Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

Proteasome inhibitors trigger NOXA-mediated apoptosis in melanoma and myeloma cells

Patients with metastatic melanoma or multiple myeloma have a dismal prognosis because these aggressive malignancies resist conventional treatment. A promising new oncologic approach uses molecularly targeted therapeutics that overcomes apoptotic resistance and, at the same time, achieves tumor selectivity. The unexpected selectivity of proteasome inhibition for inducing apoptosis in cancer cells, but not in normal cells, prompted us to define the mechanism of action for this class of drugs, including Food and Drug Administration-approved bortezomib. In this report, five melanoma cell lines and a myeloma cell line are treated with three different proteasome inhibitors (MG-132, lactacystin, and bortezomib), and the mechanism underlying the apoptotic pathway is defined. Following exposure to proteasome inhibitors, effective killing of human melanoma and myeloma cells, but not of normal proliferating melanocytes, was shown to involve p53-independent induction of the BH3-only protein NOXA. Induction of NOXA at the protein level was preceded by enhanced transcription of NOXA mRNA. Engagement of mitochondrial-based apoptotic pathway involved release of cytochrome c, second mitochondria-derived activator of caspases, and apoptosis-inducing factor, accompanied by a proteolytic cascade with processing of caspases 9, 3, and 8 and poly(ADP)-ribose polymerase. Blocking NOXA induction using an antisense (but not control) oligonucleotide reduced the apoptotic response by 30% to 50%, indicating a NOXA-dependent component in the overall killing of melanoma cells. These results provide a novel mechanism for overcoming the apoptotic resistance of tumor cells, and validate agents triggering NOXA induction as potential selective cancer therapeutics for life-threatening malignancies such as melanoma and multiple myeloma.