Necrotrophism Is a Quorum-Sensing-Regulated Lifestyle in Bacillus thuringiensis

How pathogenic bacteria infect and kill their host is currently widely investigated. In comparison, the fate of pathogens after the death of their host receives less attention. We studied Bacillus thuringiensis (Bt) infection of an insect host, and show that NprR, a quorum sensor, is active after death of the insect and allows Bt to survive in the cadavers as vegetative cells. Transcriptomic analysis revealed that NprR regulates at least 41 genes, including many encoding degradative enzymes or proteins involved in the synthesis of a nonribosomal peptide named kurstakin. These degradative enzymes are essential in vitro to degrade several substrates and are specifically expressed after host death suggesting that Bt has an active necrotrophic lifestyle in the cadaver. We show that kurstakin is essential for Bt survival during necrotrophic development. It is required for swarming mobility and biofilm formation, presumably through a pore forming activity. A nprR deficient mutant does not develop necrotrophically and does not sporulate efficiently in the cadaver. We report that necrotrophism is a highly regulated mechanism essential for the Bt infectious cycle, contributing to spore spreading

Criteria for the use of omics-based predictors in clinical trials: Explanation and elaboration

High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well. © 2013 McShane et al.; licensee BioMed Central Ltd

Leakage and lysis of lipid membranes induced by the lipopeptide surfactin

Surfactin is a lipopeptide produced by Bacillus subtilis which possesses antimicrobial activity. We have studied the leakage and lysis of POPC vesicles induced by surfactin using calcein fluorescence de-quenching, isothermal titration calorimetry and (31)P solid state NMR. Membrane leakage starts at a surfactin-to-lipid ratio in the membrane, R (b) approximately 0.05, and an aqueous surfactin concentration of C (S) (w) approximately 2 microM. The transient, graded nature of leakage and the apparent coupling with surfactin translocation to the inner leaflet of the vesicles, suggests that this low-concentration effect is due to a bilayer-couple mechanism. Different permeabilization behaviour is found at R (b) approximately 0.15 and attributed to surfactin-rich clusters, which can induce leaks and stabilize them by covering their hydrophobic edges. Membrane lysis or solubilization to micellar structures starts at R (b) (sat) = 0.22 and C (S) (w) = 9 microM and is completed at R (m) (sol) = 0.43 and C (S) (w) = 11 microM. The membrane-water partition coefficient of surfactin is obtained as K = 2 x 10(4) M(-1). These data resolve inconsistencies in the literature and shed light on the variety of effects often referred to as detergent-like effects of antibiotic peptides on membranes. The results are compared with published parameters characterizing the hemolytic and antibacterial activity