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We have developed a range of vectors for allelic replacements in Staphylococcus aureus to facilitate genetic work in this opportunistic pathogen. The central feature of the vector range is a selection/counterselection system that takes advantage of the 5-fluoroorotic acid (FOA) resistance and pyrimidine prototrophy caused by the loss and gain, respectively, of the pyrF and pyrE genes. This system allows for stringent counterselection of the vectors during the second homologous recombination of a classic allelic replacement. The basic vector pRLY2, which contains the pyrFE genes from Bacillus subtilis, was combined with chloramphenicol, erythromycin, and tetracycline resistance genes and four different versions of nonreplicative or conditionally replicative origins of replication. The choice between these 12 different pRLY vectors allows for high versatility and ensures that the vectors can be used in virtually any genetic background. Finally, as proof of concept, we present six deletions or modifications of components in the S. aureus degradosome as well as the operon containing the cshB DEAD box helicase.
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http://dx.doi.org/10.1128/AEM.00202-12 | DOI Listing |
J Econ Entomol
September 2025
Department of Entomology and Nematology, Southwest Florida Research and Education Center (SWFREC), University of Florida/IFAS, Immokalee, FL, USA.
The Citrus Under Protective Screen is a novel production system implemented to grow citrus free of huanglongbing disease vectored by Asian citrus psyllid, Diaphorina citri. Other significant pests such as mites, scales, thrips, mealybugs, and leafminers, as well as parasitoids and small predators, have been identified from Citrus Under Protective Screen and require management. Chrysomphalus aonidum (L.
View Article and Find Full Text PDFAnnu Rev Entomol
September 2025
2Department of Animal Physiology, Zoological Institute and Museum, University of Greifswald, Greifswald, Germany.
The evolutionary success of insects may be partly attributed to their profound ability to adjust metabolism in response to environmental stress or resource variability at a range of timescales. Metabolic flexibility encompasses the ability of an organism to adapt or respond to conditional changes in metabolic demand and tune fuel oxidation to match fuel availability. Here, we evaluate the mechanisms of metabolic flexibility in insects that are considered short-term, medium-term, and long-term responses.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Biology, Stanford University, Stanford, CA 94305.
Climate change is expected to pose significant threats to public health, particularly vector-borne diseases. Despite dramatic recent increases in dengue that many anecdotally connect with climate change, the effect of anthropogenic climate change on dengue remains poorly quantified. To assess this link, we assembled local-level data on dengue across 21 countries in Asia and the Americas.
View Article and Find Full Text PDFBioelectromagnetics
September 2025
Competence Centre of Sleep Medicine, Charité -Universitaetsmedizin Berlin, Berlin, Germany.
A new whole-body exposure facility for a randomized, double-blind, cross-over provocation study investigating possible effects of 50 Hz magnetic field exposure on sleep and markers of Alzheimer's disease has been developed and dosimetrically analyzed. The exposure facility was custom-tailored for the sleep laboratory where the study was carried out and enables magnetic flux densities of up to 30 μT with a maximum field inhomogeneity of less than ± 20%. Exposure is applied fully software-controlled and in a blinded and randomized manner.
View Article and Find Full Text PDFJ Phys Chem Lett
September 2025
Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
In this work, we present a machine learning (ML) approach for predicting the optimal range separation parameters in transition metal complexes (TMCs), aiming to reduce the computational cost associated with optimally tuned range-separated hybrid (OT-RSH) functionals while preserving their accuracy. A data set containing 4380 TMCs was constructed by screening the tmQM database, with each TMC represented by a 62 087-dimensional multiple-fingerprint feature (MFF) vector and labeled with its optimally tuned range separation parameter. Multiple regression models were applied to train the prediction model, and the support vector machine (SVM) model yielded the best performance.
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