Besides their commonly attributed role in the maintenance of low-copy number plasmids, toxin/antitoxin (TA) loci, also called ‘addiction modules’, have been found in chromosomes and associated to a number of biological functions such as: reduction of protein synthesis, gene regulation and retardation of cell growth under nutritional stress. The recent discovery of TA loci in obligatory intracellular species of the Rickettsia genus has prompted new research to establish whether they work as stress response elements or as addiction systems that might be toxic for the host cell. VapBC2 is a TA locus from R. felis, a pathogen responsible for flea-borne spotted fever in humans. The VapC2 toxin is a PIN-domain protein, whereas the antitoxin, VapB2, belongs to the family of swapped-hairpin β-barrel DNA-binding proteins. We have used a combination of biophysical and structural methods to characterize this new toxin/antitoxin pair. Our results show how VapB2 can block the VapC2 toxin. They provide a first structural description of the interaction between a swapped-hairpin β-barrel protein and DNA. Finally, these results suggest how the VapC2/VapB2 molar ratio can control the self-regulation of the TA locus transcription.

Recent advances in macromolecular crystallography have made it practical to rapidly collect hundreds of sub-data sets consisting of small oscillations of incomplete data. This approach, generally referred to as serial crystallography, has many uses, including an increased effective dose per data set, the collection of data from crystals without harvesting (in situ data collection) and studies of dynamic events such as catalytic reactions. However, selecting which data sets from this type of experiment should be merged can be challenging and new methods are required. Here, it is shown that a genetic algorithm can be used for this purpose, and five case studies are presented in which the merging statistics are significantly improved compared with conventional merging of all data.