Acinetobacter baumannii virulence is mediated by the concerted action of three phospholipases D
(2015)
Acinetobacter baumannii causes a broad range of opportunistic infections in humans. Its success as an emerging pathogen is due to a combination of increasing antibiotic resistance, environmental persistence and adaptation to the human host. To date very little is known about the molecular basis of the latter. Here we demonstrate that A. baumannii can use phosphatidylcholine, an integral part of human cell membranes, as sole carbon and energy source. We report on the identification of three phospholipases belonging to the PLD superfamily. PLD1 and PLD2 appear restricted to the bacteria and display the general features of bacterial phospholipases D. They possess two PLDc_2 PFAM domains each encompassing the HxKx4Dx6GS/GGxN (HKD) motif necessary for forming the catalytic core. The third candidate, PLD3, is found in bacteria as well as in eukaryotes and harbours only one PLDc_2 PFAM domain and one conserved HKD motif, which however do not overlap. Employing a markerless mutagenesis system for A. baumannii ATCC 19606T, we generated a full set of PLD knock-out mutants. Galleria mellonella infection studies as well as invasion experiments using A549 human lung epithelial cells revealed that the three PLDs act in a concerted manner as virulence factors and are playing an important role in host cell invasion.
In March 2019 the HADES experiment recorded 14 billion Ag+Ag collisions at √sNN = 2.55 GeV as a part of the FAIR phase-0 physics program. In this contribution, we present and investigate our capabilities to reconstruct and analyze weakly decaying strange hadrons and hypernuclei emerging from these collisions. The focus is put on measuring the mean lifetimes of these particles.
Motivation Expert curation to differentiate between functionally diverged homologs and those that may still share a similar function routinely relies on the visual interpretation of domain architecture changes. However, the size of contemporary data sets integrating homologs from hundreds to thousands of species calls for alternate solutions. Scoring schemes to evaluate domain architecture similarities can help to automatize this procedure, in principle. But existing schemes are often too simplistic in the similarity assessment, many require an a-priori resolution of overlapping domain annotations, and those that allow overlaps to extend the set of annotations sources cannot account for redundant annotations. As a consequence, the gap between the automated similarity scoring and the similarity assessment based on visual architecture comparison is still too wide to make the integration of both approaches meaningful.
Results Here, we present FAS, a scoring system for the comparison of multi-layered feature architectures integrating information from a broad spectrum of annotation sources. Feature architectures are represented as directed acyclic graphs, and redundancies are resolved in the course of comparison using a score maximization algorithm. A benchmark using more than 10,000 human-yeast ortholog pairs reveals that FAS consistently outperforms existing scoring schemes. Using three examples, we show how automated architecture similarity assessments can be routinely applied in the benchmarking of orthology assignment software, in the identification of functionally diverged orthologs, and in the identification of entries in protein collections that most likely stem from a faulty gene prediction.