shallow coastal groundwaters, their hydrology and environmental geochemistry : Pumicestone catchment, Southeast Queensland

Blooms of the toxic cyanobacterium majuscula Lyngbya in the coastal waters of southeast Queensland have caused adverse impacts on both environmental health and human health, and on local economies such as fishing and tourism. A number of studies have confirmed that the main limiting nutrients (“nutrients of concern”) that contribute to these blooms area Fe, DOC, N, P and also pH. This study is conducted to establish the distribution of these parameters in a typical southeast Queensland coastal setting. The study maps the geochemistry of shallow groundwater in the mainland Pumicestone catchment with an emphasis on the nutrients of concern to understand how these nutrients relate to aquifer materials, landuse and anthropogenic activities. The results of the study form a GIS information layer which will be incorporated into a larger GIS model being produced by Queensland Department of Environment and Resource Management (DERM) to support landuse management to avoid/minimize blooms of Lyngbya in Moreton Bay, southeast Queensland, and other similar settings. A total of 38 boreholes were established in the mainland Pumicestone region and four sampling rounds of groundwater carried out in both dry and wet conditions. These groundwater samples were measured in the field for physico-chemical parameters, and in the laboratory analyses for the nutrients of concern, and other major and minor ions. Aquifer materials were confirmed using the Geological Survey of Queensland digital geology map, and geomaterials were assigned to seven categories which are A (sands), B (silts, sandy silts), C (estuarine mud, silts), D (humid soils), E (alluvium), F (sandstone) and G (other bedrock). The results of the water chemistry were examined by use of the software package AquaChem/AqQA, and divided into six groundwater groups, based on groundwater chemical types and location of boreholes. The type of aquifer material and location, and proximity to waterways was found to be important because they affected physico-chemical properties and concentrations of nutrients of concern and dissolved ions. The analytical results showed that iron concentrations of shallow groundwaters were high due to acid sulfate soils, and also mud and silt, but were lower in sand materials. DOC concentrations of these shallow groundwaters in the sand material were high probably due to rapid infiltration. In addition, DOC concentrations in some boreholes were high because they were installed in organic rich wetlands. The pH values of boreholes were from acidic to near neutral; some boreholes with pH values were low (< 4), showing acid sulfate soils in these boreholes. Concentrations of total nitrogen and total phosphorus of groundwaters were generally low, and the main causes of elevated concentrations of total nitrogen and total phosphorus are largely due to animal and human wastes and tend to be found in localized source areas. Comparison of the relative percentage of nitrogen species (NH3/NH4< Org-N, NO3-N and NO2-N) demonstrated that they could be related to sources such as animal waste, residential and agricultural fertilizers, forest and vegetation, mixed residents and farms, and variable setting and vegetation covers. Total concentrations of dissolved ions in sampling round 3 (dry period) were higher than those in sampling round 2 (wet period) due to both evaporation of groundwater in the dry period and the dilution of rainfall in the wet period. This showed that the highest concentrations of nutrients of concern were due to acid sulfate soils, aquifer materials, landuse and anthropogenic activities and were typically in aquifer materials of E (alluvium) and C (estuarine muds) and locations of Burpengary, Caboolture, and Glass Mountain catchments.