The metabolic transition during disease following infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato.

The outcome of bacterial infection in plants is determined by the ability of the pathogen to successfully occupy the apoplastic space and deliver a constellation of effectors that collectively suppress basal and effector-triggered immune responses. In this study, we examined the metabolic changes associated with establishment of disease using analytical techniques that interrogated a range of chemistries. We demonstrated clear differences in the metabolome of Arabidopsis thaliana leaves infected with virulent Pseudomonas syringae within 8 h of infection. In addition to confirmation of changes in phenolic and indolic compounds, we identified rapid alterations in the abundance of amino acids and other nitrogenous compounds, specific classes of glucosinolates, disaccharides, and molecules that influence the prevalence of reactive oxygen species. Our data illustrate that, superimposed on defence suppression, pathogens reconfigure host metabolism to provide the sustenance required to support exponentially growing populations of apoplastically localized bacteria. We performed a detailed baseline study reporting the metabolic dynamics associated with bacterial infection. Moreover, we have integrated these data with the results of transcriptome profiling to distinguish metabolomic pathways that are transcriptionally activated from those that are post-transcriptionally regulated.

Arabidopsis auxin mutants are compromised in systemic acquired resistance and exhibit aberrant accumulation of various indolic compounds.

Systemic acquired resistance is a widespread phenomenon in the plant kingdom that confers heightened and often enduring immunity to a range of diverse pathogens. Systemic immunity develops through activation of plant disease resistance protein signaling networks following local infection with an incompatible pathogen. The accumulation of the phytohormone salicylic acid in systemically responding tissues occurs within days after a local immunizing infection and is essential for systemic resistance. However, our knowledge of the signaling components underpinning signal perception and the establishment of systemic immunity are rudimentary. Previously, we showed that an early and transient increase in jasmonic acid in distal responding tissues was central to effective establishment of systemic immunity. Based upon predicted transcriptional networks induced in naive Arabidopsis (Arabidopsis thaliana) leaves following avirulent Pseudomonas syringae challenge, we show that a variety of auxin mutants compromise the establishment of systemic immunity. Linking together transcriptional and targeted metabolite studies, our data provide compelling evidence for a role of indole-derived compounds, but not auxin itself, in the establishment and maintenance of systemic immunity.

R/BHC: fast Bayesian hierarchical clustering for microarray data.

BACKGROUND: Although the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data analysis, little attention has been paid to uncertainty in the results obtained. RESULTS: We present an R/Bioconductor port of a fast novel algorithm for Bayesian agglomerative hierarchical clustering and demonstrate its use in clustering gene expression microarray data. The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. CONCLUSION: Biologically plausible results are presented from a well studied data set: expression profiles of A. thaliana subjected to a variety of biotic and abiotic stresses. Our method avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric.