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Cryo-electron tomography (CryoET) resolves individual macromolecules inside living cells. However, the complex composition and high density of cells challenge the faithful identification of features in tomograms. Here, we capitalize on recent advances in electron tomography and demonstrate that 3D template matching (TM) localizes a wide range of structures inside crowded eukaryotic cells with confidence 10 to 100-fold above the noise level. We establish a TM pipeline with systematically tuned parameters for automated, objective and comprehensive feature identification. High-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, lipid membranes and microtubules, and individual subunits, demonstrate that TM is generic. We resolve ~100-kDa proteins, connect the functional states of complexes to their cellular localization, and capture vaults carrying ribosomal cargo in situ. By capturing individual molecular events inside living cells with defined statistical confidence, high-confidence TM greatly speeds up the CryoET workflow and sets the stage for visual proteomics.
Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments
(2021)
Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation–maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient. We test how well a dataset conforms to the assumptions of a diffusion model and determine the optimal number of subpopulations with the help of a quality factor of known analytical distribution. To facilitate use by practitioners, we provide a fast open-source implementation of the theory for the efficient analysis of multiple trajectories in arbitrary dimensions simultaneously.
During infection the SARS-CoV-2 virus fuses its viral envelope with cellular membranes of its human host. The viral spike (S) protein mediates both the initial contact with the host cell and the subsequent membrane fusion. Proteolytic cleavage of S at the S2′ site exposes its fusion peptide (FP) as the new N-terminus. By binding to the host membrane, the FP anchors the virus to the host cell. The reorganization of S2 between virus and host then pulls the two membranes together. Here we use molecular dynamics (MD) simulations to study the two core functions of the SARS-CoV-2 FP: to attach quickly to cellular membranes and to form an anchor strong enough to withstand the mechanical force during membrane fusion. In eight 10 μs long MD simulations of FP in proximity to endosomal and plasma membranes, we find that FP binds spontaneously to the membranes and that binding proceeds predominantly by insertion of two short amphipathic helices into the membrane interface. Connected via a flexible linker, the two helices can bind the membrane independently, yet binding of one promotes the binding of the other by tethering it close to the target membrane. By simulating mechanical pulling forces acting on the C-terminus of the FP, we then show that the bound FP can bear forces up to 250 pN before detaching from the membrane. This detachment force is more than 10-fold higher than an estimate of the force required to pull host and viral membranes together for fusion. We identify a fully conserved disulfide bridge in the FP as a major factor for the high mechanical stability of the FP membrane anchor. We conclude, first, that the sequential binding of two short amphipathic helices allows the SARS-CoV-2 FP to insert quickly into the target membrane, before the virion is swept away after shedding the S1 domain connecting it to the host cell receptor. Second, we conclude that the double attachment and the conserved disulfide bridge establish the strong anchoring required for subsequent membrane fusion. Multiple distinct membrane-anchoring elements ensure high avidity and high mechanical strength of FP–membrane binding.
Famotidine inhibits toll-like receptor 3-mediated inflammatory signaling in SARS-CoV-2 infection
(2021)
Apart from prevention using vaccinations, the management options for COVID-19 remain limited. In retrospective cohort studies, use of famotidine, a specific oral H2 receptor antagonist (antihistamine), has been associated with reduced risk of intubation and death in patients hospitalized with COVID-19. In a case series, nonhospitalized patients with COVID-19 experienced rapid symptom resolution after taking famotidine, but the molecular basis of these observations remains elusive. Here we show using biochemical, cellular, and functional assays that famotidine has no effect on viral replication or viral protease activity. However, famotidine can affect histamine-induced signaling processes in infected Caco2 cells. Specifically, famotidine treatment inhibits histamine-induced expression of Toll-like receptor 3 (TLR3) in SARS-CoV-2 infected cells and can reduce TLR3-dependent signaling processes that culminate in activation of IRF3 and the NF-κB pathway, subsequently controlling antiviral and inflammatory responses. SARS-CoV-2-infected cells treated with famotidine demonstrate reduced expression levels of the inflammatory mediators CCL-2 and IL6, drivers of the cytokine release syndrome that precipitates poor outcome for patients with COVID-19. Given that pharmacokinetic studies indicate that famotidine can reach concentrations in blood that suffice to antagonize histamine H2 receptors expressed in mast cells, neutrophils, and eosinophils, these observations explain how famotidine may contribute to the reduced histamine-induced inflammation and cytokine release, thereby improving the outcome for patients with COVID-19.
New drugs are urgently needed to combat the global TB epidemic. Targeting simultaneously multiple respiratory enzyme complexes of Mycobacterium tuberculosis is regarded as one of the most effective treatment options to shorten drug administration regimes, and reduce the opportunity for the emergence of drug resistance. During infection and proliferation, the cytochrome bd oxidase plays a crucial role for mycobacterial pathophysiology by maintaining aerobic respiration at limited oxygen concentrations. Here, we present the cryo-EM structure of the cytochrome bd oxidase from M. tuberculosis at 2.5 Å. In conjunction with atomistic molecular dynamics (MD) simulation studies we discovered a previously unknown MK-9-binding site, as well as a unique disulfide bond within the Q-loop domain that defines an inactive conformation of the canonical quinol oxidation site in Actinobacteria. Our detailed insights into the long-sought atomic framework of the cytochrome bd oxidase from M. tuberculosis will form the basis for the design of highly specific drugs to act on this enzyme.
The plasma membrane (PM) is composed of a complex lipid mixture that forms heterogeneous membrane environments. Yet, how small-scale lipid organization controls physiological events at the PM remains largely unknown. Here, we show that ORP-related Osh lipid exchange proteins are critical for the synthesis of phosphatidylinositol (4,5)-bisphosphate [PI(4,5)P2], a key regulator of dynamic events at the PM. In real-time assays, we find that unsaturated phosphatidylserine (PS) and sterols, both Osh protein ligands, synergistically stimulate phosphatidylinositol 4-phosphate 5-kinase (PIP5K) activity. Biophysical FRET analyses suggest an unconventional co-distribution of unsaturated PS and phosphatidylinositol 4-phosphate (PI4P) species in sterol-containing membrane bilayers. Moreover, using in vivo imaging approaches and molecular dynamics simulations, we show that Osh protein-mediated unsaturated PI4P and PS membrane lipid organization is sensed by the PIP5K specificity loop. Thus, ORP family members create a nanoscale membrane lipid environment that drives PIP5K activity and PI(4,5)P2 synthesis that ultimately controls global PM organization and dynamics.
Complex I couples the free energy released from quinone (Q) reduction to pump protons across the biological membrane in the respiratory chains of mitochondria and many bacteria. The Q reduction site is separated by a large distance from the proton-pumping membrane domain. To address the molecular mechanism of this long-range proton-electron coupling, we perform here full atomistic molecular dynamics simulations, free energy calculations, and continuum electrostatics calculations on complex I from Thermus thermophilus. We show that the dynamics of Q is redox-state-dependent, and that quinol, QH2, moves out of its reduction site and into a site in the Q tunnel that is occupied by a Q analog in a crystal structure of Yarrowia lipolytica. We also identify a second Q-binding site near the opening of the Q tunnel in the membrane domain, where the Q headgroup forms strong interactions with a cluster of aromatic and charged residues, while the Q tail resides in the lipid membrane. We estimate the effective diffusion coefficient of Q in the tunnel, and in turn the characteristic time for Q to reach the active site and for QH2 to escape to the membrane. Our simulations show that Q moves along the Q tunnel in a redox-state-dependent manner, with distinct binding sites formed by conserved residue clusters. The motion of Q to these binding sites is proposed to be coupled to the proton-pumping machinery in complex I.
We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala5, and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.
Transition path sampling is a powerful tool in the study of rare events. Shooting trial trajectories from configurations along existing transition paths proved particularly efficient in the sampling of reactive trajectories. However, most shooting attempts tend not to result in transition paths, in particular in cases where the transition dynamics has diffusive character. To overcome the resulting efficiency problem, we developed an algorithm for “shooting from the top.” We first define a shooting range through which all paths have to pass and then shoot off trial trajectories only from within this range. For a well chosen shooting range, nearly every shot is successful, resulting in an accepted transition path. To deal with multiple mechanisms, weighted shooting ranges can be used. To cope with the problem of unsuitably placed shooting ranges, we developed an algorithm that iteratively improves the location of the shooting range. The transition path sampling procedure is illustrated for models of diffusive and Langevin dynamics. The method should be particularly useful in cases where the transition paths are long so that only relatively few shots are possible, yet reasonable order parameters are known.