The built environment (BE) and in particular kitchen environments harbor a remarkable microbial diversity, including pathogens. We analyzed the bacterial microbiome of used kitchen sponges by 454–pyrosequencing of 16S rRNA genes and fluorescence in situ hybridization coupled with confocal laser scanning microscopy (FISH–CLSM). Pyrosequencing showed a relative dominance of Gammaproteobacteria within the sponge microbiota. Five of the ten most abundant OTUs were closely related to risk group 2 (RG2) species, previously detected in the BE and kitchen microbiome. Regular cleaning of sponges, indicated by their users, significantly affected the microbiome structure. Two of the ten dominant OTUs, closely related to the RG2-species Chryseobacterium hominis and Moraxella osloensis, showed significantly greater proportions in regularly sanitized sponges, thereby questioning such sanitation methods in a long term perspective. FISH–CLSM showed an ubiquitous distribution of bacteria within the sponge tissue, concentrating in internal cavities and on sponge surfaces, where biofilm–like structures occurred. Image analysis showed local densities of up to 5.4 * 1010 cells per cm3, and confirmed the dominance of Gammaproteobacteria. Our study stresses and visualizes the role of kitchen sponges as microbiological hot spots in the BE, with the capability to collect and spread bacteria with a probable pathogenic potential.

Modern, mainly sustainability-driven trends, such as low-temperature washing or bleach-free liquid detergents, facilitate microbial survival of the laundry processes. Favourable growth conditions like humidity, warmth and sufficient nutrients also contribute to microbial colonization of washing machines. Such colonization might lead to negatively perceived staining, corrosion of washing machine parts and surfaces, as well as machine and laundry malodour. In this study, we characterized the bacterial community of 13 domestic washing machines at four different sampling sites (detergent drawer, door seal, sump and fibres collected from the washing solution) using 16S rRNA gene pyrosequencing and statistically analysed associations with environmental and user-dependent factors. Across 50 investigated samples, the bacterial community turned out to be significantly site-dependent with the highest alpha diversity found inside the detergent drawer, followed by sump, textile fibres isolated from the washing solution, and door seal. Surprisingly, out of all other investigated factors only the monthly number of wash cycles at temperatures ≥ 60 • C showed a significant influence on the community structure. A higher number of hot wash cycles per month increased microbial diversity, especially inside the detergent drawer. Potential reasons and the hygienic relevance of this finding need to be assessed in future studies.

Self-organizing maps were trained to separate high- and low-active propafenone-type inhibitors of P-glycoprotein. The trained maps were subsequently used to identify highly active compounds in a virtual screen of the SPECS compound library.

In topological autocorrelation approaches molecular descriptors are calculated by summing up properties located at given topological distances. Since the relationship between topological and Euclidean distance contains 3D structural information, in the present paper a modified version of an autocorrelation approach is proposed to include this type of information. Steric, electronic, and indicator-variable-type descriptors are calculated and used in QSAR studies with three different data sets. The results demonstrate that the descriptors can be efficiently used in cluster- and QSAR analysis. The models obtained are highly predictive and comparable to those obtained by other commonly used 3D-QSAR methods.

Multidrug resistance presents a major obstacle to the treatment of infectious diseases and cancer. LmrA, a bacterial ATP-dependent multidrug transporter, mediates efflux of hydrophobic cationic substrates, including antibiotics. The substrate-binding domain of LmrA was identified by using photo-affinity ligands, proteolytic degradation of LmrA, and identification of ligand-modified peptide fragments with matrix-assisted laser desorption ionization/time of flight mass spectrometry. In the nonenergized state, labeling occurred in the ␣-helical transmembrane segments (TM) 3, 5 and 6 of the membrane-spanning domain. Upon nucleotide binding, the accessibility of TM5 for substrates increased, whereas that of TM6 decreased. Inverse changes were observed upon ATP-hydrolysis. An atomic-detail model of dimeric LmrA was generated based on the template structure of the homologous transporter MsbA from Vibrio cholerae, allowing a three-dimensional visualization of the substrate-binding domain. Labeling of TM3 of one monomer occurred in a predicted area of contact with TM5 or TM6 of the opposite monomer, indicating substrate-binding at the monomer/monomer interface. Inverse changes in the reactivity of TM segments 5 and 6 suggest that substrate binding and release involves a repositioning of these helices during the catalytic cycle.