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- Anion Transport System (1)
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The traffic AAA-ATPase PilF is essential for pilus biogenesis and natural transformation of Thermus thermophilus HB27. Recently, we showed that PilF forms hexameric complexes containing six zinc atoms coordinated by conserved tetracysteine motifs. Here we report that zinc binding is essential for complex stability. However, zinc binding is neither required for pilus biogenesis nor natural transformation. A number of the mutants did not exhibit any pili during growth at 64 °C but still were transformable. This leads to the conclusion that type 4 pili and the DNA translocator are distinct systems. At lower growth temperatures (55 °C) the zinc-depleted multiple cysteine mutants were hyperpiliated but defective in pilus-mediated twitching motility. This provides evidence that zinc binding is essential for the role of PilF in pilus dynamics. Moreover, we found that zinc binding is essential for complex stability but dispensable for ATPase activity. In contrast to many polymerization ATPases from mesophilic bacteria, ATP binding is not required for PilF complex formation; however, it significantly increases complex stability. These data suggest that zinc and ATP binding increase complex stability that is important for functionality of PilF under extreme environmental conditions.
The anion transport protein of the human erythrocyte membrane, band 3, was solubilized and purified in solutions of the non-ionic detergent nonaethylene glycol lauryl ether and then reconstituted in spherical egg phosphatidylcholine bilayers as described earlier (U. Scheuring, K. Kollewe, W. Haase, and D. Schubert, J. Membrane Biol. 90, 123-135 (1986)). The resulting paucilamellar proteoliposom es of average diameter 70 nm were transformed into smaller vesicles by French press treatment and fractionated according to size by gel filtration. The smallest protein-containing liposomes obtained had diameters around 32 nm; still smaller vesicles were free of protein. All proteoliposome samples studied showed a rapid sulfate efflux which was sensitive to specific inhibitors of band 3-mediated anion exchange. In addition, the orientation of the transport protein in the vesicle membranes was found to be “right-side-out” in all samples. This suggests that the orientation of the protein in the vesicle membranes is dictated by the shape of the protein’s intramembrane domain and that this domain has the form of a truncated cone or pyramid.
The interaction between the Heat Shock Proteins 70 and 40 is at the core of the ATPase regulation of the chaperone machinery that maintains protein homeostasis. However, the structural details of this fundamental interaction are still elusive and contrasting models have been proposed for the transient Hsp70/Hsp40 complexes. Here we combine molecular simulations based on both coarsegrained and atomistic models with co-evolutionary sequence analysis to shed light on this problem by focusing on the bacterial DnaK/DnaJ system. The integration of these complementary approaches resulted into a novel structural model that rationalizes previous experimental observations. We identify an evolutionary-conserved interaction surface formed by helix II of the DnaJ J-domain and a groove on lobe IIA of the DnaK nucleotide binding domain, involving the inter-domain linker.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.