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We conclude that iASPP integrates the NF-κBp65 and p53 signaling pathways and thereby regulates cell fate in response to TIS, leading to chemotherapy resistance. These findings suggest that iASPP inhibition might be a strategy that could help restore senescence in cancer cells and improve outcomes of chemotherapy-based therapies. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.Globular protein sequences encode not only functional structures (the native state) but also protein foldability, i.e. a conformational search that is both efficient and robustly minimizes misfolding. Studies of mutations associated with toxic misfolding have yielded insights into molecular determinants of protein foldability. Of particular interest are residues that are conserved yet dispensable in the native state. Here, we exploited the mutant proinsulin syndrome (a major cause of permanent neonatal-onset diabetes mellitus) to investigate whether toxic misfolding poses an evolutionary constraint. Our experiments focused on an invariant aromatic motif (PheB24-PheB25-TyrB26) with complementary roles in native self-assembly and receptor binding. A novel class of mutations provided evidence that insulin can bind to the insulin receptor (IR) in two different modes, distinguished by a “register shift” in this motif, as visualized by molecular dynamics (MD) simulations. Register-shift variants are active but defective in cellular foldability and exquisitely susceptible to fibrillation in vitro Indeed, expression of the corresponding proinsulin variant induced endoplasmic reticulum stress, a general feature of the mutant proinsulin syndrome. Although not present among vertebrate insulin and insulin-like sequences, a prototypical variant ([GlyB24]insulin) was as potent as WT insulin in a rat model of diabetes. Although in MD simulations the shifted register of receptor engagement is compatible with the structure and allosteric reorganization of the IR-signaling complex, our results suggest that this binding mode is associated with toxic misfolding and so is disallowed in evolution. Taurocholic acid The implicit threat of proteotoxicity limits sequence variation among vertebrate insulins and insulin-like growth factors. © 2020 Rege et al.Chemical biology is an emerging field that enables the study and manipulation of biological systems with probes whose reactivities provide structural insights.  The opportunistic fungal pathogen Cryptococcus neoformans possesses a polysaccharide capsule that is a major virulence factor, but is challenging to study. We report here the synthesis of a hydroxylamine-armed fluorescent probe that reacts with reducing glycans and its application to study the architecture of the C. neoformans capsule under a variety of conditions. The probe signal localized intracellularly and at the cell wall-membrane interface, implying the presence of reducing-end glycans at this location where the capsule is attached to the cell body. In contrast, no fluorescence signal was detected in the capsule body. We observed vesicle-like structures containing the reducing-end probe, both intra- and extracellularly, consistent with the importance of vesicles in capsular assembly. Disrupting the capsule with DMSO, ultrasound, or mechanical shear stress resulted in capsule alterations that affected the binding of the probe, as reducing ends were exposed and cell membrane integrity was compromised. Unlike the polysaccharides in the assembled capsule, isolated exopolysaccharides contained reducing ends. The reactivity of the hydroxylamine-armed fluorescent probe suggests a model for capsule assembly whereby reducing ends localize to the cell wall surface, supporting previous findings suggesting that this is an initiation point for capsular assembly. We propose that chemical biology is a promising approach for studying the C. neoformans capsule and its associated polysaccharides to unravel their roles in fungal virulence. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.Eukaryotic cells are compartmentalized to form organelles, whose functions rely on proper phospholipid and protein transport. Here we determined the crystal structure of human VAT-1, a cytosolic soluble protein that was suggested to transfer phosphatidylserine, at 2.2 Å resolution. We found that VAT-1 transferred not only phosphatidylserine but also other acidic phospholipids between membranes in vitro Structure-based mutational analyses showed the presence of a possible lipid-binding cavity at the interface between the two subdomains, and two tyrosine residues in the flexible loops facilitated phospholipid transfer, likely by functioning as a gate to this lipid-binding cavity. We also found that a basic and hydrophobic loop with two tryptophan residues protruded from the molecule and facilitated binding to the acidic-lipid membranes, thereby achieving efficient phospholipid transfer. © 2020 Watanabe et al.Biological systems are inherently complex, and the increasing level of detail with which we are able to experimentally probe such systems continually reveals new complexity. Fortunately, mathematical models are uniquely positioned to provide a tool amenable for rigorous analysis, hypothesis generation, and connecting results from isolated in vitro experiments with results from in vivo and whole organism studies. However, developing useful mathematical models is challenging because of the often different domains of knowledge required in both math and biology. In this work, we endeavor to provide a useful guide for researchers interested in incorporating mathematical modeling into their scientific process. We advocate the use of conceptual diagrams as a starting place to anchor researchers from both domains. These diagrams are useful for simplifying the biological process in question and distinguishing the essential components. Not only do they serve as the basis for developing a variety of mathematical models but they ensure that any mathematical formulation of the biological system is led primarily by scientific questions. We provide a specific example of this process from our own work in studying prion aggregation to show the power of mathematical models to synergistically interact with experiments and push forward biological understanding. Choosing the most suitable model also depends on many different factors and we consider how to make these choices based on different scales of biological organization and available data. We close by discussing the many opportunities that abound for both experimentalists and modelers to take advantage of collaborative work in this field. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.