The GimA Locus of Extraintestinal Pathogenic E. coli: Does Reductive Evolution Correlate with Habitat and Pathotype?

IbeA (invasion of brain endothelium), which is located on a genomic island termed GimA, is involved in the pathogenesis of several extraintestinal pathogenic E. coli (ExPEC) pathotypes, including newborn meningitic E. coli (NMEC) and avian pathogenic E. coli (APEC). To unravel the phylogeny of GimA and to investigate its island character, the putative insertion locus of GimA was determined via Long Range PCR and DNA-DNA hybridization in 410 E. coli isolates, including APEC, NMEC, uropathogenic (UPEC), septicemia-associated E. coli (SEPEC), and human and animal fecal isolates as well as in 72 strains of the E. coli reference (ECOR) collection. In addition to a complete GimA (∼20.3 kb) and a locus lacking GimA we found a third pattern containing a 342 bp remnant of GimA in this strain collection. The presence of GimA was almost exclusively detected in strains belonging to phylogenetic group B2. In addition, the complete GimA was significantly more frequent in APEC and NMEC strains while the GimA remnant showed a higher association with UPEC strains. A detailed analysis of the ibeA sequences revealed the phylogeny of this gene to be consistent with that obtained by Multi Locus Sequence Typing of the strains. Although common criteria for genomic islands are partially fulfilled, GimA rather seems to be an ancestral part of phylogenetic group B2, and it would therefore be more appropriate to term this genomic region GimA locus instead of genomic island. The existence of two other patterns reflects a genomic rearrangement in a reductive evolution-like manner

Quantification in cardiac MRI: advances in image acquisition and processing

Cardiac magnetic resonance (CMR) imaging enables accurate and reproducible quantification of measurements of global and regional ventricular function, blood flow, perfusion at rest and stress as well as myocardial injury. Recent advances in MR hardware and software have resulted in significant improvements in image quality and a reduction in imaging time. Methods for automated and robust assessment of the parameters of cardiac function, blood flow and morphology are being developed. This article reviews the recent advances in image acquisition and quantitative image analysis in CMR