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1. Using machine learning to predict protein–protein interactions between a zombie ant fungus and its carpenter ant host

   https://doi.org/10.1038/s41598-023-40764-8  

   Will, Ian ; Beckerson, William C. ; de Bekker, Charissa ( December 2023 , Scientific Reports)

   Parasitic fungi produce proteins that modulate virulence, alter host physiology, and trigger host responses. These proteins, classified as a type of “effector,” often act via protein–protein interactions (PPIs). The fungal parasiteOphiocordyceps camponoti-floridani(zombie ant fungus) manipulatesCamponotus floridanus(carpenter ant) behavior to promote transmission. The most striking aspect of this behavioral change is a summit disease phenotype where infected hosts ascend and attach to an elevated position. Plausibly, interspecific PPIs drive aspects ofOphiocordycepsinfection and host manipulation. Machine learning PPI predictions offer high-throughput methods to produce mechanistic hypotheses on how this behavioral manipulation occurs. Using D-SCRIPT to predict host–parasite PPIs, we found ca. 6000 interactions involving 2083 host proteins and 129 parasite proteins, which are encoded by genes upregulated during manipulated behavior. We identified multiple overrepresentations of functional annotations among these proteins. The strongest signals in the host highlighted neuromodulatory G-protein coupled receptors and oxidation–reduction processes. We also detectedCamponotusstructural and gene-regulatory proteins. In the parasite, we found enrichment ofOphiocordycepsproteases and frequent involvement of novel small secreted proteins with unknown functions. From these results, we provide new hypotheses on potential parasite effectors and host targets underlying zombie ant behavioral manipulation.

    

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2. Chlorovirus PBCV-1 protein A064R has three of the transferase activities necessary to synthesize its capsid protein N-linked glycans

   https://doi.org/10.1073/pnas.2016626117  

   Speciale, Immacolata ; Laugieri, Maria Elena ; Noel, Eric ; Lin, Sicheng ; Lowary, Todd L. ; Molinaro, Antonio ; Duncan, Garry A. ; Agarkova, Irina V. ; Garozzo, Domenico ; Tonetti, Michela G. ; et al ( November 2020 , Proceedings of the National Academy of Sciences)

   null (Ed.)

   Paramecium bursaria chlorella virus-1 (PBCV-1) is a large double-stranded DNA (dsDNA) virus that infects the unicellular green alga Chlorella variabilis NC64A. Unlike many other viruses, PBCV-1 encodes most, if not all, of the enzymes involved in the synthesis of the glycans attached to its major capsid protein. Importantly, these glycans differ from those reported from the three domains of life in terms of structure and asparagine location in the sequon of the protein. Previous data collected from 20 PBCV-1 spontaneous mutants (or antigenic variants) suggested that the a064r gene encodes a glycosyltransferase (GT) with three domains, each with a different function. Here, we demonstrate that: domain 1 is a β- l -rhamnosyltransferase; domain 2 is an α- l -rhamnosyltransferase resembling only bacterial proteins of unknown function, and domain 3 is a methyltransferase that methylates the C-2 hydroxyl group of the terminal α- l -rhamnose (Rha) unit. We also establish that methylation of the C-3 hydroxyl group of the terminal α- l -Rha is achieved by another virus-encoded protein A061L, which requires an O-2 methylated substrate. This study, thus, identifies two of the glycosyltransferase activities involved in the synthesis of the N -glycan of the viral major capsid protein in PBCV-1 and establishes that a single protein A064R possesses the three activities needed to synthetize the 2-OMe-α- l -Rha-(1→2)-β- l -Rha fragment. Remarkably, this fragment can be attached to any xylose unit. 

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3. Performance and Its Limits in Rigid Body Protein-Protein Docking

   https://doi.org/10.1016/j.str.2020.06.006  

   Desta, Israel T. ; Porter, Kathryn A. ; Xia, Bing ; Kozakov, Dima ; Vajda, Sandor ( September 2020 , Structure)

   null (Ed.)
4. Use of a solid‐state nanopore for profiling the transferrin receptor protein and distinguishing between transferrin receptor and its ligand protein

   https://doi.org/10.1002/elps.202200147  

   O'Donohue, Matthew ; Saharia, Jugal ; Bandara, Nuwan ; Alexandrakis, Georgios ; Kim, Min Jun ( December 2022 , ELECTROPHORESIS)

   A nanopore device is capable of providing single‐molecule level information of an analyte as they translocate through the sensing aperture—a nanometer‐sized through‐hole—under the influence of an applied electric field. In this study, a silicon nitride (Si_xN_y)‐based nanopore was used to characterize the human serum transferrin receptor protein (TfR) under various applied voltages. The presence of dimeric forms of TfR was found to decrease exponentially as the applied electric field increased. Further analysis of monomeric TfR also revealed that its unfolding behaviors were positively dependent on the applied voltage. Furthermore, a comparison between the data of monomeric TfR and its ligand protein, human serum transferrin (hSTf), showed that these two protein populations, despite their nearly identical molecular weights, could be distinguished from each other by means of a solid‐state nanopore (SSN). Lastly, the excluded volumes of TfR were experimentally determined at each voltage and were found to be within error of their theoretical values. The results herein demonstrate the successful application of an SSN for accurately classifying monomeric and dimeric molecules while the two populations coexist in a heterogeneous mixture.

    

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5. Allosterically coupled conformational dynamics in solution prepare the sterol transfer protein StarD4 to release its cargo upon interaction with target membranes

   https://doi.org/10.3389/fmolb.2023.1197154  

   Xie, Hengyi ; Weinstein, Harel ( May 2023 , Frontiers in Molecular Biosciences)

   Complex mechanisms regulate the cellular distribution of cholesterol, a critical component of eukaryote membranes involved in regulation of membrane protein functions directly and through the physiochemical properties of membranes. StarD4, a member of the steroidogenic acute regulator-related lipid-transfer (StART) domain (StARD)-containing protein family, is a highly efficient sterol-specific transfer protein involved in cholesterol homeostasis. Its mechanism of cargo loading and release remains unknown despite recent insights into the key role of phosphatidylinositol phosphates in modulating its interactions with target membranes. We have used large-scale atomistic Molecular dynamics (MD) simulations to study how the dynamics of cholesterol bound to the StarD4 protein can affect interaction with target membranes, and cargo delivery. We identify the two major cholesterol (CHL) binding modes in the hydrophobic pocket of StarD4, one near S136&S147 (the Ser-mode), and another closer to the putative release gate located near W171, R92&Y117 (the Trp-mode). We show that conformational changes of StarD4 associated directly with the transition between these binding modes facilitate the opening of the gate. To understand the dynamics of this connection we apply a machine-learning algorithm for the detection of rare events in MD trajectories (RED), which reveals the structural motifs involved in the opening of a front gate and a back corridor in the StarD4 structure occurring together with the spontaneous transition of CHL from the Ser-mode of binding to the Trp-mode. Further analysis of MD trajectory data with the information-theory based NbIT method reveals the allosteric network connecting the CHL binding site to the functionally important structural components of the gate and corridor. Mutations of residues in the allosteric network are shown to affect the performance of the allosteric connection. These findings outline an allosteric mechanism which prepares the CHL-bound StarD4 to release and deliver the cargo when it is bound to the target membrane.

    

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