Bacterial Alkaloids Prevent Amoebal Predation

The products of many bacterial non-ribosomal peptide synthetases (NRPS) are highly important secondary metabolites, including vancomycin and other antibiotics. The ability to predict substrate specificity of newly detected NRPS Adenylation (A-) domains by genome sequencing efforts is of great importance to identify and annotate new gene clusters that produce secondary metabolites. Prediction of A-domain specificity based on the sequence alone can be achieved through sequence signatures or, more accurately, through machine learning methods. We present an improved predictor, based on previous work (NRPSpredictor), that predicts A-domain specificity using Support Vector Machines on four hierarchical levels, ranging from gross physicochemical properties of an A-domain’s substrates down to single amino acid substrates. The three more general levels are predicted with an F-measure better than 0.89 and the most detailed level with an average F-measure of 0.80. We also modeled the applicability domain of our predictor to estimate for new A-domains whether they lie in the applicability domain. Finally, since there are also NRPS that play an important role in natural products chemistry of fungi, such as peptaibols and cephalosporins, we added a predictor for fungal A-domains, which predicts gross physicochemical properties with an F-measure of 0.84. The service is available at http://nrps.informatik.uni-tuebingen.de/.

Bacterial growth and survival in numerous environments are constrained by the action of bacteria-consuming protozoa. Recent findings suggest that bacterial adaptations against protozoan predation might have a significant role in bacterial persistence and diversification. We argue that selective predation has given rise to diverse routes of bacterial defense, including adaptive mechanisms in bacterial biofilms, and has promoted major transitions in bacterial evolution, such as multicellularity and pathogenesis. We propose that studying predation-driven adaptations will provide an exciting frontier for microbial ecology and evolution at the interface of prokaryotes and eukaryotes.

Type III secretion systems are toxin delivery systems that are present in a large number of pathogens. A hallmark of all type III secretion systems studied to date is that expression of one or more of their components is induced upon cell contact. It has been proposed that this induction is controlled by a negative regulator that is itself secreted by means of the type III secretion machinery. Although candidate proteins for this negative regulator have been proposed in a number of systems, for the most part, a direct demonstration of their role in regulation is lacking. Here, we report the discovery of ExsE, a negative regulator of type III secretion gene expression in Pseudomonas aeruginosa. Deletion of exsE deregulates expression of the type III secretion genes. We provide evidence that ExsE is itself secreted by means of the type III secretion machinery and physically interacts with ExsC, a positive regulator of the type III secretion regulon. Taken together, these data demonstrate that ExsE is the secreted negative regulator that couples triggering of the type III secretion machinery to induction of the type III secretion genes.