The molecular basis of allostery in a facilitated dissociation process
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The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO 2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The pore-scale results were then averaged to calculate the effective respiration rates as a function of water content in soils. The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75 that is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Simulations also illustrates that a larger fraction of CO 2 produced from microbial respiration can be accumulated inside soil cores under higher saturation conditions, implying that CO 2 flux measured on the top of soil cores may underestimate or overestimate true soil respiration rates under dynamic moisture conditions. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geochemical, and biophysical factors.
Molecular dynamics simulations have recently become capable of observing multiple protein unfolding and refolding events in a single-millisecond–long trajectory. This major advance produces atomic-level information with nanosecond resolution, a feat unmatched by experimental methods. Such simulations are being extensively analyzed to assess their description of protein folding, yet the results remain difficult to validate experimentally. We apply a combination of hydrogen exchange, NMR, and other techniques to test the simulations with a resolution of single H-bonds. Several significant discrepancies between the simulations and experimental data were uncovered for regions of the energy surface outside of the native basin. This comparison yields suggestions for improving the force fields and provides a general method for experimentally validating folding simulations.
Replication-dependent histone mRNAs end with a conserved stem loop that is recognized by stem-loop–binding protein (SLBP). The minimal RNA-processing domain of SLBP is phosphorylated at an internal threonine, and Drosophila SLBP (dSLBP) also is phosphorylated at four serines in its 18-aa C-terminal tail. We show that phosphorylation of dSLBP increases RNA-binding affinity dramatically, and we use structural and biophysical analyses of dSLBP and a crystal structure of human SLBP phosphorylated on the internal threonine to understand the striking improvement in RNA binding. Together these results suggest that, although the C-terminal tail of dSLBP does not contact the RNA, phosphorylation of the tail promotes SLBP conformations competent for RNA binding and thereby appears to reduce the entropic penalty for the association. Increased negative charge in this C-terminal tail balances positively charged residues, allowing a more compact ensemble of structures in the absence of RNA.
Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. Space based technology in concert with bird migration modeling and geographical information analysis yields new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. At the NASA Goddard Space Flight Center, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. We use an individual-based bird biophysical migration model, driven by remotely sensed land surface data, climate and hydrologic data, and biological field observations to study migratory bird responses to environmental change in North America. Simulation allows us to study bird migration across multiple scales and can be linked to mechanistic processes describing the time and energy budget states of migrating birds. We illustrate our approach by simulating the spring migration of pectoral sandpipers from the Gulf of Mexico to Alaska. Mean stopover length and trajectory patterns are consistent with field observations.
The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to identifY those bio-optical conditions under which the inversion model performs both well and poorly.
DNA amplification is the process of replication of a specified DNA sequence in vitro through time-dependent manipulation of its external environment. A theoretical framework for determination of the optimal dynamic operating conditions of DNA amplification reactions, for any specified amplification objective, is presented based on first-principles biophysical modeling and control theory. Amplification of DNA is formulated as a problem in control theory with optimal solutions that can differ considerably from strategies typically used in practice. Using the Polymerase Chain Reaction as an example, sequence-dependent biophysical models for DNA amplification are cast as control systems, wherein the dynamics of the reaction are controlled by a manipulated input variable. Using these control systems, we demonstrate that there exists an optimal temperature cycling strategy for geometric amplification of any DNA sequence and formulate optimal control problems that can be used to derive the optimal temperature profile. Strategies for the optimal synthesis of the DNA amplification control trajectory are proposed. Analogous methods can be used to formulate control problems for more advanced amplification objectives corresponding to the design of new types of DNA amplification reactions.
DNA origami has emerged as a versatile method to synthesize nanostructures with high precision. This bottom-up self-assembly approach can produce not only complex static architectures, but also dynamic reconfigurable structures with tunable properties. While DNA origami has been explored increasingly for diverse applications, such as biomedical and biophysical tools, related mechanics are also under active investigation. Here we studied the structural properties of DNA origami and investigated the energy needed to deform the DNA structures. We used a single-layer rectangular DNA origami tile as a model system and studied its cyclization process. This origami tile was designed with an inherent twist by placing crossovers every 16 base-pairs (bp), corresponding to a helical pitch of 10.67 bp/turn, which is slightly different from that of native B-form DNA (~10.5 bp/turn). We used molecular dynamics (MD) simulations based on a coarse-grained model on an open-source computational platform, oxDNA. We calculated the energies needed to overcome the initial curvature and induce mechanical deformation by applying linear spring forces. We found that the initial curvature may be overcome gradually during cyclization and a total of ~33.1 kcal/mol is required to complete the deformation. These results provide insights into the DNA origami mechanics and should be useful for diverse applications such as adaptive reconfiguration and energy absorption.
The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying FT and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).
Acylated peptides composed of glucagon-like peptide-1 receptor agonists modified with a fatty acid side chain are an important class of therapeutics for type 2 diabetes and obesity but are susceptible to an unusual physical instability in the presence of hydrophobic surfaces, i.e., spontaneous emulsification, also known as ouzo formation in practice. In this work, light scattering, small-angle X-ray scattering, and circular dichroism measurements are used to characterize the physical properties of the semaglutide colloidal phase, including size distribution, shape, secondary structure, internal structure, and internal composition, as a function of solution physico-chemical conditions. The existence and size of the colloids formed are successfully predicted by a classical Rayleigh model, which identifies the parameters controlling their size and formation. Colloid formation is found to be catalyzed by hydrophobic surfaces, and formation rates are modeled as an autocatalytic reaction, enabling the formation of a master curve for various surfaces that elucidates the mechanism. Surfaces differ due to differences in surface wettability, which can be correlated with Hansen solubility parameters. This work provides insights into this unusual colloidal phenomenon and guides the peptide synthesis process and drug product formulation in the pharmaceutical industry.
AP endonuclease 1 (APE1) processes DNA lesions including apurinic/apyrimidinic sites and 3´-blocking groups, mediating base excision repair and single strand break repair. Much effort has focused on developing specific inhibitors of APE1, which could have important applications in basic research and potentially lead to clinical anticancer agents. We used structural, biophysical, and biochemical methods to characterize several reported inhibitors, including 7-nitroindole-2-carboxylic acid (CRT0044876), given its small size, reported potency, and widespread use for studying APE1. Intriguingly, NMR chemical shift perturbation (CSP) experiments show that CRT0044876 and three similar indole-2-carboxylic acids bind a pocket distal from the APE1 active site. A crystal structure confirms these findings and defines the pose for 5-nitroindole-2-carboxylic acid. However, dynamic light scattering experiments show the indole compounds form colloidal aggregates that could bind (sequester) APE1, causing nonspecific inhibition. Endonuclease assays show the compounds lack significant APE1 inhibition under conditions (detergent) that disrupt aggregation. Thus, binding of the indole-2-carboxylic acids at the remote pocket does not inhibit APE1 repair activity. Myricetin also forms aggregates and lacks APE1 inhibition under aggregate-disrupting conditions. Two other reported compounds (MLS000552981, MLS000419194) inhibit APE1 in vitro with low micromolar IC50 and do not appear to aggregate in this concentration range. However, NMR CSP experiments indicate the compounds do not bind specifically to apo- or Mg 2+ -bound APE1, pointing to a non-specific mode of inhibition, possibly DNA binding. Our results highlight methods for rigorous interrogation of putative APE1 inhibitors and should facilitate future efforts to discover compounds that specifically inhibit this important repair enzyme.
A differential interference contrast (DIC) polarization anisotropy is reported that was successfully used for rotational tracking of gold nanorods attached onto a kinesin-driven microtubule. A dual-wavelength detection of single gold nanorods rotating on a live cell membrane is described. Both transverse and longitudinal surface plasmon resonance (SPR) modes were used for tracking the rotational motions during a fast dynamic process under a DIC microscope. A novel method is presented to determine the full three-dimensional (3D) orientation of single plasmonic gold nanorods rotating on live cell membranes by combining DIC polarization anisotropy with an image pattern recognition technique. Polarization- and wavelength-sensitive DIC microscopy imaging of 2- m long gold nanowires as optical probes in biological studies is reported. A new method is demonstrated to track 3D orientation of single gold nanorods supported on a gold film without angular degeneracy. The idea is to use the interaction (or coupling) of gold nanorods with gold film, yielding characteristic scattering patterns such as a doughnut shape. Imaging of photocatalytic activity, polarity and selectivity on single Au-CdS hybrid nanocatalysts using a high-resolution superlocalization fluorescence imaging technique is described.
The reactive behavior of individual molecules is seldom observed, because we usually measure the average properties of billions of molecules. What we miss is important: the catalytic activity of less than 1% of the molecules under observation can dominate the outcome of a chemical reaction seen at a macroscopic level. Currently available techniques to examine reaction mechanisms (such as nuclear magnetic resonance spectroscopy and mass spectrometry) study molecules as an averaged ensemble. These ensemble techniques are unable to detect minor components (under ~1%) in mixtures or determine which components in the mixture are responsible for reactivity and catalysis. In the field of mechanistic chemistry, there is a resulting heuristic device that if an intermediate is very reactive in catalysis, it often cannot be observed (termed “Halpern’s Rule” ). Ultimately, the development of single-molecule imaging technology could be a powerful tool to observe these “unobservable” intermediates and active catalysts. Single-molecule techniques have already transformed biology and the understanding of biochemical processes. The potential of single-molecule fluorescence microscopy to address diverse chemical questions, such as the chemical reactivity of organometallic or inorganic systems with discrete metal complexes, however, has not yet been realized. In this respect, its application to chemical systems lags significantly behind its application to biophysical systems. This transformative imaging technique has broad, multidisciplinary impact with the potential to change the way the chemistry community studies reaction mechanisms and reactivity distributions, especially in the core area of catalysis.
Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents in a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.
The autotrophic Sideroxydans lithotrophicus ES-1 can grow by coupling the oxidation of ferrous iron to the reduction of oxygen. Soluble ferrous iron is oxidized at the surface of the cell by an MtoAB porin-cytochrome complex that functions as an electron conduit through the outer membrane. Electrons are then transported to the cytoplasmic membrane where they are used to generate proton motive force (PMF) (for ATP synthesis) and NADH for autotrophic processes such as carbon fixation. As part of the mtoAB gene cluster, S. lithotrophicus also contains the gene mtoD that is proposed to encode a cytochrome c protein. We isolated mtoD from a Shewanella oneidensis expression system where the mtoD gene was expressed on a pBAD plasmid vector. Biochemical, biophysical, and crystallographic characterization of the purified MtoD revealed it as an 11 kDa monomeric protein containing a single heme. Sequence and structural alignment indicated that MtoD belonged to the class-1 cytochrome c family and had a similar fold to ferricytochrome c552 family, however the MtoD heme is bis-histidine coordinated and is substantially more exposed than the hemes of other family members. The reduction potential of the MtoD heme at pH 7 was +155 mV vs. Standard Hydrogen Electrode, which is approximately 100 mV lower than that of mitochondrial cytochrome c. Consideration of the properties of MtoD in the context of the potential respiratory partners identified from the genome suggests that MtoD could associate to multiple electron transfer partners as the primary periplasmic electron shuttle.
Abstract Tandem-repetitive DNA (where two or more DNA bases are repeated numerous times) can adopt non-canonical secondary structures. Many of these structures are implicated in important biological processes. Human Satellite III (HSat3) is enriched for tandem repeats of the sequence ATGGA and is located in pericentromeric heterochromatin in many human chromosomes. Here, we investigate the secondary structure of the four-repeat HSat3 sequence 5′-ATGGA ATGGA ATGGA ATGGA-3′ using X-ray crystallography, NMR, and biophysical methods. Circular dichroism spectroscopy, thermal stability, native PAGE, and analytical ultracentrifugation indicate that this sequence folds into a monomolecular hairpin with non-canonical base pairing and B-DNA characteristics at concentrations below 0.9 mM. NMR studies at 0.05–0.5 mM indicate that the hairpin is likely folded-over into a compact structure with high dynamics. Crystallographic studies at 2.5 mM reveal an antiparallel self-complementary duplex with the same base pairing as in the hairpin, extended into an infinite polymer. The non-canonical base pairing includes a G–G intercalation sandwiched by sheared A–G base pairs, leading to a cross-strand four guanine stack, so called guanine zipper. The guanine zippers are spaced throughout the structure by A–T/T–A base pairs. Our findings lend further insight into recurring structural motifs associated with the HSat3 and their potential biological functions.
According to this article, patients with type 2 diabetes mellitus (T2DM) develop thrombotic abnormalities strongly associated with cardiovascular diseases. In addition to the changes of numerous coagulation factors such as elevated levels of thrombin and fibrinogen, the abnormal rheological effects of red blood cells (RBCs) and platelets flowing in blood are crucial in platelet adhesion and thrombus formation in T2DM. An important process contributing to the latter is the platelet margination. We employ the dissipative particle dynamics method to seamlessly model cells, plasma, and vessel walls. We perform a systematic study on RBC and platelet transport in cylindrical vessels by considering different cell shapes, sizes, and RBC deformabilities in healthy and T2DM blood, as well as variable flowrates and hematocrit. In particular, we use cellular-level RBC and platelet models with parameters derived from patient-specific data and present a sensitivity study. We find T2DM RBCs, which are less deformable compared to normal RBCs, lower the transport of platelets toward the vessel walls, whereas platelets with higher mean volume (often observed in T2DM) lead to enhanced margination. Furthermore, increasing the flowrate or hematocrit enhances platelet margination. We also investigated the effect of platelet shape and observed a nonmonotonic variation with the highest near-wall concentration corresponding to platelets with a moderate aspect ratio of 0.38. We examine the role of white blood cells (WBCs), whose count is increased notably in T2DM patients. We find that WBC rolling or WBC adhesion tends to decrease platelet margination due to hydrodynamic effects. To the best of our knowledge, such simulations of blood including all blood cells have not been performed before, and our quantitative findings can help separate the effects of hydrodynamic interactions from adhesive interactions and potentially shed light on the associated pathological processes in T2DM such as increased inflammatory response, platelet activation and adhesion, and ultimately thrombus formation.