Climate-Affected Australian Tropical Montane Cloud Forest Plants: Metabolomic Profiles, Isolated Phytochemicals, and Bioactivities

The Australian Wet Tropics World Heritage Area (WTWHA) in northeast Queensland is home to approximately 18 percent of the nation's total vascular plant species. Over the past century, human activity and industrial development have caused global climate changes, posing a severe and irreversible danger to the entire land-based ecosystem, and the WTWHA is no exception. The current average annual temperature of WTWHA in northeast Queensland is 24 °C. However, in the coming years (by 2030), the average annual temperature increase is estimated to be between 0.5 and 1.4 °C compared to the climate observed between 1986 and 2005. Looking further ahead to 2070, the anticipated temperature rise is projected to be between 1.0 and 3.2 °C, with the exact range depending on future emissions. We identified 84 plant species, endemic to tropical montane cloud forests (TMCF) within the WTWHA, which are already experiencing climate change threats. Some of these plants are used in herbal medicines. This study comprehensively reviewed the metabolomics studies conducted on these 84 plant species until now toward understanding their physiological and metabolomics responses to global climate change. This review also discusses the following: (i) recent developments in plant metabolomics studies that can be applied to study and better understand the interactions of wet tropics plants with climatic stress, (ii) medicinal plants and isolated phytochemicals with structural diversity, and (iii) reported biological activities of crude extracts and isolated compounds.

Using a Bayesian network to clarify areas requiring research in a host-pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease-driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host-pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious-disease systems.

Population genetic analysis of a medicinally significant Australian rainforest tree, Fontainea picrosperma C.T. White (Euphorbiaceae): biogeographic patterns and implications for species domestication and plantation establishment

BACKGROUND

Fontainea picrosperma, a subcanopy tree endemic to the rainforests of northeastern Australia, is of medicinal significance following the discovery of the novel anti-cancer natural product, EBC-46. Laboratory synthesis of EBC-46 is unlikely to be commercially feasible and consequently production of the molecule is via isolation from F. picrosperma grown in plantations. Successful domestication and plantation production requires an intimate knowledge of a taxon's life-history attributes and genetic architecture, not only to ensure the maximum capture of genetic diversity from wild source populations, but also to minimise the risk of a detrimental loss in genetic diversity via founder effects during subsequent breeding programs designed to enhance commercially significant agronomic traits.

RESULTS

Here we report the use of eleven microsatellite loci (PIC = 0.429; P ID  = 1.72 × 10(-6)) to investigate the partitioning of genetic diversity within and among seven natural populations of F. picrosperma. Genetic variation among individuals and within populations was found to be relatively low (A = 2.831; H E  = 0.407), although there was marked differentiation among populations (PhiPT = 0.248). Bayesian, UPGMA and principal coordinates analyses detected three main genotypic clusters (K = 3), which were present at all seven populations. Despite low levels of historical gene flow (N m  = 1.382), inbreeding was negligible (F = -0.003); presumably due to the taxon's dioecious breeding system.

CONCLUSION

The data suggests that F. picrosperma was previously more continuously distributed, but that rainforest contraction and expansion in response to glacial-interglacial cycles, together with significant anthropogenic effects have resulted in significant fragmentation. This research provides important tools to support plantation establishment, selection and genetic improvement of this medicinally significant Australian rainforest species.

A Survey of Zoonotic Pathogens Carried by Non-Indigenous Rodents at the Interface of the Wet Tropics of North Queensland, Australia

In 1964, Brucella was isolated from rodents trapped in Wooroonooran National Park (WNP), in Northern Queensland, Australia. Genotyping of bacterial isolates in 2008 determined that they were a novel Brucella species. This study attempted to reisolate this species of Brucella from rodents living in the boundary area adjacent to WNP and to establish which endo- and ecto-parasites and bacterial agents were being carried by non-indigenous rodents at this interface. Seventy non-indigenous rodents were trapped [Mus musculus (52), Rattus rattus (17) and Rattus norvegicus (1)], euthanized and sampled on four properties adjacent to the WNP in July 2012. Organ pools were screened by culture for Salmonella, Leptospira and Brucella species, real-time PCR for Coxiella burnetii and conventional PCR for Leptospira. Collected ecto- and endo-parasites were identified using morphological criteria. The percentage of rodents carrying pathogens were Leptospira (40%), Salmonella choleraesuis ssp. arizonae (14.29%), ectoparasites (21.42%) and endoparasites (87%). Brucella and C. burnetii were not identified, and it was concluded that their prevalences were below 12%. Two rodent-specific helminthic species, namely Syphacia obvelata (2.86%) and Nippostrongylus brasiliensis (85.71%), were identified. The most prevalent ectoparasites belonged to Laelaps spp. (41.17%) followed by Polyplax spp. (23.53%), Hoplopleura spp. (17.65%), Ixodes holocyclus (17.64%) and Stephanocircus harrisoni (5.88%), respectively. These ectoparasites, except S. harrisoni, are known to transmit zoonotic pathogens such as Rickettsia spp. from rat to rat and could be transmitted to humans by other arthropods that bite humans. The high prevalence of pathogenic Leptospira species is of significant public health concern. This is the first known study of zoonotic agents carried by non-indigenous rodents living in the Australian wet-tropical forest interface.