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Buhlheller, C.

Publications and source records attributed to Buhlheller, C..

3 recordsLinked to original sources

Vibrio cholerae's ToxRS Bile Sensing System

Cholera represents a diarrheal disease caused by the Gram-negative bacterium Vibrio cholerae. Its environmental persistence causing recurring sudden outbreaks is enabled by V. choleraes rapid adaption to changing environments involving sensory proteins like ToxR and ToxS. Located at the inner membrane, ToxR and ToxS react to environmental stimuli like bile acid, thereby inducing survival strategies e.g. bile resistance and virulence regulation. Currently, transcription factor ToxR is described as main environmental sensor for bile acid, whose activity is enhanced by binding to ToxS. Here, the presented crystal structure of the sensory domains of ToxR and ToxS in combination with multiple bile acid interaction studies, reveals that a bile binding pocket of ToxS is only properly folded upon binding to ToxR. These findings support the previously suggested link between ToxRS and VtrAC-like co-component systems. Besides VtrAC, ToxRS is now the only experimentally determined structure within this recently defined superfamily, further emphasizing its significance. In-depth analysis of the ToxRS complex reveals its remarkable conservation across various Vibrio species, underlining the significance of conserved residues in the ToxS barrel and the more diverse ToxR sensory domain. Unraveling the intricate mechanisms governing ToxRSs environmental sensing capabilities, provides a promising tool for disruption of this vital interaction, ultimately inhibiting Vibrios survival and virulence. Our findings hold far-reaching implications for all Vibrio strains that rely on the ToxRS system as a shared sensory cornerstone for adapting to their surroundings.

biochemistry↗

Comparative genomic and crystal structure analyses identify a collagen glucosyltransferase from Acanthamoeba Polyphaga Mimivirus

Humans and Acanthamoeba Polyphaga Mimivirus share numerous homologous genes, including collagens and collagen-modifying enzymes. To explore the homology, we performed a genome-wide comparison between human and mimivirus using DELTA-BLAST (Domain Enhanced Lookup Time Accelerated BLAST) and identified 52 new mimiviral proteins that are homologous with human proteins. To gain functional insights into mimiviral proteins, their human protein homologs were organized into Gene Ontology (GO) and REACTOME pathways to build a functional network. Collagen and collagen-modifying enzymes form the largest subnetwork with most nodes. Further analysis of this subnetwork identified a putative collagen glycosyltransferase R699. Protein expression test suggested that R699 is highly expressed in E coli, unlike the human collagen-modifying enzymes. Enzymatic activity assays showed that R699 catalyzes the conversion of unique galactosylhydroxylysine within the GXXXUG motif (U=galactosylhydroxylysine) to glucosylgalactosylhydroxylysine on collagen using uridine diphosphate glucose (UDP-Glc) as a sugar donor, suggesting R699 is a mimiviral collagen galactosylhydroxylysyl glucosyltransferase (GGT) with defined substrate specificity. Structural study of R699 produced the first crystal structure of a collagen GGT with a visible UDP-Glc. Sugar moiety of the UDP-Glc resides in a previously unrecognized pocket. Mn2+ coordination and nucleoside-diphosphate binding site are conserved among GGT family members and critical for R699s collagen GGT activity. To facilitate further analysis of human and mimiviral homologous proteins, we presented an interactive and searchable genome-wide comparison website for quickly browsing human and Acanthamoeba Polyphaga Mimivirus homologs, which is available at RRID Resource ID: SCR_022140 or https://guolab.shinyapps.io/app-mimivirus-publication/.

biochemistry↗

Accurate prediction of protein structures and interactions using a 3-track network

DeepMind presented remarkably accurate protein structure predictions at the CASP14 conference. We explored network architectures incorporating related ideas and obtained the best performance with a 3-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The 3-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate models of protein-protein complexes from sequence information alone, short circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research. One-Sentence SummaryAccurate protein structure modeling enables rapid solution of structure determination problems and provides insights into biological function.

bioinformatics↗