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The mechanism of programming of iterative highly reducing polyketide synthases remains one of the key unsolved problems of secondary metabolism. We conducted rational domain swaps between the polyketide synthases encoding the biosynthesis of the closely related compounds tenellin and desmethylbassianin. Expression of the hybrid synthetases in Aspergillus oryzae led to the production of reprogrammed compounds in which the changes to the methylation pattern and chain length could be mapped to the domain swaps. These experiments reveal for the first time the origin of programming in these systems. Domain swaps combined with coexpression of two cytochrome P450 encoding genes from the tenellin biosynthetic gene cluster led to the resurrection of the extinct metabolite bassianin.
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http://dx.doi.org/10.1021/ja206914q | DOI Listing |
Elife
September 2025
Department of Chemistry, University of Massachusetts, Amherst, United States.
Voltage-dependence gating of ion channels underlies numerous physiological and pathophysiological processes, and disruption of normal voltage gating is the cause of many channelopathies. Here, long timescale atomistic simulations were performed to directly probe voltage-induced gating transitions of the big potassium (BK) channels, where the voltage sensor domain (VSD) movement has been suggested to be distinct from that of canonical Kv channels but remains poorly understood. Using a Core-MT construct without the gating ring, multiple voltage activation transitions were observed at 750 mV, allowing detailed analysis of the activated state of BK VSD and key mechanistic features.
View Article and Find Full Text PDFTrends Biotechnol
September 2025
Bioprocess Engineering Group, Wageningen University & Research, Wageningen, 6700 AA, The Netherlands. Electronic address:
Microbial whole-cell biosensors (MWCBs) harness living cells to detect analytes and produce measurable outputs, enabling continuous, low-cost, and in situ sensing. Central to MWCB function are modular sensing architectures, which can be reprogrammed to respond to diverse signals. Particularly, two-component systems (TCSs) and allosteric transcription factors (aTFs) offer modular, engineerable frameworks for building chimeric proteins.
View Article and Find Full Text PDFJ Biol Chem
September 2025
Research Unit in Biology of Microorganisms (URBM), Department of Biology, Namur Research Institute for Life Sciences (NARILIS), University of Namur, Namur, Belgium.
Metals like copper (Cu), zinc, and nickel exhibit dual nature, necessitating a tight regulation of their cellular homeostasis to meet physiological demands while preventing toxicity. In bacteria, metal homeostasis involves inner membrane (IM) P-type ATPases and ABC transporters, envelope-spanning tripartite efflux pumps, and outer membrane (OM) pore-forming proteins. Four decades ago, the OM β-barrel protein PcoB was shown to provide an additional layer of Cu resistance in an Escherichia coli strain isolated from the gut of swine fed with Cu supplements.
View Article and Find Full Text PDFActa Crystallogr D Struct Biol
September 2025
Department of Chemistry and Physics, University of Almeria, Agrifood Campus of International Excellence (ceiA3) and CIAMBITAL, Carretera de Sacramento s/n, 04120 Almeria, Spain.
The c-Src SH3 domain is one of the best-characterized modular domains from a biophysical and structural point of view. This SH3 domain displays noncanonical alternative folding, forming 3D domain-swapped oligomers and amyloid fibrils. These features make this small protein an ideal model for studying these phenomena.
View Article and Find Full Text PDF3D domain swapping is a protein structural phenomenon in which two or more protein subunits exchange identical structural subunits and form oligomers. Proteins that exhibit 3D domain swapping play a crucial role in various biological functions, such as secondary metabolite biosynthesis, and in coping with several biotic and abiotic stresses in medicinal plants. This study investigates the ability to predict 3D domain swapping patterns among the genomes of medicinal plants using random forest and K-nearest neighbor classifiers models, demonstrating accuracies of 91.
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