The MksG nuclease is the executing part of the bacterial plasmid defense system MksBEFG.

Cells are continuously facing the risk of taking up foreign DNA that can compromise genomic integrity. Therefore, bacteria are in a constant arms race with mobile genetic elements such as phages, transposons and plasmids. They have developed several active strategies against invading DNA molecules that can be seen as a bacterial 'innate immune system'. Here, we investigated the molecular arrangement of the Corynebacterium glutamicum MksBEFG complex, which is homologous to the MukBEF condensin system. We show here that MksG is a nuclease that degrades plasmid DNA. The crystal structure of MksG revealed a dimeric assembly through its C-terminal domain that is homologous to the TOPRIM domain of the topoisomerase II family of enzymes and contains the corresponding ion binding site essential for DNA cleavage in topoisomerases. The MksBEF subunits exhibit an ATPase cycle in vitro and we reason that this reaction cycle, in combination with the nuclease activity provided by MksG, allows for processive degradation of invading plasmids. Super-resolution localization microscopy revealed that the Mks system is spatially regulated via the polar scaffold protein DivIVA. Introduction of plasmids results in an increase in DNA bound MksG, indicating an activation of the system in vivo.

Whole-Genome Sequence Comparisons of Listeria monocytogenes Isolated from Meat and Fish Reveal High Inter- and Intra-Sample Diversity.

Interpretation of whole-genome sequencing (WGS) data for foodborne outbreak investigations is complex, as the genetic diversity within processing plants and transmission events need to be considered. In this study, we analyzed 92 food-associated Listeria monocytogenes isolates by WGS-based methods. We aimed to examine the genetic diversity within meat and fish production chains and to assess the applicability of suggested thresholds for clustering of potentially related isolates. Therefore, meat-associated isolates originating from the same samples or processing plants as well as fish-associated isolates were analyzed as distinct sets. In silico serogrouping, multilocus sequence typing (MLST), core genome MLST (cgMLST), and pangenome analysis were combined with screenings for prophages and genetic traits. Isolates of the same subtypes (cgMLST types (CTs) or MLST sequence types (STs)) were additionally compared by SNP calling. This revealed the occurrence of more than one CT within all three investigated plants and within two samples. Analysis of the fish set resulted in predominant assignment of isolates from pangasius catfish and salmon to ST2 and ST121, respectively, potentially indicating persistence within the respective production chains. The approach not only allowed the detection of distinct subtypes but also the determination of differences between closely related isolates, which need to be considered when interpreting WGS data for surveillance.

Time-dependent prediction of arrhythmia recurrences during long-term follow-up in patients undergoing catheter ablation of atrial fibrillation: The Leipzig Heart Center AF Ablation Registry.

The prediction of arrhythmia recurrences after catheter ablation of atrial fibrillation (AF) remains challenging. The aim of current analysis was to investigate the time-dependent prediction of arrhythmia recurrences after AF catheter ablation during long-term follow-up. The study included 879 patients (61 ± 10 years; 64% males; 39% persistent AF) undergoing first AF catheter ablation. Rhythm outcomes were documented using 7-days Holter monitoring. The APPLE score (Age, Persistent AF, imPaired eGFR, Left atrium (LA), EF) was calculated at baseline, while MB-LATER score (Male gender, Bundle branch block, LA, AF Type, Early Recurrences) 3 months after ablation. The median follow-up time was 37 months [95%CI 35;39]. ERAF and LRAF occurred in 45% and 64%, respectively. On multivariable analysis, ERAF (HR 2.095, 95%CI 1.762-2.490, p < 0.001) was strongly associated with LRAF. The APPLE (HR 1.385, 95%CI 1.276-1.505, p < 0.001) and MB-LATER (HR 1.326, 95%CI 1.239-1.419, p < 0.001) scores significantly predicted LRAF during follow-up. On the ROC analysis, APPLE (AUC 0.640, 95%CI 0.602-0.677, p < 0.001) and MB-LATER (AUC 0.654, 95%CI 0.616-0.691, p < 0.001) demonstrated moderate prediction. Summarizing, ERAF was the strongest predictor for LRAF in time-dependent manner. The APPLE and MB-LATER scores demonstrated moderate prediction of arrhythmia recurrences during long term follow-up.