The incredible diversity of structures and functions of ABC transporters

The transport activity of the multidrug ABC transporter BmrA does not require a wide separation of the nucleotide-binding domains

ATP-binding cassette (ABC) transporters are ubiquitous membrane proteins responsible for the translocation of a wide diversity of substrates across biological membranes. Some of them confer multidrug or antimicrobial resistance to cancer cells and pathogenic microorganisms, respectively. Despite a wealth of structural data gained in the last two decades, the molecular mechanism of these multidrug efflux pumps remains elusive, including the extent of separation between the two nucleotide-binding domains (NBDs) during the transport cycle. Based on recent outward-facing structures of BmrA, a homodimeric multidrug ABC transporter from Bacillus subtilis, we introduced a cysteine mutation near the C-terminal end of the NBDs to analyze the impact of disulfide-bond formation on BmrA function. Interestingly, the presence of the disulfide bond between the NBDs did not prevent the ATPase, nor did it affect the transport of Hoechst 33342 and doxorubicin. Yet, the 7-amino-actinomycin D was less efficiently transported, suggesting that a further opening of the transporter might improve its ability to translocate this larger compound. We solved by cryo-EM the apo structures of the cross-linked mutant and the WT protein. Both structures are highly similar, showing an intermediate opening between their NBDs while their C-terminal extremities remain in close proximity. Distance measurements obtained by electron paramagnetic resonance spectroscopy support the intermediate opening found in these 3D structures. Overall, our data suggest that the NBDs of BmrA function with a tweezers-like mechanism distinct from the related lipid A exporter MsbA.

Water Quality, Heavy Metals, and Antifungal Susceptibility to Fluconazole of Yeasts from Water Systems

Aquatic environments could be reservoirs of pathogenic yeasts with acquired antifungal resistance. The susceptibility to antifungal agents of yeasts present in the wastewater and natural waters of the city of Cali was evaluated. Samples were taken from two types of water: drinking water (Meléndez River, drinking water treatment plant "Puerto Mallarino" in the Cauca River) and wastewater (South Channel of the Cauca River, "Cañaveralejo-PTAR" wastewater treatment plant). Physico-chemical parameters, heavy metal concentration, and yeast levels were determined using standard procedures. Yeasts were identified using API 20 C AUX (BioMérieux) and sequence analysis of the ITS1-5.8S-ITS2 and D1/D2 regions of the large subunit of the ribosome. Susceptibility assays against fluconazole and amphotericin B using the minimum inhibitory concentration (MIC) test were determined using the microdilution method. The influence of physico-chemical parameters and heavy metals was established using principal component analysis (PCA). Yeast counts were higher at WWTP "PTAR" and lower at Melendez River, as expected. A total of 14 genera and 21 yeast species was identified, and the genus Candida was present at all locations. Susceptibility tests showed a 32.7% resistance profile to fluconazole in the order DWTP "Puerto Mallarino = WWTP "PTAR" > South Channel "Navarro". There were significant differences (p < 0.05) in the physico-chemical parameters/concentration of heavy metals and yeast levels between the aquatic systems under study. A positive association was observed between yeast levels and total dissolved solids, nitrate levels, and Cr at the "PTAR" WWTP; conductivity, Zn, and Cu in the South Channel; and the presence of Pb in the "Puerto Mallarino" DWTP. Rhodotorula mucilaginosa, Candida albicans, and Candida sp. 1 were influenced by Cr and Cd, and Diutina catelunata was influenced by Fe (p < 0.05). The water systems explored in this study showed different yeast levels and susceptibility profiles, and, therefore, possible genetic differences among populations of the same species, and different physico-chemical and heavy metals concentrations, which were probably modulating the antifungal-resistant yeasts. All these aquatic systems discharge their content into the Cauca River. We highlight the importance to further investigate if these resistant communities continue to other locations in the second largest river of Colombia and to determine the risk posed to humans and animals.

Ins and outs of AlphaFold2 transmembrane protein structure predictions

Transmembrane (TM) proteins are major drug targets, but their structure determination, a prerequisite for rational drug design, remains challenging. Recently, the DeepMind's AlphaFold2 machine learning method greatly expanded the structural coverage of sequences with high accuracy. Since the employed algorithm did not take specific properties of TM proteins into account, the reliability of the generated TM structures should be assessed. Therefore, we quantitatively investigated the quality of structures at genome scales, at the level of ABC protein superfamily folds and for specific membrane proteins (e.g. dimer modeling and stability in molecular dynamics simulations). We tested template-free structure prediction with a challenging TM CASP14 target and several TM protein structures published after AlphaFold2 training. Our results suggest that AlphaFold2 performs well in the case of TM proteins and its neural network is not overfitted. We conclude that cautious applications of AlphaFold2 structural models will advance TM protein-associated studies at an unexpected level.