Wall teichoic acid substitution with glucose governs phage susceptibility of Staphylococcus epidermidis.

The species- and clone-specific susceptibility of Staphylococcus cells for bacteriophages is governed by the structures and glycosylation patterns of wall teichoic acid (WTA) glycopolymers. The glycosylation-dependent phage-WTA interactions in the opportunistic pathogen Staphylococcus epidermidis and in other coagulase-negative staphylococci (CoNS) have remained unknown. We report a new S. epidermidis WTA glycosyltransferase TagE whose deletion confers resistance to siphoviruses such as ΦE72 but enables binding of otherwise unbound podoviruses. S. epidermidis glycerolphosphate WTA was found to be modified with glucose in a tagE-dependent manner. TagE is encoded together with the enzymes PgcA and GtaB providing uridine diphosphate-activated glucose. ΦE72 transduced several other CoNS species encoding TagE homologs, suggesting that WTA glycosylation via TagE is a frequent trait among CoNS that permits interspecies horizontal gene transfer. Our study unravels a crucial mechanism of phage-Staphylococcus interaction and horizontal gene transfer, and it will help in the design of anti-staphylococcal phage therapies.IMPORTANCEPhages are highly specific for certain bacterial hosts, and some can transduce DNA even across species boundaries. How phages recognize cognate host cells remains incompletely understood. Phages infecting members of the genus Staphylococcus bind to wall teichoic acid (WTA) glycopolymers with highly variable structures and glycosylation patterns. How WTA is glycosylated in the opportunistic pathogen Staphylococcus epidermidis and in other coagulase-negative staphylococci (CoNS) species has remained unknown. We describe that S. epidermidis glycosylates its WTA backbone with glucose, and we identify a cluster of three genes responsible for glucose activation and transfer to WTA. Their inactivation strongly alters phage susceptibility patterns, yielding resistance to siphoviruses but susceptibility to podoviruses. Many different CoNS species with related glycosylation genes can exchange DNA via siphovirus ΦE72, suggesting that glucose-modified WTA is crucial for interspecies horizontal gene transfer. Our finding will help to develop antibacterial phage therapies and unravel routes of genetic exchange.

Transition to anomalous dynamics in a simple random map.

The famous doubling map (or dyadic transformation) is perhaps the simplest deterministic dynamical system exhibiting chaotic dynamics. It is a piecewise linear time-discrete map on the unit interval with a uniform slope larger than one, hence expanding, with a positive Lyapunov exponent and a uniform invariant density. If the slope is less than one, the map becomes contracting, the Lyapunov exponent is negative, and the density trivially collapses onto a fixed point. Sampling from these two different types of maps at each time step by randomly selecting the expanding one with probability p, and the contracting one with probability 1-p, gives a prototype of a random dynamical system. Here, we calculate the invariant density of this simple random map, as well as its position autocorrelation function, analytically and numerically under variation of p. We find that the map exhibits a non-trivial transition from fully chaotic to completely regular dynamics by generating a long-time anomalous dynamics at a critical sampling probability pc, defined by a zero Lyapunov exponent. This anomalous dynamics is characterized by an infinite invariant density, weak ergodicity breaking, and power-law correlation decay.

Phage susceptibility determinants of the opportunistic pathogen Staphylococcus epidermidis.

Staphylococcus epidermidis is a common member of the human skin and nose microbiomes and a frequent cause of invasive infections. Transducing phages accomplish the horizontal transfer of resistance and virulence genes by mispackaging of mobile-genetic elements, contributing to severe, therapy-refractory S. epidermidis infections. Lytic phages on the other hand can be interesting candidates for new anti-S. epidermidis phage therapies. Despite the importance of phages, we are only beginning to unravel S. epidermidis phage interactions. Recent studies shed new light on S. epidermidis phage diversity, host range, and receptor specificities. Modulation of cell wall teichoic acids, the major phage receptor structures, along with other phage defense mechanisms, are crucial determinants for S. epidermidis susceptibility to different phage groups.

Invasive Staphylococcus epidermidis uses a unique processive wall teichoic acid glycosyltransferase to evade immune recognition.

Staphylococcus epidermidis expresses glycerol phosphate wall teichoic acid (WTA), but some health care-associated methicillin-resistant S. epidermidis (HA-MRSE) clones produce a second, ribitol phosphate (RboP) WTA, resembling that of the aggressive pathogen Staphylococcus aureus. RboP-WTA promotes HA-MRSE persistence and virulence in bloodstream infections. We report here that the TarM enzyme of HA-MRSE [TarM(Se)] glycosylates RboP-WTA with glucose, instead of N-acetylglucosamine (GlcNAc) by TarM(Sa) in S. aureus. Replacement of GlcNAc with glucose in RboP-WTA impairs HA-MRSE detection by human immunoglobulin G, which may contribute to the immune-evasion capacities of many invasive S. epidermidis. Crystal structures of complexes with uridine diphosphate glucose (UDP-glucose), and with UDP and glycosylated poly(RboP), reveal the binding mode and glycosylation mechanism of this enzyme and explain why TarM(Se) and TarM(Sa) link different sugars to poly(RboP). These structural data provide evidence that TarM(Se) is a processive WTA glycosyltransferase. Our study will support the targeted inhibition of TarM enzymes, and the development of RboP-WTA targeting vaccines and phage therapies.

The Onset of Molecule-Spanning Dynamics in Heat Shock Protein Hsp90.

Protein dynamics have been investigated on a wide range of time scales. Nano- and picosecond dynamics have been assigned to local fluctuations, while slower dynamics have been attributed to larger conformational changes. However, it is largely unknown how fast (local) fluctuations can lead to slow global (allosteric) changes. Here, fast molecule-spanning dynamics on the 100 to 200 ns time scale in the heat shock protein 90 (Hsp90) are shown. Global real-space movements are assigned to dynamic modes on this time scale, which is possible by a combination of single-molecule fluorescence, quasi-elastic neutron scattering and all-atom molecular dynamics (MD) simulations. The time scale of these dynamic modes depends on the conformational state of the Hsp90 dimer. In addition, the dynamic modes are affected to various degrees by Sba1, a co-chaperone of Hsp90, depending on the location within Hsp90, which is in very good agreement with MD simulations. Altogether, this data is best described by fast molecule-spanning dynamics, which precede larger conformational changes in Hsp90 and might be the molecular basis for allostery. This integrative approach provides comprehensive insights into molecule-spanning dynamics on the nanosecond time scale for a multi-domain protein.

Biophysical Determinants for the Viscosity of Concentrated Monoclonal Antibody Solutions.

Monoclonal antibodies (mAbs) are particularly relevant for therapeutics due to their high specificity and versatility, and mAb-based drugs are hence used to treat numerous diseases. The increased patient compliance of self-administration motivates the formulation of products for subcutaneous (SC) administration. The associated challenge is to formulate highly concentrated antibody solutions to achieve a significant therapeutic effect, while limiting their viscosity and preserving their physicochemical stability. Protein-protein interactions (PPIs) are in fact the root cause of several potential problems concerning the stability, manufacturability, and delivery of a drug product. The understanding of macroscopic viscosity requires an in-depth knowledge on protein diffusion, PPIs, and self-association/aggregation. Here, we study the self-diffusion of different mAbs of the IgG1 subtype in aqueous solution as a function of the concentration and temperature by quasi-elastic neutron scattering (QENS). QENS allows us to probe the short-time self-diffusion of the molecules and therefore to determine the hydrodynamic mAb cluster size and to gain information on the internal mAb dynamics. Small-angle neutron scattering (SANS) is jointly employed to probe structural details and to understand the nature and intensity of PPIs. Complementary information is provided by molecular dynamics (MD) simulations and viscometry, thus obtaining a comprehensive picture of mAb diffusion.

Molecular mechanisms underlying adverse effects of dexamethasone and betamethasone in the developing cardiovascular system.

Antenatal glucocorticoids accelerate fetal lung maturation and reduce mortality in preterm babies but can trigger adverse effects on the cardiovascular system. The mechanisms underlying off-target effects of the synthetic glucocorticoids mostly used, Dexamethasone (Dex) and Betamethasone (Beta), are unknown. We investigated effects of Dex and Beta on cardiovascular structure and function, and underlying molecular mechanism using the chicken embryo, an established model system to isolate effects of therapy on the developing heart and vasculature, independent of effects on the mother or placenta. Fertilized eggs were treated with Dex (0.1 mg kg-1 ), Beta (0.1 mg kg-1 ), or water vehicle (Control) on embryonic day 14 (E14, term = 21 days). At E19, biometry, cardiovascular function, stereological, and molecular analyses were determined. Both glucocorticoids promoted growth restriction, with Beta being more severe. Beta compared with Dex induced greater cardiac diastolic dysfunction and also impaired systolic function. While Dex triggered cardiomyocyte hypertrophy, Beta promoted a decrease in cardiomyocyte number. Molecular changes of Dex on the developing heart included oxidative stress, activation of p38, and cleaved caspase 3. In contrast, impaired GR downregulation, activation of p53, p16, and MKK3 coupled with CDK2 transcriptional repression linked the effects of Beta on cardiomyocyte senescence. Beta but not Dex impaired NO-dependent relaxation of peripheral resistance arteries. Beta diminished contractile responses to potassium and phenylephrine, but Dex enhanced peripheral constrictor reactivity to endothelin-1. We conclude that Dex and Beta have direct differential detrimental effects on the developing cardiovascular system.

From an Hsp90 - binding protein to a peptide drug.

The Lpl proteins represent a class of lipoproteins that was first described in the opportunistic bacterial pathogen Staphylococcus aureus, where they contribute to pathogenicity by enhancing F-actin levels of host epithelial cells and thereby increasing S. aureus internalization. The model Lpl protein, Lpl1 was shown to interact with the human heat shock proteins Hsp90α and Hsp90ß, suggesting that this interaction may trigger all observed activities. Here we synthesized Lpl1-derived peptides of different lengths and identified two overlapping peptides, namely, L13 and L15, which interacted with Hsp90α. Unlike Lpl1, the two peptides not only decreased F-actin levels and S. aureus internalization in epithelial cells but they also decreased phagocytosis by human CD14+ monocytes. The well-known Hsp90 inhibitor, geldanamycin, showed a similar effect. The peptides not only interacted directly with Hsp90α, but also with the mother protein Lpl1. While L15 and L13 significantly decreased lethality of S. aureus bacteremia in an insect model, geldanamycin did not. In a mouse bacteremia model L15 was found to significantly decreased weight loss and lethality. Although the molecular bases of the L15 effect is still elusive, in vitro data indicate that simultaneous treatment of host immune cells with L15 or L13 and S. aureus significantly increase IL-6 production. L15 and L13 represent not antibiotics but they cause a significant reduction in virulence of multidrug-resistant S. aureus strains in in vivo models. In this capacity, they can be an important drug alone or additive with other agents.

Diffusive Dynamics of Bacterial Proteome as a Proxy of Cell Death.

Temperature variations have a big impact on bacterial metabolism and death, yet an exhaustive molecular picture of these processes is still missing. For instance, whether thermal death is determined by the deterioration of the whole or a specific part of the proteome is hotly debated. Here, by monitoring the proteome dynamics of E. coli, we clearly show that only a minor fraction of the proteome unfolds at the cell death. First, we prove that the dynamical state of the E. coli proteome is an excellent proxy for temperature-dependent bacterial metabolism and death. The proteome diffusive dynamics peaks at about the bacterial optimal growth temperature, then a dramatic dynamical slowdown is observed that starts just below the cell's death temperature. Next, we show that this slowdown is caused by the unfolding of just a small fraction of proteins that establish an entangling interprotein network, dominated by hydrophobic interactions, across the cytoplasm. Finally, the deduced progress of the proteome unfolding and its diffusive dynamics are both key to correctly reproduce the E. coli growth rate.

Information Shift Dynamics Described by Tsallis q = 3 Entropy on a Compact Phase Space.

Recent mathematical investigations have shown that under very general conditions, exponential mixing implies the Bernoulli property. As a concrete example of statistical mechanics that are exponentially mixing we consider the Bernoulli shift dynamics by Chebyshev maps of arbitrary order N≥2, which maximizes Tsallis q=3 entropy rather than the ordinary q=1 Boltzmann-Gibbs entropy. Such an information shift dynamics may be relevant in a pre-universe before ordinary space-time is created. We discuss symmetry properties of the coupled Chebyshev systems, which are different for even and odd N. We show that the value of the fine structure constant αel=1/137 is distinguished as a coupling constant in this context, leading to uncorrelated behaviour in the spatial direction of the corresponding coupled map lattice for N=3.

Short-Time Transport Properties of Bidisperse Suspensions of Immunoglobulins and Serum Albumins Consistent with a Colloid Physics Picture.

The crowded environment of biological systems such as the interior of living cells is occupied by macromolecules with a broad size distribution. This situation of polydispersity might influence the dependence of the diffusive dynamics of a given tracer macromolecule in a monodisperse solution on its hydrodynamic size and on the volume fraction. The resulting size dependence of diffusive transport crucially influences the function of a living cell. Here, we investigate a simplified model system consisting of two constituents in aqueous solution, namely, of the proteins bovine serum albumin (BSA) and bovine polyclonal gamma-globulin (Ig), systematically depending on the total volume fraction and ratio of these constituents. From high-resolution quasi-elastic neutron spectroscopy, the separate apparent short-time diffusion coefficients for BSA and Ig in the mixture are extracted, which show substantial deviations from the diffusion coefficients measured in monodisperse solutions at the same total volume fraction. These deviations can be modeled quantitatively using results from the short-time rotational and translational diffusion in a two-component hard sphere system with two distinct, effective hydrodynamic radii. Thus, we find that a simple colloid picture well describes short-time diffusion in binary mixtures as a function of the mixing ratio and the total volume fraction. Notably, the self-diffusion of the smaller protein BSA in the mixture is faster than the diffusion in a pure BSA solution, whereas the self-diffusion of Ig in the mixture is slower than in the pure Ig solution.

Data-driven load profiles and the dynamics of residential electricity consumption.

The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance.

Spatial heterogeneity of air pollution statistics in Europe.

Air pollution is one of the leading causes of death globally, and continues to have a detrimental effect on our health. In light of these impacts, an extensive range of statistical modelling approaches has been devised in order to better understand air pollution statistics. However, the time-varying statistics of different types of air pollutants are far from being fully understood. The observed probability density functions (PDFs) of concentrations depend very much on the spatial location and on the pollutant substance. In this paper, we analyse a large variety of data from 3544 different European monitoring sites and show that the PDFs of nitric oxide (NO), nitrogen dioxide ([Formula: see text]) and particulate matter ([Formula: see text] and [Formula: see text]) concentrations generically exhibit heavy tails and are asymptotically well approximated by q-exponential distributions with a given width parameter [Formula: see text]. We observe that the power-law parameter q and the width parameter [Formula: see text] vary widely for the different spatial locations. For each substance, we find different patterns of parameter clouds in the [Formula: see text] plane. These depend on the type of pollutants and on the environmental characteristics (urban/suburban/rural/traffic/industrial/background). This means the effective statistical physics description of air pollution exhibits a strong degree of spatial heterogeneity.

Machine learning approach towards explaining water quality dynamics in an urbanised river.

Human activities alter river water quality and quantity, with consequences for the ecosystems of urbanised rivers. Quantifying the role of human-induced drivers in controlling spatio-temporal patterns in water quality is critical to develop successful strategies for improving the ecological health of urban rivers. Here, we analyse high-frequency electrical conductivity and temperature data collected from the River Chess in South-East England during a Citizen Science project. Utilizing machine learning, we find that boosted trees outperform GAM and accurately describe water quality dynamics with less than 1% error. SHapley Additive exPlanations reveal the importance of and the (inter)dependencies between the individual variables, such as river level and Wastewater Treatment Works (WWTW) outflow. WWTW outflows give rise to diurnal variations in electrical conductivity, which are detectable throughout the year, and to an increase in average water temperature of 1 [Formula: see text] in a 2 km reach downstream of the wastewater treatment works during low flows. Overall, we showcase how high-frequency water quality measurements initiated by a Citizen Science project, together with machine learning techniques, can help untangle key drivers of water quality dynamics in an urbanised chalk stream.

High-resolution Neutron Spectroscopy to Study Picosecond-nanosecond Dynamics of Proteins and Hydration Water.

Neutron scattering offers the possibility to probe the dynamics within samples for a wide range of energies in a nondestructive manner and without labeling other than deuterium. In particular, neutron backscattering spectroscopy records the scattering signals at multiple scattering angles simultaneously and is well suited to study the dynamics of biological systems on the ps-ns timescale. By employing D2O-and possibly deuterated buffer components-the method allows monitoring of both center-of-mass diffusion and backbone and side-chain motions (internal dynamics) of proteins in liquid state. Additionally, hydration water dynamics can be studied by employing powders of perdeuterated proteins hydrated with H2O. This paper presents the workflow employed on the instrument IN16B at the Institut Laue-Langevin (ILL) to investigate protein and hydration water dynamics. The preparation of solution samples and hydrated protein powder samples using vapor exchange is explained. The data analysis procedure for both protein and hydration water dynamics is described for different types of datasets (quasielastic spectra or fixed-window scans) that can be obtained on a neutron backscattering spectrometer. The method is illustrated with two studies involving amyloid proteins. The aggregation of lysozyme into µm sized spherical aggregates-denoted particulates-is shown to occur in a one-step process on the space and time range probed on IN16B, while the internal dynamics remains unchanged. Further, the dynamics of hydration water of tau was studied on hydrated powders of perdeuterated protein. It is shown that translational motions of water are activated upon the formation of amyloid fibers. Finally, critical steps in the protocol are discussed as to how neutron scattering is positioned regarding the study of dynamics with respect to other experimental biophysical methods.

Dynamics of Apolipoprotein B-100 in Interaction with Detergent Probed by Incoherent Neutron Scattering.

Apolipoprotein B-100 (apo B-100) is the protein moiety of both low- and very-low-density lipoproteins, whose role is crucial to cholesterol and triglyceride transport. Aiming at the molecular dynamics' details of apo B-100, scarcely studied, we performed elastic and quasi-elastic incoherent neutron scattering (EINS, QENS) experiments combining different instruments and time scales. Similar to classical membrane proteins, the solubilization results in remaining detergent, here Nonidet P-40 (NP40). Therefore, we propose a framework for QENS studies of protein-detergent complexes, with the introduction of a combined model, including the experimental apo B-100/NP40 ratio. Relying on the simultaneous analysis of all QENS amplitudes, this approach is sensitive enough to separate both contributions. Its application identified two points: (i) apo B-100 slow dynamics and (ii) the acceleration of NP40 dynamics in the presence of apo B-100. Direct translation of the exposed methodology now makes the investigation of more membrane proteins by neutron spectroscopy achievable.

Molecular Flexibility of Antibodies Preserved Even in the Dense Phase after Macroscopic Phase Separation.

Antibody therapies are typically based on high-concentration formulations that need to be administered subcutaneously. These conditions induce several challenges, inter alia a viscosity suitable for injection, sufficient solution stability, and preservation of molecular function. To obtain systematic insights into the molecular factors, we study the dynamics on the molecular level under strongly varying solution conditions. In particular, we use solutions of antibodies with poly(ethylene glycol), in which simple cooling from room temperature to freezing temperatures induces a transition from a well-dispersed solution into a phase-separated and macroscopically arrested system. Using quasi-elastic neutron scattering during in situ cooling ramps and in prethermalized measurements, we observe a strong decrease in antibody diffusion, while internal flexibility persists to a significant degree, thus ensuring the movement necessary for the preservation of molecular function. These results are relevant for a more dynamic understanding of antibodies in high-concentration formulations, which affects the formation of transient clusters governing the solution viscosity.

Temperature and salt controlled tuning of protein clusters.

The formation of molecular assemblies in protein solutions is of strong interest both from a fundamental viewpoint and for biomedical applications. While ordered and desired protein assemblies are indispensable for some biological functions, undesired protein condensation can induce serious diseases. As a common cofactor, the presence of salt ions is essential for some biological processes involving proteins, and in aqueous suspensions of proteins can also give rise to complex phase diagrams including homogeneous solutions, large aggregates, and dissolution regimes. Here, we systematically study the cluster formation approaching the phase separation in aqueous solutions of the globular protein BSA as a function of temperature (T), the protein concentration (cp) and the concentrations of the trivalent salts YCl3 and LaCl3 (cs). As an important complement to structural, i.e. time-averaged, techniques we employ a dynamical technique that can detect clusters even when they are transient on the order of a few nanoseconds. By employing incoherent neutron spectroscopy, we unambiguously determine the short-time self-diffusion of the protein clusters depending on cp, cs and T. We determine the cluster size in terms of effective hydrodynamic radii as manifested by the cluster center-of-mass diffusion coefficients D. For both salts, we find a simple functional form D(cp, cs, T) in the parameter range explored. The calculated inter-particle attraction strength, determined from the microscopic and short-time diffusive properties of the samples, increases with salt concentration and temperature in the regime investigated and can be linked to the macroscopic behavior of the samples.

Fluctuations of water quality time series in rivers follow superstatistics.

Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate water quality time series (such as dissolved oxygen concentrations and electrical conductivity) as measured in rivers and provide evidence that they exhibit superstatistical behavior. Our main example is time series as recorded in the River Chess in South East England. Specifically, we use seasonal detrending and empirical mode decomposition to separate trends from fluctuations for the measured data. With either detrending method, we observe heavy-tailed fluctuation distributions, which are well described by log-normal superstatistics for dissolved oxygen. Contrarily, we find a double peaked non-standard superstatistics for the electrical conductivity data, which we model using two combined χ 2 -distributions.