Bacterial ligases reveal fundamental principles of polyubiquitin specificity
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Histidinol-phosphate aminotransferase is the sixth protein (hence HISN6) in the histidine biosynthetic pathway in plants. HISN6 is a pyridoxal 5'-phosphate (PLP)-dependent enzyme that catalyzes the reversible conversion of imidazole acetol phosphate into L-histidinol phosphate (HOLP). Here, we show that plant HISN6 enzymes are closely related to the orthologs from Chloroflexota. The studied example, HISN6 from Medicago truncatula (MtHISN6), exhibits a surprisingly high affinity for HOLP, which is much higher than reported for bacterial homologs. Moreover, unlike the latter, MtHISN6 does not transaminate phenylalanine. High-resolution crystal structures of MtHISN6 in the open and closed states, as well as the complex with HOLP and the apo structure without PLP, bring new insights into the enzyme dynamics, pointing at a particular role of a string-like fragment that oscillates near the active site and participates in the HOLP binding. When MtHISN6 is compared to bacterial orthologs with known structures, significant differences arise in or near the string region. The high affinity of MtHISN6 appears linked to the particularly tight active site cavity. Finally, a virtual screening against a library of over 1.3 mln compounds revealed three sites in the MtHISN6 structure with the potential to bind small molecules. Such compounds could be developed into herbicides inhibiting plant HISN6 enzymes absent in animals, which makes them a potential target for weed control agents.
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MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.
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Opioid-related fatal overdoses have reached epidemic proportions. Because existing treatments for opioid use disorders offer limited long-term protection, accelerating the development of newer approaches is critical. Monoclonal antibodies (mAbs) are an emerging treatment strategy that targets and sequesters selected opioids in the bloodstream, reducing drug distribution across the blood-brain barrier, thus preventing or reversing opioid toxicity. We previously identified a series of murine mAbs with high affinity and selectivity for oxycodone, morphine, fentanyl, and nicotine. To determine their binding mechanism, we used X-ray crystallography to solve the structures of mAbs bound to their respective targets, to 2.2 Å resolution or higher. Structural analysis showed a critical convergent hydrogen bonding mode that is dependent on a glutamic acid residue in the mAbs’ heavy chain and a tertiary amine of the ligand. Further, characterizing drug-mAb complexes represents a significant step toward rational antibody engineering and future manufacturing activities to support clinical evaluation.
Arctic soil microbial communities may shift with increasing temperatures and water availability from climate change. We examined temperature and volumetric liquid water content (VWC) in the upper 80 cm of permafrost-affected soil over 2 years (2018–2019) at the Bayelva monitoring station, Ny Ålesund, Svalbard. We show VWC increases with depth, whereas in situ temperature is more stable vertically, ranging from -5°C to 5°C seasonally. Prokaryotic metagenome-assembled genomes (MAGs) were obtained at 2–4 cm vertical resolution collected while frozen in April 2018 and at 10 cm vertical resolution collected while thawed in September 2019. The most abundant MAGs were Acidobacteriota, Actinomycetota, and Chloroflexota. Actinomycetota and Chloroflexota increase with depth, while Acidobacteriota classes Thermoanaerobaculia Gp7-AA8, Blastocatellia UBA7656, and Vicinamibacteria Vicinamibacterales are found above 6 cm, below 6 cm, and below 20cm, respectively. All MAGs have diverse carbon-degrading genes, and Actinomycetota and Chloroflexota have autotrophic genes. Further, genes encoding β -glucosidase, N-acetyl-β-D-glucosaminidase, and xylosidase increase with depth, indicating a greater potential for organic matter degradation with higher VWC. Acidobacteriota dominate the top 6 cm with their classes segregating by depth, whereas Actinomycetota and Chloroflexota dominate below ~6 cm. This suggests that Acidobacteriota classes adapt to lower VWC at the surface, while Actinomycetota and Chloroflexota persist below 6cm with higher VWC. This indicates that VWC may be as important as temperature in microbial climate change responses in Arctic mineral soils. Here we describe MAG-based Seqcode type species in the Acidobacteriota, Onstottus arcticum, Onstottus frigus, and Gilichinskyi gelida and in the Actinobacteriota, Mayfieldus profundus.